Search results for: advanced radiation detection and measurement
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Search results for: advanced radiation detection and measurement

47 Mineralized Nanoparticles as a Contrast Agent for Ultrasound and Magnetic Resonance Imaging

Authors: Jae Won Lee, Kyung Hyun Min, Hong Jae Lee, Sang Cheon Lee

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To date, imaging techniques have attracted much attention in medicine because the detection of diseases at an early stage provides greater opportunities for successful treatment. Consequently, over the past few decades, diverse imaging modalities including magnetic resonance (MR), positron emission tomography, computed tomography, and ultrasound (US) have been developed and applied widely in the field of clinical diagnosis. However, each of the above-mentioned imaging modalities possesses unique strengths and intrinsic weaknesses, which limit their abilities to provide accurate information. Therefore, multimodal imaging systems may be a solution that can provide improved diagnostic performance. Among the current medical imaging modalities, US is a widely available real-time imaging modality. It has many advantages including safety, low cost and easy access for patients. However, its low spatial resolution precludes accurate discrimination of diseased region such as cancer sites. In contrast, MR has no tissue-penetrating limit and can provide images possessing exquisite soft tissue contrast and high spatial resolution. However, it cannot offer real-time images and needs a comparatively long imaging time. The characteristics of these imaging modalities may be considered complementary, and the modalities have been frequently combined for the clinical diagnostic process. Biominerals such as calcium carbonate (CaCO3) and calcium phosphate (CaP) exhibit pH-dependent dissolution behavior. They demonstrate pH-controlled drug release due to the dissolution of minerals in acidic pH conditions. In particular, the application of this mineralization technique to a US contrast agent has been reported recently. The CaCO3 mineral reacts with acids and decomposes to generate calcium dioxide (CO2) gas in an acidic environment. These gas-generating mineralized nanoparticles generated CO2 bubbles in the acidic environment of the tumor, thereby allowing for strong echogenic US imaging of tumor tissues. On the basis of this previous work, it was hypothesized that the loading of MR contrast agents into the CaCO3 mineralized nanoparticles may be a novel strategy in designing a contrast agent for dual imaging. Herein, CaCO3 mineralized nanoparticles that were capable of generating CO2 bubbles to trigger the release of entrapped MR contrast agents in response to tumoral acidic pH were developed for the purposes of US and MR dual-modality imaging of tumors. Gd2O3 nanoparticles were selected as an MR contrast agent. A key strategy employed in this study was to prepare Gd2O3 nanoparticle-loaded mineralized nanoparticles (Gd2O3-MNPs) using block copolymer-templated CaCO3 mineralization in the presence of calcium cations (Ca2+), carbonate anions (CO32-) and positively charged Gd2O3 nanoparticles. The CaCO3 core was considered suitable because it may effectively shield Gd2O3 nanoparticles from water molecules in the blood (pH 7.4) before decomposing to generate CO2 gas, triggering the release of Gd2O3 nanoparticles in tumor tissues (pH 6.4~7.4). The kinetics of CaCO3 dissolution and CO2 generation from the Gd2O3-MNPs were examined as a function of pH and pH-dependent in vitro magnetic relaxation; additionally, the echogenic properties were estimated to demonstrate the potential of the particles for the tumor-specific US and MR imaging.

Keywords: calcium carbonate, mineralization, ultrasound imaging, magnetic resonance imaging

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46 Integrating Experiential Real-World Learning in Undergraduate Degrees: Maximizing Benefits and Overcoming Challenges

Authors: Anne E. Goodenough

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One of the most important roles of higher education professionals is to ensure that graduates have excellent employment prospects. This means providing students with the skills necessary to be immediately effective in the workplace. Increasingly, universities are seeking to achieve this by moving from lecture-based and campus-delivered curricula to more varied delivery, which takes students out of their academic comfort zone and allows them to engage with, and be challenged by, real world issues. One popular approach is integration of problem-based learning (PBL) projects into curricula. However, although the potential benefits of PBL are considerable, it can be difficult to devise projects that are meaningful, such that they can be regarded as mere ‘hoop jumping’ exercises. This study examines three-way partnerships between academics, students, and external link organizations. It studied the experiences of all partners involved in different collaborative projects to identify how benefits can be maximized and challenges overcome. Focal collaborations included: (1) development of real-world modules with novel assessment whereby the organization became the ‘client’ for student consultancy work; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; (4) immersive fieldwork projects in novel locations; and (5) students working as partners on staff-led research with link organizations. Focus groups, questionnaires and semi-structured interviews were used to identify opportunities and barriers, while quantitative analysis of students’ grades was used to determine academic effectiveness. Common challenges identified by academics were finding suitable link organizations and devising projects that simultaneously provided education opportunities and tangible benefits. There was no ‘one size fits all’ formula for success, but careful planning and ensuring clarity of roles/responsibilities were vital. Students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. They frequently highlighted employability opportunities that collaborative projects opened up and analysis of grades demonstrated the potential for such projects to increase attainment. Organizations generally recognized the value of project outputs, but often required considerable assistance to put the right scaffolding in place to ensure projects worked. Benefits were maximized by ensuring projects were well-designed, innovative, and challenging. Co-publication of projects in peer-reviewed journals sometimes gave additional benefits for all involved, being especially beneficial for student curriculum vitae. PBL and student projects are by no means new pedagogic approaches: the novelty here came from creating meaningful three-way partnerships between academics, students, and link organizations at all undergraduate levels. Such collaborations can allow students to make a genuine contribution to knowledge, answer real questions, solve actual problems, all while providing tangible benefits to organizations. Because projects are actually needed, students tend to engage with learning at a deep level. This enhances student experience, increases attainment, encourages development of subject-specific and transferable skills, and promotes networking opportunities. Such projects frequently rely upon students and staff working collaboratively, thereby also acting to break down the traditional teacher/learner division that is typically unhelpful in developing students as advanced learners.

