bluuebunny/crossref_metadata_2025 huggingface dataset:
A multi-objective dynamic vehicle routing optimization for fresh product distribution: A case study of Shenzhen
Authors: Wang Wenjie , Wen Suzhen , Gao Shen , Lin Pengyi
Published: April 2024

To improve the fast and efficient distribution of fresh products with dynamic customer orders, we constructed a multi-objective vehicle routing optimization model with the objectives of minimizing the distribution costs including freshness-loss cost, cold-chain-refrigeration cost, and delay-penalty cost, and maximizing customer time satisfaction. An improved multi-objective genetic algorithm (GA)-based particle swarm optimization (MOGAPSO) algorithm was designed to quickly solve the optimal solution for the distribution routes for fresh-product orders from regular customers. Furthermore, online real-time orders of fresh products were periodically inserted into the distribution routes with local optimization solutions by applying a dynamic inserting algorithm. Finally, a case study of a fresh-product distribution company in Shenzhen, China was conducted to validate the practicality of the proposed model and algorithms. A comparison with the NSGA-Ⅱ and MOPSO algorithms showed the superiority of the proposed MOGAPSO algorithm on distribution-cost reduction and customer time-satisfaction improvement. Moreover, the dynamic inserting algorithm demonstrated a better performance on distribution-cost reduction.
An artificial neural network analysis of the thermal distribution of a fractional-order radial porous fin influenced by an inclined magnetic field
Authors: El-Shorbagy M. A. , Waseem  , Rahman Mati ur , Nabwey Hossam A. , Habib Shazia
Published: April 2024

Fins and radial fins are essential elements in engineering applications, serving as critical components to optimize heat transfer and improve thermal management in a wide range of sectors. The thermal distribution within a radial porous fin was investigated in this study under steady-state conditions, with an emphasis on the impact of different factors. The introduction of an inclined magnetic field was investigated to assess the effects of convection and internal heat generation on the thermal behavior of the fin. The dimensionless form of the governing temperature equation was utilized to facilitate analysis. Numerical solutions were obtained through the implementation of the Hybrid Cuckoo Search Algorithm-based Artificial Neural Network (HCS-ANN). The Hartmann number (M) and the Convection-Conduction parameter (Nc) were utilized in the evaluation of heat transfer efficiency. Enhanced efficiency, as evidenced by decreased temperature and enhanced heat removal, was correlated with higher values of these parameters. Residual errors for both M and Nc were contained within a specified range of $ 10^{-6} $ to $ 10^{-14} $, thereby offering a quantitative assessment of the model's accuracy. As a crucial instrument for assessing the performance and dependability of predictive models, the residual analysis highlighted the impact of fractional orders on temperature fluctuations. As the Hartmann number increased, the rate of heat transfer accelerated, demonstrating the magnetic field's inhibitory effect on convection heat transport, according to the study. The complex relationship among Nc, fractional order (BETA), and temperature was underscored, which motivated additional research to improve our comprehension of the intricate physical mechanisms involved. This study enhanced the overall understanding of thermal dynamics in radial porous fins, providing significant implications for a wide array of applications, including aerospace systems and heat exchangers.
Detecting affine equivalences between certain types of parametric curves, in any dimension
Authors: Alcázar Juan Gerardo , Çoban Hüsnü Anıl , Gözütok Uğur
Published: April 2024

Two curves are affinely equivalent if there exists an affine mapping transforming one of them onto the other. Thus, detecting affine equivalence comprises, as important particular cases, similarity, congruence and symmetry detection. In this paper we generalized previous results by the authors to provide an algorithm for computing the affine equivalences between two parametric curves of certain types, in any dimension. In more detail, the algorithm is valid for rational curves, and for parametric curves with nonrational but meromorphic components, it admits an also meromorphic, and in fact rational, inverse. Unlike other algorithms already known for rational curves, the algorithm completely avoids polynomial system solving, and instead uses bivariate factoring as a fundamental tool. The algorithm has been implemented in the computer algebra system ${\mathtt{Maple}}$ and can be freely downloaded and used.
Reconfigurable Antenna System for 5G/6G
Authors: Dwivedi Smrity
Published: April 2024

The timely upgradation in 5G technology standards has already been released by third generation partnership project, which enabled the researchers to refine the research to improve the communication and support in the development. After development of fifth generation technologies, researchers, scientists, and engineers are looking for wide bandwidth which should improve wireless systems and devices to provide better services and experiences. Because of that, beyond 5G, a sixth generation is the next step to be widely used in early 2028 or intensively used around 2030 as per demand. Parameters like gain, bandwidth, efficiency, size of the antenna, technique of fabrication, and other useful quantities can be modified and maximized, and also the cost of fabricating such antennas will be reduced and developed.
Exploring the Past and Identifying the Future Research Agenda for Social Media and Tourist Behavior
Authors: Sharma Nidhi , Khatri Bhanupriya , Khan Shad Ahmad
Published: April 2024

