Search Results (357)

Traffic flow prediction (TFP) is a fundamental component of intelligent transportation systems (ITS) that supports traffic management, congestion mitigation, and route planning. Although recent advances in deep learning have demonstrated strong capability in modeling non-linear spatio-temporal correlations, most existing approaches rely on centralized training paradigms, which incur substantial communication costs, high computational overhead, and significant data privacy risks. Federated Learning (FL) has emerged as a promising alternative by enabling decentralized model training across distributed clients while reducing privacy risks and communication overhead. However, existing FL-based TFP frameworks often employ local models with limited capacity to capture complex spatio-temporal dependencies, and their reliance on the conventional FedAvg aggregation approach restricts robustness under heterogeneous traffic data distributions. To address these challenges, this study proposes the FedASTAM framework, which integrates FL with the Adaptive Spatio-Temporal Attention-based Multi-Model (ASTAM) to effectively model complex and non-linear spatio-temporal traffic correlations in a data-local FL setting. Within FedASTAM, the road network is divided into sub-regions using spectral clustering, allowing each sub-region to train a local ASTAM model tailored to localized and heterogeneous traffic patterns. At the central server, locally trained models are aggregated using seven aggregation schemes, including the classical FedAvg, to optimize global model updates while preserving data locality. Extensive experiments conducted on two real-world benchmark datasets, PeMS04 and PeMS08, demonstrate that FedASTAM achieved strong and stable predictive performance while keeping raw data localized throughout the federated training process. The results further indicate that the aggregation approaches used in the proposed FedASTAM framework generally outperform classical FedAvg under heterogeneous traffic conditions, highlighting FedASTAM as an effective approach for traffic flow prediction in complex, distributed ITS environments. Full article

In the context of China’s pursuit of high-quality economic development, enhancing agricultural productivity is crucial for ensuring food security and promoting common prosperity. This paper constructs a systematic IV-LP-ACF-SAR econometric framework to analyze agricultural Total Factor Productivity (TFP) growth using panel data from 31 Chinese provinces spanning 2014 to 2023 (n = 341 observations). The framework employs the instrumental variable (IV)-based Levinsohn–Petrin (LP) proxy variable method under the Ackerberg–Caves–Frazer (ACF) system to estimate a Translog production function while addressing endogeneity using multiple spatial weight matrices. TFP growth is decomposed into technical change (TC), technical efficiency (EC), and scale efficiency (SC). A Spatial Autoregressive (SAR) model with Dynamic Common Correlated Effects (DCCE) explores spatial spillover effects and regional heterogeneity. Results show that China’s agricultural TFP remained largely stagnant from 2014 to 2023 with an average annual growth rate of −0.18%, where technical efficiency decline (−0.33% annually) was the main constraint. Technical change remained neutral, while scale efficiency contributed positively (+0.15% annually). Mechanization showed the highest output elasticity (0.99), while fertilizers, pesticides, and labor exhibited negative marginal returns. Spatial analysis revealed significant negative scale efficiency spillovers with regional patterns of “scale synergy in the Northeast/Northwest” and “efficiency synergy in East/North China.” These findings suggest that productivity policy should shift toward a dual-driver model combining efficiency enhancement and optimal scaling, with differentiated regional policies and inter-provincial coordination mechanisms necessary to mitigate negative spillovers and enhance sustainable agricultural growth quality. Full article

Taking the rail transit transfer stations in Qingyang, Wuhou, and Chenghua Districts of Chengdu as the research objects, this study constructs a static-dynamic coupled analytical framework by integrating the input-oriented three-stage super-efficiency SBM model and the output-oriented Malmquist-Luenberger (ML) index to systematically evaluate rail transit transfer efficiency. The findings reveal that the transfer efficiency of Chengdu Metro exhibited a fluctuating growth pattern from 2017 to 2023, with significant variations corresponding to periods of network expansion and operational adjustments. Improvements in technical efficiency and management optimization have been key drivers of overall efficiency gains. The three-stage super-efficiency SBM model effectively filters out the impacts of environmental variables and random noise, uncovering inter-station efficiency disparities and resource redundancy issues. Decomposition of the ML index indicates that both technical efficiency and technological progress jointly drive total factor productivity (TFP) changes. On average, technical efficiency has been the more stable and prominent contributor to productivity growth. However, the reasons for TFP declines at certain stations are varied; some under-performed due to lagging technological progress, while others faced constraints in technical or scale efficiencies. The study confirms that the synergistic application of the three-stage model and the ML index can accurately identify bottlenecks and provide theoretical support and practical pathways for optimizing resource allocation and dynamic management in urban rail transit systems. Findings and methods from Chengdu’s practice provide a replicable paradigm for evaluating, planning and optimizing rail transit transfer hubs in Chinese cities at different development stages, and offer empirical references for advancing urban public transport and sustainable development of comprehensive transportation systems. Full article

