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The purpose of the research was to improve the quality of information process control in the interaction of mobile object grouping. This proposal is based on developing and implementing new combined models with algorithms for optimal planning and scheduling of information processes during interaction among mobile objects. The proposed approach would guarantee the required level of aircraft maintenance at the airport. The novel aspect of the proposed solution is that it divides the spatially distributed task of selecting a plan and a schedule for information processes in mobile objects into two subtasks, describing the spatial and temporal features of the original task. The spatial component of the original problem is described as a static model. Using this model, the optimal distribution of information operations over the resources of mobile objects is carried out without binding these operations to time. The time component is described as a dynamic model, within which the information operations are tied to time and the corresponding resources. Examples of construction and research of synthesized plans and schedules are given. Abbreviations: DM, Dynamic model; FIFO, First-In First-Out; Gr, Grouping; HSC, Hardware and software complex; ITS, Intelligent Transport System; IP, Information Processes; MO, Mobile object; PC, Programmed control; SM, Static model; SMS, Special mathematic support; LDM, Logical-dynamic models [ABSTRACT FROM AUTHOR]

We address business schools' need to develop policies and practices informed by researchers' scholarly impact by offering an improved conceptualization and measure that considers contextual and temporal aspects: the Contextualized Scholarly Impact Index (CSII). We also offer software to calculate individual and institutional-level CSII scores. Our measure of scholarly impact (a) considers impact within the context of the management field, (b) relies on quantity and quality dimensions of research impact, (c) incorporates temporal aspects of impact, and (d) yields scholarly impact scores using the latest data from an inclusive set of influential management journals. CSII provides a transparent and multidimensional measure of scholarly impact to informpolicymaking, facilitate benchmarking of research impact, and support researchers in understanding and enhancing their scholarly contributions. Our study contributes to policymaking and practice by improving the theoretical conceptualization of scholarly impact; offering a metric for comparing the impact of individual scholars, research groups (e.g., teams, centers, and institutes), and business schools; aiding funding agencies in making informed decisions; assisting in the training and development of faculty and doctoral students; supporting policies for review, promotion, and tenure; and providing critical information for talent management practices including selection, succession planning, and rewards. [ABSTRACT FROM AUTHOR]

Technology in libraries has played an essential role in serving today's communities. This study provides an overview of the integrated library systems/software (ILSs) used in libraries in South Sulawesi, Indonesia. It aims to highlight the strengths and possibilities of ILSs and briefly explain their advantages and disadvantages along with the cost of implementation. The data was gathered from questionnaires sent via an online survey and from direct interviews with certain academic libraries over the period of 2019 to 2020. Fifty-three of 67 libraries that fulfilled the study have implemented an ILS. To deeply understand the application, a direct interview with some libraries was conducted to learn the advantages and disadvantages. The result of the study showed that the most used ILSs are SLiMS and INLISlite and other programs like Apollo, Athenium Light, Simpus, Spektra, Jibas, KOHA, and Openlibrary. The budget spent is an average of300 USD. While the ILSs have helped these libraries improve services, IT expertise and adequate resources are needed, especially when the systems present problems. An easy-to-use system that costs less will potentially be used in this area of research. This study will be particularly helpful for any library in Indonesia. These findings may also be generalized to libraries in other countries facing economic and technological similarities. [ABSTRACT FROM AUTHOR]

The expeditiously growing interest in Additive Manufacturing (AM) in various domains and applications leads to different challenges in terms of management and optimisation. These issues are due to the vast amount and type variety of data and knowledge generated across the AM value chain. Therefore, it becomes essential to deliver useful help to support information management and critical decisions along the AM product realisation. This paper proposes a knowledge-based Framework for traceability and decision aid in AM processes. The proposed solution is applied in a critical phase concerning process generation and cost estimation at the beginning of AM project. A software demonstrator is deployed in a real industrial case study: Heat Exchanger for Aircraft. [ABSTRACT FROM AUTHOR]

The Journal of Management Information Systems has published a special issue that focuses on two main topics: the interaction between humans and artificial intelligence (AI), and cybersecurity. The first set of papers explores the impact of generative AI on human accomplishment and productivity, as well as the concerns surrounding employment and the survival of humans in the face of AI. The second set of papers addresses the increasing importance of cybersecurity in the face of sophisticated cyberattacks and the need for a broader understanding of cybersecurity and the use of AI to combat these threats. Other topics covered in the issue include the role of AI in employee performance evaluation, the collaboration between AI and humans in demand forecasting, the effectiveness of fear appeals in shaping employee cybersecurity posture, the relationship between IT innovativeness and the risk of data breaches, the impact of avatars on community identification in virtual social worlds, the performance of foreign IT complementors in mobile app startups, the impact of open-source software communities on cryptocurrency prices, the influence of social relationships on online reviews, the digitalization of loyalty in online reward programs, and the optimization of brand offerings in online marketplaces. [Extracted from the article]

In the current media environment, some individuals have shifted from actively monitoring news toward passively waiting for the media to alert them about news to a certain extent, forming a "news-finds-me" (NFM) perception. Drawing on a cross-sectional survey (N = 906) of adults from the United States, this study investigates the relationship between the NFM perception and COVID-19 misperceptions. Findings demonstrated a positive association between NFM perception and misperceptions. Moreover, information avoidance mediated the relationship between NFM and misperception. Finally, need for cognition (NFC) was a significant moderator, such that among those with greater NFC, the indirect effect of NFM perception on misperceptions became weaker. Findings of this study can contribute to the literature of NFM perception in health contexts and provide useful guidelines for combating misinformation and misperceptions in the algorithm-generated information environment. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis is an important and active research field. Most methods construct fusion modules based on unimodal representations generated by pretrained models, which lack the deep interaction of multimodal information, especially the rich semantic-emotional information embedded in text. In addition, previous studies have focused on capturing modal coherence information and ignored differentiated information. We propose a text-enhanced multi-interactive attention and multitask learning network (TEMM). First, syntactic dependency graphs and sentiment graphs of the text are constructed, and additional graph embedding representations of the text are obtained using graph convolutional networks and graph attention networks. Then, self-attention and cross-modal attention are applied to explore intramodal and intermodal dynamic interactions, using text as the main cue. Finally, a multitask learning framework is constructed to exert control over the information flow by monitoring the mutual information between the unimodal and multimodal representations and exploiting the classification properties of the unimodal modality to achieve a more comprehensive focus on modal information. The experimental results on the CMU-MOSI, CMU-MOSEI, and CH-SIMS datasets show that the proposed model outperforms state-of-the-art models. [ABSTRACT FROM AUTHOR]

