Search results for: balloon analogue risk task (BART)

Authors: Brajesh

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Introduction: It is generally believed that women's lack power to making decision may restrict their use of modern contraceptives practices. However, few studies have examined the different dimensions of women's empowerment and contraceptive use in Asian content. Pervasive gendered inequities and norms regarding the subordination of women give Asian men disproportionately more power than women, particularly in relation to the sex. We hypothesize that lack of sexual empowerment may pose an important barrier to reproductive health and adoption of family planning methods. Using the Demographic Health Survey, we examine the association between women’s sexual empowerment and contraceptive use in Nepal, Bangladesh and Pakistan. Objectives: To understand the trend and pattern of contraceptive choices and use among women due to sexual empowerment in selected south Asian countries. To examine the association between women’s sexual empowerment and contraceptive practices among non-pregnant married and partnered women in Nepal, Bangladesh and Pakistan. Methods: Data came from the latest round of Demographic and Health Surveys conducted between 2010-12 in and during deacde1990 -92 in Nepal, Bangladesh and Pakistan. Responses from married or cohabiting women aged 15-49 years were analyzed for six dimensions of empowerment and the current use of female-only methods or couple of methods. Bi-variate and multivariate multinomial regressions were used to identify associations between the empowerment dimensions and method use. Results: Positive associations were found between the overall empowerment score and method use in all countries (relative risk ratios, 1.1-1.3). In multivariate analysis, household economic decision-making was associated with the use of either female-only or couple methods (relative risk ratios -1. 1 for all), as was agreement on fertility preferences (RRR-1.3-1.6) and the ability to negotiate sexual activity (RRR -1. 1-1.2). In Bangladesh, women's negative attitudes toward domestic violence were correlated with the use of couple of methods (RRR -1. 1). Increasing levels of sexual empowerment were found to be associated with use of contraceptives, even after adjusting for demographic predictors of contraceptive use. This association is moderated by the wealth. Formal education, increasing wealth, and being in an unmarried partnership are associated with contraceptive use, whereas women who identify as being Muslim are less likely to use contraceptives than those who identify as being Hindus or other. These findings suggest that to achieve universal access to reproductive health services, gendered disparities in sexual empowerment, particularly among economically disadvantaged women, need to be better addressed. Conclusions: Intervention programs aimed at increasing contraceptive use may need to involve different approaches, including promoting couples' discussion of fertility preferences and family planning, improving women's self-efficacy in negotiating sexual activity and increasing their economic independence. Policies are needed to encourage the rural families to give their girls a chance of attending higher level education and professional course so that can get a better job opportunity and can economically support their family as son are expected to do.

Keywords: reproductive and child health (RCH), relative risk ratios (RRR), demographic and health survey (DHS), women’s sexual empowerment (WSE)

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Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

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Authors: Mei-Hsiu Chi, Jyh-Yang Wu, Sheng-Gwo Chen

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The diffusion-reaction equations are important Partial Differential Equations in mathematical biology, material science, physics, and so on. However, finding efficient numerical methods for diffusion-reaction systems on curved surfaces is still an important and difficult problem. The purpose of this paper is to present a convergent geometric method for solving the reaction-diffusion equations on closed surfaces by an O(r)-LTL configuration method. The O(r)-LTL configuration method combining the local tangential lifting technique and configuration equations is an effective method to estimate differential quantities on curved surfaces. Since estimating the Laplace-Beltrami operator is an important task for solving the reaction-diffusion equations on surfaces, we use the local tangential lifting method and a generalized finite difference method to approximate the Laplace-Beltrami operators and we solve this reaction-diffusion system on closed surfaces. Our method is not only conceptually simple, but also easy to implement.

Keywords: closed surfaces, high-order approachs, numerical solutions, reaction-diffusion systems

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Authors: Elena Chernyak, Ryan Ceresola

