Search results for: forward modeling

Authors: A. A. Vasin, N. V. Klassen, A. M. Likhter

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Water suspensions of in-organic (metals and oxides) and organic nano-objects (chitozan and collagen) were subjected to the treatment of direct and alternative electrical fields. In addition to quasi-periodical spatial patterning resonance-like performance of spatial distributions of these suspensions has been found at low frequencies of alternating electrical field. These resonances are explained as the result of creation of equilibrium states of groups of charged nano-objects with opposite signs of charges at the interparticle distances where the forces of Coulomb attraction are compensated by the repulsion forces induced by relatively negative polarization of hydrated regions surrounding the nanoparticles with respect to pure water. The low frequencies of these resonances are explained by comparatively big distances between the particles and their big masses with t\respect to masses of atoms constituting molecules with high resonance frequencies. These new resonances open a new approach to detailed modeling and understanding of mechanisms of the influence of electrical fields on the functioning of internal organs of living organisms at the level of cells and neurons.

Keywords: bio-polymers, chitosan, collagen, nanoparticles, coulomb attraction, polarization repulsion, periodical patterning, electrical low frequency resonances, transformations

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Authors: Vivienne Langhorne, Helen Sharpe

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Body dissatisfaction begins developing in middle childhood, with wide-ranging implications for mental health and well-being. Previous research on parent behavior has focused on the role of explicit parent behaviors in adolescent and young adult body dissatisfaction, leaving a gap in understanding how implicit parent behaviors relate to body dissatisfaction in childhood. The current study investigated how implicit parent behavior (such as modeling own body dissatisfaction and dieting) relates to parent and child body dissatisfaction. It was hypothesized that implicit behavior would be directly related to parent and child body dissatisfaction and mediate the relationship between the two. Furthermore, this study aimed to examine child gender as a potential moderator in this mediation, as research shows that boys and girls experience body dissatisfaction differently. This study analyzed survey responses on parent body dissatisfaction, implicit behavior, and child body dissatisfaction measures from a sample of 166 parent-child dyads with children between the ages of 6 to 9 years old. Regression analyses revealed that parent body dissatisfaction is related to both parent-implicit behavior and child body dissatisfaction. However, implicit behavior did not mediate the relationship between the two body dissatisfaction variables. Additionally, the results of moderated mediation indicated there were no child gender differences in the strength of the association between parental implicit behaviors and child body dissatisfaction. These findings highlight the need for further research into the mechanisms behind parent and child body dissatisfaction to better understand the process through which intergenerational transmission occurs.

Keywords: body dissatisfaction, implicit behaviour, middle childhood, parenting

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Authors: Farzaneh Khorram

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This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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Authors: Benjamen Nathaniel, Eludiora Safiriyu Ijiyemi, Egume Oneme Lucky

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A review on machine translation systems shows that a lot of computational artefacts has been carried out to translate written or spoken texts from a source language to Yorùbá language through Machine Translation systems. However, there are no work on French to Yorùbá language machine translation system; hence, the study investigated the process involved in the translation of French-to-Yorùbá language equivalent with the view to adopting a rule- based MT approach to build a Machine Translation framework from simple sentences administered through questionnaire. Articles and relevant textbooks were reviewed with key speakers of both languages interviewed to find out the processes involved in the translation of French language and their equivalent in Yorùbálanguage simple sentences using home domain terminologies. Achieving this, a model was formulated using phrase grammar structure, re-write rule, parse tree, automata theory- based techniques, designed and implemented respectively with unified modeling language (UML) and python programming language. Analysing the result, it was observed when carrying out the result that, the Machine Translation system performed 18.45% above Experimental Subject Respondent and 2.7% below Linguistics Expert when analysed with word orthography, sentence syntax and semantic correctness of the sentences. And, when compared with Google Machine Translation system, it was noticed that the developed system performed better on lexicons of the target language.

