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Value co‐creation as a research topic has been a critical proposition of interest to a wide range of disciplines. In recent years, the field of cultural heritage has also developed a range of information practices to promote different forms of value co‐creation. While the body of literature has begun to accumulate, we still lack a comprehensive understanding of conceptual foundations and how value co‐creation is implemented in cultural heritage information practices. This paper conducted a hermeneutic literature review to understand and conceptualize the core aspects of value co‐creation in various cultural heritage information works. In particular, this paper provides a research mapping of the genres of co‐creation in cultural heritage information practices, the actors, and the roles played by the stakeholders. Further, this review provides an overview of the dominant value co‐creation models in the cultural heritage field. It distills the drivers of value co‐creation and the core value consequences that arise from a process perspective. Finally, this paper puts forward a thematic, theoretical, and methodological agenda for future work based on these findings. The review contributes to the literature by proposing an integrated conceptual framework that summarizes the core elements of value co‐creation in cultural heritage information practices. The framework also serves as a call for action, providing a general understanding of the conceptual foundation for future research. [ABSTRACT FROM AUTHOR]

When writing a research paper, the author has to select information to include in the paper to support various arguments. The information has to be organized and synthesized into a coherent whole through relationships and information structures. There is hardly any research on the information structure of research papers, and how information structure supports rhetorical and argument structures. Thus, this study is focused on information organization in the Abstract and Introduction sections of sociology research papers, analyzing the information structure of research objective, question, hypothesis, and result statements. The study is limited to research papers reporting research that investigated cause–effect relations between two concepts. Two semantic frames were developed to specify the types of information associated with cause–effect and comparison relations, and used as coding schemes to annotate the text for different information types. Six link patterns between the two frames were identified—showing how comparisons are used to support the claim that the cause‐effect relation is valid. This study demonstrated how semantic frames can be incorporated in discourse analysis to identify deep structures underlying the argument structure. The results carry implications for the knowledge representation of academic research in knowledge graphs, for semantic relation extraction, and teaching of academic writing. [ABSTRACT FROM AUTHOR]

When writing a research paper, the author has to select information to include in the paper to support various arguments. The information has to be organized and synthesized into a coherent whole through relationships and information structures. There is hardly any research on the information structure of research papers, and how information structure supports rhetorical and argument structures. Thus, this study is focused on information organization in the Abstract and Introduction sections of sociology research papers, analyzing the information structure of research objective, question, hypothesis, and result statements. The study is limited to research papers reporting research that investigated cause–effect relations between two concepts. Two semantic frames were developed to specify the types of information associated with cause–effect and comparison relations, and used as coding schemes to annotate the text for different information types. Six link patterns between the two frames were identified—showing how comparisons are used to support the claim that the cause‐effect relation is valid. This study demonstrated how semantic frames can be incorporated in discourse analysis to identify deep structures underlying the argument structure. The results carry implications for the knowledge representation of academic research in knowledge graphs, for semantic relation extraction, and teaching of academic writing. [ABSTRACT FROM AUTHOR]

Researchers need maps to effectively navigate increasingly voluminous literatures. This is no less the case in the field of problem structuring methods (PSMs). This paper offers an atlas of the journal literature of the theoretical development of, what are currently acknowledged to be, the four main PSMs up to their consolidation in 1989. A thorough contextual appreciation of the structure and dynamics of this literature sets the stage for addressing some of its specific aspects, for which an atlas is especially effective as an orientation device. Substantiated suggestions for exploratory excursions, as well as potential pitfalls, are accentuated, the overall aim being to provide researchers with navigational support that may assist their research objectives. Based on evidence uncovered from the atlas, a number of issues current in the PSM field are discussed, including the use of the collective descriptor 'family', the extent to which PSMs find their origins, and belong, in the wider field of operational research and the identification of sources that have hitherto received little or no acknowledgment but which merit attention as precursors and promising contributors to PSM research. The paper is accompanied by an electronic supplement containing the basic data of the atlas from which additional maps may be designed and constructed. [ABSTRACT FROM AUTHOR]

Cyber–physical distribution systems with renewable energy should have high resilience under extreme conditions. However, in a distribution system with deep cyber–physical coupling, the propagation of information risk impairs the resilience of the system. This paper proposes a strategy to improve the resilience of cyber–physical distribution systems that considers cross‐space propagation of information risk. First, the mechanism for interaction between the cyber space and physical space is analyzed, and an information risk cross‐space propagation model is proposed. Second, the risk status of key device nodes is quantified according to the risk propagation model, and an optimization strategy for information risk control is obtained, whose objective function is the minimum risk of the coupling network. Third, a fault restoration strategy that considers cyber space risk is proposed. Finally, the paper reports experiments using the modified IEEE 33‐node and 123‐node distribution networks to simulate the proposed strategy and verify its effectiveness. [ABSTRACT FROM AUTHOR]

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT‐based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top‐K main paths extracted from various time slices of semantic citation network. In addition, a three‐way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics‐agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas. [ABSTRACT FROM AUTHOR]

