Goal: This research identifies the optimal location for additive manufacturing (AM) facilities within the spare parts supply chain, addressing a critical yet underexplored dimension in the literature on strategic facility location for AM technology deployment.Design / Methodology / Approach: The study integrates agent-based discrete event simulation with scenario analysis to evaluate four facility locations for four distinct spare parts. The model aims to reduce order fulfillment losses and opportunity costs by supporting evidence-based location decisions.Results: The findings indicate that the Thane location is the most suitable for establishing an AM facility, offering a balanced trade-off between supply reliability and economic efficiency.Limitations of the investigation: The scope is confined to a specific case involving four locations and four spare parts, which may limit generalizability. The study’s scenario-based approach also relies on assumptions that warrant further validation.Practical implications: The results offer actionable insights for firms adopting AM in spare parts management. Strategic facility placement enhances service responsiveness, reduces downtime, and supports cost-effective ful-fillment strategies.Originality / Value: This research provides an incremental empirical contribution by proposing and demonstrat-ing a simulation-based AM facility location selection framework, supported by real-world case data. It addresses a less explored strategic decision of AM facility placement, considering dynamic operational uncertainties, thereby extending the existing literature on AM supply chain design.

Carbon footprint characteristics and reduction strategies of the iron and steel industry: an LCA-based study of source, process, end-use and cleaner production applications.

Method for determining spontaneous combustion status in composite goaf areas of extra-thick coal seams: A numerical simulation study based on a specific case

Designing and testing a fetal protection system for radiotherapy in pregnant patients.

Escalating climate change and the increasing frequency of weather extremes pose a threat to the resilience of urban environments and human health, highlighting the urgent need for implementing energy-efficient interventions and reducing building cooling loads. This study investigates the passive building envelope retrofit technologies of external shading, electrochromic windows, and thermochromic windows through a multi-criteria evaluation analysis based on energy savings, economic performance, and indoor thermal comfort improvement. Thermochromic windows are discerned by a mean colour transition temperature of 34 °C and operate throughout the entire year, while electrochromic windows are activated only during cooling periods. Both technologies present total solar transmittance indices of 72.6% and 8.4% in the bleached and tinted state, respectively. External shading devices are either static or movable, applied with an inclination angle, and are either standalone interventions or combined with chromogenic glazing. Eight retrofit scenarios are investigated for a single-story, fully electrified residential building in Athens, Greece. The building features south- and east-oriented windows, which is an appropriate case to assess the effectiveness of these passive envelope cooling technologies in regulating solar heat gains. Thermal comfort is assessed using Fanger’s PMV (predicted mean vote) and PPD (Predicted Percentage of Dissatisfied) indices. The combination of electrochromic windows and movable external shading yields the highest annual electricity savings at 22.2% and reduces the PPD by 15.8%. Local static shading, on the other hand, ranks as the optimal retrofit solution in terms of economic performance, with a life-cycle cost of €6378, a 9.3% improvement in thermal comfort, and a corresponding reduction of 626 thermal discomfort hours. While the proposed multi-criteria framework can be applied to other buildings and climates, the quantitative results reported here are linked to the specific case examined: a residential building with south- and east-facing glazing in Athens, Greece, representing Mediterranean climatic conditions.

The aim of this research is to examine the digital communication practices employed by museums in Greece to promote their activities to the public. It explores the role and brand identity of cultural organizations within the broader Greek cultural industries, aiming to understand how cultural institutions integrate digital marketing practices into their communication strategies. The main objective, through interviews conducted with museum communication professionals, is to investigate how augmented reality (AR) practices, as a dynamic intersection of technology and human values, are perceived by museums and how their implementation can enhance the visitor experience and create added value in cultural services. Additionally, the study examines how digital content production is influenced by employees’ digital literacy levels, the technological requirements of different communication platforms, and the core values of museums. To provide a comprehensive analysis, specific case studies from cultural institutions are examined.

