bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hepatotoxicidade do Paracetamol: uma revisão de literatura
Authors: Nascimento Naiana Pinheiro do , Santos Viviane marinho dos
Published: November 2024

Introdução: A hepatotoxicidade induzida pelo paracetamol tornou-se uma importante causa de morbidade e mortalidade, e combater esta prática cada vez mais disseminada surge como um desafio clínico significativo devido a uma série de fatores associados ao uso incorreto deste medicamento. Objetivo: Realizar uma revisão de literatura acerca da hepatotoxicidade do paracetamol, identificando os fatores associados ao seu uso inadequado. Metodologia: Foi realizado um levantamento da literatura nas seguintes bases de dados: PubMed, SCIELO (ScientificElectronic Library Online) e Periódicos CAPES. Só foram validados trabalhos no idioma português e inglês publicados durante o período de 2019 a 2024. Resultados: Foram encontrados 11 artigos relevantes, os quais abordaram sobre os efeitos hepatoprotetores de extratos vegetais naturais, efeitos hepatoprotetores de antioxidantes e agentes anti-inflamatórios, nanopartículas e sistemas avançados de entrega e novas abordagens terapêuticas com alternativas para combater a hepatotoxicidade induzida pelo paracetamol. Conclusões: Os estudos consultados sugerem que compostos naturais e novas terapias, como óleos essenciais e antioxidantes, podem prevenir a hepatotoxicidade causada pelo uso excessivo de paracetamol. Além disso, a conscientização sobre o uso racional do medicamento e a assistência farmacêutica são fundamentais para evitar a automedicação e proteger a saúde hepática.
An Approach Whose Importance is Understood More and More in Natural Disasters in Turkey: Telerehabilitation
Authors: Yılmaz Ramazan Cihad , Demirtaş Karaoba Dilan
Published: November 2024

The coronavirus disease affecting the world (COVID-19) and the Kahramanmaraş (Pazarcık and Elbistan) earthquakes that left devastating effects on many cities in Turkey have left deep traces in the lives of millions of people. These natural disasters have had a negative impact not only on financial, psychological and social life, but also on the disease management of many people with various chronic diseases. These natural disasters have made it necessary to change the daily functioning of health systems. Because, both the isolation process and the process caused by the destruction caused disruption of routine hospital visits of patients. In the aftermath of disasters, it is essential to make sustainable the rehabilitation of individuals with previous disabilities as well as individuals with new disabilities caused by the disaster. In such cases, telerehabilitation, which is considered within the scope of telehealth strategies, can be used as an effective way of applying medical resources.
A Photometric Redshift Catalogue of Galaxies from the DESI Legacy Imaging Surveys DR10
Authors: Li Changhua , Zhang Yanxia , Cui Chenzhou , Wei Shirui , Zhang Jingyi , Zhao Yongheng , Wu Xue-Bing , Tao Yihan , Li Shanshan , Wang Youfen , Kang Zihan
Published: November 2024

The large-scale measurement of galaxy redshifts holds significant importance for cosmological research, as well as for understanding the formation and evolution of galaxies. This study utilizes a known sample obtained by cross-correlating the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys DR10 galaxy catalog with various galaxy catalogs from different spectroscopic surveys. The methods Easy and Accurate Photometric Redshifts from Yale (EAZY) and CatBoost are employed to estimate redshifts. In the case of EAZY, the known sample is used solely for testing, while CatBoost utilizes it for both training and testing purposes. The known sample is categorized into different subsamples based on various classification methods. Several CatBoost regression models are trained and optimized using these subsamples. By comparing the performance of different methods and models, it is observed that the two-step and two-part models outperform the one-step model, with further enhancements achieved through the combination of the two-step and two-part models. Based on the findings from all experiments, we propose a photometric redshift estimation workflow designed to facilitate the photometric redshift measurement of all galaxies within the DESI Legacy Imaging Surveys DR10. Consequently, a photometric redshift catalog has been released, comprising a total of 1,533,107,988 galaxies. Among these, 312,960,837 galaxies have reliable redshift estimates, determined using the CatBoost algorithm, with magnitude limits set at g > 24.0, r > 23.4, and z > 22.5. For galaxies with g, r, and z magnitudes exceeding these thresholds, the photometric redshifts estimated by EAZY can be employed as a reference.
An Absolute Mass, Precise Age, and Hints of Planetary Winds for WASP-121A and b from a JWST NIRSpec Phase Curve
Authors: Sing David K. , Evans-Soma Thomas M. , Rustamkulov Zafar , Lothringer Joshua D. , Mayne Nathan J. , Schlaufman Kevin C.
Published: November 2024

