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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]

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]

Complex product and production systems often result in high variability in the production flow, prohibiting the sustainable implementation of lean practices. In this paper the authors introduce a PDCA cycle to analyse and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Lean practices can be applied in stable zones, unstable zones remain expert-driven. Measures are introduced to reduce variability in unstable zones with the ultimate target, to turn them into stable zones, extending sustainable lean activities in the value stream, step by step. An IT system is developed to acquire, process and visualise the vast amount of data to provide structured information for experts and management for the reduction of variability in production. [ABSTRACT FROM AUTHOR]

We introduce an original concept of the backroom effect for perishable products when the deterioration rate in a backroom is lower than that on retail shelves. With IoT-generated real-time information about the perishable products, this phenomenon has a significant impact on joint shelf-space and inventory decisions. We define the deterioration rate gap, formulate the perceived on-shelf product freshness, and describe the freshness-dependent demand distribution, with continuous backroom-shelf replenishment. Assuming that demand depends on both perceived freshness and shelf level, we develop a decision-making model that simultaneously determines the inventory replenishment policy and the shelf space allocation for multiple items. To facilitate the solution process, we propose a hybrid solution approach by combining genetic algorithm (GA) and variable neighbourhood search (VNS). The results provide a prioritised inventory policy for item selection that incorporates the deterioration improvement. The results of the performance analysis show that a policy considering the backroom effect achieves increased profit when the backroom/shelf deterioration gap increases. The optimal solutions for the problems with large backroom/shelf gap also show that the practitioner should increase the ordering quantity, which is contradictory to the outcome of traditional models. [ABSTRACT FROM AUTHOR]

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Over the last decade, health information systems (HIS) have undergone significant changes, particularly in embracing flexible frameworks for ongoing development. This evolution underscores the necessity for information technology (IT) infrastructures that rapidly align with clinical processes. The paper investigates the transition of hospital information systems to comprehensive strategies, examining the benefits and challenges involved. It also examines the increasing demands on health data management systems (HDMS) for patient care and biomedical research. The focus is on how the integration of the Internet of Things (IoT) and open-source enterprise resource planning (ERP) systems, such as Odoo, impacts health information management. The study evaluates the effectiveness and implications of combining these technologies. It provides examples of these integrated systems in action, particularly in resource-limited settings, and evaluates their potential to improve care. The document provides a comprehensive review of the current status and evolution of HIS and HDMS, highlighting the importance of integrating IoT and other cutting-edge technologies in healthcare. This is a crucial aspect for developing countries, where these advancements can significantly improve healthcare outcomes. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) preventive treatment (TPT) effectively prevents the progression from TB infection to TB disease. This study explores factors associated with TPT non-completion in Cambodia using 6-years programmatic data (2018–2023) retrieved from the TB Management Information System (TB-MIS). Out of 14,262 individuals with latent TB infection (LTBI) initiated with TPT, 299 (2.1%) did not complete the treatment. Individuals aged between 15–24 and 25–34 years old were more likely to not complete the treatment compared to those aged < 5 years old, with aOR = 1.7, p = 0.034 and aOR = 2.1, p = 0.003, respectively. Individuals initiated with 3-month daily Rifampicin and Isoniazid (3RH) or with 6-month daily Isoniazid (6H) were more likely to not complete the treatment compared to those initiated with 3-month weekly Isoniazid and Rifapentine (3HP), with aOR = 2.6, p < 0.001 and aOR = 7, p < 0.001, respectively. Those who began TPT at referral hospitals were nearly twice as likely to not complete the treatment compared to those who started the treatment at health centers (aOR = 1.95, p = 0.003). To improve TPT completion, strengthen the treatment follow-up among those aged between 15 and 34 years old and initiated TPT at referral hospitals should be prioritized. The national TB program should consider 3HP the first choice of treatment. [ABSTRACT FROM AUTHOR]

The goal of this research study was to identify and prioritize the significant cybersecurity challenges that vendor firms encounter during software development. Using Systematic Literature Reviews (SLRs), 13 significant challenges were found, including “Security issues/Access of Cyberattacks”, “Lack of Right Knowledge”, “Cost Security Issues”, and “Lack of Confidentiality and Trust” among others. To address these concerns, a multifaceted strategy that prioritizes continuing education, training, and investment in cybersecurity measures, as well as cross‐industry cooperation and coordination with government entities, is required. These challenges were ranked using the Fuzzy Analytic Hierarchy Process (F‐AHP). We obtained the following results after applying the Fuzzy Analytic Hierarchy Process: CSC1 (Cyber Security Challenge‐1) “Security Issues/Access of Cyber Attacks”, CSC2 “Lack of Right Knowledge”, and CSC3 “Framework” are the top most critical cyber security challenges, with weightages of 0.1687, 0.1672, and 0.1194, respectively. This study lays the groundwork for future research and assists vendor organizations in addressing the cybersecurity concerns they face during software development. The study also emphasizes the significance of addressing cybersecurity during the software development process in order to avoid the financial and reputational losses associated with cyber intrusions. [ABSTRACT FROM AUTHOR]

Whether individuals engage with or avoid health information and which sources are used is crucial for informed decision-making about mammography. Therefore, we aim to develop a typology of mammography-related information behaviors and explore their determinants, which were derived from the Theory of Motivated Information Management (TMIM). Based on a two-wave online survey of a sample of German women aged 40 to 69 years (N = 1,138), a cluster analysis resulted in five person-centric types of information behavior that cover respondents’ variety of engagement with mammography-related information: The seekers, the scanners, the avoiders, the involved, and the inactive. The types indicated that most individuals possess a high preference for one strategy of information behavior. Looking at the determinants of belonging to a particular type of information behavior, it becomes apparent that the factors of the TMIM have only limited explanatory power. The most relevant factors in distinguishing the types of information behaviors are benefit perceptions, worry, interest, avoidance efficacy, seeking, and avoidance-related outcome expectancies. Scanners and seekers had higher benefit perceptions. Seekers were further motivated by greater worries, while involved ones felt more interested and held stronger expectancies. Avoiders were more anxious and had a higher avoidance efficacy. The study suggests that inactive individuals and avoiders are highly prevalent and relevant target groups for health interventions that support informed decision-making. To facilitate informed decision-making, women should be encouraged to weigh benefits and harms of their options and to address negative emotions, such as anxiety, that may exist or arise during decision-making. [ABSTRACT FROM AUTHOR]

