Search results for: data analyses
Commenced in January 2007
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Paper Count: 27122

Search results for: data analyses

21692 Analysis of Global Social Responsibilities of Social Studies Pre-Service Teachers Based on Several Variables

Authors: Zafer Cakmak, Birol Bulut, Cengiz Taskiran

Abstract:

Technological advances, the world becoming smaller and increasing world population increase our interdependence with individuals that we maybe never meet face to face. It is impossible for the modern individuals to escape global developments and their impact. Furthermore, it is very unlikely for the global societies to turn back from the path they are in. These effects of globalization in fact encumber the humankind at a certain extend. We succumb to these responsibilities for we desire a better future, a habitable world and a more peaceful life. In the present study, global responsibility levels of the participants were measured and the significance of global reactions that individuals have to develop on global issues was reinterpreted under the light of the existing literature. The study was conducted with general survey model, one of the survey methodologies General survey models are surveys conducted on the whole universe or a group, sample or sampling taken from the universe to arrive at a conclusion about the universe, which includes a high number of elements. The study was conducted with data obtained from 350 pre-service teachers attending 2016 spring semester to determine 'Global Social Responsibility' levels of social studies pre-service teachers based on several variables. Collected data were analyzed using SPSS 21.0 software. T-test and ANOVA were utilized in the data analysis.

Keywords: social studies, globalization, global social responsibility, education

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21691 Ultradrawing and Ultimate Tensile Properties of Ultrahigh Molecular Weight Polyethylene Composite Fibers Filled with Activated Nanocarbon Particles with Varying Specific Surface Areas

Authors: Wang-Xi Fan, Yi Ding, Zhong-Dan Tu, Kuo-Shien Huang, Chao-Ming Huang, Jen-Taut Yeh

Abstract:

Original and/or functionalized activated nanocarbon particles with a quoted specific surface area of 100, 500, 1000 and 1400 m2/g, respectively, were used to investigate the influence of specific surface areas of activated nanocarbon on ultra drawing and ultimate tensile properties of ultrahigh molecular weight polyethylene (UHMWPE), UHMWPE/activated nanocarbon and UHMWPE/ functionalized activated nanocarbon fibers. The specific surface areas of well dispersed functionalized activated nanocarbon in UHMWPE/functionalized activated nanocarbon fibers can positively affect their ultra drawing, orientation, ultimate tensile properties and “micro-fibril” characteristics. Excellent orientation and ultimate tensile properties of UHMWPE/nanofiller fibers can be prepared by ultra drawing the UHMWPE/functionalized activated nanocarbon as-prepared fibers with optimal contents and compositions of functionalized activated nanocarbon. The ultimate tensile strength value of the best prepared UHMWPE/functionalized activated nanocarbon drawn fiber reached 8.0 GPa, which was about 2.86 times of that of the best-prepared UHMWPE drawn fiber prepared in this study. Specific surface area, morphological and Fourier transform infrared analyses of original and functionalized activated nanocarbon and/or investigations of thermal, orientation factor and ultimate tensile properties of as-prepared and/or drawn UHMWPE/functionalized activated nanocarbon fibers were performed to understand the above-improved ultra drawing and ultimate tensile properties of the UHMWPE/functionalized activated nanocarbon fibers.

Keywords: activated nanocarbon, specific surface areas, ultradrawing, ultrahigh molecular weight polyethylene

Procedia PDF Downloads 364
21690 Design and Evaluation of Production Performance Dashboard for Achieving Oil and Gas Production Target

Authors: Ivan Ramos Sampe Immanuel, Linung Kresno Adikusumo, Liston Sitanggang

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Achieving the production targets of oil and gas in an upstream oil and gas company represents a complex undertaking necessitating collaborative engagement from a multidisciplinary team. In addition to conducting exploration activities and executing well intervention programs, an upstream oil and gas enterprise must assess the feasibility of attaining predetermined production goals. The monitoring of production performance serves as a critical activity to ensure organizational progress towards the established oil and gas performance targets. Subsequently, decisions within the upstream oil and gas management team are informed by the received information pertaining to the respective production performance. To augment the decision-making process, the implementation of a production performance dashboard emerges as a viable solution, providing an integrated and centralized tool. The deployment of a production performance dashboard manifests as an instrumental mechanism fostering a user-friendly interface for monitoring production performance, while concurrently preserving the intrinsic characteristics of granular data. The integration of diverse data sources into a unified production performance dashboard establishes a singular veritable source, thereby enhancing the organization's capacity to uphold a consolidated and authoritative foundation for its business requisites. Additionally, the heightened accessibility of the production performance dashboard to business users constitutes a compelling substantiation of its consequential impact on facilitating the monitoring of organizational targets.