While it is a global imperative that firms should achieve superior environmental, social, and governance (ESG) performance, the specific impact of ESG on export product quality remains under-explored. Based on stakeholder theory and principal–agent theory, this paper utilizes a sample of Chinese listed companies and the High-Dimensional Fixed Effects (HDFE) Model to empirically examine the impact and underlying mechanisms of ESG performance on export product quality. The results indicate a U-shaped relationship between ESG performance and export product quality, a non-linear correlation that has received limited attention in the previous literature. This U-shaped relationship is more pronounced among state-owned enterprises (SOEs), firms producing non-high-tech products, and those in heavy-polluting industries. Mechanism analysis reveals that ESG performance influences export product quality primarily through three channels: innovation levels, total factor productivity (TFP), and supply chain stability. By unveiling these non-linear dynamics and their underlying pathways, this study provides a novel theoretical framework and critical empirical evidence that reconcile conflicting views on ESG effects. These findings offer important insights for policymakers and exporters seeking to align ESG practices with export objectives, thereby contributing to more sustainable and high-quality development of foreign trade in China and beyond. Full article

Total factor productivity (TFP) serves as the primary driver of high-quality development and a key determinant for the sustainable growth of Japan’s beef cattle industry. This study analyzes panel data from nine agricultural regions in Japan, covering the period from 2004 to 2022, and applies the Malmquist-Luenberger index model to measure and decompose TFP in the sector. It utilizes various methods, including the Dagum Gini coefficient, kernel density estimation, and Markov chains, to examine regional disparities and dynamic changes. Additionally, the study applies the geographic detector and spatial Durbin model to explore the spatiotemporal evolution and influencing factors. The results show that: (1) From 2004 to 2022, TFP in Japan’s beef cattle industry steadily declined, accompanied by growing regional imbalances. The Tokai region was the only area to experience positive TFP growth, while other regions generally saw declines. (2) The spatial disparity in TFP growth has increased, with an intensified imbalance and a widening gap between regions. TFP distribution is becoming more “multipolar,” with considerable dynamic mobility. (3) TFP exhibits a general positive spatial correlation. Geographic detector analysis reveals that factors such as the number of agricultural research and development personnel, fiscal support, industrial agglomeration, feed production capacity, and labor productivity are the key drivers behind spatial TFP differentiation, reflecting a complex interplay of multidimensional factors. (4) Industrial agglomeration, fiscal support, and the number of agricultural R&D personnel exhibit significant spatial positive spillover effects, indicating that coordinated regional progress is essential for fostering the sustainable and healthy development of the beef cattle industry. This study provides theoretical and empirical support for the sustainable development of Japan’s beef cattle industry and offers policy recommendations to enhance the economic growth quality of the beef cattle industries in both Japan and China. Full article

China’s dual pursuit of a “Digital China” and its carbon-neutral goals has driven a coordinated strategy of digitalization and green transformation. Yet the extent to which firms have realized this synergy—and its effect on total factor productivity (TFP)—remains underexplored. Using panel data from 2011 to 2025 on all A-share listed companies, we construct a composite index of digital–green coordination and estimate firm-level TFP via the Levinsohn–Petrin method. Employing fixed-effects panel regressions and mediation analyses, we find the following: (1) the digital–green synergy significantly enhances TFP growth, with robustness confirmed across alternative measures, propensity score matching, city fixed effects, and instrumental variable approaches; (2) this effect is stronger for non-SOEs and firms with higher baseline TFP and exhibited an “inverted-U” pattern over China’s 13th and 14th Five-Year Plans; (3) corporate social responsibility (CSR), cost stickiness reduction, and green technological innovation each mediate this relationship—CSR and cost stickiness play larger roles in SOEs, while green innovation mediates across all firm types and TFP levels, also showing an “inverted-U” temporal trend; and (4) over time, CSR’s mediating effect wanes in the 14th Five-Year period, cost stickiness mediation gradually declines, and green innovation mediation is continually strengthened. These findings provide evidence of the association between digital–green alignment and firm productivity in China, using an index that summarizes the joint orientation toward digitalization and greening. Full article

