Search Results (141)

The COVID-19 pandemic placed prolonged, multi-year demands on the systems supporting frontline workers in healthcare, public safety, and education. In response, approximately 150 licensed behavioral-health professionals and credentialed educators, trained in Psychological First Aid (PFA), built and staffed the Maine FrontLine WarmLine (MFLWL) as unpaid Volunteers from 21 March 2020 through 31 May 2021 and began fielding calls in April 2020, contributing approximately 33,000 h of service. Although the MFLWL fielded 100 calls in aggregate, engagement persisted and expanded into Community Outreach, reaching approximately 250 frontline workers. To understand that paradox, this narrative case study analyzed two waves of open-ended Volunteer surveys (n = 22; n = 20) using consensus-based thematic analysis. Four themes emerged: a specific COVID-19 frontline focus; personal and professional Calling; an intentionally cultivated Culture of self-care and relational support; and stakeholder relationships marked by experienced systemic betrayal and moral injury. Low call volume, rather than eroding engagement, appears to have activated Volunteers’ sense of Calling, converting frustrated readiness into new capability and new avenues of service. From these findings, we derive Emerging Volunteer Engagement (EVE), a values-and-process framework situated within Disaster Ecology that positions Volunteers as principal drivers of disaster response rather than interchangeable resources, with implications for Volunteer organization, support, and liability policy in future disasters. Full article

This paper examines the relationship among gold production, terrorist attacks, FDI, trade openness, financial assistance, World Bank aid, and economic growth in Burkina Faso over the period of 1975–2024. To account for structural shifts and nonlinear dynamics, the analysis employs the FBARDL model together with Fourier Granger causality tests. To check the robustness of the results, the FBARDL estimates were compared with those obtained from the conventional ARDL, ARDL with structural break dummies, and OLS models. In addition, the BDS and Fourier-NL tests were performed on the residuals to assess neglected nonlinear dynamics and remaining structural breaks, while the Fourier F test was employed to verify the significance of the Fourier approximation. Finally, the Fourier Granger causality test was re-estimated using alternative lag lengths to confirm the robustness of the causality. The empirical results revealed contrasting effects of gold production and terrorism on economic growth in Burkina Faso. Gold production exerts a positive and economically meaningful effect in both the long and short run: a 1% increase in gold production increases economic growth by approximately 0.894% in the long run and 0.56% in the short run. By contrast, terrorism significantly undermined long-run economic growth, with a 1% increase in terrorist activity reducing economic growth by approximately 0.45%. The causality analysis further identified unidirectional causality from gold production to terrorism and trade openness, from trade openness and FDI to terrorism, and from terrorism to IBRD/IDA assistance. Bidirectional causality is found between FDI and trade openness, economic growth and FDI, economic growth and terrorism, FDI and gold production, economic growth and trade openness, and trade openness and financial assistance. Taken together, these results revealed a resource–security paradox. Gold production generates a clear resource blessing effect in terms of economic growth, but terrorism indicated that resource expansion may simultaneously intensify conflict-related vulnerabilities. Moreover, the growth benefits generated by gold production do not necessarily translate into broader and more inclusive development. The results therefore suggest that resource blessing in economic growth can coexist with resource curse dynamics in economic development. The policy implications emphasize strengthening resource governance and security institutions while channeling mining revenues toward productive investment and inclusive development. Such measures are essential for transforming gold-driven growth into sustainable development while mitigating the security risks associated with resource dependence. The results therefore revealed a sustainability paradox in which resource wealth generates economic benefits but also increases security and development vulnerabilities. The policy implications emphasized strengthening resource governance and security institutions and improving the allocation of mining revenues toward productive investment and inclusive development. Such policies are essential for transforming gold wealth into sustainable economic development while limiting the conflict-related risks associated with resource dependence. Full article

