Search Results (1,420)

Coal-fired power plants equipped with selective catalytic reduction (SCR) and wet flue-gas desulfurization (WFGD) can co-control mercury, but performance is limited by incomplete upstream Hg⁰ oxidation and downstream re-emission. This study evaluated a 660 MW unit using gas-, liquid-, and solid-phase measurements and coordinated single-factor and coupled operating tests. Under baseline conditions, SCR Hg⁰ oxidation was 31.66%, WFGD Hg²⁺ capture was 73.79%, and net mercury removal was 31.08%, with a stack Hg^T concentration of 4.70 µg/Nm³. Coupled optimization increased SCR Hg⁰ oxidation to 69.76% and WFGD Hg²⁺ capture to 96.05%, reduced the re-emission index from 0.596 to 0.250, and raised net removal to 70.83%. SCR inlet temperature, equivalent space velocity, and catalyst health were the dominant upstream factors, while S(IV), oxidation–reduction potential (ORP), slurry pH, and oxidation air supply governed downstream stabilization. A practical operating window was identified near 340 °C, with a normalized stoichiometric ratio (NSR) of approximately 1.0, high ammonia injection uniformity, pH of 5.5–6.0, ORP of approximately 200 mV, and S(IV) of approximately 2 mmol/L. The results show that coordinated operation of existing SCR–WFGD equipment can substantially reduce stack mercury without dedicated mercury-control hardware, provided that NH₃ slip, SO₃-related risk, catalyst condition, and absorber stability are simultaneously constrained. Full article

Since heavy clutter seriously restricts the ability of radar to detect targets, it is significant to build the target detector under heavy clutter. For practical situations without the secondary data or prior knowledge of target and clutter, this paper proposes a polarization-space-time detector. First, a general radar model is constructed for multiple pulses, multiple arrays, and multiple polarizations. Based on the theory of ternary hypothesis, the secondary data free (SDF) GLRT detector is proposed, which can maintain the constant false alarm probability (CFAR) in inhomogeneous clutter. Then, this paper proposes a matrix transform operator and an adaptive detection method using sliding window. These two approaches do not need to know the steering vector of radar and the noncentral parameter of clutter in advance, so the SDF-GLRT detector can adapt to different application scenarios. In addition, this paper optimizes the polarization waveform of the radar system by constructing a projection matrix. This method yields closed-form solutions of the optimal polarization and worst polarization, rather than relying on numerical solution. Finally, the performances of the SDF-GLRT detector and three other detectors are compared by simulated and real data. The proposed SDF-GLRT maintains $P_{\mathrm{FA}}$ of $5.4\times {10}^{-3}$ and $2.6\times {10}^{-3}$ on two IPIX datasets (#54 and #310) at a design $P_{\mathrm{FA}}={10}^{-3}$, whereas the other detectors deviate to $0.0249$–$0.7405$. The optimal polarization yields a detection-probability gain of more than $0.22$ over the worst polarization at $\mathrm{SCR}=0$ dB. Full article

The proliferation of inverter-based resources (IBRs) and energy storage systems in power grids has led to a decline in the short-circuit ratio (SCR) and reduced fault current magnitudes, compromising the reliability of conventional overcurrent relays (OCRs) and creating protection blind zones. To resolve these vulnerabilities, this paper proposes an electromagnetic repulsion-based Superconducting Fault Current-Limiting Circuit Breaker (SFCL-CB) utilizing a flux-lock type mechanism. Unlike protection schemes that rely on secondary accessories such as current and potential transformers which introduce computational delays, the proposed SFCL-CB utilizes a driving force that scales with the square of the current gradient ((di/dt)²). This characteristic allows the device to distinguish low-magnitude fault currents from transient load growths. Through duality-based modeling and parametric simulations in PSCAD/EMTDC, the structural and electrical design configurations—including the coil turns (N₁, N₂) and the superconducting quench resistance (R_SC)—were optimized. The simulation results verify that the proposed SFCL-CB substantially reduces the OCR blind zone, securing fault clearance within a maximum of 0.131 s in the regions cleared under low SCR and high-fault-resistance conditions, while achieving mechanical separation in 0.0048 s under robust power system. This SFCL-CB offers an alternative to enhance the protection reliability and operational stability of distribution power system. Full article