Background: Understanding the influential factors in attracting foreign patients is possible by evaluating and identifying hospitals' capabilities, strengths, and weaknesses. This study assessed Ahvaz hospitals' readiness to attract health tourists using International Joint Commission (IJC) standards. Methods: This descriptive-analytical study examined 21 hospitals in Ahvaz using IJC standard questionnaires with 76 questions across six fields. Data were analyzed using descriptive statistics and the Mann–Whitney test in SPSS version 22. Results: The overall compliance rate with organization-oriented standards was 79.53%. Staff training and qualification standards scored highest at 81.79%, while information management standards scored lowest at 76.26%. Non-academic hospitals averaged higher scores than academic hospitals, though this difference was insignificant (p > 0.05). Bed occupancy rates ranged from 40.96% to 85.33%, with average lengths of stay between 1.33 and 64.31 days. Conclusion: Ahvaz hospitals demonstrated above-average readiness to attract medical tourists across most dimensions. To enhance their competitiveness, hospitals should prioritize improvements in information management systems, leverage strengths in staff training and qualifications, address disparities between academic and non-academic institutions, and invest in marketing their unique capabilities to potential health tourists. [ABSTRACT FROM AUTHOR]

The rapid digitization of the modern world has led to an increase in the collection and processing of personal data. The principles of transparency and consent have become crucial for citizens to understand how their data is being used and to be able to give their voluntary consent to its processing. Ukraine is actively adapting its legislation to EU standards in the field of personal data protection. In particular, the General Data Protection Regulation (GDPR) affects approaches to data collection and processing. Examining transparency and consent in the context of these changes can help identify which aspects of the law need special attention. Citizens are becoming increasingly cautious about who they trust with their data. This article analyzes and evaluates the role and impact of the principles of transparency and consent on the effective mechanism of personal data protection in Ukraine, taking into account modern technological and legislative challenges. Studying these principles demonstrates their importance and relevance in today’s digital society. The principle of transparency determines the need for accessible and understandable information for data subjects regarding the processing of their data. Openness is a fundamental requirement for maintaining trust between organizations and citizens. Providing the ability to control and regulate their data allows data subjects to play a more active role in the processing and use of their personal data. The principle of consent, in turn, emphasizes the voluntary and informed nature of consent to data processing. The consent of the data subject determines the basis for the legal processing of personal data, ensuring harmony between the rights of citizens and the interests of organizations. As technology advances and legislation changes, transparency and consent become even more important aspects. They help build trust between organizations and citizens, ensure responsible use of personal data, and empower individuals to control their own information. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to explore strategic investment in information management and its crucial role in driving financial innovation. By examining the integration of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Blockchain, Big Data Analytics, Cloud Computing, Large Language Models (LLMs), Robotic Process Automation (RPA), Internet of Things (IoT), Cybersecurity Technologies, and Quantum Computing, this research aims to highlight how these technologies enhance decision-making, operational effectiveness, risk management, and compliance within the financial sector. Methodology: The study employs a comprehensive literature review of existing research to analyze the impact of strategic investment in information management on financial innovation. Key technologies are identified and their applications in finance are discussed. The methodology includes synthesizing findings from various sources to present a cohesive understanding of the relationship between information management, technology, and financial innovation. Results: The results indicate that strategic investment in information management significantly enhances financial innovation by leveraging advanced technologies. AI and ML improve predictive analytics and customer personalization, Blockchain ensures secure transactions and transparency, Big Data Analytics enables data-driven decision-making, and Cloud Computing provides scalable solutions. LLMs enhance natural language processing capabilities, RPA automates repetitive tasks, IoT facilitates real-time monitoring, Cybersecurity Technologies protect financial data, and Quantum Computing offers potential breakthroughs in financial modeling and encryption. Implication: The implications of this study suggest that financial institutions should prioritize strategic investments in information management and the adoption of advanced technologies to stay competitive and resilient in the evolving financial landscape. Effective information management practices enable better decision-making, improved operational efficiencies, enhanced risk management, and regulatory compliance, ultimately fostering financial innovation. Contribution: This study contributes to the existing body of knowledge by providing a detailed analysis of the role of strategic investment in information management and its impact on financial innovation. It highlights the importance of integrating advanced technologies in financial practices and offers insights into how these technologies can be leveraged to achieve innovative solutions and improvements in the financial sector. The findings serve as a valuable resource for financial institutions, policymakers, and researchers interested in the intersection of technology and finance. Article Highlights: Efficient data management leads to better decision-making and improved operational effectiveness. Technology plays a key role in leveraging data for innovation in finance. Risk management and compliance are enhanced through effective information management practices. Collaboration and partnerships foster financial innovation and the development of innovative solutions. [ABSTRACT FROM AUTHOR]

Background: In 2022, India's national tuberculosis (TB) elimination program (NTEP) commissioned a national level evaluation of active case finding (ACF) for TB to guide evidence-based strategic planning. As part of this evaluation, based on secondary data analysis we observed that the quality of ACF was suboptimal in 2021. Hence, this study aimed to understand the enablers, barriers, and suggested solutions to improve ACF for TB in India from NTEP staff (provider) perspective. Methods: This was a descriptive qualitative study involving key informant interviews from six districts and eight states, conducted between February and August 2023. We purposively selected key state- district- and sub-district-level program managers and implementers who were experienced and vocal. The interviews were audio recorded and transcribed verbatim by research interns and investigators. Two investigators independently did manual descriptive thematic analysis, and a third investigator resolved inconsistencies. The themes and categories emerged by collating together the results of the coding process. Results: A total of 34 key informant interviews were conducted and of these, four were repeat interviews. Adequate budgets for ACF including incentives, performance review mechanism, engagement of all stakeholders, adopting a community friendly approach, use of rapid diagnostic tests and digitalization were the perceived enablers. In some states ACF was implemented in general population (not restricted to high-risk population) following directives at state level. There were limited mechanisms to ensure ACF quality indicators were met before disbursing incentives and cross-verification of the aggregate ACF care cascade numbers that were reported in Ni-kshay (electronic TB information management system under NTEP). In addition to the state and district level implementers having limited understanding of concepts around ACF (quality indicators, number needed to screen and yield), we also inferred the presence of a 'know-do' gap for many activities under ACF. The suggested solutions were around capacity building and quality improvement strategies. Conclusion: The existing national ACF guidance should be revised to emphasize capacity building, need to carry out ACF in high-risk (not general) population, quality control-linked incentives, and regular implementation monitoring of the activities. This should contribute towards better coverage and improved quality translating into better ACF outcomes. [ABSTRACT FROM AUTHOR]

