bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Intervention Techniques for Alzheimer’s Disease: Conventional Methods and the Role of AI in Advancing Care
Authors: Subramanian Karthikeyan , Hajamohideen Faizal , Vimbi Viswan  , Shaffi Noushath , Mahmud Mufti 
Published: April 2024

Alzheimer’s disease (AD) is a neurodegenerative condition characterized by cognitive decline and functional impairment. This study compares conventional intervention techniques with emerging artificial intelligence (AI) approaches to AD. Intervention technique refers to a specific method or approach employed to bring about positive change in a particular situation. In the context of AD, such techniques are crucial as they aim to slow down the progression of symptoms, alleviate behavioral challenges, and support patients and their caretakers in managing the complexities of the condition. Conventional intervention techniques, such as cognitive stimulation and reality orientation, have demonstrated benefits in improving cognitive function and emotional well-being. Conventional intervention approaches are widely preferred as they have a proven track record of effectiveness, personalized response, cost-effectiveness, and patient-centered care. Despite these benefits, they are limited by individual variability in response and long-term effectiveness. On the other hand, AI-based approaches such as computer vision and deep learning hold the potential to revolutionize Alzheimer’s interventions. These technologies offer early detection, personalized care, and remote monitoring capabilities. They can provide tailored interventions, assist decision-making, and enhance caregiver support. Although AI-based interventions face challenges such as data privacy and implementation complexity, their potential to transform Alzheimer’s care is significant. This research paper compares conventional and AI-based approaches. It reveals that while traditional techniques are well established and have proven benefits, AI-based interventions offer novel opportunities for personalized and advanced care. Combining the strengths of both approaches may lead to more comprehensive and effective interventions for individuals with AD. Continued research and collaboration are crucial to harness the full potential of AI in improving Alzheimer’s care and enhancing the quality of life for affected individuals and their caregivers.

Received: 19 January 2024 | Revised: 30 March 2024 | Accepted: 2 April 2024

Conflicts of Interest
Noushath Shaffi is the Associate Editor for Artificial Intelligence and Applications, and was not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflicts of interest to this work.
Data Availability StatementData sharing is not applicable to this article as no new data were created or analyzed in this study.
Impact of Social Media Sentiments on Stock Market Behavior: A Machine Learning Approach to Analyzing Market Dynamics
Authors: Kandasamy Theeshanthani , Bechkoum Kamal 
Published: April 2024

Social media has become a valuable tool for informed decision-making. This research delves into the influence of Twitter sentiments on the stock market’s movements and price fluctuations, specifically focusing on Tesla Inc. and the tweets of Elon Musk. A combination of deductive and inductive reasoning approaches is used to explore the intricate relationship between the social media platform and the stock market. Methodologically, the Twitter data undergoes rigorous processing to derive features for the machine learning predictive model, and the sentiments are extracted using the Valence Aware Dictionary and Sentiment Reasoner tool. This study emphasizes the usefulness of social media in predictive modeling while underscoring the importance of evaluating data reliability considering challenges such as spam tweets and geographical relevance. Multiple machine learning models are tested against four distinct datasets addressing the high stock price volatility. XG Boost and Random Forest Regressor emerge as the most effective performers, particularly when moving averages are included, showing enhanced performance. This research establishes an evident correlation between social media sentiments and stock market movements, however with limited predicting power. It is also noted that integrating traditional financial metrics enriches the understanding of stock market dynamics while enhancing the model’s predictability.

Received: 4 November 2023 | Revised: 13 March 2024 | Accepted: 1 April 2024

Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.

Data Availability Statement
The data that support this work are available upon reasonable request to the corresponding author.
Deciphering the Genomic Complexity of Acromesomelic Dysplasia Type Maroteaux: Insights from a Consanguineous Pakistani Family
Authors: Khalid Maryam , Khalid Mehak , Zaidi Dua Zhaira , Zhaira Ismat , Hashmi Mahe- Kamil Qureshi , Begum Shahzeera , Chaudary Shamshad Kausar , Ahmed Waseem 
Published: April 2024

