Information Network Research Articles

Optimal Status Updates for Minimizing Age of Correlated Information in IoT Networks With Energy Harvesting Sensors

Optimal Status Updates for Minimizing Age of Correlated Information in IoT Networks With Energy Harvesting Sensors

Safinamide as adjunctive therapy to levodopa monotherapy for patients with Parkinson's disease with wearing-off: The Japanese observational J-SILVER study

BackgroundSafinamide is an effective adjunctive therapy for wearing-off in Parkinson's disease (PD); however, evidence is lacking in older patients and those in the early stages of wearing-off. This study evaluated the efficacy and safety of safinamide as adjunctive therapy in patients with PD treated with levodopa monotherapy in clinical practice. MethodsThis multicentre, open-label observational study was conducted at five sites in Japan. Patients diagnosed with PD and wearing-off initiated safinamide as adjunctive therapy with levodopa monotherapy. Efficacy endpoints were mean changes in Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part I, III, and IV scores; daily ON-time without dyskinesia using 24-h patient symptom diaries; and 39-item Parkinson's Disease Questionnaire (PDQ-39) scores at 18 weeks of treatment. ResultsIn total, 24 patients initiated safinamide (66.7% were aged ≥75 years); the mean duration of wearing-off was 1.2 years. MDS-UPDRS Part III total score, Part IV total score, and PDQ-39 summary index decreased significantly from baseline (mean change −7.0 [p = 0.012], −2.4 [p = 0.007] and − 5.3 [p = 0.012], respectively). There was a non-statistically significant increase of 1.55 h in mean daily ON-time without dyskinesia. Numerical Rating Scale total score for pain (p = 0.015), and scores for OFF-period pain (p = 0.012) and nocturnal pain (p = 0.021) subdomains were significantly improved in the subgroup with pain. Most reported adverse events were classified as mild. ConclusionSafinamide improved motor and non-motor symptoms and quality of life-related measures in older patients with PD in the early stages of wearing-off without new safety concerns. Study registrationUniversity Hospital Medical Information Network in Japan; study ID: UMIN000044341.

Genetic assessment of diverse rice germplasm for yield-related and stress tolerance traits

AbstractThe development of stress-resistant crops without compromising their yield and nutritional quality is one of the major challenges in plant biology. Plant breeders have made considerable effort in developing cultivars with high yield and tolerance to biotic and abiotic stresses. This research aimed to evaluate pre-breeding resources for favorable genes conferring good yield and resistance to biotic and abiotic stresses for rice varietal improvement. Two hundred forty diverse rice cultivars from top countries with which the United States imports and exports rice were selected from the Germplasm Resource Information Network (GRIN) collection, and these were characterized using molecular markers for various desirable traits. Among the cultivars, 16 were used as checks. The genes of various traits evaluated were grain number (Gn1a), panicle weight (WFP), cold stress tolerance (qSCT-11 and qCTS-12), anaerobic germination (AG1 and AG2), rice blast disease resistance (PiB, Pi-ta, Ptr, and Piz), wide compatibility (S5-n), and restoring ability (Rf4). Out of these 240 accessions, 192 have the Gn1a gene, 168 possess the qSCT-11 cold tolerance gene, 139 carry the Rf4 gene, 152 have the qCTS12 cold tolerance gene, 87 have blast resistance genes, and 44 possess the WC gene. None of the 240 accessions possess the WFP (Wealthy Farmer’s Panicle) gene. The selections with favorable genes can be used by breeders as potential donor parents for varietal improvement programs to produce new and promising cultivars with desired specific traits that may contribute towards alleviating global issues related to food security.