Keywords: production, performance, dashboard, data analytics

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21689 A Fast Parallel and Distributed Type-2 Fuzzy Algorithm Based on Cooperative Mobile Agents Model for High Performance Image Processing

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

Abstract:

The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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21688 Electrochemical Coordination Polymers of Copper(II) Synthesis by Using Rigid and Felexible Ligands

Authors: P. Mirahmadpour, M. H. Banitaba, D. Nematollahi

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The chemistry of coordination polymers in recent years has grown exponentially not only because of their interesting architectures but also due to their various technical applications in many fields including ion exchange, chemical catalysis, small molecule separations, and drug release. The use of bridging ligands for the controlled self-assembly of one, two or three dimensional metallo-supramolecular species is the subject of serious study in last decade. Numerous different synthetic methods have been offered for the preparation of coordination polymers such as (a) diffusion from the gas phase, (b) slow diffusion of the reactants into a polymeric matrix, (c) evaporation of the solvent at ambient or reduced temperatures, (d) temperature controlled cooling, (e) precipitation or recrystallisation from a mixture of solvents and (f) hydrothermal synthesis. The electrosynthetic process suggested several advantages over conventional approaches. A general advantage of electrochemical synthesis is that it allows synthesis under milder conditions than typical solvothermal or microwave synthesis. In this work we have introduced a simple electrochemical method for growing metal coordination polymers based on copper with a flexible 2,2’-thiodiacetic acid (TDA) and rigid 1,2,4,5-benzenetetracarboxylate (BTC) ligands. The structure of coordination polymers were characterized by scanning electron microscopy (SEM), X-ray powder diffraction (XRD), elemental analysis, thermal gravimetric (TG) and differential thermal analyses (DTA). The single-crystal X-ray diffraction analysis revealed that different conformations of the ligands and different coordination modes of the carboxylate group as well as different coordination geometries of the copper atoms. Electrochemical synthesis of coordination polymers has different advantages such as faster synthesis at lower temperature in compare with conventional chemical methods and crystallization of desired materials in a single synthetic step.

Keywords: 1, 2, 4, 5-benzenetetracarboxylate, coordination polymer, copper, 2, 2’-thiodiacetic acid

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21687 European Food Safety Authority (EFSA) Safety Assessment of Food Additives: Data and Methodology Used for the Assessment of Dietary Exposure for Different European Countries and Population Groups

Authors: Petra Gergelova, Sofia Ioannidou, Davide Arcella, Alexandra Tard, Polly E. Boon, Oliver Lindtner, Christina Tlustos, Jean-Charles Leblanc

Abstract:

Objectives: To assess chronic dietary exposure to food additives in different European countries and population groups. Method and Design: The European Food Safety Authority’s (EFSA) Panel on Food Additives and Nutrient Sources added to Food (ANS) estimates chronic dietary exposure to food additives with the purpose of re-evaluating food additives that were previously authorized in Europe. For this, EFSA uses concentration values (usage and/or analytical occurrence data) reported through regular public calls for data by food industry and European countries. These are combined, at individual level, with national food consumption data from the EFSA Comprehensive European Food Consumption Database including data from 33 dietary surveys from 19 European countries and considering six different population groups (infants, toddlers, children, adolescents, adults and the elderly). EFSA ANS Panel estimates dietary exposure for each individual in the EFSA Comprehensive Database by combining the occurrence levels per food group with their corresponding consumption amount per kg body weight. An individual average exposure per day is calculated, resulting in distributions of individual exposures per survey and population group. Based on these distributions, the average and 95th percentile of exposure is calculated per survey and per population group. Dietary exposure is assessed based on two different sets of data: (a) Maximum permitted levels (MPLs) of use set down in the EU legislation (defined as regulatory maximum level exposure assessment scenario) and (b) usage levels and/or analytical occurrence data (defined as refined exposure assessment scenario). The refined exposure assessment scenario is sub-divided into the brand-loyal consumer scenario and the non-brand-loyal consumer scenario. For the brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the highest reported usage/analytical level for one food group, and at the mean level for the remaining food groups. For the non-brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the mean reported usage/analytical level for all food groups. An additional exposure from sources other than direct addition of food additives (i.e. natural presence, contaminants, and carriers of food additives) is also estimated, as appropriate. Results: Since 2014, this methodology has been applied in about 30 food additive exposure assessments conducted as part of scientific opinions of the EFSA ANS Panel. For example, under the non-brand-loyal scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 5.9 and 8.7 mg/kg body weight/day, respectively. The same estimates under the brand-loyal scenario in toddlers resulted in exposures of 8.1 and 20.7 mg/kg body weight/day, respectively. For the regulatory maximum level exposure assessment scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 11.9 and 30.3 mg/kg body weight/day, respectively. Conclusions: Detailed and up-to-date information on food additive concentration values (usage and/or analytical occurrence data) and food consumption data enable the assessment of chronic dietary exposure to food additives to more realistic levels.

