Search Results (374)

Metal oxide thin-film transistors (MO TFTs) have drawn wide interest in photodetectors and optoelectronic synaptic devices owing to their wide bandgap, low off-state current, high optical transparency, low-temperature processing, and large-area uniformity. Gate modulation in the TFT structure can tune the channel’s initial state and interfacial electric field, enhancing the tunability of photogenerated carrier transport, defect trapping/release, and interfacial charge regulation. This article reviews the progress of MO TFT photodetectors and optoelectronic synaptic devices, and examines the roles of light absorption, carrier transport, defect-related carrier dynamics, interfacial charge control, and persistent photoconductivity in different device functions. For photodetectors, key goals include broadening the response spectrum, reducing dark current, improving spectral selectivity, and enhancing response stability. For optoelectronic synaptic devices, post-illumination conductance retention and slow relaxation enable memory retention and synaptic weight modulation. Thus, rather than being separate, photodetection and optoelectronic synapses are functional extensions of the MO TFT optoelectronic response under different application targets. This article further discusses the synergy between these two functions in array sensing, visual preprocessing, and intelligent vision systems. Future development requires advances in targeted defect engineering, interface and structure optimization, array uniformity, standardized evaluation, and device–circuit–algorithm co-design for low-power, integrable intelligent vision hardware. Full article

During CO₂ flooding, unfavorable mobility ratios and interlayer heterogeneity can induce preferential flow through high-permeability intervals, leaving central low-permeability intervals insufficiently swept and rich in remaining oil. To address the strong coupling among composite chemical-plugging parameters and the high computational cost of CMG-STARS simulations for individual candidate strategies, this study proposes an adaptive heterogeneous ensemble surrogate-assisted differential-evolution method (AHES-DE). The method integrates radial basis function, inverse-distance weighting, and ridge-linear surrogate models, whose predictions are dynamically weighted according to leave-one-out cross-validation errors. Explorer, Exploiter, and Robust roles are used for global search, local exploitation, and prediction-risk control, respectively, with differential-evolution offspring generation embedded in the Exploiter role. A stratified one-injector–four-producer conceptual model with a 21 × 21 × 6 grid was used to establish a numerical evaluation workflow comprising CO₂ injection, preferential-channel development, composite chemical plugging, and subsequent displacement. Mobile chemical concentration, adsorbed preformed particle gel (PPG) mass density, water-phase resistance factor, oil saturation at a common termination time, and net economic value (NEV) were used to evaluate treatment performance. Under an equal budget of 150 high-fidelity CMG-STARS evaluations per method, the reported single-seed final best-so-far NEVs were 2.45405 × 10⁹ CNY for AHES-DE, 2.44888 × 10⁹ CNY for differential evolution (DE), and 2.44698 × 10⁹ CNY for Latin hypercube sampling (LHS). The layer-resolved responses indicate more pronounced chemical transport, retention, and resistance development in the upper and lower preferential intervals, while the oil saturation in the central low-permeability interval decreased further after treatment, indicating that flow redistribution facilitated remaining-oil mobilization. A realistic geological model was further used to assess the engineering consistency of the identified flow-control mechanism. Full article

