Search results for: feature detection

Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: Tania Vasquez Mata, Luis A. Herrera, Cristian Arriaga Canon

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Background: Locally advanced breast cancer of the luminal B phenotype, poses challenges due to its variable response to neoadjuvant chemotherapy. A predictive biomarker is needed to identify patients who will not respond to treatment, allowing for alternative therapies. This study aims to validate the use of the lncRNA GATA3-AS1, as a predictive biomarker using RNA in situ hybridization. Research aim: The aim of this study is to determine if GATA3-AS1 can serve as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Methodology: The study utilizes RNA in situ hybridization with predesigned probes for GATA3-AS1 on Formalin-Fixed Paraffin-Embedded tissue sections. The samples underwent pretreatment and protease treatment to enable probe penetration. Chromogenic detection and signal evaluation were performed using specific criteria. Findings: Patients who did not respond to neoadjuvant chemotherapy showed a 3+ score for GATA3-AS1, while those who had a complete response had a 1+ score. Theoretical importance: This study demonstrates the potential clinical utility of GATA3-AS1 as a biomarker for resistance to neoadjuvant chemotherapy. Identifying non-responders early on can help avoid unnecessary treatment and explore alternative therapy options. Data collection and analysis procedures: Tissue samples from patients with locally advanced luminal B breast cancer were collected and processed using RNA in situ hybridization. Signal evaluation was conducted under a microscope, and scoring was based on specific criteria. Questions addressed: Can GATA3-AS1 serve as a predictive biomarker for neoadjuvant chemotherapy response in locally advanced luminal B breast cancer? Conclusion: The lncRNA GATA3-AS1 can be used as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Its identification through RNA in situ hybridization of tissue obtained from the initial biopsy can aid in treatment decision-making.

Keywords: biomarkers, breast neoplasms, genetics, neoadjuvant therapy, tumor

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Authors: Rasha Ahmadi

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In December 2019, a coronavirus, currently identified as SARS-CoV-2, produced a series of acute atypical respiratory illnesses in Wuhan, Hubei Province, China. The sickness induced by this virus was named COVID-19. The virus is transmittable between humans and has caused pandemics worldwide. The number of death tolls continues to climb and a huge number of countries have been obliged to perform social isolation and lockdown. Lack of focused therapy continues to be a problem. Epidemiological research showed that senior patients were more susceptible to severe diseases, whereas children tend to have milder symptoms. In this study, we focus on other possible side effects of COVID-19 and more detailed treatment strategies. Using bioinformatics analysis, we first isolated the gene expression profile of patients with severe COVID-19 from the GEO database. Patients' blood samples were used in the GSE183071 dataset. We then categorized the genes with high and low expression. In the next step, we uploaded the genes separately to the Enrichr database and evaluated our data for signs and symptoms as well as related medication regimens. The results showed that 138 genes with high expression and 108 genes with low expression were observed differentially in the severe COVID-19 VS control group. Symptoms and diseases such as embolism and thrombosis of the abdominal aorta, ankylosing spondylitis, suicidal ideation or attempt, regional enteritis were observed in genes with high expression and in genes with low expression of acute and subacute forms of ischemic heart, CNS infection and poliomyelitis, synovitis and tenosynovitis. Following the detection of diseases and possible signs and symptoms, Carmustine, Bithionol, Leflunomide were evaluated more significantly for high-expression genes and Chlorambucil, Ifosfamide, Hydroxyurea, Bisphenol for low-expression genes. In general, examining the different and invisible aspects of COVID-19 and identifying possible treatments can help us significantly in the emergency and hospitalization of patients.

Keywords: phenotypes, drug regimens, gene expression profiles, bioinformatics analysis, severe COVID-19

Procedia PDF Downloads 142

Authors: Eman Ghoneim, Amr S. Fahil

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Many regions in Egypt are facing a reduction in crop productivity due to environmental degradation. One factor of crop deterioration includes the unsustainable drainage of surface water, leading to salinized soil conditions. Egypt has exerted time and effort to identify solutions to mitigate the surface water drawdown problem and its resulting effects by exploring renewable and sustainable sources of energy. Siwa Oasis represents one of the most favorable regions in Egypt for geothermal exploitation since it hosts an evident cluster of superficial thermal springs. Some of these hot springs are characterized by high surface temperatures and bottom hole temperatures (BHT) ranging between 20°C to 40 °C and 21 °C to 121.7°C, respectively. The depth to the Precambrian basement rock is commonly greater than 440 m, ranging from 440 m to 4724.4 m. It is this feature that makes the locality of Siwa Oasis sufficient for industrial processes and geothermal power production. In this study, BHT data from 27 deep oil wells were processed by applying the widely used Horner and Gulf of Mexico correction methods to obtain formation temperatures. BHT, commonly used in geothermal studies, remains the most abundant and readily available data source for subsurface temperature information. Outcomes of the present work indicated a geothermal gradient ranging from 18 to 42 °C/km, a heat flow ranging from 24.7 to 111.3 m.W.k⁻¹, and a thermal conductivity of 1.3–2.65 W.m⁻¹.k⁻¹. Remote sensing thermal infrared, topographic, geologic, and geothermal data were utilized to provide geothermal potential maps for the Siwa Oasis. Important physiographic variables (including surface elevation, lineament density, drainage density), geological and geophysical parameters (including land surface temperature, depth to basement, bottom hole temperature, magnetic, geothermal gradient, heat flow, thermal conductivity, and main rock units) were incorporated into GIS to produce a geothermal potential map (GTP) for the Siwa Oasis region. The model revealed that both the northeastern and southeastern sections of the study region are of high geothermal potential. The present work showed that combining bottom-hole temperature measurements and remote sensing data with the selected geospatial methodologies is a useful tool for geothermal prospecting in geologically and tectonically comparable settings in Egypt and East Africa. This work has implications for identifying sustainable resources needed to support food production and renewable energy resources.

