Software Services Research Articles

The Influence of Supportive Organizational Climate on Employees’ Innovation Behavior: The Mediating Role of Team Engagement and Work Engagement

This study aims to explore, in the Chinese software and information technology services industry, whether a supportive organizational climate will directly affect employees’ innovation behavior and indirectly affect it through employees’ team engagement and work engagement. So, this study used quantitative research methods, collected 613 questionnaires in six provinces and cities in China, and analyzed data using SPSS26.0 and AMOS23.0. Finally, the result shows that a supportive organizational climate has a direct positive influence on employees’ innovation behavior, and has a positive indirect influence on employees’ innovation behavior through team engagement and work engagement, and the mediating effect is more than a direct effect. This article not only further reinforces the foundations of social cognitive theory and self-determination theory, but also fills the research gap on employees’ innovation behavior in the Chinese software and information technology service industry: provides leaders with support on how to create a supportive organizational climate to promote employees’ innovation behavior, and assists employees in understanding how to stimulate their innovation behavior.

Информационная гигиена как фактор успешной профессиональной деятельности сотрудников уголовно-исполнительной системы

The article examines the issues of information hygiene as a factor of successful professional activity of employees of the penal correction system in the context of digital transformation. The insufficiency of research on information hygiene in the psychology of professional activity of specialists is emphasized. Information (digital) hygiene is a certain set of norms and rules that ensure optimal interaction with information of various kinds, which, in turn, ensures the preservation of professional health, personal resources, professional and personal identity and is one of the factors of success of professional activity in the context of digital transformation. Recommendations on the observance of information hygiene in the official activities of employees of the penitentiary system are given. The directions of the official activity of employees of the penal enforcement system in which the use of information hygiene is significant are highlighted: interaction with various information tools and software service products; organization of interdepartmental electronic interaction with law enforcement agencies and other federal executive authorities; information support for the activities of the Federal Penitentiary Service of Russia; information security and protection of information resources of the Federal Penitentiary Service of Russia; implementation of various projects of digital transformation of the Federal Penitentiary Service of Russia. Two approaches are proposed in training to improve the level of development of digital hygiene by employees of the penitentiary system: within the framework of higher and additional professional education. Considering information hygiene as a complex professionally important quality and a factor of successful performance of employees of the penal enforcement system, it is quite natural that these aspects can serve as the basis for taking into account and developing criteria for the success of professional activity in the future, an expanded description and characterization of generalized labor functions of professional standards by position, clarification of occupational and psychograms, optimization of procedures for professional selection and professional certification of employees of the penitentiary system in the dynamics of the professional path.

Impact of SGLT2 inhibitor dapagliflozin on myocardial protein profile in rats with long-standing Type 1 diabetes mellitus

