Search Results (75,004)

Recent earthquakes have underscored the significant seismic vulnerability and poor energy performance of existing reinforced concrete (RC) buildings, with particular deficiencies observed in non-structural components such as masonry infill walls. Conventional retrofit strategies typically address seismic and thermal deficiencies separately, often leading to increased costs and invasive interventions. This study explores the development of an innovative plaster that combines seismic strengthening with thermal insulation. The proposed plaster is produced using natural raw materials of local Calabrian origin and reinforced with broom fibers to enhance both ductility and mechanical strength. Experimental investigations included mechanical characterization through compressive and flexural strength tests, toughness, and ductility evaluation, as well as thermophysical analyses and further complementary tests. The results demonstrate that fiber reinforcement ensures adequate strength and significantly improves deformability, making the material suitable for seismic retrofitting of infill walls. In fact, the results show that the fiber insertion improves the post-critical behavior of the plaster through a significant increase in its ductility. Moreover, the thermal tests confirm a notable reduction in heat transfer, enhancing the energy performance of building envelopes. The complementary tests have demonstrated the suitability of the designed plasters for the intended applications. Full article

Wireless Sensor Networks (WSNs) are widely used in environmental monitoring, disaster early warning, and smart grids. However, sensor nodes face strict energy limitations. Unbalanced energy consumption and hotspots severely shorten the network lifetime. To address these problems, this paper proposes an optimized Spotted Hyena Optimization-Energy-Efficient Non-Uniform Clustering algorithm (SHOE) for cluster head selection and data transmission. The algorithm has three main innovations: combining a bio-inspired metaheuristic with an improved EEUC (Energy-Efficient Unequal Clustering) multi-hop relay and a Gaussian distribution model for non-uniform node deployment; designing a multi-dimensional fitness function considering energy, distance, and node location; and introducing empty cluster and isolated node repair mechanisms to balance exploration and exploitation. Specifically, the multi-dimensional fitness function guides the heuristic search process towards high-quality cluster head candidates, while the empty cluster and isolated node repair mechanisms dynamically rectify abnormal network structures, ensuring the robustness of the final architecture optimized by the bio-inspired framework. Simulations in MATLAB show that SHOE outperforms LEACH (Low-Energy Adaptive Clustering Hierarchy), PSOE (Particle Swarm Optimization with Evolutionary Strategy), PL-EBC (Probabilistic Localized Energy-Balanced Clustering), and CGWOA (Chaotic Grey Wolf Optimization Algorithm) in reducing node death, saving energy, and extending network lifetime. It improves adaptability to non-uniform distribution and optimizes energy balance, thus enhancing the efficiency and stability of WSNs. Full article

This study investigates the key determinants of firm profitability in the global automotive sector, examining whether superior returns on assets (ROA) stem from operational efficiency, strategic leverage, or innovation intensity, and highlighting the potential trade-off between efficiency and investment in capital-intensive industries. Analysing a global panel dataset of 192 automotive firms from 38 countries/regions over 2010–2024, a fixed effects regression model with Driscoll–Kraay standard errors was applied to control for unobserved heterogeneity, heteroskedasticity, and cross-sectional dependence across 11 financial and strategic variables. The findings reveal that firm size and inventory turnover are significant positive drivers of profitability, while research and development (R&D) intensity exerts a strong negative impact. The positive association with the effective tax rate reflects reverse causality, where more profitable firms incur higher tax burdens, rather than a causal effect of taxation on performance. Notably, working capital management, leverage, sales growth, and capital expenditure showed no statistically significant effects after controlling for firm and time effects. Temporal fluctuations, including a marked profitability decline in 2024, underscore the sector’s sensitivity to macroeconomic shocks. This study contributes robust, large-scale empirical evidence on the short-term profitability trade-off associated with R&D intensity in a globally integrated industry, addressing cross-sectional dependence through its methodological approach. Full article

First introduced in 1995, the Particle Swarm Optimization (PSO) algorithm offers a reliable and efficient solution to real-valued optimization problems. However, extending it to binary-valued problems proved challenging. This paper proposes a new Boolean version of the PSO technique based on a novel mutation strategy. By employing an innovative mutation mechanism in the velocity bitstring, the method enforces a minimum perturbation level, reduces the risk of premature convergence, and promotes broader global search. Several variations of the algorithm and parameter combinations are evaluated using 47 benchmark functions to derive the best-performing configuration, which is then compared with other population-based methods to demonstrate the effectiveness of the proposed algorithm. Finally, the technique is applied to an antenna array thinning problem for the design of a planar antenna array with certain specifications. Full article