Keywords: BHT, geothermal potential map, geothermal gradient, heat flow, thermal conductivity, satellite imagery, GIS

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 137

Authors: A. A. Md. Ryhan Uddin, Swarup Das, Rajesh Barua, Joheb Hasan, Rashedul Islam

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Background: The herbicide has toxicological importance because some of them are associated with high mortality rates due to respiratory failure. Organophosphate poisoning (OPC) & Paraquat self-poisoning is a major clinical and public health problems in low and middle-income countries across much of South Asia. Paraquat was not used as a common suicidal agent previously in Bangladesh. We report a case of 15 years old female admitted to the ER with a history of nausea & vomiting after ingestion of an unknown substance in a suicidal attempt, later identified as mixed poisoning- OPC & Paraquat. She was initially asymptomatic but later developed renal shutdown & lung injuries as well as pneumothorax, referred to as Daisley Barton Syndrome. Objective: This case report aims to alert spontaneous pneumothorax in mixed poisoning on uncommon forms of presentation. Pneumothorax in a patient with paraquat poisoning is a less unusual but underdiagnosed finding. It has a high index of early mortality. Case history: The patient's attendant complained about nausea followed by vomiting, which was nonprojectile & contains undigested food materials first, then gastric juice later. After a few hours, she also complains of urinary retention. Her family members treated her with some home remedies for her initial symptoms, but all attempts failed. After admission, the patient was initially asymptomatic. Through repeated history taking, her attendant showed a bottle of OPC in liquid form, which they suspected that she may have ingested some of the liquid from that bottle accidentally or attempted Suicide. So, management started for OPC poisoning. She responded well initially, but on 4th day of admission, the patient's condition became deteriorating. After the workout with the family member, 2nd bottle of Pesticide was discovered, which was Paraquat. Conclusion: Physicians should be aware of the symptoms of mixed poisoning and the timely use of urine dithionate testing for early detection and treatment. Pneumothorax is an early predictor of mortality in patients with paraquat poisoning.

Keywords: pneumothorax, suicide, dithionate, OPC, herbicide

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Authors: M. Brockes, S. Beck, A. Sigaroudi, C. Brockes

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Over the last years, telemedicine and telemonitoring have become a popular way of treatment, especially in other chronic diseases. Therefore this type of treatment methodology was also implemented in interstitial lung disease (ILD) patients. In January 2024, a new service for patients with interstitial lung disease (ILD) treated with Nintedanib was established, which contains daily telemonitoring (home spirometry, pulse oximetry, and daily level of activity), daily evaluation of parameters as well as a telemedical availability answered by doctors and telemedical specialists throughout 365 days per year. The main motivational points of this service are the early detection of first signs of exacerbations and/or other symptoms/complications as well as easier access to healthcare professionals. The evaluation of the patient’s quality of life and the subjective feeling of safetyness was measured through patient reported experience measurements (PREMs) and patient reported outcome measurements (PROMs). Patients were introduced to the telemedical and telemonitoring service six-months ago. Within this period, every sixty days, the questionnaires were conducted by the scientific employees. Due to the unlimited time frame of the long-term service the evaluation is not completed. The first analysis of patient reported experience measurements (PREMs) and patient reported outcome measurements (PROMs) have shown an increased positive effect on the patients' quality of life as well as an increased positive effect on the subjective feeling of safety at home, plus a reduction and avoidance of secondary damages (e.g., exacerbations, deterioration of typical interstitial lung disease ILD symptoms and pharmaceutical side effects). The first results have shown a tendency that the telemedical treatment combined with telemonitoring at home and the encouragement of patients to actively participate in their healthcare has a positive effect on the patient’s overall well-being and could be implemented as a complementation of the traditional standard of care.

Keywords: avoidance of secondary damages, interstitial lung disease, telemedicine and telemonitoring, subjective feeling of safety

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Yvonne Nanaama Brew, Bismark Jampim Abrokwah

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Children with disabilities in Ghana are not routinely registered, and this can imply that they may be neglected in national policy planning since global estimates may not be near the exact numbers. Although there are some studies with reports on the prevalence of disability among children in Ghana, reliable information on the prevalence, types of disability in children, and children who die with disabilities in the Greater Accra region are lacking. The current study seeks to investigate the incidence of disability among children two to fourteen years at selected districts in the Greater Accra region of Ghana. A cross-sectional design is adapted with a quantitative method for this study. Parents with disabled children who access child welfare clinics at the Greater Accra regional hospital, Maamobi hospital, Ga west, and Ga south district hospitals will be selected through purposive sampling for the study. An adapted UNICEF structured Ten Questions will be used to collect relevant data about participants. The responses to the questions will be either 'Yes' or 'No'. Parents with children who answer 'Yes' to a disability and purposively sampled parents with children who answer 'No' to disability will be invited to Child Health Clinic at the Greater Accra regional hospital for a free clinical assessment. Data will be entered into Microsoft Office Excel 2013 and imported into STATA version 15 for analysis. The study is expected to provide reliable disaggregated data on less than fourteen years of children with disabilities in the Greater Accra region. The findings and recommendations of the study will demonstrate the importance of early detection of disability and facilitate more quality and holistic planning of appropriate programmes that best safeguard the rights of children with disabilities in Ghana. It will help in policy and decision-making on children less than fourteen years with disabilities in Ghana. Also, findings will be useful for health facilities in Ghana to plan services for disabled children. Finally, the study is expected to add to the guides for the National Council of Persons with Disabilities to fulfill its legal mandate for disabled persons in Ghana.

