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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We consider a manufacturer and an e-platform where the manufacturer sells products through offline and e-platform channels under the cap-and-trade scheme. The interaction between the two channels produces the cross-channel effect (CCE). This manufacturer cooperates with the e-platform in the agency or reseller mode. In addition, the platform shares its observed data with the manufacturer and the blockchain can achieve traceability and high transparency of these data. We formulate a Stackelberg game to derive the following results: In the agency mode, the optimal service level is independent of (decreases with) CCE without (with) blockchain. CCE positively affects the optimal service level in the reseller mode and the optimal service level has no impact on (increases with) the cap in the agency (reseller) mode. Second, when the platform-enabled power is high (low), the platform is (not) willing to adopt blockchain. Third, coordination of the manufacturer and platform only can be achieved in the agency mode when CCE is low with blockchain. The reseller mode can (cannot) achieve coordination of the two firms with (without) blockchain. We also consider the cases where the manufacturer serves as the leader and the omni-channel strategy is adopted to check the robustness of the coordination results. [ABSTRACT FROM AUTHOR]

Digital enabled agility reflects the transformative outset of an organisation to first upgrade its business processes digitally towards facilitating real-time information processing/capabilities. Second, tapping from real-time capabilities, digital enabled agility maximises an agile response's efficacy in enhancing the sophistication of rapidity, flexibility, and sensing involved. In this backdrop, driven by newer IT infrastructure and disruptive technology, this research accentuates on Industry 4.0 digitalisation to understand how a manufacturer can gain digital enabled agility. An empirical survey of manufacturers within the premise of Industry 4.0 is conducted. Drawn from the findings, the capabilities of traceability and visibility can be facilitated by Industry 4.0 that would improve information sharing and information quality in real-time. These capabilities are key propellants to unlock the digital extent of agility. This research however details further how this scope of agility is an extension to that of the scope of typical agility in terms of its ability to handle expansive information processing needs and dynamic coordination/resource orchestration. Insights are weaved under the purviews of (a) organisational information processing view and (b) the manufacturer who is coordinating contemporary dynamic production and allied value chain requirements. [ABSTRACT FROM AUTHOR]

This study investigates the effects of the organization of industrial Research & Development on industrial researchers' knowledge acquisition behavior. Specifically, we test a model about how the fit of individuals with their research tasks affects whether industrial researchers acquire knowledge from outside their assigned projects. Empirical analyses from the R&D laboratory of a global pharmaceutical company show that person-task-fit has a non-linear effect on the knowledge content exchanged through interpersonal interactions. Implications for the management and organization of R&D activities are discussed. [ABSTRACT FROM AUTHOR]

Sire is a Python/C++ library that is used both to prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of many other programs and libraries. This empowers researchers to use sire to write a single script that can, for example, load a molecule from a PDBx/mmCIF file via Gemmi, perform SMARTS searches via RDKit, parameterize molecules using BioSimSpace, run GPU-accelerated molecular dynamics via OpenMM, and then display the resulting dynamics trajectory in a NGLView Jupyter notebook 3D molecular viewer. This functionality is built on by BioSimSpace, which uses sire's molecular information engine to interconvert with programs such as GROMACS, NAMD, Amber, and AmberTools for automated molecular parameterization and the running of molecular dynamics, metadynamics, and alchemical free energy workflows. Sire comes complete with a powerful molecular information search engine, plus trajectory loading and editing, analysis, and energy evaluation engines. This, when combined with an in-built computer algebra system, gives substantial flexibility to researchers to load, search for, edit, and combine molecular information from multiple sources and use that to drive novel algorithms by combining functionality from other programs. Sire is open source (GPL3) and is available via conda and at a free Jupyter notebook server at https://try.openbiosim.org. Sire is supported by the not-for-profit OpenBioSim community interest company. [ABSTRACT FROM AUTHOR]

Core enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community. [ABSTRACT FROM AUTHOR]

Cybersecurity presents non-negligible challenges for firm collaboration and supply chain viability, as information exchange among nodes introduces potential interdependent risks. How to make appropriate decisions on security investments and information exchange modes is a significant issue for supply chain members. Considering two information exchange modes: system interconnection and system independence, this study develops two game models to investigate the cybersecurity investments in a vertical supply chain composed of a retailer and n suppliers. Initial analysis shows that although firms learn investment decisions mutually in the face of a changing cybersecurity environment, suppliers always take a free ride on the efforts of retailer in two cases and the increased interdependent risks will damp nodes enthusiasm for security investments. Next, to compare the two cases, we introduce information exchange efficiency as the mediate parameter to link degree of system interconnection and proportion of information shared. We found that under the system independence mode, firms with high information-exchanging demand in the large-scale supply chain are more motivated to invest in cybersecurity. Furthermore, we extend our models to a centralised decision-making scenario. We find that security investment efficiency is greatly improved, and the free-riding behaviour of supplier is significantly reduced when systems are interconnected. [ABSTRACT FROM AUTHOR]

