Search results for: network screening

Authors: Chinedu Ifedi Okeke

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The behavioural orientations of fathers, which resonate in the way they relate to members of their families and other community members, appear to have a variety of implications for the early development of children. In this paper, a conceptual map of fathers’ lifestyles is adopted to provide an interconnected network of father lifestyles. Empirical evidence from a qualitative case study of 25 Black fathers, who had been purposively selected from a suburb in one rural Eastern Cape municipality in South Africa, is reported in this paper. Semi-structured in-depth interviews were used to obtain data, which was analysed thematically. Findings identify and provide evidence of father lifestyles that are incongruent with the kind of parental behaviour needed to support the healthy early development of children. Findings suggest that these negative lifestyles appear to incapacitate fathers who fail to make a positive contribution to their children’s early development. To ensure that fathers make the expected contributions to their children’s early development, policies aimed at rehabilitating fathers who are involved in the negative lifestyles reported in this paper should be put in place.

Keywords: childhood development, fathering, fathers, intervention strategies, lifestyles, South Africa

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Authors: Salwa Salman

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On February 2016, Egypt’s President Abdel Fattah Al-Sisi ordered the former Prime Minister, Ibrahim Mehleb, to establish a committee responsible for retrieving looted state lands or providing squatters with land titles according to their individual cases. The specificity of desert lands emerges from its unique position in both Islamic law and Egypt’s Civil Code. In Egypt, desert lands can be transferred to private ownership through peaceful occupation and cultivation. This study explores the (re-) conceptualization of land rights, state territoriality, and sovereignty as a part of an emerging narrative on informal land tenure. Through the lens of an informal settlement, the study employs methodological insights from studies in the anthropology of development and their interpretation of Foucauldian discourse analysis to examine official representations on squatting over state lands and put them in conversation with individual narratives on land ownership and dispossession. It also employs Bruno Latour’s actor-network theory to explore the development of social networks through primary land contracts and informal local resource management.

Keywords: State lands, squatter community, Islamic law, Egypt’s Civil Code

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Authors: Usha S. Adiga, Sachidanada Adiga

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Introduction: Diabetes Mellitus (DM) is one of the most common non-communicable diseases which imposes a large economic burden on the global health-care system. Cost of illness studies in India have assessed the health care cost of DM, but have certain limitations due to lack of standardization of the methods used, improper documentation of data, lack of follow up, etc. The objective of the study was to estimate the cost of illness of uncomplicated versus complicated type 2 diabetes mellitus in Coastal Karnataka, India. The study also aimed to find out the trend of cost of illness of the disease over a decade. Methodology: A prevalence based bottom-up approach study was carried out in two tertiary care hospitals located in Coastal Karnataka after ethical approval. Direct Medical costs like annual laboratory costs, pharmacy cost, consultation charges, hospital bed charges, surgical /intervention costs of 238 diabetics and 340 diabetic patients respectively from two hospitals were obtained from the medical record sections. Patients were divided into six groups, uncomplicated diabetes, diabetic retinopathy(DR), nephropathy(DN), neuropathy(DNeu), diabetic foot(DF), and ischemic heart disease (IHD). Different costs incurred in 2008 and 2017 in these groups were compared, to study the trend of cost of illness. Kruskal Wallis test followed by Dunn’s test were used to compare median costs between the groups and Spearman's correlation test was used for correlation studies. Results: Uncomplicated patients had significantly lower costs (p <0.0001) compared to other groups. Patients with IHD had highest Medical expenses (p < 0.0001), followed by DN and DF (p < 0.0001 ). Annual medical costs incurred were 1.8, 2.76, 2.77, 1.76, and 4.34 times higher in retinopathy, nephropathy, diabetic foot, neuropathy and IHD patients as compared to the cost incurred in managing uncomplicated diabetics. Other costs also showed a similar pattern of rising. A positive correlation was observed between the costs incurred and duration of diabetes, a negative correlation between the glycemic status and cost incurred. The cost incurred in the management of DM in 2017 was found to be elevated 1.4 - 2.7 times when compared to that in 2008. Conclusion: It is evident from the study that the economic burden due to diabetes mellitus is substantial. It poses a significant financial burden on the healthcare system, individual and society as a whole. There is a need for the strategies to achieve optimal glycemic control and operationalize regular and early screening methods for complications so as to reduce the burden of the disease.

