bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of DHT 11 and NTC Temperature Sensors Based on Internet of Things and Lora Ebyte 32 For Incubator
Authors: Zimamul Adli Muhammad , Suratman Euman , Firdaus Muhammad Aditiya
Published: September 2024

Incubators require precise temperature monitoring to ensure optimal conditions for the growth and development of the organisms inside. DHT11 and NTC sensors are both widely used in temperature measurement, but have different characteristics in terms of accuracy, response time, and reliability. The use of IoT technology enables real-time and remote temperature monitoring and control, while the LoRa Ebyte 32 module is used for efficient long-range wireless communication. The results show that the NTC sensor has a higher percentage error and average error compared to DHT11, namely RE 2.4681% MEA 0.8885 and DHT11 has RE 1.5255% MEA 0.5492. From these results it can be stated that the DHT11 sensor is suitable for use in baby incubators.

Keywords: DHT11; NTC; LoRa; Inkubator; IoT
Isolation, Screening and Biocidal Activity of Secondary Metabolites from Fungi of Paddy Field Soil Samples in Selected Alanganallur Sub Regions, Madurai, Tamil Nadu
Authors: Seenivasan R. , Krishnamoorthy M. , Velladurai P.
Published: September 2024

Soil is a dynamic, living matrix that is an essential part of the terrestrial ecosystem. The soil serves as a reservoir for many microbial communities of plants and herbs which are producing, CO2 and nitrogen. Paddy (Oryza sativa L.) is the most important cereal crop of the world. Paddy field soil contains rich organic matters like old stubble, paddy straw, senescent roots and wastes. It also contains numerous types of fungi, which support rice production as well as maintain the fertility of paddy soil. This study investigates the secondary metabolites produced by various fungal species isolated from the Alanganallur region, aiming to uncover novel bioactive compounds with potential pharmaceutical and agricultural applications. Soil samples were systematically collected and cultured to isolate diverse fungal strains. The secondary metabolites were extracted using solvent extraction methods and subsequently analyzed using microbial and spectroscopic techniques, including FT-IR spectroscopy. The screening revealed a wide array of secondary metabolite compounds which exhibited significant antibacterial activity when subjected to antibacterial tests. Notably, a subset of these metabolites demonstrated potent activity against Staphylococcus aureus and E. coli, highlighting their potential as leads for new antibacterial agents. This research underscores the rich biodiversity of soil fungi in the Alanganallur region and their capacity to produce bioactive secondary metabolites. The findings suggest that these metabolites could serve as a valuable resource for the development of novel therapeutic agents and biopesticides.

Keywords: Metabolites, Nitrogen, Soil fungi, Antibacterial
Stem Cell Treatment for Dilated Cardiomyopathy: A Review of Recent Scientific Advances
Authors: Kasraian Liddy , Railey John , Mehta Caitlin , Garvey Madeline H
Published: September 2024

Cardiomyopathy, a disorder of mechanical and electrical cardiac action, is a significant cause of morbidity and mortality in the United States and is seen in both adult and pediatric populations. Dilated cardiomyopathy, a subtype involving pathological enlargement of the heart, in particular causes significant reduction in quality of life and is a significant risk factor for heart failure development. Traditional treatment for dilated cardiomyopathy largely focuses on symptomatic relief and delayed progression of disease but does not offer a cure or reversal of disease process. In the past few decades, stem cell therapy has become a promising therapeutic because these cells can differentiate into human cardiomyocytes and offer a potential restoration of normal cardiomyocyte function. This review highlights 3 methodological derivations of cardiomyocytes: bone marrow–derived hematopoietic stem cells, mesenchymal stem cells, and adipose-derived stem cells. While most of the current research has focused on hematopoietic stem cells for dilated cardiomyopathy, further research is needed to elucidate which stem cell line is superior and most effective for disease treatment and reversal. This review highlights future directions of this line of research, such as direct comparison between cell types, analysis of the long-term effects of stem cell treatment, increased sample sizes, and potential use of this treatment in the pediatric and adult populations.
Conexões entre a atuação do nutricionista e o alcance das metas de desenvolvimento sustentável para promoção da saúde e bem-estar do trabalhador em Serviços de Alimentação
Authors: Brito Herbenny Hellen Medeiros de , Faustino Maria Luísa Meira , Figueiredo Tayana Cabral , Seabra Larissa Mont’Alverne Jucá , Rolim Priscilla Moura
Published: September 2024

A alimentação coletiva desempenha papel importante para o desenvolvimento sustentável relacionado à saúde e bem-estar, uma vez que configura-se como ambiente alimentar que interfere diretamente em desfechos de saúde na população. Este estudo objetivou mapear as evidências científicas sobre as conexões entre a atuação do nutricionista e o alcance das metas de desenvolvimento sustentável para promoção da saúde e bem-estar do trabalhador dos serviços de alimentação coletiva. Utilizou-se as recomendações do PRISMA-ScR para busca e seleção de artigos em bases de dados PubMed, ScienceDirect e Google Scholar, sem limite temporal e restrição de idioma. A pergunta de pesquisa foi baseada no mnemônico PCC (problema, conceito e contexto) definida “Como o nutricionista pode atuar para o cumprimento da meta 3.4. do objetivo do desenvolvimento sustentável relacionando o controle de doenças crônicas não transmissíveis e a promoção de saúde mental e bem-estar do trabalhador no contexto da alimentação coletiva?”. Foram encontrados um total de 1.715 estudos, destes, 34 artigos foram incluídos para revisão. Majoritariamente (88%) os estudos foram realizados no Brasil com foco principalmente na avaliação da qualidade nutricional dos cardápios, com destaque para cardápios hiperproteicos e hiperlipídicos, e excesso de sódio; além das condições ambientais com a presença de riscos físicos e ergonômicos. Os estudos demonstram que os ambientes dos serviços de alimentação podem estar associados ao adoecimento de seus trabalhadores, por doenças crônicas, doenças ocupacionais e/ou distúrbios psicológicos. Os nutricionistas podem minimizar esse cenário particularmente por meio do planejamento de cardápios saudáveis e sustentáveis, promoção de ações de vigilância da saúde do trabalhador, avaliação periódica do estado nutricional dos trabalhadores e fomento da liderança participativa a fim de contribuir para  desenvolvimento sustentável.
THE DEVELOPMENT OF THE SERVICE SECTOR IN THE REGION IN THE CONTEXT OF THE FORMATION OF TECHNOLOGICAL SOVEREIGNTY
Authors:   Joint Stock Company «Institute  of Regional Economic Research», Moscow, Russian Federation, Burak P.I. , Zvorykina T.I. ,   Joint Stock Company «Institute  of Regional Economic Research», Moscow, Russian Federation
Published: September 2024