We have conducted a planetary radial velocity measurement of the ultrahot Jupiter WASP-121b using JWST NIRSpec phase curve data. Our analysis reveals the Doppler shift of the planetary spectral lines across the full orbit, which shifts considerably across the detector (∼10 pixels). Using cross-correlation techniques, we have determined an overall planetary velocity amplitude of K
p = 215.7 ± 1.1 km s−1, which is in good agreement with the expected value. We have also calculated the dynamical mass for both components of the system by treating it as an eclipsing double-line spectroscopic binary, with WASP-121A having a mass of M
⋆ = 1.330 ± 0.019 M
⊙, while WASP-121b has a mass of M
p = 1.170 ± 0.043 M
Jup. These dynamical measurements are ∼3× more precise than previous estimates and do not rely on any stellar modeling assumptions that have a ∼5% systematic floor mass uncertainty. Additionally, we used stellar evolution modeling constrained with a stellar density and parallax measurement to determine a precise age for the system, found to be 1.11 ± 0.14 Gyr. Finally, we observed potential velocity differences between the two NIRSpec detectors, with NRS1 lower by 5.5 ± 2.2 km s−1. We suggest that differences can arise from day/night asymmetries in the thermal emission, which can lead to a sensitivity bias favoring the illuminated side of the planet, with planetary rotation and winds both acting to lower a measured K
P. The planet’s rotation can account for 1 km s−1 of the observed velocity difference, with 4.5 ± 2.2 km s−1 potentially attributable to vertical differences in wind speeds.
Candidates for Substellar Members of the Orion Nebula Cluster from JWST/NIRCam
∗
Authors: Luhman K. L.
Published: November 2024

In 2022, the James Webb Space Telescope (JWST) obtained 1–5 μm images of the center of the Orion Nebula Cluster (ONC). I have analyzed these data in an attempt to search for substellar members of the cluster. Using a pair of color–color diagrams, I have identified >200 brown dwarf candidates that lack spectral classifications. Some of the candidates could be protostars (either stellar or substellar) given their very red colors. Based on the age of the ONC and the photometry predicted by theoretical evolutionary models, the faintest candidates could have masses of 1–2 M
Jup. This sample of candidates may prove to be valuable for studying various aspects of young brown dwarfs, including their mass function and minimum mass. However, spectroscopy is needed to confirm the membership (via signatures of youth) and late spectral types of the candidates. Finally, I note that most of the “Jupiter-mass binary objects” that have been previously identified with these JWST images are absent from my sample of candidates because their colors are indicative of reddened background sources rather than young brown dwarfs, or their photometry is inadequate for assessing their nature because of very low signal-to-noise ratios and/or detections in only a few bands.
Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Skirvin Samuel J. , Fedun Viktor , Goossens Marcel , Silva Suzana S. A. , Verth Gary
Published: November 2024

Magnetic flux tubes in the presence of background rotational flows, known as solar vortex tubes, are abundant throughout the solar atmosphere and may act as conduits for MHD waves to transport magnetic energy to the upper solar atmosphere. We aim to investigate the Poynting flux associated with these waves within solar vortex tubes. We model a solar vortex tube as a straight magnetic flux tube with a background azimuthal velocity component. The MHD wave solutions in the equilibrium configuration of a vortex tube are obtained using the Shooting Eigensolver for SolAr Magnetohydrostatic Equilibria code and we derive an expression for the vertical component of the Poynting flux, S

z
, associated with MHD modes. In addition, we present 2D visualizations of the spatial structure of S

z
for different MHD modes under different background flow strengths. We show that S

z
increases in the presence of a background rotational flow when compared to a flux tube with no rotational flow. When the strength of the background flow is greater than 100 times the strength of the perturbation, the S

z
associated with non-axisymmetric (∣m∣ > 0) modes increases by over 1000% when compared to a magnetic flux tube in the absence of a background rotational flow. Furthermore, we present a fundamental property of solar vortices, namely that they cannot solely produce an upward Poynting flux in an untwisted tube, meaning that any observed S

z
in straight flux tubes must arise from perturbations, such as MHD waves.
Symptom Severity and Glucocorticoid Dosing in Patients With Polymyalgia Rheumatica and Obesity
Authors: Cimmino Marco A. , Crowson Cynthia S. , Dasgupta Bhaskar , Schirmer Michael , Dejaco Christian , Salvarani Carlo , Matteson Eric L. , Camellino Dario
Published: November 2024

Objective

Polymyalgia rheumatica (PMR) is an inflammatory disorder of the elderly characterized by girdle pain and stiffness. Obesity has an influence on disease activity and outcome in rheumatic diseases like osteoarthritis and rheumatoid arthritis. We aimed to investigate the relationship between high BMI and the severity and outcome of PMR, which is incompletely understood.

Methods

In a post hoc analysis, 83 patients with recent-onset PMR were studied over 6 months using clinical examination, laboratory evaluation, and girdle ultrasound (US). The modified Health Assessment Questionnaire (mHAQ), 36-item Short Form Health Survey (SF-36), and PMR visual analog scale (VAS) scores, as well as prednisone therapy data, were recorded. Patients were grouped according to their BMI.