The core predicament of energy transition lies not in the availability of clean technologies, but in whether an economy possesses the institutional capacity and social foundation to systematically regulate its carbon-energy metabolic processes. Drawing upon co-evolutionary theory from evolutionary economics, this paper constructs a composite indicator of Low-Carbon Green Energy Eco-Co-evolution (LCEE) encompassing three functional dimensions: efficiency advancement, kinetic energy replacement, and boundary adherence. Concurrently, by integrating innovation ecosystem theory with inclusive development theory, we propose the concept of “Inclusive Potential of Regional Innovation Ecosystems” (IEP), characterizing the systemic potential for transforming innovation outcomes into social welfare across four dimensions: Knowledge Matrix Abundance (KMF), Cultural Capillary Permeation (CCP), Technological Community Succession (TCS), and Social Root Nourishment (SRN). Taking China’s 2016 intellectual property (IP) powerhouse construction pilot as the institutional prototype of Industrial Intellectual Property Upgrading Reform (IPR), we incorporate IPR, IEP, and LCEE into a unified causal analytical framework, proposing a testable transmission logic of ‘institutional supply → ecological development → co-evolutionary synergy. Using panel data from 30 Chinese provincial-level administrative regions over 2010–2022, we employ a Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the direct and spatial spillover effects of IPR on LCEE, and embed a Double Machine Learning (DML) framework to test the mediating mechanism of IEP while controlling for high-dimensional nonlinear interference. The findings reveal that IPR exerts a significant and robust direct promoting effect on LCEE, generating positive spatial spillovers to neighboring regions through the public disclosure of patent information. IEP significantly promotes local LCEE, yet its spatial spillover lacks statistical support due to structural conflicts in inter-dimensional transmission attributes. IEP plays a significant partial mediating role between IPR and LCEE, with the indirect effect accounting for over one-third of the total effect, a finding robust to alternative machine learning algorithms, sample split adjustments, and exclusion of contemporaneous competing policies. Sub-path tests reveal that KMF bears the strongest mediating efficacy, serving as the primary transmission channel, while CCP exhibits full mediation—the institutional effect on LCEE in the cultural dimension depends almost entirely on the mediating transformation through the public cultural service system. Heterogeneity analysis further demonstrates full mediation in the Low-Carbon Green Energy Eco-Kinetic Replacement (KER) dimension, indicating that the institutional catalytic effect on clean energy substitution must be realized through IEP transformation. This paper provides empirical evidence for the proposed causal pathway through which institutional public goods indirectly enhance the synergistic quality of carbon-energy transition via the inclusive potential of innovation ecosystems, providing theoretical foundations and policy implications that, while grounded in China’s institutional context, may offer valuable reference points for emerging market economies facing similar dual pressures of technological constraints and green transition. Full article

The tight sandstone gas reservoir in Qingshimao gas field has the characteristics of complex gas–water distribution, low reservoir quality, low porosity, low permeability and high water saturation. Single-well productivity is low, the production and pressure decrease rapidly, the stable production period is short and economically viable development remains challenging. Therefore, considering the reservoir physical properties and development characteristics of the Qingshimao area, physical experiments and numerical simulations were conducted to investigate the reserve utilization characteristics of complex tight water-bearing gas reservoirs and to evaluate the effectiveness of CO₂ injection in restoring reservoir pressure and enhancing gas recovery after depletion. The results show that: (1) The movable-water saturation of Type I and Type II reservoirs ranged from 2 to 18% and 3–21%, respectively, while increasing water saturation reduced cumulative gas production and increased gas-flow resistance. Type III and Type IV reservoirs are limited by low permeability and fine pore throat. The movable-water saturation is less than 8% and 6% respectively under high water saturation conditions, and the gas–water flow is obviously limited. (2) Both continuous CO₂ injection and post-injection soaking can promote residual-gas recovery after depletion. Post-injection soaking prolongs the contact time between CO₂ and residual methane, whereas fractured cores exhibit more rapid pressure recovery but earlier CO₂ breakthrough. (3) Pore scale and two-dimensional visualization experiments show that after CO₂ injection, the pressure is transferred from the injection inlet to the production outlet, and the depleted low-pressure area is supplemented. The incremental recovery factor of the two-dimensional models after CO₂ injection ranged from 22.81 to 25.28 percentage points. (4) The numerical simulation results show that permeability, water saturation, and the injection and production rates jointly control pressure restoration and gas recovery during CO₂ injection. The high-permeability reservoir achieves a higher recovery factor but experiences earlier CO₂ breakthrough. High water saturation and high injection and production rates will weaken the effective sweep. In field application, the layers with good connectivity and moderate water saturation should be preferred, and the injection and production rates should be reasonably controlled to reduce the risk of gas channeling. Overall, post-depletion CO₂ injection can effectively restore reservoir pressure, mobilize residual methane, and enhance gas recovery in tight water-bearing gas reservoirs. The experimental results support post-depletion CO₂ injection as a potential approach for improving the development performance of tight water-bearing gas reservoirs. Full article

In the mining process of shallow-buried and close-distance coal seam groups in western China, the interconnected collapse fractures between the overlying goaf and the surface form large-area composite goafs, which aggravate surface air leakage and elevate oxygen levels within the goaf. This, in turn, leads to hazardous conditions such as CO over-limits and O₂ deficiency at the working face’s return air corner, which seriously threatens the respiratory health of underground operators and the safe production of mines. Taking the 104 working face of a coal mine in Shenfu-Dongsheng Mining Area as the engineering background, this paper comprehensively adopts SF₆ tracer gas test, fuzzy cluster analysis, and CFD numerical simulation methods to systematically study the distribution characteristics of three-dimensional air leakage channels in composite goafs and their influence mechanism on gas migration in goafs, and proposes a dynamic pressure equalization ventilation (PEV) regulation technology system. The research results show that a multi-dimensional three-dimensional air leakage channel of “surface-interlayer-own layer-roadway” exists in the research area, in which the surface fracture air leakage velocity is about 0.068 m/s, and the interlayer and internal goaf air leakage velocity is about 0.384 m/s. The atmospheric pressure difference between the working face and the surface is the main controlling factor inducing the O₂ deficiency disaster of the working face. Every 100 Pa change in atmospheric pressure difference causes an O₂ concentration fluctuation of about 0.30% at the return air corner, and the critical pressure difference for activating PEV is determined to be 300 Pa. Setting the PEV regulation point at the return air outlet of the working face and adopting the combined dynamic regulation system of fans and air windows can realize accurate pressure balance between the working face and the overlying composite goaf. Full article

