bluuebunny/crossref_metadata_2025 huggingface dataset:
Emotional Competence of Healthcare Workers and Its Impact on Patient Loyalty in Vietnamese Hospitals
Authors: Mai Phuoc Thien , Sa Nah Pi , Luu Triet Dinh , Ly Nam Khoa , Nguyen Phi Duong
Published: December 2024

Objective

To evaluate the effect of healthcare employees’ emotional competence (EC) on patient loyalty in public and private hospitals in Ho Chi Minh City, with a focus on the mediating roles of respect, trust, and rapport.

Method

A survey of 244 patients measured respect, trust, rapport, EC, and patient loyalty using a 5-point Likert scale. Structural equation modeling (SEM) was applied to assess the relationships between EC and patient loyalty, comparing results between public and private hospitals.

Results

EC significantly enhanced patient loyalty, with respect and rapport serving as key mediators. Private hospitals showed higher EC levels among staff, leading to greater patient loyalty, while public hospitals, impacted by staff fatigue and high patient loads, demonstrated lower EC and reduced loyalty. EC accounted for 58% of service quality variance and 65% of loyalty variance.

Conclusions

Emotional competence is essential for improving patient loyalty in healthcare settings. Training programs targeting EC, especially in public hospitals, could enhance patient satisfaction and long-term loyalty.
Geospatial AI and data analytics for satellite-based disaster prediction and risk assessment
Authors: Adeoye Idowu Afolabi  , Nurudeen Yemi Hussain  , Blessing Austin-Gabriel  , Adebimpe Bolatito Ige  , Peter Adeyemo Adepoju
Published: December 2024

The integration of Geospatial Artificial Intelligence (GeoAI) and data analytics with satellite technology offers transformative potential in disaster prediction and risk assessment. This paper explores the role of GeoAI in analyzing diverse geospatial datasets, such as optical, radar, and thermal satellite imagery, to predict and monitor disasters, including floods, wildfires, earthquakes, and landslides. Key applications of GeoAI include early warning systems, real-time hazard detection, and long-term resilience planning, enabling proactive decision-making and resource optimization. The paper also examines the benefits of predictive capabilities in minimizing disaster impacts, enhancing disaster preparedness, and reducing vulnerabilities. Furthermore, it addresses the challenges of handling complex geospatial data, ethical considerations, and the need for inclusive and transparent GeoAI frameworks. Recommendations for improving GeoAI approaches, such as enhancing data integration, advancing algorithms, and fostering public engagement, are provided. The findings underscore GeoAI's critical role in building disaster-resilient societies and highlight the need for continued innovation, collaboration, and ethical practices in its deployment.
Advances in smart warehousing solutions for optimizing energy sector supply chains
Authors: Ekene Cynthia Onukwulu  , Mercy Odochi Agho  , Nsisong Louis Eyo-Udo
Published: December 2024

The energy sector faces increasing pressure to enhance the efficiency and sustainability of its supply chains. Smart warehousing solutions have emerged as a key innovation to address these challenges, offering advanced technologies and systems that optimize storage, inventory management, and distribution processes. This paper explores the latest developments in smart warehousing and their application in the energy sector, focusing on how these solutions contribute to optimizing energy supply chains. Smart warehousing leverages technologies such as the Internet of Things (IoT), automation, robotics, and data analytics to streamline operations. IoT devices provide real-time tracking and monitoring of inventory, ensuring accurate stock levels and reducing the risk of overstocking or stockouts. Automation systems, including robotic arms and automated guided vehicles (AGVs), enhance the speed and accuracy of goods handling, reducing labor costs and improving operational efficiency. Furthermore, advanced data analytics enables predictive maintenance, helping to identify potential equipment failures before they occur, thus minimizing downtime and maintaining continuous operations. In the energy sector, smart warehousing solutions are particularly valuable in managing the complex logistics of equipment, spare parts, and raw materials. By integrating these systems into energy supply chains, companies can improve resource allocation, reduce waste, and ensure timely delivery of critical components. Additionally, smart warehouses can support sustainability goals by optimizing energy use within the facility through energy-efficient lighting, climate control systems, and energy consumption monitoring. This paper highlights the benefits of smart warehousing, including cost savings, enhanced operational visibility, and reduced environmental impact. It also discusses the challenges of adopting these technologies, such as high upfront costs, integration complexity, and workforce training. However, with continued technological advancements and strategic investments, smart warehousing solutions present a significant opportunity for optimizing energy sector supply chains.
Adaptif Lineer Toplayıcı Ağırlıklarının Optimizasyonu: Benekli Sırtlan ve Kum Kedisi Sürü Algoritmalarının Karşılaştırması
Authors: Yeşil Taha Yasir , Öztunç Abdulmelik , Seyyarer Ebubekir
Published: December 2024