Keywords: higher education, employability, link organizations, innovative teaching and learning methods, interactions between enterprise and education, student experience

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45 Small Scale Mobile Robot Auto-Parking Using Deep Learning, Image Processing, and Kinematics-Based Target Prediction

Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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44 Sustainable Antimicrobial Biopolymeric Food & Biomedical Film Engineering Using Bioactive AMP-Ag+ Formulations

Authors: Eduardo Lanzagorta Garcia, Chaitra Venkatesh, Romina Pezzoli, Laura Gabriela Rodriguez Barroso, Declan Devine, Margaret E. Brennan Fournet

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New antimicrobial interventions are urgently required to combat rising global health and medical infection challenges. Here, an innovative antimicrobial technology, providing price competitive alternatives to antibiotics and readily integratable with currently technological systems is presented. Two cutting edge antimicrobial materials, antimicrobial peptides (AMPs) and uncompromised sustained Ag+ action from triangular silver nanoplates (TSNPs) reservoirs, are merged for versatile effective antimicrobial action where current approaches fail. Antimicrobial peptides (AMPs) exist widely in nature and have recently been demonstrated for broad spectrum of activity against bacteria, viruses, and fungi. TSNP’s are highly discrete, homogenous and readily functionisable Ag+ nanoreseviors that have a proven amenability for operation within in a wide range of bio-based settings. In a design for advanced antimicrobial sustainable plastics, antimicrobial TSNPs are formulated for processing within biodegradable biopolymers. Histone H5 AMP was selected for its reported strong antimicrobial action and functionalized with the TSNP (AMP-TSNP) in a similar fashion to previously reported TSNP biofunctionalisation methods. A synergy between the propensity of biopolymers for degradation and Ag+ release combined with AMP activity provides a novel mechanism for the sustained antimicrobial action of biopolymeric thin films. Nanoplates are transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. Extrusion is used in combination with calendering rolls to create thin polymerc film where the nanoplates are embedded onto the surface. The resultant antibacterial functional films are suitable to be adapted for food packing and biomedical applications. TSNP synthesis were synthesized by adapting a previously reported seed mediated approach. TSNP synthesis was scaled up for litre scale batch production and subsequently concentrated to 43 ppm using thermally controlled H2O removal. Nanoplates were transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. This was acomplised by functionalizing the TSNP with thiol terminated polyethylene glycol and using centrifugal force to transfer them to chloroform. Polycaprolactone (PCL) and Polylactic acid (PLA) were individually processed through extrusion, TSNP and AMP-TSNP solutions were sprayed onto the polymer immediately after exiting the dye. Calendering rolls were used to disperse and incorporate TSNP and TSNP-AMP onto the surface of the extruded films. Observation of the characteristic blue colour confirms the integrity of the TSNP within the films. Antimicrobial tests were performed by incubating Gram + and Gram – strains with treated and non-treated films, to evaluate if bacterial growth was reduced due to the presence of the TSNP. The resulting films successfully incorporated TSNP and AMP-TSNP. Reduced bacterial growth was observed for both Gram + and Gram – strains for both TSNP and AMP-TSNP compared with untreated films indicating antimicrobial action. The largest growth reduction was observed for AMP-TSNP treated films demonstrating the additional antimicrobial activity due to the presence of the AMPs. The potential of this technology to impede bacterial activity in food industry and medical surfaces will forge new confidence in the battle against antibiotic resistant bacteria, serving to greatly inhibit infections and facilitate patient recovery.

Keywords: antimicrobial, biodegradable, peptide, polymer, nanoparticle

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43 Preliminary Characterization of Hericium Species Sampled in Tuscany, Italy

Authors: V. Cesaroni, C. Girometta, A. Bernicchia, M. Brusoni, F. Corana, R. M. Baiguera, C. M. Cusaro, M. L. Guglielminetti, B. Mannucci, H. Kawagishi, C. Perini, A. M. Picco, P. Rossi, E. Salerni, E. Savino

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Fungi of the genus Hericium contain various compounds with antibacterial activity, cytotoxic effect on cancer cells and bioactive molecules. Some of the active metabolites stimulate the synthesis of the Nerve Growth Factor (NGF). Recently, the effect of dietary supplement based on Hericium erinaceus on recognition memory and on hippocampal mossy fiber-CA3 neurotransmission was published. The aim of this study was to investigate the presence of Hericium species on Italian territory in order to isolate the strains for further studies and applications. The first step was to collect Hericium sporophores in Tuscany: H. alpestre Pers., H. coralloides (Scop.) Pers. and H. erinaceus (Bull.) Pers. were the species present. The strains of H. alpestre (H.a.1), H. coralloides (H.c.1) and H. erinaceus (H.e.1 & H.e.2) have been isolated in pure culture and preserved in the collection of the University of Pavia (MicUNIPV). The DNA sequences obtained from the strains were compared to other sequences found in international databases. Therefore, it was possible to construct a phylogenetic tree that highlights the clear separation in clades of the sequences and the molecular identification of our strains with the species of Hericium considered. The second step was to cultivate indoor and outdoor H. erinaceus in order to obtain as many sporophores as possible for further chemical analysis. All the procedures for H. erinaceus cultivation have been followed. Among the available recipes for indoor H. erinaceus cultivation, it was used a substrate formulation contained 70% oak sawdust, 20% rice bran, 10% wheat straw, 1% CaCO3 and 1% sucrose. The bioactive compounds present in the mycelia and in the sporophores of H. erinaceus were chemically analyzed in collaboration with the Centro Grandi Strumenti of the University of Pavia using high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC/ESI-MS/MS). The materials to be analyzed were previously freeze-dried and then extracted with an alcoholic procedure. Preliminary chromatographic analysis revealed the presence of potentially bioactive and structurally different secondary metabolites such as polysaccharides, erinacins, ericenones, steroids and other terpenoids. Ericenones C and D (in sporophores) and erinacin A (in mycelium) have been identified by comparison with the respective standards. These molecules are known to have effects on the Central Nervous System (CNS) cells, which is the main objective of our studies. Thanks to the high sensitivity in the detection of bioactive compounds of H. erinaceus, it will be possible to use the To obtain lyophilized mycelium and the respective culture broth, 4 small pieces (about 5 mm2) of the respective H.e.1 or H.c.1 strains, taken from the margin of growing cultures (MEA), were inoculated into 1 liter of 2% ME (malt extract, Biokar Diagnostics). The static liquid cultures were kept at 24 °C in the dark chamber and fungi grew for one month. 10 replicates for each strain have been done. The method proposed as an analytical screening protocol to determine the optimal growth conditions of the fungus and to improve the production chain of H. erinaceus. These results encourage to carry out chemical analyzes also on H. alpestre and H. coralloides in order to evaluate the presence of bioactive compounds in these two species.

Keywords: Hericium species, Hercium erinaceus bioactive compounds, medicinal mushrooms, mushroom cultivation

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42 Adequate Nutritional Support and Monitoring in Post-Traumatic High Output Duodenal Fistula

Authors: Richa Jaiswal, Vidisha Sharma, Amulya Rattan, Sushma Sagar, Subodh Kumar, Amit Gupta, Biplab Mishra, Maneesh Singhal

