Search Results (326)

Cultural heritage faces accelerating threats from armed conflict and climate-induced disasters, generating emergency scenarios in which the window for documentation may be measured in hours. Traditional high-fidelity workflows such as Terrestrial Laser Scanning and survey-grade Structure-from-Motion campaign can be operationally incompatible with these constraints due to costly hardware and specialist-team requirements. Emergency image acquisition can be undertaken with consumer-grade equipment, while the same photographic dataset can subsequently support both an SfM-MVS mesh for metric and geometric analysis and a 3D Gaussian Splatting (3DGS) representation for view-dependent visual interpretation. This paper evaluates an accessible, entirely graphical workflow for producing these complementary outputs, with particular attention paid to the 3DGS stage and without requiring programming or command-line expertise. We develop a theoretical case drawing on Brandinian restoration theory and the international conservation framework, introducing the concept of informational amnesia, the irreversible loss of a site’s documentary record, as a distinct and undertheorized category of heritage failure. We further argue that the democratization of 3DGS documentation cannot be measured by licensing cost alone: a tool distributed as open-source code but requiring command-line expertise presents an effective accessibility barrier functionally equivalent to a commercial paywall. True accessibility requires installable, graphical software operable by non-specialist practitioners in the field. We present a proof-of-concept application of this accessible pipeline, namely DJI Mini 5 Pro, RealityScan for photogrammetric reconstruction, and Lichtfeld Studio for 3DGS generation, to the Fontana d’Ercole at the Reggia di Venaria Reale (UNESCO World Heritage, Turin, Italy). Visual results show photorealistic, navigable 3DGS surrogates of architecturally complex heritage assets achievable by non-specialist operators within hours of acquisition and establish the empirical foundation for future quantitative evaluation. Full article

This study investigates the impact of different cases of armed conflict on the US stock market. It examines whether the market reacts differently in cases of direct versus indirect US military involvement in the conflict and at the initiation or termination of the conflict. The analysis is based on nine armed conflicts that took place from 2003 to 2022. The study utilizes an event study methodology and focuses on three sectors in the US stock market: Defense and Aerospace, Oil and Gas, and Alternative Energy. The results indicate that direct military involvement is generally associated with less favorable market responses, particularly during conflict initiation stages and within energy-related sectors. In contrast, conflict termination events frequently generate more positive market reactions, reflecting lower geopolitical uncertainty and reduced military exposure. Indirect involvement events, especially those related to the Russia–Ukraine conflict and the Russian intervention in Syria, are associated with more favorable responses in several sectors, particularly Aerospace and Defense. The study contributes to the literature by adopting a multi-conflict framework, distinguishing between direct and indirect military involvement, comparing conflict initiation and termination phases, and providing sector-level evidence on the heterogeneous effects of armed conflicts on financial markets. Full article

This article examines the legal implications of civilian intelligence applications used during armed conflict, focusing on smartphone-based reporting systems deployed in the Russian–Ukrainian war. Applications such as Ukraine’s e-Enemy feature integrated into the Diia platform and the standalone ePPO application have enabled civilians to provide real-time geolocated information concerning troop movements, missile trajectories, and military activities. While these technologies provide substantial operational advantages, they simultaneously challenge foundational principles of International Humanitarian Law (IHL), particularly the distinction between civilians and combatants. The article critically evaluates whether civilians using such applications engage in direct participation in hostilities (DPH) under Article 51(3) of Additional Protocol I, analysing the criteria of threshold of harm, direct causation, and belligerent nexus. It argues that although certain forms of real-time operational reporting may satisfy the DPH threshold in limited circumstances, existing doctrine remains insufficient to address the broader systemic implications of state-organised digital civilian mobilisation. The article further contends that embedding military intelligence functions within civilian digital infrastructure transforms such platforms into potential dual-use objects, thereby engaging state obligations under Articles 48, 52, 57, and 58 of Additional Protocol I, as well as Common Article 1 of the Geneva Conventions. Through doctrinal analysis and the Ukrainian case study, the article proposes the development of a “duty of digital separation” requiring states to maintain clearer distinctions between civilian services and military intelligence systems. It additionally advocates enhanced precautionary duties, informed consent mechanisms, risk disclosure obligations, and governance frameworks for civilian intelligence applications. Ultimately, the article demonstrates that while IHL remains technologically adaptable in principle, interpretative refinement is necessary to preserve civilian protection in the context of digitally mobilised warfare. Full article