Interorganizational partnerships can spur innovation, but their value may be diminished by friction in knowledge flows between firms. We consider how a partner's organizational structure may influence the knowledge that is accessible via partnerships. We focus on how a partner's structure trades off localized autonomy for its managers, which facilitates timelier decision making, and unified control, which facilitates integration. By shaping this balance, centralization of decision rights within the partner organization shapes access to its knowledge. Centralized structures generate wide-ranging internal knowledge pathways that enable access to a broader array of a partner's knowledge. However, the reduced managerial autonomy afforded by centralization makes decision making more cumbersome, which constricts the rate of access to a partner's knowledge. We find evidence of this tradeoff in the context of corporate venture capital relationships between incumbents and startups in the pharmaceutical industry. An increase in the incumbent's diversity of knowledge or in the knowledge required by the startup enhances the value of a greater breadth of access, whereas the degree to which the startup can leverage social ties (affinity) or hierarchical fiat (authority) alleviates the costs of a reduced access rate. Each of these features makes an incumbent organization's centralization more valuable to the startup. By highlighting this tension related to centralization, our findings suggest that new firms striving to maximize their partnership benefits may need to carefully consider their partners' internal structures. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The historiography of the American effort in World War I describes an American unwillingness to learn from the Allies. However true that may be for the combat arms, it was untrue for the Army Medical Department (AMEDD). The AMEDD sought a wide range of information from the beginning of the war, and through multiple channels that expand substantially and systematically once the U.S. entered the war. The information was also disseminated through multiple channels and made significant impacts on medical care in the American Expeditionary Force (AEF) during the Great War. Historians should be more cautious about assuming that all parts of the AEF were resistant to foreign information. [ABSTRACT FROM AUTHOR]

The Internet's widespread adoption and recent technological developments have provided researchers with the opportunity to capture new data types (e.g., images, passively collected data), which offer several advantages over conventional survey data. Nevertheless, the limited participation rate in projects requiring to share such data may limit their benefits, and even their feasibility. To estimate the willingness to participate in such projects in advance, researchers frequently rely on surveys. However, the way researchers describe what data should be shared and how, and the phrasing of questions asked to participants to obtain their agreement may result in different estimates. This study presents the results of a conjoint experiment that estimates the hypothetical willingness of participants to engage in two research activities that require sharing geolocation data. Three different descriptions of the activities were presented to participants: a neutral one, one emphasizing the necessity to commit to participate, and one emphasizing safe handling of shared data. The three descriptions elicited different levels of willingness, with a maximum effect of 7.0 percentage points (statistically significant). Additionally, the importance given by participants to the attributes of the activities (e.g., project duration or incentives) differed depending on the description. Notably, the description that emphasized data safety produced lower levels of willingness compared to the neutral one. This suggests that researchers should avoid overly emphasizing safety assurances when requesting the sharing of sensitive data, beyond the necessary information required for obtaining informed consent from participants. [ABSTRACT FROM AUTHOR]