The papers also outline different ways of conceptualising power and new insights into how different types of power yield different understandings of the role of IS and to IS research. Power as a practice also manifests through participation in decision-making, empowerment (Simeonova et al., 2020; Simeonova & Galliers, 2022), "sensemaking" and "sensegiving" (Simeonova & Galliers, 2022). The motivation for this special issue on 'Power dynamics in organisations and the role of information systems' originated from the (re)emerging interest and a lack of theorising about the role of power in Information Systems (IS) research (Jasperson et al., 2002; Silva, 2007; Silva & Backhouse, 2003; Simeonova & Galliers, 2022; Simeonova, Galliers, & Karanasios, 2020). Power as facilitation denotes the utilisation of IS to reduce communication barriers between hierarchical levels and remove status differentials and power asymmetries (Leonardi, Huysman, & Steinfield, 2013; McAfee, 2006). [Extracted from the article]

As an essential part of intelligent transportation system (ITS), traffic forecasting has provided crucial role for traffic management and risk assessment. However, complex spatial–temporal dependencies, heterogeneity, dynamicity, and periodicity of traffic data influence the traffic forecasting performance. Consequently, we propose a novel effective gated spatial–temporal merged transformer (GSTMT) inspired by multimask and dual branch for accurate traffic forecasting in this paper. Specifically, we first conduct a concatenation of gated spatial static mask transformer (GSSMT) and gated spatial dynamic mask transformer (GSDMT) with residual network. The GSSMT and GSDMT evolve from the traditional transformer by making preferable modifications that include gated linear unit (GLU), multimask mechanism including static mask matrix (SMM) and dynamic mask matrix (DMM), and spatial attention (SA). Among them, GLU is to promote the performance of capturing spatial dependency, dynamicity, and heterogeneity due to advanced performance for controlling information flow through layers. Additionally, by developing multimask mechanism including two novel SMM and DMM, the proposed GSTMT can precisely model the static and dynamic spatial structure for effectively highlighting static dependency and dynamicity. And SA is injected for enhancing the ability of capturing spatial dependency of GSSMT and GSDMT. Secondly, we develop a dual‐branch gated temporal transformer (DBGTT) for capturing temporal dependency, heterogeneity, dynamicity, and periodicity via incorporating the GLU and mixed time series decomposition (MTD) into traditional transformer. Similarly, we also introduce the GLU for empowering DBGTT with capability of capturing temporal dependency, dynamicity, and heterogeneity. In addition, MTD, which brings dual‐branch mechanism, can enhance the DBGTT for capturing more detailed temporal information via exploiting global and periodic profile of traffic data. At last, some experiments, which are performed on several real‐world traffic datasets, demonstrate the better results over classic traffic forecasting methods. [ABSTRACT FROM AUTHOR]

National and International road networks are made of structures and infrastructures that often exhibit poor performance due to a lack of maintenance. In this context, Italy recently renewed the legislation regarding existing infrastructure analysis to support knowledge and facilitate a homogeneous data acquisition process. Thus a key component of the process consists of the visual inspection protocols complemented by physical and mechanical measures. This applies to all the structures built for the road network operation, including those classified as geotechnical whose deterioration is often neglected or appropriately surveyed. Along with the definition of a data form for collecting datasets on these aspects, a relevant aspect of the process is the implementation of a collaborative environment for the information management and analysis systems supporting the interested parties in the field. The paper reports the design of a base geotechnical inspection form for Retaining Wall and illustrates some aspects of its implementation in a digital environment. Mixed Reality techniques in combination with web‐based tools for data collection are investigated to increase the feasibility and reliability of the visual inspection of existing road networks. [ABSTRACT FROM AUTHOR]

Supply chain management is impacted profoundly by digitalization in the forms of artificial intelligence (AI) or robotics applications (Bell & Griffis, 2011; Choi et al., 2021; Fragapane et al., 2021; Klumpp & Zijm, 2019). The emergent model from the implemented data analysis highlights the prevalence of marketing messages emphasizing AI trustworthiness and suggests several marketing tactics that could be used to market AI to supply chain workers internally, improving AI acceptance and use. This paper addresses the documented difference between AI adoption and AI use by exploring how AI technologies can be marketed within an organization. Based on the findings, a middle-range model of AI trustworthiness and a subsequent call for research related to the effects of AI trustworthiness on internal, upstream, and downstream activities in the supply chain is proposed. [Extracted from the article]

In this paper, the finite horizon asymmetric information linear quadratic (LQ) control problem is investigated for a discrete-time mean field system. Different from previous works, multiple controllers with different information sets are involved in the mean field system dynamics. The coupling of different controllers makes it quite difficult in finding the optimal control strategy. Fortunately, by applying the Pontryagin's maximum principle, the corresponding decentralized control problem of the finite horizon is investigated. The contributions of this paper can be concluded as follows: For the first time, based on the solution of a group of mean-field forward and backward stochastic difference equations (MF-FBSDEs), the necessary and sufficient solvability conditions are derived for the asymmetric information LQ control for the mean field system with multiple controllers. Furthermore, by the use of an innovative orthogonal decomposition approach, the optimal decentralized control strategy is derived, which is based on the solution to a non-symmetric Riccati-type equation. [ABSTRACT FROM AUTHOR]