Abstract Background Sodium-glucose cotransporter 2 (SGLT2) inhibitors have beneficial effects on the cardiovascular system in diabetes mellitus (DM) patients. However, as most trials have focused on Type 2 DM, the impact of SGLT2 inhibitors on Type 1 DM remains unclear. Objective To investigate the effects of long-term treatment with SGLT2 inhibitor dapagliflozin on the left ventricular (LV) proteome in Type 1 DM rats. Methods Male Wistar rats were divided into three groups: Control (C, n=7); Diabetes (DM, n=6); and Diabetes treated with Dapagliflozin (DM+DAPA, n=8) for 30 weeks. Diabetes was induced by streptozotocin (40 mg/kg). Dapagliflozin was added to chow at 5 mg/kg/day. Label-free mass spectrometry was used to assess LV proteome using a nanoAcquity UPLC-Xevo QTof MS system and ProteinLynx Global Server (PLGS) software. Cytoscape software, Cluster Marker, and Cluego plugins were used for bioinformatic analysis. Statistical analysis: ANOVA and Tukey or Kruskal-Wallis and Dunn. Results Dapagliflozin increased body weight (C 574±43; DM 339±31*; DM+DAPA 413±30*# g; p<0.05: * vs C; # vs DM) and reduced glycemia [C 108 (101–111); DM 554 (529–562)*; DM+DAPA 343 (237–416)*# mg/dL; p<0.05: * vs C; # vs DM]. One rat died in C and two in DM+DAPA. A total of 252 differentially expressed proteins were identified. Most proteins identified in the networks were downregulated in DM vs C and upregulated in DM+DAPA vs DM. Six proteins related to energy metabolism (Atp5j, P21571; CKm, P00564; Ak1, P39069; Atp5h, P31399; Mdh1, O88989; and Idh2, P56574), four involved in myocyte excitation-contraction (Act1, P68065; Casq2, P51868; SERCA1, Q64578; and SERCA2a, P11507), and two associated with oxidative stress (Sod1, P07632; and Sod2, P07895) were upregulated in DM+DAPA x DM. Comparing DM with C, the KEEG Pathway with the highest percentage of gene associations for upregulated proteins was related to gap junction (25.6%), necroptosis (25.6%), and fatty acid degradation (25.6%), and for downregulated proteins was related to Alzheimer disease (27.3%), cardiac muscle contraction (25%) and glycolysis/gluconeogenesis (13.6%). Comparing DM+DAPA with DM, the KEEG Pathway with the highest percentage of gene associations for upregulated proteins was related to Parkinson disease (18.3%), cardiac muscle contraction (14.2%), citrate acid cycle (9.47%), necroptosis (8.88%), and cGMP-PKG signaling (7.10 %), and for downregulated proteins was related to ketone bodies synthesis and degradation (100%). Conclusion Dapagliflozin is safe and prevents changes in the expression of proteins related to energy metabolism, cardiac muscle contraction, and oxidative stress in Type 1 diabetes mellitus rats. These results offer new insights into the cardioprotective mechanisms of dapagliflozin in Type 1 diabetes mellitus.

The impact of current academic knowledge on modern human resource practitioners’ performance within the software industry of Pakistan- Future of HR work & the need to Reskill

This research endeavors to analyze the effect of latest HR practices on the effectiveness of current HR Managers’ performance in the software industry of Pakistan. The latest quality HR practices (i.e. Technical recruitment & selection, HR Technology, HR Marketing, Dynamic Workforce & Performance Mgmt., Psychology & Stress Mgmt., Green HRM and Workspace Spirituality, Celebration & Recognition Mgmt. and Strategic HR Partnership & Organization Development) have been apportioned to contemplate the effectiveness of current HR knowledge model and its significance in HRs’ professional life. A structured questionnaire is employed as an instrument for data collection. Sample size of 120 employees has been fetched working in HR department of different software companies in Pakistan. The data has been analyzed through Multiple Regressions, Cronbach alpha, demographic and descriptive statistics that are used for various analyses by the help of statistical software SPSS. It highlights a judgmental analysis on the significance of redesigning the current HR knowledge model with modern add-on HR aspects for coping with the challenges that HR students are facing in their professional life presently. Some recommendations have been cited by the author for real-time contribution in HR sector and for escalating the performance professionally. Moreover, this research would accommodate the selected software service sector companies that are operating in developing countries like Pakistan and working on the significance of service industry. The outcomes will be useful for the academicians, researchers, HR practitioners, planners and policy makers who are involved in the concerned area.

