Search results for: synthetic aperture imaging

Authors: Mustafa Alshawaqfeh, Bilal Wajidy, Echin Serpedin, Jan Suchodolski

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Inflammatory Bowel disease (IBD) is a disease of the colon with characteristic inflammation. Clinically IBD is detected using laboratory tests (blood and stool), radiology tests (imaging using CT, MRI), capsule endoscopy and endoscopy. There are two variants of IBD referred to as Ulcerative Colitis (UC) and Crohn’s disease. This study employs a hybrid feature selection method that combines a correlation-based variable ranking approach with exhaustive search wrapper methods in order to find potential biomarkers for UC. The proposed biomarkers presented accurate discriminatory power thereby identifying themselves to be possible ingredients to UC therapeutics.

Keywords: ulcerative colitis, biomarker detection, feature selection, inflammatory bowel disease (IBD)

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Authors: Prince Kumar, Shamseer Kulangara Kandi, Diwan S. Rawat, Kasturi Mukhopadhyay

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Staphylococcus aureus is the most pathogenic of all staphylococci, a major cause of nosocomial infections, and known for acquiring resistance towards various commonly used antibiotics. Due to the widespread use of synthetic drugs, clinicians are now facing a serious threat in healthcare. The increasing resistance in staphylococci has created a need for alternatives to these synthetic drugs. One of the alternatives is a natural plant-based medicine for both disease prevention as well as the treatment of chronic diseases. Among such natural compounds, curcumin is one of the most studied molecules and has been an integral part of traditional medicines and Ayurveda from ancient times. It is a natural polyphenolic compound with diverse pharmacological effects, including anti-inflammatory, antioxidant, anti-cancerous and antibacterial activities. In spite of its efficacy and potential, curcumin has not been approved as a therapeutic agent yet, because of its low solubility, low bioavailability, and rapid metabolism in vivo. The presence of central β-diketone moiety in curcumin is responsible for its rapid metabolism. To overcome this, in the present study, curcuminoids were designed by modifying the central β-diketone moiety of curcumin into mono carbonyl moiety and their antibacterial potency against S. aureus ATCC 29213 was determined. Further, the mode of action and hemolytic activity of the most potent curcuminoids were studied. Minimum inhibitory concentration (MIC) and in vitro killing kinetics were used to study the antibacterial activity of the designed curcuminoids. For hemolytic assay, mouse Red blood cells were incubated with curcuminoids and hemoglobin release was measured spectrophotometrically. The mode of action of curcuminoids was analysed by membrane depolarization assay using membrane potential sensitive dye 3,3’-dipropylthiacarbocyanine iodide (DiSC3(5)) through spectrofluorimetry and membrane permeabilization assay using calcein-AM through flow cytometry. Antibacterial screening of the designed library (61 curcuminoids) revealed excellent in vitro potency of six compounds against S. aureus (MIC 8 to 32 µg/ml). Moreover, these six compounds were found to be non-hemolytic up to 225 µg/ml that is much higher than their corresponding MIC values. The in vitro killing kinetics data showed five of these lead compounds to be bactericidal causing >3 log reduction in the viable cell count within 4 hrs at 5 × MIC while the sixth compound was found to be bacteriostatic. Depolarization assay revealed that all the six curcuminoids caused depolarization in their corresponding MIC range. Further, the membrane permeabilization assay showed that all the six curcuminoids caused permeabilization at 5 × MIC in 2 hrs. This membrane depolarization and permeabilization caused by curcuminoids found to be in correlation with their corresponding killing efficacy. Both these assays point out that membrane perturbations might be a primary mode of action for these curcuminoids. Overall, the present study leads us six water soluble, non-hemolytic, membrane-active curcuminoids and provided an impetus for further research on therapeutic use of these lead curcuminoids against S. aureus.

Keywords: antibacterial, curcumin, minimum inhibitory concentration , Staphylococcus aureus

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Authors: Mamdouh Y. Saleh, Gaber El Enany, Medhat H. Elzahar, Moustafa H. Omran

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The discharge limits of industrial wastewater effluents are subjected to regulations which are getting more restricted with time. A former research occurred in Port Said city studied the efficiency of treating industrial wastewater using the first stage (A-stage) of the multiple-stage plant (AB-system).From the results of this former research, the effluent treated wastewater has high rates of total dissolved solids (TDS) and chemical oxygen demand (COD). The purpose of this paper is to improve the treatment process in removing TDS and COD. So a pilot plant was constructed at wastewater pump station in the industrial area in the south of Port Said. Experimental work was divided into several groups adding powdered limestone with different dosages to wastewater, and for each group wastewater was filtered after being mixed with activated carbon. pH and TSS as variables were also studied. Significant removals of TDS and COD were observed in these experiments showing that using effective adsorbents can aid such removals to a large extent.