This paper reports from a qualitative case study in the Gambian education sector. The study applies an affordance perspective to the ongoing strengthening of the national education management information system. Our analysis distinguishes between micro‐level technology‐use affordances (e.g., civil servants using IT for data capture and reporting), meso‐level information system (IS) affordances (e.g., data‐driven decision making at the organizational level), and macro‐level affordances, which include policy interventions to ensure the attainment of education sector goals. The contribution of the paper is twofold. First, the paper introduces a stepwise framework for IS affordance identification in terms of granularity levels (micro, meso and macro). Second, the paper outlines how use of IT at the micro‐level allows for the actualization of meso‐level IS affordances, which in turn serve as a foundation for the articulation of higher‐level interventions. Far too often, ICT for development (ICT4D) projects focus on putting technology in the hands of users with the assumption that "better data" will drive development. The significant work involved in identifying and actualizing meso‐level IS affordances is often not explicated and recognized in related plans and budgets. By highlighting meso‐level IS affordance actualizations, the paper explicates the link between public sector IT adoption and use and intended societal‐level impact, which remains a key policy and research concern. [ABSTRACT FROM AUTHOR]

Copyright of Geomechanik und Tunnelbau is the property of Wiley-Blackwell 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.)

Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about whether the salient words agree with those identified by humans as important. Objectives: The current study examines in‐line annotations from human annotators and saliency map annotations from a deep learning model (ELECTRA transformer) to understand how well both humans and machines provide evidence for their assigned label. Methods: Data were responses to test items across a mix of United States subjects, states, and grades. Humans were trained to annotate responses to justify a crisis alert label and two model interpretability methods (LIME, Integrated Gradients) were used to obtain engine annotations. Human inter‐annotator agreement and engine agreement with the human annotators were computed and compared. Results and Conclusions: Human annotators agreed with one another at similar rates to those observed in the literature on similar tasks. The annotations derived using the integrated gradients (IG) agreed with human annotators at higher rates than LIME on most metrics; however, both methods underperformed relative to the human annotators. Implications: Saliency map‐based engine annotations show promise as a form of explanation, but do not reach human annotation agreement levels. Future work should examine the appropriate unit for annotation (e.g., word, sentence), other gradient based methods, and approaches for mapping the continuous saliency values to Boolean annotations. Lay Description: What is known about subject matter: Explainability of deep learning models is complicated by their large size, design, and complexity.Explainability methods in deep learning exist but have not been rigorously tested.Saliency maps, as a form of explainability, can be used to generate engine annotations.Human annotations can serve as basis for comparison. What paper adds to knowledge: How well human annotations work in one domain (crisis paper identification).How well two engine annotation methods match human annotations. Implications of study findings: Human annotations have reasonable reliability.Engine annotations have lower reliability than humans.Model‐based engine annotations perform better than model‐agnostic engine annotations. [ABSTRACT FROM AUTHOR]

This paper focuses on data science in digital cultural heritage in Brazil, where there is a lack of systematized information and curated databases for the integrated organization of documentary knowledge. Thus, the aim was to systematically map the different forms of information organization and representation applied to objects from collections belonging to institutions affiliated with the federal government's Special Department of Culture. This diagnosis is then used to discuss the requirements of devising strategies that favor a better data science information infrastructure to reuse information on Brazil's cultural heritage. Content analysis was used to identify analytical categories and obtain a broader understanding of the documentary sources of these institutions in order to extract, analyze, and interpret the data involved. A total of 215 hyperlinks that can be considered cultural collections of the institutions studied were identified, representing 2,537,921 cultural heritage items. The results show that the online publication of Brazil's digital cultural heritage is limited in terms of technology, copyright licensing, and established information organization practices. This paper provides a conceptual and analytical view to discuss the requirements for formulating strategies aimed at building a data science information infrastructure of Brazilian digital cultural collections that serves as future projects. [ABSTRACT FROM AUTHOR]

This paper proposes a theory of life transitions focused on information behavior. Through a process of meta‐ethnography, the paper transforms a series of influential theories and models into a theory of transitions for use in Information Science. This paper characterizes the psychological processes involved in transitions as consisting of three main stages, Understanding, Negotiating, and Resolving, each of which have qualitatively different information behaviors and which require different types of information support. The paper discusses the theoretical implications of this theory and proposes ways in which the theory can be used to provide practical support for those undergoing transitions. [ABSTRACT FROM AUTHOR]

Background: Information specialists conducting searches for systematic reviews need to consider key questions around which and how many sources to search. This is particularly important for public health topics where evidence may be found in diverse sources. Objectives: The objective of this review is to give an overview of recent studies on information retrieval guidance and methods that could be applied to public health evidence and used to guide future searches. Methods: A literature search was performed in core databases and supplemented by browsing health information journals and citation searching. Results were sifted and reviewed. Results: Seventy‐two papers were found and grouped into themes covering sources and search techniques. Public health topics were poorly covered in this literature. Discussion: Many researchers follow the recommendations to search multiple databases. The review topic influences decisions about sources. Additional sources covering grey literature eliminate bias but are time‐consuming and difficult to search systematically. Public health searching is complex, often requiring searches in multidisciplinary sources and using additional methods. Conclusions: Search planning is advisable to enable decisions about which and how many sources to search. This could improve with more work on modelling search scenarios, particularly in public health topics, to examine where publications were found and guide future research. [ABSTRACT FROM AUTHOR]

