Search Results (4,228)

This study focuses on optimizing the flow field uniformity within a vertical honeycomb wet electrostatic precipitator (WESP), which is a critical prerequisite for achieving high particulate removal efficiency. For a vertical honeycomb WESP with an air capacity of 25,000 m³/h, the internal flow field is optimized by adjusting the opening ratio and aperture ratio of the airflow equalizing plate, installing additional deflector plates, and adding additional airflow equalizing plates at strategic locations. The optimization reduces the velocity relative standard deviation at the anode inlet section to 0.14. Through 1:1-scale equipment construction and testing, the particle concentration at the outlet is stabilized below 10 mg/Nm³, with an average removal efficiency of 95.88%—a 5.7% improvement over the original model. This study solves the design dependency on empirical guidance for vertical honeycomb WESP in the food industry, providing a green technology paradigm for low-carbon industrial emissions. Full article

The transition toward renewable-powered greenhouse agriculture offers opportunities for reducing operational costs and environmental impacts, yet challenges remain in managing fluctuating energy loads and optimizing agricultural inputs. While second-life lithium-ion batteries provide a cost-effective energy storage option, their thermal and electrical characteristics under real-world greenhouse conditions are poorly documented. Similarly, although plasma-activated water (PAW) shows potential to reduce chemical fertilizer usage, its integration with renewable-powered systems requires further investigation. This study develops an adaptive monitoring and modeling framework to estimate the thermal resistances (R_u, R_c) and internal resistance (R_int) of second-life lithium-ion batteries using operational data from greenhouse applications, alongside a field trial assessing PAW effects on beefsteak tomato cultivation. The adaptive control algorithm accurately estimated surface temperature (T_s) and core temperature (T_c), achieving a root mean square error (RMSE) of 0.31 °C, a mean absolute error (MAE) of 0.25 °C, and a percentage error of 0.31%. Thermal resistance values stabilized at R_u ≈ 3.00 °C/W (surface to ambient) and R_c ≈ 2.00 °C/W (core to surface), indicating stable thermal regulation under load variations. Internal resistance (R_int) maintained a baseline of ~1.0–1.2 Ω, with peaks up to 12 Ω during load transitions, confirming the importance of continuous monitoring for performance and degradation prevention in second-life applications. The PAW treatment reduced chemical nitrogen fertilizer use by 31.2% without decreasing total nitrogen availability (69.5 mg/L). The NO₃⁻-N concentration in PAW reached 134 mg/L, with an initial pH of 3.04 neutralized before application, ensuring no adverse effects on germination or growth. Leaf nutrient analysis showed lower nitrogen (1.83% vs. 2.28%) and potassium (1.66% vs. 2.17%) compared to the control, but higher magnesium content (0.59% vs. 0.37%), meeting Japanese adequacy standards. The total yield was 7.8 kg/m², with fruit quality comparable between the PAW and control groups. The integration of adaptive battery monitoring with PAW irrigation demonstrates a practical pathway toward energy efficient and sustainable greenhouse operations. Full article

This review provides a critical and technically grounded assessment of continuous electrocoagulation processes (CEPs) for the treatment of industrial inorganic pollutants, emphasizing recent innovations, methodological developments, and practical outcomes. A comprehensive literature survey indicates that 53 studies published over the past 25 years have investigated CEPs for inorganic contaminant removal, with 36 focusing on standalone electrocoagulation systems and 17 exploring integrated CEPs approaches. Recent advancements in reactor design, such as enhanced internal mixing, optimized electrode geometry, and modular configurations, have significantly improved treatment efficiency, scalability, and operational stability. Evidence indicates that CEPs can achieve high removal efficiencies for a wide range of inorganic contaminants, including fluoride, arsenic, heavy metals (e.g., chromium, lead, nickel, iron), nitrates, and phosphates, particularly under optimized operating conditions. Compared to conventional treatment methods, CEPs offer several advantages, such as simplified operation, reduced chemical consumption, lower sludge generation, and compatibility with renewable energy sources and complementary processes like membrane filtration, flotation, and advanced oxidation. Despite these promising outcomes, industrial-scale implementation remains constrained by non-standardized reactor designs, variable operational parameters, electrode passivation, high energy requirements, and limited long-term field data. Furthermore, few studies have addressed the modeling and optimization of integrated CEPs systems, highlighting critical research gaps for process enhancement and reliable scale-up. In conclusion, CEPs emerge as a novel, adaptable, and potentially sustainable approach to industrial inorganic wastewater treatment. Its future deployment will rely on continued technological refinement, standardization, validation under real-world conditions, and alignment with regulatory and economic frameworks. Full article

