Large Scale Research Articles

Structured invariant subspace and decomposition of systems with time delays and uncertainties

AbstractThis article discusses invariant subspaces of a matrix with a given partition structure. The existence of a nontrivial structured invariant subspace is equivalent to the possibility of decomposing the associated system with multiple feedback blocks such that the feedback operators are subject to a given constraint. The formulation is especially useful in the stability analysis of time‐delay systems using the Lyapunov–Krasovskii functional approach where computational efficiency is essential in order to achieve accuracy for large scale systems. The set of all structured invariant subspaces are obtained (thus all possible decompositions are obtained as a result) for the coupled differential‐difference equations (DDE) associated with the DDE of retarded and neutral types, as well as systems with a time‐varying delay. It was shown that the known ad hoc methods of reducing the dimensions of delay channels can be considered as special cases of decomposition where one subsystem has trivial dynamics. The reduction of computational cost is demonstrated by a numerical example. For the general case, a recursive procedure is developed to obtain the set of all structured invariant subspaces. Based on this procedure, a method is presented to obtain a nontrivial structured invariant subspace that considers computational efficiency and increased possibility of terminating in a finite number of steps.

What Mathematics Content Do Teachers Teach? Optimizing Measurement of Opportunities to Learn in the Classroom

AbstractMeasuring opportunities to learn (OTL) is crucial for evaluating education quality and equity, but obtaining accurate and comprehensive OTL data at a large scale remains challenging. We attempt to address this issue by investigating measurement concerns in data collection and sampling. With the primary goal of estimating group‐level OTLs for large populations of classrooms and the secondary goal of estimating classroom‐level OTLs, we propose forming a teacher panel and using an online log‐type survey to collect content and time data on sampled days throughout the school year. We compared various sampling schemes in a simulation study with real daily log data from 66 fourth‐grade math teachers. The findings from this study indicate that sampling 1 day per week or 1 day every other week provided accurate group‐level estimates, while sampling 1 day per week yielded satisfactory classroom‐level estimates. The proposed approach aids in effectively monitoring large‐scale classroom OTL.

A Real-Time Deep Learning-Based Facial Mask Detection System for Preventing the Transmission of Respiratory Viruses

In order to prevent the spread of respiratory viruses like COVID-19 and influenza, an effective protection method is to wear facial masks in densely populated areas. This has led to a growing need for smart services that automatically detect facial masks and replace manual reminding. To address this challenging task and to contribute towards health safety, this paper introduces MedNetV2 system, which is an efficient deep learning-based facial mask detector with a low computational cost. In comparison with existing systems, the main specificities of the proposed system are: (1) the adoption of an effective deep learning-based framework to deal with both the large scale diversity and position variations of masked faces involved in natural scenes, (2) the interaction between face localization and facial mask detection modules to achieve the overall system goal, (3) the lightweight design and the real-time response well suited for real-world scenarios. Extensive experiments on public dataset and real-world video streaming are carried out to validate quantitatively and visually the effectiveness of the proposed system. Promising results, in terms of detection accuracy as well as time response, are achieved when compared it with other state-of-the-art systems.

Novel influenza A viruses in pigs with zoonotic potential, Chile.

Novel H1N2 and H3N2 swine influenza A viruses (IAVs) have recently been identified in Chile. The objective of this study was to evaluate their zoonotic potential. We perform phylogenetic analyses to determine the genetic origin and evolution of these viruses, and a serological analysis to determine the level of cross-protective antibodies in the human population. Eight genotypes were identified, all with pandemic H1N1 2009-like internal genes. H1N1 and H1N2 were the subtypes more commonly detected. Swine H1N2 and H3N2 IAVs had hemagglutinin and neuraminidase lineages genetically divergent from IAVs reported worldwide, including human vaccine strains. These genes originated from human seasonal viruses were introduced into the swine population since the mid-1980s. Serological data indicate that the general population is susceptible to the H3N2 virus and that elderly and young children also lack protective antibodies against the H1N2 strains, suggesting that these viruses could be potential zoonotic threats. Continuous IAV surveillance and monitoring of the swine and human populations is strongly recommended.IMPORTANCEIn the global context, where swine serve as crucial intermediate hosts for influenza A viruses (IAVs), this study addresses the pressing concern of the zoonotic potential of novel reassortant strains. Conducted on a large scale in Chile, it presents a comprehensive account of swine influenza A virus diversity, covering 93.8% of the country's industrialized swine farms. The findings reveal eight distinct swine IAV genotypes, all carrying a complete internal gene cassette of pandemic H1N1 2009 origin, emphasizing potential increased replication and transmission fitness. Genetic divergence of H1N2 and H3N2 IAVs from globally reported strains raises alarms, with evidence suggesting introductions from human seasonal viruses since the mid-1980s. A detailed serological analysis underscores the zoonotic threat, indicating susceptibility in the general population to swine H3N2 and a lack of protective antibodies in vulnerable demographics. These data highlight the importance of continuous surveillance, providing crucial insights for global health organizations.