Keywords: prevalence, disability, children, Ghana

Procedia PDF Downloads 132

Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Takaharu Hirai, Yuta Mitobe, Hiromi Hirai

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Introduction: Eating disorders (ED) are serious psychiatric disorders that affect individuals, especially adolescents. It has been suggested that nonclinical ED-like characteristics are related to sleep problems. However, studies exploring the association between potential ED and sleep disorders have primarily been conducted in Europe and the United States. We conducted a survey of Japanese adolescents to investigate this claim. Method: In this cross-sectional study, 398 school-aged adolescents, aged 12–18 years old, matched for gender ratio, responded to a self-administered questionnaire survey. We used the Eating Attitudes Test-26 (EAT-26) and the Athens Insomnia Scale (AIS) to measure potential ED and sleep problems, respectively. In this study, participants with an EAT-26 total score of 0–19 points were classified as non-ED, while those with scores of 20 points or higher were classified as potential ED. Result: Of the 398 participants, 17 (4.3%) had an EAT-26 total score of 20 or higher. Among boys, the rate was 6 of 199 participants (3%), and among girls, the rate was 11 of 182 participants (6%). There were 89 participants (22.4%) with an AIS score of 6 points or higher, of which 36 (17.6%) were boys, and 53 (27.5%) were girls. Adolescents with potential ED had significantly higher rates of daytime sleep problems than those without ED. Further, while examining the types of sleep problems, adolescents with potential ED had greater problems with a sense of well-being and physical and mental functioning during the day. In contrast, no significant associations were found between potential ED and sleep initiation, awakenings during the night, early morning awakening, total sleep duration, or overall quality of sleep. Finally, nocturnal and daytime sleep scores were significantly associated with dieting, bulimia, and oral control EAT-26 sub-scores. Discussion: While Japanese adolescents with possible ED do not experience nighttime sleep problems, they do experience problems related to well-being and mental and physical functioning, which are indicators of daytime sleep problems. This may assist with early detection of disordered eating in adolescents. The study suggested that professionals working towards adolescent mental health issues need an approach that comprehensively integrates both sleep problems and potential ED.

Keywords: adolescents, potential eating disorders, sleep problems, eating attitudes test-26

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Authors: S. Hatamikia, A. Biguri, H. Furtado, G. Kronreif, J. Kettenbach, W. Birkfellner

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Nowadays, three dimensional Cone Beam CT (CBCT) has turned into a widespread clinical routine imaging modality for interventional radiology. In conventional CBCT, a circular sourcedetector trajectory is used to acquire a high number of 2D projections in order to reconstruct a 3D volume. However, the accumulated radiation dose due to the repetitive use of CBCT needed for the intraoperative procedure as well as daily pretreatment patient alignment for radiotherapy has become a concern. It is of great importance for both health care providers and patients to decrease the amount of radiation dose required for these interventional images. Thus, it is desirable to find some optimized source-detector trajectories with the reduced number of projections which could therefore lead to dose reduction. In this study we investigate some source-detector trajectories with the optimal arbitrary orientation in the way to maximize performance of the reconstructed image at particular regions of interest. To achieve this approach, we developed a box phantom consisting several small target polytetrafluoroethylene spheres at regular distances through the entire phantom. Each of these spheres serves as a target inside a particular region of interest. We use the 3D Point Spread Function (PSF) as a measure to evaluate the performance of the reconstructed image. We measured the spatial variance in terms of Full-Width-Half-Maximum (FWHM) of the local PSFs each related to a particular target. The lower value of FWHM shows the better spatial resolution of reconstruction results at the target area. One important feature of interventional radiology is that we have very well-known imaging targets as a prior knowledge of patient anatomy (e.g. preoperative CT) is usually available for interventional imaging. Therefore, we use a CT scan from the box phantom as the prior knowledge and consider that as the digital phantom in our simulations to find the optimal trajectory for a specific target. Based on the simulation phase we have the optimal trajectory which can be then applied on the device in real situation. We consider a Philips Allura FD20 Xper C-arm geometry to perform the simulations and real data acquisition. Our experimental results based on both simulation and real data show our proposed optimization scheme has the capacity to find optimized trajectories with minimal number of projections in order to localize the targets. Our results show the proposed optimized trajectories are able to localize the targets as good as a standard circular trajectory while using just 1/3 number of projections. Conclusion: We demonstrate that applying a minimal dedicated set of projections with optimized orientations is sufficient to localize targets, may minimize radiation.

