Search Results (321)

The main purpose of this study is to understand the potential determinants of sustainable field crop farm productivity. This paper considers a multi-input, multi-output production technology to estimate the effects of aridity on farm-level productivity using a stochastic input distance function. By isolating the respective weather components of agricultural total factor productivity (TFP), we can better assess the impact on productivity of adopting various technologies and farm practices that might otherwise be masked by changing climate conditions or weather shocks. We make use of data from Phase 3 of the United States Department of Agriculture (USDA) Agricultural Resource Management Survey (ARMS) between 2006 and 2020. We supplement this estimation using field crop farm productivity determinants, including technology adoption and farm practice variables derived from the ARMS Phase 2 data. We identify several factors that affect farm productivity, including many practices that help farmers make more sustainable use of natural resources. The results show that adopting yield monitoring technology, fallowing in previous years, adding or improving tile drainage, and contour farming each improved farm productivity. In particular, during our study period, conservation tillage increased by over 300% across states on average. It is estimated to increase productivity level by approximately 3% for those adopting this practice. Critically, accounting for local weather effects increased the estimated productivity of nearly all farm practices and increased the statistical significance of several variables, indicating that other TFP studies that did not account for climate or weather effects may have underestimated the technical efficiency of farms that adopted these conservation practices. However, the results also show the impacts can be heterogeneous, with effects varying between farms located in the U.S. northern or southern regions. Full article

With the deceleration of China’s economic growth, the crude economic model will progressively diminish in its competitive edge, thereby posing challenges for state-level economic and technological development zones (ETDZs) in terms of transitioning their development model and grappling with low levels of total factor productivity (TFP). This study aims to evaluate the TFP of prominent cities in China, examine the influence of the establishment of state-level ETDZs on urban TFP, and investigate the moderating effect of transportation infrastructure on this relationship. The results show that the aggregate TFP of Chinese urban areas declined from 1999 to 2020, a trend linked to structural economic adjustments and persistent underutilization of capital in several regions. The establishment of state-level ETDZs has been found to exert a notable positive influence on regional TFP. The presence of transportation infrastructure plays a moderating role in facilitating state-level ETDZs, thereby enhancing regional TFP. Among various modes of transportation, highways and railways are particularly prominent in this regard. These conclusions provide a theoretical basis and decision-making reference for further unleashing the policy potential of development zones in China. Full article

CD8+ T lymphocytes (CTLs) act as serial killers of infected or malignant cells by releasing large amounts of interferon-gamma (IFNγ) and granzymes. Although IFNγ is a pleiotropic cytokine with diverse immunomodulatory functions, its precise spatiotemporal regulation and role in CTL-mediated cytotoxicity remain incompletely understood. Using wild-type and granzyme B-mTFP knock-in mice, we employed a combination of in vitro approaches, including T cell isolation and culture, plate-bound anti-CD3e stimulation, degranulation assays, flow cytometry, immunofluorescence, and structured illumination microscopy, to investigate IFNγ dynamics in CTLs. IFNγ expression in CTLs was rapid, transient, and strictly dependent on T cell receptor (TCR) activation. We identified two functionally distinct IFNγ-producing subsets: IFNγ^high (IFNγ^hi) and IFNγ^low (IFNγ^lo) CTLs. IFNγ^hi CTLs exhibited an effector/effector memory phenotype, significantly elevated CD107a surface expression (a marker of lytic granule exocytosis), and higher colocalization with cis-Golgi and granzyme B compared to IFNγ^lo CTLs. Furthermore, CRTAM, an early activation marker, correlated with IFNγ expression in naive CTLs. Our findings establish a link between elevated IFNγ production and enhanced CTL cytotoxicity, implicating CRTAM as a potential regulator of early CTL activation and IFNγ induction. These insights provide a foundation for optimizing T cell-based immunotherapies against infections and cancers. Full article