Energy management, especially in communities, is attracting growing interest but is often marred by confusion between the terms "energy information system" (EIS) and "energy management system" (EMS). This ambiguity hinders understanding of their uses and roles in improving energy performance. Our objective is to clarify these terms and their contributions to energy management. We used a mixed qualitative and quantitative approach to evaluate and compare the criteria of definition, objective, functionality, and role, as well as correlated elements, such as organizational structure, responsibilities, planning, and policy, according to the requirements of ISO 50001, in addition to criteria specific to the two systems. The study revealed differences in the roles of the EIS and the EMS, with a complementarity of 40% between the two systems depending on the positioning of the EIS in relation to the elements of the EMS process. The EIS plays a crucial role in facilitating the implementation of the EMS according to ISO 50001. This clarification contributes to a better understanding of the respective roles of these systems in energy management, thus helping communities to improve their energy performance in an effective manner. [ABSTRACT FROM AUTHOR]

The document "Coproducing Opportunities to Advance Heat Resilience in Southern Arizona" discusses the Southern Arizona Heat Planning Summit held in Tucson on February 3, 2024. The summit aimed to address the increasing risks of extreme heat events in the region, particularly focusing on vulnerable populations like unhoused individuals, undocumented migrants, and outdoor workers. The summit brought together representatives from various sectors to identify gaps and opportunities to improve community heat resilience, resulting in recommendations that were incorporated into Arizona's Extreme Heat Preparedness Plan and the City of Tucson's Heat Strategy. The outcomes of the summit led to the adoption of new plans and policies by local agencies and the establishment of initiatives to enhance heat relief efforts and public awareness in the region. [Extracted from the article]

Based on the spring, spring MVC and MyBatis structures of the cloud platform SSM framework, an information management platform for power grid material supply chain is built. The data layer uses a variety of sensors to collect power grid material supply chain information, and the information is fed back to the data storage layer after being integrated by the logical reorganization function of the persistence layer. The data storage layer uses the multi-sensor supply chain information fusion method based on paste progress to fuse the information and store it in the database. The business logic layer calls the information in the database and uses the improved k-means clustering algorithm to detect the abnormal supply chain data information. After calculation and data control by the control layer, the data management results are displayed through the presentation layer. The experimental results show that the absolute error of data fusion is very low. It can effectively cluster data information and distinguish outlier anomaly information at the same time, and the effect of information management is good. [ABSTRACT FROM AUTHOR]

The article describes the professional career of Ursula Georgy, a scientist and career changer, who has significantly influenced the fields of library and information science as well as the profession of library and information. She has worked for various companies and institutions, has been involved in information management and marketing, and has been active in committee work. Her work also included teaching, international networking, and the establishment of further education opportunities. Georgy was an outstanding personality who became known in the professional world for her diverse activities and innovations. [Extracted from the article]

To steer public opinion, autocracies prioritize state media reports of political news while marginalizing commercial and foreign media. Can this dominance guarantee people's trust in state media news? We contend that rumors, circulated via informal channels and resistant to state information control, present a formidable challenge to public trust in state media news. Our two survey experiments in China pitted news of varying information quality (e.g. informative/detailed reports vs cursory mentions of events) from state media sources against rumors, showing that state media news can retain high levels of trustworthiness only if its information quality is high; however, low-quality state media news resulting from information control diminishes its trustworthiness and prompts people to believe rumors. Low-quality rumors have more negative effects than high-quality rumors on news trustworthiness and citizens' satisfaction with government policies. Thus, information control can paradoxically erode trust in state media, which often represent the government in autocracies. [ABSTRACT FROM AUTHOR]

Background: Healthcare laboratory systems produce and capture a vast array of information, yet do not always report all of this to the national infrastructure within the United Kingdom. The global COVID-19 pandemic brought about a much greater need for detailed healthcare data, one such instance being laboratory testing data. The reporting of qualitative laboratory test results (e.g. positive, negative or indeterminate) provides a basic understanding of levels of seropositivity. However, to better understand and interpret seropositivity, how it is determined and other factors that affect its calculation (i.e. levels of antibodies), quantitative laboratory test data are needed. Method: 36 data attributes were collected from 3 NHS laboratories and 29 CO-CONNECT project partner organisations. These were assessed against the need for a minimum dataset to determine data attribute importance. An NHS laboratory feasibility study was undertaken to assess the minimum data standard, together with a literature review of national and international data standards and healthcare reports. Results: A COVID serology minimum data standard (CSMDS) comprising 12 data attributes was created and verified by 3 NHS laboratories to allow national granular reporting of COVID serology results. To support this, a standardised set of vocabulary terms was developed to represent laboratory analyser systems and laboratory information management systems. Conclusions: This paper puts forward a minimum viable standard for COVID-19 serology data attributes to enhance its granularity and augment the national reporting of COVID-19 serology laboratory results, with implications for future pandemics. [ABSTRACT FROM AUTHOR]

Efforts to eliminate visceral leishmaniasis in India mainly consist of early detection and treatment of cases and indoor residual spraying with insecticides to kill the phlebotomine sandfly Phlebotomus argentipes that transmits the causative Leishmania protozoa. In this modelling study, we aimed to estimate the effect of indoor residual spraying (IRS) on vector abundance and transmission of visceral leishmaniasis in India. In this time-series analysis and modelling study, we assessed the effect of IRS on vector abundance by using indoor vector-abundance data (from 2016 to 2022) and IRS quality-assurance data (from 2017–20) from 50 villages in eight endemic blocks in India where IRS was implemented programmatically. To assess a potential dose–response relation between insecticide concentrations and changes in sandfly abundance, we examined the correlation between site-level insecticide concentrations and the site-level data for monthly sandfly abundances. We used mathematical modelling to link vector data to visceral leishmaniasis case numbers from the national Kala-Azar Management Information System registry (2013–21), and to predict the effect of IRS on numbers of averted cases and deaths. IRS was estimated to reduce indoor sandfly abundance by 27% (95% CI 20–34). Concentrations of insecticides on walls were significantly—but weakly—associated with the degree of reduction in vector abundance, with a reduction of –0·0023 (95% CI –0·0040 to –0·0007) sandflies per mg/m2 insecticide (p=0·0057). Reported case numbers of visceral leishmaniasis were well explained by trends in vector abundance. Village-wide IRS in response to a newly detected case of visceral leishmaniasis was predicted to reduce disease incidence by 6–40% depending on the presumed reduction in vector abundance modelled. Indoor residual spraying has substantially reduced sandfly abundance in India, which has contributed to reductions in visceral leishmaniasis and related deaths. To prevent the re-emergence of visceral leishmaniasis as a public health problem, surveillance of transmission and sandfly abundance is warranted. Bill & Melinda Gates Foundation. For the Hindi translation of the abstract see Supplementary Materials section. [ABSTRACT FROM AUTHOR]