Keywords: adsorption, filtration, synthetic wastewater, TDS removal, COD removal

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Authors: Kai Chen, Shuguang Cui, Feng Yin

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Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

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Authors: Isa Moazen, Ali Nahvi

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Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Luphumlo Ncanywa, Paul Watts

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Malaria is a disease that kills approximately one million people annually. Children and pregnant women in sub-Saharan Africa lost their lives due to malaria. Malaria continues to be one of the major causes of death, especially in poor countries in Africa. Decrease the burden of malaria and save lives is very essential. There is a major concern about malaria parasites being able to develop resistance towards antimalarial drugs. People are still dying due to lack of medicine affordability in less well-off countries in the world. If more people could receive treatment by reducing the cost of drugs, the number of deaths in Africa could be massively reduced. There is a shortage of pharmaceutical manufacturing capability within many of the countries in Africa. However one has to question how Africa would actually manufacture drugs, active pharmaceutical ingredients or medicines developed within these research programs. It is quite likely that such manufacturing would be outsourced overseas, hence increasing the cost of production and potentially limiting the full benefit of the original research. As a result the last few years has seen major interest in developing more effective and cheaper technology for manufacturing generic pharmaceutical products. Micro-reactor technology (MRT) is an emerging technique that enables those working in research and development to rapidly screen reactions utilizing continuous flow, leading to the identification of reaction conditions that are suitable for usage at a production level. This emerging technique will be used to develop antimalarial drugs. It is this system flexibility that has the potential to reduce both the time was taken and risk associated with transferring reaction methodology from research to production. Using an approach referred to as scale-out or numbering up, a reaction is first optimized within the laboratory using a single micro-reactor, and in order to increase production volume, the number of reactors employed is simply increased. The overall aim of this research project is to develop and optimize synthetic process of antimalarial drugs in the continuous processing. This will provide a step change in pharmaceutical manufacturing technology that will increase the availability and affordability of antimalarial drugs on a worldwide scale, with a particular emphasis on Africa in the first instance. The research will determine the best chemistry and technology to define the lowest cost manufacturing route to pharmaceutical products. We are currently developing a method to synthesize Lumefantrine in continuous flow using batch process as bench mark. Lumefantrine is a dichlorobenzylidine derivative effective for the treatment of various types of malaria. Lumefantrine is an antimalarial drug used with artemether for the treatment of uncomplicated malaria. The results obtained when synthesizing Lumefantrine in a batch process are transferred into a continuous flow process in order to develop an even better and reproducible process. Therefore, development of an appropriate synthetic route for Lumefantrine is significant in pharmaceutical industry. Consequently, if better (and cheaper) manufacturing routes to antimalarial drugs could be developed and implemented where needed, it is far more likely to enable antimalarial drugs to be available to those in need.

Keywords: antimalarial, flow, lumefantrine, synthesis

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Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

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Many people know ‘Mathematics needs practice!’ statement or similar ones from their mathematics lessons. It seems important to practice when learning mathematics. At the same time, it also seems important to practice how to learn mathematics. This paper places neuroscientific-radiological findings on “practicing” while learning mathematics in a context of mathematics education. To accomplish this, we use a literature-based discussion of our case study on practice. We want to describe neuroscientific-radiological findings in the context of mathematics education and point out stimulating connections between both perspectives. From a connective perspective we expect incentives that lead discussions in future research in the field of mathematics education.

Keywords: functional magnetic resonance imaging, fMRI, education, mathematics learning, practicing

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Authors: Steven Robinson, Adriana Dager, Param Patel

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Wandering spleen is a rare variant where there is abnormal development of the ligamentous peritoneal attachments of the spleen which normally anchor it in the left upper quadrant of the abdomen. Ligamentous abnormalities can be congenital, or acquired through pregnancy, injury, or iatrogenic causes. Absence or laxity of these ligaments allows migration of the spleen into ectopic portions of the abdomen, which is also associated with an elongated vascular pedicle. Incidence of wandering spleen is reported at less than 0.25% with a female to male ratio of approximately 6:1. The most common complication of a wandering spleen is torsion around its vascular pedicle which can lead to thrombosis and infarction. Torsion of a wandering spleen is a rare but important cause of an acute abdomen. Imaging, and specifically CT or ultrasound, is crucial in the diagnosis. We present a case of a torsed wandering spleen which was treated with splenectomy.