The misallocation of renewable (RE) and non-renewable energy (NRE) resources may lead to the inefficiency of economic development, thereby hindering the achievement of sustainable development goals. Basing data on 282 Chinese cities during 2005–2021, a relative factor price distortion coefficient was employed to estimate the degree and direction of resource misallocation (RM) for RE, NRE, capital, and labor at both the aggregate city level and across four disaggregated city categories. Output gaps and efficiency losses are further quantified by incorporating RM analysis into the economic growth accounting framework, revealing significant heterogeneity in RM across cities. Findings show that (1) RE and labor misallocation exceed those of NRE and capital at the city level. RE misallocation is dominant in energy misallocation. There exists an underallocation of RE, NRE, and labor, while capital is overallocated. (2) Renewable energy input and output (RE-IO) cities exhibit the highest overall RM (32.1%), whereas renewable energy input (RE-Input) cities possess the lowest ones (21.2%). Four city types demonstrate an underallocation of RE and an overallocation of capital. (3) Both output gaps and efficiency losses are on the rise. Output changes sources are transferred from the variations in factor inputs to those in total factor productivity (TFP). The contribution from the RM changes is limited. The results provide a reference for reducing RM and achieving energy transition. Full article

Background/Objectives: We have previously demonstrated that fatty acid oxidation (FAO) enzymes physically and functionally interact with electron transfer chain supercomplexes (ETC-SC) at two contact points. The FAO trifunctional protein (TFP) and electron transfer flavoprotein dehydrogenase (ETFDH) interact with the NADH⁺-binding domain of ETC complex I (com I) and the core 2 subunit of complex III (com III), respectively. In addition, the FAO enzyme very-long-chain acyl-CoA dehydrogenase (VLCAD) interacts with TFP. These interactions define a functional FAO-ETC macromolecular complex (FAO-ETC MEC) in which FAO-generated NADH⁺ and FADH₂ can safely transfer electron equivalents to ETC in order to generate ATP. Methods: In this study, we use multiple mitochondrial functional studies to demonstrate the effect of added VLCAD protein on mutant mitochondria. Results: We demonstrate that heart mitochondria from a VLCAD knockout (KO) mouse exhibit disrupted supercomplexes, with significantly reduced levels of TFPα and TFPβ subunits, electron transfer flavoprotein a-subunit (ETFα), and NDUFV2 subunit of com I in the FAO-ETC MEC. In addition, the activities of individual oxidative phosphorylation (OXPHOS) enzymes are decreased, as is the transfer of reducing equivalents from palmitoyl-CoA to ETC (FAO-ETC flux). However, the total amount of these proteins did not decrease in VLCAD KO animals. These results suggest that loss of VLCAD affects the interactions of FAO and ETC proteins in the FAO-ETC MEC. Reconstitution of VLCAD-deficient heart mitochondria with recombinant VLCAD improved the levels of FAO-ETC MEC proteins and enzyme activities, as well as restoring FAO-ETC flux. It also reduced mitochondrial ROS levels, previously demonstrated to be elevated in VLCAD-deficient mitochondria. In contrast, incubation of VLCAD KO mitochondria with two VLCADs with mutations in the C-terminal domain of the enzyme (A450P and L462P) did not restore FAO-ETC MECs. Conclusions: These results suggest that VLCAD is a necessary component of the FAO-ETC MEC and plays a major role in assembly of the macro-supercomplex. These studies provide evidence that both the level of enzyme and its structural confirmation are necessary to stabilize the FAO-ETC MEC. Full article

The mobility of data factors and the adoption of a collaborative innovation framework are key drivers influencing the gaps in total factor productivity (TFP) among enterprises in the digital economy. Using panel data from Chinese A-share listed companies between 2006 and 2022, this study empirically demonstrates how data factor flow reduces TFP gaps. The findings reveal that data factor flow enhances TFP convergence by facilitating knowledge diffusion, improving information transmission, and boosting innovation efficiency. However, the heterogeneity in enterprise RD efforts limits this convergence effect, highlighting the importance of collaborative innovation. The study further shows that the impact of data factor flow is more significant in smaller, privately owned enterprises in the eastern regions and in industries with low to high technology intensity and high market concentration. Key insights include (1) a positive synergy between government data openness policies and enterprise data flow, which reinforces the narrowing of TFP gaps; (2) a nonlinear relationship between data flow and TFP gaps, suggesting an optimal range for its maximum impact. The study concludes that an integrated framework optimizing both data governance and collaborative innovation ecosystems can foster innovation diffusion and support productivity-based competition. These findings provide valuable insights for innovation policy formulation and strategic decision-making in the digital economy. Full article