Driven by the global energy transition and carbon neutrality goals, hybrid power systems have become a core technical path for energy conservation and carbon reduction in the transportation and power sectors, and the performance of energy management strategies directly determines the system’s overall energy efficiency. Traditional energy management methods have inherent bottlenecks of high model dependence and poor adaptability, making it difficult to satisfy real-time decision-making requirements under complex operating conditions. Deep Reinforcement Learning (DRL) provides an innovative solution to this technical bottleneck, and has become a cutting-edge research direction in this field. However, existing reviews have not yet constructed a full-chain analysis framework covering its algorithms, applications, verification, challenges and prospects. Focusing on the engineering application of DRL in the real-time energy management of hybrid power systems, this paper systematically sorts out domestic and international research results up to the first quarter of 2026. The core quantitative findings of this review are as follows: (1) DRL-based strategies can achieve 93–99.5% of the Dynamic Programming (DP) theoretical global optimum in fuel economy, which is 5–25% higher than rule-based methods; (2) DRL strategies only have 3.1–4.8% performance degradation under unseen operating conditions, which is significantly better than the 10.3–14.7% degradation of the Equivalent Consumption Minimization Strategy (ECMS); (3) Actor–Critic (AC) algorithms (Twin Delayed Deep Deterministic Policy Gradient (TD3)/Soft Actor–Critic (SAC)) have become the mainstream in this field, with a 3–5 times higher sample efficiency than value function-based algorithms; and (4) offline DRL and transfer learning can reduce the training time of DRL strategies by more than 80% while maintaining equivalent optimization performance. This paper first analyzes the essential attributes and core technical challenges of hybrid power system energy management; second, classifies DRL algorithms from the perspective of control engineering and analyzes their technical characteristics; third, disassembles the application design logic of DRL around four major scenarios: land vehicles, water vessels, aerial vehicles and fixed microgrids; fourth, summarizes the mainstream verification platforms and evaluation systems; fifth, analyzes core bottlenecks and cutting-edge solutions; and finally, prospects the development trends of next-generation intelligent energy management systems combined with cross-fusion technologies. This paper aims to build a complete technical system map for this field and promote the engineering deployment and practical application of intelligent energy management technologies integrating data and knowledge. Full article

Global water pollution driven by industrial and agricultural expansion has resulted in the widespread occurrence of persistent contaminants, particularly pharmaceuticals and heavy metals, in groundwater systems. Conventional treatment methods often prove inefficient, costly, and environmentally unsustainable, highlighting the need for innovative in situ remediation technologies. Permeable Reactive Barriers (PRBs) have emerged as a promising and energy-efficient solution for the long-term purification of contaminated aquifers. Their efficiency arises from passive operation, relying on natural groundwater flow to promote pollutant removal through adsorption, ion exchange, precipitation, and redox-driven transformations. This review emphasizes the superior performance of materials such as Activated Carbon, Biochar, Zeolites, and Zero-Valent Iron (ZVI) in the immobilization and reduction in pharmaceuticals and metal ions. Key challenges to PRB longevity include permeability loss and reactive media depletion due to mineral precipitation and biofouling. Advances in hybrid PRB configurations, coupled with electrokinetic (EK) and bioreactor systems, and predictive modeling, particularly Artificial Neural Networks (ANNs), offer pathways to enhance performance, optimize design, and ensure sustainable operation. Overall, PRBs represent a scalable and environmentally sound approach to groundwater remediation, with future progress relying on the development of multifunctional, regenerable materials and integrated design strategies. Full article