Knowledge sharing is considered an important promotor of new product development (NPD) performance. However, studies have shown that making experts share knowledge in new product development (NPD) projects is often a challenging task. Consequently, this topic has attracted substantial attention in academic research. However, although studies have produced valuable insights, more detailed accounts of the mechanisms shaping knowledge sharing processes in NPD projects are sparse. To add to the knowledge on this topic, this study conducts a series of interviews with NPD professionals at manufacturers of high-tech industrial products to identify 'factors influencing knowledge sharing' (FIKS). The identified FIKS are explained through the socio-physiological theory, the 'reasoned action approach' (RAA). This involves several contributions. First, the study provides a detailed explanation of the role of FIKS by describing how they affect the behaviour of knowledge providers and receivers in NPD processes. Second, by identifying 161 FIKS in NPD processes, organised under 18 categories, the study offers the so far most extensive account of FIKS in NPD processes. Third, the findings suggest a special characteristic of knowledge sharing in NPD contexts concerning the relatively high importance of knowledge receiver behaviour. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) facilitates the connectivity of billions of physical devices for exchanging information and enabling a wide range of applications. These applications can be presented in the form of dependent tasks, as outlined in a workflow. These workflows face limitations due to constraints in IoT sensors. To address these limitations, cloud computing has emerged to offer a large capacity of computing and storing with a great capability to adjust resources according to the need. However, cloud computing might not adequately meet the low‐latency of IoT workflow requirements when scheduling a workflow composed of IoT tasks due to its centralized nature. Moreover, cloud computing is not ideal for delay‐sensitive workflows and may increase communication costs. In response to these challenges, the use of fog computing as an extension to cloud computing scheme is recommended. Fog computing aims to process workflow tasks close to IoT devices. While fog computing offers various advantages, integrating these systems into workflow scheduling remains one of the most formidable challenges in distributed environments. Indeed, significant issues arise due to the timely execution and the resource limitations. In this survey paper, we present a Systematic Literature Review (SLR) on the current state of the art in this domain. We propose a taxonomy to compare and evaluate the existing studies on workflow scheduling approaches in cloud–fog computing environments. This taxonomy encompasses various criteria, including scheduling techniques, performance metrics, workflow dependencies, scheduling policies, and evaluation tools. We highlight certain recommendations for open issues which require more investigations. Our aim is to provide valuable insights for researchers and developers interested in understanding the contributions and challenges of current workflow scheduling approaches in cloud–fog computing environments. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a rapidly emerging technology that has become more valuable and vital in our daily lives. This technology enables connection and communication between objects and devices and allows these objects to exchange information and perform intelligent operations with each other. However, due to the scale of the network, the heterogeneity of the network, the insecurity of many of these devices, and privacy protection, it faces several challenges. In the last decade, distributed DDoS attacks in IoT networks have become one of the growing challenges that require serious attention and investigation. DDoS attacks take advantage of the limited resources available on IoT devices, which disrupts the functionality of IoT-connected applications and services. This article comprehensively examines the effects of DDoS attacks in the context of the IoT, which cause significant harm to existing systems. Also, this paper investigates several solutions to identify and deal with this type of attack. Finally, this study suggests a broad line of research in the field of IoT security, dedicated to examining how to adapt to current challenges and predicting future trends. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies? Design/methodology/approach: A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels. Findings: The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item's order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy. Practical implications: The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models. Originality/value: The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature? [ABSTRACT FROM AUTHOR]

The article examines the contemporary challenges of international journalism in the context of armed conflicts, particularly the war in Ukraine. It focuses on the risks to journalists' safety, issues of censorship and information manipulation, as well as the impact of new technologies on the timeliness and accuracy of news. The study expands existing knowledge about international journalism by proposing a new model for analyzing the interaction of political, social, and technological factors in conflict situations. Using a comprehensive case study methodology and bibliometric research, the article explores practical aspects of information exchange, including the creation of secure communication channels, adherence to ethical standards, and fact-checking. Content analysis of media messages and surveys of journalists working in conflict zones are employed in the research. The study reveals that the war in Ukraine has led to a significant decline in international cooperation due to difficulties in ensuring the credibility of information, an increase in censorship and manipulation. Particularly pressing are the issues of journalists' safety, restrictions on access to critical information sources, and challenges in maintaining media independence. Additionally, the article highlights that armed conflicts pose numerous threats to journalists, such as risks of physical attacks, detention, and even life-threatening situations. In combat conditions, journalists often face restricted access to important information, complicating their work and impacting the quality of event coverage. These conditions necessitate new approaches to protecting journalists at both individual and institutional levels, as well as improving international safety standards and support. The findings indicate the need to develop new strategies for protecting journalists, ensuring the accuracy of information, and strengthening international media cooperation. These conclusions have broad implications for understanding modem information wars and forming effective mechanisms to counter disinformation. The article makes a significant contribution to the advancement of journalism and may be useful for journalists, scholars, policymakers, and anyone interested in safeguarding freedom of speech and developing a democratic society. [ABSTRACT FROM AUTHOR]

The SAMINOR Study represents a unique data collection on health and diseases among the multiethnic population – including the Sámi population in Norway – making it a case study for discussing Sámi research data governance in a health context. This article describes how Sámi interests and needs in the SAMINOR Study are governed by two steps of a research application review process consisting of the SAMINOR project board and the Sámi Expert Ethical Committee for Sámi Health Research. We explore how these two steps align with the CARE principles for Collective Benefit, Authority to Control, Responsibility, and Ethics, which are global principles for Indigenous data governance and promote Indigenous data sovereignty. The CARE principles stress the importance of Indigenous self-determination and control, tangible benefits, ethical use, and the promotion of Indigenous values and equity. We found compliance between most of the main and sub- principles but observed the need to address reuse and data sharing more explicitly. The CARE principles do not consider ownership of research data, which for the SAMINOR study is outside of Sámi people's control, hence we question whether Indigenous data sovereignty is achieved for the SAMINOR data. [ABSTRACT FROM AUTHOR]