The article examines the role and place of the service sector in the economy of the regions of Russia. Attention is drawn to the fact that the service sector is affected by modern challenges associated with the difficult economic situation in Russia due to the application of economic sanctions by unfriendly states. The situation with import substitution is analyzed and it is concluded that in the service sector it is necessary to carry out a complex of works ensuring its technological sovereignty in the regions. The tools that form technological sovereignty are proposed, among them scientific methods of standardization, technical standardization committees capable of creating standardization documents are given.
Economic space as the object of management and strategizing
Authors:   Institute of Economics of the Russian Academy of Sciences, Moscow, Russian Federation, Buchwald E.M. , Valentik O.N. ,   Institute of Economics of the Russian Academy of Sciences, Moscow, Russian Federation
Published: September 2024

The article discusses some of the tasks of updating adopted in 2019 Spatial Development Strategy of the Russian Federation until 2025. It’ noted that among these tasks is more complete and clear definition of the object of regulatory impact of this strategic planning document. The opinion is expressed that it’s most appropriate to define such an object as the economic space of the Russian Federation, accumulating all the most significant processes in the country's economy. The article constitutes the essence of the economic space as a scientific category and as an object of management and strategizing and formulates the main tasks of regulating the economic space, which should be solved in the upcoming perspective.
MENSTRÜEL SEMPTOM YAŞAMA DURUMU İLE AİLEDE MENSTRÜEL SEMPTOM ÖYKÜSÜ VE ALGILADIKLARI SOSYAL DESTEK İLŞKİLİ Mİ: KESİTSEL ÇALIŞMA
Authors: Aslan Demirtaş Fatma , Öskan Fırat Burcu , Ertop Hülya , Hotun Şahin Nevin
Published: September 2024

This study aims to determine the relationship between menstrual symptom experience, the presence of menstrual symptoms in the family, and perceived social support in women of reproductive age. This descriptive and cross-sectional study was conducted with women aged 18–49 living in XXX on online platforms between April 1 and June 30, 2022. Participants were invited to the study through social media platforms. The women 942 constituted the sample of the research. The mean age of the women who participated in the study was 28.45±6.75 years. Of the participating women, 80.1% reported that they had regular menstruation and 71.1% had a family history of menstrual symptoms. The mean total scores of the Menstruation Symptom Questionnaire (MSQ) and Multidimensional Perceived Social Support Scale (MSPSS) were 63.02±16.07 and 66.97±14.95, respectively. The results of the study showed a strong relationship between experiencing menstrual symptoms and a history of menstrual symptoms in the family. There was a low-level significant relationship between experiencing menstrual symptoms and social support. Accordingly, it is recommended to conduct more studies on the relationship between social support and menstrual symptoms using an increased sample size and prospective methods.
Biosecurity in Post-Covid-19 Dental Care: An Integrative Review
Authors: Queiroz Neyla Lima Cesar , Oliveira Ana Meylline Vieira , Barroso José Jefferson Carneiro , Cesar Ilarya Regina Lima , Nunes Nara Lhays Teixeira , Sousa Luzia Herminia Teixeira de , Nogueira Luis Henrique dos Santos , Nascimento João Victor Menezes do , Santiago Nauyla Braga Mesquita , Linhares Conceição Mikaelly de Vasconcelos , Freitas Maria Tayara Marques de , Magalhães Maria Larissa Pontes , Carneiro Jessica Rodrigues Mendes
Published: September 2024

After the emergence of Coronavirus 2019 (COVID-19), biosafety measures in dentistry had to be intensified to provide more safety for professionals and patients, given that dental care requires close contact, thus exposing the professional to contaminated fluids such as saliva and blood, increasing the chances of cross-infection. The objective of this study is to conduct an integrative review on the established biosafety in dental care after the emergence of COVID-19. A bibliographic search was conducted until November 1, 2021, through the Regional Portal of the Virtual Health Library (VHL) and PubMed, using the terms "COVID-19," "Biosafety," and "Dentistry," with no filters or limits applied. After reading and applying inclusion and exclusion criteria, 11 studies were selected. A manual search was then conducted among the already selected studies, where two more studies were included, totaling 13 studies. Biosafety measures that should be carried out before, during, and after dental care following the emergence of COVID-19 were identified. Among the main measures are pre-screening, organization of the waiting room, increased frequency of hand hygiene, use of Personal Protective Equipment (PPE) previously not widely used, such as face shields, mouthwashes that reduce viral dissemination, and rubber dams to reduce contaminated aerosols, knowledge about the types of procedures that should be avoided or performed with restrictions, and cleaning and disinfection of environments. In conclusion, biosafety measures should be employed in all dental environments to strengthen the protection of professionals and patients, thus minimizing the risk of contagion.
Tasa de egreso hospitalario por año según sexo y edad de enfermedad hepática alcohólica entre 2018-2022, Chile
Authors: Valencia Ibieta Catalina , Canelo Nigoevic Constanza , Chelén Prohens Constanza , Navarro García Javiera , López Duarte Isidora
Published: September 2024