Results

At baseline, the 12 patients with obesity had significantly more shoulder pain (P= 0.03), global pain (P= 0.03), PMR VAS (P< 0.01), and fatigue (P= 0.03); higher mHAQ (P= 0.01); and lower SF-36 physical component summary (P= 0.048) and SF-36 pain index (P< 0.001). The mean initial prednisone dose was similar among groups, but patients with obesity received a lower dose/kg (1.9 [SD 0.7] mg vs 2.2 [SD 0.7] mg;P< 0.01). At 6 months, patients with obesity were being treated with higher mean daily prednisone doses (8.5 [SD 3.2] mg/d vs 6.2 [SD 5.2] mg/d;P= 0.02), and 40% of them were receiving higher daily prednisone doses than the standard protocol compared with 14% patients without obesity (P= 0.048). Clinical features, laboratory results, and US results were similar between patients with and without obesity.

Conclusion

Obesity affects both symptom severity and prednisone utilization in patients with PMR. The reason for this may relate to different subjective pain perception rather than increased inflammation in patients with obesity. BMI should be considered when interpreting symptoms in patients with PMR and deciding their prednisone doses.
A Stratification Approach Based on Salivary Gland Ultrasonography for Assessing Secretory Function in Sjögren Disease
Authors: Huang Wenke , Hao Shaoyun , Ouyang Zhiming , Peng Liqin , Chen Xinghuan , Yang Wenjing , Zhong Wenjing , Chen Junsheng , Dai Lie , Mo Yingqian
Published: November 2024

Objective

Our aim was to develop an ultrasonographic scoring model for staging hypofunction of salivary glands (SGs) in patients with Sjögren disease (SjD).

Methods

The assessment of SG secretory hypofunction was conducted by measuring whole salivary flows. B-mode ultrasonography was performed bilaterally on the parotid and submandibular glands to quantitatively evaluate the gland score and Outcome Measures in Rheumatology (OMERACT) score. The correlation between these scores and SG secretory function in patients with SjD was analyzed, leading to the development of an ultrasonographic scoring model for staging SG hypofunction.

Results

A 1-center derivation cohort comprising 164 patients with SjD and a double-center validation cohort consisting of 107 patients with SjD were included. Both ultrasonographic scores demonstrated excellent discriminatory ability between patients with SjD with hypofunction and those with normal function (area under the curve > 0.8 for both;P< 0.001). A novel ultrasonographic scoring model revealed that low total OMERACT scores (< 5) indicated initial-stage SG hypofunction, whereas high scores (> 9) suggested end-stage hypofunction. Conversely, patients with moderate-level total OMERACT scores (5-9) required further stratification using total gland scores. The incidence of SG hypofunction among all 271 patients with SjD was found to be 18% in the initial stage, 58% in the progressive stage, and 100% in the end stage (P< 0.01). Further, the incidence of lacrimal gland involvement and hyperglobulinemia (IgG > 16 IU/mL) was significantly lower in the initial-stage patients compared to those at other stages (allP< 0.01).

Conclusion

The novel ultrasonographic scoring model incorporates precise definitions for each stage of SG hypofunction, providing a robust and clinically significant approach to stratification of SG secretory hypofunction in SjD.
Hydrocephalus-Related Dementia in Paget Disease of the Skull
Authors: Carvalho João Daniel Ferreira , Romeu José Carlos
Published: November 2024

Paget disease of bone (PDB) is a chronic skeletal disorder caused by abnormal bone remodeling. Although neurological complications are uncommon, they may arise in advanced cases, particularly with skull involvement.
La conception de l’aristo-démocratie genevoise selon Daniel Leclerc
Authors: Cuttat Romain
Published: November 2024

La notion d’aristo-démocratie qui caractérise la Genève de la première moitié du xviii e siècle s’offre comme modèle politique d’excellence pour l’oligarchie régnante. Daniel Leclerc, médecin et homme d’État mandaté en 1707 par le gouvernement pour faire face aux doléances de la bourgeoisie, propose, dans son Mémoire instructif, une structure politique pour la Parvulissime , qui, sans même recourir à l’idée d’un équilibre des pouvoirs, convie le droit naturel moderne comme mode de justification politique. Mais s’il accorde au peuple un certain nombre de prérogatives juridiques, historiquement basées sur les premières franchises, Leclerc lui ôte sitôt toute possibilité d’exercer le pouvoir au nom de la dimension représentative qu’il accorde aux magistrats dans la gestion des affaires publiques.
Entrepreneurial Empowerment
Authors: Panda Lakshmi Prasad , Rath Kali Charan , Rao N. V. Jagannadha
Published: November 2024

Business incubators help the economy of the nation through business growth. It helps to the next generation of entrepreneurs. This chapter explores how incubators help early-stage enterprises with networking, mentorship, resources, and education. It takes a look at how brooding procedures are changing, including the utilization of virtual and cross breed models, new innovation, and an emphasis on friendly impact and supportability. This chapter brings together perspectives from academia, business, and government to improve understanding of the creation of incubation system and its role in promoting development, job creation, and financial development. Practical recommendations are made to improve the manageability and viability of business visionary projects for the upcoming generation of business futurists.
Promoting Entrepreneurship Through Business Incubation
Authors: Baporikar Neeta
Published: November 2024

