Search results for: health data

Authors: Binu Sahayam

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HIV/AIDS epidemic is in its third decade and has become a virulent disease that threatens the world population. Many countless efforts had been made yet this has become a social and developmental concern. According to UNAIDS 2013 Report, In India around 2.4 million people are currently living with HIV and third in the infection rate. As every country is facing this health issue, this has become a social and developmental concern for India. In country like India, open discussion on sex and sexuality is not possible due to its conventional culture. Educational institution like schools and colleges can create awareness on sex education, life skill education, information on HIV and STD which is lacking. It is very clear that preventive knowledge remains low and this leads to increase in the HIV/AIDS infection rate. HIV/AIDS is a disease which is not curable but preventable, keeping this in mind religious leaders of various have come forward in addressing the issue of HIV/AIDS using various social strategies. The study has been focused on three main India religious teachings Hinduism, Christianity and Islam in addressing the issue of HIV/AIDS and its possible intervention in dealing with HIV/AIDS prevention. The study is important because it highlights the health issues, stigma discrimination, psychological disturbances and insecurity faced by the infected and affected persons. Therefore, this study privileges the role of religious leadership in the efforts and processes of preventing HIV/AIDS, caring and providing support to People living with HIV/AIDS and argues that intervention of religious leadership is an effective measure to confront many of the barriers associated with HIV/AIDS.

Keywords: HIV and AIDS, STDs, religion and religious organisation

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Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta

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In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.

Keywords: reliability, maintainability, homegenous poission process, repairable system

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Authors: Manushi Srivastava

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Introduction: Doctor’s role, and relation with respect to patient care is at the core of medical ethics. The rapid pace of medical advances along with increasing consumer awareness about their rights and hike in cost of effective health care demand a robust, transparent and patient-friendly medical care system. However, doctors’ role performance is still in the frame of activity-passivity model of Doctor-Patient Relationship (DPR) where doctors act as parent and use to instruct their patients, without their consensus that is not going to help in the 21st century. Thus the current situation is a new challenge for traditional doctor-patient relationship after the introduction of Consumer Protection Act (CPA) in medical profession and the same is evidenced by increasing cases of medical litigation. To strengthen this system of medical services, the doctor plays a vital role, and the same should be reviewed in the present context. Objective: To understand the opinion of consultants regarding medical negligence and effect of Consumer Protection Act in terms of current practices of patient care. Method: This is a cross-sectional study in which both quantitative and qualitative methods are applied. Total 69 consultants were selected from multi-specialty hospitals of densely populated Varanasi city catering a population of about 1.8 million. Two-stage sampling was used for selection of respondents. At the first stage, selection of major wards (Medicine, Surgery, Ophthalmology, Gynaecology, Orthopaedics, and Paediatrics) was carried out, which are more susceptible to medical negligence. At the second stage, selection of consultants from the respective wards was carried out. In-depth Interviews were conducted with the help of semi-structured schedule. Two case studies of medical negligence were also carried out as part of the qualitative study. Analysis: Data were analyzed with the help of SPSS software (21.0 trial version). Semi-structured research tool was used to know consultant’s opinion about the pattern of medical negligence cases, litigations and claims made by patient community and inclusion of government medical services in CPA. Statistical analysis was done to describe data, and non-parametric test was used to observe the association between the variables. Analysis of Verbatim was used in case-study. Findings and Conclusion: Majority (92.8%) of consultants felt changes in the behaviour of community (patient) after implementation of CPA, as it had increased awareness about their rights. Less than half of the consultants opined that Medical Negligence is an Unintentional act of doctors and generally occurs due to communication gap and behavioural problem between doctor and patients. Experienced consultants ( > 10 years) pointed out that unethical practice by doctors and mal-intention of patient to harass doctors were additional reasons of Medical Negligence. In-depth interview revealed that now patients’ community expects more transparency and hence they demand cafeteria approach in diagnosis and management of cases. Thus as study results, we propose ‘Agreement Model’ of DPR to re-ensure ethical practice in medical profession.

Keywords: doctors, communication, consumer protection act (CPA), medical error

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Authors: Koffi Sodokin

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Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.

Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: Sumara Khanzada

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This research investigated how much stress is induced by various study-related factors, in undergraduate students belonging to a renowned university in Karachi along with the unhealthy coping strategy the students use to manage the stress. The study related factors considered for the purpose of the study were curriculum and instruction based stress, teacher-student relationship, assessment system and different components related to academic work. A survey in which questionnaires were administered to hundred students was conducted. The data were analyzed quantitatively to determine the percentages of stress induced by the various factors. The study found that student-teacher relationship is the strongest factor that causes stress in the undergraduate students specifically when teachers do not deliver the lectures effectively and give assignments and presentations to students without clear guidelines and instructions. The second important factor that causes stress was the different components of academic life, such as, parental expectations and pressures to achieve one's goals. Assessment system was found to be the third key factor inducing stress and affecting students' cognitive and psychological functioning. The most commonly used unhealthy coping strategy for stress management was procrastination. In light of the findings, it is recommended that importance be given to teacher training to ensure that instruction is proper and healthy teacher student relationship exists. Effective support programs, workshops, seminars, and different awareness programs should be arranged for promoting awareness regarding mental health in educational institutions. Moreover, additional zero credit courses should be offered to teach students how to learn stress management and healthy coping skills. Sumara Khanzada Clinical Psychologist [email protected]

Keywords: Stress, coping stretigies, acadamic stress, relationship

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Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott

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Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.

Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)

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Authors: Tanit Daniel Jodar Vecina, Adriane Prisco Petry

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The shape of the wind velocity profile changes according to local features of terrain shape and roughness, which are parameters responsible for defining the Atmospheric Boundary Layer (ABL) profile. Air flow characteristics over and around landforms, such as hills, are of considerable importance for applications related to Wind Farm and Turbine Engineering. The air flow is accelerated on top of hills, which can represent a decisive factor for Wind Turbine placement choices. The present work focuses on the study of ABL behavior as a function of slope and surface roughness of hill-shaped landforms, using the Computational Fluid Dynamics (CFD) to build wind velocity and turbulent intensity profiles. Reynolds-Averaged Navier-Stokes (RANS) equations are closed using the SST k-ω turbulence model; numerical results are compared to experimental data measured in wind tunnel over scale models of the hills under consideration. Eight hill models with slopes varying from 25° to 68° were tested for two types of terrain categories in 2D and 3D, and two analytical codes are used to represent the inlet velocity profiles. Numerical results for the velocity profiles show differences under 4% when compared to their respective experimental data. Turbulent intensity profiles show maximum differences around 7% when compared to experimental data; this can be explained by not being possible to insert inlet turbulent intensity profiles in the simulations. Alternatively, constant values based on the averages of the turbulent intensity at the wind tunnel inlet were used.

Keywords: Atmospheric Boundary Layer, Computational Fluid Dynamic (CFD), Numerical Modeling, Wind Tunnel

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Authors: Ku Aina Afiqah Ku Adzman, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba

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NFC operates on low-range 13.56 MHz frequency within a distance from 4cm to 10cm, and the applications can be categorized as touch and go, touch and confirm, touch and connect, and touch and explore. NFC applications are vulnerable to various security and privacy attacks such due to its physical nature; unprotected data stored in NFC tag and insecure communication between its applications. This paper aims to determine the likelihood of security risks happening in an NFC technology and application. We present an NFC technology taxonomy covering NFC standards, types of application and various security and privacy attack. Based on observations and the survey presented to evaluate the risk assessment within the touch and go application demonstrates two security attacks that are high risks namely data corruption and DOS attacks. After the risks are determined, risk countermeasures by using AHP is adopted. The guideline and solutions to these two high risks, attacks are later applied to a secure NFC-enabled Smartphone Attendance System.

