bluuebunny/crossref_metadata_2025 huggingface dataset:
Income of workers in industrial parks post-COVID-19 pandemic: The raised issues in Vietnam
Authors: Thuy Cu Thanh , Anh Nguyen Tuan
Published: January 2025

This study aimed to analyze the adaptation of workers in industrial parks in Vietnam post-COVID-19 through fluctuations in their income. Data were collected from a survey of 438 workers working in industrial parks and in-depth interviews with five workers in different positions in industrial parks. The study utilized the ordinary least squares (OLS) method to quantify the factors influencing workers’ income. Additionally, the difference test method was applied to assess the income variations among workers based on their professional qualifications and occupational skills. The most significant factor identified is the experience of workers (unstandardized coefficient = 0.271), followed by the education level of workers (unstandardized coefficient = 0.128). Additionally, the study reveals that differences in professional qualifications lead to an income disparity of 1.898 million VND per month, while the variations in complementary skills contribute to an income difference of 0.592 million VND per month. Furthermore, the adaptation of workers in Vietnam’s industrial parks post-COVID-19 is at a relatively good level. From there, the study suggests several solutions to enhance workers’ income to adapt to new post-COVID-19 conditions.
Sinema ve Resim Sanatının Kesişen Noktası: Andrei Tarkovski
Authors: Bakırcılar Günay
Published: January 2025

Bu makale, sinema sanatı ve resim sanatının kesişen noktası olarak “Andrei Tarkovski” filmleri üzerinden görsel çözümleme yapmayı amaçlamaktadır. Araştırma kapsamında, Tarkovski sinemasının resim sanatı ile bağı incelenmiş, Leonardo Da Vinci, Albrecht Dürer, Andrei Rublev, Pieter Bruegel, Rembrandt, Jan Van Eyck, Casper David Friedrich gibi sanatçıların eserleriyle Tarkovski’nin film kareleri arasında eser çözümlemesi yapılmıştır. Eser çözümlemesinde “göstergebilim yöntemleri” kullanılmış, Tarkovski’nin sanatsal üretiminde beslendiği Aristoteles, Deleuze, Dostoyevski gibi düşünürlerin görüşlerine başvurulmuştur. Araştırmada “dokuman analizi” yöntemi kullanılmış, konu ile ilişkili basılı ve dijital ortamlarda yer alan kaynaklar kullanılmıştır. Güncel sanatçı ve yönetmenlerin, eserlerinde Tarkovskivari motiflere rastlanılmıştır. Sanatçı ve yönetmenler arasında; Sarkis Zabunyan, Terence Malik, Alejendro Gonzalez Inarritu, Nuri Bilge Ceylan ve Murat Düzgünoğlu yer alıp film sahneleri arasında benzerlikler görsellerle desteklenmiştir. Son olarak Tarkovski’nin hayatına yer verilmiştir. Araştırmanın sonucunda; Andrei Tarkovski’nin eserlerinin, dünyasının günümüz sanat anlayışında halen var olması farklı sanatsal alanlarda yeniden üretilmesi, yorumlanması makaleye yeni bir bakış açısı getirebileceği yönündedir.
Otorhinolaryngology and Metabolic Syndrome
Authors: Mohamed Salah Rashwan
Published: January 2025

Metabolic syndrome (MS) is a diverse condition linked to an elevated risk of
cardiovascular issues. Emerging evidence from various types of research, including
experimental, translational, and clinical studies, has indicated that obstructive sleep
apnoea (OSA) is connected to both existing and newly developing aspects of MS. The
plausible biological explanation centers primarily around one of OSA's main features,
intermittent hypoxia. This leads to heightened sympathetic activity with cardiovascular
consequences, increased liver glucose production, insulin resistance due to
inflammation in adipose tissue, dysfunction in pancreatic β-cells, elevated lipid levels
through deteriorating fasting lipid profiles, and decreased removal of triglyceride-rich
lipoproteins.
While several interconnected pathways exist, the clinical evidence primarily relies on
observational data, making it difficult to establish causality. The co-occurrence of
visceral obesity and potential confounding factors like medications complicates the
assessment of OSA's independent impact on MS. In this chapter, we re-evaluate the
evidence regarding how OSA and intermittent hypoxia may contribute to adverse
effects on MS parameters independently of body fat. We place particular emphasis on
recent findings from intervention studies. This chapter outlines the research gaps, the
challenges faced in the field, potential directions for future exploration, and the
necessity for more high-quality data from intervention studies that address the
influence of both established and promising therapies for OSA and obesity.
Do you want to get hit by a car? Then move like a GTA character!
Authors: Davies Nina
Published: January 2025