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Intimate partner violence is a serious social problem that affects a million women worldwide and impacts their health and wellbeing. Some risk factors for intimate partner violence against women (e.g., disobeying or arguing with a partner, women’s age, education, and employment) are similar in many countries, both developed and developing. However, one of the principal and most significant contributors to women’s vulnerability to violence perpetrated by their intimate partners is the witnessing of interparental aggression in the family of origin. Witnessing interparental violence may lead to acceptance of intimate partner violence as a normal way to resolve conflicts. Thus, utilization of violence becomes the behavioral model: men who witnessed the parental violence are more likely to employ physical violence against their female partners whereas women who observed their fathers beating their mothers learn to tolerate aggressive behavior and become victims of domestic violence themselves. Taking into consideration the importance of this subject matter, the association between witnessing intimate partner violence in family-of-origin and experience of intimate partner violence in adulthood requires further attention. The objective of this research is to analyze and compare the prevalence of intimate partner violence in ten developing countries in different regions, namely: Mali, Haiti, Jordan, Peru, the Philippines, Pakistan, Cambodia, Egypt, the Dominican Republic and Nigeria. Specifically, this research asks whether witnessing interparental violence in a family of origin is associated with the woman’s experience of intimate partner violence during adulthood and to what extent this factor varies among the countries under investigation. This study contributes to the literature on domestic violence against women, prevalence and experience of intimate partner violence against women in developing countries, and the risk factors, using recently collected, nationally representative population-based data from above-mentioned countries. The data used in this research are derived from the demographic and health surveys conducted in the ten mentioned above countries from 2013-2016. These surveys are cross-sectional, nationally representative surveys of ever-married or cohabitating women of reproductive age and the good source of high quality and comprehensive information about women, their children, partners, and households. To complete this analysis, multivariate logistic regression was run for each of the countries, and the results are presented with odds ratios, in order to highlight the effect of witnessing intimate partner violence controlling for other factors. The results of this study indicated that having witnessed partner violence in a family of origin significantly (by 50-500%) increases the likelihood of experiencing later abuse for respondents in all countries. This finding provides robust support for the intergenerational transmission of violence theory that explains the link between interparental aggression and intimate partner violence in subsequent relationships in adulthood as a result of a learned model of behavior observed in childhood. Furthermore, it was found that some of the control variables (e.g., education, number of children, and wealth) are associated with intimate partner violence in some countries under investigation while are not associated with male partner’s abusive behavior in some other, which may be explained by specific cultural and economic factors.

Keywords: intimate partner violence, domestic violence against women, developing countries, demographic and health surveys, risk factors

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Authors: Sushant Singh, Anurag Jain, Seema Sabharwal

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Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to sell their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The improved procedure has been tested using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, load balancing, throttled

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Authors: Lukas Kober, Vladimir Littva, Vladimir Siska

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The pandemic has had a significant impact on our lives. One of the most affected professions is the nursing profession. Nurses are closest to the patient, spend the most time with him, support him, often replace the closest family members, and of course, are part of the whole treatment process. Current nurses have more competencies and roles than in the past. The healthcare system has reached a turning point, also in connection with the spreading Delta variant and the risk of the arrival of the third wave. The lack of nurses is a long-term problem, but it did not arise by itself. The reasons for the departure of nurses from the health care system are not only due to the increasing average age of nurses and midwives in Slovakia and their retirement. Thousands of nurses are leaving due to poor working conditions, low wages, and poor management of individual workplaces. We need to keep older nurses in the health care system, otherwise, we risk their early departure. The pandemic only exacerbates this situation, and the associated risks, such as occupational infections or enormous overload and exhaustion, only accelerate the exit from the profession. According to current data from the register of nurses and midwives, we canceled 772 registrations from January to September 2021, and 584 nurses requested the suspension of registration due to non-performance of the profession. During the same period, we registered only 240 new nurses graduate. We have had this significant disparity here for a long time. For the whole of 2020, we canceled 911 registrations and suspended 973 registrations. We registered a total of 389 graduates. Our system loses hundreds of graduates a year and loses experienced nurses with decades of experience who leave due to poor working conditions, wages and suffer from burnout. Such compensation should also be awarded to the families of health professionals who have lost their lives due to work and to COVID-19. These options can also be motivating for promising people interested in studying nursing, who can gradually replace the missing workforce. This purchase is supported by the KEGA project no. 015KU-4/2019.

