bluuebunny/crossref_metadata_2025 huggingface dataset:
PERCEPCIÓN DE LOS PACIENTES SOBRE LOS SERVICIOS MÉDICOS DEL ULAPS DEL DISTRITO DE DOLEGA
Authors: Pitti Brayan , Machado Antonio , Quintero Edson , Berbey-Alvarez Aranzazu
Published: May 2024

El sistema de salud pública en Panamá ha sido motivo de una creciente inquietud a nivel nacional en los últimos años. En este artículo se analizó y destacó la situación del sistema de salud pública de Panamá y las diversas problemáticas que afectan al sistema: tales como: la reducción de la responsabilidad del Estado en la provisión de las instalaciones adecuadas, la necesidad de enfocarse en los niveles primarios y secundarios de atención y demás aspectos. Se establecen objetivos para crear conciencia sobre la salud, implementación de las estrategias que sean aplicadas en cada punto del país y mejorar el sistema de salud. Para esto se han recolectado datos por medio de encuestas como herramienta principal, para personas mayores de 18 años en varios puntos de la provincia de Chiriquí. Comprendiendo las problemáticas del sistema, se llevó a cabo una visita a la Unidad Local de Atención Primaria de Salud (ULAPS) en el distrito de Dolega, durante la visita se obtuvo información detallada sobre el funcionamiento de la farmacia, el manejo de recursos financieros, la falta de instalaciones médicas adecuadas, necesidad de médicos y especialistas, así como aquellos datos relevantes sobre los pacientes asegurados y no asegurados, y demás aspectos. Las opiniones expresadas por los directivos y trabajadores de la ULAPS coincidieron en ciertas carencias del sistema de salud pública en Panamá, lo cual resultó sorprendente al relacionarlo con las respuestas de las encuestas. Esta integración de información permitió obtener una perspectiva más completa y fundamentada sobre el sistema de salud y las opiniones de los diversos actores involucrados.
IMPACTO DE LA INTELIGENCIA ARTIFICIAL EN LA MEJORA DE LA PRÁCTICA DOCENTE
Authors: Marcano Lárez Beatriz Elena , Mazurkiewicz Rodríguez Héctor José , López Álvarez Liliana Ibeth
Published: May 2024

Este trabajo es un avance de un proyecto de investigación, cuyo objetivo es promover un ecosistema educativo para la integración de la inteligencia artificial en programas universitarios a través del diseño pedagógico participativo implementado por los docentes universitarios de UNICyT. Para alcanzar dicho objetivo se planteó como pregunta de investigación: ¿Cuáles son las estrategias efectivas de formación y capacitación docente para la aplicación de la inteligencia artificial en programas universitarios, que promueven cambios positivos en la práctica docente?Esto es importante de investigar porque la implementación de la inteligencia artificial en la educación superior presenta desafíos y oportunidades significativas. Al preparar adecuadamente a los docentes en el uso de la inteligencia artificial, se pueden lograr cambios positivos en la práctica docente, mejorando la calidad de la enseñanza y el aprendizaje. Además, esta investigación contribuirá al avance del conocimiento en el campo educativo y enriquecerá los programas universitarios, preparando a los estudiantes para los desafíos del siglo XXI. Desde un enfoque práctico, se busca producir y estudiar en un grupo de profesores universitarios, cambios o transformaciones en la conducta de su práctica docente que favorezcan el proceso de enseñanza-aprendizaje a partir del diseño pedagógico participativo para la integración de la inteligencia artificial en sus programas académicos, a este grupo de profesores se les denominadocentes colaboradores, y son parte del evento de estudio. Este informe de avance muestra como resultados parciales, la fase de diagnóstico del proceso metodológico llevado a cabo para realizar una investigación acción participativa.
Denominational Loyalty on the Cooperative Programme of the Nigerian Baptist Convention Between (2013-2023)
Authors: Musa Emmanuel Ubandoma , Afolaranmi Adebayo Ola
Published: May 2024

The Baptist Cooperative Programme is a system in which churches, who cooperate with the Nigeria Baptist Convention (NBC), make contributions in the form of certain percentages of their tithes, offerings, and undesignated income to their associations, state conferences, and the national body. This paper explores the effects of denominational loyalty on the Cooperative Programme of the Nigerian Baptist Convention (NBC) and strategies to deepen this loyalty among church members. Social identity theory suggests that individuals define themselves based on their membership in social groups, leading to the formation of an identity that is partly derived from their group membership. The decline in the commitment of churches within this period of ten years is worrisome. The existing problem lies in the need to strengthen denominational loyalty to the Convention amidst changing societal dynamics and competing religious influences. Using secondary sources of data collection, including scholarly articles, books, and Convention reports, this study analyses the historical context and current practices of the Baptist Cooperative Programme. Preliminary findings suggest that the Cooperative Programme plays a crucial role in fostering a sense of belonging and loyalty among members, contributing to the overall growth and sustainability of the denomination. Also, while there is a strong desire for cooperation among Baptist Churches, challenges such as lack of loyalty, proper communication, and financial constraints hinder the commitment of the members. The study concludes that the Baptist Cooperative commitment has the potential to strengthen denominational loyalty among Baptist churches in Nigeria. Hence, by addressing these challenges and building on the potential successes of the Cooperative Programme, the Nigerian Baptist Convention can further enhance unity and cooperation among its member churches, ultimately strengthening the denomination as a whole.
Phenomenology of Coping Strategies and Stress Among High School Adolescents
Authors: Kurniawaty Yuni , Veronica Silalahi  , Sri Winarni  , Ni Luh Agustini Purnama  , Baswara Yua Kristama
Published: May 2024