AI Revolution: How Malaysian Firms are Redefining Accounting Performance

Artificial Intelligence (AI) is the primary force behind the organization's continued sustainability and competitiveness. The rise of AI software, cloud computing-based software and blockchain apps and services, together with the use of accounting information outcomes indicate that computerized accounting has become available to accountants. Even if there are great hopes for the application of AI in the accounting industry, numerous nations with little infrastructure are still lagging in using this type of technology. 88.89% of the 80 questionnaires that were initially issued were returned within a week. As a result, of the 80 questionnaires issued, 75 responses were received in one week, yielding a response return rate of 93.75 percent. Managerial and non-managerial staff members from American Express (Malaysia) Sdn. Bhd, Selangor, Malaysia were chosen as research participants. By employing a sample random sampling approach, a total of 75 legitimate surveys were gathered. The results of the study have shown a positive strong relationship between the level of readiness (AI Software, Cloud technology and Blockchain) and level of adoption (AI Software, Cloud technology and Blockchain) in the accounting industry toward employees’ job efficiency. All eight hypotheses (H1 to H8) showed a significant relationship and were all accepted. The outcome of the moderating effect between working tenure and level of readiness presents a direct impact. However, the level of adoption shows an indirect impact on job efficiency whereas job efficiency shows a direct impact.

Origin & History of ASP SaaS, PaaS and Cloud Computing

This research paper outlines the evolution of cloud computing and software-as-a-service (SaaS) from their origins in 1960s time-sharing systems to microkernel based systems in the late 1980’s. It traces key developments during the period from 1987 to 1988 including the emergence of an Application Service Provider system. It uses methods and models to confirm accuracy of these claims. The paper highlights how the simple migration from mainframe to microkernels overcame the limitations of adoption by the public, ultimately leading to the dominance of SaaS and PaaS as primary models for delivering software and ASP services. This progression represents in a shift towards more flexible, scalable, and accessible computing models that are delivered by services models, by network with management platforms for software as a service (SaaS), platforms as a service (PaaS) and infrastructure as a service (IaaS) customization.

Методологическое обоснование содержания, структуры и программной реализации базы геопространственных знаний территориальных образований

The article deals with substantiating the contents, structure and software implementation of the geospatial knowledge base. The importance and relevance of forming its infrastructure and the corresponding informational base on the territory in modern geoinformatics and cartography are noted. The requirements for the contents, formal and logical representation of the mentioned base, its structure and connections of the elements at the logical level are given. The authors consider the software implementation of the processes of searching and issuing geospatial knowledge in a visualized form at the request of untrained users in the field of geoinformatics and cartography. The requisitions and information on the special original software, which allows observing the contents of the geospatial knowledge base, are shown. The effectiveness of visualizing the geospatial knowledge base through interactive configuration of software elements is substantiated, based on the metadata principle proposed by the authors, two formalisms and an algorithm for creating corresponding services for geospatial knowledge and other related data. These formalisms of the client’s parameters and server software applications are described, a variant of the geospatial knowledge base structure is given, and the requirements for the necessary software for the effective solution of the task are formulated. The authors` solution is considered in the form of a complex of multicomponent software, used at working with geodata and creating their own interactive maps by poorly trained non-professional users

The Role of Digitalization in Economic Growth: Experience of Uzbekistan

With an emphasis on Uzbekistan, the study investigates how digitization promotes economic growth. The precise effects of digitalization elements on economic development are still not well understood, despite the rising body of research on digital economies. Using data from 2010 onward, the study used multiple linear regression to close this gap, looking at variables including software and information services and innovation spending. Information services and GDP growth were found to be strongly positively correlated, but software services had the opposite effect. Spending on innovation had a small but beneficial impact. According to the study, improving digital infrastructure and expanding internet adoption are essential for long-term economic growth, especially in emerging nations like Uzbekistan.

Spatial Distribution and Environmental Correlates of Cataract and Glaucoma Prevalence in Damaturu LGA, Nigeria