La enfermedad hepática alcohólica engloba toda lesión en el hígado causada por alcohol, desde esteatosis hasta cirrosis. Objetivo: Describir la tasa de egreso hospitalario por enfermedad hepática alcohólica entre 2018-2022 en Chile. Metodología: Estudio ecológico descriptivo. Datos obtenidos del DEIS sobre egresos hospitalarios por enfermedad hepática alcohólica en Chile entre 2018-2022, según sexo y grupo etario (n= 13.259). Se calculó la tasa de egreso hospitalario. Resultado: La tasa de egreso hospitalario en el periodo de estudio fue de 15,29/100.000 habitantes sobre los 20 años. En 2021 fue el año con mayor tasa, con 17,92. El sexo masculino tuvo la mayor tasa de egreso hospitalario con 25,15 en promedio. El grupo etario con mayor tasa fue de 45 a 64 años con 8.217 egresos. Discusión: En pandemia se observó un aumento en la tasa de egreso hospitalario. Los hombres presentaron la mayor tasa, lo que podría deberse a factores como la norma asociadas al rol tradicional masculino, asociado al mayor consumo. El grupo etario con mayor tasa fue el de 45-64 años, lo que podría explicarse debido a que la enfermedad hepática alcohólica se incrementa con la ingesta de alcohol diario por 10 o más años. Conclusión: Se constató un aumento en la tasa de egreso hospitalario durante la pandemia, mayor entre los 45-64 años, con el sexo masculino más afectado. Esto demuestra la necesidad de realizar más investigaciones relacionadas a la enfermedad hepática alcohólica para comprender el impacto a nivel nacional y llevar a cabo políticas públicas atingentes.
Efficiency of Runge-Kutta-Fehlberg Method in Resolving Uncertainty: a Fuzzy Approach to Delay Differential Equations
Authors: Ch. Subba Reddy
Published: September 2024

This research delves into the examination of the convergence behavior of the Runge-Kutta-Fehlberg Method (RKFM) when applied to address the challenges posed by Delay Differential Equations (DDE) within the framework of fuzzy concepts. The integration of fuzzy logic is explored as a strategic means to grapple with the inherent uncertainty in obtained results, acknowledging the limitations of conventional approaches in dealing with nuanced uncertainties in DDEs. The core of the study involves a meticulous analysis of numerical outcomes, with a specific emphasis on evaluating the effectiveness and efficiency of the Runge-Kutta-Fehlberg method. The assessment includes a thorough comparison of results obtained through the RKFM against those derived from the Runge-Kutta 4th-order method, as well as benchmarking against the exact solution. The findings of this research not only validate the suitability of the RKFM for solving Delay Differential Equations but also highlight its comparative advantages over the traditional Runge-Kutta 4th-order method. The results contribute to an enhanced understanding of the performance and applicability of the RKFM in the context of fuzzy DDEs, thereby advancing the landscape of numerical methods for addressing complex dynamic systems.
Implementing Statistical Distribution for Control Chart Design in Higher Education Institutions
Authors: A. Loganatahan
Published: September 2024

In higher education institutions, continuous improvement of academic and administrative processes is crucial. This paper explores the use of statistical control charts for effective monitoring and management of these processes. By implementing control charts based on suitable statistical distributions, institutions can systematically track performance metrics such as exam scores, student attendance rates, graduation rates, and faculty performance. Choosing the right control chart is essential and depends on the data type. For continuous data, such as exam scores or time-to-graduation, X-bar and R (Mean and Range) charts or X-bar and S (Mean and Standard Deviation) charts are appropriate, as they assume a normal distribution and are useful for subgroup variations. For discrete data, like student absences or pass/fail outcomes, P-charts (Proportion charts) or U-charts (Defect per unit charts) are better suited, handling binomial or Poisson distributions effectively. Implementing control charts involves defining the process to be monitored, collecting and organizing data, selecting the suitable chart based on data type and distribution, and analyzing the chart to identify trends or outliers. This structured approach enables institutions to identify areas needing improvement, assess the impact of interventions, and make data-driven decisions. The use of statistical control charts facilitates proactive management by detecting issues before they escalate. For example, trends in declining exam scores or increasing absenteeism can be identified early, allowing for timely interventions. Monitoring faculty performance through control charts helps maintain high teaching standards and highlights areas for professional development. In conclusion, statistical control charts offer a structured, empirical approach to quality management in higher education. By aligning the choice of control charts with data characteristics, institutions can enhance their monitoring capabilities, leading to improved academic and administrative outcomes. This paper highlights the potential of data-driven management in fostering continuous improvement and excellence in higher education.
Implementation of Spatial Error Model through Maximum Likelihood
Authors: Raveena Begum
Published: September 2024

The implementation of spatial models through maximum likelihood is a great challenge due to the presence of Jacobian term in the log likelihood function. In literature, the implementation is usually performed using pseudo-likelihood. However, pseudo-likelihood doesn’t provide the consistent and efficient estimators. The present study implements the Spatial Error Model (SEM) through maximum likelihood. The maximum likelihood method provides the desirable properties like consistency, asymtotic efficiency, asymtotic normalilty and in some cases, it achieves unbiasness, Anselin (1988). The implementation through maximum likelihood is carried using Differential Evolution technique. The obtained results through maximum likelihood and pseudo-likelihood are compared and discussed
Solution of a Boundary Value Problem Involving General Class of Polynomial, Struve’s Function and PSI function of One Variable
Authors: B. Satyanarayana
Published: September 2024