Keywords: pandemic, COVID-19, nursing, nursing workforce, lack of nurses

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Authors: Thuraya Ahmed Al Shidhani, Yahya Al Farsi, Alya Al Husni, Samir Al Adawi

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Background: Knee osteoarthritis (knee OA) represents a major public health burden worldwide, particularly among older adults. However, little has been documented from Arabian Gulf countries, which have left an information gap. Objective: This study describes the socio-demographic, clinical risk factors, and use of herbal medicine among men and women seeking consultation for knee OA at two secondary healthcare facilities in Muscat, Oman. Methods: A cross-sectional study was conducted among 213 Omani adults with knee OA attending a referral polyclinic in Muscat, Oman, over 12 months from January to December. Socio-demographic data were collected from the participants who are seeking consultation for knee OA. Results: Among the 213 study participants, 171 were females and 42 males. The females were comparatively older than the males, had lower education and lower-income, and more overweight. The majority of the participants were normal weight or underweight. About one-third of participants reported OA in other joints as well. Most participants recalled that they had knee OA for less than a year. About 12% reported a history of trauma. The majority (63%) concurrently had other chronic illnesses, and 33% reported having at least one complication. About 22% were using herbal medicines. About 77% are using herbal local applications in form of powder and creams. Conclusion: This study, to our knowledge, is the first to explore socio-demographic characteristics, clinical risk factors and use of herbal medicine among sufferers of knee OA in Oman. Knee OA tended to occur among our participants at younger ages than reported elsewhere, while obesity appeared orthogonal to the severity of knee OA. Women were more affected than men. About one quarter of Omani patients are using herbal medicine. More studies are needed to understand the causal factors and development of knee OA in Oman. Targeted health education and rehabilitation programs are needed, particularly among Omani women, to improve their physical quality of life.

Keywords: knee joint, osteoarthritis, herbal medicine, Oman

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Authors: Supriya Majumder, Pabitra Banik

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Fates of Arsenic (As) on the soil-plant environment belong to the critical emerging issue, which in turn to appraises the threatening implications of a human health risk — assessing the dynamics of As in soil solid components are likely to impose its potential availability towards plant uptake. In the present context, we introduced an improved Sequential Extraction Procedure (SEP) questioning to identify solid-phase speciation of As in paddy soil under variable soil environmental conditions during two consecutive seasons of rice cultivation practices. We coupled gradients of water management practices with the addition of fertilizer amendments to assess the changes in a partition of As through a field experimental study during monsoon and post-monsoon season using two rice cultivars. Water management regimes were varied based on the methods of cultivation of rice by Conventional (waterlogged) vis-a-vis System of Rice Intensification-SRI (saturated). Fertilizer amendment through the nutrient treatment of absolute control, NPK-RD, NPK-RD + Calcium silicate, NPK-RD + Ferrous sulfate, Farmyard manure (FYM), FYM + Calcium silicate, FYM + Ferrous sulfate, Vermicompost (VC), VC + Calcium silicate, VC + Ferrous sulfate were selected to construct the study. After harvest, soil samples were sequentially extracted to estimate partition of As among the different fractions such as: exchangeable (F1), specifically sorbed (F2), As bound to amorphous Fe oxides (F3), crystalline Fe oxides (F4), organic matter (F5) and residual phase (F6). Results showed that the major proportions of As were found in F3, F4 and F6, whereas F1 exhibited the lowest proportion of total soil As. Among the nutrient treatment mediated changes on As fractions, the application of organic manure and ferrous sulfate were significantly found to restrict the release of As from exchangeable phase. Meanwhile, conventional practice produced much higher release of As from F1 as compared to SRI, which may substantially increase the environmental risk. In contrast, SRI practice was found to retain a significantly higher proportion of As in F2, F3, and F4 phase resulting restricted mobilization of As. This was critically reflected towards rice grain As bioavailability where the reduction in grain As concentration of 33% and 55% in SRI concerning conventional treatment (p <0.05) during monsoon and post-monsoon season respectively. Also, prediction assay for rice grain As bioavailability based on the linear regression model was performed. Results demonstrated that rice grain As concentration was positively correlated with As concentration in F1 and negatively correlated with F2, F3, and F4 with a satisfactory level of variation being explained (p <0.001). Finally, we conclude that F1, F2, F3 and F4 are the major soil. As fractions critically may govern the potential availability of As in soil and suggest that rice cultivation with the SRI treatment is particularly at less risk of As availability in soil. Such exhaustive information may be useful for adopting certain management practices for rice grown in contaminated soil concerning to the environmental issues in particular.

