bluuebunny/crossref_metadata_2025 huggingface dataset:
Forces in the engagement of planetary-pinion gear with satellite having eccentricity
Authors:   Penza State University, A. Tchufistov Evgeniy , E. Tchufistov Oleg ,   Penza State Technological University
Published: February 2025

Background. The forces acting in the engagement of the gear affect the resource of the engagement itself and the satellite supports. The number of factors on which the load distribution in the engagement depends is very large, including modification of tooth profiles, manufacturing inaccuracy of the gear and a change in the relative position of the satellite, the pinwheel and the output shaft during its operation. The existing methods of static gear calculation do not fully take into account this influence. The purpose of the study is to improve the static analysis of gear and increase the accuracy of calculation. Materials and methods. In this work, the displacements in the contact pairs of engagement are determined using the method of kinematic analysis. Next, classical Hertzian contact mechanics is used to determine the elasticity characteristics. The forces in the engagement are calculated using an iterative procedure for analyzing the state of the contacts. To obtain quantitative characteristics, computer modeling in the Mathcad system was used. Results. A mathematical model, algorithm and program for calculating the forces arising in the planetary-pinion gear with modification of the satellite teeth profile and satellite eccentricity have been created. Calculations are performed and it is shown how, in this case, the forces in the contact pairs change in the gear. Conclusions. The proposed solution makes it possible to take into account the combined influence of a uniform modification of the tooth profiles and the eccentricity of the satellite on the loads in the engagement. Research has shown that eccentricity can significantly change the load pattern of the gear engagement, which must be taken into account in engineering calculation.
New methodology for designing tension joints using strengthening technology
Authors:   Penza State University, I. Voyachek Igor , V. Kochetkov Denis ,   Penza State University, D. Tarkhanov Andrey ,   Penza State University, V. Istomina Yuliya ,   Penza State University
Published: February 2025

Background. The generally accepted design methodology for tension joints uses the method of complete interchangeability or the probability-theoretical method. When implementing these methods, the vast majority of connections in a batch have a significantly excess safety factor, which leads to additional costs. The possibility of strengthening joints during assembly, for example, by using anaerobic materials, allows for a different, more rational approach to their design. Materials and methods. The proposed method is based on the assumption that a certain (specified) part of a batch of compounds will be strengthened by using anaerobic materials, since it cannot transfer the operational load with the designated safety margin. A probabilistic approach is used. Normal and uniform distributions of part sizes in a batch are considered. Results. The theoretical substantiation of the new method and confirmation of its effectiveness in computer modeling of the manufacturing process of a batch of tension joints are presented. Conclusions. The technique allows to significantly reduce the level of tension in the connection and assign wider tolerances to the dimensions of the mating parts without losing functional properties.
Nonparametric regression models for time series analysis and forecasting
Authors:   Head of Zarechny of Penza region, V. Kostin Aleksey , P. Makarychev Petr ,   Penza State Univesity
Published: February 2025

Background. Regression analysis is a type of machine learning. With the application of regression analysis, the problems of structural-parametric identification, and predicting the behavior of systems and objects are solved. Regression models constructed using observed data at finite time intervals are time series models. The purpose of the study, the results of which are presented in the article, is to develop non-parametric regression models for the analysis and forecasting of fires, tragic events on the water, accidents on water pipes, road traffic accidents in the region. Materials and methods. Analysis and forecasting of time series levels reflecting emergencies and events in the region, by machine learning using nonparametric regression models based on linear and nonlinear functions of activation of artificial neurons. Results.The analysis and prediction of the time series levels are set and solved. Content of the problem: analysis of the stagnation of the
time series; elimination of random emissions; allocation of the piece-line trend; development of non-parametric models of machine learning; performance of a omputational experiment and evaluation of the quality of forecasting. Conclusions. The results of the computational experiments confirmed the prospects of applying the machine learning method using nonparametric regression models based on Fourier functions, piecelinear and nonlinear functions.
Album of artificial neurons with piecewise linear excitation functions tuned to predict the probabilities of their own errors
Authors:   Penza State University, I. Volchikhin Vladimir , I. Ivanov Aleksandr ,   Penza Scientific Research Electrotechnical Institute, V. Bezyaev Aleksandr ,   Penza State University, A. Filipov Ivan ,   Penza State University
Published: February 2025

Background. Currently, single-layer networks of artificial neurons are used, which are equivalent to classical statistical criteria. The purpose of the work is to move to more complex algorithms for using multilayer networks of artificial neurons. Materials and methods. Replacing classical statistical criteria with their equivalent binary neurons provides significant redundancy of the output code of the neural network, which isconvolved with error elimination. The mechanism of convolution of code redundancy can be improved if the most informative part of the neuron response is not quantized. For this purpose, it is proposed to use artificial neurons with piecewise linear excitation functions. Results. It is shown that the linear part of the excitation function is easily adjusted so as to predict the probability of errors of each of the used neurocriteria. This ultimately allows moving from single-layer networks of binary artificial neurons to two-layer networks. Examples of adjusting the functions of piecewise linear excitation for 7 artificial neurons are given
Multiletramentos no ensino de língua inglesa: uma intervenção pedagógica na escola pública de ensino médio
Authors:   , Mendes Eliziane de Sousa Sampaio
Published: February 2025