Study’s Excerpt/Novelty This study presents spatial analysis of cataracts and glaucoma within Damaturu Local Government Area, Yobe State, Nigeria, leveraging hospital records from Yobe State University Teaching Hospital to identify demographic distributions and spatial trends of these eye conditions. It employs both Arc Map software and Statistical Product and Service Solutions (SPSS) for comprehensive data evaluation, addressing the challenge of string data types in age group records to provide precise demographic insights. The research's emphasis on middle-aged and older individuals' susceptibility and the critical need for targeted healthcare interventions offers new perspectives on managing and mitigating the impact of cataracts and glaucoma in developing regions. Full Abstract The rising prevalence of blindness and vision impairments, particularly due to cataracts and glaucoma, poses significant challenges in developing countries with limited access to essential healthcare services. This paper delves into the spatial analysis of cataracts and glaucoma in Damaturu Local Government Area of Yobe State, Nigeria, aiming to uncover spatial trends and demographic distributions of these eye conditions within the region. Drawing data from Yobe State University Teaching Hospital, where records of patients with Glaucoma and Cataract diseases were periodically documented, the study included a total of 187 patients. An essential aspect of the analysis focused on mapping the age groups affected by cataracts and glaucoma, providing valuable insights into the vulnerability of different age cohorts to these diseases. The data encompassed age groups ranging from 20 to 80 years, with notable concentrations observed between ages 25 to 60 and 25 to 80 years, indicating the higher susceptibility of middle-aged and older individuals. It's noteworthy to mention that due to the nature of data collection at the hospital, the age group values were recorded as string data types, represented by unique values for each case. This necessitates a detailed understanding of the age demographics affected by cataracts and glaucoma to tailor healthcare interventions effectively. To correct any errors or ambiguities, the data was also evaluated and analyzed using the Arc Map software with variables and the Statistical Product and Service Solutions (SPSS) was also be used for analysis along with the administrative boarders. The study's conclusion underscores the critical need for intensified management and treatment of patients with progressive cataracts and glaucoma cases, emphasizing the importance of optic disc excavation and addressing distorted vision fields. These findings align with previous hospital-based studies, highlighting the ongoing challenges and the imperative for targeted healthcare strategies to address the growing burden of these eye conditions comprehensively. In essence, this research contributes valuable insights into the spatial and demographic aspects of cataracts and glaucoma in Damaturu LGA, advocating for focused healthcare interventions and management protocols to enhance patient outcomes and mitigate the impact of these prevalent eye diseases.

Driving economic transition: The impact of cross-border e-commerce policy on the upgrading of service industry structure

Cross-border e-commerce, as an innovative format and model of international trade, plays a crucial role in accelerating the transformation and upgrading of industrial structures, and shaping a modern economic framework. Using panel data from 260 prefecture-level cities in China from 2003 to 2019, this study investigates the impact of the cross-border e-commerce comprehensive pilot area (CBECCPA) policy on the upgrading of service industry structure and its mechanisms using the staggered difference-in-differences (DID) method. The results show that the CBECCPA policy can significantly promote the upgrading of service industry structure. The mechanism analysis reveals that the CBECCPA policy can promote the upgrading of service industry structure by clustering service industry enterprises, bolstering urban innovation, and increasing the scale of trade. Heterogeneity analysis indicates that the impact of the CBECCPA policy on the information transmission, software, and information technology service industry is more pronounced and the policy effect is stronger for those with a lower level of service industry structure and for pilot areas with higher levels of development, developmental foundation, developmental scale, and developmental innovation. Furthermore, the policy effect varies significantly across cities. This study provides empirical evidence and policy insights into the role of the CBECCPA in the upgrading of service industry structure.

Role Of Digital Image Processing In Education And Medical Field

Digital image processing is a technique that uses computer algorithms to analyze images and transform images into better ones.It is an important branch of Telecommunication engineering that deals with the improvisation of reliability and accuracy of the digital communication by employing multiple techniques. Image processing involves many processes such as taking images, preprocessing, image enhancement, transformation and analysis. Variations in pixel values are one of the major challenges faced by image processing. Digital Signal Processing is at the core of virtually all of today's information technology, and its impact is felt everywhere in telecommunications, medical technology, radar and sonar, and in seismic data analysis.Digital Image Processing plays an important role in medical field and education. Various researches has been done and currently popularly used. In education, pictures can be used to enhance student learning and to develop students’ self-esteem, or their utilization can be of little or no value and, if used carelessly, can, in fact, undermine students' self-confidence. Digital health technologies include both hardware and software solutions and services, including telemedicine, wearable devices, augmented reality, and virtual reality. Generally, digital health interconnects health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their patients manage illnesses and health risks, as well as promote health and wellbeing. Digital imaging gives healthcare providers better and more accurate images, which leads to establishing diagnoses sooner, making treatment of the patient more successful.