L1 Education in Times of Globalization, Digitalization and Super-Diversity

This introduction first briefly sketches the (history of the) International Mother Tongue Education Network (IMEN). IMEN was founded in 1981 as an information and research network that over the years initiated an empirical-interpretive research program focusing on comparative analyses of the rhetoric and practices of L1 education across a dozen of European countries. Main elements of IMEN’s methodology that will be discussed below were the development of different types of research collaboration, a theoretical framework for comparative analysis, and a method for international triangulation. It then describes how, at the turn of the century, IMEN’s way of doing slow science became increasingly threatened by the requirements of publish or perish mainstream research, and how its research program was confronted with the challenges posed to L1 education by processes of globalization, digitalization, and super-diversity, becoming manifest in the superdiverse nature of student bodies, their sociolinguistic and ethnocultural doings, and the increasingly digitalized modes of teaching and learning they are exposed to. All these elements, in one way or another, also have an impact on the teaching-learning practices in mainstream L1 education and consequently must be addressed by IMEN-like studies. Finally this contribution briefly introduces the contributions to this special issue and suggests that they are a strong argument for a renewed interest in international comparative discussion on and around L1 education and a plea to further collaborative research from an empirical interpretive ethnographic perspective on teachers’ professional practical knowledge and classroom practices that can guide our understanding of the ubiquitous school subject L1 education that aims at preparing students for a global, digital, and super-diverse society.

Enriching the Fake News Process of Classifying Model using Deep Learning and Machine Learning Algorithm

Fake news detection has become a pressing issue due to the rapid propagation of misinformation through various online platforms. In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance. Information carefulness on Internet, especially on social media, is an increasingly important concern, but web-scale data hampers, ability to identify, evaluate and correct such data, or so called "fake news," present in these platforms. In this paper, we propose a method for "fake news" detection and ways to apply it on Facebook, one of the most popular online social media platforms. This method uses Naive Bayes classification model to predict whether a post on Facebook will be labelled as real or fake.

Violence Detection in Jails and Mental Asylums

This research investigates the use of Long- term Recurrent Convolutional Networks (LRCNs) for violence detection in video surveillance systems. LRCNs combine the strengths of Convolutional Neural Networks (CNNs) for capturing spatial information and Long Short-Term Memory (LSTM) networks for modeling temporal sequences. This combination allows the system to learn complex spatiotemporal patterns in video data, improving violence detection accuracy in environments like jails and mental health facilities. The project focuses on the integration of the LRCN model with a Telegram bot for real-time alerting and response. Upon detecting violent incidents in the video streams, the LRCN model triggers alerts through the Telegram bot, providing instant notifications to relevant authorities. The Telegram bot facilitates seamless communication and coordination among stakeholders, enabling swift action to mitigate potential risks and ensure the safety of occupants within these facilities. Through rigorous experimentation and evaluation, the effectiveness and reliability of the LRCN-based violence detection system integrated with the Telegram bot are demonstrated. The research contributes to advancing technology-driven solutions for proactive security measures in high-risk environments, fostering safer and more secure institutional settings

Comparative Legal Analysis of IT Legislation of Russia and Sweden

INTRODUCTION. This article provides a compre­hensive analysis of the regulatory frameworks govern­ing the information technology (IT) sector in both Russia and Sweden and encompasses a comparative assessment of key legal instruments, concepts, and regulatory approaches, including the responsibility for cybercrimes, licensing procedures, standardization practices, and the safety of critical informational in­frastructure. Additionally, this article examines the roles and functions of major governing authorities in both countries.MATERIALS AND METHODS. The article is based on relevant legal acts of Russia and Sweden. While there are certain specific laws focused entirely on the informational technologies, some provisions can be found in other types of legal documents (for example criminal codes or governmental regulations). Employ­ing a comparative approach, the study delineates the scope and authority of state institutions involved in the IT sphere.RESEARCH RESULTS. Both Russian and Sweden exhibit similarities when it comes to definition of es­sential concepts such as critical infrastructure, reflect shared concerns regarding for example security issues. Main laws in the area of information technology con­tain a spectrum of key terms, including but not limited to information and communication network / elec­tronic communication network, information system operator, and information protection / network and information system security. Although the list of key definitions may appear quite similar, the Swedish leg­islation tends to offer broader definitions with the in­tention of encompassing larger domains within IT technologies, while the Russian legislators focus on more specific terms. However, while Sweden aligns closely with European Union (EU) regulatory frame­work, Russia adopts a more expansive approach, ad­dressing emerging technological challenges such as AI. In conclusion, achieving effective IT regulation neces­sitates finding a balance between international con­sistency and national adaptability to ensure strong cybersecurity, foster innovation, and maintain regula­tory flexibility in a dynamic digital environment.DISCUSSION AND CONCLUSIONS. Sweden’s re­liance on implementing EU regulations has its benefits such as harmonisation, interoperability, adopting the internationally recognised practices, easier market ac­cess, etc. However, this approach may limit the coun­try's ability to meet its specific needs and may mean additional administrative burdens associated with compliance with EU directives. Moreover, changes in EU regulations could lead to a necessity to update do­mestic laws, potentially causing regulatory vacuum or legal collisions, especially in such sphere as the IT sec­tor. Nowadays, when for example the AI and its risks are on the daily agenda one can not look away and wait for the international community to agree on the applicable regulation.