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Background: Adequate nutritional support and daily patient monitoring have an independent therapeutic role in the successful management of high output fistulae and early recovery after abdominal trauma. Case presentation: An 18-year-old girl was brought to AIIMS emergency with alleged history of fall of a heavy weight (electric motor) over abdomen. She was evaluated as per Advanced Trauma Life Support(ATLS) protocols and diagnosed to have significant abdominal trauma. After stabilization, she was referred to Trauma center. Abdomen was guarded and focused assessment with sonography for trauma(FAST) was found positive. Complete duodenojejunal(DJ) junction transection was found at laparotomy, and end-to-end repair was done. However, patient was re-explored in view of biliary peritonitis on post-operative day3, and anastomotic leak was found with sloughing of duodenal end. Resection of non-viable segments was done followed by side-to-side anastomosis. Unfortunately, the anastomosis leaked again, this time due to a post-anastomotic kink, diagnosed on dye study. Due to hostile abdomen, the patient was planned for supportive care, with plan of build-up and delayed definitive surgery. Percutaneous transheptic biliary drainage (PTBD) and STSG were required in the course as well. Nutrition: In intensive care unit (ICU), major goals of nutritional therapy were to improve wound healing, optimize nutrition, minimize enteral feed associated complications, reduce biliary fistula output, and prepare the patient for definitive surgeries. Feeding jejunostomy (FJ) was started from day 4 at the rate of 30ml/h along with total parenteral nutrition (TPN) and intra-venous (IV) micronutrients support. Due to high bile output, bile refeed started from day 13.After 23 days of ICU stay, patient was transferred to general ward with body mass index (BMI)<11kg/m2 and serum albumin –1.5gm%. Patient was received in the ward in catabolic phase with high risk of refeeding syndrome. Patient was kept on FJ bolus feed at the rate of 30–50 ml/h. After 3–4 days, while maintaining patient diet book log it was observed that patient use to refuse feed at night and started becoming less responsive with every passing day. After few minutes of conversation with the patient for a couple of days, she complained about enteral feed discharge in urine, mild pain and sign of dumping syndrome. Dye study was done, which ruled out any enterovesical fistula and conservative management were planned. At this time, decision was taken for continuous slow rate feeding through commercial feeding pump at the rate of 2–3ml/min. Drastic improvement was observed from the second day in gastro-intestinal symptoms and general condition of the patient. Nutritional composition of feed, TPN and diet ranged between 800 and 2100 kcal and 50–95 g protein. After STSG, TPN was stopped. Periodic diet counselling was given to improve oral intake. At the time of discharge, serum albumin level was 2.1g%, weight – 38.6, BMI – 15.19 kg/m2. Patient got discharge on an oral diet. Conclusion: Successful management of post-traumatic proximal high output fistulae is a challenging task, due to impaired nutrient absorption and enteral feed associated complications. Strategic- and goal-based nutrition support can salvage such critically ill patients, as demonstrated in the present case.

Keywords: nutritional monitoring, nutritional support, duodenal fistula, abdominal trauma

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41 Multimodal Integration of EEG, fMRI and Positron Emission Tomography Data Using Principal Component Analysis for Prognosis in Coma Patients

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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40 Use of Artificial Intelligence and Two Object-Oriented Approaches (k-NN and SVM) for the Detection and Characterization of Wetlands in the Centre-Val de Loire Region, France

Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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39 Using Technology to Deliver and Scale Early Childhood Development Services in Resource Constrained Environments: Case Studies from South Africa

Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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38 Correlation of Unsuited and Suited 5ᵗʰ Female Hybrid III Anthropometric Test Device Model under Multi-Axial Simulated Orion Abort and Landing Conditions

Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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37 Role of Toll Like Receptor-2 in Female Genital Tuberculosis Disease Infection and Its Severity

Authors: Swati Gautam, Salman Akhtar, S. P. Jaiswar, Amita Jain

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Background: FGTB is now a major global health problem mostly in developing countries including India. In humans, Mycobacterium Tuberculosis (M.tb) is a causating agent of infection. High index of suspicion is required for early diagnosis due to asymptomatic presentation of FGTB disease. In macrophages Toll Like Receptor-2 (TLR-2) is one which mediated host’s immune response to M.tb. The expression of TLR-2 on macrophages is important to determine the fate of innate immune responses to M.tb. TLR-2 have two work. First its high expression on macrophages worsen the outer of infection and another side, it maintains M.tb to its dormant stage avoids activation of M.tb from latent phase. Single Nucleotide Polymorphism (SNP) of TLR-2 gene plays an important role in susceptibility to TB among different populations and subsequently, in the development of infertility. Methodology: This Case-Control study was done in the Department of Obs and Gynae and Department of Microbiology at King George’s Medical University, U.P, Lucknow, India. Total 300 subjects (150 Cases and 150 Controls) were enrolled in the study. All subjects were enrolled only after fulfilling the given inclusion and exclusion criteria. Inclusion criteria: Age 20-35 years, menstrual-irregularities, positive on Acid-Fast Bacilli (AFB), TB-PCR, (LJ/MGIT) culture in Endometrial Aspiration (EA). Exclusion criteria: Koch’s active, on ATT, PCOS, and Endometriosis fibroid women, positive on Gonococal and Chlamydia. Blood samples were collected in EDTA tubes from cases and healthy control women (HCW) and genomic DNA extraction was carried out by salting-out method. Genotyping of TLR2 genetic variants (Arg753Gln and Arg677Trp) were performed by using single amplification refractory mutation system (ARMS) PCR technique. PCR products were analyzed by electrophoresis on 1.2% agarose gel and visualized by gel-doc. Statistical analysis of the data was performed using the SPSS 16.3 software and computing odds ratio (OR) with 95% CI. Linkage Disequiliribium (LD) analysis was done by SNP stats online software. Results: In TLR-2 (Arg753Gln) polymorphism significant risk of FGTB observed with GG homozygous mutant genotype (OR=13, CI=0.71-237.7, p=0.05), AG heterozygous mutant genotype (OR=13.7, CI=0.76-248.06, p=0.03) however, G allele (OR=1.09, CI=0.78-1.52, p=0.67) individually was not associated with FGTB. In TLR-2 (Arg677Trp) polymorphism a significant risk of FGTB observed with TT homozygous mutant genotype (OR= 0.020, CI=0.001-0.341, p < 0.001), CT heterozygous mutant genotype (OR=0.53, CI=0.33-0.86, p=0.014) and T allele (OR=0.463, CI=0.32-0.66, p < 0.001). TT mutant genotype was only found in FGTB cases and frequency of CT heterozygous more in control group as compared to FGTB group. So, CT genotype worked as protective mutation for FGTB susceptibility group. In haplotype analysis of TLR-2 genetic variants, four possible combinations, i.e. (G-T, A-C, G-C, and A-T) were obtained. The frequency of haplotype A-C was significantly higher in FGTB cases (0.32). Control group did not show A-C haplotype and only found in FGTB cases. Conclusion: In conclusion, study showed a significant association with both genetic variants of TLR-2 of FGTB disease. Moreover, the presence of specific associated genotype/alleles suggest the possibility of disease severity and clinical approach aimed to prevent extensive damage by disease and also helpful for early detection of disease.