Civilian communication systems often fail during armed conflicts, political unrest, and large-scale Internet disruptions—precisely when reliable communication is most needed. This paper presents HERMES, a resilient hybrid communication architecture that integrates HTTP/IP networking, Bluetooth Low Energy (BLE) mesh communication, and Delay-Tolerant Networking (DTN) within a unified adaptive routing framework. Unlike conventional approaches that treat alternative transports as backup solutions, HERMES dynamically selects the most efficient transport path based on current network conditions using a transport-aware forwarding policy whose cost function combines round-trip time, transport preference, and observed link risk. The architecture is built on distributed microservices that support topology discovery, shortest-path routing, and fault-tolerant message delivery. Reliability is enhanced through acknowledgments, bounded retransmissions, duplicate suppression, and graceful degradation mechanisms, while end-to-end authenticated encryption (Noise XX with a Double Ratchet) ensures secure communication across transport changes. A prototype implementation developed in C# on .NET 9 was evaluated on a five-node testbed, and a custom Network Simulator 3 (NS-3) module was used to extend the evaluation to networks of up to 500 nodes, under multiple failure scenarios, including node crashes, network partitioning, and complete Internet outages. Experimental results show that HERMES maintains perfect or near-perfect delivery in static topologies, including during a complete Internet blackout that disables IP-only messaging. Compared with the published Delay-Tolerant Networking protocols Epidemic and PRoPHET at one hundred nodes, HERMES exceeds their delivery ratio in static and failure scenarios and remains within 0.06 of them under pedestrian mobility during blackout, while transmitting roughly 35× fewer bytes– and about 21× fewer even relative to the more bandwidth-efficient MaxProp baseline. Under coordinated drop attacks by adversarial relays, HERMES degrades gracefully where flooding-based baselines collapse. This approach demonstrates that resilient civilian communication can be effectively achieved through metric-driven adaptive multi-transport routing, making it suitable for disaster recovery, contested environments, and connectivity-limited regions. Full article

The intensification of armed conflicts has forced thousands of women to seek refuge in other countries, exposing them to conditions of heightened vulnerability, characterized by inequality, violence, and mental health challenges. Despite these adversities, refugee women demonstrate resilience through diverse coping strategies. However, qualitative research centring women’s experiences within gender-sensitive and intersectional frameworks remains limited. This study aims to characterize the experiences of forced migration among refugee women in Portugal and to explore the coping strategies they have developed. Semi-structured interviews were conducted with six refugee women residing in Portugal. Based on thematic analysis, the data revealed a trajectory marked by material and symbolic losses, disruption of social bonds, and symptoms consistent with post-traumatic stress. Motherhood emerged both as motivation and as an obstacle to social and professional integration. Participants reported various coping strategies, including social support, self-efficacy, optimism, emotional regulation, religious coping, and contemplative practices. These findings indicate that coping strategies among refugee women are shaped not only by trauma exposure, but also by gendered structural conditions in the host context. These results highlight the need for gender-sensitive and trauma-informed public policies, as well as community-based interventions to promote social integration and well-being. Full article

Zimbabwe’s Fast Track Land Reform Programme (FTLRP) fundamentally reconfigured the country’s political economy, yet its implications for sustainable peace remain insufficiently theorised. This article interrogates how the economic fragmentation resulting from the FTLRP has shaped peacebuilding trajectories in Zimbabwe. The study draws on an integrative secondary data synthesis of existing datasets. Sources include Afrobarometer surveys, World Bank governance indicators, Uppsala Conflict Data Program and Armed Conflict Location & Event Data Project conflict event data, as well as national economic and environmental statistics. The analysis adopts a critical peacebuilding framework grounded in Johan Galtung’s distinction between positive and negative peace and Mushtaq Khan’s political settlements theory. The evidence suggests that the post-FTLRP economy is organised into three interrelated spheres: a politically dependent agrarian sector, a politically contested extractive sector, and a dominant informal economy comprising over 76% of enterprises. This configuration is associated with a form of negative peace. It is characterised by the absence of overt conflict but appears to be maintained through a coercive stability arrangement that selectively distributes land and economic rents to politically aligned elites and segments of the rural middle class while marginalising broader populations. The study concludes that achieving positive and sustainable peace requires a renegotiated political settlement centred on land tenure security, economic formalisation, and restorative justice. Full article