Scale-Up Preparation of Manganese-Iron Prussian Blue Nanozymes as Potent Oral Nanomedicines for Acute Ulcerative Colitis.

Prussian blue (PB) nanozymes are demonstrated as effective therapeutics for ulcerative colitis (UC), yet an unmet practical challenge remains in the scalable production of these nanozymes and uncertainty over their efficacy. With a novel approach, a series of porous manganese-iron PB (MnPB) colloids, which are shown to be efficient scavengers for reactive oxygen species (ROS) including hydroxyl radical, superoxide anion, and hydrogen peroxide, are prepared. In vitro cellular experiments confirm the capability of the nanozyme to protect cells from ROS attack. In vivo, the administration of MnPB nanozyme through gavage at a dosage of 10mgkg-1 per day for three doses in total potently ameliorates the pathological symptoms of acute UC in a murine model, resulting in mitigated inflammatory responses and improved viability rate. Significantly, the nanozyme produced at a large scale can be achieved at an unprecedented yield weighting ≈11g per batch of reaction, demonstrating comparable anti-ROS activities and treatment efficacy to its small-scale counterpart. This work represents the first demonstration of the scale-up preparation of PB analog nanozymes for UC without compromising treatment efficacy, laying the foundation for further testing of these nanozymes on larger animals and promising clinical translation.

Molecular farming- importance of stewarding food crops engineered to produce transferred food allergens and non-food substances

Developers are looking for new ways to produce proteins and other substances for food, pharmaceutical and industrial use by genetically engineering food crops to produce the desired substance of interest (i.e., molecular farming). Developers should be aware of the food safety concerns, legality and potential liability, and loss of consumer confidence that could arise if food or other plant materials from these crops were to inadvertently enter the food supply and compromise safety. At the earliest stages of product development, developers should consider whether it is feasible to consistently steward their crops and resulting plant materials from development through disposal to ensure they do not enter the food or feed supply in a way that would be unlawful. Developers should engage FDA’s foods program when considering their stewardship program. While molecular farming holds promise for the economical production of specific proteins and other substances at a large scale, it is important for developers to consider the efforts needed to protect the food supply from the crops used for molecular farming- particularly when the crop chosen for molecular farming is a crop traditionally used for human or animal food.

Integrated Demand Response for Micro-Energy Grid Accounting for Dispatchable Loads

Micro-energy networks are the smallest element of integrated energy systems, and tapping into the integrated demand response potential of micro-energy networks is conducive to improving energy use efficiency and promoting the development of new energy sources on a large scale. This paper proposes a day-ahead integrated demand response strategy for micro-energy grid that takes into account the dispatchable loads. Considering the gradient use of thermal energy, a typical micro-energy grid structure including electricity, gas, medium-grade heat, low-grade heat, and cold energy is constructed, a comprehensive energy equipment model is established, and the refined scheduling models of the dispatchable loads are given. On this basis, with the operating economy of the micro-energy grid as the optimization objective, the integrated demand response strategies of tariff-type and incentive-type are proposed. Through case study analysis, it is verified that the proposed strategy can optimize the energy consumption structure of the micro-energy grid under the guidance of time-of-use tariffs, reducing the operating costs. The proposed strategy fully exploits the demand response potential of the micro-energy grid through the dispatchable loads and the multi-energy complementarity of electricity, heat, and cold, realizes the comprehensive coordination and optimization of source-network-load-storage, provides a larger peak-regulating capacity, and exhibits practical applicability in engineering.