Keywords: machine translation (MT), rule-based, French language, Yoru`ba´ language

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Authors: Maximilian Richter

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Implementing shared autonomous electric vehicles (SAEVs) has many advantages. The main advantages are achieved when SAEVs are offered as on-demand services by a fleet operator. However, autonomous mobility on demand (AMoD) will be distributed nationwide only if a fleet operation is economically profitable for the operator. This paper proposes a microscopic approach to modeling two implementation scenarios of an AMoD fleet. The city of Zurich is used as a case study, with the results and findings being generalizable to other similar European and North American cities. The data are based on the traffic model of the canton of Zurich (Gesamtverkehrsmodell des Kantons Zürich (GVM-ZH)). To determine financial profitability, demand is based on the simulation results and combined with analyzing the costs of a SAEV per kilometer. The results demonstrate that depending on the scenario; journeys can be offered profitably to customers for CHF 0.3 up to CHF 0.4 per kilometer. While larger fleets allowed for lower price levels and increased profits in the long term, smaller fleets exhibit elevated efficiency levels and profit opportunities per day. The paper concludes with recommendations for how fleet operators can prepare themselves to maximize profit in the autonomous future.

Keywords: autonomous vehicle, mobility on demand, traffic simulation, fleet provider

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Mbambu K. Shaloom, Biba Kalengo, Pierre Echard, Olivier Gilson, Tshiswaka Ngalula, Léonard Kabeya Mukeba Yakasham

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In this 21st century, while design and eco-construction continue to be governed by considerations of functionality, safety, comfort and initial investment cost. Today, the principles of sustainable development lead us to think over longer time frames, to take into account new issues and the operating costs of green energy. DR Congo (sub-Saharan Africa) still suffers from the unusability of certain bio-sourced materials (such as bamboo, branches, etc.) and the lack of energy, i.e. 9% of the population has access to electricity and 21% of access to water. Ecoconstruction involves the energy performance of buildings which carry out a dynamic thermal simulation, which targets the different assumptions and conventional parameters (weather, occupancy, materials, thermal comfort, green energies, etc.). The objective of this article is to remedy the thermal, economic and technical artisanal problems in an aqueous environment in the city of Kinshasa. In order to establish a behavioral model to mitigate environmental impacts on architectural modifications and low-cost eco-construction through the approach of innovation and design thinking.

Keywords: thermal comfort, bio-sourced material, eco-architecture, eco-construction, squatting, design thinking

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Achiron Anat, Mathilda Mandel, Mayust Sue, Achiron Reuven, Gurevich Michael

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Introduction: As coronavirus disease 2019 (COVID-19) vaccination is currently spreading around the world, it is of importance to assess the ability of multiple sclerosis (MS) patients to mount an appropriate immune response to the vaccine in the context of disease-modifying treatments (DMT’s). Objectives: Evaluate immunity generated following COVID-19 vaccination in MS patients, and assess factors contributing to protective humoral and cellular immune responses in MS patients vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus infection. Methods: Review our recent data related to (1) the safety of PfizerBNT162b2 COVID-19 mRNA vaccine in adult MS patients; (2) the humoral post-vaccination SARS-CoV2 IgG response in MS vaccinees using anti-spike protein-based serology; and (3) the cellular immune response of memory B-cells specific for SARS-CoV-2 receptor-binding domain (RBD) and memory T-cells secreting IFN-g and/or IL-2 in response to SARS-CoV2 peptides using ELISpot/Fluorospot assays in MS patients either untreated or under treatment with fingolimod, cladribine, or ocrelizumab; (4) covariate parameters related to mounting protective immune responses. Results: COVID-19 vaccine proved safe in MS patients, and the adverse event profile was mainly characterised by pain at the injection site, fatigue, and headache. Not any increased risk of relapse activity was noted and the rate of patients with acute relapse was comparable to the relapse rate in non-vaccinated patients during the corresponding follow-up period. A mild increase in the rate of adverse events was noted in younger MS patients, among patients with lower disability, and in patients treated with DMTs. Following COVID-19 vaccination protective humoral immune response was significantly decreased in fingolimod- and ocrelizumab- treated MS patients. SARS-CoV2 specific B-cell and T-cell cellular responses were respectively decreased. Untreated MS patients and patients treated with cladribine demonstrated protective humoral and cellular immune responses, similar to healthy vaccinated subjects. Conclusions: COVID-19 BNT162b2 vaccine proved as safe for MS patients. No increased risk of relapse activity was noted post-vaccination. Although COVID-19 vaccination is new, accumulated data demonstrate differences in immune responses under various DMT’s. This knowledge can help to construct appropriate COVID-19 vaccine guidelines to ensure proper immune responses for MS patients.