The Vietnamese textile and garment industry faces a critical sustainability paradox under the impending Carbon Border Adjustment Mechanism (CBAM). Firms are pressured to maintain high-volume export growth while aggressively minimizing carbon and resource intensity. To empirically resolve this tension, this study develops a novel three-phase benchmarking framework that integrates the Best–Worst Method (BWM), VIKOR, and Super-Efficiency Slacks-Based Measure (Super-SBM) under Variable Returns to Scale. Applied to 12 listed enterprises using 2024 fiscal data, the methodology first identifies Energy Intensity as the paramount strategic priority via the BWM. Next, VIKOR mathematically compresses six heterogeneous environmental, social, and governance (ESG) criteria into a single composite index, thereby eliminating standard Data Envelopment Analysis dimensionality constraints. The Phase 3 Super-SBM results reveal profound sector heterogeneity. The macro-scale giant VGT defines the absolute efficiency frontier with an unprecedented score of 18.6729 and zero operational slack. However, the λ reference matrix identifies mid-cap operators such as Tien Son Thanh Hoa and Binh Duong Garment as highly replicable, agile benchmarks for the broader industry. Crucially, the non-radial projection analysis uncovers hidden structural vulnerabilities. The data show that while certain firms possess massive operational buffers, others operate on the absolute edge of the efficiency frontier, leaving them dangerously exposed to impending carbon-taxation shocks. Furthermore, the model identifies critical instances of ESG decoupling in which green investments fail to yield proportional increases in export revenues. These findings suggest that addressing the sustainability paradox requires targeted structural interventions informed by diagnostic benchmarking. Policymakers and corporate executives must integrate open innovation frameworks and systematic problem-solving methodologies to structurally decouple economic output from fossil-fuel energy dependence and outdated labor-arbitrage models. Full article

Retrieval-augmented generation has emerged as a core technological paradigm for addressing the bottlenecks of hallucinations and knowledge lag in large language models. However, many existing reviews focus on a single technical branch or vertical application scenario, making only scattered references to hardware, evaluation methods, and cross-industry empirical evidence, and lacking a systematic, end-to-end integration. This paper conducts research based on a total of 115 papers, comprising foundational literature from 1998–2019 and core RAG literature from 2020–2026, systematically cataloging end-to-end technologies and supporting solutions, establishing a quantitative hardware comparison table and comparing 11 categories of open-source and commercial APIs, constructing a two-tier, four-level standardized evaluation framework, and compiling empirical evidence and implementation challenges across eight industries from 2024 to 2026. Based on this, the paper identifies four major structural contradictions—the retrieval–creation trade-off, the geometric–semantic misalignment as a symmetry problem between representation space and semantic structure, the autonomy–reliability paradox, and evaluation blind spots—as a unified analytical framework for the five major technological strands. Finally, this paper proposes four research directions for practical implementation—differentiable joint optimization, hybrid geometric space learning, interpretable causal reasoning, and multidimensional diagnostic evaluation—providing a systematic reference for both theoretical research on RAG and its deployment in the private sector. Full article

The logarithmic law of the wall is a foundational element in turbulence modeling. Its classical derivation, rooted in Prandtl’s mixing-length theory, is predicated on the existence of a constant shear stress layer. This paper demonstrates that this foundational assumption is not strictly satisfied for two-dimensional, uniform open-channel flows, where the Reynolds shear stress profile exhibits a distinct peak near the bed and never forms a true constant stress zone. We present a novel mechanistic derivation that circumvents this inconsistency. By reframing the bed shear stress as the time-averaged momentum flux from discrete, wall-coherent eddy impacts, we recover the log law through a mechanistic framework. Our model starts from the physical definition of the Reynolds stress at the bed, employs kinematic scaling for the velocity fluctuations, and incorporates the geometric constraint of eddy size. This approach does not require a constant stress layer and provides a more physically defensible explanation for the emergence and robustness of the log-law, directly linking it to the underlying structure of wall turbulence. The derivation resolves the long-standing paradox between the theory’s assumption and the empirical reality in open channel flows. Full article