Objectives. To investigate characteristics of data reported in US medical cannabis registries across states. Methods. Data included 2021 medical cannabis registry reports from 34 states, Puerto Rico, and the District of Columbia (hereafter, states) with active medical cannabis programs. The data from the reports were manually coded into domains and subcategories, including information related to patients (e.g., number, demographics), authorizing clinicians, sales (e.g., content, revenue), license tracking, and health and safety outcomes. Results. Among 36 states, 97% reported total patient number and 75% reported number of authorizing clinicians. Least reported subcategories included patient race/ethnicity (8%), adverse events (11%), therapeutic benefits (6%), and product recalls (6%). States that recently legalized medical cannabis (2013–2018) reported a higher number of subcategories overall, with a median of 11 versus 8 for early adopting states (1996–2012). More medical-use states reported data on authorizing clinicians compared with nonmedical adult-use states but were otherwise similar. Conclusions. Medical cannabis state registries generally reported data on consumers, clinicians, and sales rather than health and safety outcomes. More comprehensive and uniform medical cannabis public health surveillance is needed. (Am J Public Health. 2024;114(S8):S685–S693. https://doi.org/10.2105/AJPH.2024.307728) [ABSTRACT FROM AUTHOR]

China's Great Firewall was designed to control information flows to keep citizens in and the wider world out. Consequently, until recently China's economic ascendancy was not mirrored in the global digital economy. However, China's increasing digital footprint and championing of national technology firms present numerous economic and security challenges for the EU and US as the dominant digital powers. This paper investigates how growing perceptions of China-based threats in the digital domain have shaped EU (including Member State-level) and US policies. Two pertinent cases – Huawei (hardware provider) and TikTok (digital platform) – illustrate how threat perceptions have catalysed securitization moves to restrict Chinese firms' roles within national digital economies. Western policymakers are increasingly concerned about China's capacity to weaponize technologically interdependent relationships by exploiting its firms' presence within Western networks. Yet significant differences between EU Member States' perceptions precluded both a uniform EU-level response and more extensive transatlantic cooperation. [ABSTRACT FROM AUTHOR]

This study attempts to understand the processes that occur until the adoption of information technology resources yields the expected results. In particular, a value chain perspective is integrated with this relationship to investigate how the characteristics of each business activity result in distinct outcomes, thereby providing specific evidence for the management of information technology resources. The study also examines the moderating role of organisational restructuring in the relationship between information technology resources and firm performance. This study takes a third way to look at this relationship, assuming that both impacts can be observed, depending on the usage level. By doing so, this study may provide some clues for the mechanisms behind assimilating technology into organisations. [ABSTRACT FROM AUTHOR]

In the context of rapid globalization and the swift advancement of information technology (IT), traditional corporate governance models are increasingly challenged by complex business environments and the growing demand for diversified collaboration. These models often exhibit rigidity and inefficiency. The introduction of mobile interactive technology offers new possibilities for the innovation and optimization of corporate governance models. Through mobile interactive networks, resource allocation and collaboration between departments can be conducted flexibly and efficiently. Existing research predominantly focuses on traditional management information systems and centralized resource allocation methods, which frequently overlook the diversity and dynamic nature of internal resource demands within enterprises, making them inadequate for addressing the needs of modern corporations. This study proposes a collaborative interaction mechanism for corporate governance based on matching theory, designing a system model that includes collaborative task demanders and executors, and the social utility of mobile interactive networks. The findings demonstrate that this mechanism enables efficient resource allocation and stable collaborative interactions in complex environments, providing both theoretical support and practical guidance for the innovation of corporate governance models. [ABSTRACT FROM AUTHOR]

The taxi-out time of an airport scene can be categorized into the unimpeded taxi-out time and the additional taxi-out time. Usually, additional taxi-out time is used as a key index to monitor taxi-out performance, and its accurate prediction plays an important role in optimizing the allocation of time slots at an airport and improving scene operation efficiency. Taking Shanghai Pudong International Airport as the research object, we first analyze its layout and construct the origin–destination pairs (ODPs) based on the stand groups and runways. Then, we develop a multiple linear regression model based on the arrival and departure flows to calculate the unimpeded taxi-out times for all ODPs. The actual taxi-out time is then subtracted from the unimpeded taxi-out time to obtain the historical additional taxi-out time of each flight. We propose three new flow features related to the structure: the corridor departure flow, the corridor arrival flow, and the departure flow proportion of ODPs, based on which we construct a dataset for training the prediction model. We then propose an additional taxi-out time prediction model based on the nutcracker optimization algorithm (NOA) and XGBoost and run comparison experiments on the operation data of our target airport. The results show that the optimized prediction model we proposed has the best performance compared with the traditional XGBoost model and other commonly used prediction models, and the proposed structure-related features have high correlations with additional taxi-out time. [ABSTRACT FROM AUTHOR]

This paper presents a significant advancement in information security risk assessment by introducing a flexible and comprehensive model. The research integrates established standards, expert knowledge, machine learning, and ontological modeling to create a multifaceted approach for understanding and managing information security risks. The combination of standards and expert insights forms a robust foundation, ensuring a holistic grasp of the intricate risk landscape. The use of cluster analysis, specifically applying k-means on information security standards, expands the data-driven approach, uncovering patterns not discernible through traditional methods. The integration of machine learning algorithms in the creation of information security risk dendrogram demonstrates effective computational techniques for enhanced risk discovery. The introduction of a heat map as a visualization tool adds innovation, facilitating an intuitive understanding of risk interconnections and prioritization for decision makers. Additionally, a thesaurus optimizes risk descriptions, ensuring comprehensiveness and relevance despite evolving terminologies in the dynamic field of information security. The development of an ontological model for structured risk classification is a significant stride forward, offering an effective means of categorizing information security risks based on ontological relationships. These collective innovations enhance understanding and management of information security risks, paving the way for more effective approaches in the ever-evolving technological landscape. [ABSTRACT FROM AUTHOR]