Action segmentation is vital for video understanding because it heuristically divides complex untrimmed videos into short semantic clips. Real-world human actions exhibit complex temporal dynamics, encompassing variations in duration, rhythm, and range of motions, etc. While deep networks have been successfully applied to these tasks, they face challenges in effectively adapting to these complex variations due to the inherent difficulty in capturing semantic information from a global perspective. Merely relying on distinguishing visual representations in local regions leads to the issue of over-segmentation. In an attempt to address this practical issue, we propose a novel approach named ASGSA, which aims to obtain smoother segmentation results by extracting instructive semantic information. Our core component, Global Semantic-Aware module, provides an effective way to encode the long-range temporal relation in the long untrimmed video. Specifically, we exploit a hierarchical temporal context aggregation, which is identified by a gated-mechanism selection to control the information passage at different scales. In addition, an adaptive fusion strategy is designed to guide the segmentation with the extracted semantic information. Simultaneously, to obtain higher-quality video representation without extra annotations, we resort to self-supervised training strategy and propose the Video Speed Prediction module. Extensive experiments demonstrate that our approach achieves state-of-the-art performance on all three challenging benchmark datasets (Breakfast, 50Salads, GTEA) and significantly improves the F1 score@50, which represents the reduction of over-segmentation. The code is available at https://github.com/ten000/ASGSA. [ABSTRACT FROM AUTHOR]

Protein crystallography is an established method to study the atomic structures of macromolecules and their complexes. A prerequisite for successful structure determination is diffraction‐quality crystals, which may require extensive optimization of both the protein and the conditions, and hence projects can stretch over an extended period, with multiple users being involved. The workflow from crystallization and crystal treatment to deposition and publication is well defined, and therefore an electronic laboratory information management system (LIMS) is well suited to management of the data. Completion of the project requires key information on all the steps being available and this information should also be made available according to the FAIR principles. As crystallized samples are typically shipped between facilities, a key feature to be captured in the LIMS is the exchange of metadata between the crystallization facility of the home laboratory and, for example, synchrotron facilities. On completion, structures are deposited in the Protein Data Bank (PDB) and the LIMS can include the PDB code in its database, completing the chain of custody from crystallization to structure deposition and publication. A LIMS designed for macromolecular crystallography, IceBear, is available as a standalone installation and as a hosted service, and the implementation of key features for the capture of metadata in IceBear is discussed as an example. [ABSTRACT FROM AUTHOR]

An online survey was conducted from June 2018 to March 2021 to elicit information from commercial farmers and growers on the economic impact of the Brown Marmorated Stink Bug (BMSB) (Halyomorpha halys (Stål)) on agriculture and their attitudes towards adopting various alternative management practices, including use of Trissolcus japonicus as a biocontrol agent. Most respondents reported that BMSB reduced the profitability of their operation, with the largest impacts coming from reduced quality and increased spray cost. Improved monitoring techniques and natural enemies have the greatest probability to be used to manage BMSB, while tactics like attract and kill, border sprays, repellents, trap crops and netting were less likely to be adopted. Further analysis using ordered logistic and tobit regression models shows that the factors that influence potential adoption vary significantly for each management practice. This suggests that adoption efforts for alternate management practices should focus on the attributes of specific commodity groups and targeted educational programmes may be required to overcome the resistance of growers using conventional growing practices. Several variables have a consistent impact on the respondent's willingness to pay for a T. japonicus‐based biocontrol including being a commercial producer (positive impact), use of conventional growing practices (negative) and increased concern about the impact of BMSB (positive). [ABSTRACT FROM AUTHOR]

The optimal output synchronization problem of heterogeneous multi‐agent systems (HMASs) with communication delays is studied in this article. In order to compensate for communication delays actively, we employ networked data‐driven predictive control method to predict the agents' outputs. Then the output synchronization issue of HAMSs is transformed into the stabilization issue of the local pseudo systems, and model‐free off‐policy reinforcement learning technique is used to learn optimal control policies of the local systems. Combined predicted output information with optimal control policies, we develop a distributed data‐driven optimal output policy for each follower. Finally, a numerical example is given to show the effectiveness of our results. [ABSTRACT FROM AUTHOR]

This research aims to identify, categorize, and prioritize the benefits and challenges of implementing common data environments (CDEs) in the construction phase of building information modeling (BIM)-based projects. For this purpose, a systematic literature review, semistructured interviews, and the Delphi method were conducted, and online sources of CDE providers were investigated. 54 benefits and 15 challenges were identified. Cronbach's alpha, standard deviation, interrater agreement level, and significance level statistics were calculated to analyze and validate Delphi method outputs. Results demonstrate that the most important benefit of implementing CDEs in the construction phase of BIM-based projects is access to accurate, reliable, up-to-date information. The most critical challenge is the exclusion of CDE planning in the front-end phase of the project. Prioritizing the benefits shows CDEs' full potential for the construction phase of BIM-based projects. Prioritizing the challenges demonstrates possible future works, requirements, and the areas that should be improved. This research provides a comprehensive point of view on the benefits and challenges of implementing CDEs in the construction phase of BIM-based projects. It analyzes the potential of CDEs by strengthening the findings from the systematic literature review with the SMEs' evaluation, comments, and feedback. This study provides valuable insights into implementing CDEs in the construction phase of BIM-based projects, defining their capabilities, status, and potential, and giving suggestions about how to deal with their challenges. This research shows how CDEs ensure streamlining information and communication flows in BIM-based projects by mitigating nonvalue-added activities resulting from informal, nonstandardized data exchanges, lack of proper data exchange protocols, loss of project data, and lack of efficient collaboration and communication between project team participants. This study reveals the importance of implementing CDEs in the construction phase of BIM-based projects to achieve adequate information and communication management that may prevent project data loss, informal, nonstandardized data exchanges, and inefficient collaboration between multidisciplinary teams. [ABSTRACT FROM AUTHOR]