Keywords: Near Field Communication (NFC), risk assessment, multi-criteria decision making, Analytical Hierarchy Process (AHP)

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Authors: Endalew Fufa Kufi

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The research investigated the role of stakeholders such as students, teachers and administrators in the practices of good governance in higher education by looking into the special contributions of top-officials, teachers and students in ensuring workable ties and productive interchanges in Adama Science and Technology University. Attention was given to participation, fairness and exemplariness as key indicators of good governance. The target university was chosen for its familiarity for the researcher to get dependable data, access to respondent and management of the processing of data. Descriptive survey design was used for the purpose of describing concerned roles the stakeholders in the university governance in order to reflect on the nature of participation of the practices. Centres of the research were administration where supportive groups such as central administrators and underlying service-givers had parts and academia where teachers and students were target. Generally, 60 teachers, 40 students and 15 administrative officers were referents. Data were collected in the form of self-report through open-ended questionnaires. The findings indicated that, while vertical interchanges in terms of academic and administrative routines were had normal flow on top-down basis, planned practices of stakeholders in decision-making and reasonably communicating roles and changes in decisions with top-officials were not efficiently practiced. Moreover, the practices of good modelling were not witnessed to have existed to the fullest extent. Rather, existence of a very wide gap between the academic and administrative staffs was witnessed as was reflected the case between teachers and students. The implication was such that for shortage in participative atmosphere and weaning of fairness in governance, routine practices have been there as the vicious circles of governance.

Keywords: governance, participative, stakeholders, transformative, role-assumption

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Authors: Esam Roshdy, Saleh AlRashdi, Turki Alharbi, Rawan Eskandarani, Zurina Cabilo

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Introduction/ background: Consultation in the Emergency Department constitute a major part of the work flow every day. Any delay in the consultation process have a major impact on the length of stay and patient disposition and thus affect the total waiting time of patients in the ED. King Fahad medical City in Riyadh City, Saudi Arabia is considered a major Tertiary hospital where there is high flow of patients of different categories visiting the ED. The importance of decreasing consultation time and decision for final disposition of patients was recognized and interpreted in this project to find ways to improve the patient flow in the department and thus the total patient disposition and outcome. Aim / Objectives: 1. To monitor the time of consultation for patients in the Emergency department and its impact on the length of stay of patients in the ED. 2. To detect and assess the problems that lead to long consultation times in the ED, and reach a targeted time of 2 hours for final disposition of patients, according to recognized international and our institutional consultation policy, to reach the final goal of decreasing total length of stay and thus improve the patient flow in the ED. Methods: Data was collected retrospectively for a 92 charts of consultations done in the ED over 2 month’s period. The data was analyzed to get the median of Total Consultation Time. A survey was conducted among all ED staff to determine the level of knowledge about the total consultation time and the compliance to the institutional policy target of 2 hours. A second Data sample of 168 chart was collected after awareness campaign and education of all ED staff about the importance of reaching the target consultation time and compliance to the institutional policy. Results: We have found that there is room for improvement in our overall consultation time. This was found to be more frequent with certain specialties. Our surveys have showed that many ED staff are not familiar or not compliant with our consultation policy which was not clear for everyone. Post-intervention data have showed that awareness of the importance to decrease the total consultation time and compliance alone to the targeted goal have had a huge impact on overall improvement and decreasing the time of final decision and disposition of the patient and the overall patient length of stay in the ED. Conclusion: Working on improving Consultation time in the Emergency Department is a major factor in improving overall length of stay and patient flow. This improvement helps in the overall patient disposition and satisfaction. Plan: As a continuation of our project we are planning to focus on the conflict of admission cases where more than one specialty is involved in the care of patients. We are planning to collect data on the time it takes to resolve and reach final disposition of those patients, and its impact on the length of stay and our department flow and the overall patient outcome and satisfaction.

Keywords: consultation time, impact, length of stay, in the ED

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Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

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Authors: Shih-Pin Chen, Shih-Syuan You

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This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.

