Effect of contextual and dispositional variables on protective behaviours in the face of imminent risk, as analysed using the virtual simulation of a tsunami.

ABSTRACT Deselection remains a core yet often contested aspect of library collection management, shaped by shifting user needs, evolving professional values, and technological developments. Although recent scholarship highlights the growing use of data analytics and decision-support tools for deselection, far less is known about how librarians understand deselection in contemporary practice, particularly in contexts where cultural obligations and responsibilities are significant, such as in Aotearoa New Zealand. This study examines the factors influencing librarians’ deselection approaches in Aotearoa. Using a qualitative design, semi-structured interviews were conducted with librarians across a range of library settings. Findings show that while space constraints continue to motivate reductions in print collections, deselection decisions are driven primarily by user-centred considerations, including the need to maintain collections that are current, relevant, and responsive. Participants valued data-driven tools for promoting consistency and reducing subjectivity, but professional judgement remained central, especially when working with Māori materials, where cultural sensitivity and accountability are critical. The analysis demonstrates that deselection in Aotearoa New Zealand libraries is not merely a technical task, but an affective, relational, and culturally informed practice shaped by local contexts, professional values, community expectations, and bicultural commitments.

ABSTRACT Climate change is increasingly recognised as a threat multiplier in agrarian societies, where erratic rainfall, fragile irrigation systems, and crop failures heighten livelihood insecurity and intensify local tensions. Deterministic accounts that portray climate change as an inevitable driver of conflict, however, often overlook community agency and the everyday practices through which households absorb environmental shocks. This article examines a traditional Javanese intercropping system, tumpangsari, as a form of social mitigation that links ecological diversification with cooperation and reciprocal labour. Drawing on comparative qualitative fieldwork in Gunungkidul Regency and Banten Province, the study shows how intercropping reduces dependence on single-crop rice harvests, distributes risk, and embeds informal mechanisms of resource sharing that diffuse grievances before they escalate into open disputes. The analysis contributes to debates on the climate – conflict nexus and environmental peacebuilding by demonstrating how locally embedded agricultural practices can redirect environmental stress towards collective risk management rather than confrontation. It also highlights the limits of such adaptation: tumpangsari often operates within patron – client hierarchies that reproduce unequal access to land and resources, producing functional stability without structural transformation.

BackgroundTo be beneficial for empirical health research, a dataset must be fit for use. The quality of a dataset can only be influenced during data collection, yet it is evaluated multiple times during analysis or secondary use by applying quality indicators.ObjectiveThis study aimed to establish an up-to-date set of indicators measuring the quality of datasets in empirical health research.MethodsA total of 3 pillars were combined. First, the 51 indicators of a German guideline from 2014 about the management of data quality were revised. Second, a literature review was performed looking for evidence sources since 2013 that describe, propose, or apply dataset quality indicators. Third, indicators were supplemented by a manual search and other sources. The quality indicators were then integrated into the IDEFIM framework. The IDEFIM framework distinguishes between the categories’ data, metadata, context, and openness quality. In this work, only the categories data and metadata quality, with their 14 dimensions were considered.ResultsIn total, 69 indicators qualified for the IDEFIM indicator set, 53 related to the category data quality, and 16 to the category metadata quality. A total of 30 indicators originated from the German guideline, 31 from the literature review. Three indicators were added to cover aspects of diversity, equity, and inclusion, and an additional 5 related to specifics of data and metadata quality not addressed so far. Most indicators were found in the dimensions accuracy (data) with 12 measures, completeness (data) with 12 measures, and consistency (data) with 19 measures. According to the number of supporting evidence sources, missing values in data elements (48 evidence sources), contradictions (31), and currentness (26) were the most popular quality indicators. Metadata quality was significantly less frequently addressed.ConclusionsThe presented IDEFIM indicator set can be used for the management of data collections as well as for the verification of a dataset’s quality for an intended use. The indicator set should also be considered in the design of a study in empirical health research and the development of software tools supporting the visualization of issues related to the quality of a dataset.