Keywords: Wandering Spleen, Torsion, Splenic Torsion, Spleen

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Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Marjila Burhanzoi, Kenta Onohara, Tomoaki Ikegami

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Faults in photovoltaic (PV) modules should be detected to the greatest extent as early as possible. For that conventional fault detection methods such as electrical characterization, visual inspection, infrared (IR) imaging, ultraviolet fluorescence and electroluminescence (EL) imaging are used, but they either fail to detect the location or category of fault, or they require expensive equipment and are not convenient for onsite application. Hence, these methods are not convenient to use for monitoring small-scale PV systems. Therefore, low cost and efficient inspection techniques with the ability of onsite application are indispensable for PV modules. In this study in order to establish efficient inspection technique, correlation between faults and magnetic flux density on the surface is of crystalline PV modules are investigated. Magnetic flux on the surface of normal and faulted PV modules is measured under the short circuit and illuminated conditions using two different sensor devices. One device is made of small integrated sensors namely 9-axis motion tracking sensor with a 3-axis electronic compass embedded, an IR temperature sensor, an optical laser position sensor and a microcontroller. This device measures the X, Y and Z components of the magnetic flux density (Bx, By and Bz) few mm above the surface of a PV module and outputs the data as line graphs in LabVIEW program. The second device is made of a laser optical sensor and two magnetic line sensor modules consisting 16 pieces of magnetic sensors. This device scans the magnetic field on the surface of PV module and outputs the data as a 3D surface plot of the magnetic flux intensity in a LabVIEW program. A PC equipped with LabVIEW software is used for data acquisition and analysis for both devices. To show the effectiveness of this method, measured results are compared to those of a normal reference module and their EL images. Through the experiments it was confirmed that the magnetic field in the faulted areas have different profiles which can be clearly identified in the measured plots. Measurement results showed a perfect correlation with the EL images and using position sensors it identified the exact location of faults. This method was applied on different modules and various faults were detected using it. The proposed method owns the ability of on-site measurement and real-time diagnosis. Since simple sensors are used to make the device, it is low cost and convenient to be sued by small-scale or residential PV system owners.

Keywords: fault diagnosis, fault location, integrated sensors, PV modules

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Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

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A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml^-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 10³ l mol^-1cm^-1 and 0.0125 μg cm^-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: solvent extraction, PMPT, Palladium (II), spectrophotometry

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Authors: Amira Touil, Achouak Arfaoui, Ibtissem Mannaii

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The aim of this work is to monitor the process adsorption of nitrates by the biochar via studying the influence of various parameters on the adsorption of this pollutant by biochar in a synthetic aqueous solution. The results which obtained indicate that the 4g/L biochar dose is the most efficient in terms of nitrates removal in aqueous solution. The biochar exhibited a good affinity for nitrates after 1hour of contact. The yield of removal of nitrate by the biochar decreases with the increase of pH of the solution and increases with increasing temperature (60°C>40°C>20°C). The best removal yield is about 80% of the initial concentration introduced (25mg/L) obtained at pH=2, T=60°C, and dose of biochar=4g/L. The second order model fit the nitrate adsorption kinetics of biochar with a high coefficient of determination (R2≥0.997); and a new equation correlating the rate constant of the reaction with temperature and pH was been built. Freundlich isotherms performed well to fit the nitrate adsorption data by biochar (R2>0.96) compared to Langmuir isotherms. The thermodynamic parameters (ΔH°, ΔG°, ΔS°) have been calculated for predicting the nature of adsorption.