This study investigates the relationship between corporate governance mechanisms, CSR sustainability reporting, and emission performance in BRICS countries. Based on a panel dataset of 862 firms covering the period from 2018 to 2023, this study investigates the impact of audit committee presence, audit committee expertise, board gender diversity, and board members’ sustainability-related skills on firms’ emission performance. We employ fixed effects models and, to address potential endogeneity concerns, two-stage least squares (2SLS) regression models. The results show that audit committee expertise (β = 2.254, p < 0.01) and board-specific sustainability skills (β = 0.129, p < 0.01) significantly enhance emission performance. Moreover, CSR sustainability reporting positively moderates these relationships, with interaction effects showing stronger environmental outcomes for audit expertise (β = 0.083, p < 0.01) and board sustainability skills (β = 0.001, p < 0.1). In contrast, board gender diversity shows an insignificant or diminishing marginal effect when interacted with CSR reporting. Robustness checks using 2SLS confirm the stability of these findings. The study provides novel evidence on how internal governance structures and sustainability disclosure jointly shape environmental responsibility in emerging economies. Policy recommendations are offered to encourage transparent reporting and strengthen governance mechanisms to support climate-related goals. Full article

As internal combustion engine (ICE) systems are increasingly exposed to severe thermal and oxidative environments, the oxidation resistance and structural integrity of exhaust valve materials have become critical for maintaining long-term engine reliability and efficiency. This study presents a comparative evaluation of the cyclic oxidation behavior of two candidate valve steels, 1.4718 (ferritic stainless steel) and 1.4871 (austenitic stainless steel), under service-temperature conditions. The specimens were exposed to repeated oxidation at 550 °C, 650 °C and 750 °C for 25 cycles in ambient air. The surface and cross-sectional morphologies of the oxide layers were analyzed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) to investigate oxide scale composition, thickness, and growth characteristics. The oxidation behavior of both alloys proceeded in two distinct stages: an initial phase marked by accelerated oxidation, followed by a slower, more stable growth period. The extent of oxidation intensified with increasing temperature. The 1.4718 alloy developed relatively porous but compositionally stable oxide layers consisting primarily of Fe- and Cr-based spinels such as FeCr₂O₄ and Cr₂SiO₄. In contrast, the 1.4871 alloy formed a dense, adherent, dual-layered oxide scale composed of an outer Mn₂O₃-rich layer and an inner Cr₂O₃-rich layer, attributable to its high Mn and Cr content. The results underscore the critical influence of elemental composition, particularly Cr, Mn and Si, on oxide scale stability and spallation resistance, demonstrating the superior cyclic oxidation resistance of the 1.4871 alloy and its potential suitability for exhaust valve applications in thermally aggressive environments. Full article