Stress cannot be avoided even by a teenager in high school. Some people use coping strategies to reduce stress. Coping strategies allow for more targeted and effective psychological interventions and will increase a person's ability to manage stress. The aim of this research is to analyze adolescents' coping strategies and stress. This research is a type of qualitative research using phenomenological methods. Research location High school. Determining research topics is inherently a snowball. The informants for this research were high school adolescents, teachers, and parents. The primary data collection technique involves conducting in-depth interviews using multiple informant interview guidelines. The process of data analysis includes: data reduction, data categorization, synthesis and ends with the development of a working hypothesis. Research findings revealed that adolescents are always stressed because stressors are always present in their lives. Internal and external sources of stress in adolescents have been found. Internal drivers of adolescent stress such as temperament, attachment, mastery, and self-determination processes. External factors observed in adolescents are social conditions, parental models and school processes. Several types of adolescent coping strategies have been shown to be adaptive and maladaptive. Adaptive coping strategies include reflection and self-reflection. Maladaptive coping strategies have been found to involve avoiding problems. Socialize to adolescents, parents and schools how to know adolescents better and help them in the developmental phase of searching for their own identity. The help of parents and stakeholders such as the school community is very important in this matter.
How social media algorithms influence the way users decide – Perspectives of social media users and practitioners
Authors: Poleac Gabriela , Gherguț-Babii Alexandra-Niculina
Published: May 2024

This study dives into the perspectives of social media users and practitioners on the impact of social media algorithms, with a focus on data curation, real-time personalization, and FOMO (fear of missing out). This research, which was conducted through two exploratory focus groups, uncovered the nuanced dynamics underlying users’ engagement with algorithms. The study of the literature emphasizes the importance of algorithms as gatekeepers in affecting online interactions, decision-making, and information intake. Our work, which is based on information foraging theory, reveals how algorithms, through characteristics such as FOMO, personalized content distribution, and the appearance of choice, profoundly shape users’ decision-making processes in the digital arena. Understanding these distinguishing characteristics reveals the psychological and behavioral elements that contribute to consumers’ continuous reliance on social media platforms. This study adds to the larger conversation about the societal implications of algorithmic influence and provides useful insights for researchers, practitioners, and policymakers navigating the ever-evolving landscape of digital interactions.
Interpersonal Conflict Resolution Styles of Pre-Marriage Student Couples Performing Abortions: A Case Study in Yogyakarta, Indonesia
Authors: Suciati Suciati , Anugrah Andika
Published: May 2024

A conflict cannot be avoided in a relationship. In the context of any relationship, there are bound to be differences in views or opinions between partners. This research examines how the conflict resolution styles of pre-marital student couples who have abortions achieve relationship sustainability. The method used in this research is descriptive qualitative. Data collection techniques were carried out through interviews with informants, namely the first pair JA and KS, and the second pair MS and IA. The data analysis technique in this research uses the Miles and Huberman interactive analysis model, starting with data collection, data reduction, data presentation, and conclusion. Based on the research results, it was found that there are different conflict resolution styles for both partners, influenced by the source and form of conflict. The case of the first couple of informants shows that they have a big source of conflict, namely religious differences and the desire for abortion. The form of conflict is a value conflict accompanied by verbal and non-verbal violence towards the partner. This happens because of the different personalities of each party and their lack of readiness to live a married life. In resolving conflicts, the first partner uses an avoidance style. The second pair of informants indicated that they had a major source of conflict namely infidelity and desire for abortion, disrespect, and abuse towards partners, which often triggers conflict in their relationship. This is a feeling of ego at their age which is not yet mature enough, so the form of conflict that occurs is ego conflict. In resolving the conflict that occurs, the second partner uses aggressiveness and argumentativeness strategies, namely the man uses verbal violence and arguments to corner his partner. The form of conflict resolution chosen by both partners cannot be separated from the personality of each partner, namely choleric-neurotic and nervous-neurotic.
Sustainability and Prosperity in Unison: The UAE's Path to Ambitious Targets through Circular Economy and Responsible Practices
Authors: Majeed Afseer
Published: May 2024