A bibliometric analysis was utilized in the study to incorporate current knowledge in the domain of social media and tourist behavior from 202 research papers published between 2012 and 2023. Scopus academic database was employed to collect the data. To recognize contributions from specific authors, sources and countries, the research conducted performance (recent trends), bibliometric analysis (bibliographic coupling, citation, co-citations, and co-word). Further, network analysis (thematic maps) was used to find out the emerging themes in the field of social media and tourist behavior providing major insights into past study in the topic and suggesting future research directions. The VOS viewer and R software were used for all analyses.
Accessibility in Digital Health
Authors: Koukopoulos Anastasios , Danias Nikolaos
Published: April 2024

Recent advances in artificial intelligence have led changes to the operation, the capabilities, and the performance of a number of industries. Provision of mental health services is expected to experience a paradigm shift, with the introduction of artificial intelligence-based virtual conversational agents (VCAs). In this conceptual chapter, the authors introduce the term Personalised Anthropomorphic VCAs (PAVCAs). The chapter proposes the use of PAVCAs to support people suffering from Prolonged Grief Disorder (PGD), following the loss of a beloved person, aiming to offer solace and companion. To drive meaningful change for the users and to deliver economic value and utility, the chapter argues for PAVCAs to be configured to characteristics of each user's beloved deceased one. Using two models, the authors suggest that the use of these platforms can comprise a reactive approach to the diagnosis of PGD; as well as a proactive approach, dealing with grief before PDG is manifested.
Model Classification Using an Extreme Gradient Boosting Algorithm to Predict the Post-Translational Modification (PTM) Glycosylation in Sequence O
Authors: Pramanik Sabyasachi
Published: April 2024

Glycosylation is one kind of post-translational modification. The most challenging modification to proteins is glycosylation. Glycosylation has also been connected to a number of diseases, such as diabetes, cancer, and the flu. It is important to anticipate glycosylation as a result. The manual lab method for calculating glycosylation requires costly upkeep and equipment. Computer technology is required to improve it by making glycosylation predictions faster. The purpose of this work was to increase sequence O post-translational modification glycosylation prediction accuracy. This study employs a more effective gradient augmentation approach called extreme gradient boosting. Experiments with the following feature extraction types—AAindex, hydrophobicity, solubility, composition, CTD, and PseAAC—help to improve this accuracy. MRMR is the method used for feature selection. The study's findings show that sequence O's post-translational modification glycosylation can be predicted with 100% accuracy.
Future Directions in the Application of Machine Learning and Intelligent Optimization in Business Analytics
Authors: Mishra Reeta , Tripathi Padmesh , Kumar Nitendra
Published: April 2024

This study envisions the future trajectory of intelligent optimization and machine learning (ML) in the realm of business analytics, introducing novel perspectives. It investigates the synergy between big data analytics and ML, underscoring the effectiveness of deep learning architectures in unravelling complex patterns. Emphasizing interpretability, the study explores the development of ML models tailored for business contexts and delves into decentralized model training and data privacy through edge computing and federated learning. In the optimization domain, it addresses the ascendancy of customized meta-heuristic algorithms and explores the convergence of optimization and ML for heightened operational efficiency. This research contributes to a nuanced understanding, fostering innovative applications in the dynamic landscape of business analytics. It has been observed that machine learning and intelligent optimization techniques are very useful for business analytics.
Exploring the Impact of Deep Learning and Neural Networks on Business Analytics
Authors: Chandra Yogesh , Panda Manjuleshwar
Published: April 2024

This chapter explores the substantial uses of deep learning and neural networks in scientific business analytics, as well as how they are transforming the field. The story walks readers through the incorporation of data science into scientific business analytics, starting with an overview of the fundamental ideas and technological history of these tools. An in-depth examination of neural network topologies is necessary before delving into their use in various commercial contexts. The story ends with a prospective examination of upcoming developments and trends, pondering the future of scientific business analytics in the era of developing deep learning technologies and the growing significance of artificial intelligence. This chapter, in its whole, offers readers a thorough exploration of the complex world of deep learning and neural networks, providing them with an understanding of the significant influence these technologies have on scientific business analytics, ranging from fundamental ideas to real-world applications and implications for the future.
AI-Driven Financial Forecasting
Authors: Kumar Nitendra , Agarwal Priyanka , Gupta Gauri , Tiwari Sadhana , Tripathi Padmesh
Published: April 2024

In today's dynamic and complex financial landscape, accurate and reliable financial forecasting is crucial for businesses to make informed decisions, manage risks, and achieve long-term success. Artificial intelligence (AI) has emerged as a transformative force in the financial industry, offering a powerful set of tools and techniques for enhancing financial forecasting capabilities. This chapter delves into the realm of AI-driven financial forecasting, exploring the role of soft computing techniques in harnessing the power of AI for data-driven financial insights. Soft computing, a branch of computational intelligence, encompasses a suite of methodologies that mimic human reasoning and learning processes to handle complex and uncertain data. A comprehensive overview of AI-driven financial forecasting, highlighting the strengths and applications of soft computing techniques in this domain, has been envisaged beginning by introducing the fundamental concepts of AI in financial forecasting, including data pre-processing, feature selection, and model evaluation. It then delves into the specific applications of soft computing techniques in financial forecasting, exploring their use in various forecasting tasks, such as stock price prediction, exchange rate forecasting, and credit risk assessment. The transformative potential of AI-driven financial forecasting, empowered by the power of soft computing techniques, have also been underscored. The effectiveness of soft computing techniques has been shown through real-world examples and case studies, demonstrating their ability to outperform traditional forecasting methods in various financial scenarios. It also discusses the challenges and limitations of using AI in financial forecasting, emphasizing the importance of data quality, model interpretability, and ethical considerations.
Fuzzy Logic Modelling-Based Measurement Approach for Mental Stress Measurement
Authors: Satapathy Suchismita
Published: April 2024