During the COVID-19 pandemic, museums worldwide were unable to accept visitors but managed to survive by strengthening their digital activities. This popular "success story," however, is based on reports from major, well-resourced institutions and systematically overlooks vulnerable small-scale museums. This study challenges that narrative by examining how education changed in small-scale museums during COVID-19 and the resulting lockdowns. Semi-structured interviews were conducted with professionals from six memorial museums in Vilnius, Lithuania, and analyzed using qualitative content analysis, which yielded three categories: Education, Backyard, and Other quarantine-related experiences. The interviews revealed three key findings. First, experiences in small museums are easily lost owing to precarious employment in underfunded institutions; notably, two of the six museums had replaced their entire pandemic-era staff, rendering those crisis experiences unrecoverable. Second, survival strategies varied according to institutional power, as museums adapted through online programming and teacher networks in different ways depending on available resources. Third, the resourcefulness born of structural constraints is reflected in “backyard work”–collection management and digitization–which the literature has largely overlooked. These findings demonstrate that established best practices derived from major museums may not apply universally. Inclusive perspectives on museums during the pandemic are essential for both equity and future crisis preparedness, and they require an understanding of how institutional power shapes survival strategies and their documentation.

Purpose Despite the co-existence of commercial, public-sector and social-welfare mindsets in business processes, the knowledge is limited about how and why these logics affect supply chains (SC). The purpose of this study is to investigate how such logic-infused activities enhance the overall performance and resilience of SC by affecting the level of trust among SC actors. Design/methodology/approach A sequential mixed-methods design was followed to develop an integrated perspective. First, a survey was conducted on a sample of 174 retailers in the pharmaceutical SC, and partial least-squares structural equation modeling was used for data analysis. In the qualitative study, we conducted interviews with 17 managers and thematically analyzed. Findings Hypothesis testing results reveal that risk avoidance-oriented, collaboration-oriented and community-oriented activities positively affect trust among SC members; in turn, trust reinforces both SC resilience and performance. In contrast, performance-oriented activities have a negative effect. Both supporting and expanding these results, the qualitative findings show that while community, social-welfare and public-sector logics complement each other through trust-based mechanisms (e.g. knowledge-sharing, traceability, loyalty and collective risk management), commercial logic contrasts them and hinders positive SC outcomes. Research limitations/implications This study proposes that SC context is shaped not only by commercial and public-sector logics but also by social-welfare logic. As a twofold construct, social-welfare logic influences the trust-building capacity of SC members by imposing unique and frequently opposing pressures. Practical implications The study suggests that engaging in activities that do not prioritize commercial goals could be particularly effective in trust-building and attaining positive SC outcomes. Moreover, shared concerns and attempts by SC members toward improved societal welfare determine trust, resilience and performance to the highest degree. Social implications The study deepens the understanding of developing countries where there is a highly complex SC setting that is mostly vulnerable to opportunistic behaviors from SC actors, which can significantly undermine trust. Originality/value To the best of the authors’ knowledge, this is the first study that identifies four unique institutional logics and compares their relative importance in the SC context by exploring the role of trust. The study also highlights the importance of collaboration and community-oriented activities, manifesting themselves in socially responsible behaviors inside and outside of SC.

Tissue biobanking is essential for biomedical research. Well-defined interfaces and standardised procedures are required to ensure sample quality and the subsequent reproducibility of research results. This paper provides an overview of the key interfaces involved in tissue biobanking workflows, including sample collection, processing, storage, distribution and data management. It outlines the minimum standards required to maintain high-quality samples and associated data, and references relevant national and international guidelines. The paper also addresses the current challenges faced by biobanks, such as harmonisation across institutions, evolving regulatory landscapes, and the integration of digital infrastructure. The primary aim of this work is to present recommendations for the effective implementation and documentation of minimum standards. These recommendations are intended to help biobanks to align with regulatory expectations, optimise operational procedures, and facilitate high-quality, ethically sound biomedical research.