The mechanistic understanding of biogeochemical dynamics in the Gulf of Guinea (GoG) has historically been hindered by persistent cloud cover and reliance on static geographic boundaries. In this study, we analysed a 20-year (2003–2022) satellite-derived chlorophyll-a (Chl-a) dataset to overcome these observational limitations through a three-part spatial and machine-learning framework. First, the Data Interpolating Empirical Orthogonal Functions (DINEOF) algorithm reconstructed a gap-free climatology, demonstrating robustness under extreme simulated cloud cover (R² = 0.884). Second, a Fuzzy C-Means (FCM) clustering algorithm objectively partitioned the basin into three dynamic, physically driven bioregions: an oligotrophic gyre, river plumes, and an upwelling mega-cluster. Third, we applied an explainable Random Forest framework, supported by SHapley Additive exPlanations (SHAP), to identify the main physical and biogeochemical predictors associated with coastal Chl-a variability using hindcast nutrients and a strict chronological split (training: 2003–2018; test: 2019–2022). The models produced conservative but meaningful independent test-period performance across coastal zones, with R²_log values from 0.437 to 0.595. Rather than revealing a new ecological paradox, the framework provides a basin-specific interpretation of a globally documented pattern: offshore oligotrophication alongside localized coastal enrichment. The open ocean and transition/upwelling sectors show negative Chl-a tendencies consistent with sea surface warming, enhanced stratification, and reduced upward nutrient supply. Conversely, coastal ecosystems are structured by local hydrological and wind-driven forcings that modulate the regional climate signal. In the Congo plume, Chl-a variability is primarily structured by haline plume dynamics and secondary nutrient constraints, whereas the Niger plume reflects coupled mixed-layer and terrigenous nutrient controls. These findings establish a spatially objective typology of the GoG, providing a regional reference framework for future high-resolution missions, monitoring, and coupled physical–biogeochemical modelling. Full article

Cellular senescence plays a complex and crucial dual role in ovarian cancer treatment: it serves as both an important tumor suppression mechanism and a potential driver of drug resistance and recurrence. This review systematically examines the intricate regulatory network of cellular senescence, encompassing multiple pathways including telomere dysfunction, DNA damage response, epigenetic remodeling, hormone signaling, and metabolic reprogramming. Studies have demonstrated that core therapeutic modalities, such as platinum-based chemotherapy, PARP inhibitors, and CDK4/6 inhibitors, can exert anti-tumor effects by inducing cellular senescence; however, their efficacy is significantly influenced by the senescence-associated secretory phenotype (SASP). Specific SASP components can activate immune surveillance, whereas others promote tumor progression, acquisition of stem cell-like characteristics, and therapeutic resistance. It is this “anti-tumor versus pro-tumor” paradox that renders senescent cells a critical variable determining treatment outcomes. In light of this, emerging strategies aim to precisely modulate the senescence process, including the use of epigenetic drugs to induce senescence, targeting metabolic vulnerabilities to eliminate senescent cells, and intervening in deleterious SASP to improve the tumor microenvironment. Integrating such strategies with conventional therapies holds promise for overcoming the resistance bottleneck in ovarian cancer and opening new avenues for improving patient prognosis. Full article

This study investigates the dual pathways of foreign language enjoyment (FLE) among left-behind children (LBC), a population constituting more than 20% of China’s child population and largely under investigated in the second-language learning context; the focus of this study is on the unique and joint contributions of FLE to learning engagement (LE) and learning burnout (LB) in determining academic achievement (AA). Our results confirm that FLE and LE are positively correlated with EFL achievement, while LB shows a significant negative correlation with EFL achievement. However, they also reveal counterintuitive positive correlations between FLE and LB and between LE and LB among LBC—contradicting prior findings from the general population. More importantly, our path analysis reveals a blocked positive association and an opened negative association: while FLE is significantly associated with LE, LE is not significantly linked to achievement; conversely, FLE is positively connected to LB, which is negatively associated with achievement. This “paradox of enjoyment” reveals that FLE acts as a double-edged sword for Chinese LBC, challenging the unidirectional positive view of FLE in second-language learning and demonstrating that positive emotions alone cannot drive sustainable EFL learning success within this vulnerable group. Our findings highlight the unique socioemotional complexities of LBC, underscoring that fostering enjoyment alone might be insufficient without targeted interventions to alleviate burnout and translate engagement into actual success, and offer valuable insights for educators and policy-makers aiming to improve foreign language education among LBC. Full article