Summary: The uncontrollable spread of contagious disease COVID‐19 is a perennial threat to mankind and has resulted in an unprecedented lockdowns in several countries including Pakistan which in turn has caused an adverse socio‐economic impact to all industries. The strategic leadership and concerned state authorities are trying hard to combat and control the spread of COVID‐19 pandemic. The effective use of Information Management & Decision Support (IMDS) System can play significant role in combating pandemic and its spread, managing relief actions effectively, accessing vulnerable communities to roll out targeted subsidies by ensuring the coordinated effort and subsequent implementation. Reliable information is significantly critical to assist government and public health agencies in determining the best way forward to control this global health emergency. Therefore, this paper aims to strengthen capacity of IMDS System used by government institutions and authorities for decision making and information dissemination. In this research work, we addressed the integrity‐based issues that include completeness, correctness, and freshness of data by proposing a block chain‐based integrity protection mechanism. The proposed novel framework is a cascaded formulation of Integrity Assurance (IA) Protocol, Cryptographic Merkle Hash Tree, Digital Signature, and Blockchain. Beside cascaded formulation, two (2) schemes for MHT Generation are also presented in the framework. The proposed framework ensures fairness, completeness, and correctness of data that will be very helpful for secure data management, integration, and utilization in analysis for decision‐making. The proposed framework achieved an accuracy of more than 98.09% with better quantitative performance in standard evaluation parameters. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell 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.)

This paper explores the use of Fisher and Tronto's four phases of ethics of care (caring about, taking care of, caregiving, and care receiving) to three personal information management (PIM) frameworks, with a focus on PIM maintaining. The author argues that ethics of care can provide a theoretical foundation for PIM by using the four phases of caring to develop a perspective of PIM as a caring process using the categories of PIM as self‐care and PIM as caring for others. The paper begins by reviewing Fisher and Tronto's ethics of care, cites research in related fields that have applied ethics of care, and then describes how ethics of care could be applied to PIM research. To conclude, the author offers suggestions for how ethics of care can be applied to future PIM research in the following areas: better understand the motivations for PIM; the ways in which PIM can contribute to the social concepts of equality, justice, and trust and how social institutions can facilitate "good" PIM. [ABSTRACT FROM AUTHOR]

A second presidential social media transition in the United States occurred as Joe Biden took office on January 20, 2021. In the years since Barack Obama pioneered the use of platforms like Facebook and Twitter while President, Donald Trump shaped his Presidency around the use of Twitter, primarily through a personal account created before entering politics. In this paper, we examine Donald Trump's use of Twitter during his presidency as a lens through which to understand the ongoing archival preservation and data management challenges posed by social media platforms. The blurred lines between public and private records, deleting tweets, and the preservation issues that appeared after his suspension from Twitter and other platforms following the January 6, 2021 insurrection at the US Capitol all highlight an urgent, ongoing need by archivists, digital preservationists, and information scholars to consider how we might collect and manage social media records in an ever‐changing information landscape. This paper draws primarily on publicly available information from existing preservation initiatives to analyze the state of digital preservation for presidential records. Our findings highlight how both public and private entities manage and provide access to Donald Trump's tweets, pointing to broader implications for social media data preservation. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a modified consensus protocol algorithm is proposed for controlling a group of identical unmanned aerial vehicles (UAVs), which have been subjected to interfering signals during coordinate information exchange, using an unknown parameter in the consensus protocol. The maximum levels of interfering signals in the proposed protocol were adjusted by incorporating a hysteresis function with a dead zone consistent with the initial coordinates and the interfering signal levels. An adaptation algorithm is proposed to address a priori uncertainty regarding the consensus parameters, involving the correction of an unknown parameter by eliminating control signals exhibiting false sign changes. This correction relies on the coordinates in the phase plane, indicating that the delay in maneuver execution occurs at the beginning of the maneuver. Furthermore, by modeling synchronized motion, UAV group consensus is demonstrated for an ideal case devoid of a priori uncertainty regarding control protocol parameters, interfering signals, or consequences. The convergence of the adaptation algorithm was assessed by defining a vector function to track parameter changes during tuning. The monotonically decreasing nature of the resulting curve, along with the finite duration of the tuning process, provides confirmation of the convergence of the adaptation algorithm. [ABSTRACT FROM AUTHOR]

The digital management of engineering construction is one of the primary tasks of smart construction sites. In the current practice of construction site information management, there are a series of fraudulent behaviors such as engineering data being forged and modified and this seriously interferes with the safety supervision of engineering projects. In order to improve the security and traceability of multi‐type engineering data, this paper presents a framework of system for construction site information management using blockchain and smart contracts. In this method, multiple independent smart contracts are developed for different data types. It ensures that the system can dynamically deploy new smart contracts without interrupting service, facilitating the expansion of scenario services. More importantly, the data analysis function is extended to the terminal, which allows the integration of different data analysis algorithms such as deep learning into information management. The design breaks the restriction that only rule‐based data analysis can be performed. Meanwhile, the distributed federation architecture ensures that the data cannot be tampered with. Finally, the three most common types of data (namely text, time‐series, and image) were used to verify the security and stability of the management system. [ABSTRACT FROM AUTHOR]

This article considers the interdisciplinary opportunities and challenges of working with digital cultural heritage, such as digitized historical newspapers, and proposes an integrated digital hermeneutics workflow to combine purely disciplinary research approaches from computer science, humanities, and library work. Common interests and motivations of the above‐mentioned disciplines have resulted in interdisciplinary projects and collaborations such as the NewsEye project, which is working on novel solutions on how digital heritage data is (re)searched, accessed, used, and analyzed. We argue that collaborations of different disciplines can benefit from a good understanding of the workflows and traditions of each of the disciplines involved but must find integrated approaches to successfully exploit the full potential of digitized sources. The paper is furthermore providing an insight into digital tools, methods, and hermeneutics in action, showing that integrated interdisciplinary research needs to build something in between the disciplines while respecting and understanding each other's expertise and expectations. [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]