Human rights groups of all sizes and specializations gather evidence of human rights violations. Those with sufficient resources commonly use dedicated databases to manage the intricate web of sources, events, and analyses that build a strong case. However, developing databases for the needs of each organization remains a challenge. Effective database design requires a data model, which functions as a blueprint for how the data is structured and related. A most basic example of what a data model can specify is that a human rights violation is committed by at least one perpetrator, and that the perpetrator's attributes, such as name or date of birth, should be recorded. A data model that is shared and generic reduces the need to reinvent the wheel since its design can be reused for several databases. In the information systems field, such shared models are called ontologies. Despite the critical nature of the matter, no ontology for human rights violations documentation exists. The present note, therefore, will present the design of the first ontology of this kind. It was developed in association with the human rights group HURIDOCS, which specializes in information management. The requirements elicitation included unstructured interviews with HURIDOCS, document analysis of human rights manuals, and a survey with practitioners. The resulting ontology, named OntoRights, is freely available online with an open license. The evaluation of OntoRights suggests that OntoRights could be highly useful for case databases. [ABSTRACT FROM AUTHOR]

Excessive earnings management can significantly reduce the quality of accounting information, consequently harming the interests of investors and creditors. In the Chinese market, research on earnings management focuses primarily on corporate governance and external environmental viewpoints, with limited literature addressing debt governance. This paper centers on exploring the protective impact of bond covenants, revealing their inhibitory effect on both accrual and real earnings management through two potential mechanisms (agency conflicts and risk-taking). Furthermore, this study conducts a heterogeneous analysis from various perspectives, identifying how bond covenants influence earnings management in different ways and underscoring the moderating role played by underwriters. The findings offer theoretical insights for the development of a high-quality information disclosure system. [ABSTRACT FROM AUTHOR]

Security Enhanced Linux (SELinux) is a security architecture for Linux implementing Mandatory Access Control. It has been used in numerous security-critical contexts ranging from servers to mobile devices. However, its application is challenging as SELinux security policies are difficult to write, understand, and maintain. Recently, the intermediate language CIL was introduced to foster the development of high-level policy languages and to write structured configurations. Despite CIL's high level features, CIL configurations are hard to understand as different constructs interact in non-trivial ways. Moreover, there is no mechanism to ensure that a given configuration obeys desired information flow policies. To remedy this, we enrich CIL with a formal semantics, and we propose IFCIL, a backward compatible extension of CIL for specifying fine-grained information flow requirements. Using IFCIL, administrators can express confidentiality, integrity, and non-interference properties. We also provide a tool to statically verify these requirements and we experimentally assess it on ten real-world policies. [ABSTRACT FROM AUTHOR]

The paper presents the creation of a database of motion norms to support the maintenance management system in an industrial production company, implemented by a team from the Faculty of Mechanical Engineering, VSB - Technical University of Ostrava. This database is intended for filling and optimal use of maintenance modules of ERP systems and for use in the processes of preparation of maintenance and service orders. The article focuses on the methodology of creation, characteristics, use and availability of this database and its application in industrial practice. [ABSTRACT FROM AUTHOR]

Information governance is crucial for firm performance. Marketing managers have been actively engaged in data analytics and information management for decision-making. Because of the role both marketing and information technology units play in information and data management, information governance needs to be well-defined in a firm. Using structure-strategy-process theory as the foundation, the authors define information governance as consisting of three dimensions: strategy, structure, and process. Based on a survey of 147 marketing managers, we demonstrate that strategy and process result in improved information quality, which enhances firm performance. IT/marketing collaboration further enhances the relationship between information strategy and information quality. The detailed analyses, results, and implications are discussed. [ABSTRACT FROM AUTHOR]

AbstractThis study aims to investigate the thematic characteristics and evolutionary patterns of library policies in China from 1949 to 2023. Employing the Latent Dirichlet Allocation (LDA) model, the research analyzed 2,703 Chinese government-issued policies related to libraries during this period, identifying key topics and tracing their developmental trajectories. The study recognized four distinct developmental phases, five major topics, and the underlying connections among feature terms within different topics. It discussed the corresponding topic strengths and evolving trends in each phase. Library policies in China are predominantly centered on five key domains: 1) spatial planning and architectural integration, 2) information management and transparency, 3) legal regulations and supervisory enforcement, 4) heritage preservation and sustainable development, and 5) community inclusion and accessibility. Notably, spatial planning and architectural integration consistently garner substantial attention, highlighting their enduring prominence, while there is relatively less emphasis on community inclusion and accessibility, as well as heritage preservation and sustainable development. The contribution of this study lies in conducting a semantic exploration of the overall transformation in library-related policies in China, validating the effectiveness of the LDA model in identifying topics within policy texts, and expanding the research perspective on library policy evolution. [ABSTRACT FROM AUTHOR]

Monitoring threatened species is essential for understanding their conservation needs and developing effective recovery strategies. However, designing and implementing monitoring programs can be challenging in resource‐constrained environments, where conservation practitioners must balance the need for detailed information with limited resources. We present a case study focusing on the design of a range‐wide monitoring program for the Endangered rufous scrub‐bird (Atrichornis rufescens) in the mountain forests of eastern Australia. We first developed a ‘wish list’ of monitoring questions and then trialed the methods needed for answering them using sequence of pilot studies. We implemented a phased approach comprising (i) a study of whether individuals could be identified by their songs, (ii) identification of a ‘core range’ using species distribution models to refine the search area, and (iii) a trial of the efficacy of a preferred feasible monitoring approach. We offer a practical pathway for designing question‐driven monitoring programs for threatened species. Our study highlights the importance of clarifying explicit monitoring goals and tailoring methods to suit species' ecological and life history characteristics. By following this systematic approach, conservation efforts can obtain valuable information for effective management, even with limited resources and prevailing uncertainty about species ecology. [ABSTRACT FROM AUTHOR]

As a high-value agricultural product, the cold chain logistics management of Gannan navel oranges has global significance. Especially in Africa and Europe, food safety and supply chain quality are critical issues. However, the existing Gannan navel orange logistics information management system relies on traditional databases and information systems, with insufficient data sharing and transparency, affecting the overall coordination of the supply chain and customer satisfaction. In addition, the traditional system is vulnerable to hacker attacks and malicious tampering of data by insiders, resulting in serious economic losses and reputation damage. So the blockchain platform constructed in this study improves the transparency and traceability of logistics data through the SMART-PBFT algorithm of the alliance chain, which optimizes the logistics management process, improves the quality of logistics services, and reduces operating costs. It improves the logistics efficiency and data transparency of local agricultural products, and also provides a demonstrative case for the cold chain management of other high-value agricultural products around the world, with broad application potential and reference value. [ABSTRACT FROM AUTHOR]