Day-ahead optimization model for renewable energy communities considering load shifting, electric vehicles and vehicle-to-grid technology

Land conservation initiatives worldwide are poised to continue rapid growth. Ranging in scale, scope, and mechanisms, these efforts include area-based conservation, incentive-based protection, and community collective management. Evidence from across fields now indicates that it is possible for land conservation to jointly improve environmental conditions, generate positive net local economic benefits, and support social equity. Yet the key policy elements that can lead to this type of multidimensional success are not well understood. Here, we review the considerable body of existing research on land conservation and propose eight emerging design principles that conservation actors can employ to support "win-win-win" outcomes: 1) identify and support credible pathways of change, 2) set goals for all outcomes, recognizing their interdependencies, 3) accommodate multiple needs and uses through spatial or place-specific differentiation, 4) facilitate temporal resilience through diversification and limits, 5) foster nested governance, 6) integrate information structures for environmental and social outcomes, 7) assess policies using counterfactual-based analysis and adaptive management, 8) establish lasting institutions and funding mechanisms. Although these design principles will likely change and evolve, they provide an evidence-grounded framework to support current and future efforts to steward global lands.

Upgrading from Java 8 to Java 17 in the enterprise setting is both challenging and an opportunity, especially for mission-critical ecosystems. Java 17 is a long-term support (LTS) version that includes numerous enhancements over Java 8, including language syntax enhancements, improved garbage collection and memory management, enhanced security models, and modularization via the Java Platform Module System (JPMS). Nevertheless, the opportunities presented by Java 17 can be fully realised with the assistance of a well-organised migration plan that assesses risks, implements mitigation strategies, and ensures the equipping of enterprise-scale systems. This paper proposes a risk-based migration framework that is SAP-based, Java environment-specific, and identifies safe migration patterns, along with a detailed case study example to demonstrate how the workflow migration methodology works. We suggest an expedient and replicable solution that accommodates modernization.

ABSTRACT Studies on collective impression management in the sport coaching literature have begun to illuminate the backstage and frontstage techniques used by teams of professional sport coaches. This study is the first to examine team assembly, deployment and alignment building within a neoliberal employment context. Data were generated via participant observation, fieldnotes, and semi-structured interviews. The data were subject to multiple rounds of emic and etic analysis, which were primarily sensitised by Goffman’s dramaturgical theorising. Analysis revealed that (1) a neoliberal and contrived approach to team administration produced transient team relations and limited opportunities for alignment building, (2) short-term team associations resulted in cynical, pragmatic and instrumental orientations to staging activities, and (3) teams relied on deception and fabricated lines of action to translate curricula and navigate performativity culture. These findings offer a new agenda for researching practitioner collaboration and a stimulus to refine administrative procedures and role preparation programmes.

This study is motivated by the high vulnerability of rare collections to physical, chemical, and biological deterioration, particularly in tropical environments with limited environmental control. Despite their substantial historical and cultural value, preservation strategies in specialized libraries remain insufficiently integrated and optimized. This study aims to analyze rare collection preservation strategies at the UPT Bung Hatta Proclamator Library based on the Preservation Pyramid Theory and to identify the supporting and inhibiting factors affecting their implementation. A qualitative approach with a case study design was employed. Six informants were purposively selected, comprising the head of preservation, preservation team members, a conservator, librarians, and a user. Data were collected through observation, in-depth interviews, and documentation, and analyzed using the interactive model of Miles, Huberman, and Saldaña. The findings reveal that preservation strategies have been implemented across four levels: preventive conservation, passive conservation, active conservation, and restoration, with preventive conservation as the dominant strategy. These efforts include environmental control using dehumidifiers, silica gel, and thermohygrometers, as well as restricted access policies. However, several limitations remain, including budget constraints, suboptimal storage facilities, and inconsistent documentation practices. Active conservation and restoration have been relatively well implemented with support from trained conservators, although technical constraints persist. The study concludes that rare collection preservation at the UPT Bung Hatta Proclamator Library has been implemented but is not yet fully integrated across strategic and operational levels. Its contribution lies in demonstrating the relevance of the Preservation Pyramid Theory for evaluating rare collection management in specialized libraries and emphasizing the need for stronger institutional policies, preservation-standard facilities, and enhanced human resource capacity to ensure sustainable rare collection preservation.