Many countries and institutions have established business incubators for promoting entrepreneurs and entrepreneurship development. Studies have shown that business incubators aid in enhancing entrepreneurial ecosystems worldwide. Some of the African countries have also established business incubators to promote entrepreneurial development. Adapting an exploratory approach the aim of this chapter is to review and examine to what extent business incubators have promoted entrepreneurship development with a focus on South Africa.
Business Incubators as Tools for Innovation and Growth of Entrepreneurship
Authors: Bagiyam Dhan , Irfan Mohammad , Singh Sandhya , Dias Rui
Published: November 2024

This chapter explores the process of relationships between business incubation and growth and development of entrepreneurship. The researcher has specifically focused on the provision of incubators and their dynamic support along with the financial support provided by the incubation centres for the growth of entrepreneurship. The researcher has focused on investigating the bibliometric investigation among the extracted documents and applications such as SPSS have been used to analyse the significant influence for the growth and development of entrepreneurship. To determine the most recent themes, developments, and trends in the subject, the network collaboration with the incubation centre has been provided.
Shaping the Future
Authors: Rai Anjali
Published: November 2024

Business incubation has become indispensable today as an activator of entrepreneurship and innovation, through which HRM's catalyst role is vital. Incubators offer a much-needed process of services and resources within which startups can be nurtured; HRM, on the other hand, looks into turning individuals into a world-class motivated workforce through effective management. This chapter also explains how bundling financial resources and physical tools with HRM increases the startup's success by incubating a strategic acceptance in the operation continuum to understand operational human capital. It lacks specific metrics, fails to name the market-driven reasons, and offers no insights into future-proofing a career or what technology may soon bring. Furthermore, more research on corporate culture, the role of regulatory frameworks, and the applications of HR policies are needed. This chapter aims to fill the gaps in our understanding with relevant research questions that describe how business incubation and HRM might foster innovation and growth performance.
Green Innovations
Authors: Arik Nehir
Published: November 2024

Metal nanoparticles (MNPs) have the potential to be employed in both therapeutic and diagnostic applications. Despite the plethora of techniques employed for the formulation of MNPs, it is evident that there is an urgent need to develop a non-toxic, environmentally friendly MNP formulation technology, namely plant-derived MNPs. This section reviews the formulation techniques of plant-derived MNPs, their application areas and a summary of the studies in the literature. First, comprehensive details on plant-derived MNP formulation techniques are provided. Then, literature review is made on the formulation and application areas of different plant-derived MNPs, and overview of the studies is provided. The following sections of this article examine the environmental impact, sustainability and industrial applicability potential of plant-derived MNPs in more detail, while also addressing the limitations of these techniques. Plant-derived MNPs have been a subject of significant interest among researchers and continues to be an endless potential area of research with ongoing studies.
Green Synthesis Methods for Metallic Zinc Oxide Nanoparticles
Authors: Jain Aishwarya , Bhise Kiran
Published: November 2024

This abstract provides a comprehensive guide on plant-mediated biocompatible metallic zinc oxide nanoparticles (ZnO NPs), emphasizing green synthesis methods' sustainability in nanoparticle production. It explores their characterization, applications in healthcare, agriculture, and environmental cleanup, and discusses challenges and opportunities within the scientific landscape. Green synthesis harnesses natural resources like plants and microorganisms to produce stable nanoparticles, offering non-toxic, cost-effective alternatives aligned with sustainability goals. The chapter highlights the role of plant-derived compounds, particularly polyphenols, in nanoparticle synthesis, and evaluates advanced characterization techniques and potential integration with artificial intelligence in nanobiotechnology applications. Ethical considerations for stakeholders navigating this evolving field are also addressed.
Green Nanoparticles
Authors: Somya Amita , Varshney Amit Prakash , Khan Anish
Published: November 2024

In environmental science, sustainable wastewater treatment is vital. Green nanoparticles have emerged as key tools, aligning with green chemistry and sustainable development. This chapter explores their role in advancing these processes, starting with eco-friendly synthesis methods like plant extract-mediated and biopolymer-based approaches, highlighting benefits such as reduced environmental impact, biocompatibility, and scalability. The chapter examines green nanoparticles' applications in wastewater treatment, emphasizing their superior pollutant adsorption, catalytic efficiency in advanced oxidation processes, and enhancement of membrane technologies for improved selectivity and antifouling properties. It underscores the environmental sustainability of these nanoparticles, focusing on their biodegradability, energy-efficient synthesis, and potential for reuse, while also addressing challenges like stability, toxicity, and regulatory issues, and exploring future technological advancements and prospects.
Biopolymeric Nanoparticles
Authors: Foujdar Rimpi , Ray Swati
Published: November 2024

Polymer-based nano-delivery systems do not conform to the toxicity standards and efficacy needed to act inside cells. Biopolymeric nanoparticles have biodegradability, compatibility with biological systems, and negligible toxicity, creating an edge over toxic polymers or metal nanoparticles. Besides being nanoparticles, they are naturally antibacterial and eco-friendly. Food-based matrices such as proteins and polysaccharides and complexes such as protein-polysaccharide complex and lipid-biopolymer hybrids are typically used to manufacture these nanoparticles. Manufacturing methods like nanoprecipitation, ionic gelation, microemulsion, and coacervation are discussed in this context. They are proven effective as food additives, vehicles for nutrient retention, packaging matrices, and functional food formulations. For wider application of this tool, testing in different systems to develop safe, effective, and degradable nano-delivery vehicles must be undertaken.
Effect of Nano-Fertilizer on Crop Plant Growth and Its Effect on Rhizospheric Microorganism and Its Application
Authors: Sethi Santosh Kumar , Dalei Smita Rani , Oko Augustine Okpani , Kumar Asish , Kindo Arati
Published: November 2024