This article examines the United Arab Emirates (UAE) approach to the concept of circular economy to balance economic prosperity with sustainability. The UAE has set ambitious sustainability targets, including reducing greenhouse gas emissions and increasing the share of clean energy. The UAE has implemented various economic incentives to achieve these targets, such as carbon tax and subsidies for renewable energy investments. Business guidelines, such as the Emirates Green Building Council's rating system and Dubai Sustainable Industry Platform, have also been introduced to encourage sustainable practices among companies. The research shows the UAE's excellent approach to a circular economy has helped promote sustainable development and keep economic growth strong. The country's efforts have led to more industries using renewable energy and environmentally friendly practices. However, the study also identifies some challenges that need to be addressed, such as the need for more awareness and implementation of circular economy principles in some sectors. The research concludes that the UAE's approach to a circular economy is a good way to find a balance between economic growth and environmental protection. It shows how important ambitious goals, economic incentives, and business guidelines are for encouraging businesses and people to act sustainably. The study suggests that the UAE can continue to lead the way in the circular economy by addressing the challenges and promoting circular economy principles more widely
The Mediating Roles of Transformational Leadership and Workplace Gossip on The Relationship Between Organizational Justice and Organizational Virtuousness
Authors: Malhotra Nidhi , Aggarwal Rashmi
Published: May 2024

The purpose of this study is to examine direct and indirect effects of organisational justice on morale and virtuousness through transformational leadership and workplace gossip. An online questionnaire was used to purposively sample 385 participants from the pharmaceutical manufacturing industry in India for this study. Important predictors of organisational virtue were identified, including workplace gossip, transformational leadership, and organisational justice. The results of the study showed a strong correlation between virtue and organisational justice. Three significant additions are revealed: Firstly, managers who possess transformational leadership skills in addition to a grasp of organisational virtuousness can foster growth in both the company and its employees. 2) Promoting office gossips that are in line with moral principles creates a happy work atmosphere and improves employee output. 3) A greater understanding of organizational justice and virtuousness enhances wellbeing, which leads to improved productivity at work. There is a considerable correlation in the Indian pharmaceutical sector between workplace gossip, virtuousness, transformational leadership, and organisational justice. The latter two serve as mediators between virtuousness and justice. Business and workforce growth are facilitated by transformational leadership that cultivates organisational virtuousness. Creating an ethically sound and equitable workplace improves wellbeing and increases output. By identifying workplace gossip and transformational leadership as mediators between organisational justice and virtuousness in India's pharmaceutical manufacturing sector, this study enhances the applicability across industries and contributes to the management literature.
Cyber Security Trends in Education: A Scientometric Study
Authors: Arockiavathy S Antony , Kavitha R  , Aravind S
Published: May 2024

This paper presents a study on the quantitative analysis of global research trends in cybersecurity in education, focusing on 136 documents published between 2018 and 2022 retrieved from the Web of Science database. Various quantitative indicators were calculated and tabulated, and different graphs were plotted to understand growth patterns, citations with H-Index, country-wise contributions, affiliations, and other aspects. The study found the United States of America has the highest number of publications on cybersecurity in education research. Based on this, the authors suggest that Indian institutions should prioritize cybersecurity in education and strategize for the future with effective collaborations. The best defense strategy in cyberspace is preventive measures supported by continuous research efforts.
Long Non-Coding RNAs as Emerging Role in Prognosis of Alcohol Related Liver Disease
Authors: Nelaturi Prabhudas , Ravikumar Sambandam , P Kademani Sangeetha
Published: May 2024

Chronic alcohol exposure significantly influences the prognosis and diagnosis of alcohol related liver disease (ALD), affecting gene expression and liver function. Hepatic proteins and non-coding RNAs are essential for many biological functions and disease progression. Regulatory processes associated with microRNAs and long non-coding RNAs (lncRNAs) are known enhanced by recent advances in RNA sequencing methods. This new importance of lncRNAs in hepatic disease progression encompasses their involvement in cellular growth, and regulation, necrosis, and the control of transcriptional factors. Regulation of cellular integrity and ECM accumulation are two of the many functions played by lncRNAs in hepatic fibrosis, a wound healing process characterized by the gradual formation of ECM during disease progression. In the context of hepatic disease progression, a multitude of lncRNAs actively participate in regulating cellular homeostasis, positioning them as potential therapeutic targets and valuable biomarkers in clinical practice. Acquiring insightful knowledge about the underlying biological processes and molecular mechanisms governing hepatic injuries is crucial for identifying specific and sensitive molecules that can facilitate hepatic regeneration. The studies are increasingly interested in understanding the function of lncRNAs in liver regeneration after long-term alcohol use. To better understand alcoholic liver disease clinically, this review seeks to clarify the predictive significance of lncRNAs regulatory factors in stimulating hepatic development and revitalization.
The Impact of Task-Based Approach through Interdisciplinary Learning for Fostering Employability Skills among Technical Students
Authors: Kailas Mayuri , Bhatt Vinod
Published: May 2024