Large language models are increasingly deployed as natural-language interfaces to clinical databases, yet their evaluation has focused almost exclusively on query correctness rather than access minimality. Data-protection frameworks such as HIPAA §164.502(b) and the GDPR data-minimisation principle require that personal data be accessed only to the extent necessary for the immediate purpose. This paper presents the first empirical audit of open-weight LLMs on this access-scope dimension, using the EHRSQL 2024 benchmark over MIMIC-IV. We measure deviations from minimum-necessary access via three static metrics computable without executing queries: Sensitive Column Exposure (SCE), Table Over-Join Rate (TOJ), and Aggregate Identifier Exposure (AIE). Unlike prior work on adversarial attacks, we study default model behaviour under ordinary, benign queries—the over-reach we document requires no attacker and is present from the first interaction. Among twelve open-weight models, a non-trivial fraction fail a basic SQL-generation viability threshold; among nine viable models, SQL-specialised training paradoxically increases over-reach while domain-adapted medical variants achieve the lowest exposure. Schema redaction largely eliminates column-level exposure but increases table-level over-reach for most models. Random in-context demonstrations produce statistically significant over-reach regressions in specific models; BM25-based retrieval resolves most of these failures, though a residual aggregate-identifier exposure risk persists for one model family. Full article

Background: In low-flow, low-gradient aortic stenosis (LFLG AS), restricted aortic valve opening may represent either fixed valvular obstruction or flow-dependent incomplete leaflet opening due to reduced forward flow. Aortic stenosis (AS) and transthyretin cardiac amyloidosis (ATTR-CM) may coexist, making it difficult to distinguish myocardial disease–driven low-flow physiology from clinically relevant valvular obstruction. Case Presentation: An 88-year-old man presented with decompensated heart failure and paradoxical LFLG AS. Dobutamine stress echocardiography (DSE) failed to restore normal flow, and the calculated aortic valve area remained within the severe range despite stress. Computed tomography showed a low aortic valve calcium score (AVCS) of 313 Agatston units, leaving true-severe versus pseudo-severe AS indeterminate. Further evaluation confirmed wild-type ATTR-CM. Because the contribution of AS to heart failure was uncertain, the patient was initially managed with optimized heart failure therapy. Approximately two years later, he was readmitted with recurrent acute decompensated heart failure, severe left ventricular systolic dysfunction, dobutamine dependency, end-organ congestion, and a classical LFLG AS phenotype. Although AS severity remained indeterminate, a clinically relevant valvular afterload component could not be excluded. At that time, tafamidis was not immediately available because of local access limitations. Because left ventricular assist device implantation and heart transplantation were not feasible and surgical aortic valve replacement carried prohibitive risk, transcatheter aortic valve implantation (TAVI) was performed after discussion by the Heart Team. Left ventricular ejection fraction improved early after TAVI, from 19.9% before the procedure to 29.4% at 3 days and 44.1% at 35 days. At 1-year follow-up, left ventricular ejection fraction remained improved at 51%, and more than two years after TAVI, the patient continues regular outpatient follow-up without recurrent heart failure hospitalization. Conclusions: In ATTR-CM with LFLG AS, DSE and AVCS may not definitively determine AS severity. Carefully selected TAVI, combined with ATTR-directed and optimized heart failure therapy, may be associated with early left ventricular functional recovery and sustained clinical improvement. Full article

Original Equipment Manufacturers (OEMs) frequently face a “digitalization paradox” in which injecting startup innovations directly into zero-tolerance production environments may disrupt core operations. Using a 15-year longitudinal dataset, executive survey evidence, CEO interviews, organizational observations, and micro-level AI execution logs from a leading hardware OEM, this study examines the structural relationships through which asset-heavy firms may internalize open innovation while protecting operational stability. We contribute to the Dynamic Capabilities theory by conceptualizing the Innovation Translation Interface, operationalized as a corporate accelerator, as a structural buffer that helps isolate and absorb open-innovation friction. Furthermore, we introduce the concept of a domain-grounded Digital Knowledge Infrastructure. By training internal AI on accumulated operational failures and iterative engineering records, firms’ practices are associated with enhanced knowledge externalization and reduced reliance on seniority-based knowledge transfer. The findings suggest that these structural configurations are positively associated with the capability development of Systematized Innovation Capability (SIC), offering an exploratory framework for legacy manufacturers seeking to balance open innovation, AI-enabled learning, and production reliability. Full article