Global supply chains face increasingly frequent disruptions, which require organizations to strengthen supply chain resilience (SCR). Drawing on Organizational Information Processing Theory (OIPT), this study examines how digital transformation and organizational learning combine to enhance SCR. Using data from 61 Chinese high-technology firms, fuzzy-set qualitative comparative analysis (fsQCA) identifies two pathways to high SCR. The first is an ambidextrous learning-driven pathway. Exploitative and exploratory learning jointly help firms refine existing routines and develop adaptive responses to disruption-induced uncertainty. The second is a digitally driven pathway. Digital strategic planning and digital ecosystem coordination help firms structure disruption-related information and coordinate responses across supply chain partners. The configurations for non-high SCR further show that exploratory learning is important for interpreting unfamiliar signals and generating adaptive responses. These findings extend OIPT by showing that SCR emerges from distinct forms of fit between information processing requirements and organizational capabilities. They therefore provide a configurational explanation of resilience formation under uncertainty. Full article

Climate risk increasingly threatens agricultural supply chain stability. Green finance (GF) and environmental regulation (ER) are two key policy instruments intended to counter this risk, yet their effectiveness in fostering supply chain resilience (SCR) remains ambiguous. Using panel data from Chinese A-share-listed agricultural firms (2010–2024), this study examines the average and conditional associations of GF, ER, and climate risk awareness (CRA) with SCR via a two-way fixed-effects model, supplemented by instrumental variables, quantile regressions, heterogeneity tests, and interaction models. Text-based CRA is positively associated with SCR. Contemporaneous physical climate risk derived from meteorological observations shows no robust association, whereas its one-period-lagged, economic-scale-adjusted counterpart is significantly negative. Neither GF nor ER exhibits an unconditional linear relationship with SCR, and CRA substantially attenuates the marginal effect of GF. Financing constraints, supply chain concentration, factor allocation efficiency, and innovation intensity do not form stable indirect channels. Taken together, the findings suggest that the relationship between GF, ER, and agricultural SCR does not operate through a single transmission pathway, but may instead be shaped by whether firm-level risk sensing, resource mobilization, operational coordination, and structural reconfiguration form an effective capability configuration. Full article

Urban air pollution remains a major public health concern, with road traffic representing one of the dominant sources of particulate matter and volatile organic compounds in growing cities. This study evaluates the level of chemical air pollution in Alba-Iulia municipality (Romania) through two measurement campaigns (May 2025 and October 2025), carried out at 26 and 19 points, respectively, selected based on traffic intensity and population vulnerability criteria (schools, kindergartens, hospitals, and the food market). Measurements targeted PM_2.5, PM₁₀, total volatile organic compounds (TVOC) and formaldehyde (HCHO), as well as carbon dioxide (CO₂), correlated with road traffic intensity. Statistical analysis revealed significant differences between the two seasons for PM_2.5, PM₁₀, and CO₂ (p < 0.01), as well as a strong correlation between particulate matter concentrations and vehicle counts (r = 0.60–0.95), consistent with road traffic being an important local contributor to particulate matter, though correlation alone cannot establish source dominance in a strict causal sense. A multiple regression controlling for both traffic and season explained over 73% of the variance in PM_2.5 and PM₁₀ and showed that traffic and season each contribute independently to particulate levels. Both mean PM_2.5 and PM₁₀ exceeded WHO and EU limit values in both campaigns, and the low-cost sensor over-read absolute concentrations by roughly 2–4× relative to the official monitoring network, so absolute values should be treated as orientative. Despite this bias, the consistent spatial and seasonal patterns show that portable low-cost sensors can reliably rank exposure hotspots and support the targeting of traffic-mitigation measures, such as selective catalytic reduction (SCR) systems, in medium-sized cities that lack dense reference monitoring networks. Full article