Keywords: covid-19, vaccination, multiple sclerosis, IgG

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Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert

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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.

Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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Authors: Morena Paulisic, Marli Gonan Bozac

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Business organization and management in theory are typically presented as gender- neutral. Although in practice female contribution to corporation is not questionable, gender diversity in top management of corporation is and that especially in emerging countries like Croatia. This paper brings insights into obstacles and problems which should be overcome. Furthermore, gives an introspective view on the most important promotion and motivation factors of powerful female CEOs in Croatia. The goal was to clarify perception and performance of female CEOs that contributed to their success and to determine mutual characteristics of women in corporate entrepreneurship regarding the motivation. For our study we used survey instrument that was developed for this research. The research methods used were: table research, field research, generalization method, comparative method, and statistical method (descriptive statistics and Pearson’s Chi-square test). Some result showed us that today even more women in corporations are not likely to accept more engagement at work if it harms their families (2003 – 31.9% in 2013 – 33.8%) although their main motivating factor is still interested job (2003 – 95.8%; in 2013-100%). It is also significant that 78.8 % of Croatian top managers (2013) think that women managers in Croatia are insufficiently spoken and written about, and that the reasons for this are that: (1) the society underestimates their ability (37.9%); (2) women underestimate themselves (22.4%); (3) the society still mainly focuses on male managers (20.7%) and (4) women managers avoid interviews and appearing on front pages (19%). The environment still “blocks” the natural course of advancement of women managers in organisations (entrepreneurship in general) and the main obstacle is that women must always or almost always be more capable than men in order to succeed (96.6%). Based on survey results on longitudinal research conducted in 2003 (return rate 30,8%) and 2013 (return rate 29,2%) in Croatia we expand understanding of determination indicators of corporate female entrepreneurship. Theoretically in practice gender structure at the management level (executive management, management board and supervisory board) throw years (2011- 2014) have positive score but still women remain significantly underrepresented at those positions. Findings from different sources have shown that diversity at the top of corporations’ correlates with better performance. In this paper, we have contributed to research on gender in corporate entrepreneurship by offering experiences from successful female CEOs and explanation why in social responsible society women with their characteristics can support needed changes and construct different way forward for corporations. Based on research result we can conclude that in future underrepresentation of female in corporate entrepreneurship should be overcome.

Keywords: Croatia, female entrepreneurship, glass ceiling, motivation

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: Sue Lynn Kim, Sang-Gyun Lee, Joan P. Yoo

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Although adolescents in low socioeconomic status (SES) have been reported to less engage in health promoting behaviors (HPB), the specific mechanism between their SES and HPB has not been extensively studied. Considering the Korean education system which focuses only on college entrance exams while lacking of interest in students’ health, and unique traits of adolescents, such as ego-centric thinking, family members can significantly contribute to develop and enhance adolescents’ HPB. Based on the review of related literature and previous researches, this study examined the mediating effect of family-based activities on the relationship between SES and adolescents' HPB. 636 adolescents (4th graders in elementary and 1st graders in middle school) and their parents from the 1st year survey of Seoul Education & Health Welfare Panel were analyzed by AMOS 19.0 utilizing structural equation modeling. Analytic results show that adolescents in low SES were less likely to engage in family-based activities as well as HPB. This association between SES and HPB was partially mediated by family-based activities. Based on the findings, we suggest that special education programs to enhance HPB should be required in schools and community organizations especially for adolescents in low SES who may have difficulties in doing family-based activities due to parents’ low income and insufficient leisure time. In addition, family-based activities should be encouraged to enhance HPB by raising parents' awareness about the importance of family-based activities on their children's HPB.