Background/Objectives: Omalizumab is an effective treatment for antihistamine-refractory chronic urticaria. However, post-injection urticaria exacerbation and related adverse reactions remain inconsistently reported. This scoping review mapped evidence on clinical presentation, timing, mechanisms, management strategies, rechallenge outcomes, treatment discontinuation, and patient outcomes associated with these reactions. Methods: The review followed the Joanna Briggs Institute methodology and was registered prospectively in INPLASY (INPLASY202650060). PubMed, Scopus, and the Directory of Open Access Journals were searched from inception to April 2026. Eligible studies included English-language case reports, case series, observational studies, cohort studies, registry or pharmacovigilance studies, postmarketing surveillance studies, and clinical trials reporting urticaria-related or hypersensitivity-type adverse reactions during omalizumab treatment for chronic urticaria. Data were charted descriptively and synthesized narratively. Results: Seventeen studies published between 2015 and 2026 included 2790 patients with chronic urticaria, 60 of whom experienced urticaria-related adverse reactions, corresponding to a mapped proportion of 2.2%. Clinical phenotypes included transient urticaria exacerbation, urticaria flare or worsening, localized urticarial plaques at the injection area, angioedema, anaphylaxis or anaphylaxis-like reactions, and serum sickness-like reactions. Reactions occurred within minutes to several hours, within 24 h, several days, or up to 1 week after injection or dose escalation. Reactions occurred following the first dose, repeated doses, and dose escalation. Proposed mechanisms included delayed hypersensitivity, possible IgE-mediated delayed-onset anaphylaxis, serum sickness-like reaction, paradoxical worsening, infection-associated flare, excipient-related reactions, and severe underlying CSU exacerbation mimicking anaphylaxis. Management strategies ranged from observation or symptomatic treatment to discontinuation of omalizumab and systemic interventions. Conclusions: Omalizumab-associated urticaria-related adverse reactions were infrequently reported across the mapped evidence but were clinically heterogeneous. Standardized definitions and detailed case reporting are needed to clarify causality, recurrence risk, rechallenge safety, and long-term outcomes. Full article

Purpose/Background: Small and medium-sized enterprises (SMEs) that deploy Enterprise Resource Planning (ERP) systems face a persistent paradox: although ERP centralises organisational data, frontline users frequently lack the technical expertise to navigate complex menu structures, preventing efficient information retrieval for decision-making. This study presents a preliminary Research and Development (R&D) effort to design, build, and qualitatively evaluate a prototype intelligent question-answering system that connects to Odoo ERP through application programming interfaces (APIs) via Retrieval-Augmented Generation (RAG), enabling natural-language access to real SME business data. Methods: A single-organisation R&D case study was conducted at an SME in Khon Kaen Province, Thailand. The development cycle comprised problem analysis and requirement specification, system architecture design, prototype construction, integration and deployment, iterative testing and refinement, and multidimensional evaluation. The prototype was implemented with Chainlit (conversational interface), FastAPI (orchestration and tool-calling layer), and Odoo XML-RPC/JSON-RPC APIs (structured data retrieval). A fixed set of 20 test questions spanning four complexity levels (easy, moderate, complex, out-of-scope) was evaluated by three automated tools (OpenAI Evals, DeepEval, Ragas), by real-task verification against live ERP data, by five domain experts using 5-point Likert-scale questionnaires, and by three end users from the case-study organisation, who additionally completed the System Usability Scale (SUS). Given the very small expert and user samples, all human evaluation results are reported descriptively as preliminary, exploratory indicators rather than as statistically generalisable measures. Results: Automated evaluation achieved indicative pass rates of 95.00% (OpenAI Evals, 19/20), 90.00% (Ragas, 18/20), and 85.00% (DeepEval, 17/20). Descriptive expert feedback (n = 5) yielded an overall mean of 3.82 (high level), and descriptive end-user feedback (n = 3) yielded an overall satisfaction mean of 4.33 (highest level). The SUS score was 66.67/100, sitting at the boundary between ‘OK’ and ‘Good’ and revealing a divergence between high stated satisfaction and lower confidence in independent system use (item 9, raw mean = 2.33) and a stronger perceived need for expert assistance (item 4, raw mean = 2.67). These results are interpreted as preliminary diagnostic signals for further development rather than as confirmatory evidence. Conclusions: This preliminary R&D study suggests that a RAG-based ERP chatbot can meaningfully simplify ERP data access for SME users, while exposing persistent gaps in multi-step reasoning, user confidence, and data privacy boundaries that must be addressed in subsequent development cycles. The SUS pattern, in particular, suggests a ‘novelty effect’ in which users are enthusiastic about the natural-language interface yet remain anxious about correctness and stability during real tasks. Originality/Value: This work contributes a transparent, replicable preliminary R&D blueprint that combines (i) live API-mediated RAG over structured ERP data, (ii) a complementary multi-tool automated evaluation set (OpenAI Evals + DeepEval + Ragas), (iii) descriptive expert and end-user feedback, and (iv) SUS-based usability assessment, all documented for a single Thai SME using Odoo 18. The study explicitly positions itself as an early step toward larger, multi-site, and on-premise deployments of trustworthy ERP-integrated conversational agents. Full article