Keywords: COI, diabetes mellitus, a bottom up approach, economics

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Authors: Mohanad Alhabo, Naveed Nawaz, Mahmoud Al-Faris

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The dense deployment of small cells is a promising solution to enhance the coverage and capacity of the heterogeneous networks (HetNets). However, the unplanned deployment could bring new challenges to the network ranging from interference, unnecessary handovers and handover failures. This will cause a degradation in the quality of service (QoS) delivered to the end user. In this paper, we propose an integrated Grey Rational Analysis Standard Deviation based handover method (GRA-SD) for HetNet. The proposed method integrates the Standard Deviation (SD) technique to acquire the weight of the handover metrics and the GRA method to select the best handover base station. The performance of the GRA-SD method is evaluated and compared with the traditional Multiple Attribute Decision Making (MADM) methods including Simple Additive Weighting (SAW) and VIKOR methods. Results reveal that the proposed method has outperformed the other methods in terms of minimizing the number of frequent unnecessary handovers and handover failures, in addition to improving the energy efficiency.

Keywords: energy efficiency, handover, HetNets, MADM, small cells

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Authors: John Chau, Tzvi Aviv

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Cardiometabolic conditions (hypertension, diabetes, and hyperlipidemia) are major public health concerns. Analysis of all prescription records from about 10 million patients at the largest network of pharmacies in Canada reveals small year-over-year increases in the treatment prevalence of cardiometabolic diseases prior to the COVID-19 pandemic. Cardiometabolic treatment rates increase with age and are higher in males than females. Hypertension treatment rates were 24% in males and 19% in females in 2021. Diabetes treatment rates were 10% in males and 7% in females in 2021. Geospatial analysis using patient addresses reveals interesting differences among provinces and neighborhoods in Canada. Using digital surveys distributed among 8,504 Canadian adults, an increase in hypertension awareness with age and female gender was observed. However, 7% of seniors and 6% of middle-aged Canadians reported uncontrolled blood pressure (>140/90 mmHg). In addition, elevated blood pressure (130-139/80-89 mmHg) was reported by 20% of seniors and 14% of middle-aged Canadians.

Keywords: cardiometabolic conditions, diabetes, hypertension, precision public health

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Authors: Karima Chaabna, Sohaila Cheema, Amit Abraham, Hekmat Alrouh, Ravinder Mamtani, Javaid I. Sheikh

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We aimed to assess the production of systematic reviews (SRs) that synthesize observational studies discussing population health issues in the Middle East and North Africa (MENA). Two independent reviewers systematically searched MEDLINE through PubMed. Between 2008-2016, 5,747 articles (reviews, systematic reviews, and meta-analyses) were identified. Following a multi-stage screening process, 387 SRs (with or without meta-analysis) on population health issues in the MENA were included in our overview. Citation numbers for each SR were retrieved from Google Scholar. Impact factor of the journal during the publication year for the included SRs was retrieved from the Institute of Scientific Information’s Journal Citation Report. We conducted linear regression analysis to assess time trends of number of publications according to SRs’ characteristics. We characterized a linear statistically significant increase in the annual numbers of SRs that summarize observational studies on the MENA population health (p-value<0.0001, R2=0.95), from 15 in 2008 to 81 in 2016. Our analysis reveals also linear statistically significant increases in numbers of SRs published by authors affiliated to institutions located inside MENA and/or neighboring countries (N=113, p-value < 0.0001, R²=0.90), by authors located outside MENA (N=155, p-value=0.0007, R²=0.82), and by collaborating authors affiliated to institutions located outside MENA and inside the region and/or in MENA’s neighboring countries (total number of SRs (N)= 119, p-value=0.0004, R²=0.85). Furthermore, these SRs were published in journals with an IF ranging from 0 to 47.8 (median=2.1). Linear statistically significant increases in numbers of published SRs were demonstrated in journals’ impact factor (IF) categories (IF=[0-2[: R²=0.79, p-value=0.0012; IF=[2-4[:R²=0.86, p-value=0.0003; and IF=[4-6[:R²=0.53, p-value=0.026). Additionally, annual numbers of citations to the SRs varied between 0 and 471 (median=7). While each year, a couple of SRs were getting more than 50 annual citations, there were linear statistically significant increases in numbers of published SRs with an annual number of citations at [0-10[(R²=0.89, p-value=0.00014) and at [10-50[ (R²=0.76, p-value=0.0021). Between 2008-2016, increasingly SRs that summarize observational studies on population health issues in the MENA were published. Authors of these SRs were located inside and/or outside the MENA region and an increasing number of collaborations were seen. Increasing numbers of SRs were predominantly observed in journals with an IF between zero and six. Interestingly, SRs covering MENA region countries were being increasingly cited, indicating an escalation of interest in this region’s population health issues.

