Software Services Research Articles

Концептуальный подход к построению платформы для рынка данных

The value of the data relates to the programs processing them. This intuitive consideration could be sup-ported by the formal grounds of an algorithmic approach to the definition of information. Proposed by Kolmogo-rov, this approach operates with information in terms of a program and a programming method that transform objects. This formalism suggests a natural way to increase the value of data by building a platform designed to connect datasets with the processing programs. The article describes a conceptual scheme of such a platform. Provided with software services for navigation through the datasets, pricing services and services to support price matching procedure the platform could facilitate data usage and influence their value.

Shifting Tides: A Closer Look at the Changing R&D Investments of US Multinationals Abroad

2021 was the first year in which US multinationals abroad spent more on R&D in services than in manufacturing. This reflects a fundamental shift in the R&D activities of US MNEs, and in our perceptions of R&D internationalization. Information, software, business, and scientific services have displaced automotive or pharmaceuticals as the main R&D investing industries. This shift also changes the relative importance of host countries; the European Union, with its specialization on manufacturing, is losing ground against Asian economies, but also other OECD countries.

A Vision for the Future of Materials Innovation and How to Fast-Track It with Services.

Today, we witness how our scientific ecosystem tries to accommodate a new form of intelligence, artificial intelligence (AI). To make the most of AI in materials science, we need to make the data from computational and laboratory experiments machine-readable, but while that works well for computational experiments, integrating laboratory hardware into a digital workflow seems to be a formidable barrier toward that goal. This paper explores measurement services as a way to lower this barrier. I envision the Entity for Multivariate Material Analysis (EMMA), a centralized service that offers measurement bundles tailored for common research needs. EMMA's true strength, however, lies in its software ecosystem to treat, simulate, and store the measured data. Its close integration of measurements and their simulation not only produces metadata-rich experimental data but also provides a self-consistent framework that links the sample with a snapshot of its digital twin. If EMMA was to materialize, its database of experimental data connected to digital twins could serve as the fuel for physics-informed machine learning and a trustworthy horizon of expectations for material properties. This drives material innovation since knowing the statistics helps find the exceptional. This is the EMMA approach: fast-tracking material innovation by integrated measurement and software services.

GREEN ACCOUNTING, CORPORATE SOCIAL RESPONSIBILITY AND FINANCIAL PERFORMANCE EVIDENCE FROM MANUFACTURING COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE IN (2015-2020)

Purpose - This research aims to examine the influence of Green Accounting and Corporate Social Responsibility on financial performance. The sample in this research is 26 companies listed on the Indonesia Stock Exchange for the 2015-2020 period Design/methodology/approach - Purpose Sampling method. The data used in this research is secondary data obtained from the Company's financial reports and annual reports have been published on the official website of the Indonesia Stock Exchange (IDX) (www.idx.co.id) during the 2015-2020 period. This research uses multiple linear regression analysis. The data in this research is processed using SPSS software (Statistical Product and Service Solution) version 23. Finding - The results of this research show that Green Accounting has no effect on financial performance and Corporate Social Responsibility (CSR) has a significant negative effect on financial performance. Originality -

Molecular Docking, Molecular Dynamics Simulation, and Analysis of EGFR-derived Peptides against the EGF

Background: The epidermal growth factor receptor (EGFR) is a member of the tyrosine kinase receptor family known as ErbB. The EGFR signaling pathway is an important regulator of cell proliferation, differentiation, division, and survival, as well as cancer development in humans. Epidermal growth factor, betacellulin, amphiregulin, transforming growth factor and heparin-binding EGF-like growth factor are high-affinity ligands of EGFR. Objective: Tumor progression can be effectively prevented by inhibiting EGF/EGFR interactions. In this study, many anti-EGF peptides targeting EGFR binding regions were designed, modeled, and evaluated. After selecting the peptides with the highest binding energy to the EGF, the interactions between the candidate peptides and all of the key EGFR ligands were investigated. Methods: To identify an EGF-binding peptide capable of blocking EGFR-EGF interactions, large-scale peptide mutation screening was performed. Using the AntiCP server, several possible peptides with anticancer properties were identified. The ClusPro analysis was performed in order to analyze the interactions between EGF and all of the library peptides. A total of five peptides with favorable docking scores were identified. The stability of three peptides with the best docking scores in complex with EGF was verified, applying molecular dynamics simulation with the help of the GROMACS software package. Finally, the interaction of candidate peptides with transforming growth factor-alpha, heparin-binding EGF-like growth factor, and betacellulin was investigated using the ClusPro server. Results: After the screening of modeled peptides by the ClusPro server and GROMACS software, two anti-EGF peptides of Pep4 and Pep5 with 31 residues were developed. Then, we demonstrate that both of these peptides can bind to the other high-affinity ligands of EGFR and block TGFA/EGFR, HBEGF/EGFR, and BTC/EGFR interactions. Conclusion: The findings suggest novel insights for developing therapies based on peptides for inhibiting the EGF, TGFA, HBEGF, and BTC signaling cascade in cancer cells. Pep4 and Pep5 designed in this work, are recommended as potentially promising anticancer peptides for further experimental evaluation.