Background: Mental health disorders, including depression, constitute a major global public health concern that can lead to significant morbidity as well as societal costs. Internally displaced people are at risk for depression. This study aimed to assess the prevalence of depressive symptoms among adults in Atbara, northern Sudan, and identify the key factors associated with depressive symptoms, including internal displacement. Methods: Using a stratified sampling technique, data were collected by trained research assistants through face-to-face interviews using a structured questionnaire. The Patient Health Questionnaire-9 (PHQ-9) was used to assess depressive symptoms. Multivariate binary analysis was performed. Results: Three hundred and seventy-three adults were enrolled in this study; 104 (27.9%) were males. Their median age was 42.0 years. Of the 373 adults, 81 (21.7%, 95.0% confidence interval = 17.5–25.9%) had depressive symptoms (PHQ-9 scores ≥ 8). The prevalence of depressive symptoms was significantly higher among displaced adults: 39 (28.1%) of the 139 displaced adults had depression, and 42 (17.9%) of the non-displaced adults had depression, p = 0.027. In multivariate binary analysis, being internally displaced was the only factor associated with depressive symptoms (adjusted odds ratio = 1.82, 95% confidence interval = 1.07–3.08); age, body mass index, sex, education, and marital status were not associated with depressive symptoms. Conclusions: One out of five adults in this region of Sudan had depressive symptoms, which was associated with internal displacement. More effort and further research are needed to explore possible interventions to improve mental health and livelihoods, especially among internally displaced people. Full article

High-rise glass curtain wall cleaning has long relied on dangerous manual high-altitude operations, which suffer from low efficiency, high labour costs and prominent safety hazards. Existing cleaning robots generally lack a systematic user demand-driven design framework, making it difficult to balance safety, obstacle-crossing capability and maintenance performance. To fill this gap, this study proposes a four-stage integrated sustainable design methodology integrating the KANO model, Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD) and TRIZ. This methodology covers requirement attribute classification, priority weight quantification, demand-technology mapping and engineering conflict resolution, which can assist in sorting out multi-constraint design contradictions for the studied high-altitude cleaning equipment. Applying this methodology, the study develops the modular NetWing curtain wall cleaning drone with a vertically separable structure, retractable obstacle-crossing cleaning arm and quick-release cleaning head, and the feasibility of the conceptual scheme is preliminarily verified through numerical simulation. This work provides a quantifiable and replicable design paradigm for high-altitude service equipment, and the proposed solution can effectively reduce occupational risks and support the sustainable development of the facade cleaning industry. Full article

With the rapid development of networked cyber-physical systems, the coordinated control of heterogeneous multi-agent systems has attracted increasing attention in applications such as autonomous vehicles, robotic arms, and distributed sensor networks. This paper investigates the leader-following cluster consensus problem for heterogeneous multi-agent systems over weighted cooperative–competitive networks with matched disturbances generated by linear exosystems. Unlike purely cooperative or binary signed networks, the considered network allows interaction weights to take arbitrary positive or negative values, thereby describing both the type and intensity of cooperative or competitive interactions. To handle heterogeneous agent dynamics and matched disturbances, a disturbance-observer-based distributed control protocol is developed for both first-order and second-order followers. Based on path-product-based coordinate transformations and Lyapunov stability analysis, sufficient conditions are derived to guarantee topology-dependent scaled leader-following cluster consensus under interactively balanced and interactively sub-balanced topologies. For interactively unbalanced topologies, a structurally selected pinning control strategy is introduced to compensate for sign conflicts caused by unbalanced directed cycles and ensure global asymptotic convergence. Numerical simulations verify the effectiveness of the proposed protocol under heterogeneous dynamics, weighted cooperative–competitive interactions, and matched disturbances. Full article