Keywords: dissemblance index, forecasting, fuzzy sets, linear regression

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Authors: Gianluca Castelnuovo, Giada Pietrabissa, Gian Mauro Manzoni, Margherita Novelli, Emanuele Maria Giusti, Roberto Cattivelli, Enrico Molinari

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Diabesity could be defined as a new global epidemic of obesity and being overweight with many complications and chronic conditions. Such conditions include not only type 2 diabetes, but also cardiovascular diseases, hypertension, dyslipidemia, hypercholesterolemia, cancer, and various psychosocial and psychopathological disorders. The financial direct and indirect burden (considering also the clinical resources involved and the loss of productivity) is a real challenge in many Western health-care systems. Recently the Lancet journal defined diabetes as a 21st-century challenge. In order to promote patient compliance in diabesity treatment reducing costs, evidence-based interventions to improve weight-loss, maintain a healthy weight, and reduce related comorbidities combine different treatment approaches: dietetic, nutritional, physical, behavioral, psychological, and, in some situations, pharmacological and surgical. Moreover, new technologies can provide useful solutions in this multidisciplinary approach, above all in maintaining long-term compliance and adherence in order to ensure clinical efficacy. Psychological therapies with diet and exercise plans could better help patients in achieving weight loss outcomes, both inside hospitals and clinical centers and during out-patient follow-up sessions. In the management of chronic diseases clinical psychology play a key role due to the need of working on psychological conditions of patients, their families and their caregivers. mHealth approach could overcome limitations linked with the traditional, restricted and highly expensive in-patient treatment of many chronic pathologies: one of the best up-to-date application is the management of obesity with type 2 diabetes, where mHealth solutions can provide remote opportunities for enhancing weight reduction and reducing complications from clinical, organizational and economic perspectives. A stepped care mHealth-based approach is an interesting perspective in chronic care management of obesity with type 2 diabetes. One promising future direction could be treating obesity, considered as a chronic multifactorial disease, using a stepped-care approach: -mhealth or traditional based lifestyle psychoeducational and nutritional approach. -health professionals-driven multidisciplinary protocols tailored for each patient. -inpatient approach with the inclusion of drug therapies and other multidisciplinary treatments. -bariatric surgery with psychological and medical follow-up In the chronic care management of globesity mhealth solutions cannot substitute traditional approaches, but they can supplement some steps in clinical psychology and medicine both for obesity prevention and for weight loss management.

Keywords: clinical health psychology, mhealth, obesity, type 2 diabetes, stepped care, chronic care management

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Authors: Nomagugu Ndlovu, Kennedy H. Erlwanger, Eliton Chivandi

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In order to enhance egg production and egg quality from layer poultry, producers use synthetic feed additives that enhance nutrient digestion and absorption in the gut. Synthetic feed additives have negative effects on consumer health hence the need to replace them with natural alternatives which are deemed safer for consumer health. Hibiscus sabdariffa calyces meal has hypolipidemic, probiotic and antioxidant activities; hence we investigated the effect of fortifying Japanese quail pullet diets with its calyces meal on egg production and egg quality. A standard Japanese quail layer diet was supplemented with H. sabdariffa calyces meal at 0%, 5% and 10% in diets 1, 2 and 3, respectively. Ninety, 5-week old Japanese quail hens were randomly allocated to and fed the layer diets for 56 days. Body mass, feed intake and egg mass, width, length, shell mass and thickness, yolk mass, height and diameter, albumen mass, length, width and height, and the proximate content and fatty acid profile of the egg albumen and yolk were determined. Supplemental fortification of the Japanese quail layer diet with H. sabdariffa calyces meal had no effect on growth performance and feed intake and conversion rate of the quail (P>0.05). The meal delayed the onset of laying and reduced (P < 0.0001) the number of eggs laid. It did not affect the external and internal egg quality parameters of Japanese quail (P > 0.05). Dietary fortification with H. sabdariffa calyces meal at 10% significantly increased the dry matter and reduced the fat content of the yolk and albumin of Japanese quail eggs (P < 0.05). Dietary H. sabdariffa calyces meal reduced the total omega 3 fatty acids in the yolk and significantly increased arachidonic acid (P = 0.0019), an omega 6 fatty acid. Inclusion of Hibiscus sabdariffa meal depressed egg production, suppressed omega 3 fatty acids and increased arachidonic acid thus, using it as a dietary supplement may result in losses to producers of Japanese quail eggs and may result in eggs whose fatty acid profile can compromise consumer health.