Mental stress affects performance. With regard to farming, it has been more dangerous with greater fatality rates than any other occupation. The farmers often work on their own for long hours with untrustworthy equipment and in hard climates, with hazardous chemicals and livestock. In addition, they make large financial commitments that expose them to higher levels of financial risks giving them higher levels of mental stress. Thus, an attempt was made in this chapter to identify the key risk factors in farming workplaces in addition to the levels of depression, anxiety, and work stress of farmers of Indian agriculture leading to mental ill health among them, and further to develop a fuzzy-based model considering both these cases in the fuzzy-environment for the evaluation of mental-stress.
Biospheric Reverie
Authors: Komalasari Rita
Published: April 2024

Indoor air quality is a critical yet often overlooked facet of our daily lives. This chapter seeks to shed light on this issue, offering a unique perspective through the lens of bio-inspired textiles. This exploration aims to create awareness and empower individuals to enhance their home environments. The method involved an extensive literature study, extracting insights from biology, design, and awareness campaigns. The results revealed the transformative potential of bio-inspired textile artifacts in raising awareness and fostering a sense of well-being in participants' homes. This research contributes valuable guidelines for decision-making for bio-inspired design, marking a significant milestone in the quest for healthier and harmonious living spaces.
How to Enhance the Cooperation Between Science and Economy Towards a Sustainable Future
Authors: Mosurović Ružićić Marija , Lazarević Moravčević Marija , Paunovic Mihailo
Published: April 2024

Sustainability has emerged as a significant and pressing issue, garnering attention from researchers, institutions, global corporations, and economies, aiming to enhance human well-being comprehensively. Within this Sustainable Development Agenda 2030, Research and Development Institutions (RDI) play an important role as catalysts for societal transformation and researching diverse societal challenges. This chapter analyses the two indicators related to achieving the sustainable development goals: research and development expenditure as a proportion of Gross Domestic Product (GDP) and researchers (in full-time equivalent) per million inhabitants. The research aims to highlight the importance of the scientific research sector as a partner for collaboration with the business community in achieving sustainable development. This chapter will also analyse some data related to Serbia. In the context of developing countries, the concept of sustainability holds great potential for improving their position within the regional context.
Innovation in Tourism and Startups in Eastern India
Authors: Guha Sriparna , Mandal Anirban , Kujur Fedric , Poddar Sandeep , Chakrabarti Samprit
Published: April 2024

Research conducted in the domain of smart city development reveals that the implementation of smart city initiatives has the propensity to draw individuals residing in the surrounding rural areas, as well as a growing influx of tourists. While numerous smart tourisms' approach primarily emphasise the advancement of technology, individuals, and institutional logic, the entrepreneurial ecosystem approach plays a crucial role in enhancing smart destinations. The objective of the current study is to examine novel initiatives pertaining to the advancement of startups in Eastern India. The study employed an exploratory and descriptive research design. Additionally, specific initiatives in the realm of tourist innovation, particularly those associated with startups, were also discovered. The findings of the study indicate that there exist guidelines associated with startups in the study area. The promotion of tourism can be facilitated through the implementation of several initiatives, which have been identified as contributing factors, including the provision of valuable experiences.
The Present of Digital Government
Authors: Guo Yuanyuan , Zhang Teng
Published: April 2024

In the context of digitization, this study meticulously explores the current evolution of government models, with a specific focus on the state of digital governance in China. The progression of China's digital government unfolds across three distinct phases: technology-oriented, mutual transparency-oriented, and people-oriented. Notably, the analysis highlights a critical shift during the people-oriented phase, moving from an initial emphasis on technological deployment to a current priority on mutual transparency and active citizen engagement. Despite the visible progress, a persistent challenge lies in accurately and objectively capturing and articulating these developmental stages. To address this challenge, the study conducts an in-depth examination of case studies corresponding to each phase, unraveling their defining characteristics. The findings suggest a potential trajectory towards a digital government model increasingly prioritizing public participation. With overarching objectives, the study aims to deepen our understanding of the evolution of digital government in China, providing valuable insights into its potential future trajectory. This contribution significantly informs discussions on policy formulation and the continuous development of digital governance, offering a nuanced perspective with a keen focus on Chinese practices that illuminate the present landscape of digital government.
The Role of Emerging Technologies in Shaping the Global Digital Government Landscape
Authors: Tariq Muhammad Usman
Published: April 2024

This chapter explores how new technologies are transforming the face of digital governance worldwide. With a particular emphasis on disruptive technologies like blockchain, artificial intelligence (AI), and the Internet of Things (IoT), the report covers the present uses, obstacles, and prospects of these technologies globally. The first section of the chapter examines the idea of “digital government,” highlighting technology's role in advancing the development of government functions and services. It offers a basic synopsis of several developing technologies and their significance in digital governance. The sections that follow take a close look at particular technologies. Using illuminating case examples to demonstrate successful implementations and their effects on public service delivery, the topic of artificial intelligence (AI) explains its applications in automated public services, predictive policymaking analytics, and AI-driven citizen engagement platforms.
Machine Learning in Medical Imaging
Authors: Singh Vikram , Rani Sangeeta
Published: April 2024

