Convenient Access Research Articles

HIV service use among minoritized racial and ethnic transgender and gender non-conforming youth in the U.S South: a qualitative investigation

ABSTRACT Transgender youth are disproportionately affected by HIV, particularly minoritized youth in the US south. To understand HIV service use among transgender youth, we interviewed 25 young racial and ethnic minority clients of four southern community-based HIV service organizations (CBOs), and CBO staff (n = 12), about service access and use. Participants were assigned male at birth and identified as female (n = 8), transgender (n = 11) or gender-fluid or nonbinary (n = 6). The majority were Black/African American or mixed race; four were Hispanic or Latino/a. Most were unemployed; nearly half were unstably housed or homeless during the prior year. Four service types were each used by approximately two-thirds of participants: counseling/support, HIV/STD testing/education, pre-exposure prophylaxis education/prescriptions, and transgender-related medical services (primarily hormone provision). Just over a quarter used social services (e.g., housing, employment). Key facilitators to service use included a non-stigmatizing CBO atmosphere, and easy and convenient access. Poor access (e.g., inconvenient hours, location), lack of transportation or parking, social service needs, and lack of money were barriers. Qualitative reports highlighted unmet social service needs, particularly housing, especially for those without HIV. To reduce disparities, HIV prevention for racial and ethnic minoritized transgender youth should simultaneously address hormone provision, HIV risk reduction and social service needs.

Experience in Creating Demographic Dashboards

"Digital technologies are now actively utilized across all scientific disciplines, and demographic science is no exception. Demographers leverage both new data sources generated in the digital environment and advanced data processing methods based on machine learning and data mining. Additionally, a significant application of digital technologies is the development of interactive web applications, or dashboards, that present demographic data. These dashboards offer convenient access to information and can be utilized in both academic research and public administration."

Planning an airport shuttle network with air taxis using choice-based optimization

Abstract Airports and airlines share a common interest in providing passengers with fast and convenient access to airports. With the introduction of air taxis as a new means of transport, the opportunity will soon emerge to introduce air taxi shuttle services to airports. In this context, for each individual airport the question arises where the facilities for landing, ground handling and take-off, also called vertiports, should be located in the area surrounding the airport. We formulate the problem as a hub location problem with multiple allocation, with the objective to maximize the number of passengers who choose to reach the airport by air taxi. In our model, we explicitly incorporate passengers’ choice behavior with respect to available means of transport using a multinomial logit model. We linearize the problem and provide guidance on the steps needed to use the model in practice. In an extensive case study, we apply the model to real data for Munich Airport, perform a stated preference study to parameterize the multinomial logit model, suggest locations for vertiports throughout Bavaria as a result, and investigate to what extent the introduction of air taxi shuttle flights can reduce travel times to Munich Airport.

Features of Distance Learning in the University Education System of Kazakhstan

The purpose of this work is to describe the modeling method and the possibility of developing a relatively inexpensive but effective educational platform using the example of an existing distance learning information system. The method of the created system is based on a special approach to the use of modern digital tools that allows one to automate the learning process at a distance. To create an information system for distance learning, a number of requirements and performance criteria were taken into account, which were determined on the basis of an expert analysis of several other similar well-known educational platforms. To develop the software component of the distance learning system, the choice was made on the scripting programming language Hypertext Preprocessor (PHP). The validity of the choice of programming language lies in the fact that, at present, this language is supported by the vast majority of organizations providing professional hosting services. PHP is an easy-to-use language, has a wide range of functionality, is flexible in terms of cross-platforms and is one of the leading languages used to create dynamic websites. The developed system, in full, serves as a good example of demonstrating the main possibilities of using modern information technologies in the field of distance learning. The approach of the received distance learning system at the university has practically proven the effectiveness of this system in the educational process. The users of the information system noted convenient access to the necessary content, ease of analysis of the learning process, and the user-friendly interface of the platform. From a technical standpoint, the introduction of this system into the educational process of a higher educational institution or organization will not incur high economic costs.