Keywords: CBCT, C-arm, reconstruction, trajectory optimization

Procedia PDF Downloads 132

Authors: Ana Hol

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We live in a constantly changing environment where technology has become an integral component of our day to day life. We rely heavily on mobile devices, we search for data via web, we utilise smart home sensors to create the most suited ambiences and we utilise applications to shop, research, communicate and share data. Heavy reliance on technology therefore is creating new connections between STEM (Science, Technology, Engineering and Mathematics) fields which in turn rises a question of what the STEM education of the future should be like? This study was based on the reviews of the six Australian Information Systems students who undertook an international study tour to India where they were given an opportunity to network, communicate and meet local students, staff and business representatives and from them learn about the local business implementations, local customs and regulations. Research identifies that if we are to continue to implement and utilise electronic devices on the global scale, such as for example implement smart cars that can smoothly cross borders, we will need the workforce that will have the knowledge about the cars themselves, their parts, roads and transport networks, road rules, road sensors, road monitoring technologies, graphical user interfaces, movement detection systems as well as day to day operations, legal rules and regulations of each region and country, insurance policies, policing and processes so that the wide array of sensors can be controlled across country’s borders. In conclusion, it can be noted that allowing students to learn about the local conditions, roads, operations, business processes, customs and values in different countries is giving students a cutting edge advantage as such knowledge cannot be transferred via electronic sources alone. However once understanding of each problem or project is established, multidisciplinary innovative STEM projects can be smoothly conducted.

Keywords: STEM, curiosity, innovation, advancements

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Authors: Taghi-Zada T. G., Hajiyeva U. K.

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Recent years, due to the development of tourism, migration and globalization, brucellosis has spread to non-endemic regions of the country in Azerbaijan and this disease has become one of the main priority areas of medicine. In our daily practice, we face patients with specific symptoms of brucellosis and also infected with this disease but misdiagnosed. It should also be noted that the symptoms and signs of brucellosis are very diverse, and since none of these signs are specific enough to confirm the diagnosis, it creates difficulties in its timely detection and diagnosis. The main purpose of the work. Therefore, the main goal of the work is to investigate the cases of delay in making the correct diagnosis in children with brucellosis and the mistakes in this matter. Material and method. 50 children with brucellosis between the ages of 6 months and 17 years were examined. The medical history and anamnesis of these children were collected, clinical-instrumental examination, and serological tests for brucellosis were performed. Patients were divided into 2 groups, taking into account the specificity of symptoms and the timely diagnosis Results. Group I included 15 (40%) children aged 3-17 years. The main specific symptoms of brucellosis in these patients; persistent or long-term fever, night sweats, arthralgia were observed. In addition to specific symptoms, anamnesis and a specific serological test confirmed the diagnosis of brucellosis. 30 (60%) patients included in group II were misdiagnosed. 3 patients (up to 1 year) were diagnosed with sepsis, 6 with acute rheumatic fever, 10 with systemic diseases, 2 with tuberculosis, 5 with Covid 19, and 4 with unspecified fever. However, we included serological tests. detailed examination revealed the presence of brucellosis in them. As can be seen, compared to group I (40%) children included in group II (60%) In modern times, brucellosis manifests itself with its own characteristics, that is, imitating a number of other diseases, which has led to wrong diagnosis. Conclusion. Thus, the lack of specificity of clinical symptoms during brucellosis in children makes diagnosis difficult, causes mistakes and non-recognition of the disease. With this in mind, physicians in predominantly endemic and even sub-endemic areas should remain vigilant about this disease and consider brucellosis in the differential diagnosis of almost every unexplained medical problem until proven otherwise.

Keywords: brucellosis, pediatrics, diagnostics, serological tests

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Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

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Authors: Shilpee Jain, Sachin Latiyan, Kaushik Suneet

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Unlike traditional robots, medical microbots are not only smaller in size, but they also possess various unique properties, for example, biocompatibility, stability in the biological fluids, navigation opposite to the bloodstream, wireless control over locomotion, etc. The idea behind their usage in the medical field was to build a minimally invasive method for addressing the post-operative complications, including longer recovery time, infection eruption and pain. Herein, the present study demonstrates the fabrication of dual nature magneto-conducting Fe3O4 magnetic nanoparticles (MNPs) and SU8 derived carbon-based Janus microbots for the efficient intracellular delivery of biomolecules. The low aspect ratio with feature size 2-5 μm microbots were fabricated by using a photolithography technique. These microbots were pyrolyzed at 900°C, which converts SU8 into amorphous carbon. The pyrolyzed microbots have dual properties, i.e., the half part is magneto-conducting and another half is only conducting for sufficing the therapeutic payloads efficiently with the application of external electric/magnetic field stimulations. For the efficient intracellular delivery of the microbots, the size and aspect ratio plays a significant role. However, on a smaller scale, the proper control over movement is difficult to achieve. The dual nature of Janus microbots allowed to control its maneuverability in the complex fluids using external electric as well as the magnetic field. Interestingly, Janus microbots move faster with the application of an external electric field (44 µm/s) as compared to the magnetic field (18 µm/s) application. Furthermore, these Janus microbots exhibit auto-fluorescence behavior that will help to track their pathway during navigation. Typically, the use of MNPs in the microdevices enhances the tendency to agglomerate. However, the incorporation of Fe₃O₄ MNPs in the pyrolyzed carbon reduces the chances of agglomeration of the microbots. The biocompatibility of the medical microbots, which is the essential property of any biosystems, was determined in vitro using HeLa cells. The microbots were found to compatible with HeLa cells. Additionally, the intracellular uptake of microbots was higher in the presence of an external electric field as compared to without electric field stimulation. In summary, the cytocompatible Janus microbots were fabricated successfully. They are stable in the biological fluids, wireless controllable navigation with the help of a few Guess external magnetic fields, their movement can be tracked because of autofluorescence behavior, they are less susceptible to agglomeration and higher cellular uptake could be achieved with the application of the external electric field. Thus, these carriers could offer a versatile platform to suffice the therapeutic payloads under wireless actuation.