Keywords: pollution, biochar, nitrate, adsorption

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

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Authors: Samson Munn, Virginia H. Kim, Huija Chen, Sean Maldonado, Michelle Kim, Paul Koscheski, Babak N. Kalantari, Gregory Eckel, Albert Lee

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In terms of screening mammography quality, neither the portion of reports that advise call-back imaging that should be bilateral versus unilateral nor how much the unilateral call-backs may appropriately diverge from 50–50 (left versus right) is known. Many factors may affect detection laterality: display arrangement, reflections preferentially striking one display location, hanging protocols, seating positions with respect to others and displays, visual field cuts, health, etc. The call-back bilateral fraction may reflect radiologist experience (not in our data) or confidence level. Thus, laterality and bilaterality of call-backs advised in screening mammography reports could be worthy quality metrics. Here, laterality data did not reveal a concern until drilling down to individuals. Bilateral screening mammogram report recommendations by five breast imaging, attending radiologists at Harbor-UCLA Medical Center (Torrance, California) 9/1/15--8/31/16 and 9/1/16--8/31/17 were retrospectively reviewed. Recommended call-backs for bilateral versus unilateral, and for left versus right, findings were counted. Chi-square (χ²) statistic was applied. Year 1: of 2,665 bilateral screening mammograms, reports of 556 (20.9%) recommended call-back, of which 99 (17.8% of the 556) were for bilateral findings. Of the 457 unilateral recommendations, 222 (48.6%) regarded the left breast. Year 2: of 2,106 bilateral screening mammograms, reports of 439 (20.8%) recommended call-back, of which 65 (14.8% of the 439) were for bilateral findings. Of the 374 unilateral recommendations, 182 (48.7%) regarded the left breast. Individual ranges of call-backs that were bilateral were 13.2–23.3%, 10.2–22.5%, and 13.6–17.9%, by year(s) 1, 2, and 1+2, respectively; these ranges were unrelated to experience level; the two-year mean was 15.8% (SD=1.9%). The lowest χ² p value of the group's sidedness disparities years 1, 2, and 1+2 was > 0.4. Regarding four individual radiologists, the lowest p value was 0.42. However, the fifth radiologist disfavored the left, with p values of 0.21, 0.19, and 0.07, respectively; that radiologist had the greatest number of years of experience. There was a concerning, 93% likelihood that bias against left breast findings evidenced by one of our radiologists was not random. Notably, very soon after the period under review, he retired, presented with leukemia, and died. We call for research to be done, particularly by large departments with many radiologists, of two possible, new, quality metrics in screening mammography: laterality and bilaterality. (Images, patient outcomes, report validity, and radiologist psychological confidence levels were not assessed. No intervention nor subsequent data collection was conducted. This uncomplicated collection of data and simple appraisal were not designed, nor had there been any intention to develop or contribute, to generalizable knowledge (per U.S. DHHS 45 CFR, part 46)).

Keywords: mammography, screening mammography, quality, quality metrics, laterality

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Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Nikhil Kumar, Aparna Singh

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Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

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Authors: Fawzyah Albaldi

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Urinary tract infections (UTIs) are the most prevalent of infectious diseases and > 80% are caused by uropathogenic E. coli (UPEC). Infection occurs following adhesion to urothelial plaques on bladder epithelial cells, whose major protein constituent are the uroplakins (UPs). Two of the four uroplakins (UPIa and UPIb) are members of the tetraspanin superfamily. The UPEC adhesin FimH is known to interact directly with UPIa. Tetraspanins are a diverse family of transmembrane proteins that generally act as “molecular organizers” by binding different proteins and lipids to form tetraspanin enriched microdomains (TEMs). Previous work by our group has shown that TEMs are involved in the adhesion of many pathogenic bacteria to human cells. Adhesion can be blocked by tetraspanin-derived synthetic peptides, suggesting that tetraspanins may be valuable drug targets. In this study, we investigate the role of tetraspanins in UPEC adherence to bladder epithelial cells. Human bladder cancer cell lines (T24, 5637, RT4), commonly used as in-vitro models to investigate UPEC infection, along with primary human bladder cells, were used in this project. The aim was to establish a model for UPEC adhesion/infection with the objective of evaluating the impact of tetraspanin-derived reagents on this process. Such reagents could reduce the progression of UTI, particularly in patients with indwelling catheters. Tetraspanin expression on the bladder cells was investigated by q-PCR and flow cytometry, with CD9 and CD81 generally highly expressed. Interestingly, despite these cell lines being used by other groups to investigate FimH antagonists, uroplakin proteins (UPIa, UPIb and UPIII) were poorly expressed at the cell surface, although some were present intracellularly. Attempts were made to differentiate the cell lines, to induce cell surface expression of these UPs, but these were largely unsuccessful. Pre-treatment of bladder epithelial cells with anti-CD9 monoclonal antibody significantly decreased UPEC infection, whilst anti-CD81 had no effects. A short (15aa) synthetic peptide corresponding to the large extracellular region (EC2) of CD9 also significantly reduced UPEC adherence. Furthermore, we demonstrated specific binding of that fluorescently tagged peptide to the cells. CD9 is known to associate with a number of heparan sulphate proteoglycans (HSPGs) that have also been implicated in bacterial adhesion. Here, we demonstrated that unfractionated heparin (UFH)and heparin analogs significantly inhibited UPEC adhesion to RT4 cells, as did pre-treatment of the cells with heparinases. Pre-treatment with chondroitin sulphate (CS) and chondroitinase also significantly decreased UPEC adherence to RT4 cells. This study may shed light on a common pathogenicity mechanism involving the organisation of HSPGs by tetraspanins. In summary, although we determined that the bladder cell lines were not suitable to investigate the role of uroplakins in UPEC adhesion, we demonstrated roles for CD9 and cell surface proteoglycans in this interaction. Agents that target these may be useful in treating/preventing UTIs.