This contribution presents a fictional script in the form of a conversation between two former law students on their podcast, Learned Friends. The dialogue revolves around an incident involving a self-driving car designed to predict pedestrian movements, exploring the legal complexities arising from the integration of predictive technologies in the justice system. The script was used as narration for a film that was featured in Precursing, a solo exhibition by the author at Matt’s Gallery in October 2023. As part of this issue of Documenta, the artist has included annotations that connect the fictional narrative to the research underpinning it. These annotations touch upon topics such as the Hammersmith Ghost case and issues of mistaken belief, the prohibition of photography and radio broadcasts following the Lindbergh baby kidnapping trial, the infiltration of artistic technologies into formal and bureaucratic sectors, the training and testing of self-driving cars in Grand Theft Auto, and the introduction of predictive technologies in judicial processes. Through this work, the author seeks to explore how the use of emerging technologies in storytelling impacts their application in fields where information accuracy is paramount.
IA GENERATIVA: POTENCIAL E LIMITAÇÕES DOS LARGE LANGUAGE MODELS E PROMPTS NA PRODUÇÃO DE NOTÍCIAS
Authors: Ioscote Fabia
Published: January 2025

A expansão da Inteligência Artificial Generativa (GenAI), exemplificada pelo ChatGPT e MidJourney, destaca a crescente tendência de criação de conteúdos textuais e visuais por meio de software. Esse estudo examina como os softwares de GenAI podem auxiliar na produção de notícias, discutindo seus potenciais e limitações. Os objetos empíricos são ChatGPT (OpenAI), Gemini AI (Google) e MariTalk (Maritaca AI). A metodologia qualitativa e exploratória inclui uma revisão de literatura e o desenvolvimento de um protocolo de testes e critérios de avaliação, abordando aspectos computacionais e jornalísticos, como títulos, leads, uso de fontes e precisão. Os resultados indicam que, embora não gerem diretamente conteúdos noticiosos, os softwares de GenAI podem ser assistentes úteis nas redações, melhorando textos e sugerindo ideias, em um equilíbrio entre a automação e o julgamento editorial humano.
Palavras-chave: jornalismo; automação; geração de linguagem natural; software; comunicação digital.
Abstract
The expansion of GenAI, exemplified by ChatGPT, and MidJourney, highlights the growing trend of creating textual and visual content through software. This study examines how GenAI software can assist in news production, discussing their potential and limitations. The empirical objects are ChatGPT (OpenAI), Gemini AI (Google), and MariTalk (Maritaca AI). The qualitative and exploratory methodology includes a literature review and the development of a testing protocol and evaluation criteria, addressing computational and journalistic aspects such as titles, leads, font usage, and accuracy. The results indicate that, although they do not directly generate news content, GenAI software can serve as useful assistants in newsrooms, enhancing texts and suggesting ideas, striking a balance between automation and human editorial judgment.
Keywords: journalism; automation; natural language generation; software; digital communication.
Resumen
La expansión de la inteligencia artificial generativa (GenAI), ejemplificada por ChatGPT y MidJourney, destaca la creciente tendencia a crear contenidos textuales y visuales mediante software. Ese estudio examina cómo los programas de GenAI pueden ayudar en la producción de noticias, discutiendo sus potencias y limitaciones. Los objetos empíricos son ChatGPT (OpenAI), Gemini AI (Google) y MariTalk (Maritaca AI). La metodología cualitativa y exploratoria incluye una revisión de literatura y el desarrollo de un protocolo de pruebas y criterios de evaluación, desarrollando aspectos computacionales y periodísticos, como títulos, leads, uso de fuentes y precisión. Los resultados apuntan que, aunque no generan directamente contenidos de noticias, los softwares de GenAI pueden ser asistentes útiles en las redacciones, mejorando textos y sugiriendo ideas, en un equilibrio entre la automatización y el juicio editorial humano.
Palabras clave: periodismo; automatización; generación de lenguaje natural; software; comunicación digital.
Community-Based 4-Level Intervention Targeting Depression and Suicidal Behavior in Europe: Protocol for an Implementation Project (Preprint)
Authors: Schnitzspahn Katharina , Abdulla Kahar , Arensman Ella , Van Audenhove Chantal , Mere Rainer , Pérez Sola Victor , Sisask Merike , Székely András , Toczyski Piotr , Hegerl Ulrich
Published: January 2025

BACKGROUND

The community-based, 4-level intervention of the European Alliance Against Depression (EAAD) is simultaneously addressing depression and suicidal behavior. Intervention activities target primary care health professionals (level 1), the general public (level 2), community facilitators (level 3), and patients and their relatives (level 4). Activities comprise the digital iFightDepression tool, a guided self-management tool based on cognitive behavioral therapy.

OBJECTIVE

This study aimed to present the European Union–cofunded EAAD-Best study protocol, aiming at the implementation, dissemination, and evaluation of the 4-level intervention and the iFightDepression tool in several countries across Europe.

METHODS

The 4-level intervention has been implemented for the first time in Bulgaria, Estonia, Greece, and Poland. In 3 countries that have already implemented the 4-level intervention (Hungary, Ireland, and Spain), activities have been extended to new regions. In addition, the nationwide uptake of the iFightDepression tool by patients with depression has been promoted in all mentioned countries and Italy.

RESULTS

To evaluate the implementation of the 4-level intervention and the iFightDepression tool, data related to the process, output, and outcome were collected between 2022 and 2024. Data processing and analyses started in 2023. Analyses are expected to be completed in 2024. Results are expected to be published in 2025.

CONCLUSIONS

This paper informs researchers, practitioners, and stakeholders on how to implement best practices in mental health promotion and evaluate their effectiveness.