In the digital age, spreading false information has a far-reaching impact on various areas, such as society, politics, and the economy. With the popularization of applications of text generation models, the cost of producing false information has significantly decreased, making it challenging for human beings to screen it. Therefore, research on detection screening and early warning control for model-generated false information becomes particularly important. In this paper, we propose a model-generated false information detection and control system based on blockchain. Firstly, we design a model-generated false information detection method combining model-generated text discrimination based on a self-attention network and text similarity detection based on a twin network. Secondly, we construct a blockchain-based model-generated false information control and traceability system. It utilizes the proposed detection algorithm to provide early warning and control of model-generated false information involving important and sensitive events before social network release. For information judged to be model-generated false, the stored data on the blockchain is utilized to track and trace the publisher. Ultimately, experimental tests prove that the proposed detection method improves the accuracy of false information detection. In addition, the operational efficiency of the prototype system can meet quality of service requirements. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative framework for the management of virtual companies in smart urban environments, with an emphasis on socio-economic resilience facilitated by Sustainable Information Systems. The system aims to equip virtual enterprises in smart cities with tools for robust operations amid socio-economic challenges. Its effectiveness is evidenced by improvements in investment risk assessment, business process simulation, and HR project management, enhancing efficiency and foresight. A key feature is predictive analytics for crisis demand forecasting, enabling swift market adjustments and strategic inventory management. It also helps identify alternative clients and suppliers, ensuring business continuity. Integrating machine learning and augmented reality, the system supports automation and strategic decision-making, significantly benefiting the e-commerce sector by addressing fluctuating demand, supply chain issues, and market adaptations during crises. The Sustainable Information System for Virtual Company Management in Smart Cities offers crucial support for e-businesses facing these socio-economic challenges, facilitating their navigation through turbulent times. Its meticulously designed architecture and functionalities make it a powerful instrument for assisting virtual companies in crisis conditions, fostering their sustainable growth within the socio-economic framework of smart urban settings. Comparative studies with existing models underscore this system's superior efficiency and holistic approach, highlighting its contribution to enhancing the operational efficiency of virtual companies by 95%, reducing the time needed for critical activities like investment risk analysis and business process simulation, and bolstering the socio-economic resilience of smart cities against crises [ABSTRACT FROM AUTHOR]

Healthcare knowledge management systems can mitigate hospitals' operational inefficiency. As a healthcare information technology, the electronic health record (EHR) receives much attention from medical institutions due to its considerable impact on operational cost performance. This paper focuses on EHR systems to address operational inefficiency by which patients pay more for health care services, and many U.S. hospitals are filing for bankruptcy. From the theoretical perspective of the practice-based view, this paper introduces a path to implement EHR systems for improving cost performance. The empirical investigation is archival data of 200 hospitals collected from the U.S. healthcare agencies. Findings contribute to prior work by hypothesizing moderating and mediating roles in EHR systems implementation. This paper introduces absorptive capacity and monitoring mechanisms as enablers of implementing EHR systems. The results showed that hospital monitoring strengthens the relationship between absorptive capacity and electronic health record systems implementation, which results in better operational cost performance. Theoretically, this study supports the long-term potential benefits of EHR adoption, and its findings are consistent with optimizing efficiency through data standardization and interoperability. From a practical perspective, this study supports hospitals' investments in evolving healthcare information technology systems through the development of a knowledge-based system employing EHR, particularly when hospitals are merging or need a financial strategic plan to control expenses. [ABSTRACT FROM AUTHOR]

This study focuses the theoretical underpinning of the so-called semantic gap. By analysing the discourses on ideals and practices of image search and image use in terms of different understandings of 'information' and 'communication' this study illuminates the epistemological foundation of different ways of thinking about image descriptions. More precisely, it compares the discourse for metadata production, standards and information management with the discourse among humanities scholars. Close readings of handbooks, best practice and interviews with metadata producers discloses a discourse imbued by a mechanical model for communication and information transmission and a focus on objectivity and effectiveness. Simultaneously, interviews with humanities scholars and close readings of recent archival theory reveal another understanding of metadata as historically, institutionally, and even individually situated interpretations. As this study shows, attentiveness to the theoretical underpinning of the different ideals, wants and needs of metadata for images may illuminate why these differences exists. [ABSTRACT FROM AUTHOR]

Spatial data management is crucial for applications like urban planning and environmental monitoring. While traditional relational databases are commonly used, they struggle with large and complex spatial data. NoSQL databases provide support for unstructured data and scalability. This article compares the performance and disk space usage of SQL Server (a relational database) and MongoDB (NoSQL database) using an open-source library. Experiments conducted with the OpenStreetMap dataset from Central America show that the MongoDB database outperformed the relational SQL Server database in most cases, offering practical advantages for spatial data management in Geographic Information System applications. [ABSTRACT FROM AUTHOR]