Keywords: UTIs, tspan, uroplakins, CD9

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Authors: John Kabuba, Hilary Rutto

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Ion exchange is one of the methods used to remove heavy metal such as copper and cobalt from wastewaters. Parameters affecting the ion-exchange of copper and cobalt aqueous solutions using clinoptilolite are the objectives of this study. Synthetic solutions were prepared with the concentration of 0.02M, 0.06M and 0.1M. The cobalt solution was maintained to 0.02M while varying the copper solution to the above stated concentrations. The clinoptilolite was activated with HCl and H2SO4 for removal efficiency. The pHs of the solutions were found to be acidic hence enhancing the copper and cobalt removal. The natural clinoptilolite performance was also found to be lower compared to the HCl and H2SO4 activated one for the copper removal ranging from 68% to 78% of Cu2+ uptake with the natural clinoptilolite to 66% to 51% with HCl and H2SO4 respectively. It was found that the activated clinoptilolite removed more copper and cobalt than the natural one and found that the electronegativity of the metal plays a role in the metal removal and the clinoptilolite selectivity.

Keywords: clinoptilolite, cobalt and copper, ion-exchange, mass dosage, pH

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Authors: Chiung-Chin Huang, Jui-Yen Lin, Yao-Hui Huang

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Among current techniques of boron removal from wastewater with high boron concentration, chemical oxo-precipitation (COP) is one of the promising methods due to its milder condition. COP uses H2O2 to transform boric acid to perborates which can easily precipitate with barium ions at room temperature. However, the generation of the waste sludge that requires sludge/water separation and sludge dewatering is troublesome. This work presents an innovative technology which integrates chemical oxo-precipitation (COP) with fluidized-bed homogeneous granulation (FBHG) to reclaim boron as homogeneous perborate particles. By conducting COP in a fluidized-bed reactor, the barium perborate can be granulated to form homogeneous particles (>1.0 mm) with low water content (< 10%). Under the suitable condition, more than 70% of boron can be recovered from 600 ppm of boron solution and the residual boron is lower than 100 ppm.

Keywords: barium, perborate, chemical oxo-precipitation, boron removal, fluidized-bed, granulation

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Authors: Arinze Ezieke, Antonio Serrano, William Clarke, Denys Villa-Gomez