Does internet-based climate information improve non-fishing employment opportunities? Insights from smallholder fishermen in Indonesia

ABSTRACT In the face of climate change, smallholder fishermen increasingly turn to non-fishing employment to sustain their livelihoods. Diversifying sources of income becomes paramount to mitigate the impact of unpredictable weather patterns on fish populations and, hence, household livelihoods. However, fishermen need convenient climate information access to navigate this transition effectively. With information about weather trends and forecasts, they can make informed decisions about when to fish and when to focus on alternative sources of income. This study offers novelty by investigating the impact of Internet-based climate information on non-fishing employment among smallholder fishermen in Indonesia. The study employs cross-sectional data collected from 503 smallholder fishermen in Indonesia, analyzed using a conditional mixed process (CMP) approach to tackle the endogeneity issue that may arise in the estimation. The results highlight that adopting Internet-based climate information among smallholder fishermen was positively and significantly associated with education, distance to fishing ports, social activity, fishing location, adoption of multiple gears, and access to the Internet among family members and relatives. However, the age of fishermen shows otherwise. Furthermore, our empirical findings confirm that Internet-based climate information significantly increases opportunities for non-fishing employment among fishermen. Disaggregate estimation by fishing boat size category strengthens this finding by showing a positive and significant coefficient in all categories. Therefore, this finding implies a need to improve and develop Internet-based climate information platforms in fisheries.

A Multi-Source Heterogeneous Data-Driven Method for Nursing Home Location Selection: The Cases of Two Districts in Beijing

Background: The configuration of nursing homes is crucial for cities with severe aging populations, traditional optimization methods mentioned in previous research rarely use multi-- source heterogeneous data. Objective: To optimize the nursing home location selection methods and improve decision effectiveness by multi-source heterogeneous data. Design: Quantitative data were collected using a mixed-methods design. Methods: The real-time data was considered and the population factors, economic level, natural factors, medical conditions, convenience of life and traffic accessibility were integrated to explain location-decision principles. Geographical Information System (GIS) was used to collect spatial data, and machine learning methods were employed to evaluate the spatial suitability of nursing homes at a 500-meter grid scale. To test the validity, Xicheng and Dongcheng districts in Beijing were chosen as cases. Results: The proposed method shows better prediction performance compared with Extreme Gradient Boost (XGBoost), Random Forest, and AdaBoost. The quantitative analysis showed that the number of schools, the proportion of green areas, medical conditions, traffic accessibility, and the number of shopping facilities are the main features for determining the location of nursing homes in Xicheng and Dongcheng Districts Beijing. Conclusion: The local government should pay attention to factors such as education, green spaces, medical conditions, transportation conditions, and shopping convenience when considering the configuration of nursing homes. The location selection method proposed in this paper considers multiple dimensions to increase objectivity and comprehensiveness.

A Review on UPI Fraud Detection using Machine Learning and Deep Learning

In today's digital era, nearly all business transactions are conducted online. While online transactions offer numerous advantages such as convenience, faster payments, and ease of access, they also come with significant risks, including fraud, phishing attacks, and data breaches. The growing volume of internet-based transactions has heightened concerns about unethical practices and threats to personal privacy.For instance, cybercriminals may gain unauthorized access to an individual's account and transfer funds illicitly. To mitigate potential financial losses, it is crucial to enhance existing machine learning methodologies. A robust, featureengineered machine learning model, leveraging algorithms like Random Forest and Gradient Boosting, can improve performance, enhance stability, and become more effective by analysing extensive datasets. Moreover, understanding the costs and risks associated with various payment systems is critical for systematically and efficiently combating fraud. We propose three models: a risk assessment model to predict and counter fraud risks, a machine learning-basedfraud detection system, and an economic optimization framework for refining machine learning outcomes. These models are validated using real-world data to ensure their reliability and applicability.