Keywords: α-tocopherol, ammonium phosphatides, dietary exposure assessment, European Food Safety Authority, food additives, food consumption data

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21686 Recommendations as a Key Aspect for Online Learning Personalization: Perceptions of Teachers and Students

Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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21685 The Effect of Vertical Integration on Operational Performance: Evaluating Physician Employment in Hospitals

Authors: Gary Young, David Zepeda, Gilbert Nyaga

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This study investigated whether vertical integration of hospitals and physicians is associated with better care for patients with cardiac conditions. A dramatic change in the U.S. hospital industry is the integration of hospital and physicians through hospital acquisition of physician practices. Yet, there is little evidence regarding whether this form of vertical integration leads to better operational performance of hospitals. The study was conducted as an observational investigation based on a pooled, cross-sectional database. The study sample comprised over hospitals in the State of California. The time frame for the study was 2010 to 2012. The key performance measure was hospitals’ degree of compliance with performance criteria set out by the federal government for managing patients with cardiac conditions. These criteria relate to the types of clinical tests and medications that hospitals should follow for cardiac patients but hospital compliance requires the cooperation of a hospital’s physicians. Data for this measure was obtained from a federal website that presents performance scores for U.S. hospitals. The key independent variable was the percentage of cardiologists that a hospital employs (versus cardiologists who are affiliated but not employed by the hospital). Data for this measure was obtained from the State of California which requires hospitals to report financial and operation data each year including numbers of employed physicians. Other characteristics of hospitals (e.g., information technology for cardiac care, volume of cardiac patients) were also evaluated as possible complements or substitutes for physician employment by hospitals. Additional sources of data included the American Hospital Association and the U.S. Census. Empirical models were estimated with generalized estimating equations (GEE). Findings suggest that physician employment is positively associated with better hospital performance for cardiac care. However, findings also suggest that information technology is a substitute for physician employment.

Keywords: physician employment, hospitals, verical integration, cardiac care

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21684 Urbanization and Income Inequality in Thailand

Authors: Acumsiri Tantikarnpanit

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This paper aims to examine the relationship between urbanization and income inequality in Thailand during the period 2002–2020. Using a panel of data for 76 provinces collected from Thailand’s National Statistical Office (Labor Force Survey: LFS), as well as geospatial data from the U.S. Air Force Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite Day/Night band (VIIRS-DNB) satellite for nineteen selected years. This paper employs two different definitions to identify urban areas: 1) Urban areas defined by Thailand's National Statistical Office (Labor Force Survey: LFS), and 2) Urban areas estimated using nighttime light data from the DMSP and VIIRS-DNB satellite. The second method includes two sub-categories: 2.1) Determining urban areas by calculating nighttime light density with a population density of 300 people per square kilometer, and 2.2) Calculating urban areas based on nighttime light density corresponding to a population density of 1,500 people per square kilometer. The empirical analysis based on Ordinary Least Squares (OLS), fixed effects, and random effects models reveals a consistent U-shaped relationship between income inequality and urbanization. The findings from the econometric analysis demonstrate that urbanization or population density has a significant and negative impact on income inequality. Moreover, the square of urbanization shows a statistically significant positive impact on income inequality. Additionally, there is a negative association between logarithmically transformed income and income inequality. This paper also proposes the inclusion of satellite imagery, geospatial data, and spatial econometric techniques in future studies to conduct quantitative analysis of spatial relationships.