This chapter explores the ethical issues surrounding medical imaging and related applications of machine learning and also covers the regulatory frameworks that control the application of machine learning in medical imaging. It examines the important questions of patient data privacy and the requirement for informed consent for data utilization. Apart from the foregoing, algorithmic bias and transparency issues, highlighting the significance of fairness in medical imagery analyses are also presented. In addition, laws about medical devices are also offered. The global context of medical imaging, looking at how various countries handle the regulatory and ethical ramifications of machine learning in the medical field is also studied. Two case studies highlighting the difficulties encountered by healthcare providers have been presented. The academic contents presented in this chapter are of considerable use to academics, researchers, legislators, physicians, radiologists, and attorneys.
Engineering Applications of Artificial Intelligence
Authors: Lakkshmanan Ajanthaa , Seranmadevi R. , Sree P. Hema , Tyagi Amit Kumar
Published: April 2024

Artificial intelligence (AI) has evolved rapidly over the past few decades, permeating various aspects of our lives and transforming industries. This chapter explores the emerging applications of AI across diverse fields, including healthcare, finance, transportation, education, and entertainment. In healthcare, AI is revolutionizing diagnostics, drug discovery, personalized medicine, and patient care. In finance, AI-powered algorithms are enhancing trading strategies, risk assessment, fraud detection, and customer service. The transportation sector is witnessing advancements in autonomous vehicles, traffic management, and logistics optimization through AI technologies. AI is also reshaping education with adaptive learning platforms, personalized tutoring, and educational analytics. Moreover, in the entertainment industry, AI is driving content creation, recommendation systems, and virtual experiences. Despite the remarkable progress, challenges such as ethical concerns, bias mitigation, data privacy, and regulatory frameworks need to be addressed for the responsible deployment of AI.
Engineering Applications of Blockchain in This Smart Era
Authors: Tyagi Amit Kumar , Kumari Shabnam , Chidambaram N. , Sharma Avinash
Published: April 2024

The advent of blockchain technology has revolutionized various industries, offering novel solutions to age-old problems. In this smart era, characterized by interconnected devices and burgeoning digital ecosystems, blockchain stands out as a transformative force. This chapter explores the emerging applications of blockchain technology in this paradigm shift towards smart systems. One prominent application of blockchain lies in the domain of decentralized finance (DeFi). Blockchain facilitates peer-to-peer transactions, eliminating the need for intermediaries like banks. Smart contracts, powered by blockchain, automate and execute agreements, enabling programmable finance, lending, and asset management. Moreover, blockchain's transparency and immutability enhance trust in financial transactions, fostering financial inclusion and security. In the realm of SCM, blockchain offers unprecedented transparency and traceability. By recording every transaction on an immutable ledger, blockchain enables users to track the journey of products from raw materials to end consumers.
Enhancing Medical Diagnosis Through Multimodal Medical Image Fusion
Authors: Prasad Kashi Sai , Kolli Meghana , Linga Bhargavi , Chikati Sai Shreeya , Veeranki Tiruneswar
Published: April 2024

In the medical domain, multimodal image fusion has emerged as a powerful technique aiming to enhance diagnostic accuracy and clinical decision-making. Image fusion technique combines two or more images from the different imaging modalities to enhance image detail and preserve information. However, single modality imaging fails to provide accurate information necessary for precise analysis and diagnosis. This chapter introduces a flask-based application that integrates multiple medical images, merging brain CT scans and MRI through landmark-based image registration. Then wavelet transform-based fusion techniques combine the registered images, providing a comprehensive view of the brain's neural structure and functions. A CNN model is then employed to identify brain tumors in the fused multimodal images. Following tumor detection, the model categorizes tumors as glioma, meningioma, or pituitary tumor. Through the incorporation of these methodologies, the application supports medical imaging and diagnosis by enhancing accuracy, efficiency, and clinical outcomes.
The Impact of Artificial Intelligence and Machine Learning in Medical Imaging
Authors: Amrita  , Baniya Pashupati , Agrawal Atul , Gupta Bishnu Bahadur
Published: April 2024

A significant fundamental change in healthcare can be seen by the integration of artificial intelligence (AI) and machine learning (ML) with medical imaging (MI). This integration holds the potential to improve patient care standards, change clinical procedures, and improve diagnostic accuracy. This chapter presents the possible impact, addressed challenges, opportunities, and impacts on medical diagnosis of recent advancements and growing advances in the application of AI and ML in the field of MI. The rapid development of AI and ML technologies have pushed MI into a new phase of data-driven healthcare and personalized medicine. Furthermore, the applications of AI and ML in MI are a variety of including automated picture analysis and disease identification to prediction, revolutionizing pathology and radiology, and healthcare management. It also suggests a future in which these innovations will work together to improve patient care, improve diagnostic accuracy, and advance healthcare delivery.
The Transformation of Healthcare Through AI-Driven Diagnostics
Authors: Tariq Muhammad Usman
Published: April 2024