O ensino da Língua Inglesa tem passado por modificações significativas a fim de suprir as necessidades que surgem com o avanço das tecnologias e da globalização nos últimos anos. Nesta pesquisa, objetivando abordar o ensino da Língua Estrangeira Moderna, apresentamos uma proposta de intervenção pedagógica fundamentada na teoria dos multiletramentos - que incorporam ao seu conceito tanto a multimodalidade como a multiculturalidade, presentes nas mais diversas formas de interações sociais - e da aprendizagem por design (THE NEW LONDON GROUP, 1996; COPE; KALANTZIS, 2009). A proposta de ensino está estruturada de acordo com os processos de conhecimentos da aprendizagem por design, contemplando a resolução de quatro atividades realizadas pelo aplicativo WhatsApp, que atuou tanto como suporte para a postagem das respostas, quanto meio de interação dos participantes. A proposta foi elaborada em consonância com as habilidades e competências regulamentadas na Base Nacional Comum Curricular e direcionada a alunos da primeira série do Ensino Médio, com baixo desempenho nos primeiros bimestres do ano letivo de 2019, na disciplina de Língua Inglesa. A avaliação da intervenção se estabelece por meio da análise das interações realizadas no WhatsApp, da resolução das atividades e de questionário de avaliação da intervenção, realizado com os alunos ao final da intervenção. Diante das exigências do mundo moderno quanto às práticas dos multiletramentos, acreditamos que a presente pesquisa possa contribuir para um ensino de Língua Inglesa que atenda às necessidades sociais de comunicação e que capacite os alunos a utilizarem os recursos midiáticos em função da aprendizagem crítica e consciente
Institucionalização da UERN a partir das fontes imagéticas e registro de memória
Authors:   , Soares Gislânia Dias
Published: February 2025

A dissertação Institucionalização da UERN a partir das fontes imagéticas e registro de memória explana a criação da primeira instituição de ensino superior na cidade de Mossoró que se constituiu e se consolidou como uma universidade pública e gratuita. Para atender a finalidade da pesquisa, elegemos como fontes os acervos documentais existentes na UERN (documentos escritos oficiais e fotografias) e uma entrevista semiestruturada. Trata-se de uma pesquisa de cunho qualitativo, bibliográfico e documental. À vista disso, o interesse dessa pesquisa foi cercar-se da UERN, gravitar em torno de sua historicidade, investigar os vestígios de sua institucionalização através dos registros imagéticos e de memória. Os resultados nos mostraram que foi possível delinear a institucionalização da UERN por meio das fontes imagéticas e registro de memória. As imagens falaram, comunicaram e descreveram, e a oralidade, por sua vez, se mostrou uma fonte rica de pesquisa, oportunizando a rememoração e perpetuação do vivido, configurando, juntas, uma história própria sobre essa institucionalização da UERN
Bibliometric Analysis of Research on Traditional Chinese Medicine Treatment of Myocardial Infarction from 2007 to 2024 Based on the Web of Science Database
Authors: Lan Qi , Wu Hao , Chen Ming-Tai , Xue Jin-Yi , Mazhar Maryam , Deng Zi-Wen , Zou Yuan , Liu Ping , Luo Gang , Dong Li , Liu Meng-Nan
Published: February 2025

Background:

Myocardial infarction (MI) is a common critical syndrome in
the late development of cardiovascular diseases (CVDs), and traditional Chinese
Medicine (TCM) treatment has become an essential branch in this field.

Objective:

This study aimed to use bibliometric methods to examine the research trajectory
of TCM treatment of MI from 2007 to 2024 from a multidimensional perspective
and analyse its characteristics, hotspots, and frontiers.

Methods:

This study used the search formula TS OR TI OR AB OR A (“traditional Chinese
medicine” or “Chinese medicine” or “TCM” or “traditional medicine, Chinese” or
” Chinese traditional medicine” or “Chinese medicine, traditional”) AND TS OR TI OR
AB OR AK (“myocardial infarction” or “myocardial infarctions” or ” infarction, myocardial”
or “infarctions, myocardial” or “myocardial infarct” or “MI”) to find the Web of
Science Core Collection (WOSCC) of relevant studies from 01/01/2007 to 04/29/2024.
Target literature records were analysed and graphed using CiteSpace, VOSviewer, and
Scimago Graphica.

Results:

A total of 754 records were obtained and 399 records were finally retained after
screening. Countries, institutions, authors, and journals were visually analyzed. The current
research hotspots and frontiers included Salvia miltiorrhiza, ischemia-reperfusion injury,
pathway, molecular docking, and network pharmacology.