This paper presents lightweight tooling concepts based on additive manufacturing, with the aim of developing advanced tooling systems as well as installing sensors for real-time monitoring and control during the anchoring and manufacturing of aeronautical parts. Leveraging additive manufacturing techniques in the production of tooling yields benefits in manufacturing flexibility and material usage. These concepts transform traditional tooling systems into active, intelligent tools, improving the manufacturing process and part quality. Integrated sensors measure variables such as displacement, humidity and temperature allowing data analysis and correlation with process quality variables such as accuracy errors, tolerances achieved and surface finish. In addition to sensor integration, additive manufacturing by directed energy arc and wire deposition (DED-arc) has been selected for part manufacturing. The research includes the mechanical characterisation of the material and the microstructure of the material once manufactured by DED-arc. Design for additive manufacturing" principles guide the design process to effectively exploit the capabilities of DED-arc. These turrets, equipped with sensors, allow real-time monitoring and control of turret deformation during clamping and manufacturing of aeronautical parts. As a first step, deformation monitoring is carried out within the defined tolerance of ± 0.15, which allows a control point to be established in the turret. Future analysis of the sensor data will allow correlations with process quality variables to be established. Remarkably, the optimised version of the turret after applying DED technology weighed only 2.2 kg, significantly lighter than the original 6 kg version. Additive manufacturing and the use of lightweight structures for fixture fabrication, followed by the addition of sensors, provide valuable information and control, improving process efficiency and part quality. This research contributes to the development of intelligent and efficient tool systems for aeronautical applications. [ABSTRACT FROM AUTHOR]

Background: Electronic medical record (EMR) systems provide timely access to clinical information and have been shown to improve medication safety. However, EMRs can also create opportunities for error, including system-related errors or errors that were unlikely or not possible with the use of paper medication charts. This study aimed to determine the detection and mitigation strategies adopted by a health district in Australia to target system-related errors and to explore stakeholder views on strategies needed to curb future system-related errors from emerging. Methods: A qualitative descriptive study design was used comprising semi-structured interviews. Data were collected from three hospitals within a health district in Sydney, Australia, between September 2020 and May 2021. Interviews were conducted with EMR users and other key stakeholders (e.g. clinical informatics team members). Participants were asked to reflect on how system-related errors changed over time, and to describe approaches taken by their organisation to detect and mitigate these errors. Thematic analysis was conducted iteratively using a general inductive approach, where codes were assigned as themes emerged from the data. Results: Interviews were conducted with 25 stakeholders. Participants reported that most system-related errors were detected by front-line clinicians. Following error detection, clinicians either reported system-related errors directly to the clinical informatics team or submitted reports to the incident information management system. System-related errors were also reported to be detected via reports run within the EMR, or during organisational processes such as incident investigations or system enhancement projects. EMR redesign was the main approach described by participants for mitigating system-related errors, however other strategies, like regular user education and minimising the use of hybrid systems, were also reported. Conclusions: Initial detection of system-related errors relies heavily on front-line clinicians, however other organisational strategies that are proactive and layered can improve the systemic detection, investigation, and management of errors. Together with EMR design changes, complementary error mitigation strategies, including targeted staff education, can support safe EMR use and development. [ABSTRACT FROM AUTHOR]

Objective To explore the epidemiological characteristics of foodborne disease events in a rural banquet in Sichuan Province from 2004 to 2023, and to provide a scientific basis for the prevention and control of foodborne disease in the rural banquet. Methods The data of foodborne disease events in a rural banquet in Sichuan Province from 2004 to 2023 were collected from the National Foodborne Disease Outbreaks Surveillance System and National Management Information System of Public Health Emergencies and analyzed by descriptive statistics. Results From 2004 to 2023, a total of 189 foodborne disease events in rural banquet were reported in Sichuan Province with 5 971 cases and 22 deaths, and the case fatality rate was 0.37%. The third quarterly was the high incidence period, accounting for 43.39% of the total events. The top three regions with the highest number of reported events were Chengdu (25 events), Luzhou (19 events) and Yibin (18 events). Microbial pathogens were the main pathogenic factors, accounting for 66.67% of the total events. Chemicals were the main causes of death, with 15 and 5 deaths caused by methanol and nitrite, respectively. Meat and meat products were the main causes of foodborne diseases. Improper processing and storage were the main inducing factors. Conclusion The targeted health education, supervision, monitoring, and emergency handling should be carried out to effectively prevent and control foodborne disease events in rural banquets. [ABSTRACT FROM AUTHOR]

Background: During the prolonged COVID-19 pandemic, hospitals became focal points for normalised prevention and control. In this study, we investigated the feasibility of an inpatient bed reservation system for cancer patients that was developed in the department?s public WeChat account. We also explored its role in improving operational efficiency and nursing quality management, as well as in optimising nursing workforce deployment. Methods: We utilised WeChat to facilitate communication between cancer patients and health care professionals. Furthermore, we collected data on admissions, discharges, average number of hospitalisation days, bed utilisation rate, and the number of bed days occupied by hospitalised patients through the hospital information system and nurses? working hours and competency levels through the nurse scheduling system. The average nursing hours per patient per day were calculated. Through the inpatient bed reservation system, the number of accepted admissions, denied admissions, and cancelled admissions from the reservation system were collected. The impact of the bed reservation system on the department?s operational efficiency was analysed by comparing the number of hospitalisation discharges before and after reservations, as well as the average hospitalisation and bed utilisation rates. By comparing nurses? working hours per month and average nursing hours per patient per day, the system?s impact on nurses? working hours and nursing quality indicators was analysed. Results: The average hospitalisation length, bed utilisation rate, and nurses? working hours were significantly lower, and the average number of nursing hours per patient per day was significantly higher after the implementation of the reservation system. The full-cycle bed information management model for cancer patients did not affect the number of discharged patients. Conclusion: Patients? ability to reserve bed types from home in advance using the department?s official WeChat-based inpatient bed reservation system allowed nurses to prepare for their work ahead of time. This in turn improved the operational efficiency of the department and nursing quality, and it optimised the deployment of the nursing workforce [ABSTRACT FROM AUTHOR]