This chapter delves into the transformative effects of artificial intelligence (AI) on healthcare diagnostics, focusing on accuracy, efficiency, and predictability. The thorough analysis is organized around the main thematic parts. The chapter opens with an informative review of AI's role in healthcare diagnostics, laying the groundwork for understanding how AI technologies, such as machine learning and deep learning, transform medical diagnostic processes. The history of diagnostic procedures is explored, emphasizing the transition from old methods to the current era of AI-driven approaches. Finally, this chapter presents a thorough investigation into how AI-driven diagnostics impact healthcare's future. Covering present applications, problems, and future possibilities, it adds to the greater discussion of AI integration in healthcare. It emphasizes the importance of responsible and collaborative growth in this transformational subject.
Emerging Technology Adoption and Applications for Modern Society Towards Providing Smart Banking Solutions
Authors: Pundareeka Vittala K. R. , Ahmad Sayed Sayeed , Seranmadevi R. , Tyagi Amit Kumar
Published: April 2024

The rapid advancement of emerging technologies has brought significant transformations to various sectors, including banking and finance. This chapter explores the adoption and application of emerging technologies in modern society, particularly focusing on their role in providing smart banking solutions. Technologies such as artificial intelligence (AI), blockchain, internet of things (IoT), and biometrics are revolutionizing traditional banking practices, enabling enhanced security, efficiency, and personalized services for customers. Through a comprehensive analysis of current trends and case studies, this chapter highlights the impact of these technologies on improving customer experiences, streamlining operations, mitigating fraud risks, and fostering financial inclusion. Additionally, it discusses the challenges and opportunities associated with the integration of these technologies into banking systems, including regulatory concerns, data privacy issues, and the need for skill development among banking professionals.
Role of Emerging Technologies in Smart Marketing and Smart Business for Modern Society
Authors: Arumugam Senthil Kumar , Pundareeka Vittala K. R. , Gaikwad Smita Manohar , Tyagi Amit Kumar
Published: April 2024

In the digital age, the fusion of emerging technologies with marketing and business strategies has become imperative for staying competitive and meeting evolving consumer demands. This chapter explores the pivotal role of emerging technologies in facilitating smart marketing and business practices in modern society. Through a comprehensive review of literature and case studies, this chapter examines the impact of technologies such as artificial intelligence (AI), machine learning (ML), big data analytics, internet of things (IoT), augmented reality (AR), and blockchain on reshaping marketing and business landscapes. The integration of AI and ML algorithms enables predictive analytics, personalized marketing, and enhanced customer experience through precise targeting and recommendation systems. Big data analytics empowers businesses to derive actionable insights from vast datasets, enabling data-driven decision-making and dynamic market segmentation.
COMPARAÇÃO DE AÇÕES DINÂMICAS DEVIDAS AO VENTO EM EDIFÍCIOS COM DIFERENTES MODELOS NUMÉRICOS
Authors: Antunes de Oliveira Filho Carlos Eduardo
Published: April 2024

O objetivo do trabalho é realizar a comparação de deslocamentos e esforços em edifícios de concreto armado decorrentes de duas abordagens distintas. Por um lado, obter esses resultados advindos da simulação numérica da vento-estrutura por meio do acoplamento fraco entre a dinâmica dos fluidos computacional e a estrutura. Por outro lado, empregar um procedimento simplificado denominado de vento sintético que realiza o cálculo das forças da superfície da estrutura em função do tempo a partir dos parâmetros das características do vento e da estrutura, conforme a norma NBR 6123/88, da frequência ressonante e de seus múltiplos, para criar as cargas permanentes e as cargas flutuantes de vento. Ambas as avaliações devem ser empregadas com o uso do método dos elementos finitos para a análise do edifício em regime linear elástico e em regime transiente com a resolução da equação de movimento dada pelo método implícito de Houbolt de integração direta.
A case of symmetrical subepidermal calcified nodules on the eyelids
Authors: Shimada Yoko , Ono Hiroto , Shimizu Akira
Published: April 2024

Dear Editor, Subepidermal calcified nodules (SCN), are typically asymptomatic, solitary, and idiopathic cutaneous calcinosis. We report a case with two SCN with a symmetrical distribution, where a single nodule was located on the medial aspect of each of the bilateral upper eyelids in a teenage male. [...]
Aspects of public health development in China’s western region
Authors: Zhang Jisha , Luo Jing , Chen Guolei , Zhang Chunyan , Li Lianlian , Ma Taijia
Published: April 2024

The public health level in a country is closely related to national development and quality of life. In order to appraise the level of health services in the western region of China, panel data of 124 prefecture-level units covering the period 2011 to 2021 was used together with a health evaluation index system based on four dimensions: quality of life, environmental situation, the level of health services and longevity. To assess this, we used entropy weights, standard deviation and coefficient of variation together with the geographical detector model that measures the stratified spatial heterogeneity. The results show that although public health services have improved overall, the various dimensions are still not balanced as longevity did not match up everywhere. While the developmental level of the various health dimensions presents a pattern of a relatively smooth increasing gradient in the west-central- east direction, the situation with respect to the north-centralsouth is more uneven with both ups and downs. However, a trend of continuous enhancement of all health dimensions was found with a significant positive correlation of spatial clustering, with hotspots and ‘sub-hotspots’ contracting from north to south, while coldspots and ‘sub-coldspots’ expanded from west to east. This can be seen as the result of multiple factors, with the level of urbanization and economic level as the dominant factors and government guidance, agglomeration capacity and industrial structure being auxiliary.
Retro superior costotransverse ligament space block as an effective analgesia after laparoscopic gastrectomy -a case report-
Authors: Lee Youngin , Bang Seunguk , Chung Jihyun , Moon Jookyoung
Published: April 2024