Safety and effectiveness of guselkumab in Japanese patients with psoriasis: 20-week interim analysis of a postmarketing surveillance study.

A 52-week postmarketing surveillance study was initiated to evaluate the safety and effectiveness of guselkumab, a human anti-interleukin 23 subunit p19 monoclonal antibody, in Japanese patients with psoriasis vulgaris, psoriatic arthritis, generalized pustular psoriasis, and erythrodermic psoriasis in real-world practice. Here, we report results of the 20-week interim analysis of the ongoing postmarketing surveillance study. Patients who received guselkumab between May 2018 (the date of commercial launch in Japan) and October 2020 were registered in this study. In total, 411 and 245 patients were included in the safety and effectiveness analysis sets, respectively. Adverse drug reactions (ADRs) occurred in 6.6% (27 of 411) and serious ADRs in 2.2% (nine of 411) of patients. The most frequent ADRs by System Organ Class were "Infections and infestations" (2.4%), with nasopharyngitis being the most frequently observed ADR (0.7%). The mean Psoriasis Area Severity Index score decreased from 11.6 at baseline to 6.5 at week 4 and 2.2 at week 20, with improvements achieving statistical significance at each time point. Clinical Global Impression, Dermatology Life Quality Index, and Nail Psoriasis Severity Index outcomesalso showed substantial improvements. Our findings demonstrate that guselkumab is well tolerated and effective in Japanese patients with psoriasis through 20 weeks of treatment in real-world clinical practice, showing significant effectiveness observed as early as 4 weeks. The study was officially registered with the University Hospital Medical Information Network Clinical Trials Registry with the identifier UMIN000032969.

Optimizing Production Supply Chain With Markov Jump System for Logistics Collaboration

This study employs a novel Markov jump system model to address complexities and uncertainties in modern logistics management, particularly in supply chain logistics information networks. It introduces dynamic memory to tackle issues in traditional static networks, enabling modeling and control of this intricate system. By assessing decision node importance, a novel strategy optimization method is devised. Through information exchange and decision adjustments among cooperating nodes, the overall decision system performance is enhanced, resulting in a comprehensive logistics information coordination mechanism for production supply chains based on the Markov jump system. The research demonstrates that this approach considers node interactions and information exchange, using dynamic memory to improve system adaptability and robustness, ultimately enhancing overall decision performance and stability. This has practical value for decision support and system optimization in production supply chain logistics information networks, offering fresh insights into Markov jump system control.

Botnet detection based on Markov chain and Fuzzy rough set

Botnets now make up a wide range of cyber-attacks, which are a network of infected computers connected to the Internet, with remote control. So far, a lot of research has been done in this field, the proposed methods are based on the signatures of discovered botnets, anomalies, traffic behavior, and addresses. Each method has both advantages and disadvantages. This research proposes a structure for performing identification operations, which is presented in this research based on the Markov chain and is based on behavioral analysis. A disadvantage of the past methods is the inability to receive network information at a very high speed. In this research, it has tried using a solution to receive traffic at a very high speed of about 40 Gbps and analyze it. To be able to perform the analysis with a lower overhead. The proposed method can investigate the behavior of botnets by examining the area of behavior better than the previous solutions, and as a result, during the solutions used by botnets to hide their behavior, it can counter and identify suspicious flows. The accuracy of the proposed method was found to be 96.170%. DOI: https://doi.org/10.52783/pst.390

Quality in care homes: How wearable devices and social network analysis might help.