Keywords: arsenic, fractionation, paddy soil, potential availability

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Naznine Anwar, Kim Cornish, Izelle Labuschagne, Nellie Georgiou-Karistianis

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Falls and subsequent injuries are common features in symptomatic Huntington’s disease (symp-HD) individuals. As part of daily walking, navigating around obstacles may incur a greater risk of falls in symp-HD. We designed obstacle-crossing experiment to examine adaptive gait dynamics and to identify underlying spatiotemporal gait characteristics that could increase the risk of falling in symp-HD. This experiment involved navigating around one or two ground-based obstacles under two conditions (walking while navigating around one obstacle, and walking while navigating around two obstacles). A total of 32 participants were included, 16 symp-HD and 16 healthy controls with age and sex matched. We used a GAITRite electronic walkway to examine the spatiotemporal gait characteristics and inter-trail gait variability when participants walked at their preferable speed. A minimum of six trials were completed which were performed for baseline free walk and also for each and every condition during navigating around the obstacles. For analysis, we separated all walking steps into three phases as approach steps, navigating steps and recovery steps. The mean and inter-trail variability (within participant standard deviation) for each step gait variable was calculated across the six trails. We found symp-HD individuals significantly decreased their gait velocity and step length and increased step duration variability during the navigating steps and recovery steps compared with approach steps. In contrast, HC individuals showed less difference in gait velocity, step time and step length variability from baseline in both respective conditions as well as all three approaches. These findings indicate that increasing spatiotemporal gait variability may be a possible compensatory strategy that is adopted by symp-HD individuals to effectively navigate obstacles during walking. Such findings may offer benefit to clinicians in the development of strategies for HD individuals to improve functional outcomes in the home and hospital based rehabilitation program.

Keywords: Huntington’s disease, gait variables, navigating around obstacle, basal ganglia dysfunction

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Authors: Naqvi Shraddha Rathi

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During the aging process, physical frailty may develop. A more sedentary lifestyle, a reduction in metabolic cell mass and, consequently, lower energy expenditure and dietary intake are important contributors to the progression of frailty. A decline in intake is in turn associated with the risk of developing a suboptimal nutritional state or multiple micro nutrient deficiencies.The tantalizing potential of nanotechnology is to fabricate and combine nano scale approaches and building blocks to make useful tools and, ultimately, interventions for medical science, including nutritional science, at the scale of ∼1–100 nm.

Keywords: aging, cells frailty, micronutrients, biochemical reactivity

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Authors: Akhil Teja Kambhampati, Mark A. Hoffman

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In the realm of infectious disease research, airborne viral transmission stands as a paramount concern due to its pivotal role in propagating pathogens within densely populated regions. However, amidst this landscape, the phenomenon of hygroscopic growth within respiratory bioaerosols remains relatively underexplored. Unlike pure water aerosols, the unique composition of respiratory bioaerosols leads to varied evaporation rates and hygroscopic growth patterns, influenced by factors such as ambient humidity, temperature, and airflow. This study addresses this gap by focusing on the behaviors of single respiratory bioaerosol utilizing salinity to induce saliva-like hygroscopic behavior. By employing mass, momentum, and energy equations, the study unveils the intricate interplay between evaporation and hygroscopic growth over time. The numerical model enables temporal analysis of bioaerosol characteristics, including size, temperature, and trajectory. The analysis reveals that due to evaporation, there is a reduction in initial size, which shortens the lifetime and distance traveled. However, when hygroscopic growth begins to influence the bioaerosol size, the rate of size reduction slows significantly. The interplay between evaporation and hygroscopic growth results in bioaerosol size within the inhalation range of humans and prolongs the traveling distance. Findings procured from the analysis are crucial for understanding the spread of infectious diseases, especially in high-risk environments such as healthcare facilities and public transportation systems. By elucidating the nuanced behaviors of respiratory bioaerosols, this study seeks to inform the development of more effective preventative strategies against pathogens propagation in the air, thereby contributing to public health efforts on a global scale.

Keywords: airborne viral transmission, high-risk environments, hygroscopic growth, evaporation, numerical modeling, pathogen propagation, preventative strategies, public health, respiratory bioaerosols