Tremella mesenterica, commonly known as the yellow brain or golden jelly fungus, has been traditionally used for its medicinal properties. In this study, we elucidated the structural characteristics of T. mesenterica polysaccharide (TMP) and evaluated its potential moisturizing mechanism in vitro, comparing it to Tremella fuciformis polysaccharide (TFP) and hyaluronic acid (HA). TMP was isolated through enzyme assisted extraction and it has a molecular weight (MW) of approximately 143 kDa. We investigated the composition of mannose, xylose, glucuronic acid, and glucose as a ratio of 59.8 ± 0.3, 24.0 ± 1.2, 11.0 ± 0.8, 5.2 ± 0.0, respectively. Through methylation and GC-MS analysis, we discovered TMP was composed of a main chain of β-(1→3)-linked mannopyranoside, substituted with various side chains such as xylopyranoside, glucuronopyranoside, glucopyranoside at the C-2 or C-4 positions of the backbone. TMP upregulated the expression of key moisturizing-related factors compared to TFP and HA, such as aquaporin-3 (AQP3) with 55% and 57% at 25 and 50 μg/mL and hyaluronic acid synthase-2 (HAS2) with 22% at 25 μg/mL, as confirmed through qRT-PCR analysis. Additionally, TMP significantly enhanced the expression of filaggrin (FLG), a critical protein involved in skin barrier function, with 22% at 25 μg/mL. Immunocytochemistry (ICC) analysis further revealed that TMP achieved the highest improvement in hyaluronic acid synthase-3 (HAS3) protein levels by 475% at 50 μg/mL. While further in vivo studies are required to substantiate its functional moisturizing efficacy, these findings suggest that TMP serves as a promising moisturizing agent. The structural and functional properties of TMP provide a potential foundation for its application in diverse industries, including cosmetics, food, biopolymers, and pharmaceuticals. Full article

Against the dual demands of green transformation and digital integration in the manufacturing industry, green value co-creation has become a core pathway for enterprises to achieve sustainable development. However, the role of artificial intelligence (AI) in driving green value co-creation remains under explored, especially in the context of Chinese manufacturing. To enrich this research, this study aims to investigate the impact of AI development on corporate green value co-creation and its intrinsic mechanism. This study draws on panel data of listed manufacturing enterprises listed on China’s Shanghai and Shenzhen A share markets spanning the period 2015–2024, and employs multiple regression and negative binomial regression as research methodologies to empirically examine the impact of AI development on corporate green value co-creation and its underlying mechanisms. The results demonstrate that: AI development exerts a significantly positive effect on manufacturing enterprises’ green value co-creation, which is achieved by enhancing firms’ technological spillover capacity and total factor productivity (TFP); financing constraints negatively moderate the aforementioned relationship, while corporate influence plays a positive moderating role; heterogeneity analysis reveals that this impact is more pronounced for enterprises under voluntary regulation, state-owned enterprises (SOEs), and high-pollution enterprises. This study elucidates AI’s role and mechanism in corporate green development at the micro level, provides empirical evidence for related research, and offers practical insights to promote enterprise AI advancement and green value co-creation. Full article

The urgent need for sustainable innovation in the construction industry necessitates a reevaluation of how architecture engages with materials and fabrication processes. This paper introduces tailored fiber placement (TFP) as a novel fabrication method with significant potential for advancing sustainable architectural practice. Originally developed for aerospace and automotive applications, TFP enables stress-oriented fiber alignment, offering precision, material efficiency, and lifecycle-conscious design opportunities. To articulate these capabilities, the paper examines four case studies at multiple scales. Ranging from small-scale seating to medium-scale façade components, these examples demonstrate TFP’s ability to enable mold-less forming and integrative fabrication in support of sustainable construction. Through digitally programmed fiber orientations, the cases achieve both structural and geometric requirements while minimizing waste and improving workflow efficiency. This research positions TFP as a material-aware and performance-driven approach to sustainable architectural production. By bridging material, design, and fabrication, TFP contributes to more circular, adaptable, and efficient construction systems. Full article