Conclusion:

This research study would enrich the researchers' understanding of the existing
research methodology and future development trends and provide a more efficient
research methodology for the research on the mechanism of action of TCM for the treatment
of MI and its clinical trials.
Protective Effect of Curcumin on Metabolic Syndrome Components through the Microbiota
Authors: Vafaeie Farzane , Farkhondeh Tahereh , Samarghandian Saeed , Miri-Moghaddam Ebrahim
Published: February 2025

Curcumin, a natural polyphenolic compound found in turmeric, has garnered
increasing research interest due to its potential health benefits, particularly in the context
of the rising global prevalence of metabolic syndrome (MetS). With MetS affecting a
significant portion of the global population and serving as a precursor to chronic diseases,
such as type 2 diabetes and cardiovascular diseases, identifying effective, accessible,
and safe interventions has become a critical public health priority. This review explores
curcumin’s role in regulating gut microbiota composition, enhancing intestinal barrier
function, and reducing inflammation, which can collectively improve key components
of MetS, such as hyperglycemia, dyslipidemia, obesity, and hypertension. Supplementation
with curcumin has shown promising results in improving metabolic health by promoting
the production of short-chain fatty acids (SCFAs), such as butyric and propionic
acids. These effects may protect against dyslipidemia and reduce the risk of chronic conditions.
Furthermore, curcumin has demonstrated potential in reducing hypertension
through various mechanisms, including inflammation reduction, modulation of
lipopolysaccharide (LPS) production, activation of G-protein-coupled receptor 43 (GPR43),
and increased levels of SCFAs. Given the significant public health implications
of MetS, understanding curcumin's impact on gut microbiota presents an opportunity for
developing novel therapeutic strategies that address this urgent health challenge. Despite
its promise, further research is necessary to fully comprehend the underlying mechanisms
involved. Additionally, determining the optimal dosage and duration of curcumin
supplementation for achieving its effects on metabolic syndrome is crucial for future
therapeutic applications. This review highlights curcumin's potential as a natural
compound with multifaceted health benefits, particularly in the context of metabolic syndrome
and its associated complications, emphasizing the pressing need for clinical
studies to validate findings and inform evidence-based therapeutic applications.
Research on Precision Medicine AI Algorithm for Neuro Immune Gastrointestinal Diseases based on Quantum Biochemistry and Computational Cancer Genetics
Authors: Li Liangyu , Li Bingyao , Wang Guangwen , Li Siyi , Li Xudong , Santos Javier , González Ana María , Guo Lizhong , Tu Yanyang , Qin Yi
Published: February 2025

Objective:

The objective of this study is to conduct network toxicology analysis
based on smoking habits and develop a simpler and more effective toxicology product ingestion
control system.

Background:

Smoking behavior can affect the pathogenesis and prognosis of neuroimmune
gastrointestinal diseases.

Aims:

The purpose of developing tools to assist clinical practice is to avoid the harm of cigarettes
to the human body.

Methods:

Molecular dynamics method was used to elucidate the biophysical mechanism of
TP53 gene mutation caused by harmful ingredients, and the signaling pathway of midbrain edge
excitation was determined by molecular dynamics of nicotine and dopamine receptor D3. The
possible involvement of nicotine in neuronal damage was determined through the molecular
interaction between nicotine and ACHE. Molecular pathways were analyzed based on the
aforementioned biological principles, developed artificial intelligence systems and brain computer
interface systems.

result:

Several molecular mechanisms were elaborated and effective AI algorithms were developed.

Results:

Several signaling pathways were elucidated, and effective AI algorithms were developed.

Conclusion:

The accuracy of artificial intelligence systems is over 70%. This study provides
clinical doctors with a new precision medicine strategy and tool to regulate patient behavior and
reduce disease risk.

Other:

This project was approved by the Ethics Committee of Chifeng Cancer Hospital and reported
to the WHO.
Targeting of Ykl-40 as a Protumor in Personalized Medicine: A New Dimension in Disease Understanding
Authors: Moustafa Hebatallah Ahmed Mohamed , Sohaib Ahmed Umer , Saleem Iqra , Ullah Asmat
Published: February 2025

Background:

Individualization of the therapeutic plan for cancer patients is the essence
of modern clinical practice. Standard cancer diagnostic and prognostic factors are invasive, and
their value for the stratification of cancer patients with a higher risk of local or distant recurrence
is limited. YKL-40 is a protumor glycoprotein linked to the immunosuppressive tumor in a microenvironment
and an important biomarker of cell activation, proliferation, and migration.

Objective:

The objective is to update the review, and molecular and clinical research should investigate
novel modalities of targeting this glycoprotein for cancer treatment.

Methodology:

Relevant studies published in the English language were identified by searching
PubMed, Google Scholar, and MEDLINE from January 2000 to December 2023. Published
studies that specifically elicited the role of YKL-40 as a biomarker in different types of tumors
were included.

Results:

YKL-40 cancer prognostic effect was reported in various cancer types.

Conclusion:

Since antibodies against YKL-40 can inhibit tumor angiogenesis and cancer progression,
it can be suggested as an attractive candidate for chemical cancer therapy and immunomodulation.
Assessing the Impact of Artificial Intelligence Applications on Diagnostic Accuracy in Saudi Arabian Healthcare: A Systematic Review
Authors: Alqurashi Moutaz Abdulrahman , Alshagrawi Salah
Published: February 2025

Background

Artificial intelligence (AI) has become a disruptive force with great potential to revolutionize healthcare. The integration of artificial intelligence in healthcare practices and its use in areas, such as the detection and diagnosis of diseases, has led to an increased interest in this topic, which has been key in informing this research study to determine its effect on diagnostic accuracy. However, the impact of AI on healthcare diagnostic accuracy, particularly in the context of Saudi Arabia, remains an underexplored area of research.

