bluuebunny/crossref_metadata_2025 huggingface dataset:
The influence of precoating layers on the performance of water-based barrier coatings
Authors: POKHAREL KRITEE , BOUSFIELD DOUGLAS , WANG JINWU
Published: February 2025

Cellulose nanofibrils (CNF) on paper have been demonstrated to be an effective barrier against oxygen and grease and have been shown to improve the barrier performance of dispersion-based barrier coatings. The potential to produce paper grades that have good oxygen, grease, and moisture barrier properties is clear, but a better understanding of the synergies between CNF, other coating layers, and water-based barrier coatings (WBBC) is needed to optimize these systems.
Different coat weights of a commercial WBBC were applied to papers that have a range of different qualities and thicknesses of CNF precoating layers. The same WBBC was also applied to pigmented coated paper, with various types of pigments and latex levels. Samples were characterized in terms of grease resistance, water vapor transmission rate (WVTR), and oxygen transmission rate (OTR) before and after folding. The results were contrasted to cases where the WBBC was applied to the paper with no precoating layer.
When the WBBC is applied on a CNF layer or the pigmented coating layer, the performance of the WBBC for the water vapor barrier improves a significant amount compared to when the WBBC is applied to the base paper with no precoating layer. This improvement likely comes from these precoating layers filling in the large paper pores, which leads to the WBBC forming a continuous layer at low coat weights. Folding decreases the moisture barrier performance to some degree, but the grease resistance is not influenced by folding when a CNF precoating layer is involved. Oxygen barrier properties are moderate for the CNF layer alone and are less than 5 cm3/m2/day when WBBC is coated on the CNF layer. This result likely comes from the barrier coating’s ability to repair defects in the CNF layer to stop the easy passage of oxygen in defect regions of the sample.
Water-based adhesive penetration into paperboard and coated paperboard
Authors: KHLEWEE MUBARAK , DESISTO WILLIAM , BOUSFIELD DOUGLAS
Published: February 2025

The setting of water-based adhesives in contact with paperboard is important in the production of boxes and other packaging, but the topic has received little attention in the literature. The penetration of the adhesive into the paper surface is important to get good bond strength through mechanical interlocking. The influence of the process conditions and the paper properties on this penetration is lacking.
A water-based adhesive was applied to an uncoated and coated paperboard. The coating layer had two latex lev-els. Samples were characterized in terms of air permeability, void fraction, average pore size, and coat weight. The adhesive was applied to the samples in a mechanical press, squeezing a drop between two samples. The penetration of the adhesive was characterized with a silicone oil absorption method that measured the decrease in pore volume after the adhesive had been applied to approximate the pore volume taken up by the adhesive. The bond strength was measured with a peeling test.
The penetration depth into uncoated paper did not depend on the application method parameters such as press-ing time, pressure, or initial solids of the adhesive. The penetration depth ranged from 35–40 mm. The penetration into 10 pph latex content coated paper was similar to the uncoated samples, but reduced penetration was observed into the 40 pph latex content coatings. The results were compared to the limiting amount of adhesive that was obtained from the weight gain of the samples and to a simple model that is based on flow in porous media. Peel tests revealed that good penetration was needed, as well as a strong coating layer to obtain high peel forces.
Enhancing Mental Health Interventions in the USA with Semi-Supervised Learning: An AI Approach to Emotion Prediction
Authors: Zeeshan MD Abdul Fahim , Mohaimin MD Rashed , Hazari Noor Ahmad , Nayeem Md Boktiar
Published: February 2025

The escalating prevalence of mental health challenges in the USA underscores the urgent need for innovative resolutions to enhance interventions and care. Accurate prediction of emotional states can empower mental health practitioners to provide timely and personalized support. The main objective of this study was to develop and evaluate semi-supervised learning models for emotion prediction in mental health. The present study's prime focus is applying semi-supervised learning in the U.S. context to mental health datasets. The Emotion Prediction Dataset is one of the diverse datasets collected from different sources with the aim of gaining a wide understanding of emotional state conditions. It includes text data from social media platforms, such as Twitter and Facebook, where users express their feelings right at the moment; audio recordings from speech and interactions that capture vocal nuances and intonation; and physiological signals captured through wearable devices measuring heart rate, skin conductance, and facial electromyography. Logistic Regression, Random Forest, and Gradient Boosting are some of the models considered in this study. Model evaluation executed proven metrics such as accuracy, precision, recall, and F1-Score assesses performance comprehensively. Although all three models generally performed worse, the SVM model provided the most reliable predictions in the context of this dataset and may, therefore, be effective for emotion classification. Integrating emotion prediction models into existing mental health services offers a new paradigm in patient care. A strong framework for such integration should start with an assessment of the current platforms, highlighting key points where emotion prediction can complement the existing services. Emotion prediction models can significantly enhance support strategies by targeting interventions at predicted emotional changes. Mental health professionals will be able to create personal treatment plans in which the trends within the data denote specific emotional states the patient is most likely to experience. The consolidation of AI-powered emotion prediction algorithms into mental health services in the USA carries substantial ramifications for improving the quality of care and accessibility of mental health resources.
Ranking Analysis of Tourist Destinations in Jakarta Using Collaborative Filtering Method
Authors: Anggi Anggi , Sudaryono Sudaryono , Azizah Nur
Published: February 2025