Keywords: family-based activity, health promoting behaviors, socioeconomic status, HPB

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Authors: W. G. Kim, C. H. Jo

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We analyzed the effects of variations in the diameter of silicone rubber and polyvinyl chloride (PVC) tubings on the likelihood of tubing rupture during modeling of accidental arterial line clamping in cardiopulmonary bypass with a roller pump. A closed CPB circuit constructed with a roller pump was tested with both PVC and silicone rubber tubings of 1/2, 3/8, and 1/4 inch internal diameter. Arterial line pressure was monitored, and an occlusive clamp was placed across the tubing distal to the pressure monitor site to model an accidental arterial line occlusion. A CCD camera with 512(H) x 492(V) pixels was installed above the roller pump to measure tubing diameters at pump outlet, where the maximum deformations (distension) of the tubings occurred. Quantitative measurement of the changes of tubing diameters with the change of arterial line pressure was performed using computerized image processing techniques. A visible change of tubing diameter was generally noticeable by around 250 psi of arterial line pressure, which was already very high. By 1500 psi, the PVC tubings showed an increase of diameter of between 5-10 %, while the silicone rubber tubings showed an increase between 20-25 %. Silicone rubber tubings of all sizes showed greater distensibility than PVC tubings of equivalent size. In conclusion, although roller-pump induced tubing rupture remains a theoretical problem during cardiopulmonary bypass in terms of the inherent mechanism of the pump, in reality such an occurrence is impossible in real clinical conditions.

Keywords: roller pump, tubing rupture, cardiopulmonary bypass, arterial line

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Authors: Taghreed Al-Khalid, Muftah El-Naas

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As an economical and environmentally friendly technology, biological treatment has been shown to be one of the most promising approaches for the removal of numerous types of organic water pollutants such as Chlorophenols, which are hazardous pollutants commonly encountered in wastewater generated by the petroleum and petrochemical industries. This study aimed at evaluating the performance of a spouted bed bioreactor (SBBR) for aerobic biodegradation of 2, 4 dichlorophenol (DCP) by a commercial strain of Pseudomonas putida immobilized in polyvinyl alcohol (PVA) gel particles. The SBBR is characterized by systematic intense mixing, resulting in improvement of the biodegradation rates through reducing the mass transfer limitations. The reactor was evaluated in both batch and continuous mode in order to evaluate its hydrodynamics in terms of stability and response to shock loads. The SBBR was able to maintain a stable operation and recovered quickly to its normal operating mode once the shock load had been removed. In comparison to a packed bed reactor bioreactor, the SBBR proved to be more efficient and more stable, achieving a removal percentage and throughput of 80% and 1414 g/m3day, respectively. In addition, the biodegradation of chlorophenols was mathematically modeled using a dynamic modeling approach in order to assess reaction and mass transfer limitations. The results confirmed the effectiveness of the use of the PVA immobilization technique for the biodegradation of phenols.

Keywords: biodegradation, 2, 4 dichlorophenol, immobilization, polyvinyl alcohol (PVA) gel