ABSTRACT In a new security world of growing international population displacement, refugee protections are an essential source of peace and global stability. This article evaluates the capacity of a bifurcated international refugee regime constructed in a neo-liberal order of the last mid-century, to respond to the humanitarian demands of the 21st century. Focusing on the UNHCR and UNRWA, this study compares two key international organizations mandated by the United Nations to protect dispossessed people and weighs them against humanitarian and demographic outcomes. The neo-institutional analyses of legal frameworks, policy instruments, and norms point to intrinsic institutional flaws hindering progress for international refugee protection. From the historical institutional perspective adopted here, the persistence of a faulty segmented refugee regime can be understood as a product of institutional path dependence. In the specific case of displaced Palestinians, the result of a stand-alone group-centric refugee organization has been a deepening politicization of refugee protection, a diminution of humanitarian aid, and perpetuation of civilian sufferings. The conclusions offer potential solutions and policy recommendations to redress the refugee settlement gap more effectively.

Sequence-dependent self-assembly of peptides yields ordered supramolecular structures with diverse nanotechnological applications. In the absence of simple design rules linking sequence to supramolecular morphology, coarse-grained molecular dynamics (CG-MD) simulations have become valuable tools for guiding the design of self-assembling peptides. The MARTINI model, despite the lack of explicit hydrogen bonding, can predict self-assembling sequences and structural features by introducing secondary structure-specific beads that adjust backbone polarity. Extended β-sheet encoding is typically used as input for short peptides, based on experimental observations. However, this assumption becomes increasingly unreliable beyond six to ten residues, where folded conformations begin to emerge. In this study, we investigated the effect of different secondary structure encodings on self-assembly simulations of hexapeptides and decapeptides using MARTINI 2.2p. The results confirmed that changes in the secondary structure encoding significantly impact the predicted self-assembly behavior, with AP scores for the same peptide varying by up to one unit─shifting from fully dissolved (AP ≈ 1) to well-aggregated states (AP > 2) in specific cases. This effect arises from alterations in overall peptide amphiphilicity caused by shifts in backbone polarity. However, the magnitude and direction of this influence depend on side-chain polarity and peptide length, making the resulting bias highly sequence-specific and difficult to anticipate or correct systematically. These findings emphasize the need to reevaluate the conventional use of extended β-sheet encoding (E-flag) and advocate for more native-like backbone representations in peptide self-assembly simulations.

Exporting food products from the European Union (EU) to the United States of America (USA) involves navigating complex regulations and procedural barriers that hinder market access. Italian food businesses (FBs), particularly small and medium-sized enterprises (SMEs), often face difficulties accessing clear guidance, as national procedures are scattered across multiple sources. This paper proposes a structured three-step analytical framework to support EU FBs: product-specific analysis, identification of relevant EU and USA legislation, comparative legislative analysis via concordance tables, and identification of procedures to integrate into the Food Safety Management System. The framework was applied to an Italian medium-sized FB exporting pork-based pasta sauce to the USA. Beyond the specific case study, the proposed analytical framework was designed to be transferable and adaptable to other food categories and destination markets, providing a structured methodological tool to support regulatory alignment. In this sense, the framework can be considered product-independent but process-specific. As such, it can support both FBs and Competent Authorities in conducting risk-based assessments of regulatory equivalence and export compliance. Results indicated the need for Sanitation Standard Operating Procedures (SSOPs), thermal process validation, direct verification activities, and pre-shipment review. Findings emphasize that operational and procedural barriers disproportionately affect SMEs, highlighting the importance of targeted support to facilitate market access and strengthen certification systems.