Social network analysis can support quality improvement in care homes but traditional approaches to social network analysis are not always feasible in care homes. Recalling contacts and movements in a home is difficult for residents and staff and documentary and other sources of individual contacts can be unreliable. Bluetooth enabled wearable devices are a potential means of generating reliable, trustworthy, social network data in care home communities. In this paper, we explore the empirical, theoretical and real-world potential and difficulties in using Bluetooth enabled wearables with residents and staff in care homes for quality improvement. We demonstrate, for the first time, that a relatively simple system built around the Internet of Things, Bluetooth enabled wearables for residents and staff and passive location devices (the CONTACT intervention) can capture social networks and data in homes, enabling social network analysis, measures, statistics and visualisations. Unexpected variations in social network measures and patterns are surfaced, alongside "uncomfortable" information concerning staff time spent with residents. We show how technology might also help identify those most in need of social contact in a home. The possibilities of technology-enabled social network analysis must be balanced against the implementation-related challenges associated with introducing innovations in complex social systems such as care homes. Behavioural challenges notwithstanding, we argue that armed with social network information, care home staff could better tailor, plan and evaluate the effects of quality improvement with the sub-communities that make up a care home community.

Trajectories of Occupational Cognitive Demands and Risk of Mild Cognitive Impairment and Dementia in Later Life: The HUNT4 70+ Study.

The cognitive reserve hypothesis posits that cognitively stimulating work delays the onset of mild cognitive impairment (MCI) and dementia. However, the effect of occupational cognitive demands across midlife on the risk of these conditions is unclear. Using a cohort study design, we evaluated the association between registry-based trajectories of occupational cognitive demands from ages 30-65 years and clinically diagnosed MCI and dementia in participants in the HUNT4 70+ Study (2017-19). Group-based trajectory modeling identified trajectories of occupational cognitive demands, measured by the routine task intensity (RTI) index (lower RTI indicates more cognitively demanding occupation) from the Occupational Information Network. Multinomial regression was implemented to estimate the relative risk ratios (RRRs) of MCI and dementia, after adjusting for age, sex, education, income, baseline hypertension, obesity, diabetes, psychiatric impairment, hearing impairment, loneliness, smoking status, and physical inactivity assessed at HUNT1-2 in 1984-1986 and 1995-1997. To handle missing data, we used inverse probability weighting to account for nonparticipation in cognitive testing and multiple imputation. Based on longitudinal RTI scores for 305 unique occupations, 4 RTI trajectory groups were identified (n = 7,003, 49.8% women, age range 69-104 years): low RTI (n = 1,431, 20.4%), intermediate-low RTI (n = 1,578, 22.5%), intermediate-high RTI (n = 2,601, 37.1%), and high RTI (n = 1,393, 19.9%). Participants in the high RTI group had a higher risk of MCI (RRR 1.74, 95% CI 1.41-2.14) and dementia (RRR 1.37, 95% CI 1.01-1.86), after adjusting for age, sex, and education compared with participants in the low RTI group. In a sensitivity analysis, controlling for income and baseline health-related factors, the point estimates were not appreciably changed (RRR 1.66, 95% CI 1.35-2.06 for MCI, and RRR 1.31, 95% CI 0.96-1.78 for dementia). People with a history of cognitively stimulating occupations during their 30s, 40s, 50s, and 60s had a lower risk of MCI and dementia older than 70 years, highlighting the importance of occupational cognitive stimulation during midlife for maintaining cognitive function in old age. Further research is required to pinpoint the specific occupational cognitive demands that are most advantageous for maintaining later-life cognitive function.

AIGO-DTI: Predicting Drug-Target Interactions Based on Improved Drug Properties Combined with Adaptive Iterative Algorithms.