The impact of using health apps as a source of information and health education in the medical field

Introduction: Medical training transcends the formal curriculum, involving the construction of a professional identity shaped by interaction with professors and professionals in the field. In response to contemporary demands, medical education has undergone adaptations, driven by the advancement of digital technologies, which offer greater flexibility and accessibility to learning. Mobile applications have gained prominence for facilitating access to medical knowledge, although they raise concerns about the quality of teaching and the technological literacy of students. Objective: This study aims to review the literature on the impact of health applications on medical education, by evaluating their contributions to the learning of students and health professionals, as well as the advantages and disadvantages associated with their use. Methods: This is an integrative literature review, carried out using the PubMed, LILACS and SciELO databases, with articles published from 2019 to July 2024, which addressed the impact of health applications in the medical field. The initial search resulted in 75 articles, of which 20 were selected according to the established criteria. Conclusion: Health applications offer flexibility, dynamism and convenient access to information, complementing medical training with a diversity of resources, especially in contexts restricted to the clinical environment. However, issues such as language interpretation and possible barriers to accessing technology can affect its effectiveness and the quality of learning. Therefore, the integration of these applications must be done critically to ensure that they do not compromise medical training and practice.

Excited state properties from the Bethe-Salpeter equation: State-to-state transitions and spin-orbit coupling.

The formalism to calculate excited state properties from the GW-Bethe-Salpeter equation (BSE) method is introduced, providing convenient access to excited state absorption, excited state circular dichroism, and excited state optical rotation in the framework of the GW-BSE method. This is achieved using the second-order transition density, which can be obtained by solving a set of auxiliary equations similar to time-dependent density functional theory (TD-DFT). The proposed formulation therefore leads to no increase in the formal computational complexity when compared to the corresponding ground state properties. We further outline the calculation of fully relaxed spin-orbit coupling matrix elements within the GW-BSE method, allowing us to include perturbative corrections for spin-orbit coupling in aforementioned properties. These corrections are also extended to TD-DFT. Excited state absorption and perturbative spin-orbit coupling corrections within GW-BSE are evaluated for a selected set of molecular systems, yielding promising results.

Development of Learning Management System with Gamification Approach for Project-Based Learning

This study focuses on the development of the Learning Management System for Innovation in Graphic and Visual Media with a gamification approach in the context of teaching the Graphic and Visual Media Innovation course. Currently, learning management utilizes the SIPEJAR Learning Management System (LMS) and the Progress Report Card (PRC), but their separate existence poses challenges to efficiency and effectiveness. Students are required to monitor their own learning resources and track their learning performance through the PRC. The optimal learning environment would be one in which all learning resources and progress are accessible in a single, integrated platform, allowing for convenient access from any location at any time. The objective of this research is to develop a Learning Management System (LMS) that incorporates gamification elements into project-based learning. Research design employed is Research and Development (RnD), adopting the Web-Based Instructional Design model. The sample for this research is composed of 134 students. The research was conducted between October and December. The data collected for this study is quantitative data obtained using the Technology Acceptance Model questionnaire and the level of student engagement in the learning process. The result is that students perceive the IMGV LMS as a beneficial addition to their learning experience. The LMS enables students to monitor their performance in the final course project and access assignment materials in a centralized location. Additionally, the LMS facilitates knowledge acquisition through the incorporation of quizzes, which are designed to engage students in a competitive learning environment.

Research on Marketing Strategies for Pharmaceutical Distributors

Abstract Under the impact of the second-generation national health insurance, pharmaceutical distributors face significant survival pressures. Given that pharmaceutical distributors have shifted from a B2B (business-to-business) model to a B2C (business-to-consumer) model, the importance of marketing strategies is undeniable, and the content and combination of these strategies warrant further investigation. This study focuses on the key customer groups of pharmaceutical distributors in a B2C context and employs the Analytic Hierarchy Process (AHP) for analysis. The research aims to: 1) Identify key factors in marketing strategies using the 4P framework; 2) Develop the relative importance of the 4P dimensions using AHP; 3) Provide pharmaceutical distributors with a marketing mix based on the findings. The results reveal that the 'Product' dimension has more influence than the other dimensions (Price, Place, and Promotion). Within the Product dimension, 'Brand Value' is of utmost importance, 'High Value Advantage' is most crucial in the Price dimension, 'Convenience of Access' ranks highest in the Place dimension, and 'Development of Advantageous Promotional Combinations' is most significant in the Promotion dimension. JEL classification numbers: C83, M15, O31. Keywords: Pharmaceutical Distributors, Marketing Strategies, Marketing Mix, Analytic Hierarchy Process (AHP).