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/64218
Diversidad del perfil emprendedor en Puebla, México: un enfoque probabilístico
Authors: Texis Flores Michelle , Saavedra-Leyva Rafael Eduardo , Contreras Flores Daniela
Published: January 2025

El presente artículo examina cómo es que las características individuales influyen en la probabilidad de elegir emprender frente a otras opciones laborales, y permite comprender la diversidad de los emprendedores. Se consideran cuatro categorías de ocupación: empleadores, subordinados y remunerados, trabajadores sin pago y por cuenta propia. La metodología empleada corresponde a su vez a un modelo de elección múltiple que permite examinar las decisiones individuales entre diferentes alternativas de elección. El estudio revela que la educación superior se asocia con mayor empleo asalariado, mientras que las personas con educación básica tienden más al emprendimiento en edades avanzadas. Además, se identificaron diferencias de género en la propensión a emprender.
BlockFund: A Blockchain-Based Platform for Secure and Transparent Investment Management
Authors: Kumar Ajeet
Published: January 2025

BlockFund is a blockchain-based investment management platform designed to revolutionize how investments are
managed and tracked. Traditional methods of investment often lead to inefficiencies, lack of transparency, and the possibility of
mismanagement, causing frustration for both investors and project creators. BlockFund solves these problems by harnessing
blockchain technology and smart contracts to create a transparent, secure, and milestone-driven investment ecosystem. With
BlockFund, funds are released automatically upon achieving predefined project milestones, ensuring accountability and
reducing the risk of fraud. The decentralized nature of the platform eliminates the need for intermediaries, significantly cutting
costs and streamlining the funding process. Investors can track their contributions in real time through an immutable ledger,
building trust and confidence in the system.
BlockFund is versatile in catering to a wide range of projects-from start-ups to large-scale ventures-and democratizes access to
investment opportunities for entrepreneurs and investors alike. BlockFund, by incorporating features like tokenization and a
refund mechanism, ensures a safe and inclusive environment for the management of investments. In this innovative approach,
BlockFund addresses the limitations that traditional funding systems have encountered and opens up avenues for an efficient
and transparent financial future.
ANALISIS TEKNIKAL DAN FUNDAMENTAL TERHADAP HARGA SAHAM PADA PERUSAHAN ROKOK DI BURSA EFEK INDONESIA SAAT PANDEMI COVID TAHUN 2020-2022
Authors: Putra Geovany Ilyas , Susilowati Dwi
Published: January 2025

Penelitian ini bertujuan untuk mengetahui adanya pengaruh analisis teknikal dan fundamental terhadap harga saham pada perusahan rokok di bursa efek indonesia saat pandemi covid tahun 2020-2022. Data yang digunakan bersumber dari Bursa Efek Indonesia (BEI). Analisis yang digunakan dalam penelitian ini adalah analisis regresi data panel dengan menggunakan pendekatan Fixed Effect Model (FEM) untuk mengetahui adanya pengaruh antara analisis teknikal dan fundamental terhadap harga saham. Berdasarkan hasil analisis menunjukkan bahwa analisis teknikal dan fundamental berpengaruh terhadap harga saham pada perusahaan rokok yang terdaftar di bursa efek indonesia.
PENGARUH STRUKTUR MODAL, PROFITABILITAS, DAN INFLASI TERHADAP HARGA SAHAM SUB SEKTOR FARMASI
Authors: Millah Rifadhatul , Susilowati Dwi , Hadi Syamsul
Published: January 2025

The pharmaceutical industry is the fourth largest non-oil and gas manufacturing industry contributing to the national economy. With its strong potential and being one of the engines of economic growth, the pharmaceutical industry plays an important role in the industrial landscape in Indonesia. The aim of this research is to analyse the influence of capital structure, profitability and inflation on pharmaceutical stock prices. The population in this research are companies operating in the pharmaceutical sector and listed on the Indonesia Stock Exchange (BEI) in 2017-2021. The sample method for this research uses a purposive sampling method, namely companies that always publish financial reports for 5 periods from 2017 to 2021. So a sample of 6 pharmaceutical companies was obtained with a total of 12 observation data. This research uses secondary data with research data collection techniques in the form of documentation methods. The data analysis used is panel data regression analysis. The results of this research show that together capital structure, profitability and inflation have a positive and significant influence on pharmaceutical stock prices, where if the values ​​of these three variables increase, pharmaceutical stock prices will also increase.
Desenvolvimento e validação de formulário on-line para busca ativa de reações adversas a medicamentos
Authors: Garcia Marton Ana Clara , Souza Anacleto de Araújo Dyego Carlos , Ribeiro Gonçalves Rita de Cássia , Caniçali Primo Cândida
Published: January 2025