The authors of this paper have established some integrals that involves the PSI-function of one variable and Struve's function with the general class of polynomials. Additionally, solved a boundary value problem involving the steady state temperature distribution of a rectangular plate using PSI-function, Struve's function and general class of polynomials. This can be considered another novel technique to solve the boundary value problem. Finally, some special cases were incorporated.
Optimizing Integrated Circuit Applications with Digital IIR Filtering Architectures
Authors: Bujjibabu P
Published: September 2024

In this research, a high-performance IIR filter for low-power DSP applications is implemented and realized using a MATLAB system generator. There are numerous ways to implement IIR filters, including the Direct Form-I(DF-I), Direct Form-II(DF-II), Cascade, and Parallel Forms. All of these structures offer a selection area for a suitable realization that will decrease power consumption and increase the speed of digital filters. This particular work uses a Xilinx FPGA device to implement a 5th order Low pass IIR filter in DF-I, DF-II, and Cascade Form (DF-I/DF-II). Cascade (Direct Form-I) realization is the best way to build higher order IIR filters where power is a primary limitation, while cascade (Direct form-II), corresponding power analysis is also conducted, the technique is optimal if the area is a main constraint.
Mathematical Optimization of Energy Utilization in Smart Meter Analytics Using Liquid Neural Networks
Authors: N.S.Usha
Published: September 2024

IntelliMeter, a novel framework integrating Liquid Neural Networks (LNN) with Wireless IoT technology and advanced Machine Learning techniques, is introduced for smart meter data analytics. Comparative evaluations against traditional methods like Linear Regression with Seasonal Decomposition (LRSD) and AutoRegressive Integrated Moving Average (ARIMA) reveal superior performance across energy demand forecasting accuracy, anomaly detection, and grid optimization efficiency. The LNN model within IntelliMeter achieves a notable 25% reduction in energy wastage compared to conventional methods. Additionally, it demonstrates a precision rate of 96.97% in anomaly detection, surpassing LRSD and ARIMA. Furthermore, the LNN model exhibits enhanced grid optimization efficiency, highlighting its potential to revolutionize energy management practices through intelligent resource allocation and operational optimization. These findings underscore the transformative impact of LNN-based approaches in enabling more efficient, reliable, and sustainable energy management solutions. IntelliMeter represents a significant advancement in smart meter data analytics, offering utilities actionable insights for optimizing energy distribution, minimizing operational costs, and enhancing grid stability.
Navigating Transitions: Factor Analysis of Competencies in Military Officers
Authors: Abhinav Kumar
Published: September 2024

The current paper’s purpose is to develop a competency model for the retired armed forces officers which would assist in identification of the major competencies of Military officers and would allow HR professional in better recruitment and further human resource development of the organizations. This study uses literature review and expert opinion to arrive at a set of competencies which characterize Military officers. The competencies, thus identified are factor analysed to reduce it to the critical competencies which forms the basis of the competency model. An analysis of the literature identifies various competencies including skills and traits which are the characteristics of military officers. These are validated through expert opinions to arrive at a set of 28 competencies which define the managerial traits of Military officers. The Military officers develop these competencies over their service period. Further factor analysis reduces these factors to a cluster of six critical competencies developed into a model, which would form the basis for various HR based decisions. The scope of this research paper is limited to the basic managerial competencies which define the Military officers. The paper arrives at a competency model specific to Military officers that would lay the foundation for the HR professionals in recruiting this trained workforce and further help them in planning their development and career progression.
Revolutionizing AI Decision-Making with Hybrid Rule-Based Systems: A Novel Framework for Transparent and Accurate Outcomes
Authors: Lakshmi Harika Palivela
Published: September 2024

The rapid advancement of artificial intelligence (AI) has led to the development of increasingly complex decision-making systems. However, these systems often face challenges related to transparency, interpretability, and accuracy. To address these issues, this paper presents a novel framework that integrates hybrid rule-based systems into AI decision-making processes. By combining the strengths of both rule-based and data-driven approaches, this framework enhances the transparency of AI models, ensuring that decisions are more understandable to users and stakeholders.The proposed hybrid system leverages explicit rules to govern certain decision-making scenarios while utilizing machine learning algorithms to manage more complex and less predictable situations. This dual approach allows for the creation of AI systems that not only perform with high accuracy but also offer clear, interpretable justifications for their decisions. Such transparency is crucial in fields where AI decisions significantly impact human lives, such as healthcare, finance, and legal systems.Furthermore, the framework is designed to be adaptable, allowing for the continuous integration of new rules and data as they become available. This adaptability ensures that the AI system remains up-to-date and relevant in a rapidly evolving technological landscape. By revolutionizing AI decision-making with this hybrid rule-based approach, the framework paves the way for more responsible, accurate, and transparent AI applications across various industries.
Harnessing Machine Learning for Metagenomics: Discovering the Invisible Microbial World
Authors: S. Sabaria
Published: September 2024