Although the weak-grid stability of grid-following inverters has been widely studied, traditional SCR-based assessment mainly describes grid strength and does not directly quantify the minimum SCR required for stable operation under a specified active-power command. This paper uses a critical-SCR-oriented operating-boundary evaluation to compare the control-dependent dynamic stability requirement with the physical steady-state feasibility limit. It proposes a channel-specific impedance-reshaping extension that retains the PLL-related q-q and d-q compensation paths and adds a voltage-loop-related q-d compensation path. The added path reduces the control-induced dynamic critical SCR, thereby allowing stable operation at lower SCR than with the original control structure. Firstly, the steady-state critical SCR is derived from the steady-state power-transfer relation under a specified active-power command to define the physical feasibility lower bound, and the dynamic critical SCR is identified using a scanning procedure based on the generalized Nyquist criterion. The resulting control-induced SCR gap quantifies the additional grid-strength requirement introduced by the control dynamics. Secondly, a simplified d-q admittance representation is used to relate established PLL-related and voltage-loop-related coupling effects to the corresponding compensation paths. Thirdly, the proposed channel-specific impedance-reshaping design is used to mitigate these effects while retaining the selected voltage-loop bandwidth, and an anti-drift correction is further introduced to improve implementation robustness. Frequency-domain analysis and time-domain simulations validate the dynamic critical-SCR evaluation, while hardware-in-the-loop experiments demonstrate the real-time operation of the proposed controller. The results show that it moves the dynamic critical-SCR boundary close to the steady-state physical boundary and improves the weak-grid stability margin. The hardware-in-the-loop results further confirm bounded operation under SCR and frequency steps. Full article

This study evaluates the cost competitiveness of the Northern Sea Route (NSR) relative to the Suez Canal Route (SCR) for a representative Asia–Europe voyage, using the Shanghai–Rotterdam route as the reference case. A scenario-conditioned stochastic Monte Carlo framework is developed to estimate the probability that the NSR incremental voyage cost is lower than that of the SCR, $P_{NSR}$. The analysis identifies the probabilistic threshold conditions under which the NSR can become cost-competitive under seasonal and geopolitical uncertainty. The model decomposes insurance-related costs into route-specific risk components and jointly incorporates seasonal conditions, Arctic geopolitical risk, and Red Sea war-risk exposure under five scenarios. The results show that $P_{NSR}$ remains below 50% in all scenarios, indicating that the NSR does not achieve cost competitiveness in the majority of simulations under the assumed cost structure. The summer-current base case yields $P_{NSR}$ = 16.6%, while geopolitical easing increases it to 23.5%. In contrast, the winter-current scenario reduces $P_{NSR}$ to 1.4%, confirming a strong seasonal constraint on NSR viability. Single-variable sensitivity analysis identifies icebreaker fees and Arctic navigation insurance premiums as the most influential NSR-side cost variables, whereas SCR war-risk exposure has the largest overall effect by increasing SCR-side costs. Further threshold analysis shows that no single variable within a plausible operating range is sufficient to raise $P_{NSR}$ to 50%. A combined two-variable analysis shows that simultaneous reductions in icebreaker fees and Arctic navigation premiums can bring $P_{NSR}$ close to 50% under less extreme individual parameter values than those required in the single-variable analysis. These findings suggest that NSR competitiveness is structurally constrained and is more likely to depend on coordinated changes in multiple cost components than on a favourable change in any single variable. Full article