Consciousness is central to the human condition, but its inherent characteristics and underlying mechanisms remain poorly understood. Advances in neuroscience based on the concept of the vegetative state have expanded the understanding of disorders of consciousness (DoC), particularly the minimally conscious state (MCS) and emergence from the MCS. Despite this progress, diagnostic uncertainty persists due to the subtlety of clinical signs and variable outcomes. Although standardized behavioral scales remain the gold standard for diagnosing DoC, advanced imaging and electrophysiological tools increasingly highlight the importance of multimodal assessments. These approaches have demonstrated that patients who appear unresponsive in behavioral assessments may voluntarily engage in mental activities that can be detected using functional magnetic resonance imaging and electroencephalography, potentially revealing covert consciousness and suggesting possible therapeutic strategies. This review consolidates the current evidence on the diagnosis, prognosis, and mechanisms of DoC across various neurological conditions. We highlight the role of brain networks in producing diverse phenotypes as well as the need for well-designed studies that can improve multimodal diagnostic strategies. Building on recent initiatives aimed at standardizing definitions, prognostic guidelines, data collection, and clinical management practices, we show that further multimodal neuroimaging research is essential to improving diagnoses, prognostication, and outcomes for patients with DoC and their families.

Electricity generation by burning by waste material, also known as thermal waste-to-energy, is a process that involves converting waste material into electricity by burning them in a combustion chamber. This process is a sustainable solution for waste management as it reduces the volume of waste sent to landfills while producing renewable energy. The methodology, for electricity generation by burning waste material typically involves waste collection, handling, and preparation, incineration, energy recovery, and ash management. The generated electricity can be used to power local communities or industries or fed back into the national grid. The process of electricity generation by burning waste materials provides a reliable source of electricity while reducing greenhouse gas emissions by avoiding the release of methane gas from landfill.

The Neuro-Ophthalmology Virtual Education Library (NOVEL) is an open-access digital repository of neuro-ophthalmology educational materials hosted by the Spencer S. Eccles Health Sciences Library (EHSL) at the University of Utah and established in collaboration with the North American Neuro-Ophthalmology Society (NANOS). Over its 20-year history, inconsistent metadata standards and evolving platforms have led to irregularities that impeded search performance and collection management across its 20,000 digital learning objects across 31 collections. In 2023, EHSL launched a comprehensive metadata remediation initiative to address these issues and align NOVEL with current metadata and digital collection practices. A five-stage roadmap consisting of collection assessment, metadata analysis, standards development, implementation, and evaluation was developed along with visualization tools and collaborative workflows. Over 18 months, the project team systematically standardized metadata fields, created a specification guide, and edited all metadata for accuracy, completeness, and consistency. This case report establishes a model for systematic metadata remediation for large legacy digital collections with the goal of improving discoverability, usability, and sustainability of the collections.

Subject. This article discusses adaptive control systems development in a changing economic environment, and approaches to risk management. Objectives. The study aims to develop a practice-oriented methodology for building a forecasting system aimed at reducing operational risks. Methods. For the study, we used mathematical modeling, and systems approach to the forecasting system architecture development. Results. The article proposes a methodology for building an intelligent forecasting system, and describes the system architecture, including modules for data collection, analysis, forecasting, and risk management. Conclusions. The integration of the forecasting system into the risk management framework is a key condition for improving the economic security of an enterprise. Forecasts based on deep learning models showed the best results, confirming the need for their implementation in the management process.