Summary: Software‐defined network (SDN) technology is widely used for computer networks, especially in enterprise data centers and virtualized networking. However, SDN networks encounter severe challenges to security. One such challenge comes from third‐party applications that contain malicious logic and security vulnerabilities, resulting in controller integrity attacks. In this paper, we propose a defensive mechanism of object integrity for SDN (DMoiSDN) to mitigate the issue known as Cross‐App Poisoning (CAP). Our results contribute to increasing the integrity level of the controller's resources by conducting a potential risk analysis, which showed a decrease of 57% in the risk factor for potential attacks. We further examined the results of comparing DMoiSDN's performance with related work that uses information flow control (IFC) policies. The best results among the three conducted scenarios were as follows: we found that decreased latency in our system ranged from 12% to 90%, with an average of 59%, when encountering an increase in requests. It ranged from 78% to 49%, with an average of 63%, when receiving a variable number of total permissions for each application. DMoiSDN is expected to show a perceptible but reasonable latency and, to some extent, be able to avoid a critical impact on performance. [ABSTRACT FROM AUTHOR]

Background: Similar to other low and middle-income countries, Ethiopia faces limitations in using local health data for decision-making.We aimed to assess the effect of an intervention, namely the data-informed platform for health, on the culture of data-based decision making as perceived by district health office staff in Ethiopia's North Shewa Zone. Methods: By designating district health offices as 'clusters', a cluster-randomised controlled trial was implemented. Out of a total of 24 districts in the zone, 12 districts were allocated to intervention arm and the other 12 in the control group arms. In the intervention arm district health office teams were supported in four-monthly cycles of data-driven decision-making over 20 months. This support included: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritizing; and (e) a consultative process to develop, commit to, and follow up on action plans. To measure the culture of data use for decision-making in both intervention and control arms, we interviewed 120 health management staff (5 per district office). Using a Likert scale based standard Performance of Routine Information System Management tool, the information is categorized into six domains:- evidence-based decision making, emphasis on data quality, use of information, problem solving, responsibility and motivation. After converting the Likert scale responses into percentiles, difference-in-difference methods were applied to estimate the net effect of the intervention. In intervention districts, analysis of variance was used to summarize variation by staff designation. Results: The overall decision-making culture in health management staff showed a net improvement of 13% points (95% C.I:9, 18) in intervention districts. The net effect of each of the six domains in turn was an 11% point increase (95% C.I:7, 15) on culture of evidence based decision making, a 16% point increase (95% C.I:8, 24) on emphasis on data quality, a 20% point increase (95% C.I:12, 28) on use of information, a 21% point increase (95% C.I:13, 29) on problem solving, and a 10% point increase (95% C.I:4, 16) on responsibility and motivation. In terms of variation by staff designation within intervention districts, statistically significant differences were observed only for problem solving and responsibility. Conclusion: The data-informed platform for health strategy resulted in a measurable improvement in data use and structured decision-making culture by using existing systems, namely the Performance Monitoring Team meetings. The intervention supported district health offices in identifying and solving problems through a structured process. After further research, DIPH intervention could also be applied to other health administration and facility levels. Trial registration: ClinicalTrials.gov ID: NCT05310682, Dated 25/03/ 2022. [ABSTRACT FROM AUTHOR]

This research was conducted to determine the impact of disruptive innovations with the emergence of online-based transportation on conventional taxi companies in Indonesia. The method used is descriptive research with case studies on two taxi companies, namely PT. Blue Bird Tbk (BIRD) and PT. Express Transindo Utama Tbk (TAXI) during the period 2014-2022. The variables studied were operating income, operating profit/loss, stock prices, and bankruptcy predictions using the Springate model. The results show that the emergence of online-based transportation affects decreasing operating income, operating profit, and stock prices in both companies. The potential for bankruptcy also increases with decrease in income and operating profit. Nevertheless, BIRD can endure in the era of disruption by innovating in services and collaborating with online transportation companies. On the other hand, TAXI’s efforts to innovate have not yielded results, leading to a lack of significant improvement signals in the company’s performance. Adaptability, innovation strategies, and collaboration are identified as key factors for the success of conventional taxi companies in surviving the era of disruption. [ABSTRACT FROM AUTHOR]

Purpose: This bibliometric study is steered to compute the impact of literature published on cloud computing within the fields of information science and library science. The research has been conducted on concentrating the term "Cloud Computing" to search the literature published in both fields, i.e. information science and library science from the time span 2007 to August 2023. This study aims to investigate the top productive country, organizations and highly cited publications. Design/methodology/approach: The period of the exploration was from 2007 to August 2023 for bibliometric analysis and data was collected from the ISI Web of Science. Total 401 documents were retrieved and analyzed to highlight the year-wise distribution of documents type, year-wise most cited articles, prominent journals of the subjects, productivity of organizations, impact of countries and cooccurrences of keywords. The results are grounded on the basis of documents types (articles, early access articles, proceeding papers, book review, editorial material, news items and reviews). Findings: The findings reveal that the most productive year of publication on cloud computing services was 2013. The top productive source is "International Journal of Information Management." The articles entitled "Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors" found as the most cited article and the significant increase in citations is also noteworthy. The most productive organizations on the topic include "Islamic Azad University of Iran," "University Cologne of Germany" and "University Nova Lisboa of Portugal." The results confirmed that the USA dominates in the production of research on "Cloud Computing Services" and the most repeated keyword in the literature is cloud computing. The research articles are the most cited sources of research. Originality/value: This bibliometric research is an original piece of work that has been conducted to measure the research production in the field of information science and library science during 2007−2023. This piece of work is valuable for those who want to study the literature on cloud computing in the area of information science and library science. [ABSTRACT FROM AUTHOR]