Washingtonia filifera is important for its ecological, economic, cultural, horticultural, ornamental, and medicinal potential. Elicitation of in vitro cultures presents a promising and efficient method for the large-scale production of valuable bioactive compounds. This study assessed the effect of chitosan concentration (0, 20, 40, 60, 80, 100 mg L⁻¹) on biomass growth [fresh weight (FW), dry weight (DW)] and phytochemical profile [total phenolic content (TPC), total flavonoid content (TFC), DPPH antioxidant activity, total phenolic productivity (TPP), total flavonoid productivity (TFP)] in W. filifera callus and cell suspension cultures. Among different plant growth regulator combinations tested, 3 mg L⁻¹ 2,4-D + 0.5 mg L⁻¹ 2ip gave higher callus induction (90%) (MS medium, 12 weeks). A maximum growth curve (FW: 180 mg) of cell suspension culture was achieved 7 weeks after initiation (shaker at 90 rpm for 24 h). Cell suspension exhibited higher FW, DW, TPC, TFC, DPPH, TPP, and TFP than callus, while flavonoid production was higher than phenolic production. FW and DW were higher in both systems, with 40 mg L⁻¹ chitosan. Chitosan at 60 mg L⁻¹ best enhanced the phytochemical profile of both the 4-week solidified callus and the 7-week liquid cell suspension (TPC: 29.9 and 32.1 mg GAE g⁻¹ DW; TFC: 40.5 and 56.1 mg QE g⁻¹ DW; TPP: 969.2 and 1122.6 mg L⁻¹; TFP: 1313.9 and 1521.7 mg L⁻¹; DPPH: 87.4 and 92.3%), respectively, while 40 mg L⁻¹ chitosan was equally effective regarding DW, TFC, and TFP in cell suspension. Chitosan elicitation provides a powerful strategy to upregulate phenolic and flavonoid biosynthesis in W. filifera in vitro systems, conferring superior antioxidant potential. The identification of peak elicitation parameters (chitosan concentration, exposure time) allows for the targeted enhancement of bioactive compound yields, suggesting a viable path for industrial bioproduction and commercialization in pharmaceuticals, nutraceuticals, and functional foods, leveraging bioreactor technology for efficient scale-up. Full article

The 2025 Ebola outbreak that ravaged the Bulape Health District (HD) in Kasai, Democratic Republic of Congo (DRC), was tackled using the incident management system (IMS) model. The Bulape HD is located in the Mweka territory, which has experienced two Ebola epidemics: one in 2007 and another in 2008. The IMS comprises seven strategies recommended for an effective response to an Ebola outbreak: (i) thorough investigation, (ii) strengthening infection prevention and control measures in the community, (iii) ensuring that medical care is provided by experienced professionals, (iv) strengthening risk communication and community engagement (RCCE), (v) ring vaccination, (vi) operational research, and (vii) anchoring interventions in the existing health system. We share our experience implementing these seven strategies and compare them with those utilized during three previous Ebola outbreaks. This paper describes our achievements, the resulting benefits, and the factors that facilitated the implementation of the aforementioned strategies. A literature review and interviews were conducted. The atlas.ti 22 software was used for data analysis. Implementing these seven strategies contributed to an effective response, largely due to the experience and expertise of those involved but also thanks to the support of technical and financial partners (TFPs) and the engagement of the local community. Challenges such as geographical accessibility, the fragile health system, the community’s strong attachment to traditional practices, and negative reactions to healthcare—which was widely discredited, with many of those involved expressing a lack of faith in its effectiveness—were major obstacles. To overcome these challenges, an integrated approach was utilized, combining a rapid comprehensive response with deep and respectful community engagement. The support and alignment of TFPs were invaluable during this process. The RCCE pillar proved key to successful IMS implementation. Our experiences will be useful during the next Ebola outbreak in the DRC; additionally, they may also help to inform the response to similar outbreaks in other countries. Full article

Optimizing resource allocation is crucial for enhancing Total Factor Productivity (TFP). This study investigates the impact of differentiated industrial land supply (DILS) on industrial Total Factor Productivity (ITFP), a topic essential for optimizing territorial spatial layouts and promoting high-quality industrial development. Using panel data from 282 Chinese cities (2007–2021) and a Spatial Durbin Model (SDM), we analyze the spatiotemporal effects of this factor. The results indicate a weakening trend in DILS over time, with a spatial pattern of lower intensity in the east and higher intensity in the west, while ITFP shows an upward trend, with higher levels in the east. Nationally, increased DILS impedes ITFP growth, a finding with robust implications for alternative approaches. This impact demonstrates significant spatiotemporal heterogeneity: at the macro-scale, eastern China shows an inverted U-shape, while the central and western regions exhibit negative impacts. At the meso-scale, the Yangtze River Economic Belt shows negative effects, while the Yellow River Basin displays an inverted U-shape. At the micro-scale, major city clusters show varied relationships (inverted U-shaped, positive, or negative). We conclude that DILS generally hinders ITFP, with effects intensifying and varying significantly across narrowing spatial scales, underscoring the need for region-specific land policies to support high-quality industrial development. This study enriches our theoretical understanding of how resource allocation affects ITFP and provides practical guidance for optimizing industrial land use. Full article