Keywords: income inequality, nighttime light, population density, Thailand, urbanization

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21683 Mesovarial Morphological Changes in Offspring Exposed to Maternal Cold Stress

Authors: Ariunaa.S., Javzandulam E., Chimegsaikhan S., Altantsetseg B., Oyungerel S., Bat-Erdene T., Naranbaatar S., Otgonbayar B., Suvdaa N., Tumenbayar B.

Abstract:

Introduction: Prenatal stress has been linked to heightened allergy sensitivity in offspring. However, there is a notable absence of research on the mesovarium structure of offspring born from mothers subjected to cold stress during pregnancy. Understanding the impact of maternal cold stress on the mesovarium structure could provide valuable insights into reproductive health outcomes in offspring. Objective: This study aims to investigate structural changes in the mesovarium of offspring born from cold-stress affected rats. Material and Methods: 20 female Westar rats weighing around 200g were chosen and evenly divided into four containers; then, 2-3 male rats were introduced to each container. The Papanicolaou method was used to estimate the spermatozoa and estrus period from vaginal swabs taken from female rats at 8:00 a.m. Female rats examined with the presence of spermatozoa during the estrous phase of the estrous cycle are defined as pregnant. Pregnant rats are divided into experimental and control groups. The experimental group was stressed using the model of severe and chronic cold stress for 30 days. They were exposed to cold stress for 3 hours each morning between 8:00 and 11:00 o’clock at a temperature of minus 15 degrees Celsius. The control group was kept under normal laboratory conditions. Newborn female rats from both experimental and control groups were selected. At 2 months of age, rats were euthanized by decapitation, and their mesovaria were collected. Tissues were fixed in 4% formalin, embedded in paraffin, and sectioned into 5μm thick slices. The sections were stained with H&E and digitized by digital microscope. The area of brown fat and inflammatory infiltrations were quantified using Image J software. The blood cortisol levels were measured using ELISA. Data are expressed as the mean ± standard error of the mean (SEM). The Mann-Whitney test was used to compare the two groups. All analyses were performed using Prism (GraphPad Software). A p-value of < 0.05 was considered statistically significant. Result: Offspring born from stressed mothers exhibited significant physiological differences compared to the control group. Specifically, the body weight of offspring from stressed mothers was significantly lower than the control group (p=0.0002). Conversely, the cortisol level in offspring from stressed mothers was significantly higher (p=0.0446). Offspring born from stressed mothers showed a statistically significant increase in brown fat area compared to the control group (p=0.01). Additionally, offspring from stressed mothers had a significantly higher number of inflammatory infiltrates in their mesovarium compared to the control group (p<0.047). These results indicate the profound impact of maternal stress on offspring physiology, affecting body weight, stress hormone levels, metabolic characteristics, and inflammatory responses. Conclusion: Exposure to cold stress during pregnancy has significant repercussions on offspring physiology. Our findings demonstrate that cold stress exposure leads to increased blood cortisol levels, brown fat accumulation, and inflammatory cell infiltration in offspring. These results underscore the profound impact of maternal stress on offspring health and highlight the importance of mitigating environmental stressors during pregnancy to promote optimal offspring outcomes.

Keywords: brown fat, cold stress during pregnancy, inflammation, mesovarium

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21682 Work Related Musculoskeletal Disorder: A Case Study of Office Computer Users in Nigerian Content Development and Monitoring Board, Yenagoa, Bayelsa State, Nigeria