Purpose: Although universities have extensive research and initiatives in place that align with the United Nations' Sustainable Development Goals (SDGs), there is still a significant gap in documenting and assessing these efforts. This paper aims to discuss how academic libraries can apply their information management skills and open-access platforms, to facilitate the discoverability and retrieval of evidence on SDGs. Design/methodology/approach: Introduced by a brief literature review on the role of libraries in contributing to the SDGs in general, the authors draw on their personal experiences as metadata specialists, participating in a project aimed at linking their university's research output to the SDGs. A case study, from the University of Pretoria's Veterinary Science Library, is used as an example to demonstrate the benefits of resourceful metadata in organising, communicating and raising awareness about the SDGs in the field of veterinary science. Findings: Through practical examples and recommended workflows, this paper illustrates that metadata specialists are perfectly positioned to apply their information management skills and library platforms to facilitate the discoverability and retrieval of evidence on SDGs. Originality/value: Although there are increasing reports on the contributions of libraries to support the successful implementation of the SDGs, limited information exists on the role of metadata specialists, as well as those with a practical focus. [ABSTRACT FROM AUTHOR]

This study suggests the need for best practices, specialized tools and standards, and targeted outreach related to Web-based content cited in theses. It analyzes citation practices in a corpus of master's theses in performance studies published at Texas A&M University from 2012 to 2020. Finding that only a slim majority of Web-based material cited in the theses remains fully functional within a decade of citation, this study confirms that "Web at large" content poses the greatest risk of irretrievable loss. Additionally, it considers actions by student authors that make theses vulnerable to evidentiary loss or change. A deeper understanding of the fragility of Web-based content and the potential for mitigation can inform needed interventions by librarians and other partners in graduate research. [ABSTRACT FROM AUTHOR]

Intelligent transportation systems (ITSs) make it possible for applications such as autonomous driving, active safety systems and smart cities. As the infrastructure of ITSs, vehicular ad-hoc network (VANET) plays a key role in ensuring traffic safety while improving driving experience and comfort. However, VANET faces many challenges as the network is exposed to the public and involves sensitive information such as vehicle control commands and driving records. Although blockchain technology can provide such features as decentralization, immutability, non-reliance on trust and traceability, most of the existing blockchain systems impose high storage and computing capacity requirements for participating nodes while terminals nodes in VANET, such as road-side units (RSUs), on-board units (OBUs) and sensors, usually have very limited storage and computing capacity. To solve this problem, this paper proposes a blockchain system that provides scalable storage capacity for VANETs. The proposed scheme uses network sharding and multi-consensus strategy to improve the topology and consensus process of the blockchain. Aimed at lowering the storage requirement on the RSU nodes that participate in the blockchain, a collaborative storage mechanism and a dynamic copy number strategy for the blockchain ledger is designed. Experimental results show that compared to existing schemes, the proposed scalable blockchain storage scheme can significantly lower the storage requirement for the blockchain nodes, thus making it possible for the nodes with limited storage capacity in VANET to participate in the maintenance of the blockchain to prevent the blockchain from drifting towards centralization, and support maximal sharing of road traffic information while ensuring the security, privacy and trustworthiness of information. [ABSTRACT FROM AUTHOR]

Wireless Power Transmission (WPT) is widely used. In practical engineering applications, the transmitter and receiver of a stable and reliable WPT system need to establish not only a power transmission channel but also a data transmission channel to realize closed-loop control and information interaction. In this paper, a novel simultaneous wireless power and data transfer system based on a series–parallel (SP) resonant network is proposed. The system integrates an SP higher-order resonant network with series carrier injection, which makes power transmission and data transmission share a magnetic coupling channel. The isolation between power and data is realized by exploiting the frequency characteristics of the compensation network, thus realizing efficient power transmission and data transmission. In this paper, accurate and detailed mathematical modeling of the system is conducted, and the gain characteristics of the power transmission channel and the data transmission channel are demonstrated. Meanwhile, the mutual interference between the two channels is analyzed, and a feasible and effective parameter design method is developed. Finally, an experimental prototype with an output power of 16 W and a backward data rate of 100 Kbps is constructed to verify the feasibility of the proposed system and the correctness of the parameter design. [ABSTRACT FROM AUTHOR]

With the increase in types of fire risk and the expansion of fire management coverage, it is urgent to involve multiple subjects in fire management. Cross-sectoral joint fire management is a new fire management mode based on collaboration between the fire management sector and the industry management sector in China. Additionally, fire information from multiple sources plays a significant role in the formation of the cross-sectoral joint fire management mode. To explore the operating characteristics and influencing factors of the cross-sectoral joint fire management mode, this paper constructed a cross-sectoral joint fire management game model by focusing on the interactions and game relationships between multiple organizations. Through numerical simulation analysis, the mechanisms by which the sharing level, coverage range, and disclosure degree of fire information influence the evolution of the game system are investigated. The results show that with the improvement in the sharing level, the coverage range, and the disclosure degree of fire information, although the evolutionary paths of the game system and game subjects' strategies are different, the cross-sectoral joint fire management game system can form a stable strategy combination of (1,1,1). This indicates that the sharing level, coverage range, and disclosure degree of fire information play positive driving roles in the formation of the cross-sectoral joint fire management mode. Furthermore, it is found that the fire management sector has a greater influence on the cross-sectoral joint fire management mode. Finally, the implications of improving the effectiveness of cross-sectoral joint fire management are proposed: enhancing institutional support, promoting information sharing, and expanding channels for information disclosure. [ABSTRACT FROM AUTHOR]