The high workload coupled with advances in technology means that employees sit all day in front of computers. This can result in stress and mental fatigue. Traveling can relieve soreness from sitting too much and make the heart happy. Indonesia is a country rich in tourist attractions. Jakarta as the capital of Indonesia itself has at least 1,016 recreation and entertainment locations. A recommendation system can be a solution to make it easier to choose tourist destinations that suit user interests and preferences. This research was created to provide users with a list of tourist destination choices based on collaborative filtering and provide method accuracy values with RMSE. The results of this research are that the system is proven to be able to provide tourist destination references for users and shows an RMSE value of 0.34. This value still shows that there is an error in the method's predictions. There is still a lot of development that can be done so that this system has more features and wider uses.
Transforming Education Through the Use of Blockchain Technology: Innovation in Educational Data Management
Authors: Sutisna Felix , Widayanti Riya , Putri Oganda Fitra , Millah Shofiyul , Maulana Sabda
Published: February 2025

This research focuses on exploring the application of blockchain technology in the management of educational data, aiming to identify the potential benefits and challenges of this technology in enhancing data security, transparency, and efficiency within educational institutions. The study also seeks to develop a conceptual framework that addresses the unique requirements and implications of blockchain integration in the academic sector. In an era where big data has become pervasive in business strategy, this research aims to understand the challenges and advantages of big data in the digital content sector related to environmental issues. The idea of “society 5.0” promotes harmony between technology and sustainable quality of life. Industry as an innovator plays an important role in offering solutions to social problems, and the digital content sector is considered to have great potential in achieving this goal. This research explores the concept of the digital content sector from a Society 5.0 perspective and discusses issues related to economics and sustainability. The importance of collaboration in creating a sustainable digital content sector is emphasized in the form of the concept of co-creation. Collaboration involves stakeholders from various levels of society, including industry, government, academia, and society, to accelerate innovation and share knowledge. In addition, the role of artists' skills in the creative sector is recognized as an important aspect that cannot be completely replaced by technology. This research also discusses the impact of the nation's innovation policies in supporting the growth and sustainability of the digital content sector. Policies that promote technological innovation, protect intellectual property rights, and provide incentives for companies that contribute to social and environmental sustainability, were identified as important factors in the development of the sector. Thus, this research explores the role of the digital economy, big data, and the concept of "society 5.0" in the sustainable digital content sector. It aims to identify challenges, opportunities and formulate policy recommendations that will advance this sector as a major contributor to economic and social sustainability in the future.
The Implementation of Artificial Intelligence in Electronic Commerce
Authors: Handra Tessa , Lestari Santoso Nuke Puji , Wilson Oliver , Ramadhan Tarisya
Published: February 2025

This research aims to explore the implementation of Artificial Intelligence (AI) within the context of electronic commerce. As digital technology evolves, AI has become a crucial tool in transforming the way businesses operate online. This study employs both qualitative and quantitative approaches to analyze how AI can enhance the online shopping experience, including personalization, customer service automation, and data analysis for market trend prediction. Through case studies on several leading e-commerce platforms, this research identifies key AI applications such as recommendation systems, chatbots, and price optimization algorithms. The findings indicate that the implementation of AI not only improves operational efficiency but also provides a more personalized and responsive experience for consumers. The study also addresses the challenges and ethical implications of using AI in e-commerce, including issues of data privacy and algorithmic bias. By providing comprehensive insights into the current applications of AI and its potential for the future, this research aims to guide developers, entrepreneurs, and researchers in integrating effective and ethical AI solutions into e-commerce business strategies.
File Upload Security: Essential Practices for Programmers
Authors: Suryaningrat Anrie , Ramayanti Desi , Taberima Glen Maxi , Kurniawan Panji Pratama
Published: February 2025

File upload processes, while convenient, introduce data security risks that must be addressed. Potential malware infections, sensitive information leaks, and data corruption necessitate the implementation of effective strategies and solutions. Data integrity refers to the accuracy, consistency, and reliability of stored and processed data. Human error, system failures, and cyberattacks can compromise data integrity, necessitating effective preventive and mitigation measures. Data security and file upload integrity are critical aspects of modern web applications. Given the escalating cyber threat landscape, implementing best practices to safeguard user data and ensure the authenticity of uploaded files is paramount. This paper delves into the implementation of best practices for protecting user data and ensuring file upload authenticity. The study proposes the implementation of best practices for secure file upload mechanisms in web applications, including the innovative application of hash-salting techniques. By adhering to the guidelines presented, developers can bolster the defenses of their web applications against a wide range of cyber threats, enhance user trust, and protect sensitive data. This approach also serves as an effective solution for improving efficiency, security, and compliance in digital records management.
Pengembangan Aplikasi Reservasi Berbasis Website Dengan ASP.NET Pada PT. Kalbe Farma Tbk (International Division)
Authors: Supriati Ruli , Suhaepi Muhammad Iip , Nurhilman Dimas , Aisyah Euis Sitinur , Rahardja Susanto
Published: February 2025