Background: Trauma is one of the leading causes of mortality worldwide, and online platforms have become essential sources of information for trauma management. YouTube can play a significant role in helping people access medical information. Methods: YouTube was searched using the keywords management of trauma and assessment of trauma to identify relevant videos. Two authors independently evaluated the videos according to the ATLS (10th edition) guidelines, the modified DISCERN (m‐DISCERN) scale, and the Global Quality Scale (GQS) criteria. The videos that met the study criteria were evaluated based on the provider, video length, and view count. Results: Out of 939 videos, 667 were excluded resulting in 272 videos included in the study. According to the ATLS (10th edition) guidelines, the median score for videos was 8 (IQR 7‐8). Videos uploaded by official institutions and healthcare professionals received higher scores than from uncertain sources (p = 0.003). According to the GQS, 86% of the videos were low or moderate quality; uncertain sources uploaded 78% of low‐quality videos. Conclusion: YouTube is an information source about trauma management that contains videos of varying quality and has a broad audience. Official institutions and healthcare professionals should be aware of this evolving technology and publish up‐to‐date, accurate content to increase awareness about trauma management and help patients distinguish helpful information from misleading content. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Objective Methods Results Conclusion TikTok contains many videos about bruxism that may help raise the level of awareness on the topic. However, the quality of these videos' information represents the greatest concern.The present cross‐sectional analysis aimed to systematically assess the reliability and educational suitability of TikTok videos as a source of information on bruxism.TikTok was searched for relevant videos uploaded until 6 March 2024, using the hashtags #bruxism, #grindingteeth and #jawclenching. Independent pre‐calibrated operators conducted video inclusion and data collection, noting videos' characteristics, source, popularity, content, reliability (assessed through the DISCERN scoring system) and educational value (assessed through the Global Quality Score [GQS]). The Kruskal–Wallis test was adopted to compare videos from different sources. Videos with low and high educational value were compared using the Mann–Whitney U‐test. Tests were considered significant when the p‐value was < 0.05.A total of 105 bruxism videos were analysed. Most videos covered bruxism management and clinical features, and more than 60% were uploaded by healthcare professionals. According to the DISCERN and GQS scoring, the videos' reliability and educational value were judged to be very poor and low, respectively, but on average they were higher for videos uploaded by healthcare professionals compared to those uploaded by laypeople. When comparing videos with high educational value to those with low educational value, differences were found in popularity, content and reliability.The present results suggest the need for greater control of information disseminated on social media to fulfil its potential role in educating laypeople about bruxism. [ABSTRACT FROM AUTHOR]

A gene bank for farm animal genetic resources (FAGR) is an important facility for the diversity conservation of FAGR. The primary purpose of gene banks for FAGR is the reconstruction of those breeds. With the advent of the post-genomic era, gene banks for FAGR have increasingly become an infrastructure for the support of livestock research and animal breeding, and a platform for international research collaboration. China is one of the richest countries in the world in terms of FAGR. Chinese National Gene Banks for FAGR (CNGBFs) have an important legal status and play an important function in the Chinese FAGR protection system. In this paper, we reviewed the current situation of CNGBFs construction, and systematically collected and analyzed legal rules related to CNGBFs. As results, those legal rules were categorized into two types: (a) organization and management, (b) activities. We summarized problems existing in the current legal rules for CNGBFs from three levels: institution, practical operation, and digital development. Improvement directions of legal rules regarding CNGBFs are proposed. They include clarifying the utilization function of CNGBFs and the ownership of FAGR in CNGBFs. Moreover, improving the mechanism of administrative management, rules on domestic and international access and benefit-sharing, and the system of digital sequence information management are also suggested. The improvements in those legal rules will contribute to the appropriate utilization of Chinese FAGR and international collaborations. [ABSTRACT FROM AUTHOR]

Energy management in datacenters is a major challenge today due to the environmental and economic impact of increasing energy consumption. Efficient placement of virtual machines in physical machines within modern datacenters is crucial for their effective management. In this context, five algorithms named CNN-GA, CNN-greedy, CNN-ABC, CNN-ACO and CNN-PSO, have been developed to minimize hosts' power consumption and ensure service quality with relatively low response times. We propose a comparative approach between the developed algorithms and other existing methods for virtual machine placement. The algorithms use optimization algorithms combined with Convolutional Neural Networks to build predictive models of virtual machine placement. The models were evaluated based on their accuracy and complexity to select the optimal solution. The necessary data is collected using the CloudSim Plus simulator, and the prediction results were used to allocate virtual machines according to the predictions of the models. The main objective of this research is to optimize the management of Information Technology resources within datacenters. This is achieved by seeking a virtual machine placement policy that minimizes hosts' power consumption and ensures an appropriate level of service for users' needs. It considers the imperatives of sustainability, performance, and availability by reducing energy consumption and response times. We studied six scenarios under specific constraints to determine the best model for virtual machines' placement. This approach aims to address current challenges in energy management and operational efficiency. [ABSTRACT FROM AUTHOR]

Objective To understand the epidemiological characteristics of non-occupational carbon monoxide poisoning incidents in Beijing from 2018 to 2022, and to explore targeted prevention and control measures. Methods The data were from the National Public Health Emergency Reporting Management Information System. Descriptive epidemiological methods were used to analyze non-occupational carbon monoxide poisoning incidents in Beijing from 2018 to 2022. Relative risk (RR) was used to assess the risk of morbidity and mortality. Results From 2018 to 2022, a total of 1841 non-occupational carbon monoxide poisoning incidents were reported in Beijing, with 2729 cases of poisoning and 31 deaths. The annual morbidity and mortality were 25.14 and 0.29 cases per million, respectively. There were two peaks of poisoning cases in spring and winter, accounting for 49.98% and 24.00% of the total cases, respectively. The highest incidence occurred between 8 and 11 o 'clock, accounting for 22.83%. In the inner suburbs, outer suburbs and urban areas, the incidence of non-occupational carbon monoxide was 0.96 cases/100 000, 1.27 cases/100 000 and 18.79 cases/100 000, and the mortality was 0.02 cases/100 000, 0.02 cases/100 000 and 0.11 cases/100 000, respectively. The poisoning incidents mainly occurred in residential families in 1633 cases, accounting for 88.70%; This was followed by 118 restaurants, accounting for 6.41 percent. The proportion of household poisoning incidents decreased from 92.10% in 2018 to 84.13% in 2022. The proportion of poisoning incidents in restaurants increased year by year from 4.23% in 2018 to 10.05% in 2022. The proportion of poisoning cases occurring at home decreased from 86.39% in 2018 to 71.84% in 2022. The proportion of poisoning cases in restaurants increased from 9.88% in 2018 to 20.57% in 2022. Conclusion The incidence and death risk of non-occupational carbon monoxide poisoning in Beijing is not balanced among regions, and the proportion of poisoning incidents in restaurants is increasing year by year. Targeted measures should be taken to strengthen the prevention and control work in the outer suburbs and key restaurants. [ABSTRACT FROM AUTHOR]