Authors: Tamadu Perry Egedegu

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Rapid growth in the use of electronic data has affected both the employee and work place. Our experience shows that jobs that have multiple risk factors have a greater likelihood of causing Work Related Musculoskeletal Disorder (WRMSDs), depending on the duration, frequency and/or magnitude of exposure to each. The study investigated musculoskeletal disorder among office workers. Thus, it is important that ergonomic risk factors be considered in light of their combined effect in causing or contributing to WRMSDs. Fast technological growth in the use of electronic system; have affected both workers and the work environment. Awkward posture and long hours in front of these visual display terminals can result in work-related musculoskeletal disorders (WRMSD). The study shall contribute to the awareness creation on the causes and consequences of WRMSDs due to lack of ergonomics training. The study was conducted using an observational cross-sectional design. A sample of 109 respondents was drawn from the target population through purposive sampling method. The sources of data were both primary and secondary. Primary data were collected through questionnaires and secondary data were sourced from journals, textbooks, and internet materials. Questionnaires were the main instrument for data collection and were designed in a YES or NO format according to the study objectives. Content validity approval was used to ensure that the variables were adequately covered. The reliability of the instrument was done through test-retest method, yielding a reliability index at 0.84. The data collected from the field were analyzed with a descriptive statistics of chart, percentage and mean. The study found that the most affected body regions were the upper back, followed by the lower back, neck, wrist, shoulder and eyes, while the least affected body parts were the knee calf and the ankle. Furthermore, the prevalence of work-related 'musculoskeletal' malfunctioning was linked with long working hours (6 - 8 hrs.) per day, lack of back support on their seats, glare on the monitor, inadequate regular break, repetitive motion of the upper limbs, and wrist when using the computer. Finally, based on these findings some recommendations were made to reduce the prevalent of WRMSDs among office workers.

Keywords: work related musculoskeletal disorder, Nigeria, office computer users, ergonomic risk factor

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21681 Bank Loans and the Business Cycle: The Case of the Czech Republic

Authors: Libena Cernohorska, Jan Cernohorsky

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This article aims to evaluate the impact of loans provided within the Czech banking sector on the growth of the Czech economy. The article is based on research of current scientific findings in respect to bank loans and economic development. The paper is based on data taken from the Czech Statistical Office on the development of the gross domestic product and data from the Czech National Bank on the development of loans from the period 2004-2015. Links between selected variables are tested using Granger causality tests. The results calculated confirm the hypothesis of the impact of the loans on economic growth, with a six-month delay. The results thus correspond to the standard economic findings and results of most previous studies.

Keywords: bank, business cycle, economic growth, loans

Procedia PDF Downloads 123
21680 Automatic Differential Diagnosis of Melanocytic Skin Tumours Using Ultrasound and Spectrophotometric Data

Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

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21679 Effect of Particles Size and Volume Fraction Concentration on the Thermal Conductivity and Thermal Diffusivity of Al2O3 Nanofluids Measured Using Transient Hot–Wire Laser Beam Deflection Technique

Authors: W. Mahmood Mat Yunus, Faris Mohammed Ali, Zainal Abidin Talib

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In this study we present new data for the thermal conductivity enhancement in four nanofluids containing 11, 25, 50, 63 nm diameter aluminum oxide (Al2O3) nanoparticles in distilled water. The nanofluids were prepared using single step method (i.e. by dispersing nanoparticle directly in base fluid) which was gathered in ultrasonic device for approximately 7 hours. The transient hot-wire laser beam displacement technique was used to measure the thermal conductivity and thermal diffusivity of the prepared nanofluids. The thermal conductivity and thermal diffusivity were obtained by fitting the experimental data to the numerical data simulated for aluminum oxide in distilled water. The results show that the thermal conductivity and thermal diffusivity of nanofluids increases in non-linear behavior as the particle size increases. While, the thermal conductivity and thermal diffusivity of Al2O3 nanofluids was observed increasing linearly with concentration as the volume fraction concentration increases. We believe that the interfacial layer between solid/fluid is the main factor for the enhancement of thermal conductivity and thermal diffusivity of Al2O3 nanofluids in the present work.

Keywords: transient hot wire-laser beam technique, Al2O3 nanofluid, particle size, volume fraction concentration

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21678 Hydrology and Hydraulics Analysis of Beko Abo Dam and Appurtenant Structre Design, Ethiopia

Authors: Azazhu Wassie

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This study tried to evaluate the maximum design flood for appurtenance structure design using the given climatological and hydrological data analysis on the referenced study area. The maximum design flood is determined by using flood frequency analysis. Using this method, the peak discharge is 32,583.67 m3/s, but the data is transferred because the dam site is not on the gauged station. Then the peak discharge becomes 38,115 m3/s. The study was conducted in June 2023. This dam is built across a river to create a reservoir on its upstream side for impounding water. The water stored in the reservoir is used for various purposes, such as irrigation, hydropower, navigation, fishing, etc. The total average volume of annual runoff is estimated to be 115.1 billion m3. The total potential of the land for irrigation development can go beyond 3 million ha.