This study analyzes transformative collaborative learning as a management innovation in a community-based service ecosystem in Phrom Kiri, Thailand. Leveraging Transformative Learning Theory and Service-Dominant Logic, the study employs qualitative participatory methods (i.e., multi-stakeholder workshops, focus groups, and field observations) to document the dynamic processes through which learning, interactions, and institutional changes evolve. These findings demonstrate how collectively informed strategies for sustainability challenges engendered collective learning processes that led to an alteration of actors’ assumptions, mobilization of shared understanding, and facilitated new governance practices driven by multi-dimensional value drives in response to accumulating disconnects. These reflect the rise of participatory governance mechanisms, the intermediation between actors to create synergies, and the anchoring of institutional frameworks into local contexts to allow for value generation both in economic terms and social ones. Our case study shows that transformative learning can be more than just a cognitive change, also enabling community-level management innovations. It finds that sustainable development of local service ecosystems relies on the formation, institutionalization, and promotion of collaborative practices that facilitate the alignment of stakeholders’ interests and competencies. By conceptualizing transformative collaborative learning as a key mechanism to understand how management innovation and value co-creation unfold in community-based development, this research advances sustainability and management literature. Full article

Background: Emerging evidence has established ferroptosis as a vital factor in the pathogenesis of cardiovascular diseases, especially in septic cardiomyopathy (SCM). Meanwhile, ondansetron (OND), a well-established 5-HT3 receptor antagonist, has gained increasing attention for its pleiotropic effects. However, its potential to modulate ferroptosis in the cardiovascular field remains unexplored. This study aims to fill this gap by exploring the potential of OND as an innovative therapeutic intervention for SCM. Methods: This study utilized both in vitro and in vivo models of septic cardiomyopathy (SCM), which was induced by lipopolysaccharide (LPS) stimulation in neonatal rat cardiomyocytes (NRCMs) and C57BL/6 mice. Through RNA sequencing, as well as molecular and functional assessments—including echocardiography and ferroptosis-related measurements—we revealed the anti-ferroptotic effect of ondansetron (OND). Mechanistically, ATF3 was identified as a pivotal regulator, with its overexpression via AAV9 in vivo and ADV in vitro confirming its role in OND-induced cardioprotection. Results: Ondansetron (OND) showed potent anti-ferroptotic effects in both cellular and murine models of septic cardiomyopathy (SCM). Treatment with OND not only improved cardiac performance but also reduced ferroptotic markers, mitigated lipid peroxidation and iron overload, and bolstered antioxidant defense. Notably, OND administration attenuated oxidative and endoplasmic reticulum (ER) stress while restoring mitochondrial integrity. Mechanistically, the anti-ferroptotic activity of OND was mediated through the HTR3A/ATF3 axis: ATF3 overexpression negated OND’s protective effects, while HTR3A antagonism with VUF10166 recapitulated its benefits. Conversely, HTR3A agonism with PBG attenuated ferroptosis resistance, further implicating this pathway as central to OND’s mechanism. Conclusions: This study demonstrated a novel pharmacological role for ondansetron (OND) in attenuating ferroptosis in septic cardiomyopathy (SCM) via the HTR3A/ATF3 signaling pathway. This finding delineates a novel therapeutic avenue and supports the repurposing of OND beyond its traditional antiemetic use to cardiovascular applications. Full article

Under China’s dual-carbon goals, Green Finance Policy (GFP) and the Environmental Protection Tax Policy (ETP) are key tools for firm-level green transformation, yet their joint micro-effects remain underexplored. Using Shanghai and Shenzhen A-share listed firms from 2011–2022, this study treats the overlapping rollout of the Green Finance Reform and Innovation Pilot Zones and the Environmental Protection Tax reform as a staggered quasi-natural experiment and applies a multi-period DID to identify their synergistic effect on Corporate Green Technology Innovation. Results show that each policy alone promotes green innovation and that their coordination further strengthens the effect. The synergy operates mainly by easing financing constraints and increasing R&D investment. The effect is stronger among firms with better resources, governance, and digitalization, and in regions with stronger institutional environments; it is also more evident in non-heavy-polluting and non-manufacturing sectors. While the policy mix raises both innovation quantity and quality, it does not significantly improve total factor productivity, indicating a “weak Porter effect.” These findings provide micro-level evidence on GFP–ETP synergy and inform the refinement of green finance, environmental tax design, and firm-level green transition policies. Full article