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Authors: Kajal Attri

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Introduction: Transgender people are considered third gender in India, although they still face identification issues and alienated from society. Furthermore, they face several challenges, including discrimination in employment, resources, education, and property as a result, most transgender people make a living through begging at traffic lights, trains, and buses; attending auspicious occasions such as childbirth and weddings; and engaging in sex work, which includes both home-based and street-based sex work. During COVID-19, maintaining social distance exacerbates transgender people's circumstances and prevents them from accessing health care services, sexual reassignment surgery, identity-based resources, government security, and financial stability. Nonetheless, the pandemic raised unfavorable attitudes about transgender persons, such as unsupportive family members and trouble forming emotional relationships. This study focuses on how we missed transgender people during COVID-19 to provide better facilities to cope with this situation when they are already the most vulnerable segment of the society. Methodology: The research was conducted using secondary data from published publications and grey literature obtained from four databases: Pubmed, Psychinfo, Science direct, and Google scholar. The literature included total 25 articles that met the inclusion criteria for a review. Result and Discussion: Transgender people, who are considered the most vulnerable sector of society, have already faced several obstacles as a result of the outbreak. The analysis underscores the difficulties that transgender persons faced during COVID-19, such as, They had trouble accessing the government's social security programmes during the lockdown, which provide rations and pensions since they lack the necessary identifying cards. The impact of COVID-19 leaves transgender people at heightened risk of poverty and ill health because they exist on the margins of society, those livelihood base on sex work, begging, and participation on auspicious occasions. They had a significant risk of contracting SARS-CoV2 because they lived in congested areas or did not have permanent shelter, and they were predominantly infected with HIV, cancer, and other non-communicable illnesses. The pandemic raised unfavorable attitudes about transgender persons, such as unsupportive family members and trouble forming emotional relationships. Conclusion: The study comes forward with useful suggestions based on content analysis and information to reduce the existing woes of transgenders during any pandemic like COVID-19.

Keywords: COVID-19, transgender, lockdown, transwomen, stigmatization

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Authors: Ehsan Sakhaei, Ali Taherabadi

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In this study, an aft sweep wing with specific characteristic feature was analysis with CFD method in Fluent software. In this analysis wings aerodynamic coefficient was calculated in different rake angle and wing lift curve slope to rake angle was achieved. Wing section was selected among NACA airfoils version 6. The sweep angle of wing is 15 degree, aspect ratio 8 and taper ratios 0.4. Designing and modeling this wing was done in CATIA software. This model was meshed in Gambit software and its three dimensional analysis was done in Fluent software. CFD methods used here were based on pressure base algorithm. SIMPLE technique was used for solving Navier-Stokes equation and Spalart-Allmaras model was utilized to simulate three dimensional wing in air. Roskam method is one of the common and most used methods for determining aerodynamics parameters in the field of airplane designing. In this study besides CFD analysis, an advanced aircraft analysis was used for calculating aerodynamic coefficient using Roskam method. The results of CFD were compared with measured data acquired from Roskam method and authenticity of relation was evaluated. The results and comparison showed that in linear region of lift curve there is a minor difference between aerodynamics parameter acquired from CFD to relation present by Roskam.

Keywords: aft sweep wing, CFD method, fluent, Roskam, Spalart-Allmaras model

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Authors: Sami Mohamed Sharif

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The current study focuses on the design and construction of a solar tunnel dryer intended for small-scale farmers in Kassala, Sudan. To determine the appropriate dimensions of the dryer, the heat and mass balance equations are used, taking into account factors such as the target agricultural product, climate conditions, solar irradiance, and desired drying time. In Kassala, a dryer with a width of 88 cm, length of 600 cm, and height of 25 cm has been built, capable of drying up to 40 kg of vegetables or fruits. The dryer is divided into two chambers of different lengths. The air passing through is heated to the desired drying temperature in a separate heating chamber that is 200 cm long. From there, the heated air enters the drying chamber, which is 400 cm long. In this section, the agricultural product is placed on a slightly elevated net. The tunnel dryer was constructed using materials from the local market. The paper also examines the solar irradiance in Kassala, finding an average of 23.6 MJ/m2/day, with a maximum of 26.6 MJ/m2/day in April and a minimum of 20.2 MJ/m2/day in December. A DC fan powered by a 160Wp solar panel is utilized to circulate air within the tunnel. By connecting the fan and three 12V, 60W bulbs in series, four different speeds can be achieved using a speed controller. Temperature and relative humidity measurements were taken hourly over three days, from 10:00 a.m. to 3:00 p.m. The results demonstrate the promising technology and sizing techniques of solar tunnel dryers, which can significantly increase the temperature within the tunnel by more than 90%.