Meta sezgisel optimizasyon algoritmaları, optimize edilmesi gereken karmaşık problemlerin çözümünde kullanılan doğal fenomenlerden ve hayvan davranışlarından esinlenen sezgisel tekniklerdir. 2017 yılında benekli sırtlanların avlanma stratejilerine dayalı olarak geliştirilen Benekli Sırtlan Optimizasyon (Spotted Hyena Optimization, SHO) ile 2022 yılında kum kedilerinin sürü davranışlarından ilham alınarak oluşturulan Kum Kedisi Sürü Optimizasyon (Sand Cat Swarm Optimization, SCSO), sürü tabanlı meta sezgisel optimizasyon algoritmalarıdır. Bu çalışmada, SHO ve SCSO algoritmalarını kullanarak belirli bir yöntemle yapılan Uyarlanabilir Finite Impulse Response (FIR) Süzgeç ağırlıklarının optimizasyonu yapılmaktadır. Belirli bir gürültüye sahip olan istenilen sinyali elde etmek amacıyla Adaptif Lineer Toplayıcıların ağırlıklarını optimize etmek için hata fonksiyonları kullanılmaktadır. Bu hata fonksiyonları Mean Square Error (MSE) fonksiyonu, Mean Absolute Error (MAE) fonksiyonu ve Least Mean Squared Error (LMS) fonksiyonudur. Bu çalışmada, tüm fonksiyonları kullanarak Adaptif Lineer Toplayıcı işaretleri SHO ve SCSO algoritmaları ile optimize edilmiş ve grafikler aracılığıyla kendi aralarında karşılaştırılmıştır. SHO ve SCSO algoritmaları kullanılarak hata fonksiyonlarından sırası ile SHO için 0.5083 (MSE), 0.7153 (LMS) ve 0.4168 (MAE); SCSO için ise 0.0695 (MSE), 0.2924 (LMS) ve 0.2151 (MAE) sonuçlarına ulaşılmıştır. Grafikler incelendiğinde, en optimal çözümün her iki algoritma için de MSE ile sağlandığı sonucuna varılmaktadır. Çalışma sonuçlarına göre, SCSO algoritmasının SHO algoritmasına göre Adaptif Lineer Toplayıcı tasarımında daha yüksek bir başarı oranına sahip olduğu sonucuna varılmıştır.
Analisis Bibliometrik Penelitian dengan Tema Pembelajaran Daring dalam Pendidikan Islam
Authors: Etivali Adzroil Ula Al , Rusydiyah Evi Fatimatur
Published: December 2024

Penelitian ini berfokus pada periode 2020-2024 dan menggunakan pendekatan bibliometrik untuk menganalisis tren literatur terkait dengan tema pembelajaran daring dalam pendidikan islam. Data berasal dari Lens.org, yang berisi lebih dari 200 juta publikasi ilmiah. Kajian ini berfokus pada publikasi pada negara Indonesia. Analisis meliputi pola kutipan, sebaran geografis, dan trend terkait. Data yang dikumpulkan melalui kata kunci “online learning in Islamic education”. Hasil yang menunjukkan peningkatan signifikan dari tahun 2022 hingga 2023, dengan jenis artikel jurnal yang menjadi tipe dokumen yang sering digunakan oleh peneliti untuk mempublikasikan jurnal. Studi ini memberikan wawasan tentang perkembangan literatur dan peluang penelitian di masa yang akan datang.
Optimizing large language models: Techniques for efficiency and scalability in NLP applications
Authors: Nandan Nagapati Bhat  , Andhe Dharani
Published: December 2024

Optimizing the efficiency and scalability of Large Language Models (LLMs) is crucial for advancing Natural Language Processing (NLP) applications. This paper explores various optimization techniques for enhancing LLMs, focusing on strategies that improve computational efficiency and model scalability. The paper provides a comparative analysis of these techniques by evaluating their impact on key performance metrics, such as training time, memory usage, and inference speed. Through rigorous experimentation, our optimized model demonstrated a 30% reduction in training time and a 25% decrease in memory consumption, while maintaining competitive accuracy levels. The integration of these optimization techniques into a comprehensive framework facilitates enhanced operational efficiency and resource utilization. The findings underscore the significant benefits of adopting optimization strategies in LLMs, offering a valuable approach for improving the performance and scalability of NLP applications.
Kars (Türkiye) Polifloral Arı Poleninin Botanik Kökeni, Antibakteriyel ve Antioksidan Özellikleri: Analitik Bir Çalışma
Authors: Mutlu Neslihan , Akdoğan Karadağ Gül Esma , Akpınar Salih
Published: December 2024

Bu çalışmanın amacı, Türkiye’nin kuzey-doğusunda yer alan Kars’ta bulunan polifloral arı poleninin otanik kökeni, antibakteriyel ve antioksidan aktivitelerinin yanı sıra toplam fenolik içeriği ve toplam flavonoid içeriğini araştırmaktır. Polenin, Cistaceae, Boraginaceae, Brassicaceae, Fabaceae, Papaveraceae, Asteraceae, Polygonaceae, Rosaceae, Lamiaceae ve Plantaginaceae dahil olmak üzere on takson içerdiği bulundu. Test edilen mikroorganizmalara karşı minimum inhibitör konsantrasyon (MİK) değerleri 2.5 ile 5 mg/mL arasında değişmektedir. Toplam fenolik içeriğin belirlenmesinde Folin-Ciocalteu yöntemi kullanılmış ve bu miktarın 23.65 mg gallik asit eşdeğeri (GAE)/g olduğu belirlenmiştir. Arı poleni etanolik ekstraktındaki toplam flavonoid içerik değeri 14.56 mg kuersetin eşdeğeri (KE)/g olarak belirlenmiştir. Arı poleni etanolik ekstraktının antioksidan kapasitesi, 1,1-Difenil-2-pikrilhidrazil (DPPH), bakır iyon azaltıcı antioksidan kapasitesi (CUPRAC) ve 2,2'-Azino-bis-3-etilbenztiyazolin-6- sülfonik asit (ABTS) yöntemleri kullanılarak değerlendirilmiş, sırasıyla 16.18 mg Trolox eşdeğeri (TE)/g, 54. mg TE/g ve 91.9 mg TE/g sonuçları elde edilmiştir. Yağ asidi bileşimleri, gaz kromatografisi/kütle spektrometrisi (GC/MS) kullanılarak belirlenmiştir. Baskın yağ asidinin α -linolenik asit (%20.46) olduğu, bunu sırasıyla linoleik asit (%16.68), palmitik asit (%12.94) ve araşidonik asitin (%9.65) takip ettiği tespit edilmiştir. Bu çalışmada, Kars'tan temin edilen polifloral arı poleninin botanik çeşitliliği, antibakteriyel ve antioksidan özellikleri ile kimyasal içeriği hakkında kapsamlı bir değerlendirme sunmaktadır.
Güneş Spektrumun Türkiye'deki Farklı Bölgeler için Spektral Etkilerin İncelenmesi
Authors: Sarıoğlu Gencer , Eke Rüştü
Published: December 2024