Estimation of industry-level basic digital capital services in China: A variable depreciation rate estimation method based on DSGE

Accurately measuring the input of digital capital is of great significance for understanding the development pattern of China's digital economy, nurturing new quality productivity, and achieving high-quality development. However, existing representative studies often assume a constant depreciation rate for capital goods, which does not align with reality. In this paper, we address this limitation by introducing dynamic stochastic general equilibrium (DSGE) model that estimates the variable depreciation rate for each capital good. By setting the depreciation rate as a function of capital maintenance expenditures and utilization rates, we provide a more realistic approach. The empirical results obtained through Monte Carlo simulation demonstrate that the trend of depreciation rates for all types of capital goods aligns with China's economic development. Additionally, we find that investment-specific technology shock plays a significant role in affecting changes in the depreciation rates of capital goods. This shock leads to an increase in capital utilization rates and a decrease in capital maintenance expenditures, resulting in higher depreciation rates. Notably, the depreciation rate of basic digital capital is more sensitive to exogenous shock compared to non-digital capital. Furthermore, the paper estimates the basic digital capital service of 19 industries in China from 1981 to 2020. The results indicate a steady increase in the services provided by basic digital capital, with particularly rapid growth observed in industries such as information transmission, software and information technology services, and the financial sector. When comparing our estimation results with those of representative literature, we find that the national-level productive capital stock and the basic digital capital services estimated using our methodology closely align with existing literature. This validation confirms the effectiveness of our methodology and the reliability of the estimated industry-level basic digital capital services.

A new service composition method in the cloud‐based Internet of things environment using a grey wolf optimization algorithm and MapReduce framework

SummaryCloud computing is quickly becoming a common commercial model for software delivery and services, enabling companies to save maintenance, infrastructure, and labor expenses. Also, Internet of Things (IoT) apps are designed to ease developers' and users' access to networks of smart services, devices, and data. Although cloud services give nearly infinite resources, their reach is constrained. Designing coherent and organized apps is made possible by integrating the cloud and IoT. Expanding facilities by combining services is a critical component of this technology. Various services may be presented in this environment based on the user's demands. Considering their Quality of Service (QoS) attributes, discovering the appropriate available atomic services to construct the needed composite service with their collaboration in an orchestration model is an NP‐hard issue. This article suggests a service composition method using Grey Wolf Optimization (GWO) and MapReduce framework to compose services with optimized QoS. The simulation outcomes illustrate cost, availability, response time, and energy‐saving improvements through the suggested approach. Comparing the suggested technique to three baseline algorithms, the average gain is a 40% improvement in energy savings, a 14% decrease in response time, an 11% increase in availability, and a 24% drop in cost.

Methscore: a comprehensive R function for DNA methylation-based health predictors.

DNA methylation-based predictors of various biological metrics have been widely published and are becoming valuable tools in epidemiologic studies of epigenetics and personalized medicine. However, generating these predictors from original source software and web servers is complex and time consuming. Furthermore, different predictors were often derived based on data from different types of arrays, where array differences and batch effects can make predictors difficult to compare across studies. We integrate these published methods into a single R function to produce 158 previously published predictors for chronological age, biological age, exposures, lifestyle traits and serum protein levels using both classical and principal component-based methods. To mitigate batch and array differences, we also provide a modified RCP method (ref-RCP) that normalize input DNA methylation data to reference data prior to estimation. Evaluations in real datasets show that this approach improves estimate precision and comparability across studies. The function was included in software package ENmix, and is freely available from Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html).