Addictive behaviours are associated with substantial neurobiological, psychological, and behavioural impairments. Exercise training has emerged as a potential complementary strategy in addiction treatment; however, the characteristics of exercise interventions and their associated outcomes remain insufficiently characterized. This scoping review (ScR) was conducted according to the Joanna Briggs Institute methodology and reported in accordance with the PRISMA-ScR guidelines. Searches were conducted across three electronic databases for studies published between January 2015 and March 2025. Eligible studies investigated structured exercise training interventions in individuals with substance-related or behavioural addictions. Data were extracted regarding study characteristics, addiction type, exercise modality, FITT parameters, and neurobiological, biochemical, psychological, behavioural, and addiction-related outcomes. Five human intervention studies met the inclusion criteria, all addressing substance-related addictions, including alcohol use disorder, methamphetamine use disorder, and polysubstance dependence. Three studies evaluated acute exercise interventions, whereas two investigated structured exercise programmes lasting 8–12 weeks. Aerobic exercise was the most frequently investigated modality, although combined aerobic and resistance training, yoga, cycling, soccer-based exercise, circuit training, and functional exercise were also identified. Exercise intensity ranged from moderate to vigorous, with substantial variability in frequency, session duration, intervention period, and reporting of progression, supervision, and adherence. Reported outcomes included dopamine-related measures, mood, anxiety, depressive symptoms, self-esteem, affect, and craving. The available evidence suggests potentially relevant effects of exercise across neurobiological, psychological, and addiction-related domains, but the limited number and heterogeneity of studies preclude conclusions regarding the effectiveness of specific exercise prescriptions. The current evidence base on structured exercise training in addictive behaviours remains limited and heterogeneous and is restricted, among the eligible intervention studies identified, to substance-related addictions. Exercise may represent a promising complementary approach, but evidence is insufficient to establish optimal exercise modalities, FITT prescriptions, or sustained clinical benefits. Future research should prioritize adequately powered longitudinal randomized controlled trials, standardized reporting of exercise prescription and adherence, and comprehensive assessment of clinically relevant addiction-related outcomes. Full article

To clarify the role of metal dopants in low-temperature NH₃-SCR of NO, FeMnTiO_x catalysts were synthesized by coprecipitation and separately modified with Ce, Co, or W. The catalysts were evaluated for NO conversion, separate O₂/H₂O switching response and dry-feed time-on-stream stability and characterized by XRD, SEM, N₂ adsorption–desorption, XPS, H₂-TPR and NH₃-TPD. Ce doping at Ce/Mn = 0.3 suppressed TiO₂ crystallization, increased the BET surface area from 136 to 231 m² g⁻¹ and the pore volume from 0.19 to 0.58 cm³ g⁻¹, raised the Mn⁴⁺/Mn³⁺ ratio from 0.70 to 1.25, and increased the medium-strong-acid relative peak area from 555.4 to 1293.2 a.u. FeMnCe_0.3TiO_x maintained at least 90% NO conversion from 140 to 360 °C, gave 75% conversion at 400 °C, and averaged 97.4% during a 40 h dry-feed test at 350 °C. The results show that the superior Ce-modified catalyst arises from the combined regulation of texture, surface redox balance and acidity. Full article

Residual mortar on recycled fine aggregate contains pores and microcracks that weaken mortar strength and resistance to water ingress. This study treated recycled fine aggregate with 5 wt.% KH570 silane and used waste ceramic micropowder, at 4–12% of the total recycled fine aggregate mass, to replace an equal mass of the fraction not exceeding 0.6 mm. At a constant water-to-cement ratio and comparable flowability, compressive strength, flexural strength, 28 d water absorption, and maximum water pressure without visible leakage were evaluated, together with SEM, XRD, and MIP analyses. Mortar strength first increased and then decreased with increasing ceramic micropowder content, whereas water absorption showed the opposite trend. Among the tested replacement levels, SCR8 achieved the most favorable mean performance, with 28 d compressive and flexural strengths of 42.4 and 6.0 MPa, respectively, 38.6% and 25.0% higher than those of the unmodified recycled mortar. Its water absorption decreased by 36.4% to 7.48%, and it sustained 0.6 MPa without visible leakage. Microstructural results indicated fewer local defects, improved interfacial continuity, lower cumulative mercury intrusion, and a shift toward smaller pore throats. These improvements could be associated with combined regulation of aggregate wettability and pore-throat structure. Full article