Antibody–drug conjugates (ADCs) are a rapidly advancing class of targeted cancer therapeutics that couple the antigen specificity of monoclonal antibodies (mAbs) with the potent cytotoxicity of small-molecule drugs. In their core design, a tumor-targeting antibody is covalently linked to a cytotoxic payload via a chemical linker, enabling the selective delivery of highly potent agents to malignant cells while sparing normal tissues, thereby improving the therapeutic index. Humanized and fully human immunoglobulin G1(IgG1) antibodies are the most common ADC backbones due to their stability in systemic circulation, robust Fcγ receptor engagement for immune effector functions, and reduced immunogenicity. Antibody selection requires balancing tumor specificity, internalization rate, and binding affinity to avoid barriers to tissue penetration, such as the binding-site barrier effect, while emerging designs exploit tumor-specific antigen variants or unique post-translational modifications to further enhance selectivity. Advances in antibody engineering, linker chemistry, and payload innovation have reinforced the clinical success of ADCs, with more than a dozen agents FDA approved for hematologic malignancies and solid tumors and over 200 in active clinical trials. This review critically examines established and emerging conjugation strategies, including lysine- and cysteine-based chemistries, enzymatic tagging, glycan remodeling, non-canonical amino acid incorporation, and affinity peptide-mediated methods, and discusses how conjugation site, drug-to-antibody ratio (DAR) control, and linker stability influence pharmacokinetics, efficacy, and safety. Innovations in site-specific conjugation have improved ADC homogeneity, stability, and clinical predictability, though challenges in large-scale manufacturing and regulatory harmonization remain. Furthermore, novel ADC architectures such as bispecific ADCs, conditionally active (probody) ADCs, immune-stimulating ADCs, protein-degrader ADCs, and dual-payload designs are being developed to address tumor heterogeneity, drug resistance, and off-target toxicity. By integrating mechanistic insights, preclinical and clinical data, and recent technological advances, this work highlights current progress and future directions for next-generation ADCs aimed at achieving superior efficacy, safety, and patient outcomes, especially in treating refractory cancers. Full article

This paper establishes dividend-based representations for two influence assessments. First, we define a system of min-dividends derived from the minimal-influence evaluation via a unique linear decomposition using unanimity-type spanning models. Building on this, we further construct a pair of internal and external min-dividends satisfying Completeness and Balancedness conditions, through which we express the stable min-value as the net difference of internal gains and external losses. We then demonstrate that the minimal self-stable value can be represented as accumulated average min-dividends across all coalitions they have participated in. Furthermore, the proposed expression also is adopted to analyze the stability of the minimal self-stable value. These results extend the classical notion of dividends into a minimal-influence-based framework with potential applications in fair resource allocation and responsibility apportionment. Full article

By modulating the mass ratio of hydrothermal agents to cobalt/iron precursors, Co₃O₄ nanowires were successfully integrated into spinel-type Co/Fe@NF, forming a heterojunction anode for alkaline water electrolysis (AWE) hydrogen production. This Co₃O₄ nanowire-assembled CoFe₂O₄ nanosheet anode (Co/Fe(5:1)@NF) exhibits exceptional electrochemical oxygen evolution reaction (OER) performance, requiring only 221 mV overpotential to achieve 10 mA cm⁻². Sulfamethoxazole (SMX) was employed as a model pollutant to investigate the anode sacrificial material; it achieved approximately 95% SMX degradation efficiency, reducing the OER potential of 50 mV/10 mA cm⁻². SMX oxidation coupled with Co/Fe heterojunction structure partially substitutes the OER. Co/Fe heterojunction generates an internal magnetic field, which induces the formation of novel active species within the system. ·O₂⁻ is the newly formed active oxygen species, which enhanced the proportion of indirect SMX oxidation. Quantitative analysis reveals that superoxide radical-mediated indirect oxidation of SMX accounts for approximately 38.5%, Fe(VI) for 9.4%, other active species for 6.1%, and direct oxidation for 46.0%. The nanowire–nanosheet assembly stabilizes a high-spin configuration on the catalyst surface, redirecting oxygen intermediate pathways toward triplet oxygen (³O₂) generation. Subsequent electron transfer from nanowire tips facilitates rapid ³O₂ reduction, forming superoxide radicals (·O₂⁻). This study effectively driven by indirect oxidation, with cathodic hydrogen production, providing a novel strategy for utilizing renewable electricity and reducing OER while offering insights into the design of Co/Fe-based catalyst. Full article

Hyperspectral band selection utilizes a crucial band subset to represent original data. In hyperspectral anomaly detection tailored for specific tasks, detection performance can be enhanced by pre-selecting a subset of bands that are more representative. However, existing methods remain constrained in modeling spatial–spectral dependencies and simultaneously extracting distinct bands’ contribution from the established model, thus struggling to balance effectiveness and stability. To address these issues, we propose a reliable band selection method for anomaly detection. Concretely, we conduct a convolution–transformer hybrid autoencoder architecture to fully exploit the local and global spatial–spectral interdependencies. Next, we design an anomaly–background separability constraint to seamlessly integrate the task priors of anomaly detection into network optimization. Furthermore, we design a spectral attention module to quantify the contribution of different bands during network optimization. Simultaneously, an adaptive band allocation method is designed to optimize the internal structure of the selected band subset. Extensive experiments demonstrate that the proposed method achieves more robust band selection results compared to existing related methods. Full article