Securing the Skies- A Critical Analysis of Cloud Infrastructure Vulnerabilities

Cloud computing offers storage, infrastructure, computing, networking, databases, platform, software, and analytics services over the Internet. It provides numerous benefits including scalability, cost management, broad access to resources, elasticity, resource pooling. Though cloud computing is mature and widely adopted computing model in software as well as non-software industries, it has several issues regarding security as it provides most of the cloud services over the public infrastructure. Denial of service (DOS), malware injection, insecure APIs, data loss, data breaches, hypervisor vulnerabilities, VM escape are a few major issues in cloud computing. In this paper, authors tried to provide a comprehensive analysis of critical security issues in cloud computing. Furthermore, this paper critically analyses the existing solutions to the various security issues in the cloud computing model.

A Descriptive Study of Orgasm in Sexual Satisfaction and Intimacy among Females in India

Background and Aim: Orgasm is the peak of sexual arousal or behavior, whenever the peak of satisfaction is attained. Sexual satisfaction refers to the subjective experience of pleasure, contentment, and fulfillment related to one’s sexual activities and relationships and intimacy is the heart and soul of a close relationship. India is a diverse country with unique cultural, social, and economic factors that can impact women’s experiences in terms of intimacy and sexual satisfaction. The aim is to find out the relationship between orgasm in sexual satisfaction and intimacy among females in India. Materials and Methods: A descriptive research design is used for the present study. Through simple random sampling, 128 females who were married, people who can understand English, and who provided informed consent were selected for the study. The study was conducted from April 2022 to March 2023. The 20-item New Sexual Satisfaction Scale and the 36-item personal assessment of intimacy in relationships, and a semi-structured interview schedule were administered. Data were statistically analyzed using the statistical package for social services software, Version 26.0. A simple percentage analysis was used. The correlation was calculated for the variables. The Pearson correlation method was used to find the relationship between variables. A one-way ANOVA was employed to find out the significant mean difference between the demographic variables with a 95% confidence level, and P < 0.05 was considered statistically significant. Results: The result reveals that there is a relationship between intimacy and sexual satisfaction. Researchers found that there is a significant difference between sexual satisfaction and age, educational qualification, family type, place of living, and orgasm. Conclusion: There exists a positive correlation between intimacy and sexual satisfaction. This study helps to create awareness and promote intimacy, orgasm, and sexual satisfaction among Indian females.

Location choice of foreign direct investment in technical KIBS in China: impact of human capital and intellectual property rights protection

PurposeThis study considers the “technology creation” characteristic of technical knowledge-intensive business services (T-KIBS) and examines how human capital and intellectual property rights (IPR) protection affect the location choice of foreign direct investment (FDI) in China for two types of T-KIBS: (1) information transmission, software and information technology (ICT) services and (2) scientific research and technology (SCI) services.Design/methodology/approachOur empirical analysis is based on panel data on 22 Chinese provinces from 2009 to 2017. We use the generalized method of moments estimation for the regression analysis.FindingsFDI in ICT services prefers regions with high human capital, while FDI in SCI services favors regions with good IPR protection.Research limitations/implicationsFuture research could use more comprehensive data and qualitative interviews to enhance the findings.Practical implicationsThese findings provide a foundation for China’s future policy on attracting FDI into T-KIBS, especially in areas related to human capital and IPR protection.Originality/valueThis study bridges the research gap on the FDI location choice of T-KIBS in China by clarifying the influences of human capital and IPR protection and providing theoretical support for the location choice of T-KIBS FDI.