Polar codes have garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provable capacity achieving capability. They have been standardized to be used for encoding information on the control channels in 5G wireless networks due to their robustness for short codeword lengths. The conventional approach to generate polar codes is to recursively use 2 × 2 kernels and polarize channel capacities. This approach however, has a limitation of only having the ability to generate codewords of length N o r i g = 2 n form. In order to mitigate this limitation, multiple techniques have been developed, e.g., polarization kernels of larger sizes, multi-kernel polar codes, and downsizing techniques like puncturing or shortening. However, the availability of so many design options and parameters, in turn makes the choice of design parameters quite challenging. In this paper, the authors propose a novel polar code construction technique called Adaptive Segmented Aggregation which generates polar codewords of any arbitrary codeword length. This approach involves dividing the entire codeword into smaller segments that can be independently encoded and decoded, thereby aggregated for channel processing. Additionally a rate assignment methodology has been derived for the proposed technique, that is tuned to the design requirement. [ABSTRACT FROM AUTHOR]

In recent years, medicine has undergone profound changes, strongly entering a new phase defined as the "era of precision medicine". In this context, patient clinical management involves various scientific approaches that allow for a comprehensive pathology evaluation: from preventive processes (where applicable) to genetic and diagnostic studies. In this scenario, biobanks play an important role and, over the years, have gained increasing prestige, moving from small deposits to large collections of samples of various natures. Disease-oriented biobanks are rapidly developing as they provide useful information for the management of complex diseases, such as melanoma. Indeed, melanoma, given its highly heterogeneous characteristics, is one of the oncologic diseases with the greatest clinical and therapeutic management complexity. So, the possibility of extrapolating tissue, genetic and imaging data from dedicated biobanks could result in more selective study approaches. In this review, we specifically analyze the several biobank types to evaluate their role in technology development, patient monitoring and research of new biomarkers, especially in the melanoma context. [ABSTRACT FROM AUTHOR]

Biobanks are infrastructures essential for research involving multi-disciplinary teams and an increasing number of stakeholders. In the field of personalized medicine, biobanks play a key role through the provision of well-characterized and annotated samples protecting at the same time the right of donors. The Andalusian Public Health System Biobank (SSPA Biobank) has implemented a global information management system made up of different modules that allow for the recording, traceability and monitoring of all the information associated with the biobank operations. The data model, designed in a standardized and normalized way according to international initiatives on data harmonization, integrates the information necessary to guarantee the quality of results from research, benefiting researchers, clinicians and donors. [ABSTRACT FROM AUTHOR]

Assertion is the use of declarative sentences to convey information, which necessitates meeting the "justified-belief norm" as a prerequisite. However, a significant amount of misinformation that did not meet these conditions was spread during COVID-19, leading to a reintroduction of the assertion norm. One possible hypothesis is that the threatening content of the misinformation influenced the perception of the norm. However, this remains unclear to researchers. Therefore, we conducted two experiments to investigate the effect of threatening content in information on individuals' perceptions of norms. In all the experiments, participants read backstories with and without threatening content, followed by answering assertion questions. It was observed that people do follow a looser assertion norm for information that contains threatening content. Additionally, further exploration revealed that threatening factors also lead individuals to more easily perceive the related content as truth and reduce the probability of being blamed. These two outcomes provide some explanation for the underlying mechanism of threatening factors' influence. The research results further refined the theory of assertion norms, offering a certain basis for information management. [ABSTRACT FROM AUTHOR]

We introduce pattern models , a dynamic epistemic logic for analyzing distributed systems. First, we present a version of pattern models where the full-information protocol , widely studied in distributed computability, is static in the product definition of pattern models. Next, we parametrize such a logic so as to add the capability to model dynamics of arbitrary deterministic protocols. We thus give a systematic construction of pattern models for a large variety of distributed-computing models called dynamic-network models. Using pattern models, the epistemic dynamics of a proper subclass of dynamic-network models called oblivious can be described using a static pattern model, hence using constant space. For this case, we present a sufficient unsolvability condition for the consensus task that can be easily verified analyzing the structure of the initial epistemic model and the pattern model for a given oblivious dynamic-network model. [ABSTRACT FROM AUTHOR]

Background: The first waves of the COVID-19 pandemic had a negative impact on health systems and health professionals, due to the high number of cases and a lack of preparation. The aim of this study was to understand how nurses working in hospital units and in intensive care perceived the performance of nurse managers and senior hospital management during the first two waves of the pandemic. Methods: The phenomenological approach proposed by Giorgi was used to investigate perceptions of the performance of nurse managers and senior hospital management during the first two waves of the COVID-19 pandemic in Spain. Fourteen clinical nurses who worked on the front line in inpatient units or intensive care units of the Health Services of Extremadura and Madrid in the first (March–April 2020) and second (October–November 2020) waves of the COVID-19 pandemic participated in this study. The data was collected through semi-structured interviews, following a script of themes, in a theoretical sample of nurses who were worked during the pandemic. Results: Two main themes emerged from the analysis of the data: (1) perceptions about the performance of nurse managers and senior hospital managers during the first and second waves of the pandemic (health system failure; belief that senior hospital management professionals could have managed the pandemic better; recognizing the efforts of middle management (nursing supervisors); insufficient institutional support) and (2) strategies employed by nurses to compensate for the weaknesses in pandemic management. Conclusions: The clinical nurses perceived that the nurse managers demonstrated better management of the pandemic than the hospital's senior management, which they attribute to their proximity, empathy, accessibility, and ability to mediate between them and the senior management. The nurses also believe that the senior management of the hospitals was to blame for organisational failures and the poor management of the pandemic. [ABSTRACT FROM AUTHOR]