Keywords: dam design, flow duration curve, peak flood, rainfall, reservoir capacity, risk and reliability

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21677 Feasibility Study of Wind Energy Potential in Turkey: Case Study of Catalca District in Istanbul

Authors: Mohammed Wadi, Bedri Kekezoglu, Mustafa Baysal, Mehmet Rida Tur, Abdulfetah Shobole

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This paper investigates the technical evaluation of the wind potential for present and future investments in Turkey taking into account the feasibility of sites, installments, operation, and maintenance. This evaluation based on the hourly measured wind speed data for the three years 2008–2010 at 30 m height for Çatalca district. These data were obtained from national meteorology station in Istanbul–Republic of Turkey are analyzed in order to evaluate the feasibility of wind power potential and to assure supreme assortment of wind turbines installing for the area of interest. Furthermore, the data are extrapolated and analyzed at 60 m and 80 m regarding the variability of roughness factor. Weibull bi-parameter probability function is used to approximate monthly and annually wind potential and power density based on three calculation methods namely, the approximated, the graphical and the energy pattern factor methods. The annual mean wind power densities were to be 400.31, 540.08 and 611.02 W/m² for 30, 60, and 80 m heights respectively. Simulation results prove that the analyzed area is an appropriate place for constructing large-scale wind farms.

Keywords: wind potential in Turkey, Weibull bi-parameter probability function, the approximated method, the graphical method, the energy pattern factor method, capacity factor

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21676 Using Geographic Information Systems in the Desertification Risk’s Cartography: Case South of the Aurès Region, Algeria

Authors: Benmessaoud Hassen

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The sensitivity to the desertification map of the south of Aurès region has been elaborated by the crossing of four thematic layers capable to have an impact on the process of desertification. The following step is inspired of MEDALUS (Mediterranean desertification and land Use), which use qualitative index to define the environment zones sensitive to the desertification. The cartographical information of vegetation, the climate, the soil and the socioeconomic state descended from cartographic data transformed to numerical data then seized on, structured and managed by an algorithm dedicated to a geographical information system. In step with information, each layer makes object of 3 or 4 classes, the geometrical median of the four layers used are leaded to sensitivity classes (ISD) of different mapped environment.

Keywords: information systems, thematic layers, the sensitivity to the desertification map, concept MEDALUS, South of Aurès

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21675 The Impact of Liquid Glass-Infused Lignin Waste Particles on Performance of Polyurethane Foam for Building Industry

Authors: Agnė Kairyte, Saulius Vaitkus

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The gradual depletion of fossil feedstock and growing environmental concerns attracted extensive attention to natural resources due to their low cost, high abundance, renewability, sustainability, and biodegradability. Lignin is a significant by-product of the pulp and paper industry, having unique functional groups. Recently it became interesting for the manufacturing of high value-added products such as polyurethane and polyisocyanurate foams. This study focuses on the development of high-performance polyurethane foams with various amounts of lignin as a filler. It is determined that the incorporation of lignin as a filler material results in brittle and hard products due to the low molecular mobility of isocyanates and the inherent stiffness of lignin. Therefore, the current study analyses new techniques and possibilities of liquid glass infusion onto the surface of lignin particles to reduce the negative aspects and improve the performance characteristics of the modified foams. The foams modified with sole lignin and liquid glass-infused lignin had an apparent density ranging from 35 kg/m3 to 45 kg/m3 and closed-cell content (80–90%). The incorporation of sole lignin reduced the compressive and tensile strengths and increased dimensional stability and water absorption, while the contrary results were observed for polyurethane foams with liquid glass-infused lignin particles. The effect on rheological parameters of lignin and liquid glass infused lignin modified polyurethane premixes and morphology of polyurethane foam products were monitored to optimize the conditions and reveal the significant influence of the interaction between particles and polymer matrix.