Background: Long non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations. Results: In this paper, we propose a prediction method for the lncRNA-disease association relationship, named LDAGM, which is based on the Graph Convolutional Autoencoder and Multilayer Perceptron model. The method first extracts the functional similarity and Gaussian interaction profile kernel similarity of lncRNAs and miRNAs, as well as the semantic similarity and Gaussian interaction profile kernel similarity of diseases. It then constructs six homogeneous networks and deeply fuses them using a deep topology feature extraction method. The fused networks facilitate feature complementation and deep mining of the original association relationships, capturing the deep connections between nodes. Next, by combining the obtained deep topological features with the similarity network of lncRNA, disease, and miRNA interactions, we construct a multi-view heterogeneous network model. The Graph Convolutional Autoencoder is employed for nonlinear feature extraction. Finally, the extracted nonlinear features are combined with the deep topological features of the multi-view heterogeneous network to obtain the final feature representation of the lncRNA-disease pair. Prediction of the lncRNA-disease association relationship is performed using the Multilayer Perceptron model. To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. Through a gate mechanism, it controls the flow of information between each hidden layer in the Multilayer Perceptron model, aiming to achieve optimal feature extraction from each hidden layer. Conclusions: Parameter analysis, ablation studies, and comparison experiments verified the effectiveness of this method, and case studies verified the accuracy of this method in predicting lncRNA-disease association relationships. [ABSTRACT FROM AUTHOR]

ABSTRACT Diet is one of the essential information used in the management of fisheries resource. The objective of this study was to assess the dietary preferences, index of preponderance, trophic level, food niche breadth, and food overlap of purple‐spotted bigeye (Priacanthus tayenus) caught from the northern coast of Java, Indonesia. A total of 407 fish samples were collected from July to October 2023. Each fish sample was measured for total length and body weight. Fish were then dissected to determine sex, gut length, gut volume, and diet composition. Data analysis included relative gut length, diet composition, frequency of occurrence, trophic level, index of preponderance, food niche breadth, and food overlap. The result showed that the purple‐spotted bigeye is a carnivorous fish (trophic level ranges from 3.88 to 4.18), whose main food is fish and shrimp. Based on the niche breadth value, purple‐spotted bigeye from East Java were more diverse in finding food (niche breadth = 0.26) than from West Java (niche breadth = 0.06) and Central Java (niche breadth = 0.09). The purple‐spotted bigeye species from West Java and Central Java exhibited a high level of competition in their search for food, as indicated by a food overlap value of 0.998. [ABSTRACT FROM AUTHOR]

To solve the problems of chaotic information management and difficult traceability in the manufacturing process of transformer coils, a traceability and management method oriented towards the manufacturing process of transformer coils has been proposed. This method integrates industrial internet identification resolution and extension of Petri net modeling theory. A comprehensive identification and resolution framework for coil manufacturing processes has been constructed. In this manuscript, the authors proposed an industrial data-sharing space based on the producer-consumer model with unified coding identification. This enables information sharing for all resources, including personnel, machinery, materials, methods, environment, and measurements. A method for modeling extensible identification primitives of coil manufacturing process information was proposed, which formalizes the correlation and data structure of process information. A Petri net model for the comprehensive acquisition and integration of elemental information in coil manufacturing processes, as well as a mathematical model for quality traceability, were constructed, thereby forming a complete path for quality traceability information. Finally, based on the method proposed above, a software and hardware environment for identification and traceability for coil manufacturing was established. Taking a certain type of coil as an example, validation was carried out; the results indicate a significant enhancement in the production management and information traceability capabilities of the coil production workshop. This study provides reference and guidance for the process traceability management of power equipment manufacturing. [ABSTRACT FROM AUTHOR]

AbstractThe market for olive leaf dietary supplements is expanding rapidly and is valued at $437.15 million today. However, information on the control of these products is sketchy and the origin and variety of olives are rarely stated. The aim of this research was to validate a simple and rapid screening method for oleuropein determination in olive leaf dietary supplements. A matrix blank was prepared by removal of oleuropein from a mixture of dietary supplements and the matrix was then spiked with known concentrations to create a spiked matrix calibration curve in the range 5 - 40% oleuropein. Five replicate extractions and analyses of the matrix standards were carried out over 10 days. Precision was less than 6% RSD and linearity was demonstrated by the Fischer test. Extraction recovery was > 90% and there was a strong linear relationship between authentic and matrix standards. All tested products conformed to the label claim which was strongly correlated with total polyphenols measured by the Folin-Ciocalteau method. Antioxidant activity was measured by the DPPH assay and was found to be strongly correlated with total phenol content and oleuropein concentration. [ABSTRACT FROM AUTHOR]

There are now a wide range of tools available to monitor employees, boasting sophisticated features like keystroke logging, geolocational tracking and video surveillance. From a legal perspective, employee monitoring is most commonly analysed in terms of the impact it has on an employee's control over their information and data, ie their ‘informational privacy’. This article argues that monitoring is a more complex and layered issue, requiring the consideration of other values as well. Specifically, we argue that there are two (by no means exhaustive) reasons why employee monitoring is concerning which go beyond the use of information and data. First, monitoring affects physical and spatial, not just informational, components of privacy. Second, monitoring can be so severe in extreme cases that it curtails individual liberty and constitutes a form of imprisonment. The article draws out the significant legal implications of each of these claims, while addressing counterarguments to our position based on employee consent and the idea that work has always involved constraints on individual freedom. [ABSTRACT FROM AUTHOR]