Vibration signals play a crucial role in mechanical fault diagnosis. However, they are susceptible to various noise disturbances, presenting challenges for reliable fault detection. We propose an end-to-end Cross-task Attention Joint Learning (CTA-JL) model that concurrently denoises and diagnoses faults in noisy signals. This model utilizes a multi-task encoder, composed of task-shared and task-specific feature encoding units, along with a feature information exchange unit with a Cross-task Attention (CTA) mechanism, fostering information exchange across different tasks. By collectively executing diagnosis and denoising tasks and sharing valuable task information, the model enhances prediction accuracy and denoising performance. Under three noise conditions of SNR = −9 dB, −6 dB, and −3 dB, the prediction accuracy of CTA-JL on the rolling bearing datasets reached 91.38%, 97.95%, and 99.69%, respectively. Meanwhile, the result on elevator guide system datasets reached 87.31%, 95.58%, and 99.64% [ABSTRACT FROM AUTHOR]

This paper discusses how purposively designed relational governance institutions may be used to engage government and the private sector to promote the growth of environmental goods and services (EGS) markets under the Africa Continental Free Trade Agreement (AfCFTA). The paper distinguishes between a transactional versus relational governance structure and finds that the system of laws, regulations, and practices governing the relationship between government and the private sector in the United States is relational. AfCFTA can benefit from the U.S. experience. There are several agencies and departments that can play a coordinating role to engage the private sector. The U.S. experience suggests that growing the relationship between government and the private sector must be at low administrative cost, trust between government and private sector, information sharing, and common policy vision. The paper discusses challenges, especially land ownership and finance that AfCFTA must address to be successful. [ABSTRACT FROM AUTHOR]

Increased use of collaborative technologies and agile teamwork models has led to a greater need for temporary teams. Unfortunately, they lack the normal team formation processes that traditional teams use. Information sharing recommender systems can be used to share information about team members amongst the team; however, these systems rely on the team members themselves to disclose valuable information. While prior research has shown that an effective way to encourage user disclosure is through explanations to the user about what benefits they will gain from disclosure, the timing of such explanations has yet to be consideblack. In a between-subjects study with 150 participants, we assessed the content and timing of explanations on levels of disclosure in temporary teams. Our results indicate that providing benefit-related explanations during the time of disclosure can increase user disclosure, and providing benefit-related explanations during the recommendation process can increase user trust in the system. These results provide important design implications for teams and the HCI community. [ABSTRACT FROM AUTHOR]

Biodiversity research is essential for addressing the global biodiversity crisis, necessitating diverse participation and perspectives of researchers from a wide range of backgrounds. However, conservation faces a significant inclusivity problem because local expertise from biodiversity‐rich but economically disadvantaged regions is often underrepresented. This underrepresentation is driven by linguistic bias, undervalued contributions, parachute science practices, and capacity constraints. Although fragmented solutions exist, a unified multistakeholder approach is needed to address the interconnected and systemic conservation issues. We devised a holistic framework of collective responsibility across all research participants and tailored strategies that embrace diversity and dismantle systemic barriers to equitable collaboration. This framework delineates the diverse actors and practices required for promoting inclusivity in biodiversity research, assigning clear responsibilities to researchers, publishers, institutions, and funding bodies. Strategies for researchers include cultivating self‐awareness, expanding literature searches, fostering partnerships with local experts, and promoting knowledge exchange. For institutions, we recommend establishing specialized liaison roles, implementing equitable policies, allocating resources for diversity initiatives, and enhancing support for international researchers. Publishers can facilitate multilingual dissemination, remove financial barriers, establish inclusivity standards, and ensure equitable representation in peer review. Funders must remove systemic barriers, strengthen research networks, and prioritize equitable resource allocation. Implementing these stakeholder‐specific strategies can help dismantle deep‐rooted biases and structural inequities in biodiversity research, catalyzing a shift toward a more inclusive and representative model that amplifies diverse perspectives and maximizes collective knowledge for effective global conservation. [ABSTRACT FROM AUTHOR]

Africa's diverse climates and sparse hydro-meteorological networks create significant challenges in accurately estimating river discharge. Discharge data are crucial for managing water resources and predicting extremes. Our review assesses the data gap, existing methods, and technologies for river discharge estimation in Africa. Limited gauging networks on rivers, including in 63 transboundary basins, hinder accurate discharge modelling, affecting resource management and disaster response. Despite the potential of remote sensing, Geographic Information System (GIS), satellite imagery, and machine learning, their large-scale application for river discharge monitoring in Africa is limited. We propose the use of a monitoring system involving local communities in data collection and decision making, supported by global data centres, enhanced regional data sharing, and strengthened transboundary cooperation. For example, incorporating water data products, including discharge data, in data cubes, such as Digital Earth Africa, could improve monitoring. Strategic investments in hydro-meteorological instrumentation are crucial for strengthening climate resilience. [ABSTRACT FROM AUTHOR]