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Authors: Debabrata Biswas

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The current trend in the development of antibiotic resistance by multiple bacterial pathogens has resulted in a troubling loss of effective antibiotic options for human. The emergence of multi-drug-resistant pathogens has necessitated higher dosages and combinations of multiple antibiotics, further exacerbating the problem of antibiotic resistance. Zoonotic bacterial pathogens, such as Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli (such as enterohaemorrhagic E. coli or EHEC), and Listeria are the most common and predominant foodborne enteric infectious agents. It was observed that these pathogens gained/developed their ability to survive in the presence of antibiotics either in farm animal gut or farm environment and researchers believe that therapeutic and sub-therapeutic antibiotic use in farm animal production might play an important role in it. The mechanism of action of antimicrobial components used in farm animal production in genomic interplay in the gut and farm environment, has not been fully characterized. Even the risk of promoting the exchange of mobile genetic elements between microbes specifically pathogens needs to be evaluated in depth, to ensure sustainable farm animal production, safety of our food and to mitigate/limit the enteric infection with multiple antibiotic resistant bacterial pathogens. Due to the consumer’s demand and considering the current emerging situation, many countries are in process to withdraw antibiotic use in farm animal production. Before withdrawing use of the sub-therapeutic antibiotic or restricting the use of therapeutic antibiotics in farm animal production, it is essential to find alternative natural antimicrobials for promoting the growth of farm animal and/or treating animal diseases. Further, it is also necessary to consider whether that compound(s) has the potential to trigger the acquisition or loss of genetic materials in zoonotic and any other bacterial pathogens. Development of alternative therapeutic and sub-therapeutic antimicrobials for farm animal production and food processing and preservation and their effective implementation for sustainable strategies for farm animal production as well as the possible risk for horizontal gene transfer in major enteric pathogens will be focus in the study.

Keywords: food safety, natural antimicrobial, sustainable farming, antibiotic resistance

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Authors: Rahul Ravindranathan, R. P. Gokul

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India, in its efforts towards economic and social development, is currently experiencing a heavy demand for energy. Due to the lack of sufficient domestic energy reserves, the country is highly dependent on energy imports which has increased rapidly at a rate of about 12 % per annum since 2005. Hence, India is currently focusing its efforts to manage this energy supply and demand gap and eventually achieve energy security. One of the most cost effective means to reduce this gap is by adopting Energy efficiency measures in the country. Initial assessments have shown that Energy efficiency measures have an energy conservation potential of about 23%. For an estimated investment potential of USD 8 Billion, the annual energy savings was estimated to be about 180 Billion Units per annum. In order to explore this huge energy conservation potential, many critical factors need to be considered to achieve practical energy savings. Financing options for these investments is one such major factor. Not only has India come out with various policy level as well as technology level drives to promote Energy efficiency but it has also developed various financing schemes to promote investment in Energy Efficiency projects. The Public sector has already come out with certain financing schemes such as the Partial Risk Guarantee Fund (PRGF), Venture Capital Fund (VCF), Partial Risk Sharing Fund (PRSF) etc., and various sectors are gradually utilizing these schemes to implement energy saving measures. However, additional financing options are required in order to explore the untouched energy conservation potential in the country. Hence, there is a need to develop some innovative financing options for India which would motivate the private sectors as well as financing institutions to invest in these energy saving measures. This paper shall review the existing financing schemes launched by the Government of India and highlight the key benefits as well as challenges with respect to these schemes. In addition to this, the paper would also review new and innovative financing schemes for India and how the same could be adopted in other parts of the globe especially in South and South East Asia. This review would provide an insight to the various Governments as well as Financial Institutions in coming out with new financing schemes for their country.

Keywords: energy, efficiency, financing, India

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Authors: Imran Dayan, Ashiqul Khan

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Internal corporate fraud, which is fraud carried out by internal stakeholders of a company, affects the well-being of the organisation just like its external counterpart. Even if such an act is carried out for the short-term benefit of a corporation, the act is ultimately harmful to the entity in the long run. Internal fraud is often carried out by relying upon aberrations from usual business processes. Business processes are the lifeblood of a company in modern managerial context. Such processes are developed and fine-tuned over time as a corporation grows through its life stages. Modern corporations have embraced technological innovations into their business processes, and Enterprise Resource Planning (ERP) systems being at the heart of such business processes is a testimony to that. Since ERP systems record a huge amount of data in their event logs, the logs are a treasure trove for anyone trying to detect any sort of fraudulent activities hidden within the day-to-day business operations and processes. This research utilises the ERP systems in place within corporations to assess the likelihood of prospective internal fraud through developing a framework for measuring the risks of fraud through Process Mining techniques and hence finds risky designs and loose ends within these business processes. This framework helps not only in identifying existing cases of fraud in the records of the event log, but also signals the overall riskiness of certain business processes, and hence draws attention for carrying out a redesign of such processes to reduce the chance of future internal fraud while improving internal control within the organisation. The research adds value by applying the concepts of Process Mining into the analysis of data from modern day applications of business process records, which is the ERP event logs, and develops a framework that should be useful to internal stakeholders for strengthening internal control as well as provide external auditors with a tool of use in case of suspicion. The research proves its usefulness through a few case studies conducted with respect to big corporations with complex business processes and an ERP in place.