Is cloud computing a game-changer for SME financial performance? Unveiling the mediating role of organizational agility through PLS-SEM

PurposeCloud computing services are game-changing in empowering organizations to drive innovation and unlock new growth opportunities. Accordingly, this study aims to examine the determinants of cloud computing adoption in SMEs and assess their impact on firm financial performance, specifically focusing on the mediating role of organizational agility in driving cloud-enabled financial improvements.Design/methodology/approachData were collected from 405 owners and managers of SMEs who used cloud computing. A “variance based-structural equation modelling” (PLS-SEM) was employed to test the hypothesis.FindingsThe PLS-SEM result shows that relative advantage, cost-effectiveness, compatibility and external environment support significantly influence cloud computing adoption in SMEs. However, complexity insignificantly impacts cloud computing adoption. The analysis also revealed that cloud computing adoption substantially influences organizational agility. Similarly, cloud computing adoption and organizational agility significantly influence firms’ financial performance.Practical implicationsThe present research provides valuable suggestions to service providers, policymakers and managers on developing and expanding cloud computing in developed and developing nations. Additionally, cloud providers can recognize their role in creating a supportive and adaptable environment that ensures convenient access to cloud computing users.Originality/valueThis research is an initial attempt to blend the strength of diffusion of innovation (DOI) theory with two additional constructs (i.e. cost-effectiveness and external environment support) for making a comprehensive model of cloud computing adoption and its influence on firm financial performance. By doing this, the research adds to the empirical knowledge on cloud computing adoption and provides an institutional framework to interpret the impact of cloud-based information technology.

Development of a Web-Based Application for Monitoring and Measuring the Physical Condition of Badminton Athletes

The research aimed to develop a digital solution for monitoring and controlling the physical condition of badminton athletes at Bina Darma University, enabling coaches to track whether athletes’ physical conditions have decreased, remained stable, or improved. Previously, physical condition measurements were recorded manually in notebooks, requiring coaches to manually search and compare past records to assess badminton athletes’ progress. This manual process was time-consuming and inefficient. To address these challenges, a responsive, web-based application was developed for real-time monitoring and management of athletes’ physical data. This application, accessible from both laptops and smartphones with internet connectivity, allows for convenient access from any location. By streamlining data collection and tracking, the application provides a more efficient tool for coaches to evaluate badminton athletes’ physical condition over time. The transition from a manual to a digital system improves data security and accessibility, supporting enhanced decision-making in athlete management and training.

Women's perspectives of molecular breast imaging: a qualitative study.

Mammography has poor sensitivity in dense breast tissue. Retrospective studies suggest that Molecular Breast Imaging (MBI), has superior diagnostic accuracy to mammography in women with very dense breast tissue. Women's perspectives of MBI are unknown, but are crucial to understanding the feasibility of, and routes to, adoption into practice. Semi-structured interviews with screened and unscreened women explored acceptability of MBI. Data were analysed thematically. Four themes were generated from nineteen interviews: (1) presumed negative aspects of MBI are acceptable (2) convenience of access, (3) comfort in familiarity and (4) need for shared decisions relating to risk. Presumed negative aspects of MBI, such as radiation dose and forty-minute scan time, were acceptable provided there are benefits. Some participants were concerned about equitable access, such as parking. Participants expressed comfort in existing and familiar screening processes. Participants acknowledged that informing women of their breast density may result in increased anxiety, but it was still felt to be important to ensure women are fully informed of the risks and harms of screening. Women consider MBI to be an acceptable breast imaging modality. High-quality information enabling informed decision-making is essential.