This paper aims to explore the causality between executive turnover and accounting information comparability (AIC) within the context of Chinese‐listed companies. The evidence with robustness tests strongly supports that the executive turnover hurts accounting comparability of corporations. These effects are more salient in the subsamples of non‐state‐owned and non‐high‐tech firms relative to state‐owned and high‐tech ones. The negative effects of executive turnover on AIC are restrained given less internal control weakness. The findings highlight the role of internal controls in ensuring AIC, and offer insights to inform the formulation of related management policies following a new executive appointment. [ABSTRACT FROM AUTHOR]

Waste collection is an important logistic operation that is often inefficient due to the high uncertainty associated with bin fill levels, resulting either in routes that visit empty bins or in bins overflowing due to lack of routes. To reduce such uncertainty, sensors installed in the bins can provide real‐time information on waste levels. However, this is not enough, and the management of this information needs to be combined with dynamic optimization approaches to effectively design smart collection routes. This paper investigates this challenge and uses real‐time information on waste levels, treated through machine learning techniques, to feed a dynamic reverse inventory routing optimization model. The resulting data‐driven optimization approach allows the definition of a medium‐term collection route plan that can be updated daily as new information becomes available. To demonstrate the applicability of such an approach, a real‐world case is solved, and the results show significant improvements in operational efficiency and service levels. [ABSTRACT FROM AUTHOR]

In order to explore the interaction law of information sharing behavior of decision‐making subjects in the agricultural product supply chain, this paper establishes a tripartite evolutionary game mathematical model, uses the replicator dynamics equation to analyze the dynamic evolution process of the three‐dimensional dynamic system, and carries out numerical simulation analysis. The results show that there are seven key factors affecting the information sharing decisions of the decision‐making subjects. This paper explores the specific role of these influencing factors and finds ways to improve supply chain performance. Finally, the study proposes four suggestions for supply chain information sharing management. [ABSTRACT FROM AUTHOR]

Information Technology (IT) investments in the public sector are large, and it is essential that they lead to benefits for the organisations themselves and wider society. While there is evidence suggesting a positive connection between the existence of benefits management practices and the realisation of benefits, less is known about how to implement such practices effectively. The aim of this paper is to provide insights into when benefits are most likely to be realised, and how benefits management practices and roles should be implemented, in order to have a positive effect on the success of projects in terms of realising benefits. We collected data relating to 10 public IT projects in Norway. For each project, information on benefits management was collected from project documents by interviewing the project owners and benefits owners and via follow‐up surveys. The benefits with the highest degree of realisation were those internal to the organisation, while those with the lowest degree were societal benefits. Projects assessed as having more specific, measurable, accountable, and realistically planned benefits were more successful in terms of realising benefits. Benefit owners were most effective when they were able to attract attention to the benefits to be realised, had a strong mandate, and had the domain expertise. [ABSTRACT FROM AUTHOR]

Non‐inferiority trials compare new experimental therapies to standard ones (active control). In these experiments, historical information on the control treatment is often available. This makes Bayesian methodology appealing since it allows a natural way to exploit information from past studies. In the present paper, we suggest the use of previous data for constructing the prior distribution of the control effect parameter. Specifically, we consider a dynamic power prior that possibly allows to discount the level of borrowing in the presence of heterogeneity between past and current control data. The discount parameter of the prior is based on the Hellinger distance between the posterior distributions of the control parameter based, respectively, on historical and current data. We develop the methodology for comparing normal means and we handle the unknown variance assumption using MCMC. We also provide a simulation study to analyze the proposed test in terms of frequentist size and power, as it is usually requested by regulatory agencies. Finally, we investigate comparisons with some existing methods and we illustrate an application to a real case study. [ABSTRACT FROM AUTHOR]

This paper studies a firm's organisational responses if its agents misevaluate information. If a manager overreacts to unusual events, it may be desirable for the firm to adopt the management practice management‐by‐exception. I develop a theoretical framework to study this technique and derive conditions under parsimonious assumptions for when it should be adopted. Moreover, I show how further assumptions can refine the model's predictions, establishing a direct link between the manager's over‐responsiveness and organisational rigidity. The strategy is implemented by controlling the information that the manager receives. [ABSTRACT FROM AUTHOR]

Copyright of Disasters is the property of Wiley-Blackwell 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.)