Osteoarthritis (OA) is a progressive joint disease characterized by cartilage degeneration, chronic low-grade inflammation, and disruption of tissue homeostasis. Although the mechanosensitive ion channel Piezo1 has been implicated in OA pathogenesis, its expression may also be modulated by inflammatory stimuli independently of applied mechanical loading. This study established a scaffold-free three-dimensional co-culture organoid model comprising human bone marrow-derived mesenchymal stem cell-derived chondrocyte-like cells and M-CSF/RANKL-differentiated RAW264.7-derived osteoclast-like cells to investigate Piezo1-associated molecular responses, inflammatory signaling, and mitophagy-related markers under lipopolysaccharide (LPS)-induced inflammatory conditions. Osteoclast-like differentiation was validated in parallel monolayer cultures by tartrate-resistant acid phosphatase staining and the presence of multinucleated cells before the corresponding differentiated cultures were used for organoid generation. Histological staining, immunofluorescence, CellTiter-Glo 3D viability assay, lactate dehydrogenase cytotoxicity assay, RT-qPCR, and Western blotting were used to evaluate extracellular matrix formation and inflammatory, catabolic, and mitochondrial quality-control-associated markers. LPS stimulation increased the expression of Piezo1, HIF-1α, phosphorylated CaMKII, NLRP3, cleaved Caspase-1, and MMP13, together with alterations in mitophagy- and autophagy-associated markers. Among the evaluated compounds, curcumin produced the greatest improvement in viability relative to the LPS-treated group and was selected for subsequent molecular analyses. Curcumin treatment was associated with reduced inflammatory and catabolic marker expression and partial preservation of cartilage-associated matrix markers. These findings demonstrate inflammation-associated changes in Piezo1 expression and related molecular markers but do not establish mechanically activated Piezo1 signaling or Piezo1-dependent causality. The organoid system therefore represents an exploratory LPS-induced inflammatory model exhibiting selected OA-relevant molecular and matrix-associated features. Full article

Visible light communication (VLC) has emerged as a transformative optical wireless technology for sixth-generation (6G) networks, offering license-free spectrum access, inherent electromagnetic-interference immunity, high spatial confinement, and the unique ability to combine high-speed wireless connectivity with solid-state lighting infrastructure. However, the transition from conventional VLC links to practical 6G optical wireless systems requires far more than advanced modulation and signal processing. Future VLC performance will be strongly determined by the co-design of photonic front-ends, including high-speed transmitters, spectrally engineered emitters, reconfigurable optical interfaces, intelligent receivers, and energy-autonomous detection units. This article provides a comprehensive, device-centered review of photonic hardware and artificial intelligence (AI) enablers for next-generation 6G VLC systems. Particular attention is given to micro-LEDs, laser diodes, color-conversion materials, including perovskite quantum dots, advanced photodetectors, imaging receivers, wavelength-shifting fiber receivers, solar-cell-based receivers, optical reconfigurable intelligent surfaces (RISs), metasurfaces, beam-steering components, and optical wireless power transfer. This review discusses how AI can support inverse photonic design, transmitter and receiver calibration, nonlinear impairment mitigation, channel-aware beam control, and energy-aware resource management. Unlike broader VLC surveys that mainly emphasize network architecture, this article provides a device-centered perspective on AI-enabled photonic integration for 6G VLC, supported by a comprehensive survey of recent experimental demonstrations. Key challenges related to bandwidth, optical efficiency, receiver field of view, mobility, safety, standardization, and practical deployment are summarized, followed by a research roadmap for 2025–2032. Full article