This study presents AD-MRCNN, an advanced deep learning framework for automated atmospheric front detection that addresses two critical limitations in existing methods. First, current approaches directly input raw meteorological data without optimizing feature compatibility, potentially hindering model performance. Second, they typically only provide frontal category information without identifying individual frontal systems. Our solution integrates two key innovations: 1. An intelligent adapter module that performs adaptive feature fusion, automatically weighting and combining multi-source meteorological inputs (including temperature, wind fields, and humidity data) to maximize their synergistic effects while minimizing feature conflicts; the utilized network achieves an average improvement of over 4% across various metrics. 2. An enhanced instance segmentation network based on Mask R-CNN architecture that simultaneously achieves (1) precise frontal type classification (cold/warm/stationary/occluded), (2) accurate spatial localization, and (3) identification of distinct frontal systems. Comprehensive evaluation using ERA5 reanalysis data (2009–2018) demonstrates significant improvements, including an 85.1% F1-score, outperforming traditional methods (TFP: 63.1%) and deep learning approaches (Unet: 83.3%), and a 31% reduction in false alarms compared to semantic segmentation methods. The framework’s modular design allows for potential application to other meteorological feature detection tasks. Future work will focus on incorporating temporal dynamics for frontal evolution prediction. Full article

Oral cancer, the most common form of head and neck cancer, is worldwide a serious public health problem. Most patients present a locally advanced disease, and face poor prognosis, even with multimodality treatment. They may also develop second primary tumors in the entirety of their upper aerodigestive tract. The most altered signaling pathways are the PI3K/AKT/mTOR, TP53, RB, and the WNT/β-catenin pathways. Genomic and molecular cytogenetic analyses have revealed frequent losses at 3p, 8p, 9p, and 18q, along with gains at 3q, 7p, 8q, and 11q, and several genes frequently affected have been identified, such as TP53, CCND1, CTTN, CDKN2A, EGFR, HRAS, PI3K, ADAM9, MGAM, SIRPB1, and FAT1, among others. Various epigenetic alterations were also found, such as the global hypomethylation and hypermethylation of CDKN2A, APC, MGMT, PTEN, CDH1, TFP12, SOX17, GATA4, ECAD, MGMT, and DAPK. Several microRNAs are upregulated in oral cancer, including miR-21, miR-24, miR-31, miR-184, miR-211, miR-221, and miR-222, while others are downregulated, such as miR-203, miR-100, miR-200, miR-133a, miR-133b, miR-138, and miR-375. The knowledge of this molecular pathogenesis has not yet been translated into clinical practice, apart from the use of cetuximab, an EGFR antibody. Oral tumors are also genetically heterogenous and affect several pathways, which means that, due to the continuous evolution of these genetic alterations, a single biopsy is not sufficient to fully evaluate the most adequate molecular targets when more drugs become available. Liquid biopsies, either resorting to circulating tumor cells, extracellular vesicles or cell-free nucleic acids, have the potential to bypass this problem, and have potential prognostic and staging value. We critically review the current knowledge on the molecular, genetic and epigenetic alterations in oral cancer, as well as the applications and challenges of liquid biopsies in its diagnosis, follow-up, and prognostic stratification. Full article

The aim of this study is to compare the environmental impact of composites reinforced with flax fiber technical embroidery and traditional woven fabric in order to provide conclusions supporting composite manufacturer management in making technology selection decisions. The research objectives are to identify the key stages in the life cycle of composites, from raw material acquisition to end-of-life; determine the environmental impact of each stage, with a particular focus on processes with the largest contribution to overall result; compare the environmental impact of embroidery-reinforced composites with traditional woven fabric-reinforced composites; propose strategies to minimize the negative environmental impact of composites, including modifying the component set and optimizing the production process. The method involves experimental research including the production of technical embroidery-based composites with varying stitch lengths and woven fabric-reinforced composites. The tensile strength of the composites was evaluated. Subsequently, life cycle assessment was conducted for each material according to the relevant ISO standards. The results presented in this paper provide a comprehensive assessment of the environmental performance of technical embroidery-reinforced composites and identify directions for future research in this field. Full article

In the context of China’s “dual carbon” goals and rising green trade barriers, green transformation is key to improving total factor productivity (TFP) and competitiveness in marine industries. This study uses panel data of Chinese listed marine enterprises (2014–2023) and a multidimensional fixed-effects model to examine how green innovation, export, and R&D investment jointly affect TFP. Results show that (1) green innovation has an inverted “S”-shaped nonlinear effect on TFP, with marginal returns rising, then accelerating, and finally declining; (2) positive synergies exist between green innovation and both exports and R&D, while the export–R&D interaction negatively affects TFP, indicating coordination challenges.; and (3) ownership heterogeneity matters, as state-owned enterprises benefit from stronger institutional support, mitigating negative effects, while private firms are more vulnerable due to weaker green technology mechanisms. This study emphasizes green innovation as a driver for sustainable productivity growth in marine enterprises and suggests policies that improve institutional frameworks, incentives, and resource allocation to support high-quality green innovation. Full article