Introduction: Pharmacovigilance is a science related to the early detection and prevention of events associated with the use of drugs, such as adverse drug reactions (ADR). Active surveillance methods are increasingly being used to detect ADRs. Although the use of triggers is recommended, active Search tools for suspected ADR are scarce in the literature. Objective: To develop an active search tool for suspected ADR using triggers. Method: This methodological development study was conducted and divided into two stages: i) a literature review to build a list of triggers and the first version of the instrument; ii) content validation using the Delphi technique with the participation of professionals  involved in Pharmacovigilance and Patient Safety at the institution. Instrument sessions were considered valid when the Content Validity Index (CVI) ≥ 0.80. Results: An online form was developed on the Google Forms platform containing three sections: review of medical records, patient and hospitalization data, and identification of suspected ADR. The final version has 28 questions, including 16 objective and 12 subjective. The material was evaluated by seven experts in two Delphi rounds, and the total CVI was 1. Conclusions: The instrument shows evidence of validity in terms of objective, structure, relevance, appearance, and content, representing another Pharmacovigilance tool for the hospital. It can be used by healthcare professionals from different backgrounds and is easily adaptable to the reality of other institutions. Future work should be carried out to validate the tool with the target audience.
The Importance of Effective Access to Justice for Charter Violations and the Role of the Court Challenges Program
Authors: Samson Marika Giles
Published: January 2025

This paper argues that the Canadian Charter of Rights and Freedoms can only deliver on its promises when those who benefit from its guarantees are able to challenge government action in courts. This is true both in considering the Charter as a constitutional document and as a human rights instrument. As such, we must be concerned about whether rightsholders have effective access to the courts to bring such cases, particularly given the long-term crisis in access to justice in Canada. Finding that access is often out of reach, the paper then considers the role that the Court Challenges Program, a publicly funded not-for-profit organization that provides funding to groups and individuals seeking to bring Charter challenges, can and does play in creating pathways for accessing Charter justice.
Un rond dans un carré: l’expérience professionnelle des spécialistes de la justice réparatrice dans le cadre d’un programme québécois de déjudiciarisation pour adultes
Authors: Marceau Laurence , Rossi Catherine
Published: January 2025

En 2017, le premier programme de déjudiciarisation en matière de criminalité adulte pour personnes non autochtones a été instauré au Québec. Le programme de mesures de rechange général implique la participation des professionnels de la justice réparatrice pour orchestrer ces mesures. Cet article présente des analyses secondaires de données qualitatives recueillies dans le cadre d’une recherche menée par une équipe de l’Université Laval. Il vise à mettre en lumière l’expérience subjective des spécialistes de la justice réparatrice dans le cadre de l’intégration du programme à leur quotidien professionnel, par le prisme de l’identité professionnelle. Les résultats montrent que l’intégration de ce programme a engendré de nombreuses (ré)flexions chez les médiateurs et une revitalisation de leur culture professionnelle. Ils révèlent également des enjeux liés au déploiement de la justice réparatrice à l’intérieur du programme et du système pénal, et à l’accès à la justice sociale en général.
Probing The Data: Perspectives on Race Visibility in Canadian Sentencing Proceedings
Authors: Jones Danardo Sanjay
Published: January 2025

This article analyzes interview data from nine Black criminalized individuals and nine defence lawyers (five white, three Black, and one Arab) about the utility of heightened race visibility in sentencing proceedings. The data reveals a schism between these groups, reflecting different responses to what I refer to as “the paradox of visibility.” For Black people, this paradox occurs when an emphasis on race may simultaneously have a deleterious and ameliorating impact on sentencing. Defence lawyers and judges laud the ameliorative potential of race visibility, which obscures the genuine concern shared by criminalized Black individuals about how they believe their Blackness betrays them in the criminal sentencing context. In this regard, the article explores ethical concerns arising from this paradox. It also argues that race-based strategies at sentencing are not a no-cost or low-cost proposition. Indeed, from the criminalized research participants’ point of view, the cost is not only the risk that an emphasis on race may result in a higher sentence, including longer and harsher custodial sentences, but also an affront to their dignity. In contrast, the defence lawyers strongly supported increased racial visibility to combat what they saw as judicial and prosecutorial intransigence to grapple with race in sentencing proceedings. These perspectives are critical for sentencing judges tasked with sentencing Black individuals and for lawyers who are developing and deploying legal strategies to assist their Black clients.
Multi-Functional Access to Justice Centres
Authors: Afilalo Nathan , Escott Daniel , Zariski Archie
Published: January 2025

In recent years, the integration of digital technology into the Canadian judicial system has accelerated, driven by both technological advancements and the urgent needs highlighted by the COVID-19 pandemic. This article explores the transformative potential of digital justice within Canadian courts, focusing on a proposal to repurpose circuit court facilities as "Access to Justice Centres" [AJCs]. These centers aim to address existing access to justice issues by providing state-of-the-art digital interfaces and centralizing court functions while preserving the dignity and decorum of in-person proceedings. Our analysis evaluates the successes and challenges of digital technologies in judicial processes, informed by empirical research with Canadian judges. The findings suggest that while digital tools have enhanced judicial efficiency and access to justice, significant disparities remain, particularly for marginalized communities. By leveraging user-centric design principles and existing infrastructure, AJCs could offer innovative solutions to bridge these gaps, ensuring that digital justice benefits all sectors of society. This article contributes to the ongoing dialogue on judicial reform, emphasizing the need for a thoughtful and inclusive approach to integrating technology in the administration of justice.
Development of face image recognition algorithm using CNN in airport security checkpoints for terrorist early detection
Authors: Anggraini Eca Indah , Nurdin Fachdy , Restianto Mohammad Obie , Dahsan Sudarti , Ardhana Andini Aprilia , Supriyadi Asep Adang , Darmawan Yahya , Arief Syachrul , Ikhsanudin Agus Haryanto
Published: January 2025