Artificial intelligence-based methods for predicting drug-target interactions (DTIs) aim to explore reliable drug candidate targets rapidly and cost-effectively to accelerate the drug development process. However, current methods are often limited by the topological regularities of drug molecules, making them difficult to generalize to a broader chemical space. Additionally, the use of similarity to measure DTI network links often introduces noise, leading to false DTI relationships and affecting the prediction accuracy. To address these issues, this study proposes an Adaptive Iterative Graph Optimization (AIGO)-DTI prediction framework. This framework integrates atomic cluster information and enhances molecular features through the design of functional group prompts and graph encoders, optimizing the construction of DTI association networks. Furthermore, the optimization of graph structure is transformed into a node similarity learning problem, utilizing multihead similarity metric functions to iteratively update the network structure to improve the quality of DTI information. Experimental results demonstrate the outstanding performance of AIGO-DTI on multiple public data sets and label reversal data sets. Case studies, molecular docking, and existing research validate its effectiveness and reliability. Overall, the method proposed in this study can construct comprehensive and reliable DTI association network information, providing new graphing and optimization strategies for DTI prediction, which contribute to efficient drug development and reduce target discovery costs.

The Formal and the Informal in the History of Socialist Scholarly Interconnectedness in East Central Europe.

With the emergence of Olympic internationalism, scholarly networking in East Central Europe came to be dominated by the idea of scholars representing their nations, which replaced the previously leading pattern of private elite scholars with extensive international contacts. This also formalised trans-border contacts, which became increasingly seen as international. In this article, we trace the relationship between these formal and informal networks from the late 19thcentury to the end of the socialist period, showing that even as formalisation grew, it depended heavily on avariety of informal connections. Even during the period of socialism, when the state sought to control international exchange, scholars used informality to circumvent politically determined constraints. Nevertheless, these informal contacts were not outside the system, but were an integral part of it and depended on formal preconditions. Concentrating on Czechoslovak-Polish relations we argue that in addressing the issue of the relationship between the formal and the informal, acombination of sources must be used, which should then be scrutinised for the stories their authors wish to tell. While archival sources are used for the formal part, oral histories or memoirs reveal the informal part. In East Central Europe, formal sources are likely to ignore informality, especially when it was associated with illegality, whereas ego-documents, especially those produced after 1989, are likely to ignore or downplay connections to the state and overemphasise informality as ameans of acting outside politics. Thus, writing the history of informality in socialist scholarship, not only in terms of international contacts but also in terms of everyday practices, is away of developing counter-narratives to the state-centeredness of current research, which must be linked to acritical study of the contemporary memory of socialist scholarship that shapes the narratives told in oral history.

The Role of Women in Developing Agriculture by Adopting Strategies for Their Empowerment India

The Role of Women in Developing Agriculture by Adopting Strategies for Their Empowerment India

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

With the rapid development of computer network technology and information technology, the e-commerce mode is constantly innovated and applied, which has injected new vitality into the commercial activities. In terms of technology, advanced technologies such as mobile payment, artificial intelligence, big data and AR technology have been widely used in the field of e-commerce, and the innovation of e-commerce technology has also promoted the enrichment of content and diversification of information dissemination. As a subject of information communication and communication, communication science provides important theoretical support and practical guidance for the development of e-commerce technology. From the perspective of communication science, this paper discusses in-depth the innovation and application of e-commerce technology, aiming to reveal the important role of the principle of communication science in the development of e-commerce technology, and discuss how to promote the sustainable development of e-commerce industry through technological innovation and application.

“We might not have been in hospital, but we were frontline workers in the community”: a qualitative study exploring unmet need and local community-based responses for marginalised groups in Greater Manchester during the COVID-19 pandemic