As pivotal nodes in maritime logistics networks, ports face mounting pressure to reconcile economic growth with environmental sustainability. Although the SBM-Undesirable model has been extensively applied to assess port environmental efficiency (PEE), most applications assume strong disposability and disregard heterogeneity in technological capacities across different port scales, potentially biasing the assessments. To overcome these limitations, coastal ports are initially categorized into three subgroups based on operational scale criteria. A meta-frontier SBM-Undesirable model incorporating weak disposability is then developed to evaluate PEE. Dynamic characteristics are further explored via the Global Malmquist Index. Results indicate substantial disparities between subgroup frontiers and the meta-frontier. The average group PEE (0.732) exceeded the meta PEE (0.570), implying potential overestimation under homogeneity assumptions. Large-sized ports, with a mean technology gap ratio (TGR) of 0.956, operated near the meta-frontier, whereas medium-sized and small-sized ports, with TGRs of 0.770 and 0.600 respectively, exhibited substantial technological gaps. Total factor productivity (TFP) demonstrated a volatile upward trend, averaging 6.8% annual growth. In large-sized and medium-sized ports, TFP growth was primarily driven by technological innovation, whereas in small-sized ports, it stemmed from combined improvements in technical efficiency and technological level. These insights underscore the necessity of differentiated decarbonization strategies for port management. Full article

This paper introduces a single-shot ultrafast imaging technique termed wavelength and polarization time-encoded ultrafast raster imaging (WP-URI). By integrating raster imaging principles with wavelength- and polarization-based temporal encoding, the system uses a spatial raster mask and time–space mapping to aggregate multiple two-dimensional temporal raster images onto a single detector plane, thereby enabling the effective spatial separation and extraction of target information. Finally, the target dynamics are recovered using a reconstruction algorithm based on the Nyquist–Shannon sampling theorem. Numerical simulations demonstrate the single-shot acquisition of four dynamic frames at 25 trillion frames per second (Tfps) with an intrinsic spatial resolution of 50 line pairs per millimeter (lp/mm) and a wide field of view. The WP-URI technique achieves unparalleled spatio-temporal resolution and frame rates, offering significant potential for investigating ultrafast phenomena such as matter interactions, carrier dynamics in semiconductor devices, and femtosecond laser–matter processes. Full article

In this study, we explore the impact of land investment introduction on efficiency loss at both the enterprise and urban levels and discuss the role of factor-biased technological progress in minimizing these losses. Using a nested constant elasticity of substitution (CES) production function, we theoretically validate the premise that land investment introduction disrupts the optimal allocation of productive factors and reduces the “threshold selection” effect of land cost, leading to efficiency losses. Empirically, the systematic generalized method of moments (GMM) is applied to analyze panel data from 284 prefecture-level cities in China between 2007 and 2019. The findings reveal that land investment introduction brings about efficiency losses and prolonged land investment strategies that deepen enterprise efficiency loss, while urban efficiency loss may be temporarily alleviated but tends to deepen over the long term. Enterprise efficiency loss can be reduced by selecting land-biased, labor-biased, and capital-biased technological progress; however, its impact on urban efficiency loss remains uncertain. These findings provide insights into the optimal selection of factor-biased technological progress for industrial enterprises and provide policy-oriented recommendations for enhancing production and improving efficiency. Full article

As the primary force driving the sustainable development of the rural economy, the improvement of the total factor productivity (TFP) of agricultural enterprises (AEs) is of great strategic significance. This study innovatively zeroes in on AEs, leveraging micro-level data from agricultural listed companies in China’s A-share market spanning from 2007 to 2023. It aims to investigate the impact of supply chain finance (SCF) on the TFP of these enterprises and elucidate the underlying mechanisms. Uniquely, this study incorporates enterprise digital transformation and innovation capability as moderating variables into the mechanism analysis framework. Furthermore, it examines the heterogeneous effects across different characteristics of AEs. The findings reveal that SCF significantly boosts the TFP of AEs. Specifically, a one-standard-deviation increase in the level of SCF is associated with a 0.2658% increase in TFP relative to the mean. This conclusion holds robustly across various tests. Moreover, the interaction terms of SCF with both enterprise digital transformation and innovation capability are significantly positive. This indicates that greater digital transformation and stronger innovation capability amplify the positive effect of SCF on TFP. The heterogeneous analysis further indicates that for AEs with highly optimized human capital, higher financing constraints, and more efficient credit resource allocation, the positive impact of SCF on TFP is particularly pronounced. Full article