Enhancing the online learning experience of Chinese college students: an investigation of facilitation strategies and their mixed association with student satisfaction

Facilitation strategies play a critical role in helping instructors teach effectively in an online environment. However, there is a lack of research on how different facilitation strategies impact the online learning experience. To address this gap, our study surveyed 5980 college students from two universities in China and analysed the associations between facilitation strategies and student satisfaction using multivariate and logistic regression analyses. Our findings reveal that facilitation strategies aimed at managerial and technical purposes have different effects on student satisfaction with instructors compared to their satisfaction with their own achievement and engagement. Additionally, we found that student group discussion had a negative association with student satisfaction, potentially due to a preference for hierarchical learning in Confucian-heritage culture. In contrast, after-class learning materials were positively associated with student satisfaction. These findings offer important implications for pedagogical practices that aim to enhance the online learning experience for Chinese students on a large scale.

Biomass study of Anabaena sphaerica cultivated in electroplating industrial effluent

The growth of microalga Anabaena sphaerica in electroplating industrial effluent with reference to the vegetative cells , heterocysts and dry biomass weight brings about oxygenation and mineralization in addition to the increase in biomass which serve as a multipurpose raw material to the industries. From lab scale experiments it is demonstrated that the present investigation could be converted to pilot study for large scale production of biofuel and other commodity chemicals. Cultivation of microalgal biomass as a potential resource / raw material for various industries to produce commodity chemicals could enhance the economy and curtail the environmental hazards.

Natural Clay-Modified Piezocatalytic Membrane for Efficient Removal of Coliform Bacteria from Wastewater.

In the modern era, water pollution, especially from industries, agricultural farms, and residential areas, is caused by the release of a large scale of heavy metals, organic pollutants, chemicals, etc., into the environment, posing a serious threat to aquatic ecosystems and nature. Moreover, untreated sewage waste discharged directly into nearby water bodies can cause various diseases to mankind due to the high load of fecal coliform bacteria. This work demonstrates the development of a biocompatible, cost-effective, highly robust, efficient, flexible, freestanding, and reusable membrane using naturally formed biocompatible kaolinite clay-doped poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP) for effective piezodynamic destruction of coliform bacteria. In this study, Escherichia coli (E. coli) and Enterococcus faecalis (E. faecalis) have been used to evaluate the mechanical stimulus-responsive antibacterial efficacy of the nanocomposite membrane. The membrane can effectively eradicate nearly 99% viable E. coli and 97% E. faecalis within a span of 40 min under mechanical stimulation (soft ultrasound ∼15 kHz). To further understand the mechanism, an evaluation of reactive oxygen species and bacterial FESEM was performed. These studies revealed that bacterial cells suffered severe visible cell damage after 40 min of piezocatalysis, elucidating the fact that the synthesized membrane is capable of producing a superior piezodynamic antibacterial effect.

Plasmonic array assisted mass spectrometry for preferential metabolite detection

Metabolites, depicting physiological and pathophysiological state, underpin diverse disease-associated phenomena. Metabolite detection offers insights for identifying disease biomarkers and monitoring treatment responses, thereby facilitating early disease diagnosis and personalized medicine. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) holds promise in molecular profiling, with advanced materials emerging as efficient matrices for metabolite detection. Yet, their preferences in analyzing various metabolites have not been systematically explored, hindering the development of matrices for suitable clinical practice. Herein, we report plasmonic array assisted MS for fast and direct quantification of specific metabolites in human biofluids. Plasmonic array is prepared by self-assembling hybrid bimetallic alloys at liquid–liquid interfaces. Large scale screening of 37 metabolites exhibited LDI preferences of plasmonic array especially for nucleosides. Plasmonic array enables sensitive and selective detection of nucleosides, due to the synergistic effect via alloy composition and chemical interactions without the use of costly antibodies. Consequently, accurate quantification is achieved with a recovery rate of 103.18 % ± 3.78 % for inosine, consuming a trace amount of serum as low as 4 μL within seconds. This work provides useful guidelines for matrix design in the MALDI MS analysis of metabolites toward biomedical applications.

Assisted phytoextraction as a nature-based solution for the sustainable remediation of metal(loid)-contaminated soils.