Current acute coronary syndrome (ACS) care relies on sequential, single-modality diagnostics, in which the electrocardiogram, the troponin trajectory, and the coronary angiogram are interpreted independently rather than as a joint signal. This narrative review maps rather than pools the evidence. We selectively searched PubMed, EMBASE, Cochrane CENTRAL, and Web of Science (January 2015–February 2026); study selection was performed by a single reviewer, without duplicate screening, a PRISMA flow diagram, or a formal risk-of-bias assessment. The three key findings are as follows: A machine learning-enabled electrocardiogram (ECG) for diagnosing occlusion due to myocardial infarction achieved an AUC of 0.938 (95% CI = 0.924–0.951) on data not seen during training and correctly diagnosed 42% of patients that expert interpreters missed. A machine learning-enabled high-sensitivity troponin interpretation method, CoDE-ACS, reported an AUC of 0.953 and increased the number of patients ruled out at initial evaluation from 27% to 61%. Angiographically derived physiological methods produced conflicting results—quantitative flow ratios reduced major adverse cardiovascular events (MACE) in the FAVOR III China trial (HR 0.65), but in FAVOR III Europe the angiography-derived approach did not prove non-inferior to FFR; if anything, QFR guidance led to more events (6.7% vs. 4.2%, an event rate about 60% higher in the QFR arm; HR 1.63; 95% CI 1.11–2.41). There was no difference between FFR-angio and FFR in the ALL-RISE trial. These are diagnostic-accuracy and prognostic-association findings; no trial has yet shown that AI-guided ACS care reduces death, reinfarction, or ischemia-driven revascularization. Full article

Existing PLC security solutions face a fundamental conflict between stringent real-time requirements and robust protection: traditional IT security mechanisms (e.g., encryption, authentication) introduce unacceptable latency, while software-based redundancy schemes operate at millisecond scale and remain vulnerable to common-cause failures. To bridge this gap, this study proposes MimicPLC v1.0, a dynamic defense mechanism based on a heterogeneous multi-core architecture that integrates threat perception, dynamic fault tolerance, and rapid recovery within a single chip, thereby reconciling real-time determinism with proactive security in industrial control systems. The architecture integrates three distinct CPU cores (MIPS, ARM, and RISC-V) within a single system-on-chip (ESC0830), coordinated by a dedicated hardware-based mimic scheduling subsystem. This subsystem performs real-time, loosely coupled, transaction-level consistency checks on the AHB-Lite bus operations of the heterogeneous processors, achieving nanosecond-scale arbitration latency for threat detection. We evaluate the proposed design using an industrial-strength testbed, incorporating a custom development board and the Synopsys Verdi simulation environment, under critical attack scenarios including Denial-of-Service (DoS), replay, code injection, and parameter overwrite attacks. The system maintains continuous operation through adaptive redundancy, demonstrating attack perception within 73 clock cycles and leveraging instruction-set asymmetry for effective threat containment. Rigorous validation, including 100 consecutive parameter override attacks, confirms a 100% interception rate within our tested attack scenarios, with zero false positives observed. The design complies with the IEC 61131-3 real-time standard, exhibiting a worst-case recovery duration of 9.3 ms and a 95% confidence interval for recovery latency of [4.0354, 4.0363] ms. This work pioneers a paradigm of rapid-detection endogenous security with nanosecond-scale arbitration for next-generation industrial control systems. Full article

Political violence poses a significant challenge to global stability, underscoring the need for comparative analytical models that support analytical interpretation of structured conflict data. This paper presents a comparative evaluation of 12 machine learning approaches, including traditional supervised models, deep learning architectures, and zero-shot large language models, for the classification of political violence events using the Armed Conflict Location and Event Data Project (ACLED) dataset (2010–2020, over 40,000 events). The results demonstrate that, on short structured event text represented via TF-IDF, fine-tuned traditional machine learning models achieve stronger performance than zero-shot LLM approaches and deep learning models on structured event data. We further introduce a multilingual classification framework for English and Urdu news content, illustrating cross-lingual transfer robustness using machine-translated Urdu data; results reflect translation-based evaluation conditions and should not be interpreted as performance on naturally occurring low-resource Urdu political-event text. As an exploratory extension, the framework is applied to 57,700 tweets related to the Article 370 crisis in Kashmir to illustrate applicability to unstructured social media text; given that the best Twitter model (55% accuracy) falls below the 69% majority-class baseline, these results should be interpreted solely as coarse discourse indicators and not as a validated classification component. Unlike prior work, this study systematically combines multilingual evaluation with zero-shot LLM analysis for political event classification. Geographic out-of-sample validation (leave-one-country-out or leave-one-region-out) was not conducted; the reported performance should therefore not be interpreted as evidence of cross-regional generalizability without further experimentation. The findings highlight practical considerations for designing data-driven analytical frameworks for conflict monitoring and analytical decision support. Full article