BackgroundThe response to the COVID-19 pandemic saw a significant increase in demand for the voluntary, community, faith and social enterprise (VCFSE) sector to provide support to local communities. In Greater Manchester (GM), the VCFSE sector and informal networks provided health and wellbeing support in multiple ways, culminating in its crucial supportive role in the provision of the COVID-19 vaccination rollout across the GM city region. However, the support provided by the VCFSE sector during the pandemic remains under-recognised. The aims of the study were to: understand the views and experiences of marginalised communities in GM during the COVID-19 pandemic; explore how community engagement initiatives played a role during the pandemic and vaccine rollout; assess what can be learnt from the work of key stakeholders (community members, VCFSEs, health-system stakeholders) for future health research and service delivery.MethodsThe co-designed study utilised a participatory approach throughout and was co-produced with a Community Research Advisory Group (CRAG). Focus groups and semi-structured interviews were conducted remotely between September-November 2021, with 35 participants from local marginalised communities, health and care system stakeholders and VCFSE representatives. Thematic framework analysis was used to analyse the data.ResultsLocal communities in GM were not supported sufficiently by mainstream services during the course of the COVID-19 pandemic, resulting in increased pressure onto the VCFSE sector to respond to local communities’ need. Community-based approaches were deemed crucial to the success of the vaccination drive and in providing support to local communities more generally during the pandemic, whereby such approaches were in a unique position to reach members of diverse communities to boost uptake of the vaccine. Despite this, the support delivered by the VCFSE sector remains under-recognised and under-valued by the health system and decision-makers.ConclusionsA number of challenges associated with collaborative working were experienced by the VSCE sector and health system in delivering the vaccination programme in partnership with the VCFSE sector. There is a need to create a broader, more inclusive health system which allows and promotes inter-sectoral working. Flexibility and adaptability in ongoing and future service delivery should be championed for greater cross-sector working.

The construction of sports tourism projects under the strategy of national fitness by wireless sensor network

Abstract In recent years, sports events have continuously attracted people’s attention, and people’s enthusiasm and participation in sports have been rising. The sports + tourism model can meet people’s travel needs and enjoy sports-related entertainment and experiences. With the expansion of sports tourism, people have a new understanding of sports + tourism. Sports tourism based on the current strategic background of national fitness is an emerging industry, and it has had a certain degree of development prospects before this. This article explores traditional sports tourism with national characteristics under the blessing of the wireless sensor network. This exploration discusses and explores the development and construction of local sports + tourism in terms of literature and logical analysis. The experimental results of this article show that most consumers are not satisfied with the construction of sports tourism network information, and they are the least satisfied with key information coverage, e-commerce, and security systems. It shows that in these aspects, the construction of sports tourism informatization is relatively lagging, and it is in urgent need of improvement and improvement.

Towards a knowledge-based decision support system to foster the return to work of wheelchair users

Accidents at work may force workers to face abrupt changes in their daily life: one of the most impactful accident cases consists of the worker remaining in a wheelchair. Return To Work (RTW) of wheelchair users in their working age is still challenging, encompassing the expertise of clinical and rehabilitation personnel and social workers to match the workers’ residual capabilities with job requirements. This work describes a novel and prototypical knowledge-based Decision Support System (DSS) that matches workers’ residual capabilities with job requirements, thus helping vocational therapists and clinical personnel in the RTW decision-making process for WUs. The DSS leverages expert knowledge in the form of ontologies to represent the International Classification of Functioning, Disability, and Health (ICF) and the Occupational Information Network (O*NET). These taxonomies enable both workers’ health conditions and job requirements formalization, which are processed to assess the suitability of a job depending on a worker’s condition. Consequently, the DSS suggests a list of jobs a wheelchair user can still perform, exploiting his/her residual abilities at their best. The manuscript describes the theoretical approach and technological foundations of such DSS, illustrating its development, its output metric, and application. The developed solution was tested with real wheelchair users’ health conditions provided by the Italian National Institute for Insurance against Accidents at Work. The feasibility of an approach based on objective data was thus demonstrated, providing a novel point of view in the critical process of decision-making during RTW.

Healthcare access for pregnant women in a rural developing country context: Formal and informal institutional challenges

This study examines healthcare access for pregnant women in a rural developing country context. Drawing upon institutional theory and Levesque et al’s model of access, the study finds pregnant women face challenges both of a formal and informal nature in accessing healthcare. The findings suggest the need for integrated and collaborative workings across formal and informal institutional networks. Theoretically, the study makes two contributions. First, it adds value to institutional theory by incorporating a dimension of access. Second, it builds upon Levesque et al.’s healthcare access framework by highlighting the role and significance of a third dimension—that is informal institutions, in addition to the current two—formal institutions and individual factors.