Soil contamination is a significant environmental issue that poses a threat to human health and the ecosystems. Conventional remediation techniques, such as excavation and landfilling, are often expensive, disruptive, and unsustainable. As a result, there has been growing interest in developing sustainable remediation strategies that are cost-effective, environmentally friendly, and socially acceptable. One such solution is phytoextraction: a nature-based approach that uses the abilities of hyperaccumulator plants to uptake and accumulate metals and metalloids (potentially toxic elements [PTE]) without signs of toxicity. Once harvested, plant biomass can be treated to reduce its volume and weight by combustion, thus obtaining bioenergy, and the ashes can be used for the recovery of metals or in the construction industry. However, phytoextraction has shown variable effectiveness due to soil conditions and plant species specificity, which has led researchers to develop additional approaches known as assisted phytoextraction to enhance its success. Assisted phytoextraction is a remediation strategy based on modifying certain plant traits or using different materials to increase metal uptake or bioavailability. This review article provides a practical and up-to-date overview of established strategies and the latest scientific advancements in assisted phytoextraction. Our focus is on improving plant performance and optimizing the uptake, tolerance, and accumulation of PTE, as well as the accessibility of these contaminants. While we highlight the advantages of using hyperaccumulator plants for assisted phytoextraction, we also address the challenges and limitations associated with this approach. Factors such as soil pH, nutrient availability, and the presence of other contaminants can affect its efficiency. Furthermore, the real-world challenges of implementing phytoextraction on a large scale are discussed and strategies to modify plant traits for successful phytoremediation are presented. By exploring established strategies and the latest scientific developments in assisted phytoextraction, this review provides valuable guidance for optimizing a sustainable, nature-based technology. Integr Environ Assess Manag 2024;00:1-20. © 2024 SETAC.

A meta-analysis of the antecedents of flexible work arrangements utilization: based on Job demands-resources model

The rapid development of internet technology has enabled organizations to implement flexible work arrangements (FWA) on a large scale. The COVID-19 global pandemic has further intensified this trend, making FWA a vital aspect of HRM to maintain organizational operations. Therefore, it is imperative to understand the causes of FWA utilization and implement effective strategies to achieve optimal outcomes. We propose a framework for FWA utilization antecedents based on the Job Demands-Resources (JD-R) model and test it using meta-analysis. Drawing on 104 studies (108 independent samples) with 1,034,603 participants, we examine the relationship between FWA utilization and its job-related antecedents. Our findings generally support the expected relationships across two categories of FWA antecedents, namely job resources and job demands. We also identify demographics and masculinity/femininity culture as moderators that influence these relationships. Finally, we discuss the theoretical and practical implications to guide HR managers in developing effective FWA strategies that meet the needs of both employees and organizations.

Early experiences on the OLCF Frontier system with AthenaPK and Parthenon‐Hydro

SummaryThe Oak Ridge Leadership Computing Facility (OLCF) has been preparing the nation's first exascale system, Frontier, for production and end users. Frontier is based on HPE Cray's new EX architecture and Slingshot interconnect and features 74 cabinets of optimized 3rd Gen AMD EPYC CPUs for HPC and AI and AMD Instinct 250X accelerators. As a part of this preparation, “real‐world” user codes have been selected to help assess the functionality, performance, and usability of the system. This article describes early experiences using the system in collaboration with the Hamburg Observatory for two selected codes, which have since been adopted in the OLCF test harness. Experiences discussed include efforts to resolve performance variability and per‐cycle slowdowns. Results are shown for a performance portable astrophysical magnetohydronamics code, AthenaPK, and a mini‐application stressing the core functionality of a performance portable block‐structured adaptive mesh refinement framework, Parthenon‐Hydro. These results show good scaling characteristics to the full system. At the largest scale, the Parthenon‐Hydro miniapp reaches a total of zone‐cycles/s on 9216 nodes (73,728 logical GPUs) at 92% weak scaling parallel efficiency (starting from a single node using a second‐order, finite‐volume method).

High-Throughput Capillary Liquid Chromatography Using a Droplet Injection and Application to Reaction Screening.