Keywords: enterprise resource planning, fraud risk framework, internal corporate fraud, process mining

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Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

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To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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Authors: Athini Ntloko

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Mycobacterium bovis and other species of Mycobacterium tuberculosis complex (MTBC) can result to a zoonotic infection known as Bovine tuberculosis (bTB). MTBC has members that may contaminate an extensive range of hosts, including wildlife. Diverse wild species are known to cause disease in domestic livestock and are acknowledged as TB reservoirs. It has been a main study worldwide to deliberate on bTB risk factors as a result and some studies focused on particular parts of risk factors such as wildlife and herd management. The significance of the study was to determine the incidence of Mycobacterium tuberculosis complex that is associated with soil, hayfeed and water. Questionnaires were administered to thirty (30) smallholding farm owners in the two villages (kwaMasele and Qungqwala) and three (3) three commercial farms (Fort Hare dairy farm, Middledrift dairy farm and Seven star dairy farm). Detection of M. tuberculosis complex was achieved by Polymerase Chain Reaction using primers for IS6110; whereas a genotypic drug resistance mutation was detected using Genotype MTBDRplus assays. Nine percent (9%) of respondents had more than 40 cows in their herd, while 60% reported between 10 and 20 cows in their herd. Relationship between farm size and vaccination for TB differed from forty one percent (41%) being the highest to the least five percent (5%). The highest number of respondents who knew about relationship between TB cases and cattle location was ninety one percent (91%). Approximately fifty one percent (51%) of respondents had knowledge about wild life access to the farms. Relationship between import of cattle and farm size ranged from nine percent (9%) to thirty five percent (35%). Cattle sickness in relation to farm size differed from forty three (43%) being the highest to the least three percent (3%); while thirty three percent (33%) of respondents had knowledge about health management. Respondents with knowledge about the occurrence of TB infections in farms were forty-eight percent (48%). The frequency of DNA isolation from samples ranged from the highest forty-five percent (45%) from water to the least twenty two percent (22%) from soil. Fort Hare dairy farm had the highest number of positive samples, forty four percent (44%) from water samples; whereas Middledrift dairy farm had the lowest positive from water, seventeen percent (17%). Twelve (22%) out of 55 isolates showed resistance to INH and RIF that is, multi-drug resistance (MDR) and nine percent (9%) were sensitive to either INH or RIF. The mutations at rpoB gene differed from 58% being the highest to the least (23%). Fifty seven percent (57%) of samples showed a S315T1 mutation while only 14% possessed a S531L in the katG gene. The highest inhA mutations were detected in T8A (80 %) and the least was observed in A16G (17%). The results of this study reveal that risk factors for bTB in cattle and dairy farm workers are a serious issue abound in the Eastern Cape of South Africa; with the possibility of widespread dissemination of multidrug resistant determinants in MTBC from the environment.

Keywords: hayfeed, isoniazid, multi-drug resistance, mycobacterium tuberculosis complex, polymerase chain reaction, rifampicin, soil, water

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Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir

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The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.

Keywords: drug discovery, ionic current, operational amplifier, patch clamp

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Neda Nabid, Iman Hajirasouliha, Sanaz Shirinbar

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One of the most challenging issues in earthquake engineering is to find effective ways to reduce earthquake forces and damage to structural and non-structural elements under strong earthquakes. While friction dampers are the most efficient systems to improve the seismic performance of substandard structures, their optimum design is a challenging task. This research aims to find more appropriate slip load distribution pattern for efficient design of friction panels. Non-linear dynamic analyses are performed on 3, 5, 10, 15, and 20-story RC frame using Drain-2dx software to find the appropriate range of slip loads and investigate the effects of different distribution patterns (cantilever, uniform, triangle, and reverse triangle) under six different earthquake records. The results indicate that using triangle load distribution can significantly increase the energy dissipation capacity of the frame and reduce the maximum inter-storey drift, and roof displacement.