This study aims to untangle the knowledge creation in the cross-project organisations. Drawing on knowledge creation theory, this study developed a theoretical model and hypotheses, and examined them with 402 samples in China. The results indicate that knowledge sharing mediates the relationship between innovation climate and knowledge creation. The mediation is further moderated by knowledge integration capability. By the comparison, marketing knowledge is the easiest to create, while managerial knowledge is the most difficult to create. This study contributes to knowledge creation theory by making an in-depth discussion on the differences of specific types of knowledge creation. [ABSTRACT FROM AUTHOR]

The article investigates the progress in the geographical knowledge of Sonora based on explorations by Adam Gilg, a Moravian Jesuit in Spanish service. Gilg spent eighteen years (1688–1710) at the northern frontier of New Spain, where he worked as a missionary among the Seri (Comcáac) and Pima (O'odham) peoples. In the period between 1688 and 1693, Gilg drafted three maps of Sonora that represent three stages in proselytization efforts and European geographical knowledge of Sonora. The comparative analysis of these maps makes an interesting case study of how a map, once compiled, was updated and corrected in accordance with new data subsequently collected. It also illustrates the interaction and knowledge exchange between Jesuits serving in the region (Eusebio Kino, Marcus Kappus) and the local Native Nations, the Seris and the Pimas. [ABSTRACT FROM AUTHOR]

In systems in which many heterogeneous agents operate autonomously, with competing goals and without a centralized planner or global information repository, safety and performance can only be guaranteed by "social" rules imposed on the behavior of individual agents. Social laws are structured in a way that they can be verified just by using local information made available to an agent by a small number of its neighbors. Automobile mobility with traffic rules and logistics robots in warehouses are canonical examples of such "regulated autonomy", but many other fairly-competing autonomous systems are to be expected shortly. In these systems, detecting whether an agent is not abiding by the rules is crucial for raising an alert and taking appropriate countermeasures. However, the limited visibility due to the local nature of the information makes the problem of misbehavior detection hard for any single agent, and only an exchange of information between agents can provide sufficient clues to arrive at a decision. This paper attacks the misbehavior detection problem for a class of socially organized autonomous systems, where the behavior of agents depends on the presence or absence of other neighbors. We propose a solution involving a "local monitor", which runs on each agent and includes a hybrid observer and a set-valued consensus node. Based on whatever visibility is available, it reconstructs a set-valued occupancy estimate of nearby regions and combines it with communicating neighbors to reach a shared view and a mismatch discovery. We provide a formal framework for describing social rules that unify many different applications and a tool to generate code automatically for local monitors. The technique is demonstrated in various systems, including self-driving cars, autonomous forklifts, and distributed power plants. [ABSTRACT FROM AUTHOR]

Digital transformation, through innovation in information and communication technologies (ICTs), impacts higher education (HE) and fosters knowledge sharing (KS). While research explores the implications of digital transformation in HE, its specific influence on KS remains understudied. This systematic literature review investigates the nexus between ICTs and KS in HE by examining peer‐reviewed literature prior to the AI boom. Three databases were searched, yielding 473 journal articles, which were screened, eligibility checked and assessed for quality and relevance to predetermined research questions. Eighteen eligible empirical studies were analysed, revealing ICTs influence on KS across university functions: teaching‐learning, governance/operations and research. Retrospectively, this study also demonstrates that the rapid pivot to fully online functions during the pandemic was possible because of prior ICT advancements despite known barriers (e.g., digital literacy, Internet connectivity). Essentially, ICTs enable vital KS for universities to ensure they remain resilient and sustainable now and into the future. [ABSTRACT FROM AUTHOR]

Reference to Knowledge Exchange (KE) in UK Higher Education Institutions (HEIs) has become common place, reflecting the continued changing role of universities within society. Arguably, KE draws together notions of HEIs as purveyors of knowledge, with students helping to create a tripartite relationship with HEIs and the wider community as well as a civic responsibility to contribute to the wider public good. Realising the potential benefits of this inter-relationship required a problematising of the meanings of both knowledge and the notion of an exchange, drawing on the work of Dewey and Bernstein. Our paper offers an analysis of the different epistemological positions governing understandings of knowledge and how these are influenced by the performativity and neoliberal responsibilisation of modern universities. More specifically, the epistemological position encouraged by the modern university leads to a tension between measurement and evaluation of KE on the one hand and pedagogical practice on the other. Taking into account these tensions, the paper offers an alternative approach to knowledge exchange with suggested principles to underpin a future relational pedagogy for KE. [ABSTRACT FROM AUTHOR]