Nanofertilizers represent a groundbreaking advancement in agricultural techniques, poised to transform how nutrients are delivered and managed in the interaction between plants and soil. Unique characteristics of nanoparticles facilitate improved nutrient absorption, precise delivery, and enhanced availability, potentially revolutionizing conventional fertilization methods. Numerous studies demonstrate significant enhancements in growth metrics, seed yield, and overall plant vigor following nanofertilizer application. Furthermore, plants treated with nanofertilizers exhibit heightened resilience to both biological and environmental stressors. Comparative assessments against traditional fertilizers underscore the superior efficacy of nanofertilizers while also highlighting economic and environmental considerations. The regulatory landscape is evolving in response to the rapid advancement of nanotechnology in agriculture, with ongoing research aiming to address existing gaps and shape the future trajectory of nanofertilizer utilization.
Plant Biogenic Nanoparticles as Antifungal Agents
Authors: Roy Anjali , Sharma Sharmistha , Dey Joydeb , Yadav Saurabh , Prasad Himanshu Kishore
Published: November 2024

Fungal infections, causing over 1.5 million annual deaths, are a significant global health threat prioritized by the World Health Organization. Plant-based nanoparticle synthesis provides an eco-friendly, rapid, and stable alternative to traditional methods. This chapter reviews the synthesis, characterization, antifungal applications, mechanisms, and clinical potential of biogenic nanoparticles, which interact with fungal cell walls, disrupt cellular processes, and modulate immune responses. Synergistic effects with conventional antifungal drugs and incorporation into new formulations and delivery systems enhance their therapeutic potential. However, clinical translation faces challenges related to toxicity, pharmacokinetics, and regulatory issues. This chapter offers valuable insights into advancing antifungal therapeutics using biogenic nanoparticles to combat fungal infections globally.
Advanced Instrumentation for Characterization of Nanoparticles
Authors: Napte Nutan Ankush , Saha Sujoy
Published: November 2024

Nanotechnology will emerge as the most significant technological breakthrough of the twenty-first century. The rapid development of nanotechnology has led to the creation and application of nanoparticles across various fields, including medicine, materials science, agriculture and environmental engineering. It is imperative to characterize these nanoparticles to comprehend their characteristics, actions and possible consequences. Depending on the intended usage, an array of techniques such as SEM, TEM, ZP, DLS, AFM, FTIR, etc., can be employed to examine and describe nanoparticles. Enhancing resolution, sensitivity and accuracy, these approaches are key in providing comprehensive insights into the size, shape, surface characteristics, composition and interactions of nanoparticles. The integration of these techniques allows for the comprehensive characterization of nanoparticles, aiding in the optimization of their design and application. This chapter summarizes the techniques that are commonly used along with their benefits and drawbacks.
Plant-Based Inorganic Quantum Dots
Authors: Chalke Tejas , Bodkhe Madhura , Kulkarni Sunil Jayant , Goswami Ajaygiri K.
Published: November 2024

The appearance of plant-based inorganic quantum dots (QDs) has attracted a lot of attention in the field of nanotechnology. This is because of the unique optical and electrical properties that these QDs possess. These QDs show potential in a variety of sectors, including biomedical imaging and optoelectronic devices. This growing interest may be traced back to the necessity of finding environmentally safe alternatives to traditional methodological approaches to the synthesis of quantum dots, which frequently include the use of potentially harmful chemicals. Leveraging the inherent abundance, biodegradability, and chemical variety of plants, researchers are digging into sustainable techniques for QD synthesis. The extraction of bioactive chemicals from plant sources is typically required for this process. These compounds serve a dual purpose in the creation of nanocrystals, functioning as both stabilizers and reducing agents.
Mapping the Landscape of Biogenic Nanoparticles in Bioinformatics and Nanobiotechnology
Authors: Padhiary Mrutyunjay , Roy Dipak , Dey Poulami
Published: November 2024

The relationship between biogenic nanoparticles, bioinformatics, and nanobiotechnology is investigated in this chapter, with an emphasis on the contribution of artificial intelligence to the advancement of science and technology. There are numerous applications for biological nanoparticles in agriculture, medicine, and environmental cleanup. The chapter emphasizes the significance of thorough investigation, safety concerns, adhering to regulations, and ethical considerations. It also discusses about how AI-powered techniques can be used to make, characterize, and use biogenic nanoparticles, which can lead to new insights based on data, predictive modeling, and personalized methods. Researchers can solve societal demands and promote environmental sustainability and human health by utilizing AI-driven technologies and biogenic nanoparticles through ethical innovation and interdisciplinary collaboration.
Bridging the Gap
Authors: Ravi R. , Sridevi T. P. , Nirmala Devi N. , Mandadi Sowmya
Published: November 2024