Measuring and Clustering Heterogeneous Chatbot Designs

Conversational agents, or chatbots, have become popular to access all kind of software services. They provide an intuitive natural language interface for interaction, available from a wide range of channels including social networks, web pages, intelligent speakers or cars. In response to this demand, many chatbot development platforms and tools have emerged. However, they typically lack support to statically measure properties of the chatbots being built, as indicators of their size, complexity, quality or usability. Similarly, there are hardly any mechanisms to compare and cluster chatbots developed with heterogeneous technologies. To overcome this limitation, we propose a suite of 21 metrics for chatbot designs, as well as two clustering methods that help in grouping chatbots along their conversation topics and design features. Both the metrics and the clustering methods are defined on a neutral chatbot design language, becoming independent of the implementation platform. We provide automatic translations of chatbots defined on some major platforms into this neutral notation to perform the measurement and clustering. The approach is supported by our tool Asymob , which we have used to evaluate the metrics and the clustering methods over a set of 259 Dialogflow and Rasa chatbots from open-source repositories. The results open the door to incorporating the metrics within chatbot development processes for the early detection of quality issues, and to exploit clustering to organise large collections of chatbots into significant groups to ease chatbot comprehension, search and comparison.

Organic 6G networks: ultra-flexibility through extensive stateless functional split

With the increase in hardware performance, the 5G mobile network architecture shifted from physical components to software-only micro-services. The very modular network functions can be deployed flexibly on commodity hardware. However, the extensive modularity of these network functions is increasing the number of managed entities, and the core network request latency. Also, it requires extensive procedures to be able to re-select the components for specific devices, a fundamental condition for a potential system scale-down. In this paper, we propose a new organic 6G network architecture that handles these challenges through a new functionality split based on the experience of IT software services. Furthermore, we provide an analysis based on main 5G procedures, showing that the newly proposed architecture is handling the re-selection of functionality significantly better, which is a cornerstone of high-speed scaling (especially scaling-out), as well as migration of functionality and users.

Digital marketing automation

Increased competition in an uncertain digital environment requires new approaches to improving marketing and business efficiency. Automation of business processes and marketing ensures management decisions aimed at improving customer experience by collecting, processing, and analyzing a huge amount of objective customer data from various sources and software services. For the company, it saves time and resources by automating routine processes, and, given the improved customer experience and corresponding loyalty of the target audience, it helps to increase the efficiency of marketing investments and improve the effectiveness of digital marketing (DM) and business. The article is aimed at substantiating the structure of a single user profile based on the integration of ESP and other DM software services with a CRM system. The hypothesis is formulated: creating a single user profile based on the integration of ESP and other DM software services with a CRM system by speeding up communication and improving customer experi­ence will increase the efficiency of DM and business in general. The research was conducted using general scientific and special methods: analysis and synthesis, system-structural analy­sis, comparison, systematic, logical generali­zation of results. Considerable attention is paid to email marketing, which remains one of the most popular DM automation tools, as it allows you to smoothly guide the consumer through the sales funnel with a high return on marketing investment. The effectiveness of integrating a CRM system and an ESP is proved, due to the specialization and functional features of the latter in interacting with consumers via email. The technologies, stages and tools of DM automation are systematized. It is proposed to collect all information about a particular consumer in a single user profile. This requires finding a technical solution for each business process and connecting software services into a single digital ecosystem. Collecting information about the company’s customers and their journey at all points of interaction in one place by integrating the services used into a single user profile allows you to make more effective decisions in marketing and business and achieve business goals

Investigating the Mechanistic of Danhong Injection in Brain Damage Caused by Cardiac I/R Injury via Bioinformatics, Computer Simulation, and Experimental Validation.