The timeline for the onset of the HIV/AIDS epidemic in the United States occurred parallel to the domestic shift of computing and the advent of DIY computer networking efforts. During this critical time, many activists and community organisers within lesbian, gay, bisexual, transgender, and queer (LGBTQ+) spaces utilised computer networking, such as bulletin board systems (BBSs) and Usenet boards to facilitate information exchange within their affected communities. Due to the sensitive nature of the epidemic and often-vital need for up-to-date information, content moderation became an increasingly important issue on these boards. This paper uses varying archival methods to explore the development of content moderation practices, and the influence of HIV/AIDS culture, on bulletin board systems and Usenet boards, with a special focus on boards dedicated to LGBTQ+ content and HIV/AIDS information exchange. [ABSTRACT FROM AUTHOR]

Attempts in the UK to regulate the sharing and use of health data for secondary purposes such as research have been dogged by controversy and failure. This article considers health data stewardship as a response to these challenges. It develops a normative understanding of the concept through an examination of stewardship in a variety of contexts. This leads to a definition of health data stewardship which encapsulates the necessary constituent elements that focus group participants viewed as crucial to an accountable health data sharing scheme in which they could place their trust. It examines two potential mechanisms for facilitating health data stewardship, the data trust and the data cooperative, arguing that whichever regulatory mechanism is adopted must incorporate mechanisms responsive to citizens' requirements for accountable stewardship of their data. Without this, their wishes, and societal aims of improving health through research using comprehensive data sets may be unachievable. [ABSTRACT FROM AUTHOR]

Motivation: Freshwater ecosystems have been heavily impacted by land‐use changes, but data syntheses on these impacts are still limited. Here, we compiled a global database encompassing 241 studies with species abundance data (from multiple biological groups and geographic locations) across sites with different land‐use categories. This compilation will be useful for addressing questions regarding land‐use change and its impact on freshwater biodiversity. Main Types of Variables Contained: The database includes metadata of each study, sites location, sample methods, sample time, land‐use category and abundance of each taxon. Spatial Location and Grain: The database contains data from across the globe, with 85% of the sites having well‐defined geographical coordinates. Major Taxa and Level of Measurement: The database covers all major freshwater biological groups including algae, macrophytes, zooplankton, macroinvertebrates, fish and amphibians. [ABSTRACT FROM AUTHOR]

PURPOSE: In Canada, health data are siloed, slowing bioinnovation and evidence generation for personalized cancer care. Secured data-sharing platforms (SDSPs) can enable data analysis across silos through rapid concatenation across trial and real-world settings and timely researcher access. To motivate patient participation and trust in research, it is critical to ensure that SDSP design and oversight align with patients' values and address their concerns. We sought to qualitatively characterize patient preferences for the design of a pan-Canadian SDSP. METHODS: Between January 2022 and July 2023, we conducted pan-Canadian virtual focus groups with individuals who had a personal history of cancer. Following each focus group, participants were invited to provide feedback on early-phase analysis results via a member-checking survey. Three trained qualitative researchers analyzed data using thematic analysis. RESULTS: Twenty-eight individuals participated across five focus groups. Four focus groups were conducted in English and one in French. Thematic analysis generated two major and five minor themes. Analytic themes spanned personal and population implications of data sharing and willingness to manage perceived risks. Participants were supportive of increasing access to health data for precision oncology research, while voicing concerns about unintended data use, reidentification, and inequitable access to costly therapeutics. To mitigate perceived risks, participants highlighted the value of data access oversight and governance and informational transparency. CONCLUSION: Strategies for secured data sharing should anticipate and mitigate the risks that patients perceive. Participants supported enhancing timely research capability while ensuring safeguards to protect patient autonomy and privacy. Our study informs the development of data-governance and data-sharing frameworks that integrate real-world and trial data, informed by evidence from direct patient input. @CLEONetwork researchers identify patient priorities for enhanced precision oncology data sharing initiatives [ABSTRACT FROM AUTHOR]