The cycle time of a standard liquid chromatography (LC) system is the sum of the time for the chromatographic run and the autosampler injection sequence. Although LC separation times in the 1-10 s range have been demonstrated, injection sequences are commonly >15 s, limiting throughput possible with LC separations. Further, such separations are performed on relatively large bore columns requiring flow rates of ≥5 mL/min, thus generating large volumes of mobile phase waste when used for large scale screening and increasing the difficulty in interfacing to mass spectrometry. Here, a droplet injector system was established that replaces the autosampler with a four-port, two-position valve equipped with a 20 nL internal loop interfaced to a syringe pump and a three-axis positioner to withdraw sample droplets from a well plate. In the system, sample and immiscible fluid are pulled alternately from a well plate into a capillary and then through the injection valve. The valve is actuated when sample fills the loop to allow sequential injection of samples at high throughput. Capillary LC columns with 300 μm inner diameter were used to reduce the consumption of mobile phase and sample. The system achieved 96 separations of 20 nL droplet samples containing 3 components in as little as 8.1 min with 5-s cycle time. This system was coupled to a mass spectrometer through an electrospray ionization source for high-throughput chemical reaction screening.

An optimal cooperative relay selection strategy for delay aware image transmission in large scale multi-radio multi-channel multimedia wireless sensor network

High bit-error rates and high transmission rates are required for the Multimedia Wireless Sensor Networks (MWSN) to transmit high-quality pictures through smart devices. To fully utilize the advantages of the technology known as Multiple-Input Multiple-Output, MWSN heavily relies on cooperative communication. Large-scale wireless networks use multi-radio-multi-channel to improve performance by simultaneous broadcasts across symmetrical channels to reduce interference. Expanding cooperative communication in vast networks is subject to severe interference. And, as each node in the network is mobile, routing and transmission delay pose significant problems for cooperative multimedia wireless sensor networks. Mobility increases the MWSNs’ dynamic nature, which reflects in the overhead control traffic. To address above issues, a Cluster-based Delay Aware Cooperative Relay Selection (CDACRS) was proposed by employing mobility and distance metrics and channel assignment (CA) using dynamic Global Table (GT). To minimize the end-to-end transmission latency without compromising aggregate throughput, our approach chooses a relay-node depending on the mobility and the maximum available channel capacity. Further, to improve the end-to-end energy consumption, Power Aware Transmission (PAT) protocol is developed by calculating maximum transmission power required to meet target bit error rate (BER). The proposed method’s performance is evaluated against the Cluster-based Cooperative Multi-Hop Optimal Relay Selection (CCORS); energy efficient and quality aware multi-hop cooperative image transmission; and Energy Aware Cooperative Image Transmission (EACIT) algorithms and observed that our approach improves the transmission delay by 37.5% (approx.) and end-to-end energy consumption by 48.8%.

Extracellular vesicles secreted by human aneuploid embryos present a distinct transcriptomic profile and upregulate MUC1 transcription in decidualised endometrial stromal cells.