Keywords: ARMS, EDTA, FGTB, TLR

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36 Differential Expression Profile Analysis of DNA Repair Genes in Mycobacterium Leprae by qPCR

Authors: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

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Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

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35 Evaluation of Coal Quality and Geomechanical Moduli Using Core and Geophysical Logs: Study from Middle Permian Barakar Formation of Gondwana Coalfield

Authors: Joyjit Dey, Souvik Sen

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Middle Permian Barakar formation is the major economic coal bearing unit of vast east-west trending Damodar Valley basin of Gondwana coalfield. Primary sedimentary structures were studied from the core holes, which represent majorly four facies groups: sandstone dominated facies, sandstone-shale heterolith facies, shale facies and coal facies. Total eight major coal seams have been identified with the bottom most seam being the thickest. Laterally, continuous coal seams were deposited in the calm and quiet environment of extensive floodplain swamps. Channel sinuosity and lateral channel migration/avulsion results in lateral facies heterogeneity and coal splitting. Geophysical well logs (Gamma-Resistivity-Density logs) have been used to establish the vertical and lateral correlation of various litho units field-wide, which reveals the predominance of repetitive fining upwards cycles. Well log data being a permanent record, offers a strong foundation for generating log based property evaluation and helps in characterization of depositional units in terms of lateral and vertical heterogeneity. Low gamma, high resistivity, low density is the typical coal seam signatures in geophysical logs. Here, we have used a density cutoff of 1.6 g/cc as a primary discriminator of coal and the same has been employed to compute various coal assay parameters, which are ash, fixed carbon, moisture, volatile content, cleat porosity, vitrinite reflectance (VRo%), which were calibrated with the laboratory based measurements. The study shows ash content and VRo% increase from west to east (towards basin margin), while fixed carbon, moisture and volatile content increase towards west, depicting increased coal quality westwards. Seam wise cleat porosity decreases from east to west, this would be an effect of overburden, as overburden pressure increases westward with the deepening of basin causing more sediment packet deposited on the western side of the study area. Coal is a porous, viscoelastic material in which velocity and strain both change nonlinearly with stress, especially for stress applied perpendicular to the bedding plane. Usually, the coal seam has a high velocity contrast relative to its neighboring layers. Despite extensive discussion of the maceral and chemical properties of coal, its elastic characteristics have received comparatively little attention. The measurement of the elastic constants of coal presents many difficulties: sample-to-sample inhomogeneity and fragility and velocity dependence on stress, orientation, humidity, and chemical content. In this study, a conclusive empirical equation VS= 0.80VP-0.86 has been used to model shear velocity from compression velocity. Also the same has been used to compute various geomechanical moduli. Geomech analyses yield a Poisson ratio of 0.348 against coals. Average bulk modulus value is 3.97 GPA, while average shear modulus and Young’s modulus values are coming out as 1.34 and 3.59 GPA respectively. These middle Permian Barakar coals show an average 23.84 MPA uniaxial compressive strength (UCS) with 4.97 MPA cohesive strength and 0.46 as friction coefficient. The output values of log based proximate parameters and geomechanical moduli suggest a medium volatile Bituminous grade for the studied coal seams, which is found in the laboratory based core study as well.

Keywords: core analysis, coal characterization, geophysical log, geo-mechanical moduli

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34 Implementation of Cord- Blood Derived Stem Cells in the Regeneration of Two Experimental Models: Carbon Tetrachloride and S. Mansoni Induced Liver Fibrosis

Authors: Manal M. Kame, Zeinab A. Demerdash, Hanan G. El-Baz, Salwa M. Hassan, Faten M. Salah, Wafaa Mansour, Olfat Hammam

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Cord blood (CB) derived Unrestricted Somatic Stem Cells (USSCs) with their multipotentiality hold great promise in liver regeneration. This work aims at evaluation of the therapeutic potentiality of USSCs in two experimental models of chronic liver injury induced either by S. mansoni infection in balb/c mice or CCL4 injection in hamsters. Isolation, propagation, and characterization of USSCs from CB samples were performed. USSCs were induced to differentiate into osteoblasts, adipocytes and hepatocyte-like cells. Cells of the third passage were transplanted in two models of liver fibrosis: (1) Twenty hamsters were induced to liver fibrosis by repeated i. p. injection of 100 μl CCl4 /hamster for 8 weeks. This model was designed as; 10 hamsters with liver fibrosis and treated with i.h. injection of 3x106 USSCs (USSCs transplanted group), 10 hamsters with liver fibrosis (pathological control group), and 10 hamsters with healthy livers (normal control group). (2) Murine chronics S.mansoni model: twenty mice were induced to liver fibrosis with S. mansoni ceracariae (60 cercariae/ mouse) using the tail immersion method and left for 12 weeks. This model was designed as; 10 mice with liver fibrosis were transplanted with i. v. injection of 1×106 USCCs (USSCs transplanted group). Other 2 groups were designed as in hamsters model. Animals were sacrificed 12 weeks after USSCs transplantation, and their liver sections were examined for detection of human hepatocyte-like cells by immunohistochemistry staining. Moreover, liver sections were examined for fibrosis level, and fibrotic indices were calculated. Sera of sacrificed animals were tested for liver functions. CB USSCs, with fibroblast-like morphology, expressed high levels of CD44, CD90, CD73 and CD105 and were negative for CD34, CD45, and HLA-DR. USSCs showed high expression of transcripts for Oct4 and Sox2 and were in vitro differentiated into osteoblasts, adipocytes. In both animal models, in vitro induced hepatocyte-like cells were confirmed by cytoplasmic expression of glycogen, alpha-fetoprotein, and cytokeratin18. Livers of USSCs transplanted group showed engraftment with human hepatocyte-like cells as proved by cytoplasmic expression of human alpha-fetoprotein, cytokeratin18, and OV6. In addition, livers of this group showed less fibrosis than the pathological control group. Liver functions in the form of serum AST & ALT level and serum total bilirubin level were significantly lowered in USSCs transplanted group than pathological control group (p < 0.001). Moreover, the fibrotic index was significantly lower (p< 0.001) in USSCs transplanted group than pathological control group. In addition liver sections, of i. v. injection of 1×106 USCCs of mice, stained with either H&E or sirius red showed diminished granuloma size and a relative decrease in hepatic fibrosis. Our experimental liver fibrosis models transplanted with CB-USSCs showed liver engraftment with human hepatocyte-like cells as well as signs of liver regeneration in the form of improvement in liver function assays and fibrosis level. These data provide hope that human CB- derived USSCs are introduced as multipotent stem cells with great potentiality in regenerative medicine & strengthens the concept of cellular therapy for the treatment of liver fibrosis.