The transportation sector faces growing supply chain disruptions driven by workforce shortages, digital skills gaps, and weak cultural readiness for risk. Human Resource Management (HRM) offers a credible path toward stronger supply chain resilience (SCR), yet existing decision support tools lack the formal reasoning and auditability that systematic HR risk assessment requires. This paper proposes a Task-Typed Reasoning Module-Enhanced Retrieval-Augmented Generation (RAG) Expert System framework for HR-driven risk assessment in transportation supply chains. The framework employs a six-layer architecture integrating four core components: a Task-Aware RAG layer for knowledge extraction from heterogeneous HR documents, a Task-Routed Evidence Extractor for risk factor identification and source reliability scoring, a Task-Based Reasoning Core applying weighted Mamdani fuzzy inference, and a Task-Guided Synthesis Module using Dempster–Shafer evidential reasoning for risk profiling. Task-Typed Reasoning Modules (TTRMs) organise reasoning into reusable, adaptable units covering Likelihood, Impact, Vulnerability, Mitigation, and Prioritisation, refined through an expert-gated feedback loop. Applied to an illustrative UK transportation logistics case study, the framework ranked HR-driven workforce risks, quantified uncertainty through belief-plausibility intervals, and generated traceable recommendations linked to four HRM-SCR dimensions. As a proof-of-concept demonstration, the framework provides a conceptual foundation for HR risk management in transportation, extending expert system reasoning through adaptive AI to offer mathematically grounded, traceable outputs for practitioners and researchers; empirical validation in live organisational settings remains a necessary next step. By formalising the human dimension of resilience, the framework contributes toward socially, economically, and environmentally sustainable transportation supply chains, aligning HR risk management with the sustainable development objectives examined in this study. Full article

Background/Objectives: Malignant cerebral edema (MCE) is an infrequent but devastating complication of acute ischemic stroke (AIS). Early, reliable identification of patients at risk remains a major clinical challenge. The purpose of this study was to evaluate SCR-U1.8, a single automated imaging biomarker integrating stroke lesion burden and cerebrospinal fluid reserve, for exploratory risk stratification of MCE after AIS. Methods: In this retrospective study, consecutive patients with AIS who underwent diffusion-weighted imaging (DWI) between January 2019 and October 2022 were screened. Stroke lesions were automatically segmented on initial DWI using an ADC threshold of <1.8 × 10⁻³ mm²/s to derive U1.8 lesion volume. Cerebrospinal fluid volume (CSFV) was automatically estimated within the intracranial compartment, and SCR-U1.8 was calculated as U1.8/CSFV. Four low-complexity prediction strategies were evaluated: U1.8 > 82 mL, U1.8 > 145 mL, single-predictor U1.8 logistic regression, and single-predictor SCR-U1.8 logistic regression. Performance was evaluated across 100 repeated stratified patient-level train–test splits. Random undersampling was restricted to the training data, and no synthetic samples were generated. Model performance was assessed by accuracy, sensitivity, specificity, precision, negative predictive value (NPV), F1 score, receiver operating characteristic area under the curve (ROC-AUC), and average precision (AP) as appropriate. Results: A total of 530 patients were included, comprising 198 women and 332 men (mean age, 68 ± 14 years); a total of 12 patients developed MCE. Across 100 repeated stratified train–test splits, SCR-U1.8-LR achieved the highest accuracy (0.990 ± 0.006), precision (0.759 ± 0.150), specificity (0.992 ± 0.005), F1 score (0.806 ± 0.131), ROC-AUC (0.998 ± 0.002), and average precision (0.935 ± 0.062). Compared with the U1.8 > 82 mL threshold, SCR-U1.8-LR achieved significantly higher accuracy, precision, specificity, and F1 score, although sensitivity decreased from 1.000 to 0.900 and NPV decreased slightly from 1.000 to 0.998. Conclusions: SCR-U1.8 may provide a simple and physiologically interpretable measure of stroke lesion burden relative to CSF reserve. The findings remain exploratory because only 12 independent MCE events were available and require external validation. Full article