Review Mate: A Cutting-Edge Model for Analyzing the Sentiment of Online Customer Product Reviews using ML.NET

E-commerce has become increasingly important in recent years due to several factors such as convenience, global reach, lower costs, personalization and uninterrupted access. In e-commerce, product reviews by customers can significantly impact purchasing behavior by providing social proof, establishing trust, aiding decision-making, improving search engine optimization, and increasing sales. Conducting an evaluation of the primary impacts of customer reviews on purchasing behavior through automated machine learning techniques has the potential to facilitate the advancement of diverse online business models. In this scope, we come with a new machine-learning model for evaluating customer sentiment based on product reviews. To this aim, a dataset consisting of 1000 positive and 1000 negative customer reviews was created by collecting publicly shared comments from online shopping websites serving in Turkey with a data collection tool developed by our research group. The model development was carried out on ML.NET, an open-source and cross-platform machine learning framework. In order to reach the most efficient model, a total of 36 machine learning models were explored for the solution of the problem within the scope of the experimental study. As a result, the model named Lbfgs Logistic Regression Binary was found to be the most efficient. The related model provided an accuracy rate of 94.76%. An API service called Review Mate has been developed to expand the potential impact of the proposed machine learning model and enable its use in different online business models. According to the findings, the proposed method outperforms the previous approach in terms of classification performance and also provides avenues for the discovery of new product ideas.

Reductive Aromatization of 5,7,12,14 Pentacenetetrone: Approach Towards Substituted Pentacenes?

Herein we report a convenient access to asymmetrically substituted, well soluble pentacene derivatives synthesized from commercially available 5,7,12,14 pentacenetetrone via reductive one step functionalization. Zinc or potassium are used as reducing agents and the reduced intermediates are trapped with electrophiles such as acetyl, triisopropylsilyl or cationic methyl synthons. The reduction allows for an unsymmetric functionalization whilst one dione moiety is maintained due to partial reduction. The resulting dyes are characterized by UV/ Vis and photoluminescence spectroscopy. Their redox potentials are studied by cyclic voltammetry. The experimentally determined molecular frontier orbital energies are rationalized by density functional theory. The spatial molecular packing motive in the solid state is studied as a function of the substituent size by X ray crystallography. Attempts of reducing the second quinone moiety towards a functionalized pentacene led to an over reduced 6,13-dihydropentacene derivative, which by means of an XRD structural analysis surprisingly displays a planar molecular conformation and unique optoelectronic properties.

Drive through dining and development: effect of zoning reform in Buffalo on site layout of and access to fast food restaurants

Fast food restaurants are ubiquitous in American cityscapes and often produce challenges for urban planners because their sites often require excessive provisions for automobiles in places where walkability and compactness are desired. This article explores the outcomes of a 2017 zoning reform in Buffalo, New York on the form and physical characteristics of fast food restaurants with drive through windows. Analyzing site plan and variance applications, we compare all drive through restaurant proposals approved under the new zoning code (2017 to 2022) with those approved prior to the zoning reform (2000 to 2016). After Buffalo’s transition to form-based zoning, fast food restaurant footprints consume on average 9 percent of property area, parking lots consume more land than building footprints in 90 percent of cases, and front setbacks are greater than 25 feet in 50 percent of cases. Automobile drivers continue to enjoy safer and more convenient site access than do pedestrians. The physical design and site layouts of drive through restaurants remain largely unchanged following the reform. Notable differences include a 25 percent decrease in parking lot size and 46 percent increase in vehicle stacking capacity in drive through lanes. Following the zoning reform, a majority (80 percent) of proposed fast food restaurants were granted variances in the approval process to allow reduced façade transparency, excessive setbacks, and drive through lanes in prohibited zones. Stricter implementation and stronger incentives to develop in appropriate locations would support achieving the broad vision of the zoning code to preserve neighborhood character and activate mixed-use centers.