Alzheimer's Disease (AD) is a relentless neurodegenerative disorder that profoundly affects cognitive abilities. Early detection and precise tracking of AD progression are pivotal for effective intervention and management. In this study, we introduce NeuroTrackNet, an innovative machine learning (ML) algorithm that seamlessly integrates a spectrum of biomarkers to enhance the detection and monitoring of Alzheimer's Disease. By leveraging a synergistic combination of imaging, genetic, and biochemical data, NeuroTrackNet significantly elevates diagnostic accuracy and offers robust tracking of disease progression. Our comprehensive validation on a robust dataset revealed NeuroTrackNet's impressive performance, achieving an overall accuracy of 92%, sensitivity of 90%, and specificity of 94%.
Decoding Alzheimer's AI-Powered Biomarker Analysis for Diagnosis and Monitoring
Authors: Sivasundarapandian S. , Ramamurthy Chaithanya Kumar Viralam , Boya Thrjoram Naresh Reddy , Matheswaran Saravanan
Published: November 2024

Alzheimer's disease (AD) necessitates early diagnosis and monitoring for effective management. This study introduces AlzNet, an AI-powered algorithm combining convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to analyze cerebrospinal fluid (CSF) biomarkers—amyloid-beta (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau181). Leveraging data from 500 participants (200 AD, 150 mild cognitive impairment (MCI), 150 healthy controls) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), AlzNet demonstrated high accuracy (92.5%), sensitivity (90.3%), specificity (94.7%), and AUC-ROC (0.96) in differentiating between AD, MCI, and controls. Notably, it identified lower Aβ42 and elevated t-tau and p-tau181 levels as significant markers. AlzNet's non-invasive, cost-effective approach and its potential to facilitate early detection and continuous monitoring of AD underscore its clinical utility. Future research will explore its validation across diverse populations and enhance real-time monitoring capabilities.
Integrating Machine Learning in Biological Markers for Enhanced Early Detection of Alzheimer's Disease
Authors: Sriman B. , Seetha R. , Durga Devi A. , Renuka Devi S. , Rashika R. S.
Published: November 2024

Alzheimer's disease (AD) presents a significant challenge in healthcare due to its progressive nature and the absence of definitive early detection methods. Recent advancements in machine learning (ML) have shown promise in integrating with biological markers to improve the early detection of AD. This paper explores the synergistic potential of ML algorithms with various biological markers, such as genetic factors, biomarkers in cerebrospinal fluid, and neuroimaging data. The integration aims to enhance prediction accuracy and reliability in identifying individuals at high risk of developing AD before clinical symptoms manifest. Challenges including data heterogeneity, scalability of models, and ethical considerations are also discussed. By leveraging ML techniques alongside biological markers, this approach holds potential to revolutionize early detection strategies for Alzheimer's disease, ultimately facilitating timely interventions and improving patient outcomes.
Natural Language Processing of Electronic Health Records for Predicting Alzheimer's Disease
Authors: Joshi Herat
Published: November 2024

This chapter explores the use of Natural Language Processing (NLP) to analyze Electronic Health Records (EHRs) for early prediction of Alzheimer's disease. It delves into NLP techniques that enhance diagnostic accuracy by extracting insights from unstructured data within EHRs. The potential of NLP to revolutionize early detection and improve patient outcomes through precise, real-time data analysis is highlighted, emphasizing advancements in healthcare technology. The integration of NLP with EHR systems promises to advance personalized medicine, allowing for earlier interventions that can significantly alter the course of Alzheimer's disease. By enabling a deeper understanding of nuanced patient data, NLP fosters a proactive approach to healthcare that prioritizes prevention and precise treatment strategies.
Orchestrating Precision in Alzheimer's Disease Progression Forecasting
Authors: Gunanidhi G. S. G. , Rajendiran P. Selvi
Published: November 2024

This study introduces a pioneering approach to forecast Alzheimer's disease progression, blending ensemble learning methods with the harmonious synergy of XGBoost and Random Forest algorithms. Through this fusion, our ensemble model orchestrates a symphony of predictive accuracy and reliability, harnessing the boosting capabilities of XGBoost and the robust tree aggregation of Random Forest. By integrating diverse datasets and employing advanced machine learning methodologies, our research aims to provide clinicians and caregivers with nuanced insights into individualized disease trajectories. This enhanced predictive modeling facilitates personalized care and intervention planning, optimizing patient outcomes and resource allocation.
Advancing Alzheimer's Disease Detection With Big Data and Machine Learning
Authors: Mahesh S. , Ram Mohan Rao K.
Published: November 2024