How green governance empowers high-quality development: An EKC framework-based analysis of ESG and green total factor productivity.

High-quality development represents a fundamental shift in China's economy from scale and speed to quality and efficiency. In this transition, environmental, social, and governance (ESG) practices are not only closely integrated with China's development strategy but have also become a core standard for measuring development quality. Nevertheless, research on how ESG practices specifically promote high-quality development in Chinese enterprises remains limited. Based on the environmental Kuznets curve (EKC) theory framework, this study uses data from the Huazheng ESG Index from 2009 to 2022 and employs fixed effect models, mediation effect models, and heterogeneity analysis to examine the specific impact of China's ESG practices on corporate high-quality development from multiple dimensions. The results show that there is a "U-shaped" relationship between the ESG practices of Chinese listed companies and green total factor productivity (GTFP). Initially, improving ESG practices may temporarily suppress GTFP, but as ESG levels further improve, they exhibit a significant positive impact on GTFP. Corporations significantly boost productivity by alleviating financing constraints and promoting green technological innovation, although the direct impact on technological advancement remains relatively limited. In China's western regions and industries such as manufacturing, electricity, heat, gas, and water production and supply, wholesale and retail, and information transmission, software, and information technology services, the positive effects of ESG on GTFP are particularly evident. Based on these findings, it is recommended that governments and financial institutions collaborate to promote green credit policies and increase support for the research and development of green technologies. Additionally, environmental education and resource use optimization should be strengthened, especially in industries such as agriculture, forestry, animal husbandry, and fisheries, and the exchange of ESG technologies and experiences between industries should be encouraged.

Realizing smart scanning transmission electron microscopy using high performance computing.

Scanning Transmission Electron Microscopy (STEM) coupled with Electron Energy Loss Spectroscopy (EELS) presents a powerful platform for detailed material characterization via rich imaging and spectroscopic data. Modern electron microscopes can access multiple length scales and sampling rates far beyond human perception and reaction time. Recent advancements in machine learning (ML) offer a promising avenue to enhance these capabilities by integrating ML algorithms into the STEM-EELS framework, fostering an environment of active learning. This work enables the seamless integration of STEM with High-Performance Computing (HPC) systems. This integration is facilitated by our developed server software, written in Python, which acts as a wrapper over DigitalMicrograph (version 3.5) hardware modules to enable remote computer interactions. We present several implemented workflows that exemplify this integration. These workflows include sophisticated techniques such as object finding and deep kernel learning. Through these developments, we demonstrate how the fusion of STEM-EELS with ML and HPC enhances the efficiency and scope of material characterization for all of STEM available globally having Gatan, Inc. image filter installed on them. The codes are available on GitHub.

Enhancing industrial IoT with edge computing and computer vision: An analog gauge visual digitization approach

The advent of Industry 4.0 has led to the widespread adoption of Industrial Internet of Things (IIoT) and Computer Vision technologies in manufacturing. However, handling the massive data generated by IIoT poses challenges. To address this, we propose a software and hardware architecture that combines edge computing with IIoT to enable computer vision applications on manufacturing floors. This research contributes to integrating edge computing and IIoT with Computer Vision technologies in manufacturing facilities, offering a cost-effective and scalable solution for machine vision applications. This approach benefits Small and Medium Manufacturers (SMMs) by utilizing low-cost hardware and open-source technologies, enabling them to harness Industry 4.0 advantages. Our approach involves IoT devices using Raspberry Pi microcomputers and USB webcams as clients and a Python-based edge node server software as the central component. Our test case study results show that a centralized edge-computing solution can offer several useability benefits and a significant performance increase over using a non-edge-enabled IIoT approach. The proposed architecture is tested, validated, and verified through a case study focused on the digitization of the readings of analog gauges. Our experimentation results can offer valuable insights and guidance for the broader adoption of edge-enabled IIoT solutions in manufacturing contexts.