With the increasing need for a workforce with diverse skill sets, educational institutions face the challenge of inventing teaching techniques that transcend disciplinary limits and foster crucial skills for career success. Task-Based Approach employs in creating and executing educational activities that revolve around real-world tasks, promoting a dynamic learning atmosphere. In contrast, Interdisciplinary Learning places emphasis on merging various disciplines to tackle challenges and find solutions. This study investigates the efficacy of using a Task-Based Approach (TBA) within an interdisciplinary classroom to foster the employability skills of students. This study also adds to the current discussion about teaching methods that ready students for prosperous careers in a professional environment that is more interconnected and complex. This research adopts a quantitative approach, where an online questionnaire distributed via Google Forms to assess the effectiveness of the Task-Based Approach in an Interdisciplinary classroom. The study examines a sample size of 760 technical students from selected colleges in Madhya Pradesh. The statistical technique employed for analysis is Multiple Linear Regression in the SPSS software version 2023, enabling the exploration of correlations and variations among independent and dependent variables. Overall, this study underscores the significance of implementing Task-Based methodology through an Interdisciplinary learning in nurturing employability skills among technical students, thereby making a meaningful contribution to their personal and professional success.
Developing a Neural Network to Assess Staff Competence and Minimize Operational Risks in Credit Organizations
Authors: Chumakova Ekaterina , Korneev Dmitry , Gasparian Mikhail , Titov Valery , Makhov Ilia
Published: May 2024

The paper is devoted to the issues of controlling the operational risks of credit organizations associated with employees. One of the leading sources of operational risks associated with the actions of staff is insufficient employee qualification. This can cause a reduction in the accessibility and quality of the services offered by credit organizations, as well as potential financial and reputational losses. The goal of the study is to create an artificial neural network using a high-level Keras library in Python that would automatically monitor the level of critical personnel competence given its impact on the occurrence of operational risk events. The research objectives encompass analyzing employee competence indicators' influence on operational risk occurrence, identifying key indicators for an artificial neural network, determining its architecture, creating datasets, and conducting comparative analysis of trained neural networks. The article outlines the primary set of indicators producing the greatest impact on the possibility of the emergence of operational risk associated with the actions of the credit organization's employees. The paper also presents the results of testing the generated sets of training and test data using application software packages that implement mathematical methods to assess the consistency of the generated data sets. Graphs showing the results of training and testing of the constructed neural network are provided. The research findings are novel and can enable credit organizations to majorly automate the monitoring of personnel-related operational risk.
Improved Tuberculosis Detection through Deep Learning
Authors: Deepak Goutham
Published: May 2024

Tuberculosis (TB) is a significant public health challenge worldwide. Early and accurate diagnosis is crucial for effective treatment and containment of the disease. This research work addresses the problem by proposing a multi-model classification method for identifying TB cases from chest X-rays with high accuracy. It utilizes a dataset created from realtime patient data collected from TB hospitals. Additionally, a comparative analysis of two deep learning models is conducted for the accurate detection of TB from chest X-ray images. The models were assessed based on accuracy, precision, recall, and F1-score, with the one unconventional model demonstrating superior performance. This paper discusses the potential reasons for the observed discrepancies, including differences in model architecture, data handling, and training processes. Our findings suggest that the integration of the softmax activation function into binary classification models can have a beneficial impact on training efficiency, leading to improved performance in medical image analysis for Tuberculosis detection. Although softmax is mathematically equivalent to sigmoid in binary tasks, our results indicate a potential advantage in utilizing softmax that warrants further investigation. To further enhance the robustness of our approach, future research will focus on incorporating additional datasets from diverse populations and exploring the integration of ensemble learning techniques, aiming to increase the generalizability and reliability of TB detection in chest X-ray images across varied demographic groups.
Simposio Internacional de Neurocirugía Estereotáctica, Funcional y Dolor
Authors: Espinosa Martínez Jairo
Published: May 2024

Desde el 30 de abril al 2 de mayo de 2007 hemos tenido la satisfacción de celebrar en Cartagena de Indias, Colombia un exitoso evento que congregó a varios de los más destacados especialistas médicos y quirúrgicos de la Neurocirugía Estereotáctica, Funcional y Manejo del Dolor de nuestra América Latina.
Bajo la impronta multidisciplinaria que caracterizó a esta reunión recibimos el aval de la Sociedad Latinoamericana de Neurocirugía Funcional y Esteretotaxia (SLANFE), la Asociación Colombiana de Neurocirugía (ACN), la Asociación Colombiana de Neurología (ACN), la Asociación Colombiana de Psiquiatría Biológica y de la Asociación Colombiana para el Estudio del Dolor (ACED), todas con activa participación en el evento.
Asistieron al mismo más de cien especialistas y subespecialistas de distintas disciplinas que, involucrados.
Células precursoras hematopoyéticas en sangre periférica
Authors: Sanchez N , Minissale C , Martinez E , Malusardi C , Auat M , Altube A , Sciaccaluga D
Published: May 2024