Alzheimer's disease (AD) detection and diagnosis face challenges due to its complexity. This study explores the fusion of advanced machine learning algorithms and big data methods to improve detection accuracy. In addition to commonly used algorithms like Random Forest and Support Vector Machines, the study introduces Gradient Boosting Decision Trees (GBDT) for AD prediction. GBDT combines the strength of multiple weak learners to enhance predictive performance. Furthermore, the study implements big data techniques such as data parallelization and distributed computing to handle large-scale datasets efficiently. By leveraging these methods, the study achieves a significant improvement in computational efficiency, enabling timely analysis of extensive AD-related data. Results show that the GBDT algorithm outperforms traditional methods, achieving an accuracy of 85% in predicting AD onset and progression. When combined with big data techniques, the overall accuracy further increases to 88%.
Alzheimer's Disease Prediction Using InceptionResNet Integrating Deep Learning Models
Authors: Jenath M. , Lalitha Y. , Vidhyalakshmi A. M. , Ramya N. , Keerhti Latha C. V. , Matheswaran Saravanan
Published: November 2024

This research explores the application of deep learning methodologies for predicting Alzheimer's disease progression using MRI scans and clinical data. The study leverages the InceptionResNet architecture, known for its effectiveness in image classification tasks, to analyze MRI scans from a dataset.Patients diagnosed with Alzheimer's disease. The methodology involves preprocessing MRI images to enhance quality and standardize dimensions, followed by training InceptionResNet on a [mention hardware setup] platform using [mention deep learning framework]. Performance evaluation metrics including accuracy (92%), precision (89%), recall (91%), and F1-score (90%) demonstrate the model's robustness in early-stage disease detection. Comparative analysis with baseline models reveals significant improvements, affirming the efficacy of InceptionResNet in identifying Alzheimer's disease markers. Insights gained from the model contribute to understanding disease progression dynamics, highlighting its potential for clinical application in early diagnosis and intervention.
A Practical Guide to Strategic Planning in Higher Education
Authors: Kayyali Mustafa
Published: November 2024

Strategic planning is a key procedure for higher education institutions attempting to manage the complicated and continuously shifting educational landscape. This chapter offers a practical guide for planning, implementing, and assessing strategic plans within the higher education sector. It begins by identifying the core components of a strategic plan, including vision and mission statements, goals, and objectives. The importance of stakeholder involvement and collaboration is underlined as a critical aspect in establishing a successful and sustainable plan. The guide also gives insights into the practical aspects of executing and monitoring strategic initiatives, ensuring alignment with institutional goals. Finally, it discusses the evaluation of outcomes and the importance of ongoing development in sustaining the relevance and success of the strategic plan. This chapter seeks to empower educational leaders and administrators with the tools and information necessary to effectively manage their institutions toward long-term success.
Adapting to the Unpredictable and Uncertain Academic Environments
Authors: Goronga Pedzisai , Matongo Morine , Deredzai Memory
Published: November 2024

This chapter examines the critical importance of cultivating organisational resilience within academic institutions to ensure their long-term survival and success amid the unprecedented uncertainty and change facing the higher education landscape. Recognising the inadequacy of traditional planning frameworks, the chapter outlines evidence-based strategies for building adaptable and future-ready academic institutions. These include fostering resilient organisational cultures, developing dynamic capabilities, and implementing flexible operational models. By embracing the principles of organisational resilience, institutions can position themselves to not only withstand disruptive challenges, but also capitalise on emerging opportunities in the volatile, uncertain, complex, and ambiguous environment of 21st century higher education.
Development of Decision Support System to Evaluate the Performance of Turkish Universities
Authors: Ünal Ferhat , Tüfekci Aslıhan
Published: November 2024

Historically, Higher Education Institutions (HEI) shown great changed relatively, while prioritised one aim 1st and 2nd generation universities (e.g. research-oriented university of the 2nd type) at the beginning, 3rd type university is defined as multicentral information network presented scientific and technical solution to need of the society with the supra-disciplinary attitude at the education, research and innovation intersect by Professor J.G. Wissema. In this study, the University monitoring and evaluation criteria of the Turkish Council of Higher Education, which have been used in universities in Turkey since 2019 and have not been evaluated and analyzed, and which are obtained from national and international data sources, are introduced and their suitability for the functions of universities is discussed.
Diversity, Equity, and Inclusion (DEI) in Academia
Authors: Simbanegavi George , Goronga Pedzisai
Published: November 2024

Diversity, equity, and inclusion are fundamental and critical ingredients in the flourishing of any organisation as they capacitate, spur and foster genuine belongingness among diverse people because among others it promotes and sustains: epistemic representation, hermeneutical justice, genuine engagement, enriching belongingness and participation which are core in higher education dispensation for quality education and national development. It is against this backdrop that the purpose of this chapter is to explore the state of diversity, equity and inclusion in the academia. Marginalised and disadvantaged students and people find it hard to be included in the academia. Diversity, equity and inclusion were conceptualised in the context of higher education in Zimbabwe. The chapter explored the state of DEI in Zimbabwe and it was established that many problems are faced stemming from rurality, gender inequity, and epistemic injustice. Some strategies were proposed like, epistemic justice deploying Ubuntu and setting robust committees for monitoring and implementing the DEI polices
Enriching Satisfaction With Web-Based Learning (WBL) Among Higher Education Students in Thailand
Authors: Siripipatthanakul Supaprawat , Limna Pongsakorn , Phuangsuwan Penpim , Siripipattanakul Sutithep
Published: November 2024