Against the background of climate uncertainty, market volatility, and evolving regulatory environments, firms embedded in agricultural value chains face increasing pressure to maintain sustainable growth. This study examines China’s A-share-listed Traditional Chinese Medicine (TCM) firms to explore how internal organizational factors and external institutional conditions jointly shape firm-level sustainable growth capability. This setting is characterized by strong ecological dependence, strict quality regulation, deep policy embeddedness, and supply-chain sensitivity. Drawing on the resource-based view, dynamic capability theory, contingency theory, and the institutional environment perspective, this study applies fuzzy-set qualitative comparative analysis (fsQCA) to 2023 cross-sectional data from 59 A-share-listed TCM firms. The results show that no single condition constitutes a necessary condition for high sustainable growth capability. Instead, high sustainable growth capability is mainly achieved through three configurational pathways: innovation-driven growth, policy-supported development, and market-responsive strategy. Low sustainable growth capability follows asymmetric pathways, mainly reflected in the mismatch between innovation capability and the institutional environment, and the coexistence of high financing constraints and low agility response. The findings indicate that sustainable growth capability is not the result of isolated factors, but a context-specific configurational outcome shaped by innovation, agility response, internationalization, equity governance, ESG performance, government support, marketization level, and financing conditions. This study provides a configurational explanation for growth research on agriculture-related firms and offers differentiated pathway implications for managers and policymakers. Full article

Nowadays, Global Value Chains (GVCs) play a vital role in job creation, income generation, knowledge diffusion, and productivity growth. However, significant disparities exist across countries in terms of their integration into GVCs, and Tunisia is no exception to this pattern. In this regard, the question about factors that influence GVCs’ participation is yet to be discussed, to formulate and implement appropriate strategies and reforms. Thus, using firm-level data from the 2025 World Bank Enterprise Survey, this paper examines the role of female leadership and innovation in determining Tunisian firms’ participation in GVCs. Participation in GVCs is captured by a dummy variable indicating the firm’s export and import status. Estimation results from the logit model show that female representation in decision-making positions significantly increases the likelihood of firms’ participation in GVCs. The results also highlight the importance of process innovation in GVC participation, while product innovation appears to have no significant effect. Notably, when firms combine both types of innovation, their likelihood of joining GVCs increases further. Regarding control variables, firm size appears to be an important determinant, as larger firms display a greater tendency to participate in GVCs. The findings further indicate that firm certification and foreign equity participation significantly promote integration into GVCs, while corruption constitutes a major constraint on the integration of Tunisian firms. From a policy perspective, these findings highlight the need to rethink industrial policies, with a stronger focus on process innovation as a key lever of productive sector modernization. Achieving this transformation also requires the development of an inclusive policy ecosystem that supports meaningful and sustainable progress in female’s leadership representation. Full article

Toxicological testing for drugs of abuse (DOAs) is an essential tool for healthcare practitioners and law enforcement agencies. Oral fluid (OF) is an alternative biological fluid for detecting recent DOA intake and is widely employed in forensic investigations. In the current study, a relatively novel and “green” fabric phase sorptive extraction (FPSE) procedure for sample preparation was coupled to liquid chromatography–tandem mass spectrometry (LC–MS/MS) to provide simplicity, cost-effectiveness, rapidity, low solvent consumption, and high analytical performance for the quantitative determination of ten commonly encountered DOAs and metabolites: amphetamine, benzoylecgonine, cocaine, codeine, ecgonine methyl ester, methadone, methamphetamine, 3,4-methylenedioxyamphetamine, 6-monoacetylmorphine, and morphine. The FPSE procedure was optimized by testing different filters, pH, extraction time, and solvents. The validated method demonstrated excellent linearity for all analytes, selectivity, acceptable precision, and high sensitivity (ranges for limits of detection (LODs) and quantification (LOQs) were 0.01–2 ng/mL and 0.03–6 ng/mL, respectively). Autosampler and short-term freeze stability exceeded 95% and 90% for all analytes, respectively. Overall, the combination of FPSE with LC–MS/MS provided a sensitive, selective, and environmentally friendly innovative analytical approach for the determination of DOA in OF and is suitable for both screening and confirmatory forensic and clinical applications. Full article