Purpose: This study delves into the genetic basis of Acromesomelic Dysplasia (AMD), a rare skeletal disorder, particularly focusing on the Maroteaux type within a consanguineous Pakistani family. The purpose is to explore the genetic landscape beyond known mutations and understand the underlying causes of AMD.
Methodology: A comprehensive approach was adopted, combining detailed clinical examinations with advanced genomic methodologies. Ethical clearance was obtained, and pedigree design facilitated the identification of affected individuals. Molecular techniques including DNA extraction and linkage analysis were conducted to investigate known AMD-related genes such as NPR2, BMPR1B, GDF5, GALNS, GLB1, and GHR. Whole-genome sequencing was emphasized despite financial constraints to uncover potential novel genetic loci associated with AMD.
Findings: Despite exhaustive analysis, no mutations in known AMD-related genes were identified within the studied family. Linkage analysis did not correlate with any known genetic loci, suggesting the presence of unidentified genetic elements contributing to AMD. Autosomal recessive inheritance was confirmed through pedigree and molecular scrutiny, highlighting the complexity of AMD genetics.
Unique Contribution to Theory, Policy and Practice: This research underscores the importance of employing advanced genomic strategies, such as whole-genome sequencing, in decoding rare genetic disorders like AMD. By revealing the limitations of current diagnostic approaches and advocating for collaborative efforts and resource pooling, this study contributes to the advancement of genetic counseling, therapeutic interventions, and precision medicine in rare genetic disorders.
Lord Jesus Christ
Authors: Hurtado Larry W. 
Published: April 2024

This outstanding book provides an in-depth historical study of the place of Jesus in the religious life, beliefs, and worship of Christians from the beginnings of the Christian movement down to the late second century.
Lord Jesus Christ is a monumental work on earliest Christian devotion to Jesus, sure to replace Wilhelm Bousset’s Kyrios Christos (1913) as the standard work on the subject. Larry Hurtado, widely respected for his previous contributions to the study of the New Testament and Christian origins, offers the best view to date of how the first Christians saw and reverenced Jesus as divine. In assembling this compelling picture, Hurtado draws on a wide body of ancient sources, from Scripture and the writings of such figures as Ignatius of Antioch and Justin to apocryphal texts such as the Gospel of Thomas and the Gospel of Truth.
Hurtado considers such themes as early beliefs about Jesus’ divine status and significance, but he also explores telling devotional practices of the time, including prayer and worship, the use of Jesus’ name in exorcism, baptism and healing, ritual invocation of Jesus as “Lord,” martyrdom, and lesser-known phenomena such as prayer postures and the curious scribal practice known today as the nomina sacra.
The revealing portrait that emerges from Hurtado’s comprehensive study yields definitive answers to questions like these: How important was this formative period to later Christian tradition? When did the divinization of Jesus first occur? Was early Christianity influenced by neighboring religions? How did the idea of Jesus’ divinity change old views of God? And why did the powerful dynamics of early beliefs and practices encourage people to make the costly move of becoming a Christian?
Boasting an unprecedented breadth and depth of coverage — the book speaks authoritatively on everything from early Christian history to themes in biblical studies to New Testament Christology — Hurtado’s Lord Jesus Christ is at once significant enough that a wide range of scholars will want to read it and accessible enough that general readers interested at all in Christian origins will also profit greatly from it.
Measurement report: Bio-physicochemistry of tropical clouds at Maïdo (Réunion, Indian Ocean): overview of results from the BIO-MAÏDO campaign
Authors: Leriche Maud , Tulet Pierre , Deguillaume Laurent , Burnet Frédéric , Colomb Aurélie , Borbon Agnès , Jambert Corinne , Duflot Valentin , Houdier Stéphan , Jaffrezo Jean-Luc , Vaïtilingom Mickaël , Dominutti Pamela , Rocco Manon , Mouchel-Vallon Camille , El Gdachi Samira , Brissy Maxence , Fathalli Maroua , Maury Nicolas , Verreyken Bert , Amelynck Crist , Schoon Niels , Gros Valérie , Pichon Jean-Marc , Ribeiro Mickael , Pique Eric , Leclerc Emmanuel , Bourrianne Thierry , Roy Axel , Moulin Eric , Barrie Joël , Metzger Jean-Marc , Péris Guillaume , Guadagno Christian , Bhugwant Chatrapatty , Tibere Jean-Mathieu , Tournigand Arnaud , Freney Evelyn , Sellegri Karine , Delort Anne-Marie , Amato Pierre , Joly Muriel , Baray Jean-Luc , Renard Pascal , Bianco Angelica , Réchou Anne , Payen Guillaume 
Published: April 2024