Chronic pancreatitis is a progressive inflammatory disorder marked by irreversible parenchymal injury, fibrosis, and multifactorial pain. Therapeutic endoscopy plays a central role in managing obstructive phenotypes and selected complications. This review synthesizes contemporary evidence on endoscopic management of pancreatic duct stones, main pancreatic duct strictures, benign biliary strictures (BBS), pancreatic duct leaks, pancreatic pseudocysts, and endoscopic ultrasound-guided celiac plexus block, addressing the role of endoscopy. A narrative review was performed, evaluating pain relief, ductal decompression, quality of life, adverse events, and reintervention across ERCP-based therapies, extracorporeal shock wave lithotripsy, pancreatoscopy-guided electrohydraulic or laser lithotripsy, and endoscopic management of pancreatic fluid collections and ductal leaks, and endoscopic ultrasound-guided pain interventions. In painful obstructive chronic pancreatitis, targeted endotherapy can provide symptom relief; however, randomized trials generally favor surgery drainage procedures and/or pancreatic resection over endoscopy for sustained pain control, ductal decompression, and physical quality of life, with comparable safety. ERCP alone is appropriate for small pancreatic duct stones, whereas larger stones are managed with extracorporeal shock wave lithotripsy or pancreatoscopy-guided electrohydraulic or laser lithotripsy to achieve ductal clearance. Main PD strictures are managed with dilation and stenting, with single large-caliber plastic stents preferred; routine use of fully covered self-expandable metal stents is discouraged due to higher adverse events. For chronic pancreatitis-associated BBS, fully covered metal and multiple plastic stents demonstrate similar long-term efficacy, with metal stents reducing procedural burden. Symptomatic PPCs are optimally managed endoscopically based on anatomy and ductal communication. EUS-CPB provides short-term analgesia for refractory pain. Endoscopic therapy is integral to multidisciplinary CP management, offering effective, anatomy-driven interventions, while surgery remains preferred for durable pain control in selected patients.

Actuarial science is a growing discipline that applies mathematical and statistical methods to transform business data into practical strategies for risk and insurance management for individuals and organizations. Because the field is highly interdisciplinary, intersecting mathematics, statistics, finance, economics, medicine, and the social sciences, it can pose challenges for collection development. Citation analysis is an important method for determining whether a library’s collection adequately supports the academic programs it serves and for understanding trends in users’ resource use. This study employs an AI-assisted citation analysis methodology to examine references cited in articles published from 2015 to 2024 in nine actuarial science journals. The citation analysis identifies leading resources across various resource types and examines trends in resource use within actuarial science research. The author further analyzes the data, applying Bradford’s Law to provide a core list of journal titles. The study includes implications for collection management in actuarial science.

Robotization and the introduction of AI exert systemic pressure on the social contract due to the gap between the pace of technological transformation and the speed of institutional adaptation. In this context, the revision of the social contract to align with new realities is relevant. The purpose of the article is to examine the model of the new social contract forming as a result of robotization and the introduction of AI. The study employs conceptual modeling based on trends in political practices, labor market, and economic policy. As a result of the research, the main factors for revising the social contract are identified: (1) deficit of accountability of algorithmic power, (2) labor polarization and increasing vulnerability of social groups, (3) employment redistribution and problems of social integration. A model of the new social contract is presented, including algorithm transparency, innovations in the field of labor and education, as well as new tools for resource redistribution. The new social contract performs an adaptive function, providing intermediate institutions for collective risk management and future design. The research results supplement current works on the consequences of robotization and the introduction of AI, future research should account for new links between technologies, institutions, employment, and social mobility.

Influenced by factors such as residents’ living habits, commuting patterns, and commercial activity cycles, the generation of domestic waste exhibits a distinct double-peak distribution. To meet the high demand during peak periods, collection companies typically deploy excess transportation capacity, which leads to severe resource idleness during off-peak periods, imposing significant economic and environmental burdens. To address this issue, this study develops a dynamic smart waste collection routing model aimed at minimizing the coordinated collection cost between self-owned and outsourced multi-compartment vehicles, and designs a two-phase algorithm to solve it. In the pre-optimization phase, an improved Harris Hawks Optimization algorithm integrated with multiple heuristic algorithms is employed to generate initial collection routes. In the re-optimization phase, a hybrid strategy combining periodic and continuous re-optimization is used to dynamically update collection routes. Finally, the effectiveness of the proposed model and algorithm is validated through case studies. Furthermore, a systematic sensitivity analysis is conducted to investigate the impact of key parameters, yielding practical insights for waste collection management.