Fotovoltaik (PV) modüller üzerine düşen güneşin spektral dağılımından etkilenmektedir. Bu çalışmada farklı iller seçilmiş ve SPCTRL2 programı kullanılarak faklı zamanlar için gelen doğrudan güneş ışınımı spektrumu elde edilmiştir. Bu spektrumlar kullanılarak ortalama foton enerjisi (APE) ve yararlı kesir (UF) ifadeleri güneş gözelerinin spektral tepki aralığına uyumlu olarak seçilmiş ve 300-1200 nm aralığında hesaplanmıştır ve karşılaştırılmıştır. Elde edilen APE değerleri AM 1.5D spektrum ile karşılaştırılmıştır. Aynı enlem üzerindeki incelenen şehirler için (Muğla, Şanlıurfa, İstanbul ve Trabzon) APE ve UF parametreleri batıda bulunan şehirlerde daha büyük olduğu görülmüştür. Aynı boylam üzerindeki incelenen şehirleri (Muğla, Şanlıurfa, İstanbul ve Trabzon) karşılaştırdığımızda güneyde bulunan şehirler daha büyük APE ve UF parametrelerine sahip olduğu görülmüştür. PV modül teknolojisinin yapıldığı yarıiletkenin yasak enerji aralığı ile UF parametresi arasında ilişki vardır ve yasak enerji aralığı arttıkça UF parametresi azalmaktadır. UF parametresinin düşük olduğu güneş gözesi teknolojileri spektral etkiye karşı daha hassas davranmaktadır.
Naujosios medijos, "prarastos" temos ir šiuolaikinės kultūros studijos
Authors: Repšienė Rita
Published: December 2024

XXI amžiaus mentalinį kraštovaizdį okupuojančios virtualios medijos, kaip socialiniai tinklai, internetinės svetainės, tinklaraščiai, akademinė elektroninė leidyba ir visa skaitmeninėje terpėje kuriama bei skleidžiama produkcija, sąlygoja tapaty- bines transformacijas ir komunikacijų vyravimą, „triukšmą" bei dezorientaciją, kaip beprasmio blaškymosi būseną, paverčiančią mūsų kasdienybę nesiliaujamu žinių, informacijos, invazijų, tikrų ir „netikrų“ naujienų srautu. Žiniasklaidos, kaip masinio komunikavimo priemonės, naudojamos skaitmeninės technologijos - internetas, mobilusis ryšys, inovatyvios platformos, pasitelkia vaizdą, meną, poveikio neišvengiamumą ir suteikia kultūrai vertybinės profanacijos bei elitiškumo kaip izoliacijos iššūkį. Populiarioji kultūra, reprezentuojama visuotiniame savitiksliame savęs viešinime ir paviršutiniškumo demonstracijoje, skiriant vis mažiau laiko įsigilinimui ir tikintis aprėpti kuo plačiau, išgyvena pakilimo apoteozę ir tampa tam tikra kokybės, savigarbos ir privatumo praradimo išraiška. Šiuolaikinio visuotinio medialumo, viešinimosi ir vertybinio savęs niveliavimo pasekmės skatina naujumo sąvoką suteikti realybės kaip demencijos pokyčiams. Globali vartotojų kultūra, kuri formuojama laksčiai prisitaikančios paslaugų rinkos (Frederic Jameson), inicijuoja nuolatinio naujumo gimimą: naujos temos, nauji įvaizdžiai, naujos prieigos, nauji požiūriai, atmetant tradiciją, paveldą bei ritualus ir inicijuojant naujus išbandymus.
A study of peripheal nervous system alterations in hypothyroid patients
Authors: Das Deep Ayan , Mukheri Sibaprakash , Samanta Shubhrangsu , Kannabathula Ajay Babu
Published: December 2024

Introduction: Hypothyroidism is an endocrine disorder of deficient thyroid hormone levels in the circulation. Thyroid hormones are essential for the normal functioning of the brain and nervous system. One of the manifestations of the hypothyroidism is the peripheral neuropathy. Methods: This cross sectional study includes 30 hypothyroid patients and 30 normal subjects between the age group of 20 to 60 years. The nerve conduction study was done by using Recorders Medicare System (RMS) EMG EPM2K version-1. Three parameters (latency, amplitude and nerve conduction velocity) of motor and sensory component of three nerves (Median nerve, Ulnar nerve and Peroneal nerve) were compared between cases (Hypothyroidism) and controls (non hypothyroid). Statistical analysis was done by unpaired ‘t’ test and ANOVA with SPSS software for various analysis. Results: The nerve conduction velocity is reduced in right median, right and left ulnar and left common peroneal nerves. The latency is prolonged in the right and left ulnar nerve as well as in the peroneal (both right and left) nerve. The amplitude of the nerve conduction action potential of the all the nerves is not significantly reduced. The sensory nerve conduction velocity of the sural nerve is reduced in our present study.
The Corruption Reduction with an Administrative Law Approach: Evidence from Australia
Authors: Hafidz Jawade , Amalia Fitri Dini , Muhammad Azam  , Arifullah Achmad , Prasetia Wiranto Agus
Published: December 2024