Metagenomics has revolutionized our understanding of microbial communities by enabling the study of genetic material recovered directly from environmental samples. Traditional methods of microbiology often miss the vast majority of microorganisms that are unculturable in laboratory settings. Harnessing the power of machine learning in metagenomics provides an unprecedented opportunity to uncover the diversity and functionality of these invisible microbial worlds. By analyzing large-scale metagenomic datasets, machine learning algorithms can identify patterns and associations that are not easily discernible through conventional analytical techniques, paving the way for new discoveries in microbial ecology and evolution.The integration of machine learning into metagenomics has the potential to enhance the accuracy and speed of taxonomic classification, functional annotation, and the prediction of microbial interactions. Machine learning models can process complex, high-dimensional data, enabling researchers to make more informed predictions about microbial roles in various ecosystems. Additionally, machine learning techniques can aid in identifying novel genes and metabolic pathways that could have significant implications for biotechnology, medicine, and environmental science. These advancements could lead to breakthroughs in areas such as antibiotic resistance, bioremediation, and the development of new bioproducts.As machine learning continues to evolve, its application in metagenomics will likely expand, offering deeper insights into microbial dynamics and their influence on human health and the environment. However, challenges remain, including the need for large, well-curated datasets and the development of models that can handle the complexity and variability of metagenomic data. Despite these challenges, the synergy between machine learning and metagenomics holds great promise for advancing our understanding of the microbial world and unlocking the potential of microbes in various fields.
Applications of Chromatic Numbers in Traffic Control Problems
Authors: Shakera Tanveer
Published: September 2024

The primary objective of this work is to illustrate the application of chromatic numbers in traffic control problems. It is simple to depict most traffic lanes as graphs with points (vertices) and lines (edges). In order to determine the minimum number of phases needed for the traffic light to allow all cars to pass through the intersection during a specific phase of the light and those in lanes where the light is green to pass through the intersection safely, this article uses three examples of traffic lanes to demonstrate how chromatic number can be applied effectively to traffic management problems.
A Mathematical and Hybrid Deep Learning Model for Real-Time Intrusion Detection in IoT-Based Electric Vehicle Charging Stations
Authors: Adil Fahad
Published: September 2024

The recent frame of IoT and Industrial IoT security brings new type of intrusion detection systems. We propose a new method for Intrusion Detection in IoT based EVCS with the integration of Convolutional Neural Network, Long Short-term Memory model and Gated Recurrent Unit. This work uses a naturally pervasive, and representative real-world security focusing on IoT typical applications to address the capillary layer inherent challenges (e.g. at each EVCS vs through IT infrastructure as compared peripheral equipment). We have tested this both with Binary and Multiclass exhaustively. The benchmarks are perfectly accurate (100 % binary class, 97.44% six-class classification and near ~96/90%% in fifteen classes that certainly sets a new bar for the going forward!) Collectively, the entire ensemble architecture demonstrates a scalable high performance mean so again this ways these accomplishments certify that CNN-LSTM-GRU-based complex models can be used in space-strapped and processing constrained Intrusion Detection system for IoT to perform consistently robust. The ensemble algorithm, which is open sourced on the GitHub under our simulation framework codebase also represents a significant improvement in securing Internet of Things based EVCS from various cyber security threats.
Tripled Fixed Point Results in G_b-Metric Spaces
Authors: V. Rajitha
Published: September 2024

In recent work authors were discussed fixed point results with various contractions like (ψ,ϕ)-weakly contractive mappings, cyclic contraction, E.A property, Suzuki-type contraction etc. in complete -metric spaces, With the help of completeness property and continuous function we obtained unique tripled fixed point in -metric spaces.
Objectives: To show tripled fixed point theorems in -metric spaces via new type of contraction and shown illustrate an example which supports the main result.
Methods: In recent work authors were discussed fixed point results with various contractions like (ψ, ϕ)-weakly contractive mappings, cyclic contraction, E.A property, Suzuki-type contraction etc. in complete -metric spaces, here we have showed tripled fixed point results by using new type of contraction.
Results: Unique tripled fixed points with new type of contraction in -metric spaces.
Conclusions: In this work we have obtained TFP results by using a new type of contraction and discussed corollary also an example which supports the main result.
Rayleigh Waves Propagation in a Micropolar Viscothermoelastic Half-Space with Impedance Boundary Conditions
Authors: Mamatha Kumari
Published: September 2024

This paper deals with the propagation of Rayleigh waves in a micropolar viscothermoelastic half space with impedance boundary conditions. The boundary of the half space is thermally insulated/isothermal and it is assumed that normal traction, shear traction and shear couple traction at the surface, varies linearly with normal, tangential components of displacement and microrotation respectively. The secular equation for Rayleigh wave with impedance boundary conditions is obtained and this equation is in agreement with the classical secular equation for elastic solid with traction free boundary conditions when micropolar, thermal and impedance parameters are removed. The non-dimensional speed of Rayleigh wave is computed as a function of impedance parameters and presented graphically for a particular micropolar thermoelastic material.
Routing through LEO Satellite Constellation Networks: A DopplerShift Measurement based Coverage window Detection Approach
Authors: Eman Adel Elbehiry
Published: September 2024

Most Internet-of-Things (IoT) applications via satellite depend on reasonably priced, energy-constrained, location-aware IoT sensors. In this letter, we present a brand technique that uses straightforward Doppler measurements to estimate the satellite visibility window on Internet of Things devices. We provide two cases where the IoT device does not initially know the geographic coordinates of the serving satellite: (i) we assume that the IoT device knows the coordinates, and (ii) we assume that the coordinates are unknown. As a result, we obtain the Doppler measurement likelihood function and reduce it to a problem of minimizing root mean square error (RMSE). We use a stochastic optimizer to minimize the root mean square error (RMSE) to predict the orbital parameters of the serving satellite from a series of Doppler observations. We then forecast the satellite visibility window (satellite pass) based on the orbital estimation. We compute the overlapping visibility window between the ground truth and the estimation using the intersection-over-union metric in order to assess the correctness of the window estimation. The results are based on extensive MATLAB simulations. In addition to the proposed technique utilizing Doppler measurements for estimating satellite visibility windows in IoT devices, the system is structured around two ground stations. These ground stations are interconnected through a process facilitated by Dijkstra’s Algorithm, which calculates the shortest path between them via visible satellites. This integration of Dijkstra’s Algorithm ensures optimal routing and connectivity between the ground stations, enhancing the efficiency and reliability of the IoT application over satellite communication.
On Discrete Harmonic Distributions related with Harmonic Mean Random Variable
Authors: Prasanta Kumar Das
Published: September 2024