Determining whether a cyber operation meets the threshold for being designated cyber warfare involves ethical, technical, and strategic criteria. These are primarily derived from international law frameworks such as the Tallinn Manual 2.0 and principles of the UN Charter. What are the primary criteria for cyber operations to be called acts of Cyber Warfare Threshold? (1). Scale and Effects of cyber operations. The cyber operation must cause effects comparable to a kinetic attack, such as: Physical destruction (e.g., damaging power plants, pipelines). Loss of life or serious injury. Severe disruption of essential services (power, water, healthcare). Example: Stuxnet physically damaged Iranian centrifuges, meeting this criterion. (2). The Intent and Purpose of the Cyber Operation. The cyber-attack must be strategically motivated and aimed at: Weakening an adversary’s military or economic capability, Coercing or punish a state. Achieving political or military objectives. Example: Ukraine power grid attacks were linked to geopolitical conflict. (3) Cyber operation must be attributed to a State. The cyber operation must be attributable to a state or conducted under its direction/control. State sponsorship or direct involvement elevates an attack from the level of being a cybercrime to the level of acts of cyber warfare. Example: WannaCry and NotPetya were attributed to North Korea and Russia respectively. (4) There must be severity and consequences related to cyber operations. The impact of cyber operation must be significant enough to trigger international legal obligations, such as a Breach of sovereignty. The possible classification of the cyber operation as a “use of force” under Article 2(4) of the UN Charter. Example: Triton/Trisis targeted safety systems in petrochemical plants, risking catastrophic damage. (5) The Target Type of cyber operation. Attacks by the cyber operation on critical infrastructure or military systems are more likely to meet the threshold. Civilian systems may also qualify if disruption is widespread and severe. (6) The Context and Scale of the cyber operation. The cumulative effects of cyber operations mean that: repeated or coordinated attacks may collectively meet the threshold even if individual cyber operations do not. This analysis will identify the ethical and anticipated ethical issues with the identification of Cyber Operations and the ethical criteria for these operations to reach the threshold for being classified as acts of Cyber Warfare. Our methodology will employ an interdisciplinary method that draws upon distinctions taken from Bratman’s BDI Model of rational agency, computer science, and conceptual ethical analysis with reference to specific case studies.

This study uses technological infrastructures to inform evidence-based policy design, addressing the conundrum of agricultural productivity and agro-environmental sustainability in Africa. The investigations are done using the Instrumental Variable Two-Stage Least Squares (IV-2SLS) strategy to control for potential endogeneity, covering the period 2000–2020. The findings show that farmers, in their pursuit of greater productivity, often adopt unsustainable agricultural practices, which degrade agro-environmental quality through emissions of nitrous oxide and methane gases. The findings remain consistent after considering the specific cases of crop production and animal agriculture. Similarly, results indicate that technology-infrastructure reduces nitrous oxide and methane gas emissions. Moreover, the negative marginal effect indicates that the indirect benefits for sustainable agriculture provided by integrating technological infrastructure outweigh the adverse impacts on agricultural sustainability. These findings suggest that policymakers should promote the integration of technology infrastructures into the agricultural sector, as they serve as effective tools for enhancing agro-environmental sustainability.

This study presents an integrated numerical–experimental assessment of the steel box-girder bridge located in the central span of the Honestino Guimarães Bridge, the only bridge designed and built by Oscar Niemeyer. Motivated by recent rehabilitation works, including the replacement of support bearings, the research combines long- and short-term ambient vibration monitoring, static load testing, and finite element (FE) modelling. Operational Modal Analysis was used to extract modal parameters, which were subsequently employed in a model updating procedure based on a linear programming routine implemented in MATLAB. The updated model achieved frequency discrepancies below 2% and reproduced static strains with errors under 3% when compared with field test results. Beyond the specific case analysed, the study provides a structured and transferable methodological framework for researchers and practitioners working with existing bridges. By demonstrating how ambient vibration data, FE modelling, and iterative updating can be effectively integrated to handle uncertainties in boundary conditions, material properties, and undocumented interventions, this work contributes to ongoing scientific efforts to improve the reliability of numerical simulations and the development of digital twins for ageing infrastructures. The results reinforce findings from recent literature and highlight the value of combining multi-source experimental data with advanced numerical techniques to enhance structural assessment, rehabilitation planning, and long-term monitoring.

In the current work, we propose a discrete version of the Ricci–Bourguignon flow, based on the notion of Ollivier–Ricci curvature, to investigate the evolution of weighted graphs. This flow generalizes the Ollivier–Ricci flow in community detection problems. By deriving essential Lipschitz estimates for curvature operators and using standard ODE theory, we prove local results, including existence, uniqueness, continuous dependence, and a blow-up criterion for solutions to the proposed equation. In addition, we derive global-in-time results for some specific cases with idleness parameter larger than 1 / 2 . Precisely, considering a path graph of length 3 and the Wasserstein distance defined with the resistance mobility function, we obtain not only the global well-posedness of the solution but also its asymptotic behaviors. For a star graph with one center and the Wasserstein distance defined with the linear mobility function, we show that the proposed flow coincides with a normalized Ollivier–Ricci flow which preserves the total volume of the graph. Furthermore, we prove that under the action of the flow, the graph converges to a uniform star graph.