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Berry cultivation results in discharge of high organic strength putrescible solid waste which potentially contributes to environmental degradation, making it imperative to assess options for its complete management. Anaerobic digestion (AD) could be an ideal option when the target is energy generation; however, due to berry fruit characteristics high carbohydrate composition, the technology could be limited by its high alkalinity requirement which suggests dosing of additives such as buffers and trace elements supplement. Overcoming this limitation in an economically viable way could entail replacement of synthetic additives with recycled by-product waste. Consequently, ash from co-smouldering of high COD characteristic AD digestate and coco-coir could be a promising material to be used to enhance the AD of berry fruit waste, given its characteristic high pH, alkalinity and metal concentrations which is typical of synthetic additives. Therefore, the aim of the research was to evaluate the stability and process performance from the AD of BFW when ash from co-smoldered digestate and coir are supplemented as alkalinity and trace elements (TEs) source. Series of batch experiments were performed to ascertain the necessity for alkalinity addition and to see whether the alkalinity and metals in the co-smouldered digestate ash can provide the necessary buffer and TEs for AD of berry fruit waste. Triplicate assays were performed in batch systems following I/S of 2 (in VS), using serum bottles (160 mL) sealed and placed in a heated room (35±0.5 °C), after creating anaerobic conditions. Control experiment contained inoculum and substrates only, and inoculum, substrate and NaHCO3 for optimal total alkalinity concentration and TEs assays, respectively. Total alkalinity concentration refers to alkalinity of inoculum and the additives. The alkalinity and TE potential of the ash were evaluated by supplementing ash (22.574 g/kg) of equivalent total alkalinity concentration to that of the pre-determined optimal from NaHCO3, and by dosing ash (0.012 – 7.574 g/kg) of varying concentrations of specific essential TEs (Co, Fe, Ni, Se), respectively. The result showed a stable process at all examined conditions. Supplementation of 745 mg/L CaCO3 NaHCO3 resulted to an optimum TAC of 2000 mg/L CaCO3. Equivalent ash supplementation of 22.574 g/kg allowed the achievement of this pre-determined optimum total alkalinity concentration, resulting to a stable process with a 92% increase in the methane production rate (323 versus 168 mL CH4/ (gVS.d)), but a 36% reduction in the cumulative methane production (103 versus 161 mL CH4/gVS). Addition of ashes at incremental dosage as TEs source resulted to a reduction in the Cumulative methane production, with the highest dosage of 7.574 g/kg having the highest effect of -23.5%; however, the seemingly immediate bioavailability of TE at this high dosage allowed for a +15% increase in the methane production rate. With an increased methane production rate, the results demonstrated that the ash at high dosages could be an effective supplementary material for either a buffered or none buffered berry fruit waste AD system.

Keywords: anaerobic digestion, alkalinity, co-smoldered digestate ash, trace elements

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Authors: Lingfeng Wang, Zhipeng Chen, Shuang Qiu, Shijian Ge

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The effects of wastewater, with four different nutrient loadings, from synthetic centrate on biomass production of Chlorella vulgaris, nutrient removal, microalgal settling, and lipid production were investigated in photobioreactors under both batches and, subsequently, semi-continuous operations. At higher centrate concentration factors (17.2% and 36.2%), hydraulic retention time and pH adjustments could be employed to sustain acceptable microalgal growth rates and wastewater treatment. Similar nutrient removals efficiencies (>95%) and biomass production (0.42-0.51 g/L) were observed for the four centrate concentrations. Both the lipid productivity and lipid content decreased with increasing nutrient loading in the wastewater. The results also demonstrated that the mass ratio of carbohydrate to protein could provide a good indication of microalgal settling performance, rather than sole component composition or total extracellular polymeric substances.

Keywords: lipid production, microalgae, nutrient removal, wastewater

Procedia PDF Downloads 241

Authors: Silvia Moreno, Banu Iyisan, Hannes Gumz, Brigitte Voit, Dietmar Appelhans

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Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. In addition, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: multifunctionalized, pH stimulus, controllable release, cellular uptake

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Authors: Dinara Ikramova, Karin A. Hing, Simon C. F. Rawlinson