As urbanization intensifies, the ecological area ratio (EAR) has become an essential tool for assessing ecological performance in urban development projects. However, conventional EAR systems remain largely prescriptive and surface-oriented, lacking adaptability to diverse planning contexts. This study proposes a probability-based EAR reference table developed from empirical data collected across six representative large-scale urban development districts. EAR values were statistically analyzed for 16 land-use types to construct a reference table using mean and quartile indicators. The table was then applied to seven newly planned towns to evaluate its predictive utility. The results showed that predicted EAR values closely aligned with institutional targets and revealed meaningful internal variation depending on land-use composition. Green space and parks showed the highest ecological contributions, while multi-family housing, despite moderate unit-area performance, played a key stabilizing role due to its large spatial footprint. Correlation analyses further demonstrated that EAR composition varied across housing supply types, shaped by differing regulatory frameworks and design priorities. By transitioning EAR from a uniform ratio to a data-driven, probabilistic guideline, this study offers both a practical estimation tool and a strategic planning aid. The findings provide actionable insights for more adaptive, equitable, and ecologically robust urban development practices. Full article

Internal erosion is a significant issue caused by water flow within soils, resulting in structural collapse of hydraulic structures, particularly in coarse soils located near rivers. These soils typically exhibit granulometric instability due to low clay content, resulting in poor hydraulic and mechanical properties. To mitigate this problem, cement treatment is applied as an alternative to soil removal, reducing transportation and storage costs. The hole erosion test (HET) and Crumbs tests, shearing behaviour through consolidated undrained (CU) triaxial, and microstructure analyses regarding scanning electron microscopy (SEM), mercury intrusion porosimeter (MIP) and thermogravimetric analysis (TGA) were conducted for untreated and treated coarse soil specimens with varying cement contents (1%, 2%, and 3%) and curing durations (1, 7, and 28 days). The findings indicate a reduction in the loss of eroded particles and overall stability of treated soils, along with an improvement in mechanical properties. SEM observations reveal the development of hydration gel after treatment, which enhances cohesion within the soil matrix, corroborated by TGA analyses. MIP reveals the formation of a new class of pores, accompanied by a reduction in dry density. This study demonstrates that low cement addition can transform locally unsuitable soils into durable construction materials, reducing environmental impact and supporting sustainable development. Full article

Systemic scleroderma (SSc) is an autoimmune disease characterized by excessive collagen production and progressive fibrosis. As the disease advances, vascular injury leads to fibrosis of the skin and internal organs, among which interstitial lung disease (ILD) carries the worst prognosis. Recent advances in biomarkers, imaging techniques, and innovative therapies offer hope for improving outcomes and quality of life in patients with SSc and ILD. To evaluate the usefulness of disease biomarkers and the efficacy and safety of immunomodulatory therapies in SSc-associated ILD (SSc-ILD), a literature review was conducted using the PubMed database for studies published mainly over the last 5 years. After applying inclusion criteria, 53 clinical studies were analyzed. Treating SSc-ILD remains challenging, with therapeutic strategies aiming to suppress inflammation and limit fibrosis progression. Clinical studies have demonstrated moderate to good efficacy of immunosuppressants such as cyclophosphamide (CYC) and mycophenolate mofetil (MMF), showing improvements in lung function parameters, such as forced vital capacity (FVC), and slowing disease progression. Additionally, biological agents such as nintedanib and tocilizumab have shown promising results—nintedanib in reducing the annual rate of FVC decline and tocilizumab in decreasing inflammatory biomarkers and stabilizing pulmonary function. However, despite these therapeutic advances, many studies had small sample sizes, heterogeneous patient populations, and varying inclusion criteria. Given the challenges in diagnostics and the critical need to evaluate the efficacy alongside the safety of immunomodulatory and anti-fibrotic therapies in systemic sclerosis-associated interstitial lung disease (SSc-ILD), there remains a strong demand for large, well-designed, multicenter trials with clearly defined patient cohorts to reliably assess the long-term outcomes of agents such as tocilizumab and nintedanib. Full article