Through a questionnaire survey of 326 respondents in romantic relationships, we apply the theory of motivated information management (TMIM) in explaining the process of managing uncertainty through interpersonal electronic surveillance (IES) in romantic relationships. Our results indicate that: (1) In the interpretation phase of TMIM, the uncertainty discrepancy of romantic relationship is positively related to people's anxiety. (2) In the evaluation phase, the anxiety can significantly decrease the individual's efficacy, while increase (positive) outcome expectancy (OE) of IES and OE would positively influence people's efficacy. (3) In the decision phase, the positive effect of outcome expectation is significant enough, showing a direct and positive impact on IES, which causes efficacy not to significantly influence IES. Theoretical implications related to revised TMIM and practical implications related to IES as a means of managing uncertainty in romantic relationships are discussed. [ABSTRACT FROM AUTHOR]

The ‘Rational Laboratory Use Project’ (RLUP) was launched in 2018 by the Department of Examination and Diagnosis Services under the General Directorate of Health Services of the Republic of Turkey’s Ministry of Health. In this study, we aimed to determine the rate of implementation of RLUP in medical biochemistry laboratories, and to contribute to new regulations by collecting the information and opinions of the laboratory experts participating the survey.Thirty questions were uploaded to an online survey tool (SurveyMonkey®, San Mateo, ABD). The first five were descriptive for laboratories. Among the remaining 25 questions, one is open-ended and addresses the various topics encompassed by the project’s scope.The questionnaire was completed by 202 medical biochemistry specialists, of whom 82.12 % reported that they did not implement autoverification. 55.65 % defined consultations in Hospital Management Information System (HIMS), but; 70.49 % were not using it actively. 57.69 % of the participants answered, “I agree” to the statement “I think RLUP is feasible”. It was observed that the specialists tried to implement rational laboratory practices partially depending on their laboratory capacity, hospital administration and Laboratory Information Management System (LIMS).Increasing clinicians’ awareness could increase the success of this project, which might provide more effective diagnosis and treatment for the patient. In our view, actively involving stakeholders of the information management system, which is not under the direct control of laboratory professionals, in the RLUP will accelerate the development of the project. [ABSTRACT FROM AUTHOR]

The application of computer information management system (IMS for short here) in university management faces problems such as incomplete system software and complex system design. Applying clustering algorithms (CA for short here) to computer student IMS can help optimize the system's overall effectiveness. This article constructed a computer student IMS based on computer technology and applied it to the management of college students. This article also combined CA to conduct relevant effectiveness tests on the system, in order to optimize the overall effectiveness of the system. Under the algorithm in this article, the average connection speed for each user accessing the system was 9.17 Mbps. The average reaction time was 0.34 seconds, the average security level was 92.47%, and the highest memory usage rate of the system was 34.27%; Under the decision tree algorithm, the average connection speed of each user accessing the system was 8.82 Mbps, and the average reaction time reached 0.64 s. The average security level was 88.41%, and the highest memory usage rate was 42.58%. Under the artificial neural network algorithm, the average connection speed of the system was 8.47 Mbps, the average response time was 0.86 s, and the highest memory usage rate was 45.97%. Analyzing the data reveals that the algorithm introduced in this paper significantly enhances system connection speed and reduces reaction time. This improvement not only enhances security measures but also minimizes memory usage, effectively optimizing the overall efficiency of the system. [ABSTRACT FROM AUTHOR]

Purpose: Using a case study of Zimbabwe's central government, this study aims to empirically examine the extent to which senior management was supportive of the records management function as well as the reasons why such levels of support subsisted. Design/methodology/approach: This mixed methods research made use of the explanatory sequential research design where quantitative responses from records and information supervisors were either confirmed or disconfirmed by open-ended interview responses from finance and administration directors. Fifteen records and information supervisors and eight finance and administration directors participated in the study. Document reviews and personal observation were also used in soliciting data. Findings: The study revealed that top management was not very supportive of the records management function as a result of lack of knowledge about records management and because of negative perceptions and attitudes harboured by some senior managers towards the functional area. The study also revealed that organisational structural factors also played a part as the records and information management section was poorly represented by finance and administration directors at the top, who by virtue of their training had little knowledge about and interest in records management. Originality/value: The study raises the importance of senior management in records management processes, projects and programmes. It highlights that without senior management support, records management initiatives are bound to fail. Thus, the study is important as it raises the need to incorporate senior management as part of organisations' tactical and operational strategy. [ABSTRACT FROM AUTHOR]

The human resources mobile information system (HRMoIS) provides users with direct access to information via mobile devices, enhancing efficiency, productivity, and the user experience. It includes mobile applications, websites, SMS services, and other communication mediums. This system enhances information mobility, facilitates operational processes, and supports decision-making in the ever-evolving technological landscape, ultimately improving users' efficiency and productivity. Al-Anbar Province is undergoing significant urban and economic development. Still, more research is needed on the impact of HRMoIS on employee performance in Anbar to enhance their skills. This study aims to provide insights for top management and decision-makers on implementing similar methods to enhance employee performance. The study employs a questionnaire to survey managers and regular employees in 20 small organizations in Al Anbar, Iraq. The data is analyzed using percentages, frequencies, Pearson correlation, and Cronbach's alpha coefficient. This allows for a comprehensive examination of all the essential aspects of human resource dynamics. The questionnaire upholds integrity and precision by aligning with roles and responsibilities. The study found that organizations implementing HRMoIS had higher mean values despite barriers such as organizational resistance, limited resources, and inadequate training. The results underscore the importance of organizations addressing these issues and enhancing their HRMoIS adoption. The study investigates the impact of HRMoIS on HR performance in small organizations in Iraq. The results show a positive correlation between mobile information systems and HR management efficiency. The study recommends implementing mobile information systems in small organizations in Al Anbar to enhance their performance. It emphasizes the need for providing necessary hardware and software, hiring experienced consultants, ensuring employee training and development, supplying HRMoIS with relevant data, and appointing experienced employees to keep up with technological advancements. [ABSTRACT FROM AUTHOR]