Keywords: tunnel dryer, solar drying, moisture content, fruits drying modeling, open sun drying

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Authors: Hamza Benzerrouk, Alexander Nebylov

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In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

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Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Nasser Alsadoun

Abstract:

Today's companies in Saudi Arabian capital market must comply with strict criteria and adhere to rigid corporate governance rules and continuous disclosure requirements. Unlike other regulators in the region, decision makers of the Capital Market Authority (hereafter CMA) of Saudi Arabia believes that the announcements of economic sanctions and penalties for non-compliance firms will foster more effective regulatory compliance and hence improve the quality of financial reporting. An implied argument put forward by the opponents, however, states that such penalties are unnecessary and stated to be onerous for non-compliance firms. Over that last years, the CMA has publicly announced several economic fines levied on some listed companies for their failing to comply with corporate governance and continuous disclosure regulation clauses, with the amount of fine levied ranges between 50,000 SR to 100,000 SR for each failing. Economic theory suggests that rational investors make decisions based on a cost-benefit principal. The regulatory intervention made by CMA on the announcement of economic sanctions has been costly to the society (economy) hoping that it improves the transparency of financial statements. It is argued, therefore, that threat of regulators and economic sanctions will provide incentives for firms’ managers to report more relevant and reliable accounting information, and the benefit of such announcements is likely to be reflected in the context of the quality of the financial reports. Yet, the economic consequences of the revealed fines announcement for non-compliance firms in Saudi Arabian market have not been examined. Thus, this study attempts to empirically examine whether market participants are pricing the supposed benefits of rigid governance and disclosure rules in the Saudi market. The study employs an event study methodology to assess the impact of CMA economic sanctions announcements on the market price of non-compliance firms. The study also estimates and examines bid–ask spread behavior of violated firms around the CMA announcements. The findings indicate that the CMA fines announcements for failing to comply with governance and disclosure rules do not appear to play any significant role in securities pricing. In addition, tests of bid-ask behavior does not indicate any significant increases in information asymmetry surrounding these announcements. While the CMA has developed many goals to increase the awareness of listed companies with the best governance and disclosure practices, it seems they have to develop more goals to improve market efficiency and increase investors and public awareness.

Keywords: governance and disclosure violations, financial reporting quality, regulatory intervention, market efficiency

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Authors: Daniyar Bossinov

Abstract:

This paper considers a non-isothermal stationary waxy crude oil flow in a two-dimensional axisymmetric pipe with the transition of a Newtonian fluid to a non-Newtonian fluid. The viscosity and yield stress of waxy crude oil are highly dependent on temperature changes. During the hot pumping of waxy crude oil through a buried pipeline, a non-isothermal flow occurs due to heat transfer to the surrounding soil. This leads to a decrease in flow temperature, an increase in viscosity, the appearance of yield stress, the crystallization of wax, and the deposition of solid particles on the pipeline's inner wall. The deposition of oil solid particles reduces a pipeline flow area and leads to the appearance of a stagnant zone with thermal insulation in the near-wall area. Waxy crude oil properties change. A Newtonian fluid at low temperatures transits to a non-Newtonian fluid. The one-dimensional modeling of a non-isothermal waxy crude oil flow in a two-dimensional axisymmetric pipeline by traditional averaging of temperature and velocity over the pipeline cross-section does not allow for explaining a physics phenomenon. Therefore, in this work, a two-dimensional flow model and the heat transfer of waxy oil are constructed. The calculated data show the transition of a Newtonian fluid to a non-Newtonian fluid due to the heat exchange of waxy oil with the environment.