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Silicate-substituted hydroxyapatite (SiHA) has been shown to enhance bone regeneration in vivo compared with phase pure stoichiometric hydroxyapatite. Evidence suggests that substrate chemistry dependent formation of a permissive protein layer on the surface of synthetic bone graft substitute materials is key for bioactivity and cell attachment. However, little information is available on whether the substrate chemistry may affect cell migration and recruitment. The aim of this study is to investigate whether or not human Mesenchymal Stem Cells (hMSCs) exhibit a chemotactic response to SiHA porous granules and if it can be linked to either the ion exchange or protein sequestering and enrichment on the surface of the material. 150mg of SiHA granules with 80% total porosity and 20% strut porosity were incubated in 1ml of either Serum Free Media (SFM) or 10% Serum Containing Media (SCM) under static cell culture conditions (37°C, 5% CO2) in absence of cells. Protein sequestering and exchange of calcium, phosphate and silicate ions were analysed at 0.5, 1, 2, 4, 8, 16 and 24 hours with n=12 per time point. Migration of hMSCs in the presence of 150mg of SiHA granules was assessed over 24 hours using a modified transwell migration system in either SFM or SCM (n=6) with 30% serum containing media acting as a positive control. At 24 hours protein sequestering and ionic exchange were analysed, and the number of cells was quantified using a high throughput confocal microscope (IN Cell Analyser 6000). In acellular condition, both calcium and phosphate ion concentrations in media showed a decrease at 24 hours which was greater in SFM than in SCM. This suggests possible formation and precipitation of a bone like apatite on the surface of SiHA. Reduction in this activity observed in SCM indicates that the presence of serum proteins is interfering with the ion exchange at the material and media interface. Adsorbed protein levels showed fluctuation over time followed by sharp decrease at 24 hours, suggesting a possible protein rearrangement on the surface of the material. The ion analysis performed on SFM and SCM after 24-hour incubation with cells in the presence of granules showed a greater reduction in phosphate concentration in both SFM and SCM compared to phosphate levels in acellular condition. Silicate concentration in SCM increased from 1.6mM (absence of cells) to 5.1mM (presence of cells). This indicates that the cells are promoting the uptake of phosphate and release of silicate ions. No significant change was seen in levels of adsorbed proteins in the presence and absence of cells. Further analysis is required to determine whether the species of these proteins change over time. The analysis of cell migration after 24-hour incubation showed more cells migrating towards the granules, 12.7% in SFM and 8.3% in SCM, than in positive control, 4.5% in SFM and 3.6% in SCM respectively. These results suggest that SiHA has a chemotactic activity independent of serum proteins. A property which has not previously been demonstrated for a synthetic bone graft material.

Keywords: cell migration, hMSCs, SiHA, transwell migration system

Procedia PDF Downloads 132

Authors: Anésio de Leles Ferreira Filho, Wesley Rodrigues de Oliveira, Jéssica Santoro Gonçalves, Jorge Andrés Cormane Angarita

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The increase in electric power demand in face of environmental issues has intensified the participation of renewable energy sources such as photovoltaics, in the energy matrix of various countries. Due to their operational characteristics, they can generate time-varying harmonic and inter-harmonic distortions. For this reason, the application of methods of measurement based on traditional Fourier analysis, as proposed by IEC 61000-4-7, can provide inaccurate results. Considering the aspects mentioned herein, came the idea of the development of this work which aims to present the results of a comparative evaluation between a methodology arising from the combination of the Prony method with the Kalman filter and another method based on the IEC 61000-4-30 and IEC 61000-4-7 standards. Employed in this study were synthetic signals and data acquired through measurements in a 50kWp photovoltaic installation.

Keywords: harmonics, inter-harmonics, iec61000-4-7, parametric estimators, photovoltaic generation

Procedia PDF Downloads 487

Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Frazer Kirk, Rohen Skiba, Pankaj Saxena

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The natural history of the QAV is poorly understood due to the exceeding rarity of the condition. Incidence rates vary between 0.00028-1%. Classically patients present with Aortic Regurgitation (AR) between 40-60 years of age experiencing palpitations, chest pain, or heart failure. (1, 2) Echocardiography is the mainstay of diagnosis for this condition; however, given the rarity of this condition, it can easily be overlooked, as demonstrated here. The case report that follows serves as a reminder of the condition to reduce the innate cognitive bias to overlook the diagnosis due to the availability heuristic. Intraoperative photography, echocardiographic and magnetic resonance imaging from this case for reference to demonstrate that while the diagnosis of Aortic regurgitation was recognized early, the valve morphology was underappreciated.

Keywords: quadricuspid aortic valve, cardiac surgery, echocardiography, congenital

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

Procedia PDF Downloads 346

Authors: Jurij Tasinkiewicz

Abstract:

The aim of this work is to present a theoretical analysis of a 2D ultrasound transducer comprised of crossed arrays of metal strips placed on both sides of thin piezoelectric layer (a). Such a structure is capable of electronic beam-steering of generated wave beam both in elevation and azimuth. In this paper, a semi-analytical model of the considered transducer is developed. It is based on generalization of the well-known BIS-expansion method. Specifically, applying the electrostatic approximation, the electric field components on the surface of the layer are expanded into fast converging series of double periodic spatial harmonics with corresponding amplitudes represented by the properly chosen Legendre polynomials. The problem is reduced to numerical solving of certain system of linear equations for unknown expansion coefficients.

Keywords: beamforming, transducer array, BIS-expansion, piezoelectric layer

Procedia PDF Downloads 423