Keywords: filler, lignin waste, liquid glass, polymer matrix, polyurethane foam, sustainability

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21674 Saponins vs Anthraquinones: Different Chemicals, Similar Ecological Roles in Marine Symbioses

Authors: Guillaume Caulier, Lola Brasseur, Patrick Flammang, Pascal Gerbaux, Igor Eeckhaut

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Saponins and quinones are two major groups of secondary metabolites widely distributed in the biosphere. More specifically, triterpenoid saponins and anthraquinones are mainly found in a wide variety of plants, bacteria and fungi. In the animal kingdom, these natural organic compounds are rare and only found in small quantities in arthropods, marine sponges and echinoderms. In this last group, triterpenoid saponins are specific to holothuroids (sea cucumbers) while anthraquinones are the chemical signature of crinoids (feather stars). Depending on the species, they present different molecular cocktails. Despite presenting different chemical properties, these molecules share numerous similarities. This study compares the biological distribution, the pharmacological effects and the ecological roles of holothuroid saponins and crinoid anthraquinones. Both of them have been defined as allomones repelling predators and parasites (i.e. chemical defense) and have interesting pharmacological properties (e.g. anti-bacterial, anti-fungal, anti-cancer). Our study investigates the chemical ecology of two symbiotic associations models; between the snapping shrimp Synalpheus stimpsonii associated with crinoids and the Harlequin crab Lissocarcinus orbicularis associated with holothuroids. Using behavioral experiments in olfactometers, chemical extractions and mass spectrometry analyses, we discovered that saponins and anthraquinones present a second ecological role: the attraction of obligatory symbionts towards their hosts. They can, therefore, be defined as kairomones. This highlights a new paradigm in marine chemical ecology: Chemical repellents are attractants to obligatory symbionts because they constitute host specific chemical signatures.

Keywords: anthraquinones, kairomones, marine symbiosis, saponins, attractant

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21673 Exploring the Intrinsic Ecology and Suitable Density of Historic Districts Through a Comparative Analysis of Ancient and Modern Ecological Smart Practices

Authors: HU Changjuan, Gong Cong, Long Hao

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Although urban ecological policies and the public's aspiration for livable environments have expedited the pace of ecological revitalization, historic districts that have evolved through natural ecological processes often become obsolete and less habitable amid rapid urbanization. This raises a critical question about historic districts inherently incapable of being ecological and livable. The thriving concept of ‘intrinsic ecology,’ characterized by its ability to transform city-district systems into healthy ecosystems with diverse environments, stable functions, and rapid restoration capabilities, holds potential for guiding the integration of ancient and modern ecological wisdom while supporting the dynamic involvement of cultures. This study explores the intrinsic ecology of historic districts from three aspects: 1) Population Density: By comparing the population density before urban population expansion to the present day, determine the reasonable population density for historic districts. 2) Building Density: Using the ‘Space-mate’ tool for comparative analysis, form a spatial matrix to explore the intrinsic ecology of building density in Chinese historic districts. 3) Green Capacity Ratio: By using ecological districts as control samples, conduct dual comparative analyses (related comparison and upgraded comparison) to determine the intrinsic ecological advantages of the two-dimensional and three-dimensional green volume in historic districts. The study inform a density optimization strategy that supports cultural, social, natural, and economic ecology, contributing to the creation of eco-historic districts.

Keywords: eco-historic districts, intrinsic ecology, suitable density, green capacity ratio.

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21672 Electrical Decomposition of Time Series of Power Consumption

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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21671 Re-Engineering Management Process in IRAN’s Smart Schools

Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

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21670 Association Between Grandchild Caring With Different Household Structures and Depression at Later Life: A Cross-Sectional Study in India

Authors: Papai Barman, Harihar Sahoo

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With increasing life expectancy, urbanization, and adult out migration, elder people live without adult child and most of time responsible for grandchild caring while the care is needed for them. On this line, the current study examined the association between grandchild caring (GCC) with different household structures and depression among elderly (60+) grandparents (GP) living in India using Longitudinal Aging Study in India (LASI), 2017-18. HH structure was defined as the skipped-generation household (SGH) where GP and GC lived together without middle generation and the multi-generation household (MGH) where more than two generations lived together. GCC was defined by two categories, compulsive and non-compulsive caring. CES-D depression scale was utilized to measure GP’s mental health. Socio-economic characteristics, chronic diseases, and health behavior were controlled to get the effect of HH structure and GCC considered key explanatory variables. Bivariate analyses showed that the prevalence of elderly lived in SGH in India (2.5%). Prevalence of compulsive caring was found 16.3% in MGH and 51.1% in SGH. Prevalence of depressions was found nearly 37.1 and 49.5% among the GPs responsible for GCC in MGH and SGH, respectively. Using Biprobit and margins results, GPs lived in SGH were 0.40 times (dy/dx=0.40, p<0.001) more likely to report depression than GPs lived in MGH, given the condition on compulsive caring. Ensuring SDG goal-3, health aging, and giving more social security to the elder people responsible for caring while they are needed care at later life, the current study may improve the existing knowledge and help policy makers to make an intervention on this most vulnerable people, especially for the elderly people living in SGH and responsible for caring.