Aim

This systematic review sought to address this gap by analyzing the effect of AI applications' diagnostic accuracy in Saudi Arabia's healthcare.

Methods

The study employed a structured and systematic search strategy in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Three databases were used to identify the articles, including PubMed, Embase, and CINAHL. The search for relevant articles linked to the impact of AI applications on diagnostic accuracy in the KSA healthcare sector was narrowed down to articles published between 2013 and 2023. This step generated 450 articles, which were further evaluated based on the inclusion criteria of the study to narrow down to 12 articles for analysis.

Results

11 out of 12 studies were conducted between 2020 and 2023, indicating that the last three years have witnessed the largest number of studies on artificial intelligence. The included studies were conducted in KSA and within different hospitals. The studies included 7 cross-sectional studies, 3 observational studies (1 retrospective study), 1 experimental study, and 1 randomized controlled trial (RCT). They all showed that the use of AI has been increasing in healthcare, and its use is enhancing the overall healthcare outcomes and is helpful in a wide variety of diseases and conditions, including chronic diseases.

Conclusion

The models have shown that the use of AI is capable of enhancing diagnostics and treatment quality, which can be essential in planning for preventing care in line with Vision 2030. Hence, the findings of this systematic review can contribute to a better understanding of the role of AI applications in diagnostic accuracy within Saudi Arabia's healthcare and offer insights applicable to regions facing similar challenges.

PROSPERO Registration Number

611347
The Study on Innovative Development of the Elderly Care Industry under the Community-based Elderly Care Model Based on the SERVQUAL Model
Authors: Feng Guanzhou , Li Quanlin
Published: February 2025

Background

China's rapidly aging population has highlighted the importance of community-based elderly care, particularly in urban areas like Shanghai, as traditional family-based care declines due to urbanization, smaller families, and shifting dynamics. Community care models provide scalable solutions to address the healthcare and social needs of elderly individuals while fostering innovation in service delivery.

Objective

This study investigates how the quality of community-based elderly care services influences elderly satisfaction and drives innovation within the elderly care industry. Using the SERVQUAL model, it explores the impact of service dimensions—reliability, responsiveness, assurance, empathy, and tangibles—on satisfaction and their role in promoting new care models and technologies.

Methods

The study surveyed 622 residents in Shanghai and analyzed the data with Structural Equation Modeling (SEM). It assessed the relationships between the five service quality dimensions, satisfaction, and innovation in elderly care, offering insights into how these factors interact.

Results

Reliability (β = 0.42), responsiveness (β = 0.35), assurance (β = 0.28), and empathy (β = 0.33) significantly enhance elderly satisfaction, which mediates their impact on innovation. Tangibles (β = 0.09) had minimal influence, suggesting emotional and relational factors are more important than physical care environments. Satisfaction was a key driver of innovation, encouraging the adoption of personalized and technology-driven care models.

Conclusion

High-quality services that improve elderly satisfaction are essential for boosting industry innovative. Smart technology, telemedicine, and remote health monitoring are critical for addressing the challenges of China’s aging population, closing service gaps, and creating responsive and efficient care systems.
Enzymes and Alzheimer's Disease: Pioneering Drug Development Strategies
Authors: Godwa Tejas , Dubey Sonal , Tiwari Prashant
Published: February 2025

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by
cognitive decline, memory loss, and functional impairment. Despite extensive research, effective
treatments remain elusive, highlighting the need for innovative therapeutic approaches. This review
article explores enzymatic targets and drug development strategies aimed at combating AD. Key
enzymatic targets include beta-secretase (BACE1), gamma-secretase, and tau protein kinases, all of
which play critical roles in the pathogenesis of AD. BACE1 and gamma-secretase are involved in
the production of amyloid-beta (Aβ) peptides, whose aggregation forms the hallmark amyloid
plaques in AD brains. Inhibitors targeting these enzymes aim to reduce Aβ production and accumulation.
Tau protein kinases, such as glycogen synthase kinase-3 (GSK-3) and cyclin-dependent kinase
5 (CDK5), are implicated in tau hyperphosphorylation and subsequent neurofibrillary tangle
formation. Modulating these kinases offers the potential for reducing tau pathology. The review further
discusses various drug development strategies, including small-molecule inhibitors, monoclonal
antibodies, and gene therapy. Small molecule inhibitors, such as BACE1 and gamma-secretase
inhibitors, have shown promise in preclinical studies but face challenges related to specificity and
side effects. Monoclonal antibodies targeting Aβ and tau provide an alternative approach, with several
candidates currently undergoing clinical trials. Gene therapy represents a cutting-edge strategy
aiming to correct or modulate disease-causing genetic mutations. In summary, targeting enzymatic
pathways involved in AD pathogenesis offers a promising avenue for drug development. While significant
challenges remain, ongoing research and clinical trials continue to advance our understanding
and potential treatment options for this debilitating disease.
Fabrication and Optimization of Regorafenib-loaded Solid Lipid Nano Carrier Using Box Behnken Design: In Vitro and Ex Vivo Intra-nasal Permeation Study
Authors: Padhi Priyanka , Kar Nihar Ranjan
Published: February 2025

Background:

Over the last ten years, there has been little clinical progress in the treatment of glioblastoma, partially because there are no efficient drug delivery techniques that can pass across the blood-brain-tumor-barrier.