Carbon dioxide water-alternating-gas (CO₂-WAG) flooding simultaneously enables carbon emission mitigation, improved oil displacement efficiency, and expanded gas sweep coverage. Nevertheless, the field performance of this technology remains significantly constrained by gravity override effects, especially in ultra-thick oil reservoirs. In this work, a synthetic heterogeneous dipping mechanistic reservoir model is constructed. Using a quantitative metric for gravity override index in WAG processes, the variation patterns of gravity override under various operational factors are systematically analyzed. Furthermore, the eXtreme Gradient Boosting (XGBoost) machine learning algorithm is employed to conduct feature importance analysis of the controlling factors, identifying parameters with the most substantial impacts. The results indicate that well spacing, oil production rate, WAG injection strategy, and WAG slug duration all exert pronounced effects on both gravity override index and oil recovery factor. Gravity override is confirmed as the dominant factor governing the production performance of WAG flooding in ultra-thick reservoirs. In addition, an optimal combination of operational parameters exists that counterbalances the adverse effects of gravitational and viscous forces, thereby maximizing gas sweep efficiency, delaying gas breakthrough, and enhancing oil recovery. This study provides valuable insights and technical guidance for gas channeling mitigation, vertical gas sweep improvement, and efficient development of analogous ultra-thick reservoirs. Full article

Solar-driven interfacial evaporation (SDIE) represents a highly promising technology for decentralized desalination and wastewater treatment, yet its practical industrial deployment is severely constrained by the intrinsic intermittency of natural solar irradiance and nocturnal salt crystallization. To smooth energy fluctuations and achieve all-weather, continuous freshwater output, integrating solid–liquid phase change materials (SLPCMs) into SDIE has evolved into a system-level paradigm shift driven by advanced spatiotemporal thermal-mass management. This review systematically summarizes recent breakthroughs in micro-to-macro structural engineering for phase-change-coupled SDIE systems. Spatially, advanced microscopic encapsulation strategies such as 3D matrices, core–shell architectures, and solid–solid transitions eradicate molten PCM leakage and reconstruct heat transfer networks, while macroscopic configurations involving sandwich structures and 3D directional channels realize functional zoning to maximize thermal localization. Temporally, the controlled nocturnal release of stored latent heat establishes a cross-timeline energy relay, sustaining dark evaporation and activating interfacial hydrodynamics via Marangoni convection and thermophoretic diffusion to prevent salt clogging under extreme conditions. Furthermore, cross-disciplinary integrations for water-electricity co-generation, targeted resource recovery, and environmental remediation are comprehensively discussed. Finally, critical engineering challenges regarding scalability, cost-effectiveness, and condensation system integration are addressed, offering forward-looking perspectives on coupling thermal storage with physical catalysis to transcend classical thermodynamic limits. Full article

The global energy sector is undergoing rapid and, in many respects, irreversible transformation driven by the convergence of digital disruption, sustainability mandates, and shifting investor expectations. Technologies such as artificial intelligence (AI), blockchain, and digital twin systems are fundamentally reshaping energy operations and strategic decision-making, while ESG governance quality and renewable energy adoption have emerged as two of the most consequential determinants of corporate financial competitiveness and equity valuation. Despite growing practitioner and regulatory interest in these dynamics, limited empirical evidence exists on how ESG governance, renewable adoption, and digital disruption jointly influence financial performance and environmental outcomes across multiple sectors simultaneously. This study addresses that gap using panel data from 26 large-cap US-listed firms across five sectors over 2015–2022 (N = 208 firm-year observations for Revenue/Market Cap/ROA models; N = 91 for the CO₂ model). A multi-method econometric framework is employed, comprising Fixed Effects and Random Effects panel regression with Hausman specification testing, Difference in Differences quasi-experimental analysis, and sequential OLS path analysis with HC3 robust standard errors. Three of four hypotheses are supported. ESG governance quality generates a significant market capitalisation premium of approximately 10–14% per unit Bloomberg ESG Score improvement, after controlling for firm size and R&D intensity; no significant revenue channel effect is found once firm size is properly accounted for. Renewable energy adoption shows a marginal association with market capitalisation at the 10% significance level (FE β = 0.019, p = 0.086; RE β = 0.016, p = 0.077), suggesting capital markets may price clean energy adoption as a forward-looking signal. ESG governance quality drives within-firm CO₂ emission reduction substantially more powerfully than renewable energy quantity alone, with the Fixed Effects estimator identifying a governance-led eco-efficiency mechanism. Firm profitability functions as a cross-model financial capacity moderator, enabling simultaneous ESG investment and environmental improvement. The findings carry direct implications for corporate managers, institutional investors, and policymakers aligned with SDG 7, SDG 9, and SDG 13. Full article