Development of a software service for stock price forecasting based on sentiment analysis and autoregressive models

This paper addresses the critical need for efficient market analysis tools in the era of big data and artificial intelligence. We present a novel software service that integrates real-time news sentiment analysis with stock market prediction, enhancing the accuracy and speed of trading decisions. The system employs APIs for data collection, FinBERT for sentiment analysis, and MongoDB for data storage, overcoming limitations of existing platforms like Investing.com and MarketWatch. Our methodology combines sentiment analysis with autoregressive models to forecast stock prices for 11 major companies. The experiment utilized 141 observations, applying multiple regression and binary outcome models. Results demonstrate that investor sentiment significantly affects stock prices for 2 out of 11 companies, with Meta showing a 70 % determination coefficient in price direction changes based on sentiment. The study reveals that incorporating both quantitative (previous stock prices) and qualitative (sentiment) data improves forecast accuracy for certain stocks. This research contributes to the field of financial analytics by providing a more comprehensive approach to stock price prediction, integrating ML models and data analytics to support informed decision-making in dynamic financial markets.

Literature Review on Cloud Computing: A Paradigm Combining Service-Oriented Architecture with Internet-Based Solutions

Cloud computing, a paradigm combining service-oriented architecture with Internet-based network solutions, has rapidly transformed the IT industry by offering on-demand access to shared resources. Key models of cloud services include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These models provide cost-effective, scalable, and flexible alternatives to traditional IT infrastructure, enabling enterprises to outsource hardware, software, and network services. Cloud systems such as Amazon EC2, Google App Engine, and IBM’s Blue Cloud illustrate these benefits, significantly lowering costs through pay-as-you-go pricing structures. However, data security and privacy have become critical concerns, as cloud users must entrust sensitive information to third-party providers. Ensuring data confidentiality and implementing fine-grained access control are essential to maintaining user trust and enabling compliance with legal and organizational regulations. The success of cloud computing in the future depends on overcoming these security challenges, allowing enterprises to fully embrace its potential

Lifetime deals: the role of software service offering in convincing consumers

Purpose This study aims to reveal consumer purchase intentions for Software-as-a-Service (SaaS) lifetime deals and the role of service offerings in shaping these intentions. Design/methodology/approach Lifetime deals − an aggressive market penetration strategy − have the potential to allow startups to gain market share, user base and the cash necessary for growth. However, startups need to mitigate consumer concerns for which service offering design plays a key role. Drawing on expectancy-value and signaling theories, this study developed a research model and then conducted empirical research on 2,173 consumers via choice-based conjoint analysis to reveal the critical service offering attributes for consumer utility in lifetime deals in the SaaS presentation tool market context. After using the hierarchical Bayes model to derive each respondent’s part-worth utilities for service offering attributes, the hypotheses were tested via the factor score regression method. Findings The results show that the service offering attributes of low price, refund option, human support and feature updates enhance consumer utility in SaaS lifetime deals. Three of these four attributes, namely, low price, refund option and feature updates, enhance consumers' purchase intentions by reducing their concerns about the service’s performance, seller and lifespan, respectively. Originality/value This study elucidates consumer purchase intentions for SaaS services in digital marketplaces. By investigating a widespread market entry strategy − lifetime deals − it shows consumer preferences and behavior for these deals in the fast-growing online tools market. This study also shows how startups can use lifetime deals through a well-designed service offering to mitigate various consumer concerns.

O-GlcNAc informatics: advances and trends.