Keywords: amorphous carbon, electric/magnetic stimulations, Janus microbots, magnetic nanoparticles, minimally invasive procedures

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Authors: A. Kachmazova, A. Shadiev, Y. Teterin, P. Yartcev

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Introduction: Biliary calculi disease (LCS) still occupies the leading position among urgent diseases of the abdominal cavity, manifesting itself from asymptomatic course to life-threatening states. Nowadays arsenal of diagnostic methods for choledocholithiasis is quite wide: ultrasound, hepatobiliscintigraphy (HBSG), magnetic resonance imaging (MRI), endoscopic retrograde cholangiography (ERCP). Among them, transabdominal ultrasound (TA ultrasound) is the most accessible and routine diagnostic method. Nowadays ERCG is the "gold" standard in diagnosis and one-stage treatment of biliary tract obstruction. However, transpapillary techniques are accompanied by serious postoperative complications (postmanipulative pancreatitis (3-5%), endoscopic papillosphincterotomy bleeding (2%), cholangitis (1%)), the lethality being 0.4%. GBSG and MRI are also quite informative methods in the diagnosis of choledocholithiasis. Small size of concrements, their localization in intrapancreatic and retroduodenal part of common bile duct significantly reduces informativity of all diagnostic methods described above, that demands additional studying of this problem. Materials and Methods: 890 patients with the diagnosis of cholelithiasis (calculous cholecystitis) were admitted to the Sklifosovsky Scientific Research Institute of Hospital Medicine in the period from August, 2020 to June, 2021. Of them 115 people with mechanical jaundice caused by concrements in bile ducts. Results: Final EUS diagnosis was made in all patients (100,0%). In all patients in whom choledocholithiasis diagnosis was revealed or confirmed after EUS, ERCP was performed urgently (within two days from the moment of its detection) as the X-ray operation room was provided; it confirmed the presence of concrements. All stones were removed by lithoextraction using Dormia basket. The postoperative period in these patients had no complications. Conclusions: EUS is the most informative and safe diagnostic method, which allows to detect choledocholithiasis in patients with discrepancies between clinical-laboratory and instrumental methods of diagnosis in shortest time, that in its turn will help to decide promptly on the further tactics of patient treatment. We consider it reasonable to include EUS in the diagnostic algorithm for choledocholithiasis. Disclosure: Nothing to disclose.

Keywords: endoscopic ultrasonography, choledocholithiasis, common bile duct, concrement, ERCP

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Authors: Nkechi V. Osuji

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The use of blockchain to address the issue of climate change is increasingly a discourse among countries, industries, and stakeholders. For a long time, the European Union (EU) has been combating the issue of climate action in industries through sustainability programs. One of such programs is the EU monitoring reporting and verification (MRV) program of the EU ETS. However, the system has some key challenges and areas for improvement, which makes it inefficient. The main objective of the research is to look at how blockchain can be used to improve the inefficiency of the EU ETS program for the Danish energy industry with a focus on its monitoring and reporting framework. Applying empirical data from 13 semi-structured expert interviews, three case studies, and literature reviews, three outcomes are presented in the study. The first is on the current conditions and challenges of monitoring and reporting CO₂ emission trading. The second is putting into consideration if blockchain is the right fit to solve these challenges and how. The third stage looks at the factors that might affect the implementation of such a system and provides recommendations to mitigate these challenges. The first stage of the findings reveals that the monitoring and reporting of CO₂ emissions is a mandatory requirement by law for all energy operators under the EU ETS program. However, most energy operators are non-compliant with the program in reality, which creates a gap and causes challenges in the monitoring and reporting of CO₂ emission trading. Other challenges the study found out are the lack of transparency, lack of standardization in CO₂ accounting, and the issue of double-counting in the current system. The second stage of the research was guided by three case studies and requirement engineering (RE) to explore these identified challenges and if blockchain is the right fit to address them. This stage of the research addressed the main research question: how can blockchain be used for monitoring and reporting CO₂ emission trading in the energy industry. Through analysis of the study data, the researcher developed a conceptual private permissioned Hyperledger blockchain and elucidated on how it can address the identified challenges. Particularly, the smart contract of blockchain was highlighted as a key feature. This is because of its ability to automate, be immutable, and digitally enforce negotiations without a middleman. These characteristics are unique in solving the issue of compliance, transparency, standardization, and double counting identified. The third stage of the research presents technological constraints and a high level of stakeholder collaboration as major factors that might affect the implementation of the proposed system. The proposed conceptual model requires high-level integration with other technologies such as the Internet of Things (IoT) and machine learning. Therefore, the study encourages future research in these areas. This is because blockchain is continually evolving its technology capabilities. As such, it remains a topic of interest in research and development for addressing climate change. Such a study is a good contribution to creating sustainable practices to solve the global climate issue.