The main purpose of this paper is to introduce the concept of harmonically distributed discrete random variable. We define probability mass function such as harmonic mass function, exponential harmonic mass function, natural logarithmic  harmonic mass function and their associated cumulative distribution functions. Existence the distribution is shown with some examples. Finally harmonic mass function is used to solve a run-time problem and a capacitance problem as an application of the distribution  in the field of electrical engineering.
Exploring Real-Time Data Processing Using Big Data Frameworks
Authors: Sampath Kini K
Published: September 2024

Big data frameworks that weaken the throughput of data processing, allowing for real-time data processing like Apache Spark, Kafka, and Flink are other developments. Regarding quick decisions by each measurement, the scalability, fault tolerance, and latency of three architectures Here each stream processing, lambda, and Kappa have been further studied and measured to approach a conclusion. Based on a methodical survey of literature, performance laws, and case studies, all three frameworks and architectures pros and cons measure us, which can then be used for separate operations use situations. For example, our studies have shown that the smudge feels natural for micro-batch situations, and for high-throughput, Kafka, and actual stream processing, Flink feels natural due to complicated event time handling. However, the findings from this research show a relevant effect on the system architecture for companies that want to implement real-time data. Future research needs to study the possibility of edge computing to reduce reaction time and data processing bottlenecks, as well as the possibility of connecting that with machine knowledge opportunities to better understand predictive analysis. This illustrates the research that practitioners and researchers have to do to make real-time data processing part of their operations
On δgα Closure and δgα Interior S In TSS
Authors: M. Madhesan
Published: September 2024

The purpose of this research article is to explain the new notions of δgα - derived, δgα-closure, δgα-interior, δgα-nbd., and moreover, the connections among them are identified.
Strategic Intelligence and Its Role in Enhancing Competitive Advantages for Organizations – A Field Study – Antibiotical Pharmaceutical Industries Company.
Authors: Allali Zahra Elhachemi Rebiai,
Published: September 2024

Through this study, our aim was to measure the correlation and impact of strategic intelligence on competitive advantages. Strategic intelligence holds significant importance and is an indispensable factor in organizations' pursuit of achieving goals and objectives. Its main concept revolves around a series of pivotal activities that enable organizations to formulate long-term strategies, plan, and make decisions that surpass those of their competitors. The motivation behind this study was to conduct research within the Antibiotical Company, a subsidiary of the Saidal Group. Therefore, we adopted an analytical and descriptive approach and conducted a field study using a well-designed questionnaire to collect data, which was then distributed to a sample of 80 employees and officials in the aforementioned company. By using appropriate statistical methods and leveraging the SPSS program, we meticulously analyzed the collected data. The study conclusively revealed that strategic vision, partnership, the ability to inspire employees, creativity, and intuition all have a profound impact on enhancing competitive advantages.
Data-Driven Decision-Making: Leveraging Analytics for Performance Improvement
Authors: S. Dhivya devi A. Vinay Bhushan, G. Lakshmi, , Usman AK Subhajit Brojabasi, Syed Shujauddin Sameer,
Published: September 2024

In the modern world, businesses, societies, and investigators all depend on decisions. However, to make intelligent judgments, they must embrace emerging innovations such as big data, analytics, ML, and automatic decision-making. To improve on traditional decision theory, this article presents a new data-driven theory. It asserts that analytical tools and big data need to be viewed as individual factors, that individuals who make decisions and analytics can work together to achieve cooperative logical thinking, and that significant incorporation of data and analytics with traditional decision-making aspects may outcome in more effective, more informed decisions. The theory is expanded upon in the article, along with examples of how it is used to data-driven decisions.
Interdisciplinary approaches to understanding language endangerment
Authors: Bromham Lindell
Published: September 2024

Language diversity is under threat, with between a third to a half of the world’s spoken languages considered endangered, and predicted rates of loss equivalent to one language per month for the rest of the century. This seminar focuses on interdisciplinary research adapting methods developed in biology to study patterns and causes of language endangerment and loss. While the causes of language endangerment are different to those for species, their analyses must overcome similar challenges, including detecting significant patterns over stochastic processes, and avoiding confounding correlations due to phylogenetic non-independence and spatial autocorrelation. I will briefly discuss three case studies: using population modelling to study language shift over generations; adapting the genotype concept to identify risk factors for language loss in a small community; and application of macroecological approaches to describing global patterns and correlates of language endangerment, including prediction of future language loss.
Sàng lọc Methylmalonic Acidemia và Propionic Acidemia bằng phương pháp khối phổ đôi: Hồi cứu loạt ca bệnh
Authors: Mai Tô Tuyết , Mai Trần Thị Chi
Published: September 2024