The reverse burden of proof mechanism shifts the responsibility to the fraudster to prove that his wealth did not come from corruption. This system raises concerns regarding justice, legal certainty, and the protection of human rights. This research aims to analyze the application of reverse evidence in criminal and criminal acts of corruption in procuring goods and services from the perspective of state administrative law. Reversal of the burden of proof in criminal acts of corruption is essential to eradicate corruption in Indonesia. From the standpoint of state administrative law, reverse evidence functions as a monitoring tool to prevent abuse of authority by public officials and ensure the implementation of the principles of good governance, namely transparency, accountability, and integrity in the procurement of goods/services. The novelty of this study lies in its proposal to explicitly clarify the balance of evidentiary obligations between the public prosecutor and the defendant in reversing the burden of proof under Law No. 20 of 2001, ensuring fair legal certainty and protection of human rights. Indonesia can adopt Australia's Proceeds of Crime Act 2002 approach, enabling asset seizure from suspected corruption without conviction, to enhance accountability and recover state losses effectively.
Análise da temperatura média radiante em Alagoas
Authors: Vanderlei Mário Henrique Guilherme dos Santos , Silva Fabrício Daniel dos Santos , Costa Rafaela Lisboa , Mariano Glauber Lopes , Accioly João Otávio Alves , Gomes Helber Barros , Cabral Júnior Jório Bezerra , Reis Jean Souza dos , Gomes Heliofabio Barros , Silva Maria Cristina Lemos da
Published: December 2024

Este estudo analisa a evolução temporal e espacial da Temperatura Média Radiante (TMR), um dos principais componentes para a avaliação do conforto térmico através do Universal Thermal Climate Index (UTCI). Utilizando dados horários de reanálise do ERA-5 do ECMWF (European Centre for Medium-Range Weather Forecasts), foram comparados os períodos de 1961-1990 e 1991-2020. A TMR quantifica a troca de calor radiante entre um indivíduo e seu entorno. Os resultados revelam tendencia de aumento da TMR em Alagoas, com destaque para as estações quentes (verão e outono), onde as anomalias positivas de TMR foram mais pronunciadas e abrangem a maior parte do estado. Entretanto, o norte alagoano apresentou um comportamento divergente, com anomalias negativas especialmente no inverno e primavera, indicando um padrão climático mais complexo nessa região. A análise anual confirmou a tendência de aumento da TMR em grande parte do território alagoano, com exceção de algumas áreas do norte. Esses resultados evidenciam a necessidade de estudos mais aprofundados sobre as causas e consequências dessas variações térmicas, e destacam a importância de considerar as particularidades regionais ao se planejar ações de adaptação e mitigação das mudanças climáticas em Alagoas.
Analisis Performa Website Universitas Widya Husada Semarang Menggunakan Metode Automated Usability Testing Dengan Tools Google Pagespeed Insights Dan Gtmetrix
Authors: Sandy Irawan  , Cahyono Rahadiyanto
Published: December 2024

Universitas Widya Husada Semarang adalah salah satu institusi pendidikan tinggi yang berkomitmen untuk menyediakan pendidikan berkualitas di bidang kesehatan. Terletak di kota Semarang, universitas ini menawarkan berbagai program studi yang didesain untuk mencetak tenaga profesional yang kompeten dan berintegritas. Website adalah kumpulan halaman web yang saling terhubung dan dapat diakses melalui internet menggunakan sebuah domain atau alamat web tertentu. Universitas Widya Husada memiliki website yang cukup aktif dalam memberikan informasi kepada calon mahasiswa yang ingin mendaftar maupun website untuk mahasiswa mengenai informasi seputar kampu, nilai akademik, jadwal perkuliahan dan lain sebagainya. Universitas Widya Husada Semarang sedang menghadapi permasalahan serius terkait performa website resminya. Masalah ini mencakup waktu loading yang lambat, seringnya terjadi downtime, dan respons server yang tidak konsisten. Keadaan ini berdampak negatif terhadap aksesibilitas informasi bagi mahasiswa, staf, dan calon mahasiswa. Untuk mengatasi masalah performa website Universitas Widya Husada Semarang, penggunaan tools seperti Google PageSpeed Insights dan GTmetrix dapat menjadi solusi efektif. Google PageSpeed Insights membantu menganalisis dan memberikan rekomendasi perbaikan performa berdasarkan dua aspek utama: kecepatan dan pengalaman pengguna. Hasil yang didapatkan dari Google PageSpeed Insight adalah sebesar 78% Performance, 78% Accessibility, 78% Best Practices dan 85% SEO dalam versi desktop sedangkan versi mobile adalah 66% Performance, 77% Accessibility, 79% Best Practices dan 85% SEO.  Sedangkan GTMetrix hasil performa yang ditunjukkan adalah memiliki skor 78%. Jadi pada intinya baik Google Page Speed Insight dan GTMetrix memiliki nilai performa yang sama yaitu 78 atau 78%.
PENGUJIAN BLACK BOX PADA WEBSITE BUITENZORG OUTDOOR MENGGUNAKAN METODE USE CASE TESTING DAN BOUNDARY VALUE
Authors: Jovita Nabilah Azizi  , Silalahi Ester Olivia , Rafli Damara  , Muhammad Farhan Fahrezy  , Fikri Saputra  , Wicaksono Aditya , Muhammad Nasir
Published: December 2024