Understanding how transcription factors regulate biomass accumulation and sucrose storage is essential for improving sugarcane productivity. In this study, we quantified transcription factor protein (TFP) abundance in sugarcane internodes across developmental stages and growth rates. These profiles were correlated with key biochemical traits, including lignin, glucan, hemicellulose, and sucrose content. From 7333 identified proteins, 205 were annotated as transcription factors spanning 22 families. By applying Pearson correlation followed by Partial Correlation with Information Theory (PCIT), we identified 46 high-confidence TFP-trait associations. Key regulators, such as ScMYB113, ScMADS15, and ScbZIP85, exhibited trait-specific roles, influencing sucrose storage and cell wall biosynthesis. Network topology revealed distinct transcriptional modules linked to biomass production, polysaccharide deposition, and intermediary metabolism. Notably, sucrose and lignin accumulation intensified after internode elongation ceased, highlighting shifts in transcriptional control during maturation. This study delivers the first protein-level regulatory map linking transcription factors to metabolic traits in sugarcane and provides a framework for targeting candidate regulators to enhance biomass quality and yield in bioenergy crops such as sugarcane. Full article

Against global carbon neutrality goals and China’s “dual carbon” strategy, this study examines how green technology innovation shapes corporate carbon performance through a dual-path mechanism—improving enterprises’ resource utilization efficiency and environmental governance capabilities. Leveraging data from Chinese A-share listed firms (2007–2022) and methods including fixed effects, instrumental variables, and Heckman two-stage models, key findings include: (1) Green technology innovation significantly improves carbon performance. (2) This effect operates through two pathways: enhancing total factor productivity (TFP) and strengthening environmental governance. (3) Green media and investor attention amplify the positive impact of green innovation on carbon performance. (4) The effect remains significant but shows diminishing marginal returns over 1–4 future periods. (5) Non-state-owned enterprises and non-high-carbon industries exhibit more pronounced improvements. This research provides micro-level evidence for “technology-driven low-carbon transformation”, offering theoretical support for policy differentiation and corporate green technology strategies, with practical implications for achieving China’s “dual carbon” objectives. Full article

The ESG performance of enterprises is congruent with contemporary development concepts and plays a pivotal role in promoting enterprises to achieve high-quality development. The present study commences with an evaluation of the high-quality development of firms across multiple dimensions. It then undertakes an empirical investigation into the impact of ESG performance on the high-quality development of firms. This study utilises data from Chinese A-share listed firms from 2010 to 2023. The findings indicate that ESG performance has the capacity to encourage firms to advance towards high-quality development. Digital transformation is identified as a significant factor that positively moderates the facilitating effect of ESG performance on firms. The mechanism of action of ESG performance involves enhancing supply chain stability and alleviating financing constraints. Furthermore, evidence suggests that ESG performance tends to be heterogeneous in its contribution to the high-quality development of enterprises, with more significant facilitating effects for state-owned enterprises and firms in regions with favourable business environments. The present study offers theoretical and practical empirical support for the establishment of an ESG system that is suitable for China’s national conditions and that will promote high-quality firm development. Full article

As global climate change intensifies and resources become increasingly scarce, China’s sustainable development of freshwater aquaculture faces unprecedented challenges. This study utilizes panel data from 31 provincial-level regions in mainland China (2000–2023) and innovatively constructs a multi-stage sequential modified slack-based measure data envelopment analysis (MSBM-DEA) model. By endogenizing extreme climate factors within the aquaculture production efficiency framework, this study reveals the dynamic impact of climate change on freshwater aquaculture total factor productivity (TFP). The finding indicates that extreme climate events reduce freshwater aquaculture TFP by 1.66% and technical advancement by 18.9%. The impact varies regionally, with eastern provinces experiencing a maximum TFP decline of 3.1%, while western provinces face a significant drop of 5.2%. The eastern region, supported by technology and policy, shows a relatively strong recovery capacity, whereas the western region suffers more due to resource scarcity and technical lag. To tackle these challenges, this study recommends establishing a climate-adaptive TFP monitoring framework and promoting a dual-driven model of technical innovation and efficiency enhancement to bolster fisheries’ climate resilience. This research provides valuable decision making support for climate adaptation strategies in China’s freshwater aquaculture and serves as empirical evidence and theoretical guidance for other climate-vulnerable regions globally. Full article