Teknologi merupakan salah satu faktor penting yang dapat meningkatkan kinerja perusahaan. PT Kalbe Farma Tbk (International Division) adalah salah satu perusahaan yang telah memanfaatkan teknologi untuk kegiatan reservasi di perusahaan. Namun, aplikasi reservasi yang digunakan saat ini masih memiliki beberapa keterbatasan dan kekurangan, seperti fitur yang terbatas, akses yang terbatas, dan proses yang manual. Oleh karena itu, penulis ingin mengembangkan sebuah aplikasi reservasi berbasis website dengan ASP.NET yang dapat memberikan fitur-fitur baru dan memudahkan pengguna dalam melakukan reservasi ruangan, mobil, dan pengajuan surat. Tujuan dari penelitian ini adalah untuk membuat sebuah sistem reservasi yang lebih efektif, efisien, dan produktif bagi PT Kalbe Farma Tbk (International Division).
Implementasi K-Medoids Untuk Clustering Penduduk Dengan Pendidikan SMA Menurut Jenis Kelamin
Authors: Faisal Muhammad , Utami Wiranti Sri , Pratiwi Nila
Published: February 2025

Pendidikan merupakan proses kegiatan belajar mengajar yang dilakukan di sekolah. Salah satu program pemerintah dalam mendukung Pendidikan adalah Wajib belajar 12 tahun, yang dimaksud adalah generasi bangsa memiliki pendidikan minimal tamatan Sekolah Menengah Atas (SMA) Sederajat. Proses pengelompokkan tamatan SMA sangat berguna untuk melihat siswa atau siswi yang lulus SMA disetiap Provinsi. Implementasi Data Mining menggunakan metode K-Medoids ini diharapkan dapat membantu pihak kepala daerah setempat dalam memantau kelompok usia dan jenis kelamin yang lulus SMA disetiap Provinsi masing-masing. Data yang didapat merupakan dataset yang berasal dari Badan Pusat Statistik (BPS) kemudian data tersebut dianalisa menggunakan metode K-Medoids. Hasil dari analisa menggunakan metode K-Medoids menampilkan 2 cluster pada tahun 2021 Rata-rata penduduk laki-laki usia 25 tahun lulus SMA 58,2 sampai dengan 32,8. Pada tahun 2022 58,5 sampai 33,9. Sedangkan pada tahun 2021 rata-rata penduduk perempuan usia 25 tahun lulus SMA 52,5 sampai 26,9. Pada tahun 2022 54,0 sampai 29,3
Prediksi Harga Penjualan Dan Restorasi Motor Klasik Tahun 1990-2003 Menggunakan Algoritma K- Nearst Neighbors (KNN)
Authors: Lesmana Fadlan Ilyas , Irawan Bambang , Bahtiar Agus
Published: February 2025

Pada era modern, minat terhadap motor klasik kembali meningkat. Hal ini dibuktikan dengan meningkatnya penjualan motor klasik dan permintaan layanan restorasi. Sebuah penelitian yang berjudul Analisis Data Penjualan dan Tren Restorasi Motor Klasik menggunakan metode/algoritma k-nearst neigh bors (KNN). Data yang digunakan dalam penelitian ini bersumber dari bengkel restorasi grage. Dalam melakukan analisis mendalam terhadap data penjualan dan tren restorasi motor klasik untuk membantu dalam tren restorasi dan motor yang diminati pasar. Penelitian ini menggunakan metode analisis data KNN untuk memahami perubahan dan preferensi pasar terkait motor klasik.Temuan penelitian menunjukkan bahwa konsumen motor klasik di Indonesia lebih menyukai merek dan model klasik yang ikonik, seperti Vespa, Honda Astrea, dan Yamaha RX-King. Harga jual motor klasik juga dipengaruhi oleh faktor-faktor seperti kondisi, merek, model, dan tahun produksi. Selain itu, permintaan layanan restorasi motor klasik juga meningkat, terutama untuk restorasi dengan kualitas dan karakteristik tertentu.Temuan penelitian ini memberikan wawasan yang berharga bagi industri otomotif dalam memahami dinamika pasar motor klasik dan peluang bisnis di era modern. Hasil dari penelitian ini dapat memberikan gambaran terhadap harga yang sesuai dengan restorasi dan harga beli agar bengkel restorasi grage dapat bersaing terhadap harga jual dan dapat memberikan harga yang sesuai bagi konsumen.
Credit Risk Prediction Model Using Support Vector Machine with Parameter Optimization in Banks
Authors: Martono Aris , Padeli Padeli , Suhaepi Muhamad Iip , Santoso Sugeng , Sunandar Endang
Published: February 2025