Keywords: friction panels, slip load, distribution patterns, RC frames, energy dissipation

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Authors: Deepak M. Sajnekar, S. B. Deshpande, R. M. Mohril

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At present many rotary excitation control system are using analog type of Automatic Voltage Regulator which now started to replace with the digital automatic voltage regulator which is provided with PID controller and tuning of PID controller is a challenging task. The cases where digital excitation control system is used tuning of PID controller are still carried out by pole placement method. Tuning of PID controller used for static excitation control system is not challenging because it does not involve exciter time constant. This paper discusses two methods of tuning PID controller i.e. Pole placement method and pole zero cancellation method. GUI prepared for both the methods on the platform of MATLAB. Using this GUI, performance results and time required for tuning for both the methods are compared. Sensitivity of the methods is also presented with parameter variation like loop gain ‘K’ and exciter time constant ‘te’.

Keywords: digital excitation system, automatic voltage regulator, pole placement method, pole zero cancellation method

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Authors: Merad Boudia Omar Rafik, Feham Mohammed

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Data aggregation in wireless sensor networks (WSNs) provides a great reduction of energy consumption. The limited resources of sensor nodes make the choice of an encryption algorithm very important for providing security for data aggregation. Asymmetric cryptography involves large ciphertexts and heavy computations but solves, on the other hand, the problem of key distribution of symmetric one. The latter provides smaller ciphertexts and speed computations. Also, the recent researches have shown that achieving the end-to-end confidentiality and the end-to-end integrity at the same is a challenging task. In this paper, we propose (SA-SPKC), a novel security protocol which addresses both security services for WSNs, and where only the base station can verify the individual data and identify the malicious node. Our scheme is based on stateful public key encryption (StPKE). The latter combines the best features of both kinds of encryption along with state in order to reduce the computation overhead. Our analysis

Keywords: secure data aggregation, wireless sensor networks, elliptic curve cryptography, homomorphic encryption

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Authors: Rozeena Baig, R. Rehana Rehman, Rifat Ahmed

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Background: Osteoporosis, characterized by low bone mineral density, poses a global health concern. Diagnosis increases the likelihood of developing osteoporosis, a multifactorial disorder marked by low bone mass, elevating the risk of fractures in the lumbar spine, femoral neck, hip, vertebras, and distal forearm, particularly in postmenopausal women due to bone loss influenced by various pathophysiological factors. Objectives: The aim is to investigate the association of serum cytokine, bone turnover marker, bone mineral density and TLR4 gene polymorphism in pre and post-menopausal women and to find if any of these can be the potential predictor of osteoporosis in postmenopausal women. Material and methods: The study participants consisted of Group A (n=91) healthy pre-menopausal women and Group B (n=102) healthy postmenopausal women having ≥ 5 years’ history of menopause. ELISA was performed for cytokine (TNFα) and bone turnover markers (carboxytelopeptides), respectively. Bone Mineral Density (BMD)was measured through a dual X-ray absorptiometry (DEXA) scan. Toll-like Receptors 4 (TLR4) gene polymorphisms (A896G; Asp299Gly) and (C1196T; Thr399Ile) were investigated by PCR and Sanger sequencing. Results: Statistical analysis reveals a positive correlation of age and BMI with T scores in the premenopausal group, whereas in post-menopausal group found a significant negative correlation between age and T-score at hip (r = - 0.352**), spine (r = - .306**), and femoral neck (r = - 0.344**) and a significant negative correlation of BMI with TNF-α (- 0.316**). No association and significant differences were observed for TLR4 genotype and allele frequencies among studied groups However, both SNPs exhibited significant association with each other. Conclusions: This study concludes that BMI, BMD and TNF-α are the potential predictors of osteoporosis in post-menopausal women. However, CTX and TLR4 gene polymorphism did not appear as potential predictors of bone loss in this study and apparently cannot help in predicting bone loss in post-menopausal women.