Ensuring airport security is of paramount importance to safeguard the lives of passengers and prevent acts of terrorism. In this context, developing advanced technology for early terrorist detection is crucial. This paper presents a novel approach to enhancing security measures at airport checkpoints by applying Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) algorithms in face image recognition. Our system utilizes state-of-the-art artificial intelligence techniques to analyze facial features. Our research uses VGG architecture and pre-trained with face data as a CNN model. This model is used to extract face embedding features from the dataset. These embedding features are then compressed with Principal Component Analysis (PCA) to obtain the meaningful feature as training data for the ANN algorithm. We trained our system using data from 500 identities data with 60 data for each identity.  This training enables our system to recognize known terrorists and individuals on watchlists by comparing the facial features of individuals passing through security checkpoints with those in the database. The proposed CNN-ANN-based face recognition system not only enhances airport security but also significantly reduces the processing time for security checks. It can quickly identify potential threats, allowing security personnel to take appropriate actions in real time ensuring a rapid response to security concerns. We present the architecture, training methodology, and evaluation of the CNN-ANN model, achieving a high accuracy of 91.16% and precision of 91.36%. Through this research, we aim to increase airport security and strengthen efforts to combat terrorism, making air travel safer and more secure for all passengers.
Spatial decision-making model for priority development of Indonesia coast guard stations
Authors: Adiatmaja Novianto Hary , Septiani Winnie , Dewayana Triwulandari Satitidjati , Luis Martino
Published: January 2025

Indonesia Coast Guard (IDNCG) is a paramilitary agency in charge of security and safety patrols in Indonesian maritime waters. The research objective is to develop priorities for the development of 35 IDNCG stations are expected to be constructed within 3 years and are considered priority project to face the increasing threats at sea. However, there is presently no system to provide support for the scientific solutions to prioritize station development despite the need for immediate decisions. This research was used to design model for determining station development priorities using the integration method of Geographic Information Systems (GIS), Analytical Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). GIS was used as an effective tool for identifying and taking measurements in certain areas. Meanwhile, multi-criteria decision-making (MCDM) methods such as AHP and TOPSIS provided structural and pairwise quantification, as well as comparisons between elements and criteria for ranking station construction priorities. The most suitable alternative stations to be prioritized were determined by integrating the three methods which were classified as cost-effective for decision-making. Model was based on four criteria, including distance to Archipelagic Sea Lanes (ASL), Distance to the port, vulnerability coverage, and vessel density coverage. Stations were ranked based on a three-year development plan. The location ranking is then expressed in the form of a map to be used by policy makers in determining priorities for developing IDNCG Stations which will have an impact on increasing security and safety in Indonesian waters.
Support Vector Machine (SVM) based Detection for Volumetric Bandwidth Distributed Denial of Service (DVB-DDOS) attack within gigabit Passive Optical Network
Authors: Bibi Sumayya , Zulkifli Nadiatulhuda , Safdar Ghazanfar Ali , Iqbal Sajid
Published: January 2025

The dynamic bandwidth allocation (DBA) algorithm is highly impactful in improving the network performance of gigabit passive optical networks (GPON). Network security is an important component of today’s networks to combat security attacks, including GPON. However, the literature contains reports highlighting its vulnerability to specific attacks, thereby raising concerns. In this work, we argue that the impact of a volumetric bandwidth distributed denial of service (DVB-DDOS) attack can be mitigated by improving the dynamic bandwidth assignment (DBA) scheme, which is used in PON to manage the US bandwidth at the optical line terminal (OLT). Thus, this study uses a support vector machine (SVM), a machine learning approach, to learn the optical network unit (ONU) traffic demand patterns and presents a hybrid security-aware DBA (HSA-DBA) scheme that is capable of distinguishing malicious ONUs from normal ONUs. In this article, we consider the deployment of the HSA-DBA scheme in OMNET++ to acquire the monitoring data samples used to train the ML technique for the effective classification of ONUs. The simulation ﬁndings revealed a mean upstream delay improvement of up to 63% due to the security feature offered by the mechanism. Besides, signiﬁcant reductions for the upstream delay performance recorded at 63% TCONT2, 65% TCONT3, and 95% TCONT4 and for frame loss rate reduction for normal ONU traffic, respectively, were observed in comparison to the non-secure DBA mechanism. This research provides a significant stride towards secure GPONs, ensuring reliable defense mechanisms are in place, which paves the way for more resilient future broadband network infrastructures.
Performance evaluation of hyper-parameter tuning automation in YOLOV8 and YOLO-NAS for corn leaf disease detection
Authors: Saputra Huzair , Muchtar Kahlil , Chitraningrum Nidya , Andria Agus , Febriana Alifya
Published: January 2025