Keywords: quail, eggs, hibiscus sabdariffa, quality

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Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

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Authors: Beyene Daniel Abrha

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Agritourism in Eritrea is increasingly threatened by climate change, manifesting through rising temperatures, shifting rainfall patterns, and resource scarcity. This study employs quantitative methods to assess the economic and environmental impacts of climate change on agritourism, utilizing metrics such as annual income fluctuations, changes in visitor numbers, and energy consumption patterns. The methodology relies on secondary data sourced from the World Bank, government reports, and academic publications to analyze the economic viability of integrating solar energy into agritourism operations. Key variables include the Benefits from Renewable Energy (BRE), encompassing cost savings from reduced energy expenses and the monetized value of avoided greenhouse gas emissions. Using a net present value (NPV) framework, the research compares the impact of solar energy against traditional fossil fuel sources by evaluating the Value of Reduced Greenhouse Gas Emissions (CO2) and the Value of Health-Related Costs (VHRC) due to air pollution. The preliminary findings of this research are of utmost importance. They indicate that the adoption of solar energy can enhance energy independence by up to 40%, reduce operational costs by 25%, and stabilize agritourism activities in climate-sensitive regions. This research aims to provide actionable insights for policymakers and stakeholders, supporting the sustainable development of agritourism in Eritrea and contributing to broader climate adaptation strategies. By employing a comprehensive cost-benefit analysis, the study highlights the economic advantages and environmental benefits of transitioning to renewable energy in the face of climate change.

Keywords: agritourism, climate change, renewable energy, cost benefit analysis, resilience, cost-benefit analysis

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Authors: Ali Al-Ghalib, Fouad Mohammad

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The identification of damage in reinforced concrete structures subjected to incremental cracking performance exploiting vibration data is recognized as a challenging topic in the published and heavily cited literature. Therefore, this paper attempts to shine light on the extent of dynamic methods when applied to reinforced concrete beams simulated with various scenarios of defects. For this purpose, three different reinforced concrete beams are tested through the course of the study. The three beams are loaded statically to failure in incremental successive load cycles and later rehabilitated. After each static load stage, the beams are tested under free-free support condition using experimental modal analysis. The beams were all of the same length and cross-sectional area (2.0x0.14x0.09)m, but they were different in concrete compressive strength and the type of damage presented. The experimental modal parameters as damage identification parameters were showed computationally expensive, time consuming and require substantial inputs and considerable expertise. Nonetheless, they were proved plausible for the condition monitoring of the current case study as well as structural changes in the course of progressive loads. It was accentuated that a satisfactory localization and quantification for structural changes (Level 2 and Level 3 of damage identification problem) can only be achieved reasonably through considering frequencies and mode shapes of a system in a proper analytical model. A convenient post analysis process for various datasets of vibration measurements for the three beams is conducted in order to extract, check and correlate the basic modal parameters; namely, natural frequency, modal damping and mode shapes. The results of the extracted modal parameters and their combination are utilized and discussed in this research as quantification parameters.

Keywords: experimental modal analysis, damage identification, structural health monitoring, reinforced concrete beam

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Authors: Burcu Babadağ Savaş, Nihal Orlu, Güler Balcı Alparslan, Ertuğrul Çolak, Cengiz Korkmaz

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Introduction/objectives: We aimed to investigate the effect of humor on pain and state anxiety in patients with rheumatoid arthritis (RA) receiving biologic intravenous (IV) infusion therapy. Method: The study sample consisted of 36 patients who met the classification criteria for RA and inclusion criteria in a rheumatology outpatient clinic at a university hospital between September 2020 and November 2021. Two sample groups were formed: the intervention group (watching a comedy movie) (n=18) and the control group (n=18). The intervention group consisted of the patient watching a comedy movie of his/her choice from an archive created by the researchers during the biological IV infusion therapy (approximately 90-120 minutes). The data collection instruments used before and after the test were the descriptive identification form, the visual analog scale (VAS), and the state anxiety scale. Results: The mean VAS scores of patients in the intervention group were 5.05 ± 2.01 in the pre-test and 2.61 ± 1.91 in the post-test. The mean state anxiety scores of patients in the intervention group were 45.94 ± 9.97 in the pre-test and 34.22 ± 6.57 in the post-test. Thus, patients who watched comedy movies during biologic IV infusion therapy in the infusion center had a greater reduction in pain scores than the control group and the effect size was small. Although there was a decrease in state anxiety scores in both groups, there was no significant difference between groups and the effect size was not relevant. Conclusions: During IV infusion therapy, watching comedy movies is recommended as a nursing care intervention for reducing pain in patients with RA in cooperation with other health professionals.