Pengujian perangkat lunak menjadi aspek penting dalam pengembangan aplikasi untuk menjamin kualitas dan fungsionalitas. Penelitian ini berfokus pada pengujian black box pada website Buitenzorg Outdoor, sebuah platform penyewaan perlengkapan outdoor. Dengan menggunakan metode Use Case Testing dan Boundary Value Analysis, penelitian ini bertujuan untuk mengidentifikasi keandalan fungsionalitas berdasarkan skenario pengguna serta validasi data input/output. Metodologi melibatkan analisis use case untuk mendefinisikan skenario pengujian utama dan analisis nilai batas pada fitur-fitur kritikal. Hasil menunjukkan bahwa beberapa modul website memiliki cacat pada validasi input, terutama pada form pemesanan dan pendaftaran pengguna baru. Berdasarkan hasil pengujian, sistem berjalan dengan baik dengan persentase keberhasilan 98,64%. Studi ini memberikan kontribusi dalam meningkatkan proses pengujian sistem berbasis web melalui pendekatan sistematis yang dapat direplikasi. Temuan juga menunjukkan pentingnya pengujian berbasis use case untuk memitigasi risiko fungsional di lingkungan penggunaan nyata.
THE IMPLEMENTATION OF MANAGEMENT INFORMATION SYSTEMS IN THE DIGITAL ERA: CHALLENGES AND SOLUTIONS
Authors: Ana Nurfadilah  , Ilham
Published: December 2024

This research discusses the challenges and solutions of implementing management information systems in the digital era. In the digital era, the development of information technology is rapidly advancing and has brought significant changes to various aspects of life, including the business world. Companies and organizations are now required to be more responsive, faster, and more efficient in their operations. One way to achieve that goal is through the implementation of a Management Information System. (SIM ). This research uses the literature review method by examining the implementation of SIM through previous studies and articles. The results of this study indicate that the implementation of SIM does not always go smoothly; there are challenges that must be faced, such as costs, the integration of old systems into new ones, and data security. Therefore, solutions are needed to address these challenges.
Study of Argumentative Writing and Narrative Methods for English Majors based on Graph Neural Networks
Authors: Yao Shuang , Mai Hongyu
Published: December 2024

The main purpose of this study is to investigate the differences between narrative writing errors and argumentative writing errors of Chinese learners by using the argumentative writing and narrative writing methods of English majors based on graph neural networks. Using graph neural networks and the error analysis method described by Corder (1981), our research classification method is consistent with the theoretical framework of Burt and Kiparski. Our analysis aims to identify the different nature and characteristics of the errors present in these two components. The correlation between the prevalence of global and local errors, as well as their relationship to different types of writing, is carefully examined through graph neural networks. The findings ultimately suggest a targeted teaching approach tailored specifically to address common errors in different writing styles. This method is expected to significantly improve the writing level of English majors.
The Dynamic Evolution of Black Holes in General Relativity: Numerical Relativity Simulation
Authors: Huang Kenny S
Published: December 2024

As the core of the star left behind by the supernova explosion continues to collapse, the immense pressure causes protons to absorb electrons and transform into electrically neutral neutrons. The core of the star eventually forms a dense neutron star about 10 kilometres across, much smaller than a city. Neutron stars resemble giant atomic nuclei and are much denser than any atomic material on Earth. A small cup of matter from a neutron star exceeds the total mass of everyone on Earth. If the mass of the star's core is large enough, it will continue to collapse beyond the Schwarzschild radius, eventually forming a black hole. The gravitational field of a black hole is so strong that neither matter nor electromagnetic waves (including visible light) can escape from it. The boundary of this inescapable region is called the event horizon. In our experiments, we used a high-performance computing cluster and numerical relativity simulation software to accurately solve Einstein's field equations and demonstrate that the peak amplitude of gravitational waves emitted by black holes during mergers can reach with a frequency of 300 Hz. This study provides important insights into the dynamic evolution of black holes and the emission of gravitational waves under various initial conditions.
Re-assemblage and Dispersal: Exploring the Agency of Etruscan Votive Bronze Figurines in Museum Collections
Authors: Negro Marianna , Joy Jody
Published: December 2024

The document investigates the evolving role of museum collections, particularly through the lens of ‘re-assemblage’, which involves studying the histories and contexts of artefacts. Focusing on Etruscan votive bronze figurines from the British Museum and the Metropolitan Museum of Art, the research reveals how these objects, despite losing their original archaeological settings, continue to possess agency and accrue new meanings as they are collected and dispersed. Ultimately, the paper underlines that museum collections remain fluid and are subject to constant reinterpretation and renewal of value over time.
Naxos di Sicilia. Indagini nella città di età classica. La scoperta di tracce di un rituale di abbandono (scavi 2019)
Authors: Lentini Maria Costanza
Published: December 2024

Una breve campagna di scavo nel 2019 ha riportato in luce i crocevia tra gli stenopoi 8 e 9 e la plateia A, principale asse viario E/O dell’impianto urbano a griglia di epoca classica. Come tutti i crocevia sinora scoperti, essi conservano presso l’angolo sud-est i resti della base quadrangolare di un altare, particolarità unica del sistema urbano di V secolo a.C. di Naxos di Sicilia. Nel crocevia A9, l’esplorazione estesa ai prospicienti blocchi di abitazioni ha individuato all’interno di un ambiente aperto sull’incrocio un deposito votivo, nel quale è possibile riconoscere le tracce di un rituale compiuto all’interno della casa in concomitanza con la distruzione della città nel 403 a.C., forse assimilabile a un rito di abbandono.
User-Centered Usability Evaluation of the DiaCare App for Diabetes Self-Management: A uMARS Analysis
Authors: Kurnia Anih , Said Faridah Mohs , Paduragan Santhna Letchmi
Published: December 2024