Tea is an important global commodity, with important tea-growing regions spanning across South America, Africa, and Asia, and burgeoning smaller-scale and artisanal tea production in the UK and Europe. In each of these regions, the quality and quantity of tea production, with their economic and social consequences, are highly sensitive to variations in the climate on both short-term weather, seasonal and climate change timescales. The provision of tailored climate information in a timely and accessible manner through the development, delivery and use of climate services can help tea-farmers and other relevant stakeholders better understand the impacts of climate variability and climate change on decision-making and a range of adaptive actions. This paper presents an overview of the Tea-CUP project (Co-developing Useful Predictions), a joint initiative between UK and Chinese partners, which aims to develop and implement solutions for improving robust decision-making. Co-production principles are core, ensuring that the resultant climate services are usable and useful; users' needs are met through close engagement and joint research and decision-making. The paper also reports on the exchange of knowledge and experiences, such as between tea growers in China and the UK, which has resulted from this collaborative work, fostering global knowledge sharing, enriching understanding, and driving innovation by integrating diverse perspectives and expertise from different countries. This is an unintended but valuable side-effect of the collaborative approach taken and highlights the benefits of a highly relational and multidisciplinary approach to climate services development that will inform future work in the field. [ABSTRACT FROM AUTHOR]

This study combined the dual perspectives of team interaction and decision-making stages. Based on 22,654 behavioral units from 20 four-person teams, we developed a team decision-making process model encompassing goal-driven patterns, information sharing, knowledge integration, and decision-making transition. Additionally, we found that high-performance teams engage more in exploratory discussions, timely summarization, and conflict coordination mechanisms, compared to low-performance teams. We summarize the specific interactions that are beneficial and harmful to decision-making performance. This study supplements previous research on team interaction during the decision-making stage and expands the nuanced understanding of how team interactions affect decision-making performance. [ABSTRACT FROM AUTHOR]

Question-answering (QA) platforms such as Stack Overflow, Quora, and Stack Exchange have become favourite places to exchange knowledge with community users. Finding answers to simple or complex questions is easier on QA platforms nowadays. Due to a large number of responses from users all around the world, these CQA systems are currently facing massive problems. Stack Overflow allows users to ask questions and give answers or comments on others' posts. Consequently, Stack Overflow also rewards those users whose posts are appreciated by the community in the form of reputation points. The accepted answer provides maximum reputation points to the answerer. More reputation points allow getting more website privileges. Hence, each answerer needs to get their answer accepted. Very little research has been done to check whether the user's answers will be accepted or not. This paper proposes a model that predicts answer acceptability and its reason. The model's findings help the answerer know about the answer acceptance; if the model predicted the probability of acceptance is less, the answerer might revise their answer immediately. The comparison with the state-of-the-art literature confirmed that the proposed model achieves better performance. [ABSTRACT FROM AUTHOR]

The quick emergence in the quantity of data produced through the linked devices of Internet of Things (IoT) models opened the novel potential to improve service qualities for budding tools considering data sharing. However, privacy problems are main issues of data providers for sharing data. The outflow of confidential data causes severe problems beyond the loss in finance of providers. A blockchain-based secured data-sharing model is devised for dealing with various kinds of parties. Thus, data-sharing issue is modeled as a machine learning issue by adapting federated learning (FL). Here, data privacy is controlled by sharing data in spite of exposing genuine data. At last, the FL is combined in consensus task of permissioned blockchain for accomplishing federated training. Here, the data model learning is executed using a deep maxout network (DMN), which is trained using jellyfish search African vultures optimization (JSAVO). Moreover, the data-sharing records are generated to share data amid data providers and requestors. The proposed JSAVO-based DMN outperformed with better accuracy of 93.3%, FPR of 0.054, loss function of 0.067, mean square error (MSE) of 0.346, mean average precision of 94.6, RMSE of 0.589, computational time of 17.47 s, and memory usage of 48.62 MB. [ABSTRACT FROM AUTHOR]

Cloud computing is widely used for medical data sharing due to its convenience and scalability in data access. In practice, patients prefer to share their medical data with healthcare professionals in a controlled manner due to the sensitive information it implies. Specifically, patients often delegate data ownership to healthcare professionals for more comprehensive treatment. When patients are cured, they wish to revoke the delegation of data ownership. In this process, data security must be ensured when implementing ownership delegation revocation. However, although schemes have been proposed to support fine-grained access control, existing data-sharing systems do not meet the need for dynamic management of data ownership between doctors and patients, and the security issues posed by revocation of ownership delegation remain unexplored. In response to this problem, we propose a time-limited data ownership delegate system (DLDS system) with revocation security, which enables data owners to flexibly control data sharing according to time and user requirements. We design a time-based prefix tree that can revoke data ownership without compromising patient data privacy. To verify the validity of data ownership delegation in a privacy-preserving manner, we design a new interactive authentication method using the Paillier encryption method and inner product computation to ensure that only authorized users can access the data. Finally, the proposed scenarios were thoroughly discussed and simulated experimentally to assess their safety and effectiveness. [ABSTRACT FROM AUTHOR]