Background: The retro superior costotransverse ligament space (RSS) block, reported as a novel target in paraspinal block, involves the spreading of local anesthetics into the thoracic paravertebral space through slits around the superior costotransverse ligament . This blocks not only the dorsal rami but also the ventral rami, achieving a reliable complete sensory blockade. Case: We performed an RSS block at the T5, T7, and T9 levels on both sides for postoperative analgesia in two patients who underwent laparoscopic gastrectomy. Both patients showed complete sensory blockade from T4 to L1 on the anterior, lateral, and posterior chest walls in the recovery room. The resting and dynamic pain scores were 0 at 30 min and 6 h postoperatively. The pain score consistently remained below 3 throughout postoperative period. Conclusions: The RSS block provided effective postoperative analgesia in laparoscopic gastrectomy through definitive complete sensory blockade.
Patient with ATTR cardiac amyloidosis presenting with heart failure with reduced ejection fraction
Authors: Gohri Jay , Rao Sudipta , Aggarwal Shailesh
Published: April 2024

ATTR amyloidosis involving the heart solely despite it being a multisystem disease is quite an enigmatic entity. Here is a case of a 65-year-old man presenting with features of heart failure with reduced ejection fraction who on extensive workup and imaging was found to have cardiac amyloidosis of ATTR hereditary variety despite a negative family history. This sporadic case of hereditary transthyretin amyloidosis affecting only the heart was put through profound genetic workup and eventually treated with newer but expensive drugs in the hopes to achieve clinical remission.
Masquerading Spitz naevi on the upper lip: A case report with a brief review of the literature
Authors: Nithya S , Saxena Susmita , Kharbanda Jitin
Published: April 2024

In a scenario where there is an increased incidence of oral squamous cell carcinoma (OSCC) in younger age groups, the diagnosis of pseudo-malignant lesions that mimic the histopathology of a moderate or even high-grade carcinoma becomes imperative for oral pathologists. Though paediatric malignancies such as melanomas and thyroid carcinomas and even OSCCs have been reported in young children, they are rare in the pre-pubertal age group. Melanocytic naevi such as Spitz naevi (SNs) or atypical SNs is, however, more common in this age group and could create some difficulty in diagnosis due to its histological variations that could mimic a malignancy. Hence, the need for a cautious correlation between clinical and histopathological features becomes manifold. Adjunct tools that use diagnostic and molecular techniques such as immunohistochemistry (IHC) and comparative genomic hybridisation (CGH) help in diagnosis and in differentiating certain types of SNs from Spitzoid melanomas or melanomas. A case that histopathologically resembled a moderately differentiated squamous cell carcinoma without any evidence of melanocytic content proved to be a melanocytic naevus after clinical correlation of both age and immunohistochemical analysis. This case report with review brings to light the importance of being aware of such pseudo-malignant lesions in our daily practice.
Research on Establishment and Application of Evaluation System of Urban Energy Strategy Development Indicators under the Perspective of Carbon Neutrality
Authors: Chen Chenyu , Song Yunlong , Ke Xuesong , Ping Yang , Shang Fangze , Xiang Chaoyang , Chen Qiang , Yin Haiwei , Zhang Zhenzhou , Fu Hao , Wu Fan
Published: April 2024

A scientific, comprehensive and integrated assessment of urban energy development is of great significance for the establishment of a clean, low-carbon and efficient urban modern energy system. From the perspective of carbon neutrality, this paper sets 25 evaluation indicators in seven dimensions: energy supply, energy consumption, energy efficiency improvement, clean and low-carbon, safety and reliability, low-carbon transport, and scientific and technological innovation, and constructs a secondary indicator system for evaluating the strategic development of urban energy. The system adopts the hierarchical analysis method to determine the weights of the indicators, the double-baseline progression method to standardize the indicator scores, and finally the weighted composite index method to calculate the level of urban energy strategy development. This paper applies the index system to evaluate the current energy development status of Wenzhou city in 2020 and 2022, and to predict the energy strategy development in 2025 and 2030. The scores of Wenzhou city's urban energy strategy development level in the corresponding four periods are 63.56, 70.59, 77.87 and 85.06, indicating that by 2023, Wenzhou city's urban energy development level will go from medium development to high development. Wenzhou City should accelerate the proportion of renewable energy in the future. It is necessary to complement multiple energy sources and improve the integration of heat, electricity, gas and cold. In terms of end consumption, it is necessary to improve the efficiency of energy use, reduce energy intensity, implement electric energy substitution and form an energy consumption pattern centered on electricity.
Effector Function Characteristics of Exhausted CD8+ T-Cell in Microsatellite Stable and Unstable Gastric Cancer
Authors: Han Dong-Seok , Kwak Yoonjin , Lee Seungho , Nam Soo Kyung , Kong Seong-Ho , Park Do Joong , Lee Hyuk-Joon , Kwon Nak-Jung , Lee Hye Seung , Yang Han-Kwang
Published: April 2024