Background: Diabetes mellitus (DM) is a common illness that requires appropriate self-management for the best health outcomes. Mobile health (mHealth) apps, such as DiaCare, can improve management of DM. However, usability issues must be solved to ensure long-term user involvement and effectiveness. Objective: To assess the usability of the DiaCare app for DM management using quantitative and qualitative approaches. Methods: A total of 100 participants took part, including fifty Type 2 diabetes (T2DM) patients and fifty healthy subjects. Data were gathered using the uMARS tool, which evaluated six domains: interaction, performance, visual appeal, information quality, perceived impact, and subjective evaluation. Results: Healthy subjects demonstrated superior ratings in all domains except perceived impact. The qualitative analysis showed the importance of a personalized, interactive app for DM control. Conclusions: While DiaCare provides benefits, more customization is required to suit the demands of T2DM patients, particularly in terms of personalization and navigation. Future research should focus on social interaction aspects to improve user assistance.
Effect of Bodyweight Squat Exercise With Blood Flow Restriction on Sprint and Jump Performance in Collegiate Soccer Players
Authors: Kamiş Okan , Kurt Muhammet , Blaisdell Robert , Macdonald Christopher , Nobarı Hadi
Published: December 2024

This study investigated the effect of bodyweight squat (BWS) with blood flow restriction (BFR) exercise on sprint and jump performance in collegiate male soccer players. Twenty-four male collegiate soccer players (age: 19.3±1.0 years; height: 178.8±5.8 cm; body mass: 73.5±10.7 kg) were randomly divided equally into BFR or control groups. The BFR group performed BWS with BFR, while the Control group performed BWS without BFR 3x/week for eight weeks on nonconsecutive days. Both groups performed BWS for 30-15-15-15 repetitions with 30-second rest between sets (with continuous BFR pressure between sets). Limb occlusion pressure (LOP) was measured in a supine position after 10 min of passive rest by the automated device. Progressive overload was achieved by increasing LOP % weekly. The pressure was set at 60% LOP for the first four weeks and then was increased to 70% LOP for weeks 5 and 6 and then to 80% LOP for weeks 7 and 8. Countermovement jump (CMJ) and 30m sprint performance were assessed before and after the exercise program. No statistically significant differences between groups were identified. Both groups significantly increased sprint and CMJ performance (p
Response A Trees Date palm Phoenix dactylifera L. For salt stress conditions
Authors: Hassanein M. Gabash  , Mortada Shanan Awda  , Al-Rabea'A, J.A.R
Published: December 2024

Degradation of agricultural land due to soil salinity and irrigation water is one of the major soil constraints that greatly hinders agricultural production and food security in any country and is one of the most difficult challenges at present, in addition to climate change and increasing frequency lonliness Phenomena Climate Extreme Especially Recurring droughts have attracted the attention of researchers to address them and develop possible solutions to address them by relying on the research aspect, which is of utmost importance, with the aim of improving soil resource capabilities and irrigation management by improving the quality and productivity of irrigation water in order to maintain the sustainability of the agricultural sector. The current review summarizes an explanation of how salt stress affects growth indicators in palm trees, which negatively and significantly affects the ability and production. Agricultural and thus disturbance and imbalance in providing the growing global demand, especially with the steady increase in population growth. Discusses the effect of soil salinity and irrigation water on plant pigments and some growth indicators and characteristics Physics For the fruits The result Furthermore, the article deals with determining the effect of salt stress on the mineral content of leaves and fruits. As significant indicators for assessing the severity and intensity of salt stress, it is therefore recommended to conduct more comprehensive studies on a larger scale, which will contribute to understanding these effects in developing strategies to reduce and minimize salt stress and its harmful effects on date palm cultivation.
Investigation the impact of turmeric supplementation on mRNA expression of growth-related peptides and gut health in broilers
Authors: Hakeem J Kadhim
Published: December 2024

Antibiotic resistance has prohibited its use for non-therapeutic purposes in livestock. Recent studies have suggested that turmeric, a natural compound, could serve as a potential alternative to antibiotics in promoting growth in chickens. Therefore, this study aimed to determine the effects of turmeric supplementation on the gene expression of growth-related peptide and mucin2, an indicator of intestinal health, in broilers. We added two percentages of turmeric (0.5% and 1%) to the standard diet, categorizing them as turmeric 0.5% and turmeric 1%, and compared the results with the control group (turmeric 0.0%). Gene expression analysis was conducted anterior pituitary (APit), liver, and intestine. The results showed that body weight gain was higher in the turmeric-treated groups, and feed conversion ratio was improved significantly, indicating that turmeric is more efficient in converting feed into body mass. Analysis of gene expression by RT-qPCR revealed an increase in mucin2 gene expression in the turmeric-treated groups, suggesting an enhancement of gut health. Furthermore, the study found overexpression of the growth hormone (GH) and thyroid-stimulating hormone mRNA expression in the APit. In the liver, an increase in the mRNA expression of the GH receptor in the turmeric-treated groups could facilitate GH action on hepatocytes, leading to an increase in the gene expression of insulin-like growth factors and their binding proteins, which supports muscle cell differentiation and proliferation. Data suggested that turmeric might stimulate myoblast differentiation and satellite cell proliferation to increase muscular growth. In summary, turmeric addition promoted body growth by activating certain genes and inhibiting others. This effect could be due to an increase in the expression of genes that drive muscle cell proliferation. Finally, turmeric enhances gut health through the mucin2 gene.
A Review on the Role of Machine Learning in Predicting the Spread of Infectious Diseases
Authors:   Computer Science and Intelligent Systems Research Center, Blacksburg 24060, Virginia, USA, S. S. ,   School of ICT, Faculty of Engineering, Design and Information  Communications Technology (EDICT), Bahrain Polytechnic, Isa Town, Bahrain, Elkanzi Mohamed
Published: December 2024