Abstract
 This research aims to determine the Support Vector Machine (SVM) model with Parameter Optimization in predicting loan worthiness to avoid the risk of bad credit at the Bank. Every bank tries to market financial loan products with very strict requirements. One of the requirements is that the company's financial reports must be healthy if it borrows money from a bank to develop the company's business. In the credit analysis process, there are 19 financial factors that must be measured from dozens or even hundreds of companies proposing financial loans, making it difficult for credit analysts to make decisions about whether these companies are worthy of borrowing or not. Therefore, this research was carried out by comparing the two models, namely SVM with parameter optimization and SVM with parameter optimization and Particle Swarm Optimization (PSO) to select the best model. The research results show that the Area Under Curve (AUC) criteria with validation number of folds (nof) = 10 and nof = 5 are 98.80% and 98.80%, meaning good and stable in the SVM model with parameter optimization. Meanwhile, the SVM model with parameter optimization and PSO has better AUC for validation nof=5 (99%) but for AUC with validation nof=10 (98.30%) it is less good.
Automatic Machine Control System Using Arduino Microcontroller
Authors: Harfizar Harfizar , Wardoyo Rizky Adytya , Atmojo Tito Tri , Supriyono Ignatius Agus
Published: February 2025

Filling the tank with water uses a water machine to suck and put water into it. Water tanks are used to store clean water for household needs, especially from wells. This system requires manual supervision. The machine must be turned on if the tank is empty and turned off if it is full. If you forget to turn off the machine, the water will overflow and cause waste of water and electricity. Technological developments encourage the use of microcontrollers to overcome this problem. A microcontroller is a chip that processes digital data with a special language. Microcontrollers can be used as electronic controllers and to store programs. By using this technology, the problem of wasting water can be reduced. An automatic control system with an Arduino microcontroller can turn the water machine on and off automatically when the tank is empty and full. It is hoped that this system can help humans use water and electricity effectively and efficiently.
Application of the Prototype Method in the Export Section Goods Delivery Document Monitoring System
Authors: Sari Meri Mayang , Iskandar Dedy , Supriadi Ajay , Sudarto Ferry , Saptono Arief
Published: February 2025

Companies can now handle and organize data systematically thanks to advances in information technology. Monitoring is a daily assessment (evaluation) of activities and progress. On the other hand, evaluation is an assessment carried out periodically regarding all achievements. Well-managed data will help companies make decisions. PT Gajah Tunggal Tbk is engaged in the manufacturing industry which meets customer needs by making product samples. One of the problems is that document control is carried out manually, which makes obtaining product trial data difficult. Additionally, there is no storage space for product sampling documents, which results in loss or damage to copies of documents. Product sampling is used according to customer needs, allowing companies to develop new products that meet customer or customer needs. Thus, the products produced will try to meet customer satisfaction. The aim of this research is to improve the services provided by PT Gajah Tunggal Tbk by building a goods delivery document monitoring system using the prototype method. To achieve this goal, previously built systems must be evaluated. The results obtained from monitoring goods delivery documents can increase the efficiency and efficiency of the service process with shorter waiting times and simpler delivery procedures. Using the prototype method can help PT Gajah Tunggal Tbk improve the efficiency and performance of its services.
Automatic Fire Detection Alarm Monitoring System in Balaraja District Based on Internet of Things
Authors: Ilamsyah Ilamsyah , Tandilintin Abert , Putra Lingga Buana , Jawahir Jawahir , Arribathi Abdul Hamid
Published: February 2025

The Balaraja Sub-District Office, as a Regional Apparatus Work Unit in Tangerang Regency, faces challenges in preventing fire disasters. Fires can cause significant loss of life, economic, and material losses. Currently, the sub-district lacks an effective prevention system, relying solely on post-fire handling measures. This research aims to design and implement a monitoring system and automatic fire detection alarm based on the Internet of Things (IoT) in the Balaraja Sub-District. This system is expected to detect fires early and provide rapid alarms to reduce losses. The research confines its scope to the Balaraja Sub-District, utilizing interviews and literature studies as data collection methods. The design method involves creating flowcharts and block diagrams, while the analysis method employs the PIECES framework. System testing is conducted using blackbox testing methods. The findings of this research are expected to contribute to the development of IoT technology for disaster mitigation in Indonesia, as well as enhancing the safety of employees and the surrounding community.
Aprendizaje inmersivo en las ciencias naturales
Authors: López Franco Daniela , Montoya Pérez Isabella Carolina , Jaramillo Garzón Luisa , Bolívar Ávila María Paula , Betancourt Rodríguez Miguel Ángel
Published: February 2025

Este artículo surge a raíz de una falencia detectada en cuanto a la actualización del uso de herramientas tecnológicas digitales por parte de los docentes de ciencias naturales y los motivos que los llevan a optar por mantener el sistema educativo tradicional, que bien puede estar obstaculizando el rendimiento académico y resultados en pruebas de conocimiento nacionales e internacionales de los estudiantes. Debido a esto, se plantea la elaboración de una consulta referencial en bases de datos académicas (ProQuest, Gale, Aula abierta, Redalyc y Educ@net) en función del uso de realidad virtual en la educación; así como la creación y aplicación de una encuesta especializada hacia un total de 26 docentes de ciencias naturales, entre cuatro instituciones -tanto públicas como privadas- en la ciudad de Bogotá; esto, con el fin de conocer las opiniones de los profesores frente al uso de la realidad virtual como herramienta de ayuda para la enseñanza. Los resultados arrojados afirman que, si bien gran parte del cuerpo docente conoce la RV y estarían dispuestos a implementarla y/o a capacitarse en ella, existen ciertos limitantes externos que no les permiten su uso como la falta de recursos y el apoyo por parte de sus instituciones.
El videojuego como estrategia educativa para la enseñanza de terminología en Optometría
Authors: Angulo Sánchez Sara Viviana
Published: February 2025