Purpose Gastric cancer exhibits molecular heterogeneity, with the microsatellite instability–high (MSI-H) subtype drawing attention for its distinct features. Despite a higher survival rate, MSI-H gastric cancer lack significant benefits from conventional chemotherapy. The immune checkpoint inhibitors, presents a potential avenue, but a deeper understanding of the tumor immune microenvironment of MSI-H gastric cancer is essential.Materials and Methods We explored the molecular characteristics of CD8+ T-cell subtypes in three MSI-H and three microsatellite stable (MSS) gastric cancer samples using single-cell RNA sequencing and spatial transcriptome analysis.Results In MSI-H gastric cancer, significantly higher proportions of effector memory T cell (Tem), exhausted T cell (Tex), proliferative exhausted T cell (pTex), and proliferative T cell were observed, while MSS gastric cancer exhibited significantly higher proportions of mucosal-associated invariant T cell and natural killer T cell. In MSI-H gastric cancer, Tex and pTex exhibited a significant upregulation of the exhaustion marker LAG3, as well as elevated expression of effector function markers such as IFNG, GZMB, GZMH, and GZMK, compared to those in MSS gastric cancer. The interferon γ (IFN-γ) signaling pathway of Tex and pTex was retained compared to those of MSS gastric cancer. The spatial transcriptome analysis demonstrates the IFN-γ signaling pathway between neighboring Tex and malignant cell, showcasing a significantly elevated interaction in MSI-H gastric cancer.Conclusion Our study reveals novel finding indicating that IFN-γ signaling pathway is retained in Tex and pTex of MSI-H gastric cancer, offering a comprehensive perspective for future investigations into immunotherapy for gastric cancer.
О начальной задаче для невыпуклозначных дифференциальных
включений дробного порядка в банаховом пространстве
Authors: Obukhovskii Valeri Vladimirovich , Petrosyan Garik , Soroka Maria
Published: April 2024

На основе теории неподвижных точек для уплотняющих операторов
исследуется начальная задача для полулинейных дифференциальных
включений дробного порядка $q\in(1,2)$ в банаховых пространствах.
Предполагается, что линейная часть включения порождает семейство
косинус оператор-функций, а нелинейная часть является
многозначным отображением с невыпуклыми значениями.
Доказываются локальная и глобальная теоремы существования
интегральных решений начальной задачи.
Библиография: 35 названий.
О локально чебышевских множествах
Authors: Shklyaev Konstantin Sergeevich
Published: April 2024

Доказывается, что всякое связное ограниченно компактное локально
чебышевское множество в нормированном пространстве
является чебышевским.
Библиография: 8 названий.
Большие промежутки между суммами двух полноквадратных чисел
Authors: Kalmynin Aleksandr Borisovich , Konyagin Sergei Vladimirovich
Published: April 2024

Пусть $M(x)$ - длина наибольшего подотрезка в $[1,x]$, не содержащего сумм двух полноквадратных чисел. Мы доказываем нижнюю оценку
$$
M(x)\gg \frac{\ln x}{(\ln\ln x)^2}
$$
для всех $x\geqslant 3$. Доказательство опирается на свойства случайных подмножеств множества простых чисел.
Библиография: 8 названий.
Об аддитивной сложности некоторых числовых последовательностей
Authors: Sergeev Igor Sergeevich
Published: April 2024

В работе представлено несколько результатов о сложности вычислений
в модели векторных аддитивных цепочек. Получено уточнение верхней
оценки Н. Пиппенджера сложности класса целочисленных $m \times n$
матриц с ограничением $q$ на размер коэффициентов при $H=mn\log_2
q \to \infty$ до $\min\{m,n\}\log_2 q+(1+o(1))H/\log_2 H+n$.
Асимптотически точно установлена сложность вычисления числа
$2^n-1$ в базисе из степеней двойки: она равна $(2+o(1))\sqrt n$.
На основе обобщенных последовательностей Сидона построены
конструктивные примеры числовых множеств мощности $n$: с полиномиальным размером элементов, имеющие сложность $n+\Omega(n^{1-\varepsilon})$ при любом $\varepsilon>0$, с размером элементов $n^{O(\log n)}$, имеющие сложность $n+\Omega(n)$.
Библиография: 15 названий.
Лапласиан Лихнеровича с точки зрения техники Бохнера
Authors: Alexandrova Irina Aleksandrovna , Stepanov Sergey Evgenevich , Tsyganok Irina Ivanovna
Published: April 2024

Доказываются теоремы об обращении в нуль ядер лапласианов Лихнеровича и Ходжа на полном римановом многообразии, дается оценка собственных значений лапласиана Лихнеровича на замкнутом римановом многообразии.
Библиография: 19 названий.
Предельная теорема для момента максимума случайного блуждания, достигающего фиксированного уровня, лежащего в зоне умеренно больших уклонений
Authors: Anokhina Mariya Andreevna
Published: April 2024