As a post-translational modification, protein glycosylation is critical in health and disease. O-Linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation), as an intracellular monosaccharide modification on proteins, was discovered 40 years ago. Thanks to technological advances, the physiological and pathological significance of O-GlcNAcylation has been gradually revealed and widely appreciated, especially in recent years.O-GlcNAc informatics has been quickly evolving. Clearly, O-GlcNAc informatics tools have not only facilitatedO-GlcNAc functional studies, but also provided us a unique perspective on proteinO-GlcNAcylation. In this article, we review O-GlcNAc-focused software tools and servers that have been developed forO-GlcNAc research over the past four decades. Specifically, we will (1) survey bioinformatics tools that have facilitated O-GlcNAc proteomics data analysis, (2) introduce databases/servers forO-GlcNAc proteins/sites that have been experimentally identified by individual research labs, (3) describe software tools that have been developed to predictO-GlcNAc sites, and (4) introduce platforms cataloging proteins that interact with the O-GlcNAc cycling enzymes (i.e., O-GlcNAc transferaseand O-GlcNAcase). We hope these resources will provide useful information to both experienced researchers and new incomers to the O-GlcNAc field. We anticipate that this review provides a framework to stimulate the future development of more sophisticated informatic tools for O-GlcNAc research.

The integration and challenges of digital economy with the tourism industry: Evidence from the Yellow River Basin in China

As the global economic landscape evolves, the digital economy becomes a central domain, gradually deepening and widening its confluence with diverse fields. This study aims to systematically explain the intricacies and dynamics of the amalgamation of the digital economy with tourism within the Yellow River Basin. The study builds an evaluative framework based on integrative development mechanisms; this study measures the combined development between the tourism industry and the digital economy between 2011 and 2021. After this quantification, it delves into their unified growth spatiotemporal nuances and discerns impediments based on an obstacle degree analysis. As far as development is concerned, a paradigm of “dual-track convergence” is observed in the Basin, showcasing the gradual ascension of digitalization and diversification of tourism. Regarding the coupling coordination degree (CCD), the nexus between the two exhibits temporal dynamics of a “spiral ascent followed by a transient descent” and a spatial “U-shaped differentiation,” undoubtedly reflecting the vivacity and heterogeneity inherent in their integration.Regarding impediments, the analysis reveals a multifaceted dynamism of barriers across various strata. Systemically, the tourism sector encounters escalating hindrances, with digital infrastructure and market breadth constituting predominant sectoral bottlenecks. On the indicator plane, critical limiting factors include tourism's foreign exchange earnings, the influx of inbound tourists, the proliferation of web pages, e-commerce turnover, and the count of corporate entities within the software and information technology services domain. This study is based on the theory of collaborative development and offers nuanced recommendations by dissecting the co-progress of tourism and the digital economy. The insights tendered herein profoundly impact China and the global community in fostering the common proliferation in both fields.

A Novel Method for Optimising Energy Efficiency in High-Performance Computing Systems

This paper introduces a new method to promote energy efficiency in computing systems. The rapidly growing demand for computational power in high-performance computing (HPC) systems is accompanied by a significant increase in energy consumption. This research investigates the many ways to minimise energy consumption in HPC systems without sacrificing computational performance. Building upon previous research we combined and refined ideas to develop an optimised approach. Our method utilises a tri-modular framework incorporating an Energy-Efficient Hardware Design, Resource Management, and Optimisation, and Server Virtualisation. The first module employs a method of designing smart energy-efficient hardware. This method incorporates leakage reduction techniques such as clock gating and sleep states. The second module uses a technique focused on optimising server software. This method is based on Dynamic Voltage and frequency scaling (DVFS) for power management in data centres. The third module is based on server virtualisation and employs software to create multiple virtual machines on a single physical server allowing for a significant reduction in energy and hardware costs. The methods used in these three modules are systematically integrated to produce a more efficient consumption of electricity. This will allow for the computing system to minimise energy consumption without compromising computational power.