Methylmalonic Acidemia (MMA) là một nhóm rối loạn di truyền lặn trên nhiễm sắc thể (NST) thường, liên quan đến sự khiếm khuyết trong quá trình chuyển đổi methylmalonyl-CoA thành succinyl-CoA, đặc trưng bởi sự tích tụ của acid methylmalonic. Trong khi đó, Propionic Acidemia (PPA) là bệnh di truyền lặn liên quan đến việc chuyển đổi propionyl-CoA thành methylmalonyl-CoA bởi enzyme propionyl-CoA carboxylase của ty thể. Do các biểu hiện lâm sàng không đặc hiệu, các xét nghiệm hóa sinh đóng vai trò cốt lõi trong sàng lọc, chẩn đoán MMA và PPA. Nghiên cứu hồi cứu, mô tả một loạt ca bệnh được thực hiện nhằm đánh giá kết quả sàng lọc MMA và PPA ở các bệnh nhân có nguy cơ cao. Định lượng các acylcarnitin trong mẫu máu thấm khô bằng kĩ thuật khối phổ đôi (MS/MS) và phân tích acid hữu cơ niệu bằng kỹ thuật sắc ký khí ghép nối khối phổ (GC/MS) được áp dụng để sàng lọc và chẩn đoán cho 6 bệnh nhân mắc MMA và 7 bệnh nhân mắc PPA (từ 9/2018 đến 12/2021) tại Bệnh viện Nhi Trung ương. Kết quả sàng lọc MS/MS của 6 bệnh nhân MMA có 4/6 tăng C3, 3/6 bệnh nhân giảm C0 và tất cả 6/6 tăng tỉ lệ C3/C2. Kết quả sàng lọc rối loạn chuyển hoá bằng MS/MS của 7 bệnh nhân PPA cho thấy tất cả đều tăng C3 và tỷ lệ C3/C2. Kết quả xét nghiệm acid hữu cơ niệu tăng cao acid methylmalonic cho phép phân biệt giữa bệnh nhân MMA và PPA vì acid methylmalonic không tăng trong PPA.
Xác định đột biến gen EIF4G1 trên bệnh nhân Parkinson
Authors: Chinh Vũ Thị , Tuấn Phạm Lê Anh , Hải Lê Hạ Long , Việt Nguyễn Hoàng , Hằng Trần Nguyễn Thanh , Thịnh Trần Huy , Khánh Trần Vân
Published: September 2024

Bệnh Parkinson là bệnh thoái hóa thần kinh trung ương phổ biến thứ hai thế giới sau bệnh Alzheimer, ảnh hưởng đến khả năng kiểm soát cơ, giữ thăng bằng và vận động tự chủ của bệnh nhân. Gen EIF4G1 là một thành phần của phức hợp eIF4F, cần thiết trong việc điều hòa quá trình dịch mã ATF4 mRNA mã hóa ty thể, sự sống của tế bào, và các gen tăng trưởng để đáp ứng với các căng thẳng khác nhau. Các đột biến trên gen EIF4G1 gần đây đã được xác định là nguyên nhân gây ra bệnh Parkinson khởi phát muộn chi phối trên nhiễm sắc thể thường (PARK18), tuy nhiên vai trò của nó trong quá trình thoái hóa thần kinh liên quan đến Parkinson vẫn chưa rõ ràng. Vì vậy, nghiên cứu được thực hiện với mục đích xác định các đột biến của gen EIF4G1 ở bệnh nhân Parkinson bằng kỹ thuật giải trình tự gen Sanger. Nghiên cứu tiến hành trên 30 bệnh nhân Parkinson với độ tuổi trung bình 53,97 ± 7,35 tuổi, tỷ lệ nam/nữ = 1,31. Nhóm nghiên cứu đã phát hiện các đột biến điểm trên gen EIF4G1 với tỷ lệ 16,66% tương ứng 5/30 bệnh nhân mang 5 dạng đột biến khác nhau. Nghiên cứu có ý nghĩa trong hỗ trợ trong tư vấn di truyền, phát triển các phương pháp trị liệu và đóng góp vào cơ sở dữ liệu bệnh Parkinson tại Việt Nam.
Đặc điểm lâm sàng và cận lâm sàng bệnh phổi mô kẽ trong bệnh lý mô liên kết
Authors: Dân Bùi Văn , Triều Trần Minh Long , Minh Nguyễn Anh , Lượng Trần Văn , Phương Nguyễn Hoàng , Tùng Lê Đình
Published: September 2024

Nghiên cứu của chúng tôi được thực hiện với mục đích đánh giá tần suất và kiểu hình của bệnh phổi mô kẽ (interstitial lung disease - ILD) ở người bệnh đã được chẩn đoán bệnh mô liên kết (connective tissue disease - CTD). Nghiên cứu mô tả cắt ngang trên 49 người bệnh đã được chẩn đoán xác định CTD bao gồm xơ cứng bì hệ thống (systemic sclerosis - SSc), lupus ban đỏ hệ thống (systemic lupus erythematosus - SLE), viêm đa cơ/viêm da cơ (polymyositis/dermatomyositis - PM/DM) và bệnh mô liên kết hỗn hợp (mixed connective tissue disease - MCTD), điều trị tại Trung tâm Dị ứng - Miễn dịch lâm sàng, Bệnh viện Bạch Mai từ tháng 8/2023 đến tháng 2/2024. Độ tuổi trung bình đối tượng nghiên cứu là 57,8 ± 12,1 (tuổi), chủ yếu là nữ giới (~80%), thời gian phát hiện ILD từ khi chẩn đoán CTD là 18,1 tháng. Phân loại theo bệnh, SSc gặp nhiều nhất ở 21/49 trường hợp (42,9%), SLE gặp ở 16/49 người bệnh (32,7%), PM/DM là 9/49 trường hợp (18,4%) và thấp nhất là nhóm bệnh MCTD với 3/49 người bệnh (6,1%). Trên lâm sàng, khoảng 67,3% các trường hợp có biểu hiện ho; 87,5% người bệnh khó thở khi gắng sức trong đó có 29/49 trường hợp mMRC ≥ 2; và trên 75,5% trường hợp phát hiện bất thường khi nghe phổi. Bất thường trên Xquang phổi thẳng chỉ có thể phát hiện ở 50 - 60% các trường hợp. Trên phim chụp cắt lớp vi tính độ phân giải cao (high resolution computed tomography - HRCT), kính mờ, tổ ong và giãn phế quản co kéo là các dạng tổn thương thường gặp nhất. Khi đánh giá hình thái tổn thương, viêm phổi kẽ không đặc hiệu (nonspecific interstitial pneumonia - NSIP) và viêm phổi kẽ thông thường (usual interstitial pneumonia - UIP) là hai hình thái phổ biến trong nhóm ILD-CTD. Qua nghiên cứu, chúng tôi thấy ILD có thể gặp ở hầu hết các bệnh CTD với các dạng và hình thái tổn thương khác nhau. Do đó, cần thăm khám kĩ lâm sàng và có thể chỉ định chụp HRCT sớm để tránh bỏ sót tổn thương ILD ở nhóm bệnh CTD.
Nội khí quản khó không dự kiến trước: Báo cáo 2 ca lâm sàng
Authors: Minh Phạm Quang , Hùng Trần Thanh , Tú Nguyễn Hữu
Published: September 2024