Objective:

The present study deals with the development optimization of Regorafenib-loaded Solid lipid na-noparticle(RF-SLN) for intranasal delivery of Regorafenib.

Method:

A Box-Behnken Design was employed to develop and optimize seventeen formulations using the solvent evaporation method, followed by ultrasonication. Each formulation was characterized in terms of particle size, entrapment efficiency (EE%), and zeta potential. The optimized SLN formulation was then con-verted into an in situ gel and assessed for intranasal ex vivo permeation.

Results:

The optimized formulation showed a particle size of 190.1nm, EE% of 81.3%, and zeta potential of -23.8 mV. The optimized Regorafenib-SLN in-situ gel showed enhanced drug permeability as compared to the Regorafenib-in-situ gel.

Conclusion:

It can be concluded that an SLN-based nanocarrier system can be successfully applied for the intranasal delivery of Regorafenib targeting to the brain.
A Study on Privacy Preserving Techniques in Fog Computing: Issues, Challenges, and Solutions
Authors: Banu Sabitha , Mohammed Isbudeen Noor , Ahmad Shabir , Gheisari Mehdi
Published: February 2025

Privacy plays a substantial role in both public and private, databases especially in
the healthcare industry and government sectors require a high-confidential data transmission
process. Most often, these data contain personal information that must be concealed throughout
data processing and transmission between terminal devices and cloud data centers, such as
username, ID, account information, and a few more sensitive details. Recently, fog computing
highly utilized for such data transmission, storing, and network interconnection processes due
to its low latency, mobility, reduced computational cost, position awareness, data localization,
and geographical distribution. It delivers to cloud computing and the widespread positioning of
IoT applications. Since fog-based service is provided to the massive-scale end-end users by fog
server/node, privacy is a foremost concern for fog computing. Fog computing poses several
challenges if it comes to delivering protected data transfer; making the development of privacy
preservation strategies particularly desirable. This paper exhibits a systematical literature review
(SLR) on privacy preservation methods developed for fog computing in terms of issues,
challenges, and various solutions. The main objective of this paper is to categorize the existing
privacy-related research methods and solutions that have been published between 2012 and
2022 using analytical and statistical methods. The next step is to present specific practical issues
in this area. Depending on the issues, the merits and drawbacks of each suggested fog security
method are explored, and some suggestions are made for how to tackle the privacy concerns
with fog computing. To build, deploy, and maintain fog systems, several imminent motivational
directions and open concerns in this topic were presented.
Exploring Generative AI Applications in Combating COVID-19
Authors: M.A Jabbar , Tasneem Rayeesa , Farhat Shaista
Published: February 2025

The COVID-19 pandemic has reshaped the world, causing widespread health crises, economic
disruption, and some serious social changes. The initial outbreak in Wuhan saw a rapid escalation
in cases, leading Chinese authorities to enforce stringent lockdown measures. Traditional testing
methods for COVID-19 are time-consuming and can be costly, often taking hours or days to
yield results. To overcome these challenges, researchers have developed automated systems employing
various Artificial Intelligence (AI) techniques to detect coronavirus infections. Over the previous
decade, the integration of AI with medical imaging has revolutionized multiple industries, particularly
healthcare, by improving the diagnosis and treatment of numerous conditions. Generative AI and
Generative Adversarial Networks (GANs) play a significant role in detecting and managing COVID-
19 through various innovative applications. This paper draws attention to the applications of generative
AI systems for COVID-19 detection, highlighting their potential to enhance testing efficiency
and accuracy.
Enhancing GNSS Signal Integrity in Medical Logistics: A Deep Learning Solution
Authors: Ar-Reyouchi El Miloud , Chabel Saâdia
Published: February 2025

Introduction:

Ensuring the integrity of Global Navigation Satellite System (GNSS) signals
is critical for the timely and accurate delivery of pharmaceuticals within smart medical supply
chain logistics (SMSCL).

Method:

In this study, we propose a novel deep learning (DL) framework that integrates a Bidirectional
Long Short-Term Memory (BiLSTM)-Attention model with Principal Component Analysis
(PCA) and Bayesian Optimization (BO) for feature selection. This approach enhances GNSS signal
reliability by accurately detecting anomalies, especially in environments prone to interference. The
PCA-BO feature selection process optimizes relevant features like signal strength and Doppler shifts,
improving model performance while reducing overfitting.

Result:

Our results demonstrate that the proposed model significantly outperforms conventional
methods, enhancing the precision of pharmaceutical deliveries in critical healthcare settings.