Internet of Medical Things (IoMT) has gradually become the main solution for smart healthcare, and cloud-assisted IoMT is becoming a critical computing paradigm to achieve data collection, fine-grained data analysis, and sharing in healthcare domains. Since IoMT data can be frequently shared for accurate diagnosis, prognosis prediction, and health counseling, how to solve the contradiction between data sharing and privacy protection for IoMT data is a challenge problem. Besides, the cloud-assisted medical system is still at risk of a single point of failure and usually suffers from poor scalability and large response delay. Hence, we propose a blockchain-based privacy-preserving and secure sharing scheme for IoMT data, named BAPS. In BAPS, the Interplanetary File System (IPFS) is adopted to store encrypted records. Then, a non-interactive zero-knowledge proof protocol is employed to verify whether the stored data meets the specific request from data requesters without disclosing personal privacy. Moreover, we combine cryptographic primitives and decentralized smart contracts to achieve user anonymity. Finally, we leverage blockchain and proxy re-encryption to achieve fine-grained sharing of healthcare data. Security analysis indicates that this scheme meets the expected security requirements. The computational cost of BAPS is reduced by about 6% compared to state-of-the-art schemes, while the communication overhead is reduced by about 8%. Both theoretical analysis and experiment results show that this scheme can realize privacy-preserving and secure data sharing with acceptable computational and communication costs. [ABSTRACT FROM AUTHOR]

Fog computing is a revolutionary technology that, by expanding the cloud computing paradigm to the network edge, brings a significant achievement in the resource-constrained IoT applications in intelligent environments. However, security matters still challenge the extensive deployment of fog computing infrastructure. Ciphertext policy attribute-based encryption prepares a solution for data sharing and security preservation issues in fog-enhanced intelligent environments. Nevertheless, the lack of an effective mechanism to moderate the execution time of CP-ABE schemes due to the diversity of attributes used in secret key and access structure, as well as ensuring data security, practically restricts the deployment of such schemes. In this regard, a collaborative semantic model, including an outsourced CP-ABE scheme with the attribute revocation ability, together with an impressive AES algorithm relying on an ensemble learning system, was proposed in this study. The ensemble learning model uses multiple classifiers, including the GMDH, SVM, and KNN, to specify attributes corresponding to CP-ABE. The Dragonfly algorithm with a semantic leveling method generates outstanding and practical feature subsets. The experimental results on five smart building datasets indicate that the recommended model performs more accurately than existing methods. Also, the encryption, decryption, and attribute revocation execution time are significantly modified with the average time of 1.95, 2.11, and 14.64 ms, respectively, compared to existing works and conducted the scheme's security. [ABSTRACT FROM AUTHOR]

With data and code sharing policies more common and version control more widely used in statistics, standards for reproducible research are higher than ever. Reproducible research practices must keep up with the fast pace of research. To do so, we propose combining modern practices of leadership with best practices for reproducible research in collaborative statistics as an effective tool for ensuring quality and accuracy while developing stewardship and autonomy in the people we lead. First, we establish a framework for expectations of reproducible statistical research. Then, we introduce Stephen M.R. Covey's theory of trusting and inspiring leadership. These two are combined as we show how stewardship agreements can be used to make reproducible coding a team norm. We provide an illustrative code example and highlight how this method creates a more collaborative rather than evaluative culture where team members hold themselves accountable. The goal of this manuscript is for statisticians to find this application of leadership theory useful and to inspire them to intentionally develop their personal approach to leadership. [ABSTRACT FROM AUTHOR]

The present paper is concerned with the derivation, via asymptotic studies, of a reduced hybrid model describing the anisotropic fusion plasma dynamics. The parallel dynamics is governed by a kinetic equation, whereas the perpendicular dynamics is described by a Maxwellian distribution function, whose temperature $ T_\perp $ satisfies an evolution equation, exchanging information with the parallel direction via some coupling terms. The reduced model is obtained from the underlying fully kinetic model, under the assumption of a strong magnetic field and strong collisionality in the perpendicular direction. From a numerical point of view, reduced models are very advantageous, permitting significant savings in computational times and memory. To improve the precision of the reduced description, we propose in this paper also first order correction terms with respect to the parameter describing the anisotropy, and discuss these terms from a physical point of view. This first order truncated model is new to our knowledge, meets the desired requirements of precision and efficiency, and its derivation is clearly exposed in this work, based on formal asymptotic studies. [ABSTRACT FROM AUTHOR]