Metal additive manufacturing (AM) enables components with high geometric complexity and functional integration; however, these advantages are realized only when topology optimization (TO) aligns with AM-specific constraints. This review examines TO strategies for metal AM, with emphasis on laser powder bed fusion (LPBF) as the most established industrial route. It categorizes and assesses density-based methods, level-set approaches, and lattice or architected-material optimization, focusing on how each captures manufacturability (overhang limits, minimum feature size, surface roughness), physics (residual stress, thermal distortion), and AM-induced anisotropy. It further distinguishes algorithms that embed constraints directly into the TO loop from workflows that rely on post-optimization repair. It discusses implications for robustness and transferability across machines and alloys. Experimental and numerical evidence for titanium alloys, aluminum alloys, nickel-based superalloys, and stainless steels is synthesized to relate design decisions and processing conditions to reported gains in stiffness-to-weight ratio, strength, fatigue performance, and buy-to-fly efficiency. Persistent gaps include validation under realistic load spectra, uncertainty quantification, standardized benchmarks, microstructure-informed objectives, and sustainability metrics. Beyond synthesizing existing TO formulations and constraints, this review contributes a criteria-based decision structure linking TO method selection, constraint strategy, and process-physics coupling and identifies four inherent paradoxes defining the field’s open challenges. Full article

Myocardial ischemia–reperfusion injury (MIRI) represents a major contributor to morbidity and mortality in patients undergoing reperfusion therapy after acute myocardial infarction. Although timely restoration of coronary blood flow is essential for myocardial salvage, reperfusion paradoxically initiates a complex cascade of molecular and cellular events that may aggravate myocardial injury. Oxidative stress is considered one of the central mechanisms underlying MIRI, primarily through excessive production of reactive oxygen species (ROS) and reactive nitrogen species (RNS), leading to mitochondrial dysfunction, calcium overload, endothelial injury, inflammatory activation, and cardiomyocyte death. This review summarizes the current understanding of the pathophysiological mechanisms involved in oxidative stress-mediated reperfusion injury, with emphasis on mitochondrial permeability transition pore opening, inflammasome activation, cytokine release, neutrophil extracellular trap formation, macrophage polarization, and interconnected cell death pathways including PANoptosis. Emerging evidence regarding immunometabolic regulation and epigenetic modulation in MIRI is also discussed. In addition, current pharmacological and non-pharmacological cardioprotective strategies targeting oxidative stress, mitochondrial dysfunction, and inflammatory signaling are reviewed, highlighting both promising experimental findings and the persistent challenges in clinical translation. A deeper understanding of the molecular interplay between oxidative stress and inflammatory pathways may facilitate the development of integrated therapeutic approaches aimed at improving myocardial recovery and long-term cardiovascular outcomes following reperfusion therapy. Full article