Do extracellular vesicles (EVs) secreted by aneuploid human embryos possess a unique transcriptomic profile that elicits a relevant transcriptomic response in decidualized primary endometrial stromal cells (dESCs)? Aneuploid embryo-derived EVs contain transcripts of PPM1J, LINC00561, ANKRD34C, and TMED10 with differential abundance from euploid embryo-derived EVs and induce upregulation of MUC1 transcript in dESCs. We have previously reported that IVF embryos secrete EVs that can be internalized by ESCs, conceptualizing that successful implantation to the endometrium is facilitated by EVs. Whether these EVs may additionally serve as biomarkers of ploidy status is unknown. Embryos destined for biopsy for preimplantation genetic testing for aneuploidy (PGT-A) were grown under standard conditions. Spent media (30 μl) were collected from euploid (n = 175) and aneuploid (n = 140) embryos at cleavage (Days 1-3) stage and from euploid (n = 187) and aneuploid (n = 142) embryos at blastocyst (Days 3-5) stage. Media samples from n = 35 cleavage-stage embryos were pooled in order to obtain five euploid and four aneuploid pools. Similarly, media samples from blastocysts were pooled to create one euploid and one aneuploid pool. ESCs were obtained from five women undergoing diagnostic laparoscopy. EVs were isolated from pools of media by differential centrifugation and EV-RNA sequencing was performed following a single-cell approach that circumvents RNA extraction. ESCs were decidualized (estradiol: 10 nM, progesterone: 1 µM, cAMP: 0.5 mM twice every 48 h) and incubated for 24 h with EVs (50 ng/ml). RNA sequencing was performed on ESCs. Aneuploid cleavage stage embryos secreted EVs that were less abundant in RNA fragments originating from the genes PPM1J (log2fc = -5.13, P = 0.011), LINC00561 (log2fc = -7.87, P = 0.010), and ANKRD34C (log2fc = -7.30, P = 0.017) and more abundant in TMED10 (log2fc = 1.63, P = 0.025) compared to EVs of euploid embryos. Decidualization per se induced downregulation of MUC1 (log2fc = -0.54, P = 0.0028) in ESCs as a prerequisite for the establishment of receptive endometrium. The expression of MUC1 transcript in decidualized ESCs was significantly increased following treatment with aneuploid compared to euploid embryo-secreted EVs (log2fc = 0.85, P = 0.0201). Raw data have been uploaded to GEO (accession number GSE234338). The findings of the study will require validation utilizing a second cohort of EV samples. The discovery that the transcriptomic profile of EVs secreted from aneuploid cleavage stage embryos differs from that of euploid embryos supports the possibility to develop a non-invasive methodology for PGT-A. The upregulation of MUC1 in dESCs following aneuploid embryo EV treatment proposes a new mechanism underlying implantation failure. The study was supported by a Marie Skłodowska-Curie Actions fellowship awarded to SM by the European Commission (CERVINO grant agreement ID: 79620) and by a BIRTH research grant from Theramex HQ UK Ltd. The authors have no conflicts of interest to declare.

Symmetries of the Large Scale Structures of the Universe as a Phenomenology of a Fractal Turbulence: The Role of the Plasma Component

We present a new perspective on the symmetries that govern the formation of large-scale structures across the Universe, particularly focusing on the transition from the seeds of galaxy clusters to the seeds of galaxies themselves. We address two main features of cosmological fluid dynamics pertaining to both the linear and non-linear regimes. The linear dynamics of cosmological perturbations within the Hubble horizon is characterized by the Jeans length, which separates stable configurations from unstable fluctuations due to the gravitational effect on sufficiently large (and therefore, massive enough) overdensities. On the other hand, the non-linear dynamics of the cosmological fluid is associated with a turbulent behavior once the Reynolds numbers reach a sufficiently high level. This turbulent regime leads to energy dissipation across smaller and smaller scales, resulting in a fractal distribution of eddies throughout physical space. The proposed scenario suggests that the spatial scale of eddy formation is associated with the Jeans length of various levels of fragmentation from an original large-scale structure. By focusing on the fragmentation of galaxy cluster seeds versus galaxy seeds, we arrived at a phenomenological law that links the ratio of the two structure densities to the number of galaxies in each cluster and to the Hausdorff number of the Universe matter distribution. Finally, we introduced a primordial magnetic field and studied its influence on the Jeans length dynamics. The resulting anisotropic behavior of the density contrast led us to infer that the main features of the turbulence could be reduced to a 2D Euler equation. Numerical simulations showed that the two lowest wavenumbers contained the major energy contribution of the spectrum.

Which international co‐authorships produce higher quality journal articles?

AbstractInternational collaboration is sometimes encouraged in the belief that it generates higher quality research or is more capable of addressing societal problems. Nevertheless, while there is evidence that the journal articles of international teams tend to be more cited than average, perhaps from increased international audiences, there is no science‐wide direct academic evidence of a connection between international collaboration and research quality. This article empirically investigates the connection between international collaboration and research quality for the first time, with 148,977 UK‐based journal articles with post publication expert review scores from the 2021 Research Excellence Framework (REF). Using an ordinal regression model controlling for collaboration, international partners increased the odds of higher quality scores in 27 out of 34 Units of Assessment (UoAs) and all Main Panels. The results therefore give the first large scale evidence of the fields in which international co‐authorship for articles is usually apparently beneficial. At the country level, the results suggests that UK collaboration with other high research‐expenditure economies generates higher quality research, even when the countries produce lower citation impact journal articles than the United Kingdom. Worryingly, collaborations with lower research‐expenditure economies tend to be judged lower quality, possibly through misunderstanding Global South research goals.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain.Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits.Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %–69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %–50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau.Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.