Privacy‐enhancing technologies that incorporate a socially meaningful conception of privacy, one that meets people's expectations and is ethically defensible, need to factor in contextual privacy norms and information governance as part of their design. This involves understanding what information handling practices users deem acceptable, what factors influence users' perceptions and behaviors, and how informational norms evolve. In this paper, we present GKC‐CI, a unifying framework for examining contextual privacy norms and information governance in a given context to help structure research inquiries around these questions. [ABSTRACT FROM AUTHOR]

GLAM organizations have been digitizing their collections and making them available for the public for several decades. Recent methods for publishing digital collections such as "GLAM Labs" and "Collections as Data" provide guidelines for the application of computational methods to reuse the contents of cultural heritage institutions in innovative and creative ways. Jupyter Notebooks have become a powerful tool to foster use of these collections by digital humanities researchers. Based on previous approaches for quality assessment, which have been adapted for cultural heritage collections, this paper proposes a methodology for assessing the quality of projects based on Jupyter Notebooks published by relevant GLAM institutions. A list of projects based on Jupyter Notebooks using cultural heritage data has been evaluated. Common features and best practices have been identified. A detailed analysis, that can be useful for organizations interested in creating their own Jupyter Notebooks projects, has been provided. Open issues requiring further work and additional avenues for exploration are outlined. [ABSTRACT FROM AUTHOR]

Information and communication technology for development (ICT4D) is a field of research concerned with studying how information and communication technologies (ICTs) can be used to improve the socio‐economic situation of marginalized communities in developing countries. The authors identify the preservation of the information provided or accessed during ICT4D projects as a critical gap in ICT4D research. They argue that archival science, an information discipline concerned with the preservation of recorded information, provides theories and models that can help make ICT4D projects more sustainable. They discuss the creation of analog backups by participants in an ICT4D project in Bangladesh as an example of communities taking the initiative to remedy the limitations of an ICT4D project with simple pen and paper technology to preserve the information they wanted to keep. Conversely, they argue that insights on how marginalized communities interact with and preserve information gained through ICT4D projects can enrich archival science and foster the development of more inclusive theories and practices. Finally, they suggest areas for interdisciplinary research between ICT4D and archival science. [ABSTRACT FROM AUTHOR]

There is ongoing digital transformation in many industrial contexts including non‐digital hardware‐intensive domains such as heavy construction equipment machinery. This transformation is augmented by the latest technologies, increasing sustainability regulations, as well as integrated customer needs. This paradigm shift is causing transformation of current product‐centric business models towards complex business models enabled by so‐called Product Service Systems (PSS) offering advanced "capabilities" and "services". However, the development of PSSs requires a holistic approach to unify underlying solution domains such as mechatronic systems, embedded software control as well as information systems. In this paper, we describe a holistic "unified" architecture description methodology towards aligning the underlying domain‐specific design and development contexts. The framework, developed in construction domain, consists of two main parts: a minimalistic reference model as the "common language" for cross‐functional stakeholder communication; a modeling methodology based on existing standard modeling frameworks. We illustrate the methodology using examples from the construction equipment domain. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between the co‐shareholding network and negative media coverage in the context of China. We find that the high degree centrality and structural holes of firm's co‐shareholding networks have negative effects on the amount and severity of negative media coverage but through differentiated mechanisms. Focal firms in high degree centrality positions can decrease negative coverage by information sharing through the network, but focal firms in the position of structural holes reduce negative coverage through information control. Our findings can complement both research on the disparate impacts of co‐shareholding networks and the media spin effect. [ABSTRACT FROM AUTHOR]

Background: Fungal skin infections are recognised as one of the most common health disorders globally, and dermatophyte infections of the skin, hair and nails are the most common fungal infections. Dermatophytes can be classified as anthropophilic, zoophilic or geophilic species based on their primary habitat association, and this classification makes epidemiological analysis useful for the prevention and control of these infections. The Irish contribution to the epidemiology of these infections has been scant, with just two papers (both reporting paediatric tinea capitis only) published in the last 20 years, and none in the last seven. Objectives: To perform a comprehensive retrospective epidemiological analysis of all dermatological mycology tests performed in University Hospital Limerick over a 20‐year period. Methods: All mycology laboratory test results were extracted from the Laboratory Information Management System (LIMS, iLab, DXC Technologies) from 2001 to 2020 inclusive for analysis. Specimen types were categorised according to the site of sampling. The data were analysed using Microsoft Excel. Results: About 12,951 specimens of skin, hair and nails were studied. Median patient age was 42 years (IQR 26–57) with a slight female preponderance (57.2%). Two thirds of samples (67%, n = 8633) were nail, 32% were skin scrapings (n = 4118) and 200 hair samples (1.5%) were received. Zoophilic dermatophytes were more commonly present in females (38% F, 23% M, proportion of dermatophytes) and in those under 10 years of age or from 45 to 70 years (36% and 34% zoophiles, respectively, proportion of dermatophytes), although anthropophiles predominated every age and gender category. Anthropophiles had their highest prevalence in the 10–20 years age category (80% anthropophiles, proportion of dermatophytes), and yeast infections were more prevalent in older patients (29% of >60 year olds vs. 17% of <60 year olds, proportion of all fungal positives). Trichophyton rubrum was the most prevalent pathogen detected, accounting for 53% of all dermatophytes detected, 61% of those detected from nail samples and 34% from skin and hair samples. Trichophyton tonsurans was the most prevalent dermatophyte in tinea capitis, accounting for 37% of dermatophytes detected. Both of these organisms are anthropophilic, and this group showed consistently increased prevalence in proportion to all fungal isolates. The proportion of this dermatophyte class (anthropophiles) increased among both nail samples and skin/hair samples during the study period, from 55% of samples in the first 5 years of the study (2001–2005) to 88% (proportion of dermatophytes) in the final 5 years. Conversely, yeast detection decreased. Conclusions: This study provides a detailed overview of the epidemiology of the fungal cultures of skin, nail and hair samples in the Mid‐West of Ireland over a 20‐year period. Monitoring this changing landscape is important in identifying likely sources of infections, to identifying potential outbreaks, and may help guide empiric treatment. To the best of our knowledge, this study provides the first detailed analysis from Ireland of fungal detections from skin, hair and nail samples, and is the first epidemiological fungal report of any kind in over 7 years. [ABSTRACT FROM AUTHOR]