Water flooding in low-permeability, highly heterogeneous reservoirs often causes a rapid increase in water cut and inefficient pressure maintenance because injected water preferentially flows through high-permeability channels. In this study, a field-scale compositional simulation model was established to evaluate CO₂ water-alternating-gas (WAG) enhanced oil recovery in a mature waterflooded reservoir in the Daqing Oilfield. The model was constrained by geological data, experimentally tuned pressure–volume–temperature (PVT) behavior, relative-permeability measurements, and slim-tube tests. The minimum miscibility pressure (MMP) of the CO₂-oil system was estimated to be 19.8 MPa. An 187-month production history was matched using field oil rate, water production, water cut, and reservoir-pressure data. At the current development stage, the reservoir has an oil recovery of 23.6%, an average water cut of 61.34%, and an average reservoir pressure of approximately 6.9 MPa. A 30-year prediction was then performed to compare continued water flooding with several CO₂-WAG development strategies. Sensitivity analyses were conducted for the pressure-restoration level, pre-injection fluid, well-pattern conversion, slug size, and gas/water slug-size ratio. Continued water flooding increased the final oil recovery to only 28.4% and resulted in a water cut of 92.8%. Sequential scenario screening identified a best-performing case among the tested scenarios, consisting of CO₂ pre-injection to restore the average reservoir pressure to 11 MPa, conversion to a staggered line-drive well pattern, a slug size of 0.025 PV, and a gas/water slug-size ratio of 1:1. Under this sequentially selected case, the end-of-forecast oil recovery reached approximately 57.24%, which was the highest value among the cases evaluated in this study and was 28.84 percentage points higher than continued water flooding. The predicted recovery is conditional on the adopted geological, relative-permeability, EOS, and history-matching assumptions. Because the designed average reservoir pressure is below the measured MMP and local pressure above the MMP was not demonstrated, the modeled process is consistently interpreted as immiscible CO₂-WAG. The predicted recovery improvement is interpreted as being associated with pressure support, gas-mobility control, improved sweep efficiency, and compositional CO₂–oil interactions represented by the model, including CO₂ dissolution, oil swelling, and viscosity reduction. The contribution of this work is a field-scale, experimentally constrained workflow for selecting CO₂-WAG operating parameters in mature waterflooded low-permeability reservoirs; CO₂ storage performance should be quantified separately in future work. This study provides an experimentally constrained and history-validated field-scale workflow for identifying a best-performing CO₂-WAG operating case among the tested scenarios in mature waterflooded low-permeability reservoirs. Full article

Astrocytes, once regarded primarily as structural and metabolic support cells, are now increasingly recognized as active participants in neural information processing. Within respiratory control networks, astrocytes are widely distributed throughout the brainstem and spinal cord, where they engage in bidirectional communication with neurons to regulate breathing. This review summarizes current knowledge regarding the roles of astrocytes in respiratory rhythm and pattern generation, central respiratory chemoreception, hypoxic ventilatory responses, respiratory plasticity, and respiratory pathophysiology. Recent advancements in calcium imaging, optogenetics, and pharmacology have revealed that astrocytes modulate respiratory network activity through intracellular Ca²⁺ signaling and the release of gliotransmitters, particularly ATP. In the ventrolateral medulla and the parafacial respiratory group/retrotrapezoid nucleus, astrocytes contribute to central CO₂/H⁺ chemoreception through mechanisms involving connexin hemichannels, potassium channels, and purinergic signaling. Emerging evidence further suggests that astrocytes participate in central hypoxic responses and adaptive respiratory plasticity. In addition, astrocytic dysfunction has been implicated in several disorders affecting respiratory control, including brainstem astrocytoma, Rett syndrome, sudden infant death syndrome, and sudden unexpected death in epilepsy. Collectively, accumulating evidence identifies astrocytes as integral components of respiratory control networks that contribute to both the maintenance of respiratory homeostasis and the pathogenesis of respiratory dysfunction. A deeper understanding of astrocyte–neuron interactions may provide novel therapeutic opportunities for the treatment of respiratory disorders. Full article