Abstract. The BIO-MAÏDO (Bio-physicochemistry of tropical clouds at Maïdo: processes and impacts on secondary organic aerosols formation) campaign was conducted from 13 March to 4 April 2019 on the tropical island of Réunion. The main objective of the project was to improve understanding of cloud impacts on the formation of secondary organic aerosols (SOA) from biogenic volatile organic compound (BVOC) precursors in a tropical environment. Instruments were deployed at five sites: a receptor site, Maïdo Observatory (MO) at 2165 m a.s.l. and four sites along the slope of the Maïdo mountain. Observations include measurements of volatile organic compounds (VOCs) and characterization of the physical, chemical and biological (bacterial diversity and culture-based approaches) properties of aerosols and cloud water. Turbulent parameters of the boundary layer, radiative fluxes and emissions fluxes of BVOCs from the surrounding vegetation were measured to help interpret observed chemical concentrations in the different phases. Dynamical analyses showed two preferred trajectory routes for air masses arriving at MO during the daytime. Both trajectories correspond to return branches of the trade winds associated with upslope thermal breezes, where air masses likely encountered cloud processing. The highest mixing ratios of oxygenated VOCs (OVOCs) were measured above the site located in the endemic forest and the highest contribution of OVOCs to total VOCs at MO. Chemical compositions of particles during daytime showed higher concentrations of oxalic acid, a tracer of cloud processing and photochemical aging, and a more oxidized organic aerosol at MO than at other sites. Approximately 20 % of the dissolved organic compounds were analyzed. Additional analyses by ultra-high-resolution mass spectrometry will explore the complexity of the missing cloud organic matter.
Elasticity curves describe streamflow sensitivity to precipitation across the entire flow distribution
Authors: Anderson Bailey J. , Brunner Manuela I. , Slater Louise J. , Dadson Simon J. 
Published: April 2024

Abstract. Streamflow elasticity is the ratio of the expected percentage change in streamflow to a 1 % change in precipitation – a simple approximation of how responsive a river is to precipitation. Typically, streamflow elasticity is estimated for average annual streamflow; however, we propose a new concept in which streamflow elasticity is estimated for multiple percentiles across the full distribution of streamflow. This “elasticity curve” can then be used to develop a more complete depiction of how streamflow responds to climate. Representing elasticity as a curve which reflects the range of responses across the distribution of streamflow within a given time period, instead of as a single-point estimate, provides a novel lens through which we can interpret hydrological behaviour. As an example, we calculate elasticity curves for 805 catchments in the United States and then cluster them according to their shape. This results in three distinct elasticity curve types which characterize the streamflow–precipitation relationship at annual and seasonal timescales. Through this, we demonstrate that elasticity estimated from the central summary of streamflow, e.g. the annual median, does not provide a complete picture of streamflow sensitivity. Further, we show that elasticity curve shape, i.e. the response of different flow percentiles relative to one another in one catchment, can be interpreted separately from between-catchment variation in the average magnitude of streamflow change associated with a 1 % change in precipitation. Finally, we find that available water storage is likely the key control which determines curve shape.
7. ĐÁNH GIÁ SỰ THAY ĐỔI KIẾN THỨC TỰ CHĂM SÓC CỦA NGƯỜI BỆNH PHỔI TẮC NGHẼN MẠN TÍNH SAU CAN THIỆP GIÁO DỤC SỨC KHỎE TẠI BỆNH VIỆN ĐA KHOA THÀNH PHỐ VINH NĂM 2023
Authors: Nguyệt Chu Thị , Hiền Võ Thị Thu 
Published: April 2024

Mục tiêu nghiên cứu: Đánh giá sự thay đổi kiến thức tự chăm sóc của người bệnh phổi tắc nghẽn mạn tính sau can thiệp giáo dục sức khỏe (GDSK) tại Khoa Nội tổng hợp Bệnh viện đa khoa Thành Phố Vinh năm 2023.
Phương pháp nghiên cứu: Nghiên cứu can thiệp có so sánh trước sau. Nghiên cứu trên 72 người bệnh phổi tắc nghẽn mạn tính đang điều trị nội trú tại khoa nội Tổng hợp Bệnh viện đa khoa Thành Phố Vinh từ tháng 5/2023 đến tháng 11/2023.
Kết quả nghiên cứu: Sau can thiệp GDSK kiến thức tự chăm sóc của người bệnh chuyển từ loại khá (93,1%) lên loại tốt (95,8%). Trong đó, kiến thức về tên bệnh trước can thiệp (54,2%) sau can thiệp (100%), kiến thức về tập thở trước can thiệp (16,7%) sau can thiệp (100%), Kiến thức về ho có kiểm soát trước can thiệp (21,3%) sau can thiệp (100%).
Kết luận: Tỷ lệ kiến thức tự chăm sóc của người bệnh trước can thiệp xếp loại khá (93,1%). Sau can thiệp (95,8%) người bệnh có kiến thức tự chăm sóc xếp loại tốt.
40. ĐẶC ĐIỂM LÂM SÀNG CỦA THAI PHỤ NHIỄM COVID-19 TẠI BỆNH VIỆN PHỤ SẢN HÀ NỘI NĂM 2021
Authors: Đạt Đỗ Tuấn , Hà Nguyễn Thị Thu 
Published: April 2024