Summary: In software‐defined network (SDN) architecture, the network decisions are all located on a logically centralized controller. Based on installing rules into switches of the data plane, the controller directly initiates and schedules a network update and which will cause a delay in the completion time of a network update. The situation is aggravated in wide area networks (WANs) further due to the switches deployed in a wide geographical area bring long propagation delay. On account of adopting the in‐band transmission style to deliver control messages instead of dedicated control channels is economics in WANs, the retransmission of control messages causing by congestion of the data channels is another unbearable delay source. This paper describes a new control information batch delivery mechanism (CIBDM) of network updates to relieve the delay and enhance the reliability of control message transmission in SD‐WANs. The characteristics of the novel scheme include the following: (1) every control information message may contain multiple update information of different forwarding devices, and each update information consists of a set of update instructions with dependencies; (2) by using a similar mechanism of onion routing, in the delivering process of control messages, it attains the security for each control rule of the specified devices; (3) with delegating the update consistency coordination into the data plane, it improves network update on the completion time. A comprehensive evaluation runs on 10 network topologies selected from all over the world. Experimental results show that CIBDM achieves rapid network updates with reliable message transmission. [ABSTRACT FROM AUTHOR]

Summary: With the development of cloud computing, the security of information has gradually become the focus of people. The patient information processed by the medical system has a very high sensitivity and privacy. If there is a leak, it will have a great impact on the patients. The purpose of this study is to explore the privacy information antistealing control method of medical system based on cloud computing. In this paper, through big data analysis, experimental research, variable comparison, and other methods, combined with modern security management means, we carry out the algorithm experiment and research on the privacy information antistealing control means. The result is that the running time of the three algorithms is 18, 16, and 10 s in turn when the algorithm runs 1000 times. It can be seen that the operation time of the enhanced encryption algorithm in this study is less than the initial algorithm by 8 s, the speed is increased by more than 40%. The conclusion is to improve the efficiency of data computing time and make the encryption process more efficient and accurate. The privacy data protection of medical system plays a good role. [ABSTRACT FROM AUTHOR]

In many orphan diseases and pediatric indications, the randomized controlled trials may be infeasible because of their size, duration, and cost. Leveraging information on the control through a prior can potentially reduce sample size. However, unless an objective prior is used to impose complete ignorance for the parameter being estimated, it results in biased estimates and inflated type‐I error. Hence, it is essential to assess both the confirmatory and supplementary knowledge available during the construction of the prior to avoid "cherry‐picking" advantageous information. For this purpose, propensity score methods are employed to minimize selection bias by weighting supplemental control subjects according to their similarity in terms of pretreatment characteristics to the subjects in the current trial. The latter can be operationalized through a proposed measure of overlap in propensity‐score distributions. In this paper, we consider single experimental arm in the current trial and the control arm is completely borrowed from the supplemental data. The simulation experiments show that the proposed method reduces prior and data conflict and improves the precision of the of the average treatment effect. [ABSTRACT FROM AUTHOR]

The architectures of many neural networks rely heavily on the underlying grid associated with the variables, for instance, the lattice of pixels in an image. For general biomedical data without a grid structure, the multi‐layer perceptron (MLP) and deep belief network (DBN) are often used. However, in these networks, variables are treated homogeneously in the sense of network structure; and it is difficult to assess their individual importance. In this paper, we propose a novel neural network called Variable‐block tree Net (VtNet) whose architecture is determined by an underlying tree with each node corresponding to a subset of variables. The tree is learned from the data to best capture the causal relationships among the variables. VtNet contains a long short‐term memory (LSTM)‐like cell for every tree node. The input and forget gates of each cell control the information flow through the node, and they are used to define a significance score for the variables. To validate the defined significance score, VtNet is trained using smaller trees with variables of low scores removed. Hypothesis tests are conducted to show that variables of higher scores influence classification more strongly. Comparison is made with the variable importance score defined in Random Forest from the aspect of variable selection. Our experiments demonstrate that VtNet is highly competitive in classification accuracy and can often improve accuracy by removing variables with low significance scores. [ABSTRACT FROM AUTHOR]

Medicine is practiced in environments of volatility, uncertainty, complexity, ambiguity, and disruption (VUCAD). Medical educators are tasked with providing an education that prepares graduates to successfully practice medicine in those types of environments. While medical education is continually evolving to incorporate new content and educational approaches, there are two mega‐evolutions that have permeated medical education: increased curricular structure and content integration. Structure and integration are assumed to be positive changes; however, they may alter the development of higher cognitive skills such as information management, planning, breadth of approach, strategy, and initiative. As new graduates will practice in VUCAD environments, it seems prudent to consider the effects of medical education's mega‐evolutions on the development of higher cognitive skills critical to those types of environments. This paper explores the potential consequences of the increased curricular structure and content integration in medical education for learners who will practice in VUCAD environments and proposes a research agenda to better understand the relationship between curricular structure and integration and higher cognitive skill development. [ABSTRACT FROM AUTHOR]