Corn cultivation was crucial in Southeast Asia, significantly contributing to regional food security and economies. However, leaf diseases posed a significant threat, causing substantial losses in production and quality. This research utilized artificial intelligence (AI) technology to address this issue by automating the hyper-parameter tuning process in YOLO (You Only Look Once) object detection models for early corn leaf disease detection. High-resolution images of corn leaves were captured and preprocessed for consistency. The preprocessing stage involved creating new dataset folders for images and labels, resizing images while preserving their aspect ratio, and rotating them if necessary. The images, containing 11,596 labeled instances, were analyzed using YOLOv8 and YOLO-NAS models. Each image's detected disease regions were converted into YOLO-format text files with x, y, width, and height coordinates, describing the presence and severity of infections. The models' performances were evaluated using precision, recall, mAP50, and mAP50-95 metrics. YOLOv8m achieved a mAP50 of 98.5% and mAP50-95 of 67.8%, while YOLO-NAS-L demonstrated superior detection capabilities with a mAP50 of 70.3% and mAP50-95 of 38.9%. This automated system facilitated early disease identification and enabled prompt preventive measures, thereby enhancing crop yields and mitigating losses. The findings highlighted the potential of advanced AI-driven detection systems in revolutionizing crop management and supporting global food security.
Classification of palm oil fruit ripeness based on AlexNet deep Convolutional Neural Network
Authors: Kurniawan Rudi , Samsuryadi Samsuryadi , Mohamad Fatma Susilawati , Wijaya Harma Oktafia Lingga , Santoso Budi
Published: January 2025

The palm oil industry faces significant challenges in accurately classifying fruit ripeness, which is crucial for optimizing yield, quality, and profitability. Manual methods are slow and prone to errors, leading to inefficiencies and increased costs. Deep Learning, particularly the AlexNet architecture, has succeeded in image classification tasks and offers a promising solution. This study explores the implementation of AlexNet to improve the efficiency and accuracy of palm oil fruit maturity classification, thereby reducing costs and production time. We employed a dataset of 1500 images of palm oil fruits, meticulously categorized into three classes: raw, ripe, and rotten. The experimental setup involved training AlexNet and comparing its performance with a conventional Convolutional Neural Network (CNN). The results demonstrated that AlexNet significantly outperforms the traditional CNN, achieving a validation loss of 0.0261 and an accuracy of 0.9962, compared to the CNN's validation loss of 0.0377 and accuracy of 0.9925. Furthermore, AlexNet achieved superior precision, recall, and F-1 scores, each reaching 0.99, while the CNN scores were 0.98. These findings suggest that adopting AlexNet can enhance the palm oil industry's operational efficiency and product quality. The improved classification accuracy ensures that fruits are harvested at optimal ripeness, leading to better oil yield and quality. Reducing classification errors and manual labor can also lead to substantial cost savings and increased profitability. This study underscores the potential of advanced deep learning models like AlexNet in revolutionizing agricultural practices and improving industrial outcomes.
Human vs machine learning in face recognition: a case study from the travel industry
Authors: Lionnie Regina , Hermanto Vidya
Published: January 2025

This research was conducted to help answer whether a machine learning simulation can replace the human ability to recognize human faces, especially under challenges under travel industry requirements. The human ability to recognize faces was evaluated using a series of questions in a survey. The questions challenged the human respondents to recognize faces under similar looks, with hair and makeup disguises, only part of the facial area, and under dark lighting conditions. At the same time, a histogram of oriented gradient (HoG) combined with a support vector machine (SVM) was built for machine learning simulations. The machine learning was evaluated using two datasets, i.e., the Extended Yale B (EYB) Face dataset for challenge under dark lighting conditions and The Extended Makeup Face Dataset (EMFD) for challenge using face with makeup disguise. The results showed that machine learning simulation of the face recognition system yielded accuracy as high as 95.4% under dark lighting conditions and 70.8% under facial makeup disguise. On the contrary, only 48% of respondents accurately recognized human faces in dark lighting. The number was increased to 94-96% when the face images were adjusted first with the contrast adjustment method.  However, only 36-37% of respondents accurately recognized human faces under face makeup disguise.
Experimental investigation on slope runoff, sediment, and hydraulic parameters under different underlying surface
Authors: Hamizak Siti Norhafizah , Suif Zuliziana , Jelani Jestin , Ahmad Nordila , Akhtar Muhammad Izzul
Published: January 2025