Mục tiêu: Mô tả đặc điểm lâm sàng của thai phụ nhiễm COVID-19 điều trị tại Bệnh viện Phụ Sản Hà Nội từ tháng 12/2021 đến tháng 4/2022.
Đối tượng và phương pháp nghiên cứu: Nghiên cứu mô tả cắt ngang lấy mẫu hồi cứu dựa vào thông tin bệnh án điện tử của 1261 thai phụ nhiễm COVID-19 có tuổi thai từ 22 tuần trở lên nhập viện điều trị tại Bệnh viện Phụ Sản Hà Nội.
Kết quả: Trong thời gian từ 06/12/2021 đến 31/04/2022, có tổng số 1261 thai phụ được điều trị COVID-19 tại Bệnh viện Phụ Sản Hà Nội. Tuổi mẹ trung bình: 29,6 ± 5,1 tuổi. Thể nặng nhất của thai phụ nhiễm covid 19 khi điều trị ở mức độ nhẹ chiếm tỷ lệ cao nhất 88,7%, mức độ trung bình chiếm 7,3%, mức độ nặng chiếm 4,0% cao hơn so với thai phụ nhiễm covid 19 nhập viện (mức độ nhẹ chiếm 96,3%, mức độ trung bình chiếm 3,0%, mức độ nặng chiếm 0,7%). Đa số thai phụ vào viện có triệu chứng covid 19 với biểu hiện chủ yếu là ho, đau họng, ngạt mũi chiếm tỷ lệ lần lượt là (57,3%, 40,2%, 41,2%). Ở nhóm mức độ nặng, số mũi tiêm vắc xin càng tăng tương ứng với mức độ nặng càng giảm từ 6.3% đến 0% với p=0,000 <0.05 sự khác biệt có ý nghĩa thống kê. Ở nhóm mức độ nặng và trung bình, đái tháo đường làm tăng mức độ nặng của bệnh với p=0,016 <0,05, sự khác biệt có ý nghĩa thống kê.
Kết luận: Có mối liên quan giữa tuổi thai, số mũi tiêm vắc xin, triệu chứng lâm sàng, đái tháo đường với mức độ nặng của bệnh.
Morphology of the digestive canal of broilers under the influence of Reasil® Humic Health
Authors: Dmitriev N. O. , Salautin V. V. , Pudovkin N. A. , Salautina S. E. 
Published: April 2024

The introduction of new technologies for keeping and feeding poultry, shortening the growing time of modern poultry crosses, often lead to various stress conditions, which makes them highly sensitive to diseases of various etiologies, due to an insufficiently formed immune system. In most cases, this manifests itself in the form of gastrointestinal diseases and, as a result, an increase in poultry mortality. Currently, this problem is being solved by introducing feed additives into diets that contribute to increasing natural resistance and positively affect metabolic processes in general. One of these is the feed additive Reasil® Humic Health, which improves the condition of the digestive tract, which directly affects the acceleration of growth and development of the body, an increase in average daily weight gain, and obtaining safe meat products from broilers.The object of the study was a control and experimental group of 21-day-old Cobb-500 cross broilers, with 18,000 heads each. The broilers of the control group received the basic diet. In addition, Reasil® Humic Health feed additive at a dose of 2 g/ kg of feed was included in the main diet of the poultry of the experimental group. The selection of poultry for control slaughter at the ages of 22, 36 and 41 days, 60 individuals from each group, was carried out by random sampling. Thus, it can be concluded that Reasil® Human Health had a positive effect on the dynamics of weight and organometric parameters in broilers of the experimental group: the mass of the muscular stomach - by 11.4%, intestines - by 12% and liver - by 8% was higher compared with intact poultry.
Методологический конструкт исследования феномена государственности
Authors: Абдуллаев Магомедзапир Нурмагомедович , Сафронова Елена Викторовна 
Published: April 2024