Keywords: bibliometric, citation, impact factor, Middle East and North Africa, population health, systematic review

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann

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This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.

Keywords: rail-track components, maintenance, optimal clustering, possession capacity

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Ar.Abhishek Ranka

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Cultural landscapes are a part of a nation’s heritage, which represent the exquisite combination of Natural (Ecological) & Built (Architectural) fabric, consisting of many historic gardens, water management system, sustainable planning, and designed framework. The use of landscape and topography with Tangible &Intangible heritage components (forts, temples, tombs, mosques, etc.) are locally, regionally, and nationally significant. The paper speaks about the contribution of Bahmani Sultanate to military architecture in the Deccan region. It is a study of the series of seven land forts as a cultural landscape, which plays an important role in shaping the knowledge systems in the form of typologies of military architecture, water management system, and the administrative setups, which are presently located in the cultural region, Marathwada of the Deccan. Conservation of Culturall and scapeasan approach offers opportunities to better integrate natural and cultural heritage conservation. Conserving of Seven Land forts could act as an inspirational model for other sites.

Keywords: bahmani sultanate, deccan region, land forts, culture landscape, military architecture, tradational knowledge system, architectural conservation

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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Authors: Prachyanun Nilsook, Panita Wannapiroon

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The purpose of this research is to study a Digital Learning Repository System (DLRS) on vocational teachers and teaching in Thailand. The innobpcd.net is a DLRS being utilized by the Office of Vocational Education Commission and operationalized by the Bureau of Personnel Competency Development for vocational education teachers. The aim of the system is to support and enhance the process of vocational teaching and to improve staff development by providing teachers with a variety of network connections and information. The system provides centralized hosting and access to content, and the ability to share digital objects or files, to set permissions and controls for access to content that can be used vocational education teachers for their teaching and for their own development. The elements of DLRS include; Digital learning system, Media Library, Knowledge-based system and Mobile Application. The system aims to link vocational teachers to the most effective emerging technologies available for learning, so they are better resourced to support their vocational students. The initial results from this evaluation indicate that there is a range of services provided by the system being used by vocational teachers and this paper indicates which facilities have the greatest usage and impact on vocational teaching in Thailand.

Keywords: digital learning repositories, vocational education, knowledge sharing, learning objects

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Authors: Gabriele Borg, Alexei Debono, Charlie Abela

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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

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Authors: Ehsan Abshirini

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Rivers as one of the most important topographic factors have played a strategic role not only on the appearance of cities but they also affect the structure and morphology of cities. In this paper author intends to find out how a city in its physical network interacts with a river flowing inside. The pilot study is Angers, a city in western France, in which it is influenced by the Maine River. To this purpose space syntax method integrating with GIS is used to extract the properties of physical form of cities in terms of global and local integration value, accessibility and choice value. Simulating the state of absence of river in this city and comparing the result to the current state of city according to the effect of river on the morphology of areas located in different banks of river is also part of interest in this paper. The results show that although a river is not comparable to the city based on size and the area occupied by, it has a significant effect on the form of the city in both global and local properties. In addition, this study endorses that tracking the effect of river-cities and their interaction to rivers in a hybrid of space syntax and GIS may lead researchers to improve their interpretation of physical form of these types of cities.