La aplicación de herramientas multimedia tales como los videojuegos o juegos serios impacta en todos los campos del conocimiento especialmente en el entorno educativo, de allí que surja la necesidad de promover la interacción multilateral entre estudiante / docente y multimedia con el fin de fomentar la construcción educativa efectiva que articule la motivación y rescate el potencial de los recursos didácticos que incentiven el autoaprendizaje, limitando la aplicación de métodos tradicionales dentro del aula. Por lo tanto, los videojuegos permiten a partir de propósitos definidos emplear la entretención para la formación educativa, familiarizar la adquisición y retención de conceptos, fortalecer contenidos, fomentar la integración de las tecnologías en el aula, estimular la participación activa gracias a la construcción social de conocimiento significativo y transformar el proceso de evaluación en el entorno de la educación superior.
Rare urban-acquired human leptospirosis and environmental health investigation in Sydney, Australia
Authors: Ferson Mark J , Flanigan Sinead , Westman Mark E , Pastrana Velez Ana M , Cains Toni , Martinello Marianne
Published: February 2025

Leptospirosis is a zoonosis caused by exposure to Leptospira excreted into the environment by rodents or other mammals. A notification of a case of leptospirosis in an adult male with no history of travel or exposure to livestock or rodents triggered an environmental health investigation of his workplace, a local golf course. We hypothesised that a water splash in the eye from a creek running through the golf course, which occurred after a period of heavy rainfall, had led to Leptospira exposure, likely on the basis of contamination of the creek water by rodent urine. Testing of environmental water samples detected pathogenic Leptospira DNA in ten of eleven samples, although cultures were negative. However, we had difficulty interpreting this finding as we found Leptospira DNA in ten of 14 environmental samples in inner and eastern Sydney remote from the workplace, and these were not associated with notified human cases. When we reviewed the 53 human leptospirosis cases notified over the twenty-year period 2003–2022 in residents of metropolitan Sydney, of the 49 cases with Leptospira exposure information, 46 had recognised sources of exposure: travel overseas (27) or to tropical northern Australia (5); rural exposure often to livestock and/or rodents (12); work in an abattoir (1); and involvement in a raspberry farm outbreak (1). Only three, including the case described, acquired infection in suburban Sydney. Acquisition of human leptospirosis is a rare event in suburban Sydney; true cases without a travel or occupational exposure history may be under-recognised by clinicians. However, with increasing biodiversity loss and where climate change results in heavier rainfall and more frequent floods, it is likely that human leptospirosis will become more common in urban as well as endemic settings.
Pendampingan Pengenalan IoT dalam Pertanian Pintar : Strategi Meningkatkan Produktivitas Tani di Desa Jurit Kabupaten Lombok Timur
Authors: Juliansyah Akbar , Mulada Diman Ade , Purmadi Ary
Published: February 2025

This community service activity aims to empower farmer groups in Jurit Village, East Lombok Regency, through the introduction of smart farming technology based on the Internet of Things (IoT). The initiative seeks to enhance agricultural productivity and economic empowerment by integrating advanced technology with robust business legalities. The participatory method employed in this program is based on the four-dimensional approach: Purpose, Process, Partnership, and Product. The outcomes of this community service demonstrate an improvement in the understanding and capabilities of the Lombok Organik farmer group in implementing IoT-based smart farming technology. Furthermore, the farmer group successfully established a legally recognized business, enabling them to expand market access and improve the competitiveness of their agricultural products.
Pelatihan Penerapan Teknologi Alat Produksi dan Pengemasan bagi UMKM Labuana Kota Banjarbaru Kalimantan Selatan
Authors: Normaidah Normaidah , Mazdadi Muhammad Itqan , Ratnapuri Prima Happy , Buih Putri Helena Junjung
Published: February 2025

This community service aims to improve the skills of UMKM Labuana in applying production equipment technology and product packaging instruments. The methods used include initial surveys, followed by technology application training, and evaluation with observation methods on improving partner skills in the equipment used. The results of this service show that the increasing skills of UMKM Labuana in applying product production and packaging technology include installation, operation, and maintenance of equipment.
Enhancing ICT Teachers' Competence with Nearpod : Transforming Interactive Learning Media in the Digital Age
Authors: Effendi Hastria , Effendi Hansi , Hendriyani Yeka , Ranuharja Fadhli , Novid Igor , Saari Erni Marlina
Published: February 2025