Keywords: household structure, grandchild caring, skipped-generation household, multi-generation household, depression, mental health, India

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21669 The Methodology of Out-Migration in Georgia

Authors: Shorena Tsiklauri

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Out-migration is an important issue for Georgia as well as since independence has loosed due to emigration one fifth of its population. During Soviet time out-migration from USSR was almost impossible and one of the most important instruments in regulating population movement within the Soviet Union was the system of compulsory residential registrations, so-called “propiska”. Since independent here was not any regulation for migration from Georgia. The majorities of Georgian migrants go abroad by tourist visa and then overstay, becoming the irregular labor migrants. The official statistics on migration published for this period was based on the administrative system of population registration, were insignificant in terms of numbers and did not represent the real scope of these migration movements. This paper discusses the data quality and methodology of migration statistics in Georgia and we are going to answer the questions: what is the real reason of increasing immigration flows according to the official numbers since 2000s?

Keywords: data quality, Georgia, methodology, migration

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21668 Evaluation of Low Power Wi-Fi Modules in Simulated Ocean Environments

Authors: Gabriel Chenevert, Abhilash Arora, Zeljko Pantic

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The major problem underwater acoustic communication faces is the low data rate due to low signal frequency. By contrast, the Wi-Fi communication protocol offers high throughput but limited operating range due to the attenuation effect of the sea and ocean medium. However, short-range near-field underwater wireless power transfer systems offer an environment where Wi-Fi communication can be effectively integrated to collect data and deliver instructions to sensors in underwater sensor networks. In this paper, low-power, low-cost off-the-shelf Wi-Fi modules are explored experimentally for four selected parameters for different distances between units and water salinities. The results reveal a shorter operating range and stronger dependence on water salinity than reported so far for high-end Wi-Fi modules.

Keywords: Wi-Fi, wireless power transfer, underwater communications, ESP

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21667 Numerical Modelling of Wind Dispersal Seeds of Bromeliad Tillandsia recurvata L. (L.) Attached to Electric Power Lines

Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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21666 Analysis of Impact of Air Pollution over Megacity Delhi Due to Agricultural Biomass Burning in the Neighbouring States

Authors: Ankur P. Sati, Manju Mohan

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The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

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21665 Nonlinear Finite Element Modeling of Deep Beam Resting on Linear and Nonlinear Random Soil

Authors: M. Seguini, D. Nedjar

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An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.

Keywords: finite element method, geometric nonlinearity, material nonlinearity, soil-structure interaction, spatial variability

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21664 'CardioCare': A Cutting-Edge Fusion of IoT and Machine Learning to Bridge the Gap in Cardiovascular Risk Management

Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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21663 Descriptive Analysis of Community-Based Needs among Asylum Seekers in New England before and after COVID-19

Authors: Viknesh Kasthuri, Victoria Angenent-Mari, Jade Wexler

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The COVID-19 pandemic dramatically altered the landscape of asylum medicine. Brown Human Rights Asylum Clinic (BHRAC) is a medical-student-run asylum clinic that provides pro-bono medical evaluations and forensic affidavits for individuals seeking asylum in New England. After the outbreak of COVID-19 in March 2020, BHRAC experienced numerous changes both in the number of clients requesting services as well as in the resource needs of these clients. Uniquely, BHRAC assesses the needs of clients during their affidavit interview and seeks to address these needs by connecting clients to local community organizations and resources. Data regarding the specific needs of clients range from 2019-present day. Analysis of internal BHRAC’s internal data suggested a small increase in requests for assistance with light and gas (from 5% of total resource requests pre-COVID to 11%), as well as a decrease in requests for mental health services (from 20% of resources pre-COVID to 13% post-COVID). Furthermore, BHRAC witnessed a decline in clinic volume during the second half of 2020. In short, our data suggest that the pandemic affected asylum seekers' access to medico-legal services and the resources they need. Future research with larger sample sizes and in other geographic locations is required to determine the holistic impact of the COVID-19 pandemic on asylum seekers.

Keywords: asylum clinic, asylum medicine, COVID, social determinants of health

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