Keywords: river-cities, Physical form, space syntax properties, GIS, topographic factor

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Authors: Clifford Otieno Ochieng, Nsenda Lukumwena

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Cities worldwide and most notably those in the global south, including Nairobi City are experiencing accelerated population growth and urban sprawl, accompanied with multiple socioeconomic challenges’ which in turn increase the pressure on already limited infrastructure such as public lighting and on limited financial resources. Based on this premise, through reimaging the value of street lighting infrastructure, the study attempts to highlight the affordance and affordability of streetlights and suggests them as a tool to optimally address limited financial resources that characterize cities in the global south. As a methodology, the paper reviews and analyzes literature available online including Nairobi city budgets; reports from Kenya Power, World Health Organization and United Nations; and articles on enterprise level Internet of Things (IoT) solutions. In conclusion, this study illustrates that streetlights can go well beyond their traditional roles of illuminating cities at night. They can be as suggested in this paper charging stations, communication network terminals and disease prevention nodes.

Keywords: affordance, Nairobi, developing economies, IoT, smart street lights, smart cities

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Authors: Gajaanuja Megalathan, Banuka Athuraliya

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Crime is one of our society's most intimidating and threatening challenges. With the majority of the population residing in cities, many experts and data provided by local authorities suggest a rapid increase in the number of crimes committed in these cities in recent years. There has been an increasing graph in the crime rates. People living in Sri Lanka have the right to know the exact crime rates and the crime rates in the future of the place they are living in. Due to the current economic crisis, crime rates have spiked. There have been so many thefts and murders recorded within the last 6-10 months. Although there are many sources to find out, there is no solid way of searching and finding out the safety of the place. Due to all these reasons, there is a need for the public to feel safe when they are introduced to new places. Through this research, the author aims to develop a mobile application that will be a solution to this problem. It is mainly targeted at tourists, and people who recently relocated will gain advantage of this application. Moreover, the Arima Model combined with ANN is to be used to predict crime rates. From the past researchers' works, it is evidently clear that they haven’t used the Arima model combined with Artificial Neural Networks to forecast crimes.

Keywords: arima model, ANN, crime prediction, data analysis

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Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

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The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

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Authors: Vanessa Bennemann, Gabriela Laste, Márcia Inês Goettert

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The gestational period is a phase in which the pregnant woman undergoes constant physiological and hormonal changes, which are part of the woman’s biological cycle, the development of the fetus, childbirth, and lactation. These are factors of response to the immunological adaptation of the human reproductive process that is directly related to the pregnancy’s well-being and development. Although most pregnancies occur without complications, about 15% of pregnant women will develop potentially fatal complications, implying maternal and fetal risk. Therefore, requiring specialized care for high-risk pregnant women (HRPW) with obstetric interventions for the survival of the mother and/or fetus. Among the risk factors that characterize HRPW are the women's age, gestational diabetes mellitus (GDM), autoimmune diseases, infectious diseases such as syphilis and HIV, hypertension (SAH), preeclampsia, eclampsia, HELLP syndrome, uterine contraction abnormalities, and premature placental detachment (PPD), thyroid disorders, among others. Thus, pregnancy has an impact on the thyroid gland causing changes in the functioning of the mother's thyroid gland, altering the thyroid hormone (TH) profiles and production as pregnancy progresses. Considering, throughout the gestational period, the interpretation of the results of the tests to evaluate the thyroid functioning depends on the stage in which the pregnancy is. Thyroid disorders are directly related to adverse obstetric outcomes and in child development. Therefore, the adequate release of TH is important for a pregnancy without complications and optimal fetal growth and development. Objective: Investigate the physiological effects caused by thyroid disorders in the gestational period. Methods: A search for articles indexed in PubMed, Scielo, and MDPI databases, was performed using the term “AND”, with the descriptors: Pregnancy, Thyroid. With several combinations that included: Melatonin, Thyroidopathy, Inflammatory processes, Cytokines, Anti-inflammatory, Antioxidant, High-risk pregnancy. Subsequently, the screening was performed through the analysis of titles and/or abstracts. The criteria were: including clinical studies in general, randomized or not, in the period of 10 years prior to the research, in the English literature; excluded: experimental studies, case reports, research in the development phase. Results: In the preliminary results, a total of studies (n=183) were found, (n=57) excluded, such as studies of cancer, diabetes, obesity, and skin diseases. Conclusion: To date, it has been identified that thyroid diseases can impair the fetus’s brain development. Further research is suggested on this matter to identify new substances that may have a potential therapeutic effect to aid the gestational period with thyroid diseases.