This community service program aimed to enhance junior high school teachers' understanding and ability to utilize interactive learning media through the Nearpod platform conducted in collaboration with the Technology and Information Communication Subject Teacher Consultation (MGMP TIK) in the Fifty Cities Regency, involving 25 teachers from junior high schools and Islamic junior high schools as participants. The initiative employed the ABCDE method, encompassing five stages: (1) Assessment, (2) Building, (3) Collaboration, (4) Delivery, and (5) Evaluation. Data analysis included pre- and post-test comparisons, descriptive statistics, and questionnaire evaluations to assess knowledge improvement, performance, and interest in adopting Nearpod Evaluation results indicated a high level of interest and readiness among teachers to implement Nearpod in their instructional practices. The results showed a significant increase in post-test scores compared to pre-test scores, meeting the target of a minimum of 20% knowledge improvement. A total of 80% of participants were able to apply Nearpod effectively, and 75% demonstrated a high interest in integrating this technology into their teaching These findings suggest that Nearpod-based training is effective in improving teachers' competencies and digital skills, thereby holding the potential to strengthen educational quality in the digital era.
Peningkatan Produktivitas Kerja Melalui Penguatan Pemahaman Aqidah bagi Pekerja Roya Perkulakan di Mantingan Ngawi Jawa Timur
Authors: Ihsan Nur Hadi , Huda Annisa Nurul , Fauziah Afifah , Rahmawati Aisyah , Silmi Nadaa Afifah , Taufiqurrahman Taufiqurrahman
Published: February 2025

This community service activity aims to enhance workers' productivity by strengthening their understanding of aqidah, thereby fodtering intrinsic motivation that promotes dedication, honesty, and responsibility in the workplace. The implementation method involved interactive counseling conducted in six sessions, which included a pre-test, material presentation, and a post-test. The participants were 13 workers from “Roya Perkulakan” in Mantingan, Ngawi, East Java, with the material focusing on strengthening aqidah, worship practices, and the application of Islamic values in daily life. The data analysis technique used was quantitative analysis with a One Group Pretest-Posttest experimental design to measure changes in program outcomes. The result of this activity indicated an improvement in aqidah understanding from 49% before the program to 96% after its implementation. This improvement demonstrated that aqidah plays a significant role in improving work productivity. A strong understanding of aqidah shapes workers into individuals who are honest, disciplined, and responsible, thereby contributing to enhanced productivity and work quality.
Keterampilan Menangkap Makna Artikel Ilmiah Jurnal Online melalui Google Forms
Authors: Damayanti Welsi , Razak Abdul , Hamidah Siti
Published: February 2025

The skill of reading comprehension of scientific articles in online journals is very important for students. Through this written literacy skill, students gain an understanding according to the focus and scope of the journal in question. This research is to review the Indonesian Language liberal art lectures when they are in their first year of college. The research uses a quantitative method by describing the score of the skill of capturing the meaning of scientific articles in online journals through parametric inferential statistical procedures. The research took place in the middle of the even semester of the 2022/2023 academic year. The subjects of this study were 83 students from the Indonesian Education University; divided into 29 students from the Communication Science Study Program, 26 students from the Physics Study Program, and 28 students from the Computer Science Study Program. The sample consisted of 69 students, divided into 24 students from the Communication Science Study Program, 22 students from the Physics Study Program, and 23 students from the Computer Science Study Program. The research instrument was in the form of a multiple-choice test via Google Forms media. The findings of the study: 1) the skill of reading comprehension of scientific articles in online journals via Google Forms media is in the moderate category; 2) there are differences in the skill reading comprehension of scientific articles in online journals via Google Forms media per sample group. Therefore, an effective strategy to improve students' meaning-making skills is written literacy skills with online media.
Supplementation with selenium, iron, and vitamin E in calves under immunological challenge
Authors: Salles Márcia S. V. , Figueiroa Fábio J. F. , Bittar Carla M. M. , Gomes Viviani , Marques Raquel S. , da Silveira Julia A. G , Facury Filho Elias J. , de Freitas José Esler , Saran Netto Arlindo
Published: February 2025

Introduction

The management and nutrition of young calves are important for the production system due to their great impact on future milk production potential. This study was to evaluate the performance and health of calves in the suckling phase, with supplementation of selenium, iron, and vitamin E while undergoing immunological challenge with Anaplasma marginale.

Methods

An experiment was conducted on an experimental farm using 42 newborn Holstein male calves, aged up to 60 days, in a completely randomized design, and they were assigned to the following three treatments: C (control milk replacer, N = 14); SeVitE (milk replacer supplemented with 0.6 mg organic selenium/kg + 100 IU vitamin E, N = 14); SeVitEFe (milk replacer supplemented with 0.6 mg organic selenium/kg + 100 IU vitamin E + 200 mg Fe chelate/kg, N = 14).

Results

Selenium, iron, and vitamin E intakes were higher in supplemented animals. The mean blood count of Anaplasma marginale was lower in supplemented calves compared to controls and increased with time after inoculation. Increased serum selenium was observed in supplemented calves, without vitamin E and iron changes. Plasma lactate concentration was lower in supplemented animals and those with SeVitEFe had lower urea concentration at 60 days compared to control. Treatments did not influence hematological parameters, while some only changed with the age of animals. Plasma glutathione peroxidase concentrations were higher in supplemented animals, with the interaction between treatment and time, where higher concentrations were observed at 40 days of experiment for supplemented calves compared to control. Treatments did not influence the performance of animals. Animals with SeVitEFe showed a lower incidence of diarrhea in the first thirty days of the experiment.