En una medula ósea (MO) normal se detectan dos compartimentos de células que expresan CD34: una población principal que corresponde a las células precursoras hematopoyéticas (CPH) y una población minoritaria que corresponde a células endoteliales (células del estroma medular). Las CPH son una población celular heterogénea que incluye precursores CD34+ pluripotentes no comprometidos hacia ninguna línea celular y precursores CD34+ ya comprometidos. Dentro de esta última población, se observa compromiso a linaje linfoide B y hacia las diferentes líneas mieloides, es decir, compromiso a línea eritroide, megacariocítica, monocítica, mieloide granular neutrófila, a eosinófilos, y también a líneas mieloides minoritarias como basófilos, mastocitos y células dendríticas. En condiciones normales, un pequeño porcentaje de CPH (menor a 0,10%) se encuentran circulando en sangre periférica (SP), desde aquí migran a nichos medulares distantes con el objetivo de mantener niveles adecuados y constantes de hematopoyesis. Estas CPH circulantes, en su mayoría son CD34+ no comprometidas a ninguna línea celular(1). Bajo ciertas condiciones de estrés, como infecciones, tumores sólidos, ciertas neoplasias hematológicas, anemia, estrés metabólico o cambios en el microambiente hematopoyético, una gran cantidad de CPH son liberadas desde MO a SP, proceso conocido como “movilización”. Estas CPH movilizadas son la base para inducir hematopoyesis extramedular (HEM), mecanismo compensatorio para la hematopoyesis ineficaz de la MO(2). Los sitios más comunes para la HEM incluyen bazo e hígado, aunque también ha sido descripta en muchos otros tejidos, incluida la piel(3).
Recommended dosages of analgesic and sedative drugs in intensive care result in a low incidence of potentially toxic blood concentrations
Authors: Lennborn Ulrica , Johansson Anna , Lindgren Erik , Nielsen Elisabet I. , Sandler Håkan , Bertilsson Maria , Kronstrand Robert , Ahlner Johan , Kugelberg Fredrik C. , Rubertsson Sten
Published: May 2024

Background: Standard dosages of analgesic and sedative drugs are given to intensive care patients. The resulting range of blood concentrations and corresponding clinical responses need to be better examined. The purpose of this study was to describe daily dosages, measured blood concentrations, and clinical responses in critically ill patients. The purpose was also to contribute to establishing whole blood concentration reference values of the drugs investigated.
Methods: A descriptive study of prospectively collected data from 302 admissions to a general intensive care unit (ICU) at a university hospital. Ten drugs (clonidine, fentanyl, morphine, dexmedetomidine, ketamine, ketobemidone, midazolam, paracetamol, propofol, and thiopental) were investigated, and daily dosages recorded. Blood samples were collected twice daily, and drug concentrations were measured. Clinical responses were registered using Richmond agitation-sedation scale (RASS) and Numeric rating scale (NRS).
Results: Drug dosages were within recommended dose ranges. Blood concentrations for all 10 drugs showed a wide variation within the cohort, but only 3% were above therapeutic interval where clonidine (57 of 122) and midazolam (38 of 122) dominated. RASS and NRS were not correlated to drug concentrations.
Conclusion: Using recommended dose intervals for analgesic and sedative drugs in the ICU setting combined with regular monitoring of clinical responses such as RASS and NRS leads to 97% of concentrations being below the upper limit in the therapeutic interval. This study contributes to whole blood drug concentration reference values regarding these 10 drugs.
An Efficient Design of 2-BIT Arithmetic Logical Unit in Quantum Dot Cellular Automata
Authors: Gaurang Tyagi  , Ayushi Ojha  , Shivanshu Nanda
Published: May 2024

For the past two decades, CMOS technology has reigned supreme in the world of Very Large Scale Integration (VLSI). But Quantum Dot Cellular Automata (QCA) is stepping into the spotlight, offering a fresh solution to the growing challenges of CMOS. This paper delves into the potential of QCA circuits by presenting a 2-bit Arithmetic Logic Unit (ALU) crafted with this groundbreaking technology, while also benchmarking it against conventional CMOS designs. The proposed QCA-based ALU delivers a trifecta of benefits: streamlined circuit design, exceptional space efficiency, and reduced quantum cost—all while keeping performance sharp in terms of latency and area usage. This 2-bit ALU encompasses a suite of operations: addition, subtraction, multiplication, division, bitwise AND, OR, XOR, and XNOR. QCA technology addresses some of CMOS's major pain points, like slow switching speeds, and doesn't require additional power sources, making it both efficient and environmentally friendly. This is not just an incremental improvement; it's a bold leap into the future of circuit design
Effects of the Extensive Use of Mechanization on Farm Labor Use and Patterns in Rice and Corn Production Systems in the Philippines
Authors:   University of the Philippines Los Baños, Rodulfo, Jr Victor , del Rosario Alexis , Larona Maria Victoria , Salandanan Alfrederick , Bautista Mary Grace , Querijero Nelson Jose Vincent
Published: May 2024