Keywords: pregnancy, thyroid, melatonin, high-risk pregnancy

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini

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The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.

Keywords: climate change, projections, solar radiation, validation

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Authors: Suman Som, Abhijit Maity, Sunil B. Daschakraborty, Sujit Chaudhuri, Manik Pradhan

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Background: Helicobacter pylori is a common and important human pathogen and the primary cause of peptic ulcer disease and gastric cancer. Currently H. pylori infection is detected by both invasive and non-invasive way but the diagnostic accuracy is not up to the mark. Aim: To set up an optimal diagnostic cut-off value of 13C-Urea Breath Test to detect H. pylori infection and evaluate a novel c-PDR methodology to overcome of inconclusive grey zone. Materials and Methods: All 83 subjects first underwent upper-gastrointestinal endoscopy followed by rapid urease test and histopathology and depending on these results; we classified 49 subjects as H. pylori positive and 34 negative. After an overnight, fast patients are taken 4 gm of citric acid in 200 ml water solution and 10 minute after ingestion of the test meal, a baseline exhaled breath sample was collected. Thereafter an oral dose of 75 mg 13C-Urea dissolved in 50 ml water was given and breath samples were collected upto 90 minute for 15 minute intervals and analysed by laser based high precisional cavity enhanced spectroscopy. Results: We studied the excretion kinetics of 13C isotope enrichment (expressed as δDOB13C ‰) of exhaled breath samples and found maximum enrichment around 30 minute of H. pylori positive patients, it is due to the acid mediated stimulated urease enzyme activity and maximum acidification happened within 30 minute but no such significant isotopic enrichment observed for H. pylori negative individuals. Using Receiver Operating Characteristic (ROC) curve an optimal diagnostic cut-off value, δDOB13C ‰ = 3.14 was determined at 30 minute exhibiting 89.16% accuracy. Now to overcome grey zone problem we explore percentage dose of 13C recovered per hour, i.e. 13C-PDR (%/hr) and cumulative percentage dose of 13C recovered, i.e. c-PDR (%) in exhaled breath samples for the present 13C-UBT. We further explored the diagnostic accuracy of 13C-UBT by constructing ROC curve using c-PDR (%) values and an optimal cut-off value was estimated to be c-PDR = 1.47 (%) at 60 minute, exhibiting 100 % diagnostic sensitivity , 100 % specificity and 100 % accuracy of 13C-UBT for detection of H. pylori infection. We also elucidate the gastric emptying process of present 13C-UBT for H. pylori positive patients. The maximal emptying rate found at 36 minute and half empting time of present 13C-UBT was found at 45 minute. Conclusions: The present study exhibiting the importance of c-PDR methodology to overcome of grey zone problem in 13C-UBT for accurate determination of infection without any risk of diagnostic errors and making it sufficiently robust and novel method for an accurate and fast non-invasive diagnosis of H. pylori infection for large scale screening purposes.