Conclusion:

This work represents a key advancement in using DL to ensure GNSS signal integrity
for SMSCL, contributing to more efficient and secure logistics operations.

conclusion:

The advanced DL approach significantly improves GNSS signal integrity, ensuring reliable and timely delivery of critical medical supplies. These findings suggest that integrating deep learning with feature selection algorithms can enhance the robustness of GNSS applications in medical logistics.

other:

This article extends its impact beyond medical logistics by offering several key contributions. The deep learning approach is applicable across industries like autonomous vehicles and aviation, where GNSS reliability is vital. The PCA-BO method provides an innovative solution for high-dimensional data analysis and is useful in various machine-learning tasks. Additionally, the model improves GNSS resilience against jamming and spoofing, which is crucial for navigation security. Its adaptability across dynamic and static scenarios underscores its scalability. Furthermore, the research advances logistics innovation, demonstrating how deep learning can enhance efficiency and reliability in critical supply chains.
Etiology and Pathogenesis of Caries and Gingivitis in Young People. Prevention and Medicinal Treatment in the Complex Therapy of Caries and Gingivitis
Authors: Dombrovych Sofiia , Rozhko Mykola , Tarnavska Liliia , Dmytryshyn Tetiana , Dombrovych Viktor , Rozhko Olena , Kovalyshyn Khrystyna
Published: February 2025

The prevalence of periodontal diseases is extremely high, and in recent decades its significant increase in young people has been noted, and a more aggressive course of periodontal diseases has been identified. The development and progression of periodontal disease and caries in younger individuals exhibit distinctive peculiarities. Today, special attention is paid to the condition of microbiocenosis in the oral cavity, which can be both a consequence of various diseases and a contributing factor in the exacerbation and aggravation of dental diseases such as caries, gingivitis, periodontitis, stomatitis and others. The oral microflora is a highly sensitive indicator system that responds with qualitative and quantitative shifts to changes in the state of various organs and systems of the body, and requires further study. The control of dental plaque also serves to reduce gingivitis, which, in turn, helps to prevent the development of periodontitis in later life. Good oral hygiene, primarily through effective tooth brushing, reduces plaque and is crucial for the prevention of caries. Good oral hygiene habits, formed at an early age, thus help to lay the foundation for maintaining dental health. Oral hygiene with antimicrobial and remineralizing agents, in addition to the mechanical plaque removal, could be used to treat and prevent dental diseases.
Maribavir for Management of Cytomegalovirus in Lung Transplant Recipients: A Case Series and Literature Review
Authors: Kozuch Jade M , Afshar Kamyar , Feist Ashley
Published: February 2025

Lung transplant recipients represent a high-risk group for cytomegalovirus (CMV) infection and disease, even among solid organ transplant (SOT) recipients, due to multiple factors. Additionally, CMV has significant consequences in this group including pneumonitis, acute rejection, and chronic lung allograft dysfunction. For the past two plus decades, treatment of CMV in SOT recipients has been limited to off-label use of 4 antiviral medications associated with significant toxicities including myelosuppression and nephrotoxicity. In November 2021, maribavir became the first antiviral agent approved by the United States Food and Drug Administration for the treatment of resistant or refractory CMV in transplant recipients. Herein, we present two reports of the successful use of maribavir at our center along with a review the evidence for maribavir for CMV management in lung transplant recipients.
From data to decisions: the vital role of digital epidemiology for strengthening public health (Preprint)
Authors: Hussain Syed Shah Areeb , Pushpa R. , Sharma Amit , Yadav C. P.
Published: February 2025

UNSTRUCTURED

The academic landscape has witnessed an overwhelming surge in published research, with over 64 million scholarly articles added since 1996 and a growth rate of over 22% in the last five years (2018-2022). This rapid expansion of data represents a vast repository of knowledge, yet it also poses significant challenges in synthesizing and extracting meaningful insights. Traditional methods like systematic reviews, while valuable, often capture only a fraction of the available information due to methodological constraints. In contrast, the rise of digital tools such as interactive dashboards offers a more dynamic and comprehensive approach to data integration. These tools enable the visualization, analysis, and dissemination of large datasets in an accessible format, expanding their reach and utility. Digital epidemiology, by leveraging such advancements, is poised to transform medical research, offering innovative solutions for data synthesis and contributing to more informed, evidence-based outcomes in healthcare.
Farming While Aging: Reasons and Strategies for Maintaining Family Farming in Parbotihan Village, North Sumatera
Authors: Marbun Firdaus
Published: February 2025