Discussion

Supplementation of selenium, iron, and vitamin E showed effectiveness in improving the animals’ oxidative metabolism, altering biochemical and hematological parameters, and reducing the pathogens of Anaplasma marginale, and the incidence of diarrhea, but did not enhance the animals’ performance.
YEATS2 promotes malignant phenotypes of esophageal squamous cell carcinoma via H3K27ac activated-IL6ST
Authors: Zhai Yuanfang , Zhang Fanyu , Shi Xiaoyu , Zou Siwei , Hu Xiaoling , Shan Chengyuan , Zhang Ling , Zou Binbin , Yang Xin , Kong Pengzhou , Cheng Xiaolong
Published: February 2025

Introduction

Histone acetylation modifications can regulate gene transcription and play crucial roles in multiple tumorigeneses processes. YEATS domain proteins are one important type of acetylation readers. We have found significant mutations and copy number amplifications of YEATS domain containing 2 (YEATS2) gene in esophageal squamous cell carcinoma (ESCC) through whole genome sequencing (WGS). However, the function and molecular mechanism of YEATS2 in ESCC remain elusive.

Methods

Chi-squared test and Kaplan-Meier methods were used to analyze the clinical significance of YEATS2. MTT, Colony Formation Assay, Transwell, Scratch Wound Healing, subcutaneous tumorigenesis model and lung metastatic tumor model were performed to detect YEATS2 effect on the proliferation and migration ability of ESCC cells in vivo and in vitro Co-IP-based mass spectrum (MS) assays and Chromatin immunoprecipitation (ChIP) were performed to explore the molecular mechanism of YEATS2 function in ESCC.

Results

ESCC patients with copy number amplification of YEATS2 had shorter postoperative survival. Furthermore, YEATS2 expression was positively correlated with copy number amplification. We have also found that YEATS2 expression was significantly upregulated in ESCC tissues and was correlated closely with the differentiation degree of ESCC cells. The results of in vivo and in vitro experiments revealed that YEATS2 enhanced the abilities of ESCC cells to proliferate and migrate. Mechanistically, YEATS2 activated NF-κB signaling to promote ESCC progression. YEATS2 and H3K27 acetylation (H3K27ac) were both enriched in the promoter region of IL6ST, which is involved in the regulation of YEATS2 on NF-κB signaling. Additionally, YEATS2 could recruit TAF15 and KAT5 to enhance H3K27ac enrichment in the promoter region of IL6ST to regulate its expression.

Conclusion

In conclusion, YEATS2 might function as a potential driver gene and a potential therapeutic target in ESCC.
A model for predicting bacteremia species based on host immune response
Authors: Simons Peter , Bondu Virginie , Shevy Laura , Young Stephen , Wandinger-Ness Angela , Bologa Cristian G. , Buranda Tione
Published: February 2025

Introduction

Clinicians encounter significant challenges in quickly and accurately identifying the bacterial species responsible for patient bacteremia and in selecting appropriate antibiotics for timely treatment. This study introduces a novel approach that combines immune response data from routine blood counts with assessments of immune cell activation, specifically through quantitative measurements of Rho family GTPase activity. The combined data were used to develop a machine-learning model capable of distinguishing specific classes of bacteria and their associations.

Methods

We aimed to determine whether different classes of bacteria elicit distinct patterns of host immune responses, as indicated by quantitative differences in leukocyte populations from routine complete blood counts with differential. Concurrently, we conducted quantitative measurements of activated Rac1 (Rac1•GTP) levels using a novel ‘G-Trap assay’ we developed. With the G-Trap, we measured Rac1•GTP in peripheral blood monocytes (PBMC) and polymorphonuclear (PMN) cells from blood samples collected from 28 culture-positive patients and over 80 non-infected patients used as controls.

Results

Our findings indicated that 18 of the 28 patients with bacteremia showed an increase of ≥ 3-fold in Rac1•GTP levels compared to the controls. The remaining ten patients with bacteremia exhibited either neutrophilia or pancytopenia and displayed normal to below-normal Rac1 GTPase activity, which is consistent with bacteria-induced immunosuppression. To analyze the data, we employed partial least squares discriminant analysis (PLS-DA), a supervised method that optimizes group separation and aids in building a novel machine-learning model for pathogen identification.

Discussion

The results demonstrated that PLS-DA effectively differentiates between specific pathogen groups, and external validation confirmed the predictive model's utility. Given that bacterial culture confirmation may take several days, our study underscores the potential of combining routine assays with a machine-learning model as a valuable clinical decision-support tool. This approach could enable prompt and accurate treatment on the same day that patients present to the clinic.
Application of microphysiological systems to unravel the mechanisms of schistosomiasis egg extravasation
Authors: Alfred Martin Omondi , Ochola Lucy , Okeyo Kennedy , Bae Euiwon , Ogongo Paul , Odongo David , Njaanake Kariuki , Robinson J. Paul
Published: February 2025