This study utilizes a rainfall simulator to conduct an experimental investigation of slope and rainfall on various underlying surfaces. This study aimed to determine the relationship between various hydraulic factors and sediment concentration by estimating runoff, sediment concentration generation, and hydraulic parameters on various underlying surfaces. The flow velocity, flow depth, shear stress, and unit stream power are the hydraulic parameters in this experiment. The soil sample will be set up appropriately in the rainfall simulator with a slope of 20º and subjected to a rainfall event for two hours on four trays with various underlying surface types. The rainfall intensity of 10 Lmin⁻¹ was designated for the rainfall simulator. Throughout a two-hour period, the runoff flow was collected at intervals of 30, 60, 90, and 120 minutes. The measured sediment concentration using Total Suspended Solid (TSS). Then measurements were conducted of the sediment concentration, runoff discharge, and hydraulic parameters. According to the results, the stream power of the four covers is higher for the dried leaves (0.004606 ms-3), grass cover (0.003274 ms-3), gravel (0.00232 ms-³), and bare soil cover (0.00081 ms-³). But bare soil produces the maximum concentration of sediment and surface runoff, which is then followed by grass, gravel, and leaves. In general, the generation of sediment began with the bare surface, gravel, dry leaves, and grass in descending sequence. Research has shown that rain-induced plant cover can be used as a low-cost strategy to reduce soil erosion on construction slope sites.
Influence of hyperbaric air exposure on the function of brachial artery
Authors:   Department of Diving and Hyperbaric Medicine, Naval Medical Center, Naval Medical University, Shanghai, P.R. China, Ting-Ting Zhang , Zhen-Biao Guan ,   Department of Respiratory and Critical Care, Changhai Hospital, Shanghai, P.R. China, Jia-Jun Xu ,   Department of Diving and Hyperbaric Medicine, Naval Medical Center, Naval Medical University, Shanghai, P.R. China, Shi-Feng Wang ,   Department of Diving and Hyperbaric Medicine, Naval Medical Center, Naval Medical University, Shanghai, P.R. China, Wen-Wu Liu ,   Department of Diving and Hyperbaric Medicine, Naval Medical Center, Naval Medical University, Shanghai, P.R. China
Published: January 2025

Decompression after diving may inevitably cause the production of bubbles in the body, even without protocol violation. Bubbles produced in the circulation may damage the vascular cells, leading to vascular dysfunction. In this study, five subjects were recruited and subjected to hyperbaric exposure (15 meters; 100 minutes). The function of the brachial artery was assessed by measuring diameter, systolic peak velocity (SPV), resistance index (RI), and flow-mediated dilation (FMD) of the brachial artery before and after hyperbaric exposure. Our results showed that hyperbaric air exposure slightly increased the diameter of the brachial artery and significantly increased its RI but reduced the FMD and markedly decreased the SPV. This study indicates that hyperbaric air exposure at low pressure may also alter the function of the brachial artery.
Keywords: brachial artery, diving, flow-mediated dilation, ultrasound, vascular endothelium
Non-technological determinants of inter-industry knowledge sharing among port workers: Strategic insights from Malaysia
Authors: Yusoff Mohd Zarir , Saadon Mohd Saiful Izwaan , Shafi Muhammad Ammar , Zulkipli Hafizah , Mohamad Arifha , Ramasamy Chandrashekar , Aziz Nurhanim Abdul , Toh Yoke Teng
Published: January 2025

Efficient port operations rely on knowledge exchange among industry workers. Previous studies have identified several factors influencing this exchange. For instance, Caporuscio et al. (2020) noted that port operators often have limited industry-specific knowledge, which can hinder effective knowledge sharing. Additionally, there is a recognized gap in understanding the non-technological elements that shape the exchange of inter-industry information among port operators. Al-Busaidi and Olfman (2017) highlighted the crucial roles played by individuals, peers, and organizations in facilitating information-sharing processes. This study examines how individual, peer, and organizational non-technological factors impact port workers’ willingness to share their expertise across industries. Using a sample of seven critical operators from Malaysia’s federal port, the research employs a revised tool to measure these factors and promote information flow. Survey data from knowledge workers in Malaysia’s port operator sector further supports the findings, indicating that individual characteristics notably influence knowledge sharing among port personnel. This study contributes valuable insights to the broader understanding of how these factors influence information exchange among port workers across different industries.
Technological transformation in the delivery of public services: A study of public governance in the emerging market
Authors: Naveen Naveen , Sharma Rajendra
Published: January 2025

The State of Haryana offers more than 650 services/schemes through its unique one-stop SARAL portal. While exploring the SARAL performance, determined using a mathematical equation SARAL portal, it has been observed that the districts’ performance is asymmetrical in the technological impact of governance in the state. To study this research problem, the objective was to trace the factors responsible for this asymmetrical technological transformation in the state. To meet the research objective, the authors selected the Karnal, Jind, and Nuh districts, considering the top, middle, and bottom performers in SARAL score indicators by using a purposive sampling technique. This quantitative research has been analytical and empirical based on the secondary data. The study has found that not only technical but there are other significant factors viz., social, political, administrative, awareness, and economic factors influence the technological transformation in public service delivery. The findings may help the government policymakers in reengineering the technological development policy in the state so as to move towards fulfilling the spirit of Article 38 of the Indian Constitution and Sustainable Development Goal (SDG) 16 prescribed by the United Nations (UN). Further research can supplement this study by collecting primary data from the service providers and the service recipients.
Factors Influencing the Use of Community Integrated Care Services : Focused on the Andersen's Behavior Model
Authors:   Korean Academy of Integrated Care Management, Lee Yong-hee , Moon Yong-pil
Published: January 2025