Keywords: cord blood, liver fibrosis, stem cells, transplantation

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33 Early Predictive Signs for Kasai Procedure Success

Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

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32 Analyzing Spatio-Structural Impediments in the Urban Trafficscape of Kolkata, India

Authors: Teesta Dey

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Integrated Transport development with proper traffic management leads to sustainable growth of any urban sphere. Appropriate mass transport planning is essential for the populous cities in third world countries like India. The exponential growth of motor vehicles with unplanned road network is now the common feature of major urban centres in India. Kolkata, the third largest mega city in India, is not an exception of it. The imbalance between demand and supply of unplanned transport services in this city is manifested in the high economic and environmental costs borne by the associated society. With the passage of time, the growth and extent of passenger demand for rapid urban transport has outstripped proper infrastructural planning and causes severe transport problems in the overall urban realm. Hence Kolkata stands out in the world as one of the most crisis-ridden metropolises. The urban transport crisis of this city involves severe traffic congestion, the disparity in mass transport services on changing peripheral land uses, route overlapping, lowering of travel speed and faulty implementation of governmental plans as mostly induced by rapid growth of private vehicles on limited road space with huge carbon footprint. Therefore the paper will critically analyze the extant road network pattern for improving regional connectivity and accessibility, assess the degree of congestion, identify the deviation from demand and supply balance and finally evaluate the emerging alternate transport options as promoted by the government. For this purpose, linear, nodal and spatial transport network have been assessed based on certain selected indices viz. Road Degree, Traffic Volume, Shimbel Index, Direct Bus Connectivity, Average Travel and Waiting Tine Indices, Route Variety, Service Frequency, Bus Intensity, Concentration Analysis, Delay Rate, Quality of Traffic Transmission, Lane Length Duration Index and Modal Mix. Total 20 Traffic Intersection Points (TIPs) have been selected for the measurement of nodal accessibility. Critical Congestion Zones (CCZs) are delineated based on one km buffer zones of each TIP for congestion pattern analysis. A total of 480 bus routes are assessed for identifying the deficiency in network planning. Apart from bus services, the combined effects of other mass and para transit modes, containing metro rail, auto, cab and ferry services, are also analyzed. Based on systematic random sampling method, a total of 1500 daily urban passengers’ perceptions were studied for checking the ground realities. The outcome of this research identifies the spatial disparity among the 15 boroughs of the city with severe route overlapping and congestion problem. North and Central Kolkata-based mass transport services exceed the transport strength of south and peripheral Kolkata. Faulty infrastructural condition, service inadequacy, economic loss and workers’ inefficiency are the most dominant reasons behind the defective mass transport network plan. Hence there is an urgent need to revive the extant road based mass transport system of this city by implementing a holistic management approach by upgrading traffic infrastructure, designing new roads, better cooperation among different mass transport agencies, better coordination of transport and changing land use policies, large increase in funding and finally general passengers’ awareness.

Keywords: carbon footprint, critical congestion zones, direct bus connectivity, integrated transport development

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31 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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30 Research Cooperation between of Ukraine in Terms of Food Chain Safety Control in the Frame of MICRORISK Project

Authors: Kinga Wieczorek, Elzbieta Kukier, Remigiusz Pomykala, Beata Lachtara, Renata Szewczyk, Krzysztof Kwiatek, Jacek Osek

Abstract:

The MICRORISK project (Research cooperation in assessment of microbiological hazard and risk in the food chain) was funded by the European Commission under the FP7 PEOPLE 2012 IRSES call within the International Research Staff Exchange Scheme of Marie Curie Action and realized during years from 2014 to 2015. The main aim of the project was to establish a cooperation between the European Union (EU) and the third State in the area important from the public health point of view. The following organizations have been engaged in the activity: National Veterinary Research Institute (NVRI) in Pulawy, Poland (coordinator), French Agency for Food, Environmental and Occupational Health & Safety (ANSES) in Maisons Alfort, France, National Scientific Center Institute of Experimental and Clinical Veterinary Medicine (NSC IECVM), Kharkov and State Scientific and Research Institute of Laboratory Diagnostics and Veterinary and Sanitary Expertise (SSRILDVSE) Kijev Ukraine. The results of the project showed that Ukraine used microbiological criteria in accordance with Commission Regulation (EC) No 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Compliance concerns both the criteria applicable at the stage of food safety (retail trade), as well as evaluation criteria and process hygiene in food production. In this case, the Ukrainian legislation also provides application of the criteria that do not have counterparts in the food law of the European Union, and are based on the provisions of Ukrainian law. Partial coherence of the Ukrainian and EU legal requirements in terms of microbiological criteria for food and feed concerns microbiological parameters such as total plate count, coliforms, coagulase-positive Staphylococcus spp., including S. aureus. Analysis of laboratory methods used for microbiological hazards control in food production chain has shown that most methods used in the EU are well-known by Ukrainian partners, and many of them are routinely applied as the only standards in the laboratory practice or simultaneously used with Ukrainian methods. The area without any legislation, where the EU regulation and analytical methods should be implemented is the area of Shiga toxin producing E. coli, including E. coli O157 and staphylococcal enterotoxin detection. During the project, the analysis of the existing Ukrainian and EU data concerning the prevalence of the most important food-borne pathogens on different stages of food production chain was performed. Particularly, prevalence of Salmonella spp., Campylobacter spp., L. monocytogenes as well as clostridia was examined. The analysis showed that poultry meat still appears to be the most important food-borne source of Campylobacter and Salmonella in the UE. On the other hand, L. monocytogenes were seldom detected above the legal safety limit (100 cfu/g) among the EU countries. Moreover, the analysis revealed the lack of comprehensive data regarding the prevalence of the most important food-borne pathogens in Ukraine. The results of the MICRORISK project are networking activities among researches originations participating in the tasks will help with a better recognition of each other regarding very important, from the public health point of view areas such as microbiological hazards in the food production chain and finally will help to improve food quality and safety for consumers.

Keywords: cooperation, European Union, food chain safety, food law, microbiological risk, Microrisk, Poland, Ukraine

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29 Turn Organic Waste to Green Fuels with Zero Landfill