Keywords: 13C-Urea breath test, c-PDR methodology, grey zone, Helicobacter pylori

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Authors: Javier Menéndez, Jorge Loredo

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Large scale energy storage systems (LSESS) such as pumped-storage hydro-power (PSH) are required in the current energy transition towards a low carbon economy by using green energies that produce low levels of greenhouse gas (GHG) emissions. Coal mines are currently being closed in the European Union and their underground facilities may be used to build PSH plants. However, the development of this projects requires the excavation of a network of tunnels and a large cavern that would be used as a powerhouse to install the Francis turbine and motor-generator. The technical feasibility to excavate the powerhouse cavern has been analyzed in the North of Spain. Three-dimensional numerical models have been conducted to analyze the stability considering shale and sandstone rock mass. Total displacements and thickness of plastic zones were examined considering different support systems. Systematic grouted rock bolts and fibre reinforced shotcrete were applied at the cavern walls and roof. The results obtained show that the construction of the powerhouse is feasible applying proper support systems.

Keywords: closed mines, mine water, numerical model, pumped-storage, renewable energies

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Authors: Rigas Kotsakis, Nikolaos Tsigilis, Vasilis Grammatikopoulos, Evridiki Zachopoulou

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During the last decade, Greece has faced an unprecedented financial crisis, affecting various aspects and functionalities of Higher Education. Besides the restricted funding of academic institutions, the students and their families encountered economical difficulties that undoubtedly influenced the effective completion of their studies. In this context, a fairly large number of students in Alexander campus of International Hellenic University (IHU) delay, interrupt, or even abandon their studies, especially when they come from low-income families, belong to sensitive social or special needs groups, they have different cultural origins, etc. For this reason, a European project, named “Umbrella”, was initiated aiming at providing the necessary psychological support and counseling, especially to disadvantaged students, towards the completion of their studies. To this end, a network of various academic members (academic staff and students) from IHU, namely iMentor, were implicated in different roles. Specifically, experienced academic staff trained students to serve as intermediate links for the integration and educational support of students that fall into the aforementioned sensitive social groups and face problems for the completion of their studies. The main idea of the project is held upon its person-centered character, which facilitates direct student-to-student communication without the intervention of the teaching staff. The backbone of the iMentors network are senior students that face no problem in their academic life and volunteered for this project. It should be noted that there is a provision from the Umbrella structure for substantial and ethical rewards for their engagement. In this context, a well-defined, stringent methodology was implemented for the evaluation of the extent of the problem in IHU and the detection of the profile of the “candidate” disadvantaged students. The first phase included two steps, (a) data collection and (b) data cleansing/ preprocessing. The first step involved the data collection process from the Secretary Services of all Schools in IHU, from 1980 to 2019, which resulted in 96.418 records. The data set included the School name, the semester of studies, a student enrolling criteria, the nationality, the graduation year or the current, up-to-date academic state (still studying, delayed, dropped off, etc.). The second step of the employed methodology involved the data cleansing/preprocessing because of the existence of “noisy” data, missing and erroneous values, etc. Furthermore, several assumptions and grouping actions were imposed to achieve data homogeneity and an easy-to-interpret subsequent statistical analysis. Specifically, the duration of 40 years recording was limited to the last 15 years (2004-2019). In 2004 the Greek Technological Institutions were evolved into Higher Education Universities, leading into a stable and unified frame of graduate studies. In addition, the data concerning active students were excluded from the analysis since the initial processing effort was focused on the detection of factors/variables that differentiated graduate and deleted students. The final working dataset included 21.432 records with only two categories of students, those that have a degree and those who abandoned their studies. Findings of the first phase are presented across faculties and further discussed.