This paper investigates the interplay between oil, critical minerals, and military expenditure in the U.S. and China. The research goal is to evaluate how sensitive the military expenditure of these countries is to shocks in energy markets. It develops a stylized dynamic model of the arms race and conflict, with a particular focus on U.S.–China tensions surrounding access to these vital resources. Empirical analysis using VAR estimations reveals that: (1) shocks to China’s military spending prompt increases in U.S. military expenditure, whereas the reverse effect is not observed; (2) critical mineral production significantly influences China’s military spending; and (3) U.S. military expenditure is affected by both Chinese military spending and fluctuations in oil prices. Full article

Background/Objectives: Triple-rule-out CT angiography (TRO-CTA) enables simultaneous evaluation of coronary, pulmonary, and aortic causes of acute chest pain, but conventional single-acquisition protocols may compromise vascular enhancement because of conflicting contrast timing requirements. This study evaluated whether a physiology-based sequential helical–axial–helical acquisition strategy could provide consistent tri-territory enhancement in emergency settings. Methods: In this retrospective single-center study, 71 consecutive evaluable emergency department patients (mean age, 66.6 ± 17.0 years; 33 women) with undifferentiated acute chest pain underwent TRO-CTA using a structured sequential protocol (pulmonary, coronary, and aortic phases) guided by individualized test-bolus timing. Objective image quality was assessed using vascular attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR); subjective image quality was independently graded by two radiologists. Results: Mean vascular attenuation exceeded predefined diagnostic thresholds in all territories (pulmonary 546.7 ± 237.8 HU [95% CI, 490.4–603.0]; coronary 438.8 ± 113.9 HU [95% CI, 411.9–465.8]; aortic 604.3 ± 190.9 HU [95% CI, 559.2–649.5]). Diagnostic interpretability was achieved in all three territories in every technically analyzable examination without repeat contrast-enhanced imaging. Median subjective image-quality scores were 5 (IQR, 4–5) for pulmonary, 4.5 (IQR, 4–5) for coronary, and 4 (IQR, 4–5) for aortic phases; interobserver agreement was good to excellent. Mean total DLP was 461.5 ± 122.5 mGy·cm. Conclusions: A sequential physiology-based TRO-CTA strategy is technically feasible in a tertiary emergency setting and provides consistent tri-territory enhancement. Because this was a single-arm technical validation study, prospective comparative and outcome-based studies are required to confirm its clinical impact. Full article

Background: Nutritional therapy is central in the management of chronic kidney disease (CKD) and cancer, yet these conditions impose partially conflicting requirements. The 2024 KDIGO guideline recommends a controlled protein intake (~0.8 g/kg/day) to reduce metabolic burden in non-dialysis CKD patients, whereas the ESPEN (European Society for Clinical Nutrition and Metabolism) guidelines support higher protein intake (≥1.0–1.5 g/kg/day) to prevent cancer-related malnutrition. Evidence guiding patients affected by both conditions is limited. We evaluated the effects of a Mediterranean-like controlled protein diet in onconephrological patients compared with CKD controls. Methods: In this retrospective study, 358 CKD patients (183 onconephrological, 175 controls) were followed at a tertiary center (2017–2024). Patients received a protein-controlled diet (0.6–1.0 g/kg/day) tailored to comorbidities and nutritional status. Nutritional assessment included bioelectrical impedance analysis and anthropometry. Renal function was evaluated using creatinine and cystatin C, and measured GFR by iohexol clearance at baseline and 12 months. Results: Baseline body composition was comparable between groups. After intervention, serum urea significantly decreased in both groups, without a decline in measured or estimated GFR. Fat mass and central adiposity indices were reduced, while lean mass and phase angle remained stable. No evidence of protein–energy wasting or catabolic activation emerged. Longitudinal analyses showed no significant time × cancer interaction for renal function or most bioimpedance-derived body composition parameters. However, at extended follow-up, arm circumference and tricipital skinfold thickness showed significant time × cancer interactions, suggesting different longer-term peripheral anthropometric trajectories according to cancer status. Conclusions: In this retrospective real-world cohort, structured nephro-nutritional management with an individualized Mediterranean-like controlled protein prescription was associated with preserved renal function and no evidence of overt nutritional deterioration in onconephrological patients. These findings support the feasibility and apparent safety of this approach in selected patients, while highlighting the need for prospective studies with objective dietary adherence assessment and longer-term evaluation of cancer-related anthropometric trajectories. Full article