Authors: Xu Fei (Philip) WU

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As waste recycling concept been accepted more and more in modern societies, the organic portion of the municipal waste become a sires issue in today’s life. Depend on location and season, the organic waste can bee anywhere between 40-65% of total municipal solid waste. Also composting and anaerobic digestion technologies been applied in this field for years, however both process have difficulties been selected by economical and environmental factors. Beside environmental pollution and risk of virus spread, the compost is not a product been welcomed by people even the waste management has to give up them at no cost. The anaerobic digester has to have 70% of water and keep at 35 degree C or above; base on above conditions, the retention time only can be up to two weeks and remain solid has to be dewater and composting again. The enhancive waste water treatment has to be added after. Because these reasons, the voice of suggesting cancelling recycling program and turning all waste to mass burn incinerations have been raised-A process has already been proved has least energy efficiency and most air pollution problem associated process. A newly developed WXF Bio-energy process employs recently developed and patented pre-designed separation, multi-layer and multi-cavity successive bioreactor landfill technology. It features an improved leachate recycling technology, technologies to maximize the biogas generation rate and a reduced overall turnaround period on the land. A single properly designed and operated site can be used indefinitely. In this process, all collected biogas will be processed to eliminate H2S and other hazardous gases. The methane, carbon dioxide and hydrogen will be utilized in a proprietary process to manufacture methanol which can be sold to mitigate operating costs of the landfill. This integration of new processes offers a more advanced alternative to current sanitary landfill, incineration and compost technology. Xu Fei (Philip) Wu Xu Fei Wu is founder and Chief Scientist of W&Y Environmental International Inc. (W & Y), a Canadian environmental and sustainable energy technology company with patented landfill processes and proprietary waste to energy technologies. He has worked in environmental and sustainable energy fields over the last 25 years. Before W&Y, he worked for Conestoga-Rovers & Associates Limited, Microbe Environmental Science and Technology Inc. of Canada and The Ministry of Nuclear Industry and Ministry of Space Flight Industry of China. Xu Fei Wu holds a Master of Engineering Science degree from The University of Western Ontario. I wish present this paper as an oral presentation only Selected Conference Presentations: • “Removal of Phenolic Compounds with Algae” Presented at 25th Canadian Symposium on Water Pollution Research (CAWPRC Conference), Burlington, Ontario Canada. February, 1990 • “Removal of Phenolic Compounds with Algae” Presented at Annual Conference of Pollution Control Association of Ontario, London, Ontario, Canada. April, 1990 • “Removal of Organochlorine Compounds in a Flocculated Algae Photo-Bioreactor” Presented at International Symposium on Low Cost and Energy Saving Wastewater Treatment Technologies (IAWPRC Conference), Kiyoto, Japan, August, 1990 • “Maximizing Production and Utilization of Landfill Gas” 2009 Wuhan International Conference on Environment(CAWPRC Conference, sponsored by US EPA) Wuhan, China. October, 2009. • “WXF Bio-Energy-A Green, Sustainable Waste to Energy Process” Presented at 9Th International Conference Cooperation for Waste Issues, Kharkiv, Ukraine March, 2012 • “A Lannfill Site Can Be Recycled Indefinitely” Presented at 28th International Conference on solid Waste Technology and Management, Philadelphia, Pennsylvania, USA. March, 2013. Hosted by The Journal of Solid Waste Technology and Management.

Keywords: green fuel, waste management, bio-energy, sustainable development, methanol

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28 Prevalence and Diagnostic Evaluation of Schistosomiasis in School-Going Children in Nelson Mandela Bay Municipality: Insights from Urinalysis and Point-of-Care Testing

Authors: Maryline Vere, Wilma ten Ham-Baloyi, Lucy Ochola, Opeoluwa Oyedele, Lindsey Beyleveld, Siphokazi Tili, Takafira Mduluza, Paula E. Melariri

Abstract:

Schistosomiasis, caused by Schistosoma (S.) haematobium and Schistosoma (S.) mansoni parasites poses a significant public health challenge in low-income regions. Diagnosis typically relies on identifying specific urine biomarkers such as haematuria, protein, and leukocytes for S. haematobium, while the Point-of-Care Circulating Cathodic Antigen (POC-CCA) assay is employed for detecting S. mansoni. Urinalysis and the POC-CCA assay are favoured for their rapid, non-invasive nature and cost-effectiveness. However, traditional diagnostic methods such as Kato-Katz and urine filtration lack sensitivity in low-transmission areas, which can lead to underreporting of cases and hinder effective disease control efforts. Therefore, in this study, urinalysis and the POC-CCA assay was utilised to diagnose schistosomiasis effectively among school-going children in Nelson Mandela Bay Municipality. This was a cross-sectional study with a total of 759 children, aged 5 to 14 years, who provided urine samples. Urinalysis was performed using urinary dipstick tests, which measure multiple parameters, including haematuria, protein, leukocytes, bilirubin, urobilinogen, ketones, pH, specific gravity and other biomarkers. Urinalysis was performed by dipping the strip into the urine sample and observing colour changes on specific reagent pads. The POC-CCA test was conducted by applying a drop of urine onto a cassette containing CCA-specific antibodies, and the presence of a visible test line indicated a positive result for S. mansoni infection. Descriptive statistics were used to summarize urine parameters, and Pearson correlation coefficients (r) were calculated to analyze associations among urine parameters using R software (version 4.3.1). Among the 759 children, the prevalence of S. haematobium using haematuria as a diagnostic marker was 33.6%. Additionally, leukocytes were detected in 21.3% of the samples, and protein was present in 15%. The prevalence of positive POC-CCA test results for S. mansoni was 3.7%. Urine parameters exhibited low to moderate associations, suggesting complex interrelationships. For instance, specific gravity and pH showed a negative correlation (r = -0.37), indicating that higher specific gravity was associated with lower pH. Weak correlations were observed between haematuria and pH (r = -0.10), bilirubin and ketones (r = 0.14), protein and bilirubin (r = 0.13), and urobilinogen and pH (r = 0.12). A mild positive correlation was found between leukocytes and blood (r = 0.23), reflecting some association between these inflammation markers. In conclusion, the study identified a significant prevalence of schistosomiasis among school-going children in Nelson Mandela Bay Municipality, with S. haematobium detected through haematuria and S. mansoni identified using the POC-CCA assay. The detection of leukocytes and protein in urine samples serves as critical biomarkers for schistosomiasis infections, reinforcing the presence of schistosomiasis in the study area when considered alongside haematuria. These urine parameters are indicative of inflammatory responses associated with schistosomiasis, underscoring the necessity for effective diagnostic methodologies. Such findings highlight the importance of comprehensive diagnostic assessments to accurately identify and monitor schistosomiasis prevalence and its associated health impacts. The significant burden of schistosomiasis in this population highlights the urgent need to develop targeted control interventions to effectively reduce its prevalence in the study area.

Keywords: schistosomiasis, urinalysis, haematuria, POC-CCA

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27 Location3: A Location Scouting Platform for the Support of Film and Multimedia Industries

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

Abstract:

The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

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26 Microdiamond and Moissanite Inclusions in Garnets from Pohorje Mountains, Eastern Alps, Slovenia

Authors: Mirijam Vrabec, Marian Janak, Bojan Ambrozic, Angelja K. Surca, Nastja Rogan Smuc, Nina Zupancic, Saso Sturm

Abstract:

Natural microdiamonds and moissanite (SiC) can form during the orogenic events under ultrahigh-pressure metamorphic conditions (UHP), when parts of Earth’s crust are subducted to extreme depths. So far, such processes were identified only in few places on the Earth, and therefore, represent unique opportunity to study the evolution of the Earth’s deep interior. An important discovery of microdiamonds and moissanite was reported from Pohorje, (Slovenia), where they occurred as single or polyphase inclusions in garnets. Metasedimentary rocks from Pohorje are predominantly gneisses representing parts of the Austroalpine metamorphic units of the Eastern Alps. During Cretaceous orogeny, (ca. 95–92 Ma) continental crustal rocks were deeply subducted to the mantle depths (below 100 km) and metamorphosed at pressures exceeding 3.5 GPa and temperatures between 800–850 °C. Microstructural and phase analysis of the inclusions as well as detailed elemental analysis of host garnets were carried out combining several analytical techniques: optical microscope in plane polarized transmitted light, electron probe microanalysis (EPMA) with wavelength-dispersive x-ray spectrometry (WDS) and field-emission scanning microscope (FEG-SEM) with energy-dispersive x-ray spectroscopy (EDS). Micro-Raman analysis revealed sharp, first order diamond bands sometimes accompanied by graphite bands implying that transformation of diamond back to graphite occurred. To study the chemical and crystallographic relationship between microdiamonds and co-inclusions, advanced techniques of transmission electron microscopy (TEM) were applied, which included high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), combined with EDS and electron energy-loss spectroscopy (EELS). To prepare electron transparent TEM lamellae selectively a dual-beam Focused Ion Beam/SEM (FIB/SEM) was employed. Detailed study of TEM lamellae, which was cross-sectioned from the highly faceted inclusion body located within the host garnet crystal matrix, revealed rich and rather complex internal structure. Namely, the negative crystal facets of the main inclusion body were typically decorated with up to 1 μm thick amorphous layer, reflecting the general garnet composition with slight variations in Fe/Ca content. Within these layers, ELNES analysis revealed the presence of a 28–30 nm thick layer of amorphous carbon. The very last section of this layer corresponds to composition of SiO2. Within the inclusion, besides diamond and moissanite alumosilicate mineral with pronounced layered structure, iron sulfides and chlorine were identified under TEM and CO2 and CH4 using Raman. Moissanite is found as single crystal or composed from numerous highly textured nano-crystals with the average size of 10 nm. Moissanite inclusions were found embedded inside the amorphous crust implying that moissanite crystalized well before the deposition of the amorphous layer. From the microstructural, crystallographic and chemical observations so far we can deduce, that polyphase inclusions in diamond bearing garnets from Pohorje most probably crystallized from reduced supercritical fluids. Based on layered interface structure of the host mineral multiphase process of crystallization is possible. The presence of microdiamonds and moissanite in rocks from Pohorje demonstrates that these parts of the Eastern Alps were subducted to extreme depths, and were subsequently exhumed back to the Earth's surface without complete breakdown of UHP mineral phases, allowing a rear and exceptional opportunity to study them in-situ.

Keywords: diamond, fluid inclusions, moissanite, TEM, UHP metamorphism.

Procedia PDF Downloads 299
25 Electronic Raman Scattering Calibration for Quantitative Surface-Enhanced Raman Spectroscopy and Improved Biostatistical Analysis

Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

Abstract:

Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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24 Impacts of School-Wide Positive Behavioral Interventions and Supports on Student Academics, Behavior and Mental Health

Authors: Catherine Bradshaw

Abstract:

Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

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23 Spectroscopic Study of the Anti-Inflammatory Action of Propofol and Its Oxidant Derivatives: Inhibition of the Myeloperoxidase Activity and of the Superoxide Anions Production by Neutrophils

Authors: Pauline Nyssen, Ange Mouithys-Mickalad, Maryse Hoebeke

Abstract:

Inflammation is a complex physiological phenomenon involving chemical and enzymatic mechanisms. Polymorphonuclear neutrophil leukocytes (PMNs) play an important role by producing reactive oxygen species (ROS) and releasing myeloperoxidase (MPO), a pro-oxidant enzyme. Released both in the phagolysosome and the extracellular medium, MPO produces during its peroxidase and halogenation cycles oxidant species, including hypochlorous acid, involved in the destruction of pathogen agents, like bacteria or viruses. Inflammatory pathologies, like rheumatoid arthritis, atherosclerosis induce an excessive stimulation of the PMNs and, therefore, an uncontrolled release of ROS and MPO in the extracellular medium, causing severe damages to the surrounding tissues and biomolecules such as proteins, lipids, and DNA. The treatment of chronic inflammatory pathologies remains a challenge. For many years, MPO has been used as a target for the development of effective treatments. Numerous studies have been focused on the design of new drugs presenting more efficient MPO inhibitory properties. However, some designed inhibitors can be toxic. An alternative consists of assessing the potential inhibitory action of clinically-known molecules, having antioxidant activity. Propofol, 2,6-diisopropyl phenol, which is used as an intravenous anesthetic agent, meets these requirements. Besides its anesthetic action employed to induce a sedative state during surgery or in intensive care units, propofol and its injectable form Diprivan indeed present antioxidant properties and act as ROS and free radical scavengers. A study has also evidenced the ability of propofol to inhibit the formation of the neutrophil extracellular traps fibers, which are important to trap pathogen microorganisms during the inflammation process. The aim of this study was to investigate the potential inhibitory action mechanism of propofol and Diprivan on MPO activity. To go into the anti-inflammatory action of propofol in-depth, two of its oxidative derivatives, 2,6-diisopropyl-1,4-p-benzoquinone (PPFQ) and 3,5,3’,5’-tetra isopropyl-(4,4’)-diphenoquinone (PPFDQ), were studied regarding their inhibitory action. Specific immunological extraction followed by enzyme detection (SIEFED) and molecular modeling have evidenced the low anti-catalytic action of propofol. Stopped-flow absorption spectroscopy and direct MPO activity analysis have proved that propofol acts as a reversible MPO inhibitor by interacting as a reductive substrate in the peroxidase cycle and promoting the accumulation of redox compound II. Overall, Diprivan exhibited a weaker inhibitory action than the active molecule propofol. In contrast, PPFQ seemed to bind and obstruct the enzyme active site, preventing the trigger of the MPO oxidant cycles. PPFQ induced a better chlorination cycle inhibition at basic and neutral pH in comparison to propofol. PPFDQ did not show any MPO inhibition activity. The three interest molecules have also demonstrated their inhibition ability on an important step of the inflammation pathway, the PMNs superoxide anions production, thanks to EPR spectroscopy and chemiluminescence. In conclusion, propofol presents an interesting immunomodulatory activity by acting as a reductive substrate in the peroxidase cycle of MPO, slowing down its activity, whereas PPFQ acts more as an anti-catalytic substrate. Although PPFDQ has no impact on MPO, it can act on the inflammation process by inhibiting the superoxide anions production by PMNs.