One of the challenges for farming sustainability and food security into the future is the aging of farmers. The reluctance of youth to work in farming and their choice to migrate to urban areas has resulted in a scarcity of productive workers in rural areas. As a result, farming production relies on aging farmers. The implications of this condition not only have an impact on decreasing farming productivity but also to the family farming sustainability and threats of food security in the future. Apart from the impact on decreased production, it is important to see how aging farmers overcome their limited capabilities by rely on farming as a source of their daily needs. This research aimed to explain the impact of migration of rural youth for family farming’s sustainability and what strategies that aging farmer carried out to maintain their farm when they become the main actors in farming. This research was conducted on rice farmers in the village of Parbotihan, North Sumatra using qualitative methods and data collection techniques through observation and in-depth interviews. The findings in this study are that the reluctance of rural youth to work in farming is influenced by society’s negative view of farming. This negative view encourages rural youth migrate to urban areas and leave their family farming for their parents who have limited capabilities yet still fulfil their needs. In the end, farmers made efforts to overcome their limitations in several ways, such as setting a more flexible planting schedule, choosing the type of crop, and maintaining the season once a year.
Dinamika Kelembagaan dan Permasalahan Interaksi Lembaga: Studi Kasus Wisata Desa Karangrejo, Kecamatan Borobudur, Magelang
Authors: Beryl Chansya , Satriawan Ferdhika Riki , Dahlia Ira , Azzahra Miladia , Khairunisa Vinda Permata , Zalzabila Zalzabila
Published: February 2025

Community Based Tourism (CBT) is a variation of the tourism model that is widely applied in tourist destinations. This study explores the institutional dynamics and interaction problems in tourism management in Karangrejo Village, Borobudur District, Magelang, Indonesia. This is based on the challenges faced by Karangrejo Village in managing effective and sustainable tourism. This study aims to analyze institutional dynamics and the problems and complexity of interactions between stakeholders in Karangrejo Village. The study uses a qualitative-descriptive approach with primary and secondary data sources obtained through interviews, observations, and document studies. The results indicate that tourism management in Karangrejo Village is based on community initiatives with the village government acting as a supporter. This study also notes unique relationship patterns between stakeholders based on family and friendship, as well as adaptation to the COVID-19 crisis with assistance from external institutions, namely UNESCO. The conclusion emphasizes the importance of an adaptive and collaborative approach in village tourism management, with a deep understanding of the local context and strategic partnerships between stakeholders to ensure sustainable tourism development and empower local communities. Further research is needed on the institutional resilience of CBT management that is fluid during crisis conditions.
Dampak Pariwisata dalam Mewujudkan Kesejahteraan Masyarakat di Desa Wisata Karangrejo melalui Community Based Tourism (CBT)
Authors: El Yamin Dioda Ashaab , Noor S. Fathia Salma Jihan , Salsabila Idelia , Khairani Jihan Nisrina , Putri Nandita Arfiliana , Pratiwi Ninda Ayu
Published: February 2025

Community-based Tourism (CBT) is one of the concepts of tourism development through the role of local communities that is increasingly being developed in various specific tourist destinations. This study aims to explore the impact of tourism on the economic sector in realizing community welfare in Karangrejo Tourism Village, Borobudur District, Magelang Regency, through the role of CBT. In the process of managing and strategic tourism governance, Karangrejo Village has succeeded in implementing a fairly innovative and sustainable tourism base to be able to feel the positive impact of realizing the independence of the tourist village. The descriptive phenomenological approach was carried out through observation, interviews, and various documentation. The results show that the CBT strategy produces: (1) new business opportunities; (2) improving community skills; (3) opening access to a wider market; and (4) in the context of income, it is able to improve the welfare of the community involved by reducing poverty rates. In line with this, CBT is also able to encourage the preservation of culture and the environment to become an identity and strengthen the attraction in Karangrejo Tourism Village. Therefore, the active role and willingness of the local community to utilize the potential of Karangrejo Village has opened up broad economic opportunities so as to encourage the creation of sustainable local economic stability.
Analisis Peran CBT terhadap Lingkungan di Desa Wisata Karangrejo
Authors: F. Cyrillus Fishio , Cahyanti S Dhistia , Aulia’i Iqrima Aurora , Jagad Lintang Sekar , Kumala Natalia Citra , Qasamah Syakira Isyraf
Published: February 2025

Karangrejo Tourism Village is one of the tourism villages that implements Community-Based Tourism (CBT) as the main strategy in managing and developing local tourism. Through active community involvement in various initiatives such as tour guide services, empowerment through the Sumber Makmur Organic Farmers Association (PPOSM), development of Kampung Organic agrotourism, provision of homestays based on local wisdom, as well as environmental cleaning and education activities, CBT has succeeded in improving economic welfare and maintaining environmental sustainability. This study aims to explore the context of environmental sustainability that arises with tourism using the CBT model. The method used in this study is qualitative-descriptive using primary and secondary data obtained through interviews and document studies by reviewing relevant sources. The data shows that village income reached 2 billion rupiah, reflecting a positive contribution from the implementation of CBT. The success of Karangrejo Village in implementing CBT shows that with the right strategy and strong community participation, community-based tourism can be a model for developing sustainable tourism villages that provide economic, social, and environmental benefits holistically. This study underlines the importance of CBT management in supporting sustainability for the environment and provides recommendations for other regions to develop it.
Analisis Potensi Perkampungan Budaya Betawi Setu Babakan dalam Pengembangan Obyek Wisata Berkelanjutan
Authors: Qurrotul Alfiah , Nailisa Anindya , Abimanyu Bagas , Umami Faza Cahya
Published: February 2025