Keywords: blockchain, carbon emission trading, European Union emission trading system, monitoring and reporting

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Authors: Y. A. Prada, Fanny Guzman, Rafael Cabanzo, John J. Castillo, Enrique Mejia-Ospino

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In this work, we show the important results about of synthesis of photoluminiscents gold nanoclusters using a small peptide as template for biosensing applications. Interestingly, we design one peptide (NBC2854) homologue to conservative domain from 215 250 residue of a galactolectin protein which can recognize the proteophosphoglycans (PPG) from Leishmania. Peptide was synthetized by multiple solid phase synthesis using FMoc group methodology in acid medium. Finally, the peptide was purified by High-Performance Liquid Chromatography using a Vydac C-18 preparative column and the detection was at 215 nm using a Photo Diode Array detector. Molecular mass of this peptide was confirmed by MALDI-TOF and to verify the α-helix structure we use Circular Dichroism. By means of the methodology used we obtained a novel fluorescents gold nanoclusters (AuNC) using NBC2854 as a template. In this work, we described an easy and fast microsonic method for the synthesis of AuNC with ≈ 3.0 nm of hydrodynamic size and photoemission at 630 nm. The presence of cysteine residue in the C-terminal of the peptide allows the formation of Au-S bond which confers stability to Peptide-based gold nanoclusters. Interactions between the peptide and gold nanoclusters were confirmed by X-ray Photoemission and Raman Spectroscopy. Notably, from the ultrafine spectra shown in the MALDI-TOF analysis which containing only 3-7 KDa species was assigned to Au₈-₁₈[NBC2854]₂ clusters. Finally, we evaluated the Peptide-gold nanocluster as an optical biosensor based on fluorescence spectroscopy and the fluorescence signal of PPG (0.1 µg-mL⁻¹ to 1000 µg-mL⁻¹) was amplified at the same wavelength emission (≈ 630 nm). This can suggest that there is a strong interaction between PPG and Pep@AuNC, therefore, the increase of the fluorescence intensity can be related to the association mechanism that take place when the target molecule is sensing by the Pep@AuNC conjugate. Further spectroscopic studies are necessary to evaluate the fluorescence mechanism involve in the sensing of the PPG by the Pep@AuNC. To our best knowledge the fabrication of an optical biosensor based on Pep@AuNC for sensing biomolecules such as Proteophosphoglycans which are secreted in abundance by parasites Leishmania.

Keywords: biosensing, fluorescence, Leishmania, peptide-gold nanoclusters, proteophosphoglycans

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Authors: Chen Liu, Dawit Negussey

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EPS (Expanded Polystyrene) geofoam as light-weight material in geotechnical applications are made of pre-expanded resin beads that form fused cellular micro-structures. The strength and deformation properties of geofoam blocks are determined by unconfined compression of small test samples between rigid loading plates. Applied loads are presumed to be supported uniformly over the entire mating end areas. Predictions of field performance on the basis of such laboratory tests widely over-estimate actual post-construction settlements and exaggerate predictions of long-term creep deformations. This investigation examined the development of contact pressures at a large number of discrete points at low and large strain levels for different densities of geofoam. Development of pressure patterns for fine and coarse interface material textures as well as for molding skin and hot wire cut geofoam surfaces were examined. The lab testing showed that I-Scan tactile sensors are useful for detailed observation of contact pressures at a large number of discrete points simultaneously. At low strain level (1%), the lower density EPS block presents low variations in localized stress distribution compared to higher density EPS. At high strain level (10%), the dense geofoam reached the sensor cut-off limit. The imprint and pressure patterns for different interface textures can be distinguished with tactile sensing. The pressure sensing system can be used in many fields with real-time pressure detection. The research findings provide a better understanding of EPS geofoam behavior for improvement of design methods and performance prediction of critical infrastructures, which will be anticipated to guide future improvements in design and rapid construction of critical transportation infrastructures with geofoam in geotechnical applications.

Keywords: geofoam, pressure distribution, tactile pressure sensors, interface

Procedia PDF Downloads 173

Authors: Chalachew Gashu, Yoseph Kassa, Habtamu Geremew, Mengestie Mulugeta

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Background and Aims: Severe acute malnutrition remains a significant health challenge, particularly in low‐ and middle‐income countries. The aim of this study was to determine the survival time of under‐five children with severe acute malnutrition. Methods: A retrospective cohort study was conducted at a hospital, focusing on under‐five children with severe acute malnutrition. The study included 322 inpatients admitted to the Chiro hospital in Chiro, Ethiopia, between September 2019 and August 2020, whose data was obtained from medical records. Survival functions were analyzed using Kaplan‒Meier plots and log‐rank tests. The survival time of severe acute malnutrition was further analyzed using the Cox proportional hazards model and Bayesian parametric survival models, employing integrated nested Laplace approximation methods. Results: Among the 322 patients, 118 (36.6%) died as a result of severe acute malnutrition. The estimated median survival time for inpatients was found to be 2 weeks. Model selection criteria favored the Bayesian Weibull accelerated failure time model, which demonstrated that age, body temperature, pulse rate, nasogastric (NG) tube usage, hypoglycemia, anemia, diarrhea, dehydration, malaria, and pneumonia significantly influenced the survival time of severe acute malnutrition. Conclusions: This study revealed that children below 24 months, those with altered body temperature and pulse rate, NG tube usage, hypoglycemia, and comorbidities such as anemia, diarrhea, dehydration, malaria, and pneumonia had a shorter survival time when affected by severe acute malnutrition under the age of five. To reduce the death rate of children under 5 years of age, it is necessary to design community management for acute malnutrition to ensure early detection and improve access to and coverage for children who are malnourished.