Keywords: Diprivan, inhibitor, myeloperoxidase, propofol, spectroscopy

Procedia PDF Downloads 143
22 Improving Patient Journey in the Obstetrics and Gynecology Emergency Department: A Comprehensive Analysis of Patient Experience

Authors: Lolwa Alansari, Abdelhamid Azhaghdani, Sufia Athar, Hanen Mrabet, Annaliza Cruz, Tamara Alshadafat, Almunzer Zakaria

Abstract:

Introduction: Improving the patient experience is a fundamental pillar of healthcare's quadruple aims. Recognizing the importance of patient experiences and perceptions in healthcare interactions is pivotal for driving quality improvement. This abstract centers around the Patient Experience Program, an endeavor crafted with the purpose of comprehending and elevating the experiences of patients in the Obstetrics & Gynecology Emergency Department (OB/GYN ED). Methodology: This comprehensive endeavor unfolded through a structured sequence of phases following Plan-Do-Study-Act (PDSA) model, spanning over 12 months, focused on enhancing patient experiences in the Obstetrics & Gynecology Emergency Department (OB/GYN ED). The study meticulously examined the journeys of patients with acute obstetrics and gynecological conditions, collecting data from over 100 participants monthly. The inclusive approach covered patients of different priority levels (1-5) admitted for acute conditions, with no exclusions. Historical data from March and April 2022 serves as a benchmark for comparison, strengthening causality claims by providing a baseline understanding of OB/GYN ED performance before interventions. Additionally, the methodology includes the incorporation of staff engagement surveys to comprehensively understand the experiences of healthcare professionals with the implemented improvements. Data extraction involved administering open-ended questions and comment sections to gather rich qualitative insights. The survey covered various aspects of the patient journey, including communication, emotional support, timely access to care, care coordination, and patient-centered decision-making. The project's data analysis utilized a mixed-methods approach, combining qualitative techniques to identify recurring themes and extract actionable insights and quantitative methods to assess patient satisfaction scores and relevant metrics over time, facilitating the measurement of intervention impact and longitudinal tracking of changes. From the themes we discovered in both the online and in-person patient experience surveys, several key findings emerged that guided us in initiating improvements, including effective communication and information sharing, providing emotional support and empathy, ensuring timely access to care, fostering care coordination and continuity, and promoting patient-centered decision-making. Results: The project yielded substantial positive outcomes, significantly improving patient experiences in the OB/GYN ED. Patient satisfaction levels rose from 62% to a consistent 98%, with notable improvements in satisfaction with care plan information and physician care. Waiting time satisfaction increased from 68% to a steady 97%. The project positively impacted nurses' and midwives' job satisfaction, increasing from 64% to an impressive 94%. Operational metrics displayed positive trends, including a decrease in the "left without being seen" rate from 3% to 1%, the discharge against medical advice rate dropping from 8% to 1%, and the absconded rate reducing from 3% to 0%. These outcomes underscore the project's effectiveness in enhancing both patient and staff experiences in the healthcare setting. Conclusion: The use of a patient experience questionnaire has been substantiated by evidence-based research as an effective tool for improving the patient experience, guiding interventions, and enhancing overall healthcare quality in the OB/GYN ED. The project's interventions have resulted in a more efficient allocation of resources, reduced hospital stays, and minimized unnecessary resource utilization. This, in turn, contributes to cost savings for the healthcare facility.

Keywords: patient experience, patient survey, person centered care, quality initiatives

Procedia PDF Downloads 55
21 Image Segmentation with Deep Learning of Prostate Cancer Bone Metastases on Computed Tomography

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

Abstract:

Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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20 The Routes of Human Suffering: How Point-Source and Destination-Source Mapping Can Help Victim Services Providers and Law Enforcement Agencies Effectively Combat Human Trafficking

Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

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19 Characterizing and Developing the Clinical Grade Microbiome Assay with a Robust Bioinformatics Pipeline for Supporting Precision Medicine Driven Clinical Development

Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

Abstract:

Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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18 Magnetic Single-Walled Carbon Nanotubes (SWCNTs) as Novel Theranostic Nanocarriers: Enhanced Targeting and Noninvasive MRI Tracking

Authors: Achraf Al Faraj, Asma Sultana Shaik, Baraa Al Sayed

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Specific and effective targeting of drug delivery systems (DDS) to cancerous sites remains a major challenge for a better diagnostic and therapy. Recently, SWCNTs with their unique physicochemical properties and the ability to cross the cell membrane show promising in the biomedical field. The purpose of this study was first to develop a biocompatible iron oxide tagged SWCNTs as diagnostic nanoprobes to allow their noninvasive detection using MRI and their preferential targeting in a breast cancer murine model by placing an optimized flexible magnet over the tumor site. Magnetic targeting was associated to specific antibody-conjugated SWCNTs active targeting. The therapeutic efficacy of doxorubicin-conjugated SWCNTs was assessed, and the superiority of diffusion-weighted (DW-) MRI as sensitive imaging biomarker was investigated. Short Polyvinylpyrrolidone (PVP) stabilized water soluble SWCNTs were first developed, tagged with iron oxide nanoparticles and conjugated with Endoglin/CD105 monoclonal antibodies. They were then conjugated with doxorubicin drugs. SWCNTs conjugates were extensively characterized using TEM, UV-Vis spectrophotometer, dynamic light scattering (DLS) zeta potential analysis and electron spin resonance (ESR) spectroscopy. Their MR relaxivities (i.e. r1 and r2*) were measured at 4.7T and their iron content and metal impurities quantified using ICP-MS. SWCNTs biocompatibility and drug efficacy were then evaluated both in vitro and in vivo using a set of immunological assays. Luciferase enhanced bioluminescence 4T1 mouse mammary tumor cells (4T1-Luc2) were injected into the right inguinal mammary fat pad of Balb/c mice. Tumor bearing mice received either free doxorubicin (DOX) drug or SWCNTs with or without either DOX or iron oxide nanoparticles. A multi-pole 10x10mm high-energy flexible magnet was maintained over the tumor site during 2 hours post-injections and their properties and polarity were optimized to allow enhanced magnetic targeting of SWCNTs toward the primary tumor site. Tumor volume was quantified during the follow-up investigation study using a fast spin echo MRI sequence. In order to detect the homing of SWCNTs to the main tumor site, susceptibility-weighted multi-gradient echo (MGE) sequence was used to generate T2* maps. Apparent diffusion coefficient (ADC) measurements were also performed as a sensitive imaging biomarker providing early and better assessment of disease treatment. At several times post-SWCNT injection, histological analysis were performed on tumor extracts and iron-loaded SWCNT were quantified using ICP-MS in tumor sites, liver, spleen, kidneys, and lung. The optimized multi-poles magnet revealed an enhanced targeting of magnetic SWCNTs to the primary tumor site, which was found to be much higher than the active targeting achieved using antibody-conjugated SWCNTs. Iron-loading allowed their sensitive noninvasive tracking after intravenous administration using MRI. The active targeting of doxorubicin through magnetic antibody-conjugated SWCNTs nanoprobes was found to considerably decrease the primary tumor site and may have inhibited the development of metastasis in the tumor-bearing mice lung. ADC measurements in DW-MRI were found to significantly increase in a time-dependent manner after the injection of DOX-conjugated SWCNTs complexes.

Keywords: single-walled carbon nanotubes, nanomedicine, magnetic resonance imaging, cancer diagnosis and therapy

Procedia PDF Downloads 327