Background/Objectives: Benchmark performance does not establish that a wrist-wearable stress measure is valid in healthcare workflows. We tested whether binary stress-versus-non-stress performance reflects stress-specific physiology rather than heart-rate (HR) arousal, as well as whether models generalize from wellness-like corpora to a clinical workforce context. Methods: We analyzed three public wrist Empatica E4 corpora: Wearable Stress and Affect Detection (WESAD), Stress-Predict, and a real-world Nurse dataset. An iso-heart-rate (iso-HR) evaluation balanced the HR within subjects before measuring non-cardiac discriminability. We compared a continuous skin conductance response (SCR) count with logistic regression, gradient boosting, four unsupervised domain-adaptation methods, and an accelerometer context-aware variant, under leave-one-subject-out and leave-one-dataset-out evaluation with subject-cluster bootstrap intervals. Results: The single SCR score was statistically indistinguishable from logistic regression in paired cross-corpus tests, and no adaptation method moved a weak corpus into a usable range: across all evaluated models, the transfer area under the receiver operating characteristic curve (AUROC) was approximately 0.90 with WESAD as the target but 0.52–0.57 with Stress-Predict or Nurse. Adding activity context raised the within-corpus AUROC yet lowered cross-corpus transfer, because the movement–stress association reverses across protocols. On Nurse, source-trained models reached AUROC 0.541–0.559 against prevalence 0.796 with poor calibration, and conditioning on movement or on distance to the source distribution removed the residual discrimination. Iso-HR evidence was diagnostic mainly in WESAD. Conclusions: Neither shallow unsupervised adaptation nor wrist activity context established reliable transfer to Nurse, and sparse retrospective labels prevent attributing this solely to physiological non-transfer. Cross-corpus and iso-HR controls, not model complexity, determine what can be concluded for healthcare workflows. Full article

Strawberry is a globally important yet stress-sensitive crop, increasingly threatened by combined abiotic and biotic stresses. Unlike single stresses, combined stresses elicit unique, non-additive responses through complex signaling and gene regulatory networks. This review synthesizes current knowledge on the molecular mechanisms underlying strawberry responses to combined stresses, focusing on signal perception and transduction as well as gene regulation. We examine how combined stresses are perceived by membrane-localized sensors and calcium channels, and how these signals are transduced through MAPK (mitogen-activated protein kinase) cascades, CDPKs (calcium-dependent protein kinases), and hormonal crosstalk involving ABA (abscisic acid), JA (jasmonic acid), and ethylene. At the gene regulation level, we discuss the roles of key transcription factors (WRKY, NAC (NAM, ATAF1, ATAF2 and CUC2), GRAS (GAI-RGA-and-SCR), DREB (Dehydration-Responsive Element-Binding protein), bZIP (basic leucine zipper transcription factor), CAMTA (calmodulin-binding transcription activator), ARF (auxin response factor), and LAV (Leafy Cotyledon2–Abscisic Acid Insensitive3–Val)), transcriptional cascades, epigenetic regulation via DNA methylation, and post-transcriptional (miRNAs such as Fan-miR73) and post-translational (ubiquitination and phosphorylation) control mechanisms. The review also evaluates emerging mitigation strategies informed by these molecular insights, including genomic selection, and explores future directions such as CRISPR (clustered regularly interspaced short palindromic repeats)-based genome editing and multi-omics integration. We conclude that understanding the integrated signaling and gene regulatory networks is essential for developing climate-resilient strawberry cultivars capable of withstanding increasingly complex stress combinations. Full article