The information professions need a paradigmatic shift to address the epistemicide happening within our field and the ways we have systematically undermined knowledge systems falling outside of Western traditions. Epistemicide is the killing, silencing, annihilation, or devaluing of a knowledge system. We argue epistemicide happens when epistemic injustices are persistent and systematic and collectively work as a structured and systemic oppression of particular ways of knowing. We present epistemicide as a conceptual approach for understanding and analyzing ways knowledge systems are silenced or devalued within Information Science. We extend Fricker's framework by: (a) identifying new types of epistemic injustices, and (b) by adding to Fricker's concepts of Primary and Secondary Harm and introducing the concept of a Third Harm happening at an intergenerational level. Addressing epistemicide is critical for information professionals because we task ourselves with handling knowledge from every field. Acknowledgement of and taking steps to interrupt epistemic injustices and these specific harms are supportive of the social justice movements already happening. This paper serves as an interruption of epistemic injustice by presenting actions toward justice in the form of operationalized interventions of epistemicide. [ABSTRACT FROM AUTHOR]

Mid‐Elizabethan rivalry over policy and patronage split the system of state information and espionage into the collaboration of individuals. To maintain the utmost privacy, Francis Walsingham, principal secretary to Queen Elizabeth I, designed a comparatively enclosed information management and secretarial machinery that combined household space with clientage. This strategy facilitated the multiple infiltrations of clientage into the different levels of power politics, ranging from pan‐European espionage to government administration and parliament. The political involvement of clientele hence constructed the late Tudor polity out of another amalgam of bureaucratic and household elements. Using the model of Walsingham's privatised, flexible and meritocratic secretariat, this essay will examine a new style of Tudor clientage and their capture of power within the mid‐Elizabethan regime. In doing so, it explores the connection within and between clients, bureaucrats and the monarch, as well as a political controversy concerning the late Tudor polity. [ABSTRACT FROM AUTHOR]

This article reports the first occurrence of leaf spot disease caused by Colletotrichum coffeanum on Tabernaemontana divaricata (crape jasmine) in India. The disease was observed on the leaves of T. divaricata near Gauhati University in Guwahati, Assam. The symptoms started as small, circular, yellow-halo spots and progressed to angular brown spots with yellowing of the surrounding leaf tissues. The pathogen was identified through morphological and molecular characterization, and pathogenicity assays confirmed its role as the causative agent. This report provides valuable information for the development of management strategies for leaf spot disease on T. divaricata. [Extracted from the article]

The International Conference on Geographical Information Systems Theory, Applications and Management aims at creating a meeting point of researchers and practitioners that addresses new challenges in geospatial data sensing, observation, representation, processing, visualisation, sharing and managing, in all aspects concerning both information and communications technologies (ICTs) as well as management information systems and knowledge-based systems. Conference areas: Data Acquisition and Processing Remote Sensing Modelling, Representation and Visualisation Knowledge Extraction and Management Domain Applications Although the conference is back to the normal mode (i.e., in-person), speakers are allowed to present remotely if unable to travel to the venue (hybrid support). The conference welcomes original papers of either practical or theoretical nature, presenting research or applications, of specialised or interdisciplinary nature, addressing any aspect of geographic information systems and technologies. [Extracted from the article]

Metamorphic testing addresses the issue of the oracle problem by comparing results transformation from multiple test executions. The relationship that governs the output transformation is called metamorphic relation. Metamorphic relations require expert knowledge and the generation of them is considered a time‐consuming task. Researchers have proposed various techniques to automate metamorphic testing, generation, and selection. Although there are several research articles on this issue, there is a lack of overview of the state‐of‐the‐art of metamorphic relation automation. As such, we performed a systematic literature review study to collect, extract, and synthesize the required data. Based on our research questions, the literature was categorized and summarized into different categories. We found that the automation of metamorphic relation is most effective in mathematical and scientific applications. We concluded that some approaches involve analysis of different forms of software‐related information such as control flow graph and program dependence graph as well as an initial set of metamorphic relations. On the other hand, other methods involve analysis of executions of the software functions with random and specific inputs. The results show that this field is still in its infancy with opportunities for novel work, especially in methods utilizing machine learning. [ABSTRACT FROM AUTHOR]

The concept of 'Regulation by Information' is changing. Past such approaches consisted mainly of signalling regulatory intent and indirectly guiding how and when regulatory discretion should be exercised. We suggest that this conceptual understanding must be reviewed in view of developing regulatory technologies (RegTech) allowing for a far more proactive integration of data flows into regulatory processes. RegTech is thereby changing conditions of Regulation by Information. This article uses financial regulation as an information‐intensive and highly regulated policy field to illustrate and analyse RegTech‐induced changes to conditions of Regulation by Information. It finds that the rise of near real‐time information flows between market participants and regulatory bodies and, consequently, the need for near real‐time regulatory responses on the European Union level have led to an ever higher degree of integration of regulatory software into market data flows. Regulatory software now increasingly shapes the definitions of reporting standards and formats, which in turn shape regulatory choices by influencing information flows. The article shows how this development will likely be used in other data‐ and information‐dense policy areas outside of financial markets. Critics of Regulation by Information argue that it can lead to a lack of accountability and transparency, increasing the democratic deficit within the European Union. This article scrutinises both continuities and changes in the role and significance of legal principles and procedures used in regulatory oversight, following the evolution of this new form of Regulation by Information within the EU. [ABSTRACT FROM AUTHOR]