Keywords: osteoporosis, post-menopausal, pre-menopausal woemn, genetics mutaiont, TLR4 genepolymorphsum

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Authors: Kehinde Joseph Awosan, Balarabe Adami Isah, Edzu Usman Yunusa, Sarafadeen Adeniyi Arisegi, Izuchukwu Obasi, Oluchi Solomon-Anucha

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Background: Metabolic syndrome (MetS) is prevalent in patients with diabetes mellitus and a significant risk for major cardiovascular events. Identifying its burden and peculiarities is crucial to preventing complications among those at risk. Aim: This study was conducted to determine the prevalence and predictors of metabolic syndrome among diabetes clinic attendees in Sokoto, Nigeria. Materials and Methods: A cross-sectional study was conducted among 365 patients with type 2 diabetes attending the diabetes clinic of Specialist Hospital, Sokoto, Nigeria. A structured questionnaire was used to obtain data on the respondents’ socio-demographic variables, treatment history, and lifestyle. Blood pressure and anthropometric measurements (including weight, height, and waist circumference) were done for the patients. Likewise, biochemical assessment (including fasting plasma glucose, high-density lipoprotein cholesterol (HDL-c), and triglyceride (TG) was done. Metabolic syndrome was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III). Data were analyzed using the IBM Statistical Package for Social Sciences (SPSS) version 25. Results: The ages of the patients ranged from 30 to 78 (mean = 50.9 ±11.7) years. The overall prevalence of MetS was 57.3%, with a higher prevalence in females (68.1%) than males (43.0%). The most common components of MetS observed were hypertension (69.2%), and elevated fasting plasma glucose (65.7%); while the predictors of MetS were age > 50 years (OR 6.960, 95% CI: 3.836-12.628, p < 0.001), female sex (OR 2.300, 95% CI: 1.355-3.903, p = 0.002), physical activity (OR 0.214, 95% CI: 0.126-0.363, p < 0.001), and overweight/obesity (OR 3.356, 95% CI: 1.838-6.127, p < 0.001). Conclusion: Metabolic syndrome is prevalent among patients with type 2 diabetes in Sokoto, Nigeria, and the predictors were age > 50 years, female sex, physical activity, and overweight/obesity. Diabetes care providers should screen their patients for MetS to prevent adverse cardiovascular events.

Keywords: prevalence, predictors, metabolic syndrome, diabetes

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Authors: I. A. Harris, J. M. Naylor

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Antibiotic guidelines are published in order to reduce the risk of perioperative infection in orthopaedics. We surveyed 20 orthopaedic hospitals in Australia to determine their protocols for antibiotic prophylaxis around joint replacement surgery. We tested the protocols against Australian guidelines. We found that less than half of all protocols adhered to Australian guidelines. This indicates that current practice may lead to increased infection rates and increased antibiotic resistance.

Keywords: antibiotics, practice guidelines, orthopaedic surgery, joint replacement

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

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Authors: Marek Kuźniewski, Magdalena B. Kaziuk , Danuta Fedak, Paulina Dumnicka, Ewa Stępień, Beata Kuśnierz-Cabala, Władysław Sułowicz

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Background: The high prevalence of cardiovascular morbidity and mortality among patients with chronic kidney disease (CKD) is observed especially in those undergoing dialysis. Osteoprotegerin (OPG) and its ligands, receptor activator of nuclear factor kappa-B ligand (RANKL) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) have been associated with cardiovascular complications. Our aim was to study their role as cardiovascular risk factors in stage 5 CKD patients. Methods: OPG, RANKL and TRAIL concentrations were measured in 69 hemodialyzed CKD patients and 35 healthy volunteers. In CKD patients, cardiovascular dysfunction was assessed with aortic pulse wave velocity (AoPWV), carotid artery intima-media thickness (CCA-IMT), coronary artery calcium score (CaSc) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) serum concentration. Cardiovascular and overall mortality data were collected during a 7-years follow-up. Results: OPG plasma concentrations were higher in CKD patients comparing to controls. Total soluble RANKL was lower and OPG/RANKL ratio higher in patients. Soluble TRAIL concentrations did not differ between the groups and OPG/TRAIL ratio was higher in CKD patients. OPG and OPG/TRAIL positively predicted long-term mortality (all-cause and cardiovascular) in CKD patients. OPG positively correlated with AoPWV, CCA-IMT and NT-proBNP whereas OPG/TRAIL with AoPWV and NT-proBNP. Described relationships were independent of classical and non-classical cardiovascular risk factors, with exception of age. Conclusions: Our study confirmed the role of OPG as a biomarker of cardiovascular dysfunction and a predictor of mortality in stage 5 CKD. OPG/TRAIL ratio can be proposed as a predictor of cardiovascular dysfunction and mortality.

Keywords: osteoprotegerin, tumor necrosis factor-related apoptosis-inducing ligand, receptor activator of nuclear factor kappa-B ligand, hemodialysis, chronic kidney disease, cardiovascular disease

Procedia PDF Downloads 336