Background: Despite being preventable and curable, leprosy remains endemic in some undeveloped regions, including China. Wenshan Zhuang and Miao Autonomous Prefecture (Wenshan prefecture) currently bears the highest leprosy burden in China. In this ecological study, we aimed to analyze the epidemiological characteristics as well as identify and visualize the high-risk townships of Wenshan prefecture using the most updated leprosy data from 2010 to 2022. Methods: Geographical information system combined with spatial scan statistics was used for newly detected leprosy cases abstracted from the Leprosy Management Information System in China. Global Moran's I index was used to uncover the spatial pattern of leprosy at the township level. Spatial scan statistics, encompassing purely temporal, purely spatial, spatial variation in temporal trends, and space-time analysis, were implemented for detecting the risk clusters. Results: Between 2010 and 2022, Wenshan prefecture detected 532 new leprosy cases, comprising 352 (66.17%) males and 180 (33.83%) females. The aggregated time primarily occurred between October 2010 and March 2014. The distribution pattern of newly detected leprosy cases was spatially clustered. We identified four high-risk spatial clusters encompassing 54.51% of the new cases. Furthermore, spatial variation in temporal trends highlighted one cluster as a potential high-risk area. Finally, two space-time clusters were detected, and the most likely cluster was predominantly located in the central and northwest regions of Wenshan prefecture, spanning from January 2010 to September 2013. Conclusions: In this ecology study, we characterized the epidemiological features and temporal and spatial patterns of leprosy in Wenshan prefecture using the most recent leprosy data between 2010 and 2022. Our findings offer scientific insights into the epidemiological profiles and spatiotemporal dynamics of leprosy in Wenshan prefecture. Clinicians and policymakers should pay particular attention to the identified clusters for the prevention and control of leprosy. [ABSTRACT FROM AUTHOR]

The role of Transformational Leadership in hospital organizations is very important, where hospitals are organizations that have a complex environment, there is a lot of unclear information. With the increase in health services to the community along with changes in demographics, changes in health service technology, and the adoption of new information technology. So performance measurement is important in order to improve the quality of health services. The aim of this research is to find out how transformational leadership influences the success of hospitals management information systems (HMIS). The method used was a quantitative descriptive and verification survey with 181 respondents from 15 hospital in the city of Bandung. The sampling technique uses proportionate stratified random sampling. Data analysis using structural equation modeling (SEM) with partial least squares (PLS). The findings of the proposed hypothesis are that the quality of technology, transformational leadership, and users have a significant effect on service performance. Users can mediate technology quality, transformational leadership and service performance. Conclusion of the study is the novelty of the development of the information system success model by adding the context of transformational leadership in evaluating the success of the information system, where transformational leadership has a positive effect on improving the performance of hospital management information system services through users. Implications of the results of this study contribute to the development of an information system success model that can be used to evaluate the success of information systems in general. [ABSTRACT FROM AUTHOR]

As digitally enabled information systems play an increasingly central role in culture and economics, their negative consequences have become apparent. This guest editorial addresses the urgent need for information scientists to take a more deliberate stance in designing and guiding the evolution of these systems. We propose a framework for conceptualizing "healthier information ecosystems" by drawing on theories from complex systems and ecological research, grounded in a value‐oriented approach. The article reviews key concepts from systems science, complex systems, and ecology, with a focus on ecosystem and adaptation research. These perspectives offer analytical approaches for decomposing information ecosystems and provide a foundation for understanding "health" in the context of evolving, open systems. Unlike natural ecosystems, information ecosystems must be evaluated according to human values; thus, we articulate a set of values as a starting point for defining health in this context. By introducing insights from beyond the field of information systems, we aim to instigate scholarly dialog, connect prior work in new ways, and reveal new opportunities for research and intervention. This connective and argumentative contribution is intended to guide future research and identify solutions to the proliferating problems in our current information ecosystems. [ABSTRACT FROM AUTHOR]

One of the new approaches to organizing journal articles is using Semantic Web technologies and new "Semantic Publishing" methods based on the ontological models for semantic modeling and representation of these publications. This study aims to design the metadata ontology model for semantic modeling and representation of scholarly journal articles. This research was carried out using the content analysis method. The study population includes articles published in ISC journals (i.e., journals indexed in ISC). A sample of 200 articles from a Persian journal (i.e., "Iranian Journal of Information Processing & Management") and an English journal (i.e., "International Journal of Information Science and Management (IJISM)") were considered for semantic modeling and representation using the metadata ontology model. The data-gathering method was a systematic observation, and the data-gathering tool was a checklist based on the Semantic Publishing and Referencing Ontologies (SPAR Ontologies). This research identified the metadata entities required for semantic modeling and representation of ISC scholarly journal articles. Then, the metadata ontology model was designed using Protege (an ontology editor) and the RDF representation of the model was created in RDF/XML Syntax. After designing the metadata ontology model, the RDF graph of this model was developed to analyze the entities and relationships between them, and its results were analyzed. The results of RDF graph analysis show that the design of the ontology model and the creation of the RDF links between entities significantly impact the semantic description and representation of metadata entities of the ISC scholarly journal articles and the network of relations between them. [ABSTRACT FROM AUTHOR]

Health care in developing countries often lacks adequate bookkeeping and national cancer registries, means of information that have proven to impact disease research and care. The true burden of brain tumors therefore remains unchecked and so does the extent of the problem. Therefore, this study aims to explore the challenges and potential strategies related to information management of brain tumors in low- and middle-income countries (LMICs). A comprehensive literature search conducted using databases such as PubMed, Scopus, Google Scholar, and Cumulated Index in Nursing and Allied Health Literature, without any language restrictions, from inception to October 20, 2022. Following screening and extraction of data, themes were generated using the information management domain of the National Surgical, Obstetric, and Anesthesia Plan framework. The final analysis includes 23 studies that highlighted the challenges to managing information to the surgical care given to brain tumors in LMICs, including lack of proper hospital record system (43%), lack of national brain tumor registry (67%), lack of local management guidelines (10%), and low research output (33%). Some of the proposed strategies in the literature to address these barriers include improving data management systems (45%), developing a population-based brain tumor registry (64%), and formulating local treatment guidelines (9%) for the management of brain tumors. In LMICs, improving patient outcomes and quality of life postneurosurgical intervention for brain tumors requires coordinated efforts to enhance information systems. The support of the government and public health professionals is vital in implementing strategies to achieve this goal. [ABSTRACT FROM AUTHOR]

Against the background of Job Demands‐Resources and Conservation of Resources theory and research on organizational communication, this prospective study among n = 312 employees explores the significant role of perceived information process quality (PIPQ) in enhancing employees' optimism during the COVID‐19 pandemic. It thereby contributes to a deeper understanding of the factors influencing employee optimism in challenging contexts. In this study, PIPQ is defined by the availability of timely information, clarity, and consistency in the information provided. Results from latent change score modelling revealed that employees who experienced high PIPQ, particularly consistent information, reported feeling more optimistic about work‐related aspects and also experienced spillover effects into their private lives. Notably, both consistency in information prior to the pandemic and increases in consistent information during the pandemic demonstrated this beneficial effect. Moreover, timely available information also positively influenced optimism, especially regarding work‐related aspects. However, the study did not find evidence that clarity in information significantly affected optimism. In summary, the findings underscore the importance of accessible and consistent information as a vital resource for employees' ability to navigate crises. [ABSTRACT FROM AUTHOR]