Nội khí quản khó là một trong ba vấn đề lớn trong chuyên ngành gây mê hồi sức cùng với tồn dư giãn cơ và shock phản vệ. Nội khí quản khó có định nghĩa rất đặc biệt, khi một bác sỹ gây mê có kinh nghiệm đặt nội khí quản trên hai lần hoặc trên mười phút mà không được. Tại thời điểm đó bệnh nhân thường đã được dùng thuốc giãn cơ, bệnh nhân không còn tự thở, không thể tự bảo vệ được mình. Vì vậy, việc tiên lượng nội khí quản khó là rất quan trọng. Tuy nhiên, trong thực tế lâm sàng có nhiều trường hợp đặt nội khí quản khó không dự kiến trước nên nguy cơ cho bệnh nhân là rất cao, mặc dù đã có protocol xử lý. Chúng tôi đưa ra hai ca lâm sàng đặt nội khí quản khó không dự kiến trước. Hai bệnh nhân này có bất thường vùng thanh môn, hạ thanh môn nên mặc dù đã nhìn rõ lỗ thanh môn nhưng không thể đưa ống nội khí quản vào đúng vị trí. Chúng tôi phải áp dụng các biện pháp khác nhau để giải quyết kể cả giải giãn cơ tức thì. Qua hai ca này giúp các bác sỹ lâm sàng có thêm phương án cũng như chiến lược phù hợp trước bệnh nhân thực tế không giống như trong protocol.
Mức độ biểu hiện miR-125b trên bệnh nhân u thần kinh đệm
Authors: Chi Đỗ Thị , Thúy Nguyễn Thu , Khánh Trần Vân , Phương Lê Thị , Hệ Đồng Văn , Liên Nguyễn Đức , Hùng Kiều Đình
Published: September 2024

U thần kinh đệm là khối u ác tính xuất phát từ nhu mô não, việc chẩn đoán sớm và điều trị đích đến nay vẫn là một bài toán đối với y học hiện đại. Nhiều nghiên cứu đã chứng minh miRNA có ý nghĩa quan trọng trong cơ chế bệnh sinh của u thần kinh đệm, trong đó miR-125b hoạt động như một gen gây ung thư với mức độ biểu hiện cao nhất trong mô não hứa hẹn trở thành một dấu ấn sinh học hữu hiệu có thể hỗ trợ trong chẩn đoán và điều trị. Nghiên cứu này nhằm tìm hiểu mức độ biểu hiện của miR-125b trong huyết tương 62 bệnh nhân được chẩn đoán xác định là u thần kinh đệm và 62 người chứng khỏe mạnh. Kết quả cho thấy: mức độ hiểu hiện miR-125b thấp hơn có ý nghĩa thống kê ở nhóm u thần kinh đệm (0,77 ± 1,318) so với nhóm chứng (1,165 ± 1,404) (p < 0,001) và ở nhóm bệnh nhân dưới 50 tuổi (0,318 ± 0,312) so với nhóm trên 50 tuổi (1,143 ± 1,678) (p = 0,01). Điều này cho thấy có mối liên quan giữa sự giảm mức độ biểu hiện miR-125b với bệnh u thần kinh đệm và tuổi của người bệnh.
Dấu hiệu “lollipop” của u nội mô mạch máu dạng biểu mô gan (hehe): Báo cáo chùm ca lâm sàng
Authors: Anh Nguyễn Minh , Kiên Nguyễn Trung , Đức Phạm Hồng
Published: September 2024

U nội mô mạch máu dạng biểu mô (HEHE) là một bệnh lý hiếm gặp, khó phân biệt với hầu hết các khối u gan khác về mặt hình ảnh đơn thuần. Nhân 3 trường hợp, chúng tôi muốn nhấn mạnh các đặc điểm hình ảnh cần lưu ý về HEHE này. Trên CHT hoặc CLVT có tiêm thuốc tương phản thì tĩnh mạch, tổn thương u gan đa ổ ngấm thuốc viền có dấu hiệu “kẹo mút” (“lollipop” sign) với u không ngấm thuốc (hình viên kẹo) và tĩnh mạch ngấm thuốc bị cắt cụt khi hướng tới u (hình que). Đây là dấu hiệu đặc trưng mà các bác sĩ chẩn đoán hình ảnh cần phải tìm kiếm khi nghĩ đến bệnh này. Hơn nữa, nó cũng có thể là đặc điểm hỗ trợ cho các bác sĩ giải phẫu bệnh hướng đến chẩn đoán HEHE.