Since the early twentieth century, historical accounts of belief in the devil have tended to see the period from the Enlightenment onwards as the nadir of belief in a personified devil, particularly in secularising Europe. While this is demonstrably the case in some regards, more recent scholarship has complicated this picture, and this is particularly salient with reference to sectors of the Roman Catholic Church. This article examines the specific case of the survival of Roman Catholic demonology in the period from the late nineteenth century through to the eve of the Second Vatican Council (1962–1965). By surveying a series of discursive fields usually treated separately, this article highlights that far from being abandoned, demonological discourse remained a feature of various sectors of the Church during the period between around 1850 through to 1960 and can be evidenced in a variety of intellectual domains ranging from the developing discipline of Biblical Studies to the historiography of witchcraft and touching on areas extending from the Roman Catholic response to Spiritualism through to the modernist controversy and popular literature.

Preoperative imaging is vital for cochlear implant surgeries, aiding diagnosis, and surgical planning. This study evaluated global practices and the value of preoperative imaging through an international survey. A cross-sectional survey was conducted among international cochlear implantation experts using a 112-item questionnaire. The study explored imaging modalities, anatomical targets, evaluated parameters, and different imaging approaches' perceived value and risks. Participants were recruited from a global consortium of otolaryngology, otology, neurotology, and cochlear implant surgery professionals. Thirty-nine practitioners from 36 centers in 16 countries completed the survey (95.1% response rate). All used computed tomography (CT) and magnetic resonance imaging (MRI) for preoperative evaluation; MRI was deemed more valuable for diagnosis and candidacy assessment, while CT was preferred for surgical planning. Nearly half utilized additional imaging modalities, with functional MRI being the most common (20.5%). Additionally, 79.5% of respondents reported using image-based surgical planning software. Results show a universal reliance on CT and MRI for cochlear implant evaluations, with MRI aiding diagnosis and CT focusing on surgical planning. Advanced imaging techniques may emerge in specific clinical cases. Modern imaging practices and their potential changes can enhance protocol development and improve preoperative evaluations, ultimately boosting patient safety and outcomes in cochlear implantation.

Blood pressure (BP) measurement always has been a critical technique for cardiovascular health assessment by playing a vital role in diagnosing and managing hypertension, which is a leading risk factor for various heart diseases and strokes [5]. Over the years, BP measurement techniques have evolved many times, like transitioning from invasive, complex methods to non-invasive ones. Also, now we have automated and wearable technologies [6]. This paper reviews the historical development of BP measurement devices by tracing their improvement from the mercury sphygmomanometers to the modern digital and wearable monitors that can integrate through artificial intelligence and IoT-enabled health monitoring systems. Here we have examined the various BP measurement techniques, which also include various unique methods like auscultatory and oscillometric methods, highlighting their principles, accuracy, and clinical relevance [5], [6]. Traditional methods such as the Riva-Rocci mercury sphygmomanometer and aneroid sphygmomanometers were widely used, but they did have many limitations regarding accuracy, observer bias, and environmental concerns due to the hazardous impact of mercury poisoning [3], [4]. The advent of automated digital BP monitors has made our lives a little easier but presents many challenges related to calibration, accuracy, etc., in specific cases. But by this we have also explored many emerging cuffless and continuous BP monitoring technologies, which can leverage optical sensors, pulse transit time, and machine learning algorithms to offer real-time and long-term BP tracking [7], [8], [9]. Through our analysis, in this paper we discuss the advantages and drawbacks of past and present BP measurement methods, also emphasizing factors such as accuracy, convenience, affordability, and their effectiveness in clinical and home settings. While traditional devices remain the unique and rare standard in clinical practice, technological advancements aim to enhance user compliance, real-time monitoring, and remote patient management [6]. Looking ahead to the future of BP measurement lies in the integration of wearable and implantable biosensors, which are AI-driven predictive analytics, and they are also non-invasive monitoring techniques, which eliminates the need for cuffs. The development of photoplethysmography (PPG)-based smartwatches, flexible skin patches, and nanotechnology-enabled biosensors guarantees continuous and more accurate BP monitoring without any discomfort, which is associated with conventional devices. Additionally, advancements in AI and cloud-based data analytics will enable personalized BP monitoring and early disease predictions and also better management of hypertension through telemedicine and other remote healthcare solutions. In conclusion, we can say that while traditional BP measurement methods have shaped the clinical practices for over a century, emerging innovations have the potential to revolutionize cardiovascular monitoring, making it more accessible, precise, and patient-friendly [7], [8], [9], [10]. This review provides a comprehensive comparison of historical and contemporary BP measurement techniques and discusses the future trajectory of this field, also emphasizing the shift towards continuous, cuffless, and AI-enhanced monitoring systems [9], [10].