Cardiac ischemia-reperfusion (I/R) injury has negative effects on the brain and can even lead to the occurrence of ischemic stroke. Clinical evidence shows that Danhong injection (DHI) protects the heart and brain following ischemic events. This study investigated the mechanisms and key active compounds underlying the therapeutic effect of DHI against brain damage induced by cardiac I/R injury. The gene expression omnibus database provided GSE66360 and GSE22255 data sets. The R programming language was used to identify the common differentially expressed genes (cDEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed, and protein-protein interaction network was constructed. Active compounds of DHI were collected from the Traditional Chinese Medicine Systems Pharmacology database. Molecular docking and molecular dynamics simulations were performed. The MMPBSA method was used to calculate the binding-free energy. The pkCSM server and DruLiTo software were used for Absorption, Distribution, metabolism, excretion, and toxicity (ADMET) analysis and drug-likeness analysis. Finally, in vitro experiments were conducted to validate the results. A total of 27 cDEGs had been identified. The PPI and enrichment results indicated that TNF-α was considered to be the core target. A total of 80 active compounds were retrieved. The molecular docking results indicated that tanshinone I (TSI), tanshinone IIA (TSIIA), and hydroxyl safflower yellow A (HSYA) were selected as core active compounds. Molecular dynamics verification revealed that the conformations were relatively stable without significant fluctuations. MMPBSA analysis revealed that the binding energies of TSI, TSIIA, and HSYA with TNF-α were -36.01, -21.71, and -14.80 kcal/mol, respectively. LEU57 residue of TNF-α has the highest contribution. TSI and TSIIA passed both the ADMET analysis and drug-likeness screening, whereas HSYA did not. Experimental verification confirmed that DHI and TSIIA reduced the expression of TNF-α, NLRP3, and IL-1β in the injured H9C2 and rat brain microvascular endothelial cells. TNF-α can be considered to be a key target for BD-CI/R. TSIIA in DHI exerts a significant inhibitory effect on the inflammatory damage of BD-CI/R, providing new insights for future drug development.

Web Application Penetration Testing on Udayana University's OASE E-learning Platform Using Information System Security Assessment Framework (ISSAF) and Open Source Security Testing Methodology Manual (OSSTMM)

Education is a field that utilizes information technology to support academic and operational activities. One of the technologies widely used in the education sector is web-based applications. Web-based technologies are vulnerable to exploitation by attackers, which highlights the importance of ensuring strong security measures in web-based systems. As an educational organization, Udayana University utilizes a web-based application called OASE. OASE, being a web-based system, requires thorough security verification. Penetration testing is conducted to assess the security of OASE. This testing can be performed using the ISSAF and OSSTMM frameworks. The penetration testing based on the ISSAF framework consists of 9 steps, while the OSSTMM framework consists of 7 steps for assessment. The results of the OASE penetration testing revealed several system vulnerabilities. Throughout the ISSAF phases, only 4 vulnerabilities and 3 information-level vulnerabilities were identified in the final testing results of OASE. Recommendations for addressing these vulnerabilities are provided as follows. Implement a Web Application Firewall (WAF) to reduce the risk of common web attacks in the OASE web application. input and output validation to prevent the injection of malicious scripts addressing the stored XSS vulnerability. Update the server software regularly and directory permission checks to eliminate unnecessary information files and prevent unauthorized access. Configure a content security policy on the web server to ensure mitigation and prevent potential exploitation by attackers.

Proactive Fault Tolerance in Distributed Cloud Systems: A Review of Predictive and Preventive Techniques

In a cloud computing environment, various hardware and software services are provided to the users across multiple servers and data centers. These servers are communicated to each other to allow greater scalability, flexibility, and reliability. Reliability is a vital factor in cloud computing that ensures that the requested services will be delivered to the users whenever they request them. However, different hardware or software faults may occur in cloud servers or data centers that prevent the users from receiving the service. Fault tolerance is defined as the ability of the system to provide services to the users even with the presence of faults or failures. In this review, we focused on some of the emerging fault tolerance techniques researchers have proposed to tackle the fault issues in cloud computing. We divided these techniques into three main categories: proactive and reactive techniques. Proactive techniques involve protecting the system defects by proposing certain procedures to prevent reaching the defective condition. Reactive techniques refer to the ability of the cloud system to recover the defective server or framework to continue working and providing the service.

Asymmetrical individual both left and right otoliths of Tuna Scombrini collected from the Java Sea