AI and the development of the ML system are expected to play a crucial role in preventing and controlling infectious diseases as part of global health issues. Typically, conventional epidemic models give a narrow perspective of the distribution of diseases and their causes, which leads to the use of AIML solutions. Some of these tools utilize genomic data and environmental and patient information to boost forecasts' accuracy and facilitate real-time disease surveillance. The human-driven models of pandemic identification were replaced by sophisticated artificial intelligence models such as deep learning and advanced neural networks indicating patterns, the possibility of future outbreaks, and driving the concept of public health interventions. Many examples can be provided to support the efficiency of ML's approaches to combating antimicrobial resistance, tuberculosis relapse, and the spatial-temporal modeling of an alternative disease such as measles or COVID-19; nonetheless, data standardization, scaling, ethics, and bias issues are limitations to the application of such solutions. Controlling unfairness consists of the problem of transparency, patient data confidentiality, and disparities in the deployment of AI systems. However, practical and comparable implementations of these systems require cross-sector cooperation and global data sharing for varied conditions in the broader healthcare environment. Future developments point to the opportunity to enrich epidemic prediction models by blending genomic precision systems, explainable artificial intelligence, and interdisciplinary studies. This review provides evidence for how AIML has revolutionized infectious disease management, calls for responsible innovation and ethical deployment of AI, and encourages international collaborations to safeguard the global health sector against new and emerging diseases. Subsequently, unexpected events with high fatality rates and global impact, such as disease outbreaks, epidemics and pandemics, are still a threat to life; therefore, the ability of AI and ML to advance epidemic preparedness and response in the future is promising to enhance global health protection to future pandemics.
A Review of Metaheuristic Algorithms for Load Forecasting in Smart Grids
Authors:   Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt, Mohammed Mohammed ,   Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia, Alharbi Amal H.
Published: December 2024

Smart electrical grids (SGs) have emerged to advance the management of power systems by solving issues such as voltage instability, reactive loads, power loss, and the integration of renewable energy resources. This review focuses on the applicability of metaheuristic algorithms to energy distribution systems, improve operation, and overcome the repercussions affecting the environment and overall costs. PSO, GA, and GWO have been identified for their effectiveness in dealing with the complexity of PS due to the nonlinear and dynamic nature of today's energy systems. The review also addresses the extension of methods in machine learning for enhancing load forecasting and real-time energy control, which are key factors for shifting to innovative and renewable energy systems. Based on the literature review of the state of the art over the last five years, this research highlights some achievements and limitations. It provides recommendations for further directions in advancing Smart Grid algorithms. These results highlight the use of meta-heuristics in redesigning processes that offer optimal, reliable and sustainable energy facilities.
Machine Learning in Stock Price Prediction: A Review of Techniques and Challenges
Authors:   Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia, Doaa Doaa ,   School of Computer Science, University of Petroleum and Energy Studies, Dehradun, 248001, India, Kumar Sunil
Published: December 2024

Future stock price prediction is one of the most important and complex tasks in the lecture on finance, mainly due to the characteristics of the financial world. Machine learning techniques have greatly improved this area: problems with frequent data and nonlinear processes, which cannot be solved using conventional models, have been solved. In this paper, the author looks at how the methodology of data preprocessing and two modeling techniques, namely, the high-frequency data model and the sentiment analysis model, have helped improve the efficiency of stock price forecasts. Among the proposed techniques, Temporal Convolutional Networks (TCN), Attention Mechanisms, and Transformer-based architectures are mentioned due to their capability to distill complex market dynamics. However, issues like data quality and fluctuations in the market remain sticky even as we see the speed of innovation picking up, and thus, the importance of model robustness and interpretability. Drawing on recent advances and mapping out the directions for future studies, this paper reveals how machine learning may revolutionize stock market prediction and investment decision-making in a continuously transforming financial environment.
“Kaikki lähtee vuorovaikutuksesta” – Varhaiskasvatuksen ammattilaisten kieli-, kulttuurija katsomuspedagoginen osaaminen
Authors: Arvola Outi , Haanpää Monika , Lastikka Anna-Leena , Kangas Jonna
Published: December 2024

Tässä artikkelissa tarkastellaan, millaista on varhaiskasvatuksen ammattilaisten kieli-, kulttuuri- ja katsomuspedagoginen osaaminen ja miten sitä tulisi vahvistaa. Tutkimustehtävänä oli selvittää, miten ammattilaiset kuvaavat omaa ammatillista kieli-, kulttuuri- ja katsomuspedagogista osaamistaan suhteessa lapsiin ja huoltajiin. Lisäksi selvitettiin yksilö- ja tiimitason tietoja ja taitoja, joita heillä on kieli-, kulttuuri- ja katsomuspedagogiikan toteuttamiseen ja kehittämiseen. Tutkimusaineisto on kerätty varhaiskasvatuksen opettajina toimivilta ammattilaisilta (N = 10) fokusryhmähaastatteluina. Tutkimusaineisto on osa laajempaa “Avaimia yhteiseen ymmärrykseen” -tutkimushanketta, jossa tarkastellaan inkluusion, osallisuuden ja moninaisuuden hyviä käytäntöjä varhaiskasvatuksessa.
Tutkimustulosten perusteella ammattilaisten kieli-, kulttuuri- ja katsomuspedagogisessa osaamisessa korostuvat moninaiset vuorovaikutustaidot: lasten ja ammattilaisten välinen vuorovaikutus, huoltajien kanssa tehtävä yhteistyö, sekä tiimin ja henkilöstön keskinäinen vuorovaikutus. Vuorovaikutuksessa lasten ja perheiden kanssa painottuu yksilöllinen kohtaaminen. Luottamuksen rakentamisessa ja kohtaamisten onnistumisessa eri kieli- ja kulttuuritaustaisella henkilöstöllä on osaamista vahvistava merkitys. Ammattilaisten reflektio- ja tiimitaidot sekä tiimin sitoutuminen työhön ovat keskeisiä osaamista kehittäviä tekijöitä pedagogiikan toteuttamisessa. Myös työn jousto- ja muuntautumiskyky tunnistetaan osaamisessa olennaiseksi. Ammattilaisten vahva kieli-, kulttuuri- ja katsomuspedagoginen osaaminen on investointi varhaiskasvatuksen inklusiiviselle tulevaisuudelle.
Links Between the Teacher’s Atmosphere Postures and the Pupils’ Study Postures When Solving Proportionality Problems, identified under Implicative Statistical Analysis in ICHC-MGK
Authors: Razafindrabehita Lwanga Albert , Ravelomanana Juvenile Christalin , Ravelojaona Vatosoa Tsirinala Fabiola , Rakotomalala Hery Frédéric , Totohasina André
Published: December 2024