The urbanization of the population so that there is a shift in the original residents of Jakarta, of course, resulting in an increasing number of residents and acculturation of immigrant cultures in the future, the impact is that Betawi culture can be forgotten. This encourages the Government to strive to create a place for the preservation of Betawi culture so that it remains recognized and continues to grow. By using a descriptive qualitative method, the author tries to identify the potential of Setu Babakan Betawi Cultural Village in supporting the development of tourism objects through the SWOT method. The results of the research obtained factors that influence tourist attraction and to evaluate aspects of potential tourism development so as to increase the sustainability and cultural value of tourist attractions in the Setu Babakan Betawi Cultural Village. The writing of this report is used as evaluation data and alternative solutions to the Setu Babakan Betawi Cultural Village area based on the SWOT method.
Pengaruh Harga terhadap Loyalitas Pelanggan Studi Kasus pada Antavaya Tour and Travel Jakarta
Authors: Hartono Sofiani Marcelline
Published: February 2025

The Travel Bureau is one of the supporters that makes it easy for the public to access various information and transportation that supports tourist trips. The high level of tourism travel in Indonesia with easy access for the community, especially the emergence of a travel agency that makes it easier for the public to access various information and transportation that supports tourism travel. The existence of online transactions also helps boost sales of travel agents as well as helping the country's economy. The method used in this study is a quantitative method that is associative and explanatory with primary data by distributing questionnaires to 100 respondents. The analytical method used is simple linear regression analysis, validity test, reliability test, classic assumption test which consists of a normality test, linearity test, and hypothesis testing, namely the T test and the coefficient of determination test. The results of the study indicate that there is a significant positive effect of price on customer loyalty at AntaVaya Tour & Travel by 55.7% and the remaining 44.3% is influenced by other variables not examined in this study. The conclusion in this study is that price has an influence on customer loyalty so that Antavaya Tpur and Travel should pay attention to price and also other aspects such as service quality, facilities, ease of ordering, and so on. For other researchers, it is better to add other variables besides price in influencing customer loyalty.
Evaluasi Kerangka Konseptual Daya Dukung Ekowisata (Studi Kasus: Taman Nasional Karkheh dengan Taman Nasional Indonesia)
Authors: Salusu Fransisca Rimbunita , Khairunnisa Ayang , Amalia Affrida , Zidany Naufalika Anggi , Febriawan Teten , Furqan Alhilal
Published: February 2025

Carrying capacity measurement in an ecotourism concept is very important to measure the capacity of space to receive the number of tourists and their activities in the area. The calculating methods of the carrying capacity concept have been implemented in several ecotourism areas based on several categories, such as; physical, real, effective, ecological and socio-cultural carrying capacity. In this case, research was carried out with the aim of studying the concept of carrying capacity applied in Karkheh National Park and National Parks in Indonesia. This can be studied to find a new concept that can be useful for carrying capacity calculations in Indonesia which are more complex and on target. Literature study is the method used in this research to examine information related to each National Park area. Thus, the results of the elaboration of the concept of carrying capacity between Karkheh National Park and National Parks in Indonesia show that socio-cultural carrying capacity needs to be applied to National Parks in Indonesia because of the same high density context.
Pandemi COVID-19: Pengaruh Positif pada Jaminan Kesehatan di Destinasi Pariwisata Super Prioritas
Authors: Syafera Arkan
Published: February 2025

Penguatan baru di tengah masyarakat terjadi di tengah pandemi COVID-19 khususnya terkait dengan kesehatan. Jaminan kesehatan lengkap dengan informasi dan layanannya mengalami peningkatan drastis dibanding sebelum masa pandemi. Studi ini berupaya untuk mengkajinya secara lebih lanjut dengan 3 pertanyaan utama: : a) bagaimana posisi dimensi CHSE di tengah elemen vital lain dalam evaluasi DPSP selama COVID-19?; b) bagaimana unsur dimensi CHSE di DPSP berubah selama COVID-19?; dan c) bagaimana pengaruh dimensi CHSE terhadap dinamika wisatawan di DSPS?. Data untuk menjawab pertanyaan tersebut didapatkan dengan menggunakan metode kuisioner, wawancara, dan FGD. Responden dipilih secara purposif, yakni mereka yang sebelum dan semasa pandemi masih melakukan aktivitas kepariwisataan. Mereka terdiri dari pengelola desa wisata dan pemilik usaha-usaha pariwisata. Selain bersumber dari responden, informasi juga didapat dari informan dengan total 2 informan. Dalam forum FGD, juga hadir 2 narasumber yang berasal dari instansi pemerintah daerah, 1 narasumber dari Asita (Asosiasi Perusahaan Perjalanan Wisata Indonesia), 1 narasumber dari PHRI (Perhimpunan Hotel dan Restoran Indonesia, forum komunikasi desa wisata, dan 1 narasumber dari BDOT (Badan Otorita Danau Toba). Hasil penelitian menunjukkan bahwa CHSE menjadi satu-satunya dimensi yang mengalami kenaikan dibanding dengan dimensi lain—yakni dimensi produk, dimensi pasar dan pemasaran, dimensi kelembagaan, dimensi investasi, dimensi adaptasi, serta dimensi kebutuhan—dalam merespon kebutuhan wisatawan di era pandemi.