Effective intracellular delivery for ovarian cancer therapy remains a significant challenge. We present chrysin-loaded p(MMA-co-DMAEMA)-b-(OEGMA-co-DMA), PMOD-Chr, a nanoparticle platform precisely engineered via RAFT polymerization for advanced therapeutic delivery. This multi-functional platform features a hydrophobic p(MMA) core encapsulating chrysin (Chr), a pH-responsive p(DMAEMA) segment for endosomal escape, and a hydrophilic OEGMA (Oligo(ethylene glycol) methyl ether methacrylate) shell functionalized for enhanced cellular affinity and systemic stability. The combination of OEGMA and DMA (Dopamine methacrylamide) block facilitates passive targeting of ovarian cancer cells, enhancing internalization. Nanoparticles prepared via the nanoprecipitation method exhibited ~220 nm, demonstrating effective size modulation along with high homogeneity and spherical morphology. In A2780 and OVCAR3 ovarian cancer cells, PMOD-Chr demonstrated significantly enhanced cytotoxicity, substantially lowering the effective IC₅₀ dose of Chr. Mechanistically, PMOD-Chr induced a potent G2/M cell cycle arrest, driven by the upregulation of the CDK1/Cyclin B1 complex. Furthermore, the formulation potently triggered programmed cell death by concurrently activating both the intrinsic apoptotic pathway, evidenced by the modulation of Bax, Bcl2, and caspase 9, and the extrinsic pathway involving caspase 8. These findings emphasize that precision engineering via RAFT polymerization enables the creation of sophisticated, multi-stage nanomedicines that effectively overcome key delivery barriers, offering a highly promising targeted strategy for ovarian cancer. Full article

Agricultural plastic waste is a growing global concern, as the widespread use of plastics in farming paired with limited waste management infrastructure has led to environmental pollution, resource inefficiency, and practical challenges in rural communities. This review systematically analyzes international policy frameworks and technological advancements aimed at improving agricultural plastic waste management, drawing on peer-reviewed literature and policy documents identified through targeted database searches and screened by transparent inclusion criteria. Comparative analysis of national strategies, such as extended producer responsibility, regional management models, and technology-driven incentives, is combined with a critical evaluation of recycling and biodegradable innovations. The results reveal that while integrated policies can enhance collectthion efficiency and funding stability, their implementation often encounters high costs, logistical barriers, and variability in stakeholder commitment. Advanced recycling methods and emerging biodegradable materials demonstrate technical promise, but face challenges related to field performance, cost-effectiveness, and scalability. The review concludes that sustainable management of agricultural plastics requires a multi-faceted approach, combining robust regulation, economic incentives, technological innovation, and ongoing empirical assessment. These findings emphasize the importance of adapting strategies to local contexts and suggest that the successful transition to circular management models will depend on continued collaboration across policy, technology, and stakeholder domains. Full article

This paper introduces a novel Underclothing Body Shape Perception Network (UBSP-Net) for reconstructing parametric 3D human models from clothed full-body 3D scans, addressing the challenge of estimating body shape and pose beneath clothing. Our approach simultaneously predicts both the internal body point cloud and a reference point cloud for the SMPL model, with point-to-point correspondence, leveraging the external scan as an initial approximation to enhance the model’s stability and computational efficiency. By learning point offsets and incorporating body part label probabilities, the network achieves accurate internal body shape inference, enabling reliable Skinned Multi-Person Linear (SMPL) human body model registration. Furthermore, we optimize the SMPL+D human model parameters to reconstruct the clothed human model, accommodating common clothing types, such as T-shirts, shirts, and pants. Evaluated on the CAPE dataset, our method outperforms mainstream approaches, achieving significantly lower Chamfer distance errors and faster inference times. The proposed automated pipeline ensures accurate and efficient reconstruction, even with sparse or incomplete scans, and demonstrates robustness on real-world Thuman2.0 dataset scans. This work advances parametric human modeling by providing a scalable and privacy-preserving solution for applications to 3D shape analysis, virtual try-ons, and animation. Full article