Keywords: non-isothermal laminar flow, waxy crude oil, stagnant zone, yield stress

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

Abstract:

Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Alejandra Cardenas, Ona Flores, Fabiola Gretzinger

Abstract:

Since the 1990s, legal strategies for the promotion and protection of maternal health rights have achieved significant gains. Successful litigation in courts around the world have shown that these rights can be judicially enforceable. Governments and international organizations have acknowledged the importance of a human rights-based approach to maternal mortality and morbidity, and obstetric violence has been recognized as a human rights issue. Despite the progress made, maternal mortality has worsened in some regions of the world, while progress has stagnated elsewhere, and mistreatment in maternal care is reported almost universally. In this context, issues of maternal autonomy and decision-making during pregnancy, labor, and delivery as a critical barrier to access quality maternal health have been largely overlooked. Indeed, despite the principles of autonomy and informed consent in medical interventions being well-established in international and regional norms, how they are applied particularly during childbirth and pregnancy remains underdeveloped. National and global legal standards and decisions related to maternal health were reviewed and analyzed to determine how maternal autonomy and decision-making during pregnancy, labor, and delivery have been protected (or not) by international and national courts. The results of this legal research and analysis lead to the conclusion that a few standards have been set by courts regarding pregnant people’s rights to make choices during pregnancy and birth; however, most undermine the agency of pregnant people. These decisions recognize obstetric violence and gender-based discrimination, but fail to protect pregnant people’s autonomy, privacy, and their right to informed consent. As current human rights standards stand today, maternal health is the only field in medicine and law in which informed consent can be overridden, and patients can be forced to submit to treatments against their will. Unconsented treatment and loss of agency during pregnancy and childbirth can have long-term physical and mental impacts, reduce satisfaction and trust in health systems, and may deter future health-seeking behaviors. This research proposes a path forward that focuses on the pregnant person as an independent agent, relying on the doctrine of self-determination during pregnancy and childbirth, which includes access to the necessary conditions to enable autonomy and choice throughout pregnancy and childbirth as a critical step towards our approaches to reduce maternal mortality, morbidity, and mistreatment, and realize the promise of access to quality maternal health as a human right.

Keywords: autonomy in childbirth and pregnancy, choice, informed consent, jurisprudential analysis

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Authors: M. Solairaju, Nithin J. Thomas, S. Ganesan

Abstract:

Each and every rotating part of a machine element consists of bearings within its structure. In particular, the rolling element bearings such as cylindrical roller bearing and deep groove ball bearings are frequently used. Improper handling, excessive loading, improper lubrication and sealing cause bearing damage. Hence health monitoring of bearings is an important aspect for radiation pattern of bearing vibration is computed using the dipole model. Sound pressure level for defect-free and race defect the prolonged life of machinery and auto motives. This paper presents modeling and analysis of Acoustic response of deep groove ball bearing with localized race defects. Most of the ball bearings, especially in machine tool spindles and high-speed applications are pre-loaded along an axial direction. The present study is carried out with axial preload. Based on the vibration response, the orbit motion of the inner race is studied, and it was found that the oscillation takes place predominantly in the axial direction. Simplified acoustic is estimated. Acoustic response shows a better indication in identifying the defective bearing. The computed sound signal is visualized in diagrammatic representation using Symmetrised Dot Pattern (SDP). SDP gives better visual distinction between the defective and defect-free bearing

Keywords: bearing, dipole, noise, sound

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Authors: May M. Youssef

Abstract:

This article introduces a design, for additive manufacturing technology, face shield as Personal Protective Equipment from the respiratory viruses such as coronavirus 2. The face shields help to reduce ocular exposure and play a vital role in diverting away from the respiratory COVID-19 air droplets around the users' face. The proposed face shield comprises three assembled polymer parts. The frame with a transparency overhead projector sheet visor is suitable for frontline health care workers and ordinary citizens. The frame design allows tightening the shield around the user’s head and permits rubber elastic straps to be used if required. That ergonomically designed with a unique face mask support used in case of wearing extra protective mask was created using computer aided design (CAD) software package. The finite element analysis (FEA) structural verification of the proposed design is performed by an advanced simulation technique. Subsequently, the prototype model was fabricated by a 3D printing using Fused Deposition Modeling (FDM) as a globally developed face shield product. This study provides a different face shield designs for global production, which showed to be suitable and effective toward supply chain shortages and frequent needs of personal protective goods during coronavirus disease and similar viruses.

Keywords: additive manufacturing, Coronavirus-19, face shield, personal protective equipment, 3D printing

Procedia PDF Downloads 195