The purpose of this study is to empirically analyze the factors that influence the use of community integrated care services by local residents who participated in pilot projects organized by the Ministry of Health and Welfare. To achieve this objective, the Andersen's behavior model was employed to analyze the users of community integrated services in Seo-gu, Gwangju, in 2022. The study examined factors influencing the use of these services, including health and welfare dimensions, as well as the number of service uses, duration of use, and service prices. The results of the analysis are as follows: First, in the examination of users who utilized health and welfare services within the integrated care framework, the factors affecting each dependent variable (number of uses, duration of use, and price of use) varied. Second, for users who simultaneously accessed both health and welfare services, the factors influencing the number of uses, duration of use, and price of use were distinct for each service. Third, in both prior analyses, significant variables within the predisposing factors, enabling factors, and needs factors differed. Notably, activities of daily living (ADL) and long-term care grade variables were significant in determining the price of health services, welfare services, and health-welfare services. Based on these findings, policy implications are presented for future initiatives related to integrated community care projects and the integration of medical and community care support.
A Study on Experiences of Family Members of Suspects with Intellectual Disabilities Participating in Criminal Proceedings
Authors:   Korean Academy of Integrated Care Management, Im Jung-Hu , Kim Ji-Hye
Published: January 2025

The objective of this study is to provide empirical evidence to support the development of practical interventions by examining the experiences of family members of suspects with intellectual disabilities within the criminal justice system. In-depth interviews were conducted with five family members who have participated in the criminal justice process involving an adult suspect with intellectual disabilities. The inductive analysis, of the qualitative data resulted in the identification of 18 meaning units, 7 subcategories, and 3 primary categories through thematic analysis. The three core categories identified were: The first category is 'Involvement in criminal incidents due to the characteristics of the person with intellectual disabilities,' The second category is 'Experiencing exclusion during the judicial process,' The third category is 'Shouldering the burden of dual responsibilities in resolving the incident and caregiving as a family member of a suspect with intellectual disabilities.' In light of these findings, we have proposed improvements to effectively safeguard the procedural rights of suspects with intellectual disabilities and alleviate the caregiving burden on family members.
Relatos de experiências de extensionistas
Authors: Silva Ana Clara Fontes da , Silva Nilvania dos Santos
Published: January 2025

Em síntese, este ensaio apresenta uma pesquisa sobre as contribuições das ações de extensão realizadas por uma equipe da Universidade Federal da Paraíba. O estudo enfoca, particularmente, a relevância dessas ações no processo de formação de docentes e discentes de um curso de Graduação em Pedagogia, com base em registros obtidos durante intervenções voltadas para profissionais da educação e/ou estudantes de turmas multisseriadas. Ressalta-se que este artigo também se apoia em dados coletados no desenvolvimento de um Trabalho de Conclusão de Curso. A fundamentação teórica foi construída a partir de autores como Caldart, Melo e Freire, entre outros. A pesquisa, de natureza qualitativa e exploratória, utilizou análise documental e se baseou em experiências vivenciadas em ações extensionistas. Concluiu-se que a extensão constitui uma oportunidade enriquecedora para o compartilhamento de informações essenciais, contribuindo para a construção de conhecimentos fundamentais no processo de formação.
Rnd3 Ameliorates Diabetic Cardiac Microvascular Injury via Facilitating Trim40-mediated Rock1 Ubiquitination
Authors: Lin Jie , Zhang Xuebin , Ge Wen , Duan Yu , Zhang Xiao , Zhang Yan , Dai Xinchun , Jiang Mengyuan , Zhang Xiaohua , Zhang Jiye , Qiang Huanhuan , Sun Dongdong
Published: January 2025

Diabetic microvascular dysfunction is evidenced by disrupted endothelial cell junctions and increased microvascular permeability. However, effective strategies against these injuries remain scarce. In this study, the type 2 diabetes mouse model was established by high-fat diet combined with streptozotocin injection in Rnd3 endothelial- specific transgenic and knockout mice. Echocardiography was employed to evaluate cardiac function. Microvascular corrosion casts, lanthanum nitrate perfusion, trans-endothelial electrical resistance, FITC-dextran permeability assay and laser speckle contrast imaging were performed to evaluate the integrity of endothelial cell junctions and microvascular function. RNA sequencing, mass spectrometry, co-immunoprecipitation, immunofluorescence and molecular docking were used to explore the downstream regulators of Rnd3. Evidence from gain/loss-of-function studies denoted a protective role for Rnd3 against microvascular dysfunction in diabetic heart. Endothelial-specific deletion of Rnd3 significantly exacerbated coronary microvascular barrier dysfunction under diabetic conditions, while Rnd3 overexpression effectively prevented these effects. Furthermore, Rnd3 overexpression also attenuated cardiac dysfunction in diabetic mice, as indicated by increased LVEF, LVFS, and E/A ratio. Rnd3 overexpression inhibited CMECs apoptosis and increased CMECs migration in response to HG-PA challenge. Rnd3 overexpression inhibited Rock1 activity and MLC phosphorylation in CMECs treated with HG-PA stimulus. Mechanically, Rnd3 recruited and interacted with the E3 ubiquitin ligase Trim40 which further facilitated the degradation of Rock1, thus inhibiting endothelial barrier hyperpermeability in HG-PA-stimulated CMECs. However, the cardioprotective effects of Rnd3 were largely abrogated by Trim40 deficiency in diabetic conditions. Collectively, Rnd3 alleviates microvascular hyperpermeability, maintains endothelial barrier integrity, and mitigates cardiac dysfunction by regulating the Rock1/MLC signaling pathway in the state of DCM.