Keywords: watching comedy movie, humor, pain, anxiety, nursing, care

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Authors: Anna Siuda-Bak

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This paper adopts a comparative approach to examining the determinants of international mobility of German, Italian and British researchers who completed their doctoral education in the UK. Structured sampling and data collection techniques have been developed in order to retrieve information on participants from publicly available sources. This systematically collected data was supplemented with an on-line survey which captures participants’ job trajectories, including movements between positions, institutions and countries. In total, data on 949 German, Italian and British PhDs was collected. Logistic regression was employed to identify factors associated with one’s probability of moving outside the UK after his or her graduation. The predictor variables included factors associated with one’s PhD (field of study, ranking of the university which awarded the PhD degree) and family factors (having a child, nationality of the partner). Then, 9 constrained models were estimated to test the effect each variable has on probability of going to a specific destination, being English-speaking country, non-English speaking country or returning to the home country. The results show that females, arts and humanities graduates, and respondents with a partner from the UK are less mobile than their counterparts. The effect of the ranking of the university differed in two groups. The UK graduates from higher ranked universities were more likely to move abroad than to stay in the UK after their graduation. In contrast, non-UK natives from the same universities were less likely to be internationally mobile than non-UK natives from lower ranked universities. The nationality of the partner was the most important predictor of the specific destination choices. Graduates with partner from the home county were more likely to return home and those with a partner from the third country least likely to return.

Keywords: doctoral graduates, international mobility, nationality, UK

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Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Akram Mahdaviparsa, Tamera McCuen, Vahideh Karimimansoob

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Fire service is responsible for protecting life, assets, and natural resources from fire and other hazardous incidents. Search and rescue in unfamiliar buildings is a vital part of firefighters’ responsibilities. Providing firefighters with precise building information in an easy-to-understand format is a potential solution for mitigating the negative consequences of fire hazards. The negative effect of insufficient knowledge about a building’s indoor environment impedes firefighters’ capabilities and leads to lost property. A data rich building information modeling (BIM) is a potentially useful source in three-dimensional (3D) visualization and data/information storage for fire emergency response. Therefore, this research’s purpose is prioritizing the required information for firefighters from the most important information to the least important. A survey was carried out with firefighters working in the Norman Fire Department to obtain the importance of each building information item. The results show that “the location of exit doors, windows, corridors, elevators, and stairs”, “material of building elements”, and “building data” are the three most important information specified by firefighters. The results also implied that the 2D model of architectural, structural and way finding is more understandable in comparison with the 3D model, while the 3D model of MEP system could convey more information than the 2D model. Furthermore, color in visualization can help firefighters to understand the building information easier and quicker. Sufficient internal consistency of all responses was proven through developing the Pearson Correlation Matrix and obtaining Cronbach’s alpha of 0.916. Therefore, the results of this study are reliable and could be applied to the population.

Keywords: BIM, building fire response, ranking, visualization

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

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This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

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Authors: Thao Thi Vu, Libby Lee-Hammond, Andrew McConney

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In Vietnam, the Vietnamese language is normally used as the language of instruction. The dominance of this language places children who have a different first language such as Indigenous children at a disadvantage when commencing school. This study explores preschool teachers’ beliefs about second language acquisition in Lai Chau provinces where is typical of highland provinces of Vietnam and the proportion of Indigenous minority groups in high. Data were collected from surveys with both closed-end questions and opened-end questions. The participants in this study were more than 200 public preschool teachers who come from eight different districts in Lai Chau. An analysis of quantitative data survey is presented to indicate several practical implications, such as the connection between teachers’ knowledge background that gained from their pre-service and in-service teacher education programs regarding second language teaching for Indigenous children and their practice. It also explains some factors that influence teachers’ beliefs and perspective about Indigenous children and pedagogies in their classes.

Keywords: indigenous children, learning Vietnamese, preschool, teachers’ beliefs

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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