Otolith can be used as a natural marker of fish stock or anomalies between individuals within fish stock. This research aims to study the relationships between fish length and otolith length and confirm differences in otolith shape between species in the Scombrini tribe and Carangidae family (Decapterus ruselli). Sample used in our analysis were collected around July - September 2023 from three different location, Rastrelliger brachysoma (Lekok waters, Pasuruan), Scomber australasicus (Bali Strait waters) and Decapterus ruselli (Sendang Biru, South Malang). Total 96 specimens were identified based on morphological character as Rastrelliger brachysoma, Scomber australasicus and Decapterus ruselli. Each of following samples were cut horizontally at the frontal head to open the skull and remove sagitta otolith below the hindbrain using dissecting set, then cleaned and stored dry in microtube 1,5 ml separately for left and right to further documented using Celestron Digital Microscope Pro Gray USB 44308. Otolith morphometric data collected includes maximum length using TpsDig and weight using analytical balance. The relationship between Forked Length (FL) and otolith length, length-weight relationship of otolith was determined using simple linear regression on software Statistical Product and Service Solutions (SPSS). Paired sample t-test was applied to determine asymmetrical size of left and right otoliths. In this study, it was found that the shape of the otoliths between species has differences in the rostrum, antirostrum, ventral and dorsal parts. FL-otolith length relationship of S. australasicus, R. brachysoma and D. ruselli are Y=0,725+0,164X, r2= 0,519; Y=0,191+0,230X, r2= 0,911; Y=3,156+0,075X, r2=0,071 respectively. The LW sagitta relationship shows that there is a very strong relationship (P<0,05) between L and W of otoliths. The results of the Paired Sample T-test showed that there was no significant difference in the size of the left and right otoliths (Sig>0.05). Otolith shape is influenced by fish behaviour, diet and environment and it may be used as additional information to distinguish between tribe or even species. Otherwise, its asymmetric relationship and LW relationship may be potential new methods for stock discrimination and have other implications such as stock assessment, understanding natural asymmetry, and its potential applications in fisheries management and conservation.

A Federated Distributed Digital Forensic Readiness Model for the Cloud

Digital forensics in modern, cloud-based, microservice-based applications are complicated by multiple layers of abstraction, thereby making it difficult to accurately capture and correlate events that occur across these layers due to filtering caused by abstraction. The complexities linked to each layer of abstraction are primarily invisible to subsequent layers. Similarly, software services are often composed of one or more services provided by various service providers across the globe. Investigators are often faced with situations where breaches span over multiple service provider boundaries where not all digital forensic readiness evidence artefacts are captured by the service provider's forensic readiness processes. Instead, digital evidence artefacts are scattered across multiple service provider domains. This paper presents a novel, federated distributed digital forensic readiness model suitable for use in software-as-service, platform-as-service and infrastructure-as-service provider scenarios. The proposed model enables a service provider to capture and inspect forensic readiness artefacts in environments with various layers of abstraction. More importantly, the model also offers a way to share and access forensic readiness artefacts in a forensically sound manner to ultimately ensure that investigators can obtain a clear view of digital forensic events as they occur between amalgamated services provided by one or more separate service providers.

In silico design of potential Mcl-1 peptide-based inhibitors.

BIM (Bcl-2 interacting mediator of apoptosis)-derived peptides that specifically target over-expressed Mcl-1 (myeloid cell leukemia-1) protein and induce apoptosis are potentially anti-cancer agents. Since the helicity of BIM-derived peptides has a crucial role in their functionality, a range of strategies have been used to increase the helicity including the introduction of unnatural residues and stapling methods that have some drawbacks such as the accumulation in the liver. To avoid these drawbacks, this study aimed to design a more helical peptide by utilizing bioinformatics algorithms and molecular dynamics simulations without exploiting unnatural residues and stapling methods. MM-PBSA results showed that the mutations of A4fE and A2eE in analogue 5 demonstrate a preference towards binding with Mcl-1. As evidenced by Circular dichroism results, the helicity increases from 18 to 34%, these findings could enhance the potential of analogue 5 as an anti-cancer agent targeting Mcl-1. The applied strategies in this research could shed light on the in silico peptide design. Moreover, analogue 5 as a drug candidate can be evaluated in vitro and in vivo studies. The sequence of the lead peptide was determined using the ApInAPDB database and PRALINE program. Contact finder and PDBsum web server softwares were used to determine the contact involved amino acids in complex with Mcl-1. All identified salt bridge contributing residues were unaltered to preserve the binding affinity. After proposing novel analogues, their secondary structures were predicted by Cham finder web server software and GOR, Neural Network, and Chou-Fasman algorithms. Finally, molecular dynamics simulations run for 100 ns were done using the GROMACS, version 5.0.7, with the CHARMM36 force field. MM-PBSA was used to assess binding affinity specificity in targeting Mcl-1 and Bcl-xL (B-cell lymphoma extra-large).