The digital age requires WBL. Student satisfaction impacts adoption efficacy. This study evaluates Thai higher education student happiness and WBL components (communication, collaboration, creativity, and critical thinking). This quantitative study surveyed 225 Thai higher students online using convenience sampling. PLS-SEM (ADANCO Version 23) tested hypotheses and SPSS Version 27 analyzed data. Collaboration greatly affects WBL's creativity and critical thinking. Online student satisfaction is highly affected by collaboration. Communication boosts web-based learning creativity and critical thinking. Communication substantially affects student satisfaction. Creativity and critical thinking don't affect student satisfaction. Collaboration, communication, and student satisfaction depend on creativity and critical thinking. WBL may improve Thai higher education students' communication, collaboration, creativity, and critical thinking, increasing student satisfaction. Qualitative research like interviews and regional sampling may inform future studies.
Leadership in Higher Education
Authors: Salendab Fahad Abdul
Published: November 2024

This chapter explores the multifaceted nature of leadership inside higher education institutions, emphasizing its crucial position as a pillar of educational achievement and institutional effectiveness. It begins by defining the essence of effective leadership and its foundational importance in shaping academic environments. The chapter then examines numerous leadership styles, including transformational, transactional, servant, distributed, and adaptive management, and their respective influence on higher education. Building on this foundation, the chapter outlines critical components of effective management in academia, inclusive of visionary leadership, effective communication, empowerment and collaboration, innovation and adaptability, promoting diversity and inclusivity, and financial management. It proposes techniques for reinforcing leadership in higher education, such as fostering leadership diversity, promoting professional development, enhancing leadership resilience, and integrating technology.
Leadership Styles and Their Impact on Organizational Effectiveness in Academia
Authors: Brown Santarvis
Published: November 2024

Few elements have as significant an impact on organizational effectiveness as experienced leadership. This chapter looks at some of the most effective leadership styles in academia and explores how each of them shapes faculty engagement, informs decision-making and problem-solving, and, ultimately, leads to improved student outcomes. More specifically, it examines transformational, transactional, servant, and distributed leadership in higher education through the lens of real-world examples to showcase the successes and challenges associated with each. This chapter is designed to provide academic leaders with valuable insights into the ways various leadership approaches affect overall organizational effectiveness and health. By building a comprehensive understanding of leadership styles in academia, this text aids in driving organizational success, adaptability, and long-term sustainability in the ever-evolving landscape of higher education.
Promoting Diversity, Equity, and Inclusion
Authors: Samuel Humphrey Sam , Etim Emmanuel Edet , Nweke-Maraizu Ugo , Shinggu John Paul
Published: November 2024

In contemporary world, fostering diversity, equity, and inclusion (DEI) has become a major concern for organizations across various sectors. Inclusion, diversity, and equity acknowledge that individuals have varying backgrounds and might require particular resources to realize their full potential. This chapter delves into effective strategies to cultivate a DEI-centric environment, focusing on building organizational capacity and fostering a sense of belonging among all employees. The chapter highlights the pivotal role of leadership commitment in driving DEI efforts. Top-level support is essential in creating a culture where diversity is valued, and inclusion is a priority. Additionally, the study emphasizes the importance of cultural competency training for all employees. Employee Resource Groups (ERGs) emerge as powerful tools for fostering belonging and advocacy. These groups provide spaces for marginalized employees to connect, share experiences, and advocate for their needs. The chapter underscores the need for inclusive policies and practices.
Strategic Management of Online Higher Education Institutions
Authors: Okpala Peterchris
Published: November 2024

Significant changes have been transforming the educational landscape, enormously complicating the management and leadership of higher education institutions. For instance, our technology-driven society has led to the successful establishment of online higher education institutions (OHEIs) to fulfill the educational needs of modern learners. Indeed, OHEIs have rapidly grown in size and reach to deliver education to international students. Moreover, increasing stakeholder demands for knowledge production, value creation, and excellent education have exerted excessive pressure on OHEI leaders to be strategically positioned to seize opportunities to fulfill these demands. A considerable body of literature is currently dedicated to the strategic management of higher education institutions, although less attention is given to the strategic management of OHEIs. Notably, academia has long-held traditions about management and leadership that hark back to centuries of practice. This chapter aims to explore strategic management as applied to OHEIs.
The Relationship Between Organizational Culture and Academic Staff Performance in Universities in Zimbabwe
Authors: Muchowe Regis Misheal , Mubango Hazel
Published: November 2024

Organizational culture has been overlooked as a necessary ingredient to employee performance. Studies on organizational performance have focused on different contexts, such as the mining, retail, and hospitality industries. The study is guided by the following objective of the investigation, which will seek to establish the relationship between academic staff performance and four dimensions of Hofstede's theory: power distance, masculinity, uncertainty avoidance, and individualism. The hypotheses were developed around the four dimensions. Various scholars have tested and proved these four dimensions to represent organizational culture. What other scholars have failed to do is to test these dimensions in the academic context. The investigation used quantitative methodologies. Three hundred eighty-five questionnaires were distributed through Google Forms. The study found a negative relationship between organizational culture indicators and academic staff performance. The study emphasizes that organizations should encourage collective culture.