The study assessed the status of farm labor use and changing patterns as a result of extensive mechanization in the farm labor sector. It showed that the extensive use of mechanization, specifically for land preparation, planting, harvesting, threshing, and shelling, decreased the demand for manual labor in terms of man-day per hectare requirement. The study indicated significant reports on the changes in labor arrangements in farm operations from planting-harvesting arrangement to land preparation-harvesting arrangement, payment agreement (daily wage to informal contract), and mode of contracting labor (hired to family labor). The study also showed significant reports of labor shifting of farm workers from on-farm to off-farm activities. Three (3) policy recommendations were provided as a result of the study: (1) organization and recognition of landless farmworkers; (2) provision of training, upskilling, and employment opportunities; and (3) integration of the organized landless farm workers as human capital input needed in the establishment of Farm and Fisheries Clustering and Consolidation Program (F2C2) of the government.
Towards a sustainable mobility as a service: general framework and models’ evolution
Authors: Musolino Giuseppe
Published: May 2024

The evolution of Mobility as a Service (MaaS) and the necessity to achieve sustainability goals, defined by Agenda 2030, impose to build a roadmap for: (i) define a Sustainable MaaS (S-MaaS) able to achieve sustainable goals by taking into consideration the emerging ICTs, (ii) define and develop Transport System Models (TSMs) to support the design of sustainable transport services for ex-ante and ex-post evaluations. This paper aims to address the study of S-MaaS with particular reference to the consolidated methodologies used in the transport systems for the design, management and monitoring of the transport services. The paper presents three main elements: (i) a framework that supports MaaS actors for services design, for demand management and for policies evaluation leaving from the monitoring, in order to implement a S-MaaS; (ii) the identification of the sustainability goals as defined by Agenda 2030; (iii) the methods to analyze passengers’ behavior in the presence of MaaS with particular reference to TSMs.
VOSA: A Reusable and Reconfigurable Voice Operated Support Assistant Chatbot Platform
Authors: Lutalo Joseph Willrich , J. Oyana Tonny
Published: May 2024

Current research shows that offering customer support in any form is a guaranteed means to boost and sustain business growth. Modern support services are steadily embracing automation to improve effectiveness, support scalability, and reduce costs, with the most promising approaches leveraging artificial assistants in the form of chatbots and interactive support services. In this paper, we employ the Design Science Research method to explore and then practically implement an original, reusable, re-configurable chatbot platform for designing and delivering autonomous product and customer support services leveraging voice interactions. Further, additional focus was placed on leveraging a scan-to-know information access model, and we especially considered users operating on mobile computers such as smartphones, with active connectivity. The implemented chatbot platform was explored and evaluated from the context of two practical cases; banking and hotel customer support. Important results obtained included; an original architecture of an autonomous, natural-interface, reusable and reconfigurable personal assistant chatbot platform; a working proofof-concept reference implementation of the VOSAC, currently published and accessible via the Google Play Store; a simple and efficacious method of encoding and expressing knowledge in the form of QAKBs, useful in extending/reconfiguring QAKB-compliant personal assistants such as the VOSAC, and finally, the realization of a Scan-toKnow information retrieval method for making access to autonomous support services more scalable and cheaper to implement.
Logical Analysis and Contradiction Detection in High-Level Requirements During the Revi̇ew Process using SAT-Solver
Authors: Yatkın Simge , Ovatman Tolga
Published: May 2024

DO-178C stands out as a guiding standard for aviation system development processes. This standard not only mandates ensuring the consistency of requirements in the software verification process but also recognizes it as a mandatory element. The main objective of this study is to introduce a method for analyzing and identifying inconsistencies between high-level requirements using information obtained from a data dictionary. This method aims to transform high-level requirements into logical expressions and then thoroughly examine them using a SAT Solver to detect inconsistencies. While methods focused on identifying inconsistencies among requirements often appear in the literature, this study presents a novel approach to detect contradictions between non-natural language, systematically structured, and language-independent requirements. The goal of this approach is to significantly reduce the review time of high-level requirements in the software verification process. Evaluations indicate that the use of this method results in substantial time savings in the inconsistency detection process.
An Intelligent Mobile Application to Assist in Mathematics Learning and Discussions using Advanced Sortings for Multiple Platforms
Authors: He Xi , Sun Yu
Published: May 2024

There is a growing need for a modern platform for learning and discussing mathematics. With the development of mobile technology, mathematicians worldwide can communicate easily with each other. This paper develops an application using simple AI and data structure to build a social network for everyone to learn and appreciate math with likeminded people. We use Firebase as a backend service provider for Authentication and cloud storage with blocking posts and comments feature. The app is great for math lovers worldwide, with our experiments showing that the mean time for a complete browsing section is approximately 14.545 milliseconds and a median of 13.8 milliseconds across regions. In addition, our built-in blocking mechanism will ensure that people can feel the inclusivity and openness that allows math ideas to freely flow without fear or prejudice. For this application, we took reliability, usability, and openness into consideration. The application aims to be an open platform for every math lover and encourage people to look at math more interactively.
Automation of Pet Behavior Improvement and Service Training using Artificial Intelligence and Computer Vision
Authors: Wang Shengyu , Sahagun Jonathan
Published: May 2024