Рассмотрена методологическая проблема дефинирования явления государственности, определено предметное поле научного исследования сущности государственности как сложного системного феномена. Разработка дефиниции «государственность» в соотношении с понятием «государство» позволяет оценивать общественные явления с различных сторон. Исследование природы и сущностных проявлений многоаспектного феномена «государственность» диктует необходимость преодоления научно-отраслевой односторонности и актуализирует привлечение междисциплинарного подхода, систематизирующего и объединяющего отраслевые, теоретические знания на более высоком и качественном уровне концептуализации. Отмечено значение определения структурных базовых единиц методологического конструкта исследования государственности, позволяющих провести историко-правовое описание ее модели в России и регионах. В этой связи подробно рассматриваются индикаторы измерения государственности и факторы, оказывающие на нее детерминирующее влияние. Авторы приходят к выводу, что современный уровень развития науки позволяет и предполагает проводить исследовательскую работу в русле методологического синтеза. Творческое сочетание универсализма, характерного для формационного подхода и цивилизационного индивидуализма в канве исторического подхода, утверждения историзма в подходе к изучению государственности и использование методов историко-сравнительного и сравнительно-правового анализа целесообразно рассматривать в качестве рационального методологического конструкта исследования российской государственности.
МОДЕЛИРОВАНИЕ СТРОИТЕЛЬНОГО ПРОИЗВОДСТВА
С УЧЕТОМ ОГРАНИЧЕНИЯ РЕСУРСОВ И ЭНЕРГОСБЕРЕЖЕНИЯ
Authors: Bayramukov Salis Khamidovich , Dolayeva Zuryat Nyuzyurovna 
Published: April 2024

В современном мире оптимальное планирование строительного производства является актуальной практической и научной задачей. Достаточно сложно наладить ресурсный баланс, требуется оперативно регулировать пространственно- временные параметры планирования строительного процесса. Предложена модель математического программирования,
позволяющая оптимизировать процесс строительного производства, которая представляет собой смешанную нелинейную математическую модель. Предлагается использовать свойства экспоненциальной функции, чтобы ее линеаризировать и преобразовать в модель линейного программирования. Разработанная математическая модель позволяет сократить продолжительность работ и возможные задержки, снизить затраты, повысить энергоэффективность и, в целом, способствует повышению надежности процесса.
Intelligent Deep Adaptive Intuitionistic Fuzzy Classifier Based Dyslexia Prediction Among Children at its Early Stage
Authors: P. J. Arul Leena Rose Vinodh M. R., 
Published: April 2024

The inability of standard linear research to clearly define the role of cognitive abilities in reading difficulties is most likely due to the fact that reading and the components that are related to reading are both part of a system of factors. There are numerous interrelated and mitigating elements that conventional statistical models are unable to deal effectively. This work aims to increase dyslexia prediction accuracy by introducing two stage non-linear methodology which incorporate both deep learning and uncertainty theory. In the first stage, the pattern of dyslexic symptoms is learned by introducing deep adaptive neural network. During the training phase, the hyperparameters weight and learning rate are optimized using a metaheuristic algorithm called the fruit fly optimization algorithm. This algorithm imitates the behavior of fruit flies to search for the best set of values. The acquired knowledge is infused in the uncertainty inference model known as intuitionistic inference classifier. Each characteristic that defines an instance as dyslexic or non-dyslexic is represented in tristate degrees to precisely address the inconsistent or vague instance which neither or nor exhibit dyslexic symptoms by introducing the hesitancy factor. The simulation results support the proposed intuitionistic fuzzy rules prominently improves the accuracy rate of dyslexia prediction compared to the other existing state of arts.
“Hybrid MAC Methodology for Improving the QOS in Fiber Wireless Network”
Authors: Hardeep Singh Saini Prabhjot Kaur, 
Published: April 2024

The Fi-Wi (Fiber-Wireless) approach stands out as a crucial element in the realm of networks, demonstrating superiority over various technologies. With the exponential growth in Internet users, significant strides have been made in the evolution of Fi-Wi networking systems in recent years. This mechanism offers broader bandwidth and network stability, ensuring high-speed connectivity with "Anytime Anywhere" availability for end users. However, the escalating energy demand in networking systems poses a constraint on the network's lifespan, impacting transmission.
Over the years, researchers have proposed and tested various Media Access Control (MAC) protocols to address transmission and energy consumption issues. Despite these efforts, existing protocols have encountered challenges such as overheating, delays, throughput issues, and collisions. This research paper introduces a combination of Time Division Multiple Access (TDMA) and Carrier Sense Multiple Access (CSMA) to tackle associated challenges. The primary objective is to enhance throughput and reduce delays in Fi-Wi networks.
To achieve this goal, the study employs techniques that involve and Utilizing an Orthogonal Frequency Division Multiplexing (OFDM) modulator, a free-space optical (FSO) communication channel, an OFDM demodulator, and Opti-system for the analysis and enhancement of received signals, our study demonstrates that the proposed MAC protocol surpasses conventional MAC protocols in terms of delay, data throughput, and transmission efficiency.