Рассмотрим случайное блуждание с нулевым средним и конечной дисперсией, шаги которого являются арифметическими. Хорошо известен предельный закон арксинуса для момента достижения блужданием максимума. В настоящей работе рассматривается распределение момента достижения максимума при условии фиксации самого значения максимума. Показано, что при совершении максимумом умеренного уклонения распределение момента максимума при правильной нормировке сходится к распределению хи-квадрат с одной степенью свободы. Аналогичные результаты получены в нерешетчатом случае.
Библиография: 9 названий.
Аппроксимация масштабирующими масками
Authors: Lebedeva Elena Alexandrovna
Published: April 2024

Для произвольной непрерывной $2\pi$-периодической функции
$f$, $f(0)=1$, удовлетворяющей неравенству $|f(x)|^2+|f(x+\pi)|^2\leqslant 1$,
построен фрейм Парсеваля всплесков с компактным носителем. Масштабирующая маска фрейма равномерно приближает $f$. Масштабирующая функция имеет стабильные целочисленные сдвиги.
Библиография: 8 названий.
К продолжению ростков решений
Authors: Shananin Nikolai Alekseevich
Published: April 2024

В заметке на модельном примере линейного уравнения в частных производных продемонстрировано, как меняются свойства продолжения ростков обобщенных решений в зависимости от типа дифференциальной системы, порожденной старшим вещественно аналитическим символом уравнения, и принадлежности бесконечно дифференцируемого коэффициента при младшем члене уравнения классу вещественно аналитических функций.
Библиография: 5 названий.
О существовании и свойствах выпуклых продолжений булевых функций
Authors: Barotov Dostonjon Numonjonovich
Published: April 2024

В данной статье изучается задача существования выпуклого продолжения
произвольной булевой функции $f(x_1,x_2,…,x_n)$ на множество $[0,1]^n$.
Построено $f_C(x_1,x_2,…,x_n)$ - выпуклое продолжение произвольной
булевой функции $f(x_1,x_2,…,x_n)$ на множество $[0,1]^n$. На основе
одного конструированного выпуклого продолжения $f_C(x_1,x_2,…,x_n)$
доказано, что для любой булевой функции $f(x_1,x_2,…,x_n)$ существует
бесконечно много функций, каждая из которых является ее выпуклым продолжением
на $[0,1]^n$. Также конструктивно доказано, что для любой булевой функции
$f(x_1,x_2,…,x_n)$ существует единственная функция $f_{DM}(x_1,x_2,…,x_n)$,
являющаяся максимальной среди всех ее выпуклых продолжений на множество $[0,1]^n$.
Библиография: 15 названий.
О периодичности последовательностей Сомоса по модулю $m$
Authors: Ustinov Alexey Vladimirovich
Published: April 2024

Для последовательностей Сомоса конечного ранга доказывается периодичность
повторения остатков по произвольному модулю $m$. В качестве приложения
доказывается периодичность остатков последовательности Сомос-(6).
Библиография: 19 названий.
Об аппроксимативных числах двумерного прямоугольного оператора Харди
Authors: Stepanov Vladimir Dmitrievich , Ushakova Elena Pavlovna
Published: April 2024

В работе получены верхние и нижние оценки на аппроксимативные числа двумерного оператора Харди прямоугольного интегрирования, действующего в весовых пространствах Лебега на $\mathbb{R}_+^2$.
Библиография: 22 названия.
Об ограниченности дробно-максимального оператора, потенциала Рисса и их коммутаторов в пространствах Орлича
Authors: Aliev Araz Rafig ogly , Aliev Rashid Avazaga
Published: April 2024

В работе найдены условия для ограниченности дробно-максимального оператора, потенциала Рисса и их коммутаторов в пространствах Орлича.
Библиография: 16 названий.
Mobile Application to Improve Just-in-Time 2-Way Formative Feedback in Graduate Medical Education
Authors: Rowat Jane , Mhatre Girish , Suneja Manish
Published: April 2024

Background An easy-to-use application to facilitate direct observation and allow for 2-way feedback between residents and faculty is needed.

Objective To develop a mobile-based application (app) with the goals of (1) providing just-in-time feedback to residents; (2) improving timeliness of feedback by faculty; and (3) allowing residents to comment on the value of faculty feedback.

Methods Fifty-one of 69 (74%) internal medicine (IM) residents and 20 of 25 (80%) IM core faculty participated in the study from July 1, 2020, to December 31, 2021. An iOS app was designed by authors with expertise in medical education and application development to capture entrustable professional activities (EPAs)-based feedback (eg, informed consent) based on direct observation of residents’ skills in the workplace. App utilization and narrative feedback characteristics of faculty comments were examined by exporting the data from the database server. The end user satisfaction was examined using a survey instrument.

Results Eighty-seven percent of assessments (117 of 134) initiated were fully completed by residents and faculty. Faculty narrative comments were noted in 97% (114 of 117) of completed assessments and 64% (75 of 117) of residents’ feedback to the faculty contained narrative comments. Eighty-three percent (97 of 117) of comments were behaviorally specific and 71% (83 of 117) contained an actionable item. Eighty-six percent (18 of 21) of residents and 90% (9 of 10) of core faculty stated that this application promoted an educational interaction between them.

Conclusions This app facilitates the efficient completion of EPA-based formative assessments and captures bidirectional feedback in the workplace setting.