Owning a dog brings with it a multitude of responsibilities, chief among them being the essential task of dedicating ample time to training [1]. While the specific time commitment may vary, effective training necessitates steadfast dedication and effort. Unfortunately, many dog owners struggle to allocate sufficient time, leading to untrained canine behavior [2]. Research indicates that approximately 75% of dogs worldwide lack proper training. Effective training serves as the bedrock of a harmonious human-canine relationship, fostering mutual understanding and safety [3]. Despite its paramount importance, training demands patience, consistency, and perseverance, qualities often underestimated by dog owners. Addressing this issue requires a shift in owners' perspectives, underscoring the significance of prioritizing training through professional guidance and obedience classes. Ultimately, investing in training not only enhances the quality of life for dogs but also strengthens the bond between owners and their cherished companions, showcasing the dedication necessary to ensure canine well-being in an ever-changing world.
An Innovative Digital Platform to Enhance CPR Training Accessibility and Effectiveness using Gamification and Interactive Simulations
Authors: Yang Kaiwen , Boulom Tyler
Published: May 2024

This paper addresses the critical gap in public knowledge and skill in performing Cardiopulmonary Resuscitation (CPR), a key factor in increasing survival rates in cardiac arrest scenarios [1]. Despite the importance of CPR, traditional training methods often fail to reach or engage the general population effectively. Our proposal introduces an innovative, interactive digital CPR training platform that combines the latest in educational technology with the principles of gamification and simulation-based learning [2]. Key components include a user-friendly interface, real- time feedback mechanisms, and scenario-based simulations that cater to a wide range of learning styles and environments. Challenges such as ensuring the physical accuracy of CPR techniques and broadening accessibility were addressed through the integration of adaptive learning algorithms and offline functionalities [3]. Experimentation across various settings demonstrated significant improvements in users' CPR knowledge, skills, andconfidence. The results underscore the platform's potential to democratize CPR training, making it more accessible, engaging, and effective. Our project offers a scalable solution to a widespread public health issue, advocating for itsadoption as a standard in CPR education.
Legal Documents Drafting with Fine-Tuned Pre-Trained Large Language Model
Authors: Lin Chun-Hsien , Cheng Pu-Jen
Published: May 2024

With the development of large-scale Language Models (LLM), fine-tuning pre-trained LLM has become a mainstream paradigm for solving downstream tasks of natural language processing. However, training a language model in the legal field requires a large number of legal documents so that the language model can learn legal terminology and the particularity of the format of legal documents. The typical NLP approaches usually rely on many manually annotated data sets for training. However, in the legal field application, it is difficult to obtain a large number of manually annotated data sets, which restricts the typical method applied to the task of drafting legal documents. The experimental results of this paper show that not only can we leverage a large number of annotation-free legal documents without Chinese word segmentation to fine-tune a large-scale language model, but more importantly, it can fine-tune a pre-trained LLM on the local computer to achieve the generating legal document drafts task, and at the same time achieve the protection of information privacy and to improve information security issues.
Lyrically Yours: A Mobile Application for Automated Music Therapy through Lyric Analysis Utilizing Natural Language Processing and Machine Learning
Authors: Yang Yuqi , Sun Yu
Published: May 2024

Music plays a vital role in therapy, offering a unique avenue for emotional expression and connection. This proposed project seeks to enhance the effectiveness of music therapy by leveraging natural language processing (NLP) techniques and machine learning to provide personalized song recommendations based on both emotional and narrative elements within lyrics, moving beyond traditional approaches that focus solely on emotional categorization [4]. By utilizing keyword matching algorithms, the project expands the scope of song selection, allowing users to explore music beyond predefined emotional categories [5]. The proposed system integrates with Firebase for efficient data storage and retrieval, while the Flutter framework facilitates the development of a user-friendly mobile application interface [6]. Through this interdisciplinary approach, the project endeavors to offer an accessible and automated music therapy experience.
SyntaxStar: An Adaptive Desktop Program Management System for Enhanced Focus and Productivity in Writing using NLP and Machine Learning
Authors: He Kyle , Gonzalez Carlos
Published: May 2024