Keywords: Bayesian analysis, severe acute malnutrition, survival data analysis, survival time

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Authors: Matthew D. Baffa

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Infrared thermography is a non-destructive test method used to estimate surface temperatures based on the amount of electromagnetic energy radiated by building envelope components. These surface temperatures are indicators of various qualitative building envelope deficiencies such as locations and extent of heat loss, thermal bridging, damaged or missing thermal insulation, air leakage, and moisture presence in roof, floor, and wall assemblies. Although infrared thermography is commonly used for qualitative deficiency detection in buildings, this study assesses its use as a quantitative method to estimate the overall thermal conductance value (U-value) of the exterior above-grade walls of a study home. The overall U-value of exterior above-grade walls in a home provides useful insight into the energy consumption and thermal comfort of a home. Three methodologies from the literature were employed to estimate the overall U-value by equating conductive heat loss through the exterior above-grade walls to the sum of convective and radiant heat losses of the walls. Outdoor infrared thermography field measurements of the exterior above-grade wall surface and reflective temperatures and emissivity values for various components of the exterior above-grade wall assemblies were carried out during winter months at the study home using a basic thermal imager device. The overall U-values estimated from each methodology from the literature using the recorded field measurements were compared to the nominal exterior above-grade wall overall U-value calculated from materials and dimensions detailed in architectural drawings of the study home. The nominal overall U-value was validated through calendarization and weather normalization of utility bills for the study home as well as various estimated heat loss quantities from a HOT2000 computer model of the study home and other methods. Under ideal environmental conditions, the estimated overall U-values deviated from the nominal overall U-value between ±2% to ±33%. This study suggests infrared thermography can estimate the overall U-value of exterior above-grade walls in low-rise residential homes with a fair amount of accuracy.

Keywords: emissivity, heat loss, infrared thermography, thermal conductance

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Authors: Chanya Jetsukontorn

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Dengue hemorrhagic fever is the most important Mosquito-borne disease and the major public health problem in Thailand. The most important vector is Aedes aegypti. Environmental factors such as temperature, relative humidity, and biting rate affect dengue virus infection. The most effective measure for prevention is controlling of vector mosquitoes. In addition, surveillance of field-caught mosquitoes is imperative for determining the natural vector and can provide an early warning sign at risk of transmission in an area. In this study, Aedes aegypti mosquitoes were collected in Amphur Muang, Phetchabun Province, Thailand. The mosquitoes were collected in the rainy season and the dry season both indoor and outdoor. During mosquito’s collection, the data of environmental factors such as temperature, humidity and breeding sites were observed and recorded. After identified to species, mosquitoes were pooled according to genus/species, and sampling location. Pools consisted of a maximum of 10 Aedes mosquitoes. 70 pools of 675 Aedes aegypti were screened with RT-PCR for flaviviruses. To confirm individual infection for determining True infection rate, individual mosquitoes which gave positive results of flavivirus detection were tested for dengue virus by RT-PCR. The infection rate was 5.93% (4 positive individuals from 675 mosquitoes). The probability to detect dengue virus in mosquitoes at the neighbour’s houses was 1.25 times, especially where distances between neighboring houses and patient’s houses were less than 50 meters. The relative humidity in dengue-infected villages with dengue-infected mosquitoes was significantly higher than villages that free from dengue-infected mosquitoes. Indoor biting rate of Aedes aegypti was 14.87 times higher than outdoor, and biting times of 09.00-10.00, 10.00-11.00, 11.00-12.00 yielded 1.77, 1.46, 0.68mosquitoes/man-hour, respectively. These findings confirm environmental factors were related to Dengue infection in Thailand. Data obtained from this study will be useful for the prevention and control of the diseases.

Keywords: Aedes aegypti, Dengue virus, environmental factors, one health, PCR

Procedia PDF Downloads 145

Authors: Eric Dede, Marcus Tindall, John W. Cherrie, Steve Hankin, Christopher Collins

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Current exposure models used in contaminated land risk assessment are highly conservative. Use of these models may lead to over-estimation of actual exposures, possibly resulting in negative financial implications due to un-necessary remediation. Thus, we are carrying out a study seeking to improve our understanding of human exposure to selected toxic elements in soil: arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb) resulting from allotment land-use. The study employs biomonitoring and physiologically-based pharmacokinetic (PBPK) modelling to quantify human exposure to these elements. We recruited 37 allotment users (adults > 18 years old) in Scotland, UK, to participate in the study. Concentrations of the elements (and their bioaccessibility) were measured in allotment samples (soil and allotment produce). Amount of produce consumed by the participants and participants’ biological samples (urine and blood) were collected for up to 12 consecutive months. Ethical approval was granted by the University of Reading Research Ethics Committee. PBPK models (coded in MATLAB) were used to estimate the distribution and accumulation of the elements in key body compartments, thus indicating the internal body burden. Simulating low element intake (based on estimated ‘doses’ from produce consumption records), predictive models suggested that detection of these elements in urine and blood was possible within a given period of time following exposure. This information was used in planning biomonitoring, and is currently being used in the interpretation of test results from biological samples. Evaluation of the models is being carried out using biomonitoring data, by comparing model predicted concentrations and measured biomarker concentrations. The PBPK models will be used to generate bioavailability values, which could be incorporated in contaminated land exposure models. Thus, the findings from this study will promote a more sustainable approach to contaminated land management.