This article aims to examine the possible links between the teacher’s atmospheric postures and the students’ learning postures during the teaching of mathematics, particularly with regard to solving proportionality problems in 3rd grade at Bourbon College on Reunion Island. This analysis will be based on the observation of teaching practices through video sequences, and will be deepened through the use of Implicative Statistical Analysis (ISA) according to ICHC-MGK. The study results show that maintaining a space for dialogue encourages students to adopt an academic posture. Creating this space for dialogue also helps to capture their attention. As a result, the study highlights the importance of providing teachers with in-depth training and a better understanding of their pupils’ individual needs. This would enable them to adapt their teaching methods more effectively to the particularities of each learning context, in order to improve student success.
Histopathological Insights into Partial and Complete Typhlectomy in Dogs: A Comparative Study
Authors: Khaled Hadeer , Ahmed Howaida , Korritum Ahmed , Nouh Samir
Published: December 2024

The cecal resection indicated disorders such as impaction, inversion, perforation, dilatation, neoplasia, and severe inflammation (typhlitis). The cecum surgical ablation depends on the disease's progression and stringency; the cecum can be excised partially or completely from the colon. This study aimed to investigate the histopathological findings and provide a comparative analysis of cecal tissue following partial and complete typhlectomy in dogs, offering insights into the comparative outcomes and implications aiding in surgical decision-making and postoperative management strategies. Tissue samples from the cecum were collected from two dogs who underwent exploratory laparotomies two months later, either partial or complete typhlectomy procedures, and were subjected to histopathological examination. The results reveal distinct histopathological changes associated with each surgical approach, demonstrating that partial typhlectomy involved more active repair and healing processes in the cecal intestinal wall layers compared to the changes in granulation or organized tissue proliferation in complete typhlectomy. Partial typhlectomy was characterized by more active lymphoglandular complexes and peripheral lymphoid follicle formations having vast, clear germinal centers, while complete typhlectomy had fewer active changes. The mucosa surface looked near normal histology after a partial typhlectomy. In contrast, in a complete typhlectomy, the upper villi appeared short and thickened due to connective tissue proliferation and dilated lacteal ducts. In Conclusion, the histopathological results show distinct tissue responses. The comparative analysis indicates differences in tissue damage and healing and revealed that partial typhlectomy resulted in an enhanced or more advanced degree of repair than complete typhlectomy in dogs.
DETERMINATION OF THE PREVALENCE OF ASTHMA AND ASTHMA SYMPTOMS IN BAKERY WORKERS IN MALATYA
Authors: R ADEM , KAYHAN MEHMET , TOPAL ERDEM
Published: December 2024

SUMMARY
Purpose: Asthma is one of the most commonly reported occupational lung diseases. Studies indicate that one of the primary causes of occupational asthma is baker’s asthma. This study aims to determine the prevalence of asthma and asthma-related symptoms among bakery workers in Malatya, Turkey.
Materials and Methods: Designed as a cross-sectional study, this research was conducted through a survey to assess the prevalence of asthma, the frequency of asthma symptoms, and factors influencing asthma among bakery workers in Malatya between December 2022 and May 2023.
Results: The study included 142 participants, comprising 139 men and 3 women. Of the participants, 35.5% had been working for over 21 years, while 34% had been employed for less than 10 years. Approximately 20% of participants reported atopic complaints. While 6.3% of workers were previously diagnosed with asthma, 14.1% had at least two asthma-related symptoms. The risk of asthma was notably higher among workers in dough production compared to those in other departments.
Conclusion: Occupational exposure appears to significantly contribute to the increased frequency of asthma among bakers working in dough production.
Surgical Treatment of Complete Bronchial Rupture Due to Blunt Thoracic Trauma with Bronchoplasty
Authors: BIYIKLI MERVE , KILI MURAT
Published: December 2024

Tracheobronchial ruptures are rare but potentially life-threatening injuries. These injuries can develop as a result of high-energy motor vehicle accidents, falling from a height, crushing, and penetrating injuries. If diagnosed early, tracheobronchial ruptures can be successfully treated.The most common symptoms include shortness of breath, subcutaneous emphysema, and pneumomediastinum. Diagnosis may be delayed due to other accompanying system injuries. Pneumomediastinum, which does not respond to tubular toracostomy, massive air leakage from the thoracic drain and the presence of pneumothorax should warn the clinic of the possibility of intratorastic tracheobronchial rupture. Early diagnosis prevents non-reversible loss of parenchym, resulting in fewer complications and an increase in survival.