To address the technical challenges associated with complex connection configurations and excessively long lap zones in the industrialized and prefabricated construction of reinforcements, this study proposes a novel parallel-lap splice that incorporates a third overlapping reinforcement. This innovative design offers several advantages, including neat ends, ease of construction, and enhanced economic efficiency. An experimental investigation was conducted to evaluate the effects of this new splice on the flexural behavior of reinforced concrete (RC) beams, with lap length (l_l) as the key variable (l_l = 64d, 40d, and 25d). A total of nine simply supported RC beams (three groups of three specimens each), all incorporating parallel-lap splices, were tested under four-point bending. The key mechanical properties were analyzed, including the mechanical characteristics, failure modes, flexural capacity, bending stiffness, and maximum flexural crack width. The experimental and analytical results reveal that RC beams with the new parallel-lap splice exhibit a distinctive “one primary + two secondary” crack pattern, characterized by a dominant flexural crack at midspan and secondary cracks at the ends of the lap zone. At the ultimate limit state, specimens with l_l = 64d experienced concrete crushing at the top surface of the midspan while those with l_l = 40d and l_l = 25d did not. Additionally, the l_l = 64d and l_l = 40d beams showed slight strength hardening, whereas the l_l = 25d beams exhibited rapid strength degradation. In terms of load-bearing capacity, both the l_l = 64d and l_l = 40d beams met the requirements specified in current design codes, while the l_l = 25d specimens showed a reduction in capacity exceeding 20%. Under serviceability limit states, midspan deflections and maximum crack widths for the l_l = 64d, l_l = 40d, and l_l = 25d specimens were found to fully comply with, marginally satisfy, and fail to meet the requirements of the design code, respectively. Based on these findings, as well as regression analysis of the relationship between peak load and lap length, it is recommended that a reasonable lap length for the proposed parallel-lap splice be taken as 60d, with a lap length correction factor of 1.5. Full article

This article offers a theoretically nuanced and empirically grounded investigation into the paradoxical afterlife of classical versification within the poetic practices of the Russian and Soviet avant-garde. Challenging the persistent historiographic narrative that equates avant-garde poetics with an unequivocal rupture from tradition, the study demonstrates that canonical metrical forms—most notably iambic tetrameter—continued to operate as structurally productive, albeit critically reconfigured, elements within experimental verse. Drawing on a broad corpus encompassing poetic manifestos, verse texts, and prose writings by Vladimir Maiakovskii, Ilia Sel’vinskii, Semen Kirsanov, and Nikolai Aseev, the authors combine close formal analysis with quantitative prosodic modeling, including linguistic and speech models derived from Kolmogorov–Taranovsky verse theory. The article argues that avant-garde poets did not simply negate inherited metrics but subjected them to a process of internal recomposition, shifting attention from meter as a fixed scheme to rhythm as a dynamic, semantically charged construct. While rhythmic innovation is shown to be consciously engineered in verse, the analysis of verse-like fragments in prose reveals persistent, unconscious attachments to “classical” rhythmic patterns, particularly the Pushkinian alternating rhythm. This tension between declarative rejection and latent continuity illuminates the avant-garde’s distinctive mode of negotiating tradition: not abolishing it, but instrumentalizing it within a broader project of total artistic reorganization. The study thus reframes avant-garde prosody as a site where innovation and inheritance coexist in a state of productive contradiction, reshaping our understanding of modernist poetic technique. Full article

Hybrid role-playing games are increasingly used to support democratic learning, yet there is limited empirical evidence on how such hybrid designs function across contexts. This study analyses the pedagogical and deliberative effects of Empaville, a hybrid role-playing game designed to simulate a green participatory budgeting process by embedding deliberation, competition, and voting within a fictional urban setting. We analyse six implementations conducted between 2023 and 2025 in the United Kingdom and Morocco (N = 118), combining participant observation with post-game survey data. The analysis examines role activation, phase-level enjoyment, and participants’ reported learning and deliberative experiences, using descriptive statistics, non-parametric tests, effect size measures, and qualitative thematic analysis. Across contexts, participants report that the game supports perspective-taking, intellectual humility, and constructive engagement with disagreement, while perceived learning and participation intensity vary more substantially across individuals and sessions. Cross-national comparisons reveal some statistically detectable differences in how specific phases are experienced, particularly voting, but effect sizes are generally small or trivial, indicating limited substantive divergence overall. These findings suggest that hybrid role-playing games can foster deliberative learning outcomes in short educational interventions, while highlighting the importance of distinguishing between enjoyment, engagement, and perceived pedagogical value. The study contributes an exploratory but systematic mixed-methods evaluation suitable for small-N pedagogical interventions without causal claims. Full article