Keywords: higher education, students support, economic crisis, mentoring

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Authors: Aradhna Pandarum

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South Africa is experiencing an exponential growth of distributed solar PV installations. This is due to various factors with the predominant one being increasing electricity tariffs along with decreasing installation costs, resulting in attractive business cases to some end-users. Despite there being a variety of economic and environmental advantages associated with the installation of PV, their potential impact on distribution grids has yet to be thoroughly investigated. This is especially true since the locations of these units cannot be controlled by Network Service Providers (NSPs) and their output power is stochastic and non-dispatchable. This report details two case studies that were completed to determine the possible voltage and technical losses impact of increasing PV penetration in the Northern Cape of South Africa. Some major impacts considered for the simulations were ramping of PV generation due to intermittency caused by moving clouds, the size and overall hosting capacity and the location of the systems. The main finding is that the technical impact is different on a constrained feeder vs a non-constrained feeder. The acceptable PV penetration level is much lower for a constrained feeder than a non-constrained feeder, depending on where the systems are located.

Keywords: medium voltage networks, power system losses, power system voltage, solar photovoltaic

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Authors: Hanmei Peng, Yiqun Wang, Mao Tan, Zhuocen Dai, Yongxin Su

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Efficient energy management in multi-microgrid distribution systems holds significant importance for enhancing the economic benefits of regional power grids. To better balance conflicts among various stakeholders, a two-stage game-based collaborative optimization approach is proposed in this paper, effectively addressing the realistic scenario involving both competition and collaboration among stakeholders. The first stage, aimed at maximizing individual benefits, involves constructing a non-cooperative tariff game model for the distribution network and surplus microgrid. In the second stage, considering power flow and physical line capacity constraints we establish a cooperative P2P game model for the multi-microgrid distribution system, and the optimization involves employing the Lagrange method of multipliers to handle complex constraints. Simulation results demonstrate that the proposed approach can effectively improve the system economics while harmonizing individual and collective rationality.

Keywords: cooperative game, collaborative optimization, multi-microgrid distribution system, non-cooperative game

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Authors: Elmira Davasaz Tabrizi, Müşteba Sevil, Ercan Arican

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In recent decades, there has been a sharp increase in the prevalence of several unrelated chronic diseases. The use of long-term antibiotics for chronic illnesses is increasing. The antibiotic resistance occurrence and its relationship with host microbiomes are still unclear. Properties of the identifying antibodies have been the focus of chronic disease research, such as prostatitis or autoimmune. The immune system is made up of a complicated but well-organized network of cell types that constantly monitor and maintain their surroundings. The regulated homeostatic interaction between immune system cells and their surrounding environment shapes the microbial flora. Researchers believe that the disappearance of special bacterial species from our ancestral microbiota might have altered the body flora that can cause a rise in disease during the human life span. This unpleasant pattern demonstrates the importance of focusing on discovering and revealing the root causes behind the disappearance or alteration of our microbiota. In this review, we gathered the results of some studies that reveal changes in the diversity and quantity of microorganisms that may affect chronic and autoimmune diseases. Additionally, a Ph.D. thesis that is still in process as Metagenomic studies in chronic prostatitis samples is mentioned.

Keywords: metagenomic, autoimmune, prostatitis, microbiome

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Authors: Joshua Midha

Abstract:

The basis for information campaigns and behavioral interventions has long reigned as a tactic. From the Soviet-era propaganda machines to the opinion hijacks in Iran, these measures are now commonplace and are used for dissemination and disassembly. However, the use of these tools for strategic diffusion, specifically in a counter-terrorism setting, has only been explored on the surface. This paper aims to introduce a larger conceptual portion of guided information campaigns into preexisting terror cells and situations. It provides an alternative, low-risk intervention platform for future military strategy. This paper highlights a theoretical framework to lay out the foundationary details and explanations for behavioral interventions and moves into using a case study to highlight the possibility of implementation. It details strategies, resources, circumstances, and risk factors for intervention. It also sets an expanding foundation for offensive PsyOps and argues for tactical diffusion of information to battle extremist sentiment. The two larger frameworks touch on the internal spread of information within terror cells and external political sway, thus charting a larger holistic purpose of strategic operations.

Keywords: terrorism, behavioral intervention, propaganda, SNA, extremism

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Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Hexiong Liu

Abstract:

Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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