Abstract Federated learning (FL) is a promising paradigm for collaborative, privacy-preserving training of machine learning (ML) models on decentralized, private data. However, significant challenges limit the broader adoption of FL. First, existing FL workflows are often tailored to specific use cases, requiring extensive manual setup and customization of execution environments. Second, establishing collaborations and matching partners is complicated by the diversity of organizational and collaboration goals, data properties, and data distributions. Third, tracking the provenance of the collaboration process and the artifacts created and used during collaboration is challenging, impeding accountability, transparency, and debugability. Our goal is to address these barriers by lowering the technical expertise required from collaborators. We contribute mechanisms for flexible collaboration composition and creation, automated collaborator matching, and collaboration and artifact provenance.

Abstract Large- to global-domain short-term prediction of clouds (0–3 hours), or cloud nowcasting, remains relevant to civilian and military applications ranging from solar energy production to intelligence gathering. Despite the capabilities of contemporary numerical weather prediction models, nowcasting methods based on near real-time observations (i.e. satellite imagery) hold operational value due to their relative computational efficiency and accuracy for short-term applications. A commonly used nowcasting approach involves using two or more images to retrieve the apparent motions of features, or optical flow, which can be used to extrapolate the future location of those features. However, such approaches generally assume that the optical flow field remains unchanged with respect to time which is challenging to apply to piecewise cloud fields from satellite imagery. Here, we propose a method to nowcast clouds that adapts a computer vision technique for image interpolation, commonly referred to as warping, to account for temporal changes to optical flow fields derived from infrared satellite imagery. We evaluate the proposed method for 991 randomly selected regional cases from 2024 and perform a detailed analysis on three specific cases from 2023. Applying a dense (every image pixel) optical flow retrieval technique to full-disk GOES infrared imagery, we demonstrate that forward warping, when coupled with simple occlusion reasoning, improves nowcasting skill. In addition, we leverage the same optical flow method to predict satellite brightness temperatures and compare the resulting nowcast to the predictions produced from a U-Net architecture implemented autoregressively. Ultimately, the optical flow method outperforms the U-Net at the 3-hour prediction timeframe when evaluated using root mean square error.

Abstract This research review focuses on the catastrophic earthquake that hit Türkiye on February 6, 2023. The mainshock was magnitude Mw 7.8, with its epicenter in southern Türkiye, close to the northern Syrian border. Approximately nine hours later, there was a second large earthquake of magnitude Mw 7.5 some 95 km (59 miles) to the southwest. These seismic events resulted in significant building and infrastructure damage throughout the affected area. This review considers the major factors that led to structural collapse during the earthquakes, such as design, construction practice, and maintenance deficiencies. The function of seismic codes and regulations in preventing structural collapse is also considered. Specific building failure case studies are compared to gain an understanding of the weaknesses of various structural types. The review concludes by highlighting the need to incorporate lessons drawn from these incidents into future building design and construction processes to make structures more resilient in seismically active areas like Türkiye.

The analysis of inequalities aids in the formulation of optimal coding schemes that improve the rate of information transfer while reducing the probability of errors. This consequently implies that we have a major impact on having solid and secured correspondence systems for applications running from broadcast communications to information pressure. Information theory inequalities constitute a theoretical toolbox for designing channels that can overcome a challenging environment, allowing information to be held and communicated reliably and securely in a world that is becoming ever more interconnected. The paper introduces a general divergence model in general probability spaces and extends known information-theoretic inequalities and results based on variational models. We have built various inequalities for finite sequences of positive real numbers, the specific cases of which are important in information theory, especially in connection with several divergence models that remain in the literature. Additionally, we have derived certain other important communications concerning positive real numbers in relation to some divergence models.