A coupled numerical model was developed to investigate the phase evolution and diverting acidizing performance of CO₂-foamed acid in heterogeneous carbonate reservoirs. The model integrates CO₂ phase evolution, gas–liquid two-phase Darcy flow, acid–rock reactions, heat transfer, pore-structure evolution, and foam mobility control. By dynamically updating CO₂ thermophysical properties in response to local temperature and pressure variations, the model captures the coupled effects of phase behavior on foam quality, apparent viscosity, flow resistance, and acid redistribution between high- and low-permeability layers. The effects of reservoir temperature, foam quality, and permeability contrast on wormhole propagation, foam distribution, and stimulation depth in the low-permeability layer were systematically evaluated. Under the simulated conditions, low-permeability-layer stimulation initially increased with reservoir temperature, reached its maximum near 393 K, and declined at 413 K. This non-monotonic behavior reflects the balance among CO₂ phase behavior, foam stability, and acid–rock reaction rate: moderate temperatures promote the formation of a favorable foam region and effective diversion, whereas excessive temperatures weaken foam stability and accelerate acid consumption near the wellbore. Foam quality also exhibited a non-monotonic influence on diversion performance. Foam qualities of 60–80% provided strong mobility control and effective acid redistribution, while a foam quality of 90% restricted liquid-acid transport because of excessive near-wellbore foam accumulation. In contrast, the pure-acid system preferentially entered the high-permeability layer and broke through at approximately 0.3 PV. Increasing permeability contrast weakened foam retention and intensified preferential channeling; at a permeability contrast of 8, the wormhole length in the low-permeability layer was less than 50% of that obtained at a contrast of 4. These results demonstrate that phase-dependent foam resistance can redirect acid from preferential high-permeability channels toward low-permeability regions. This study defines an effective operating window for CO₂-foamed-acid diversion and provides a theoretical basis for designing diverting acidizing treatments in heterogeneous, high-temperature carbonate reservoirs. Full article

Concurrent exposure to analgesic and psychotropic drugs is frequent in patients with pain, psychiatric comorbidity, frailty, or acute-care needs. The clinically important question is whether analgesics and psychotropic drugs act on the same metabolic, transporter, receptor, ion-channel, or cellular stress systems. This narrative mechanistic review discusses those points of contact. CYP-mediated inhibition or induction, phenoconversion, altered parent-to-metabolite ratios, and blood–brain barrier transporter effects can change both systemic and central exposure, particularly through CYP2D6, CYP3A4, CYP2C9, CYP2B6, and P-glycoprotein. Pharmacodynamic toxicity may involve serotonergic excess, opioid and GABAergic effects in respiratory-control networks, hERG/IKr-related loss of repolarization reserve, or dopamine D2 receptor blockade. Non-opioid analgesics and psychotropic background therapy add further pathways involving renal and gastrointestinal vulnerability, hematological toxicity, mitochondrial injury, and altered central nervous system function. At the cellular level, mitochondrial dysfunction, oxidative stress, calcium dysregulation, and endoplasmic reticulum stress are discussed primarily as mechanistic or preclinical contributors unless direct clinical evidence is available. Overall, analgesic–psychotropic co-exposure is presented as a clinically important example of pathway convergence, while pharmacogenomic and computational approaches are interpreted in relation to drug exposure, organ reserve, and patient-specific vulnerability. Full article

Real-time visual detection is essential for personnel safety control in firework manufacturing workshops, where inadequate personnel-count control can increase safety risks in hazardous production zones. This study proposes a visual detection and multi-zone personnel safety control method that combines edge-oriented personnel detection, cross-camera identity association, and polygon-based boundary filtering. The detection module is built on YOLO26, which supports inference without non-maximum suppression (NMS). A Global Attention Mechanism (GAM) is adopted instead of the Convolutional Block Attention Module (CBAM) because its sequential channel-spatial attention preserves cross-dimensional interactions without the global pooling operations used in CBAM, thereby retaining weak spatial cues from small personnel targets. GAM is incorporated after the Spatial Pyramid Pooling-Fast (SPPF) module to improve detection under overhead views, dust, and occlusion. A cross-camera person re-identification (ReID) layer maintains identity consistency across workshops, while an Irregular Electronic Fence (IEF) excludes detections outside hazardous operating boundaries. On in-situ data collected from Deren Firework Co., Ltd., the proposed method achieves a 98.3% mean average precision at an intersection-over-union threshold of 0.5 (mAP@0.5) with a per-image central processing unit (CPU) processing time of 36.5 ms. Compared with YOLOv8n, this represents a 5.9 percentage point improvement in mAP@0.5 and a 54.6% latency reduction. A three-month field deployment detected 15 safety breaches and supported timely intervention in 4 critical overcrowding incidents, indicating the practical applicability of the method under the evaluated factory conditions. Full article