Despite decades of control efforts, the prevalence of schistosomiasis remains high in many endemic regions, posing significant challenges to global health. One of the key factors contributing to the persistence of the disease is the complex life cycle of the Schistosoma parasite, the causative agent, which involves multiple stages of development and intricate interactions with its mammalian hosts and snails. Among the various stages of the parasite lifecycle, the deposition of eggs and their migration through host tissues is significant, as they initiate the onset of the disease pathology by inducing inflammatory reactions and tissue damage. However, our understanding of the mechanisms underlying Schistosoma egg extravasation remains limited, hindering efforts to develop effective interventions. Microphysiological systems, particularly organ-on-a-chip systems, offer a promising approach to study this phenomenon in a controlled experimental setting because they allow the replication of physiological microenvironments in vitro. This review provides an overview of schistosomiasis, introduces the concept of organ-on-a-chip technology, and discusses its potential applications in the field of schistosomiasis research.
Embodied cognition perspectives within early executive function development
Authors: Pearce Z. Reagan , Miller Stephanie E.
Published: February 2025

The development of executive function (EF) has become a central focus in early cognitive development research. While movement is frequently used to measure EF in young children and may significantly contribute to its development, many leading EF theories do not fully explore the role of movement. This review investigates the critical role of movement in the development of EF during early childhood through the framework of embodied cognition, particularly drawing on the central themes outlined by Lawrence Shapiro. By applying Shapiro's themes, this narrative review examines whether and how these embodied cognition concepts are integrated into leading theories of EF development. The analysis identifies key gaps where current theories could benefit from a deeper incorporation of embodied cognition. This work aims to support future research that emphasizes the importance of movement in fostering EF during early childhood.
Assessing accuracy of BiliPredics algorithm in predicting individual bilirubin progression in neonates—results from a prospective multi-center study
Authors: Steffens Britta , Koch Gilbert , Engel Corinna , Franz Axel R. , Pfister Marc , Wellmann Sven
Published: February 2025

Background

Neonatal jaundice affects more than half of neonates. As bilirubin values usually peak few days after hospital discharge, jaundice remains a leading cause of rehospitalization. The recently developed BiliPredics algorithm, integrated in the first CE-approved bilirubin prediction tool, predicts individual bilirubin progression for up to 60 h into the future. Goal of the prospective study was to assess accuracy of this algorithm in predicting individual bilirubin prior to hospital discharge in neonates.

Methods

A prospective multi-center study was conducted in 2021 at the University Children's Hospitals in Tübingen and Regensburg, Germany. Various scenarios differing in type and number of bilirubin measurements and in prediction horizon were tested. Primary objective was prediction accuracy of the BiliPredics algorithm based on total serum bilirubin (TSB) measurements or based on transcutaneous bilirubin (TcB) measurements alone. Secondary objective was prediction accuracy based on combinations of TSB and TcB measurements. For assessment of accuracy, two validation metrics, absolute prediction error (aPE) and relative prediction error (rPE), and two clinical acceptance conditions, margin of error of the 95%-confidence interval (95%-CI) and percentage of clinically relevant mis-predictions defined as aPE>85μmol/L, were investigated.

Results

Out of 455 enrolled neonates, 276 neonates met bilirubin inclusion criteria and were included in the analyses. Irrespective from tested prediction horizons, median rPE was small (8.5% to 9.5%) utilizing TSB measurements for up to 30 and 60 h and slightly higher (13.8%) utilizing TcB measurements for up to 48 h. The same applied for median aPE. Both clinical acceptance conditions were fulfilled across tested scenarios. Results for combined TSB-TcB scenarios up to a prediction horizon of 48 h without adjustment for type of measurement were comparable to TSB and TcB scenarios fulfilling both clinical acceptance conditions.

Conclusion

Results from this prospective study in neonates confirm that the BiliPredics algorithm accurately predicts bilirubin progression up to 60 h with TSB measurements and up to 48 h with TcB or combined TSB-TcB measurements. As such, prediction tools utilizing this algorithm are expected to facilitate and safely optimize jaundice risk assessment at hospital discharge with the potential to reduce jaundice-related rehospitalizations.
Optimal scheduling of distributed shared energy storage based on optimal SOC interval
Authors: Zhang Tong , Zhang Liudong , Chen Yan , Peng Zhiqiang
Published: February 2025

Proposed within the framework of the sharing economy, Shared Energy Storage (SES) aims to enhance the efficiency of Energy Storage Systems (ESS) and drive down costs. This study focuses on an innovative approach to emphasize the multifaceted utilization of individual ESS units and the centralized use of dispersed ESS resources. Renewable Energy Power Plants (REPPs) collaborate to create SES pools, leveraging their ESS assets. Beyond meeting the needs of REPPs, these resources are shared for ancillary services like Secondary Frequency Regulation (SFR) to yield additional benefits. The paper delves into the scheduling techniques for SES. While conventional day-ahead robust optimization algorithms specify ESS power output for each period, they struggle to adjust schedules due to time-dependent constraints like renewable energy output and ESS state limitations. To address this, a distributed SES scheduling method based on optimal operating intervals is proposed. This method introduces an optimal interval variable for Energy Storage State of Charge (SOC) into the traditional three-layer optimization problem, effectively decoupling time-related constraints. Furthermore, a novel Nested Column and Constraint Generation (Nested C&CG) algorithm is presented to solve the mathematical model. Lastly, a revenue sharing model grounded in cooperative game theory is introduced, along with an illustrative example showcasing the efficacy of the proposed approach in managing uncertainties.