Keywords: biomonitoring, exposure, PBPK modelling, toxic elements

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Authors: Mokhlisur Rahman

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Consumers' understanding of the products depends on what levels of information the advertisement contains. Consumers' attitudes vary widely depending on factors such as their level of environmental awareness, their perception of the company's motives, and the perceived effectiveness of the advertising campaign. Considering the growing eco-consciousness among consumers and their concern for the environment, strategies for green advertising have become equally significant for companies to attract new consumers. It is important to understand consumers' habits of purchasing, knowledge, and attitudes regarding eco-friendly products depending on promotion because of the limitless options of the products in the market. Additionally, encouraging consumers to buy sustainable products requires a platform that can message the world that being a stakeholder in sustainability is possible if consumers show eco-friendly behavior on a larger scale. Social media platforms provide an excellent atmosphere to promote companies' sustainable efforts to be connected engagingly with their potential consumers. The unique strategies of green advertising use techniques to carry information and rewards for the consumers. This study aims to understand the consumer behavior and effectiveness of green advertising by experimenting in collaboration with three companies in promoting their eco-friendly products using green designs on the products. The experiment uses three sustainable personalized offerings, Nike shoes, H&M t-shirts, and Patagonia school bags. The experiment uses a pretest and posttest design. 300 randomly selected participants take part in this experiment and survey through Facebook, Twitter, and Instagram. Nike, H&M, and Patagonia share the post of the experiment on their social media homepages with a video advertisement for the three products. The consumers participate in a pre-experiment online survey before making a purchase decision to assess their attitudes and behavior toward eco-friendly products. The audio-only feature explains the product's information, like their use of recycled materials, their manufacturing methods, sustainable packaging, and their impact on the environment during the purchase while the consumer watches the product video. After making a purchase, consumers take a post-experiment survey to know their perception and behavior toward eco-friendly products. For the data analysis, descriptive statistical tools mean, standard deviation, and frequencies measure the pre- and post-experiment survey data. The inferential statistical tool paired sample t-test measures the difference in consumers' behavior and attitudes between pre-purchase and post-experiment survey results. This experiment provides consumers ample time to consider many aspects rather than impulses. This research provides valuable insights into how companies can adopt sustainable and eco-friendly products. The result set a target for the companies to achieve a sustainable production goal that ultimately supports companies' profit-making and promotes consumers' well-being. This empowers consumers to make informed choices about the products they purchase and support their companies of interest.

Keywords: green-advertising, sustainability, consumer-behavior, social media

Procedia PDF Downloads 86

Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

Procedia PDF Downloads 139

Authors: Tatiana S. Ogneva

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Aluminum and nickel-based intermetallic compounds have attracted the attention of scientific community as promising materials for heat-resistant and wear-resistant coatings in such manufacturing areas as microelectronics, aircraft and rocket building and chemical industries. Magnetron sputtering makes possible to coat materials without formation of liquid phase and improves the mechanical and functional properties of nickel aluminides due to the possibility of nanoscale structure formation. The purpose of the study is the investigation of structure and properties of intermetallic coatings produced by magnetron sputtering technique. The feature of this work is the using of composite targets for sputtering, which were consisted of two semicircular sectors of cp-Ni and cp-Al. Plates of alumina, silicon, titanium and steel alloys were used as substrates. To estimate sputtering conditions on structure of intermetallic coatings, a series of samples were produced and studied in detail using scanning and transition electron microcopy and X-Ray diffraction. Besides, nanohardness and scratching tests were carried out. The varying parameters were the distance from the substrate to the target, the duration and the power of the sputtering. The thickness of the obtained intermetallic coatings varied from 0.05 to 0.5 mm depending on the sputtering conditions. The X-ray diffraction data indicated that the formation of intermetallic compounds occurred after sputtering without additional heat treatment. Sputtering at a distance not closer than 120 mm led to the formation of NiAl phase. Increase in the power of magnetron from 300 to 900 W promoted the increase of heterogeneity of the phase composition and the appearance of intermetallic phases NiAl, Ni₂Al₃, NiAl₃, and Al under the aluminum side, and NiAl, Ni₃Al, and Ni under the nickel side of the target. A similar trend is observed with increasing the distance of sputtering from 100 to 60 mm. The change in the phase composition correlates with the changing of the atomic composition of the coatings. Scanning electron microscopy revealed that the coatings have a nanoscale grain structure. In this case, the substrate material and the distance from the substrate to the magnetron have a significant effect on the structure formation process. The size of nanograins differs from 10 to 83 nm and depends not only on the sputtering modes but also on material of a substrate. Nanostructure of the material influences the level of mechanical properties. The highest level of nanohardness of the coatings deposited during 30 minutes on metallic substrates at a distance of 100 mm reached 12 GPa. It was shown that nanohardness depends on the grain size of the intermetallic compound. Scratching tests of the coatings showed a high level of adhesion of the coating to substrate without any delamination and cracking. The results of the study showed that magnetron sputtering of composite targets consisting of nickel and aluminum semicircles makes it possible to form intermetallic coatings with good mechanical properties directly in the process of sputtering without additional heat treatment.

Keywords: intermetallic coatings, magnetron sputtering, mechanical properties, structure

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

Procedia PDF Downloads 248