SyntaxStar, a desktop program management system, aims to enhance writing quality for users. Ineffective word choices hinder engagement and effective communication, contributing to reading struggles among eighth graders which often leads to a challenging pathway in higher education [7]. SyntaxStar addresses these concerns, emphasizing the importance of writing as a fundamental communication skill, and is driven by the goal of avoiding repetition and improving clarity. Upon creation of this project, things to note are that there exists no current method to update the software automatically for users. There is also no current way of receiving user feedback, which can significantly maintain the longevity and integrity of the software design. Despite this, the pipeline has been solidified and working with an interactive frontend, a comprehensive backend that hosts the application and machine learning model [9]. With regards to performance, the concept of word similarity in the Word2Vec library was applied to not only cross-check words with their paired synonyms but also to assign a score for these synonyms [8]. Cosine similarity scores were applied and distributed onto a plot which showcases how accurately the model classified words with their appropriate synonym. In the future, the model can improve by looking at a more intensive preprocessing section by shuffling words and their parts of speech, prior to recommending a synonym. This is for the sake of adding variability and reducing bias for synonyms that wouldn’t make sense in certain contexts. To propel future growth, more marketing and publications should be incorporated to generate awareness and usage of the app. Developing more components for the software, such as a dedicated website serving as the landing page for a downloadable version, would also be beneficial.
Comparing Carotid Artery Stenting and Carotid Endarterectomy in Symptomatic and Asymptomatic Carotid Stenosis
Authors: Khan Rizwan , Jamil Mughal Usman , Manzoor Bhatti Ahsin , Bin Saif Anas , Badshah Athar , Nofal Sabih
Published: May 2024

Objective: In patients with symptomatic and asymptomatic carotid artery stenosis, this retrospective observational study compared the clinical outcomes and side effects of carotid endarterectomy (CEA) with carotid artery stenting (CAS). The study took patient-specific risk variables into account and concentrated on major adverse cardiovascular events (MACE), such as myocardial infarction (MI), stroke, readmission, and death. Material and Method: This was a retrospective observational study carried out at Vascular Surgery Department and Interventional Radiology department of two tertiary care hospitals in Rawalpindi, from Jan 2022 to March 2023. With a 30-day follow-up, 60 patients from two Pakistani tertiary care centres underwent either carotid end arterectomy and carotid artery stenting were included. Patient having asymptomatic and symptomatic carotid disease were selected for the procedure. The impact of risk factors on procedural success and development of major adverse cardiovascular events (MACE) was examined in the study. Data regarding 30-day postoperative parameters of the procedure were collected and evaluated. p< 0.05 is considered significant. Results: The majority of patients in our series were males 46(77%) compared to 14(23%) females in the study. There were no intraoperative mortalities in our patients. The mortality rate of CAS alone was 1(1.66%). Four patients developed complications. Three in CAS group and 1 in CEA group. Comorbidities were present in 46(77%). Conclusion: Compared to CEA, CAS is linked to a greater risk of stroke or mortality in patients with symptomatic carotid stenosis within 30 days of treatment. Patients' unique characteristics, age, comorbidities, and previous surgical experiences should guide the choice of treatment.
Does Colchicine Prevent Progression to Artificial Ventilation in Covid-19 Positive Patients? A Study from Lahore, Pakistan
Authors: Suhail Rana Maaz , Ghazanfar Jawaria , Sarwar Huda , Sarwar Erum , Umer Farooq Muhammad , Usman Muhammad
Published: May 2024

Objective: To find out the effect of colchicine in prevention of progression to artificial ventilation in Covid-19 patients including young and elderly patients. Material and Methods: Study was conducted from 1st April 2020 till 30th September 2020 in a private, tertiary care hospital of Lahore. A retrospective cohort study was conducted on conveniently selected 179 PCR or radiologically confirmed Covid-19 positive adult and elderly, male and female patients admitted in Covid ward and Intensive care Unit (ICU) using the electronic as well as paper-based record. Amongst these patients, 33 patients were given colchicine, 137 recovered and 20 progressed to invasive ventilation. Result: Total 179 patients were included int the study and 96 (53.6%) were males and 83 (46.4%) were females. 52.5% had Diabetes mellitus, 58.7% had hypertension, 27.9% had ischemic heart disease, 8.4% had renal disease, 6.7% had lung disease/smoker. The average length of stay in hospital was 6.569±6.355 days. The outcome and progression to artificial ventilation in the patients who were given colchicine as compared to those who were not given colchicine were not statistically significant with a p value of 0.053 and 0.619, respectively. Conclusion: Colchicine has not shown a significant improvement in the outcome of Covid-19 and does not help in prevention of progression to invasive ventilation irrespective of age, gender, and co-morbidities.
An Interpretive Case Study of Chinese New Zealanders’ Participation in Non-elected Representation
Authors: Du Yu
Published: May 2024

This paper adopts Michael Saward’s representative claims theory to analyze Chinese New Zealanders’ participation in non-elected representation. It explores how they made representative claims and examines the democratic legitimacy of their claims. Based on an interpretive analysis of in-depth interviews with 38 Chinese New Zealanders, I found age-based and educational-level-based patterns of how they participate in non-elected representation. Individuals and Chinese associations made representative claims based on various grounds. However, the democratic legitimacy of individual-made claims and association-made claims varied. When interviewees made representative claims, they cherished the claims’ instrumental goals and intrinsic values. These findings expand our knowledge of Chinese New Zealanders’ political participation and representation. This paper also analyzes the difference between making representative claims and political advocacy. It deepens our understanding of non-elected representation.