AHP-Driven Strategic Decision Framework for Selecting Optimal Radiopharmaceutical Facility Locations

Given the increasingly important role of radiopharmaceutical products in medical diagnosis and treatment, choosing a strategic location for a new radiopharmaceutical facility is an important decision for pharmaceutical companies. This research develops a multi-criteria decision-making framework for selecting optimal radiopharmaceutical facility locations. The framework begins by generating alternative locations and criteria by using a PESTEL analysis to assess the external environment. Five key criteria were then identified for evaluation: customer proximity, transportation accessibility, operational support, public acceptance, and legal acceptance, with each criterion further broken down into specific sub-criteria. The Analytical Hierarchy Process (AHP) method was used to weigh these criteria and sub-criteria based on expert and stakeholder input, and to evaluate the alternative locations. Results of the AHP analysis showed that proximity to customers and accessibility to transportation were the most important criteria, leading to the selection of Cikarang as the optimal location due to its proximity to hospitals, convenient transportation access, and compliance with regulations and permits. Sensitivity analysis confirmed the robustness of this choice against variations in criteria weights. This framework provides a structured approach for pharmaceutical companies in strategic decision-making regarding the siting of radiopharmaceutical facilities.

Analysis of Economic Vitality and Development Equilibrium of China’s Three Major Urban Agglomerations Based on Nighttime Light Data

Eliminating poverty, reducing inequality, and achieving balanced development are one of the United Nations Sustainable Development Goals. Objectively and accurately measuring regional economic vitality and development equilibrium is a pressing scientific issue that needs to be addressed in order to achieve common prosperity. Nighttime light (NTL) remote sensing data have been proven to be a good proxy variable for socio-economic development, and are widely used due to their advantages of convenient access and wide spatial coverage. Based on multi-source data, this study constructs an Economic Development Index (EDI) that comprehensively reflects regional economic vitality from two aspects, economic quality and development potential, combines the Nighttime Light Development Index (NLDI) as the evaluation indicators to measure the economic vitality and development equilibrium, analyzes the economic vitality and development equilibrium of 300 district and county units in China’s three major urban agglomerations from 2000 to 2020 and their temporal and spatial variation characteristics, and discusses the connotation of EDI and its availability. The results show the following: (1) From 2000 to 2020, the average growth rate of EDI in China’s three major urban agglomerations reached 36.32%, while the average decrease rate of NLDI reached 38.75%; both economic vitality and the development equilibrium have been continuously enhanced. Among them, the Yangtze River Delta (YRD) urban agglomeration experienced the fastest economic growth, while the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) exhibited the strongest economic strength. (2) Both economic vitality and the development equilibrium in these three urban agglomerations exhibited distinct spatial agglomeration characteristics, namely center-surrounding distribution, coastal–inland distribution, and radial belt–pole distribution, respectively. (3) Over the past two decades, the economic development of these three urban agglomerations has progressed towards the pattern of regional coordinated development, pole-driven development and urban–rural integrated development. The research results can provide new research perspectives and scientific support for promoting regional balanced development, achieving sustainable development goals, and reducing inequality.

Ruthenium-Catalyzed α-Regioselective Hydroboration of Allenes.

Hydroboration of allenes is powerful and atom-economic approach to the synthesis of organoboranes, such as the highly versatile allylboranes. However, regarding regiocontrol, existing methods uniformly deliver the boron functionality to the less hindered β- or γ-position, but not the α-position. The latter is particularly challenging for allenes with substantial steric difference between the two terminals and lacking electronic bias (e.g., 1,1-disubstituted allenes). Herein we report the first highly efficient ruthenium-catalyzed hydroboration of allenes featuring exclusive α-regioselectivity, providing access to sterically hindered allyl boranes that are limitedly accessible by conventional methods. DFT studies suggested that the unusual α-regioselectivity is attributed to the disfavored reductive elimination at the γ-position due to the high energy cost required to overcome the agnostic interaction and rotation of the key π-allyl intermediates. This protocol is also applicable to the previously unprecedented α-hydroalkynylation and underdeveloped α-hydrosilylation of allenes, thus complementing known catalytic systems and providing convenient access to highly congested yet densely-functionalized allyl silanes and skipped enynes bearing a fully-substituted allylic carbon center. It is expected that this ruthenium-catalyzed system can serve as a new platform for the development of other hydrofunctionalization processes with unorthodox selectivity.