Search Results (5,965)

Mathematical abilities are critical for the developmental outcomes of children with autism spectrum disorder (ASD). However, little is known about these abilities and their association with the approximate number system (ANS) in preschoolers with ASD beyond Western samples, including Chinese children. This cross-sectional study examined whether formal and informal mathematical abilities differed between children with and without ASD and assessed the extent to which these abilities were associated with ANS acuity. Participants included 47 children with ASD and 47 typically developing (TD) children aged 3–7 years. All children were assessed on measures of formal and informal mathematical abilities, ANS acuity, and non-verbal IQ. No significant group differences in mathematical abilities were found among children aged 3–5 years. However, among children aged 6–7 years, the ASD group showed significantly lower performance in mathematical abilities compared to their TD peers. ANS acuity was significantly correlated with both formal and informal mathematical abilities in the ASD group, but only with informal mathematical abilities in the TD group. Furthermore, ANS acuity accounted for 5.4% of the unique variance in formal mathematical abilities specifically within the ASD group. The patterns of mathematical abilities and their relationship with ANS acuity differ between preschoolers with and without ASD. These findings suggest a differential association between ANS and formal mathematics learning in children with ASD, highlighting implications for the design of early numeracy interventions. Full article

Plant volatiles are critical mediators of insect–plant interactions, guiding natural enemies to specific habitats and prey. The flower bug, Orius maxidentex Ghauri (Hemiptera: Anthocoridae), is a generalist predator that exhibits a specialized ecological association with the weed Celosia argentea L. (Caryophyllales: Amaranthaceae), utilizing the plant as a primary floral niche in Hainan Island. In this study, the attractiveness of C. argentea floral volatiles to O. maxidentex was confirmed using a Y-tube olfactometer. Solid-phase microextraction (SPME) combined with gas chromatography–mass spectrometry (GC-MS) was utilized to identify six compounds in the floral volatiles: 1,3-diethenylbenzene, trans-cinnamaldehyde, β-bisabolene, methyl salicylate, 3-ethylbenzaldehyde, and nonanal. Electroantennogram (EAG) assays revealed that O. maxidentex antennae showed significant physiological responses to these compounds, and the EAG relative values were positively correlated with concentration gradients. Furthermore, O. maxidentex exhibited significant orientation responses to 1,3-diethenylbenzene, trans-cinnamaldehyde, β-bisabolene, and methyl salicylate, whereas no behavioral response was observed for 3-ethylbenzaldehyde or nonanal. Further tests revealed that β-bisabolene elicited the highest attractiveness, comparable to a synthetic blend formulated to mimic the natural release ratio of the active semiochemicals. These findings reveal the hidden chemical cues mediating the interaction between a predator and its preferred habitat. Understanding this mechanism not only helps explain insect adaptation but also offers new strategies for using these plant volatiles to influence the behavior of this specific predator, potentially enhancing its targeted recruitment in agroecosystems. Full article

Cymbidium eburneum Lindl. is a valuable ornamental orchid and breeding parent, but its genetic background remains unclear due to habitat destruction and germplasm mixing. This study developed specific SSR markers to evaluate the genetic diversity and structure of 96 C. eburneum Lindl. accessions from China and Vietnam. Transcriptome analysis identified 47,248 SSR loci. Sixteen polymorphic core primer pairs detected 150 alleles (mean Na = 9.375) with an average Polymorphism Information Content (PIC) of 0.444. Observed heterozygosity (Ho = 0.290) was noticeably lower than expected (He = 0.478), indicating heterozygote deficiency. UPGMA clustering identified eight groups strongly correlated with geography. Principal Coordinate Analysis (PCoA) revealed a clear geographical differentiation pattern, featuring the most genetically cohesive group from Guangxi and more differentiated geographically marginal populations from Hainan and Vietnam. STRUCTURE analysis (K = 2) indicated two main gene pools with signals of genetic admixture. Geographical isolation was suggested as a potential driver of genetic differentiation. The Guangxi population represents a genetically consistent major reservoir, while marginal populations harbor unique variations. These findings provide a scientific basis for germplasm identification, conservation, and parental selection in C. eburneum Lindl. breeding. Full article

A nano-CuO/ZnO desulfurizer was successfully prepared via a homogeneous precipitation method, and the effects of Cu doping on its microstructure, oxygen species, desulfurization performance, and reaction mechanism were systematically investigated. The results show that an appropriate Cu doping amount (TZ2, Cu:Zn = 1:18.40) significantly reduces the particle size (to ~10.9 nm) compared with pure ZnO (14.3 nm), leading to an increased number of surface-active sites. XPS and TG analyses reveal that Cu incorporation increases the proportion of lattice oxygen and decreases the concentration of oxygen vacancies, indicating that the modification effect of Cu dominates over the particle size effect in regulating surface oxygen species. Despite the reduced oxygen vacancy concentration, the desulfurization performance is markedly enhanced, with TZ2 exhibiting the longest breakthrough time under oxygen-free conditions at room temperature. This improvement is attributed to the strong interaction between highly dispersed Cu species and the ZnO matrix, which promotes H₂S adsorption and activation. Mechanistic studies demonstrate that, unlike pure nano-ZnO, where oxygen vacancy-mediated reactions dominate, the CuO/ZnO system follows a chemisorption-driven pathway involving the formation of copper sulfides and highly reactive polysulfide intermediates. Furthermore, the presence of oxygen significantly influences the reaction behavior, with an optimal oxygen concentration (~10%) maximizing desulfurization performance by balancing the generation of reactive oxygen species and sulfur intermediates. This work provides new insights into the design of high-performance ZnO-based desulfurizers and highlights the critical role of Cu-induced mechanism transformation. Full article

The development of rice flowers and panicles critically affects grain yield and quality. LEAFY HULL STERILE1/OsMADS1, a grass-specific SEPALLATA-like MADS-box transcription factor, is essential for rice floral development and floral meristem activity maintenance. However, the mechanism through which OsMADS1 interacts with other genes to regulate floral organ identity and meristem determinacy remains unclear. In this study, we first generated OsMADS1 knockout mutants using CRISPR/Cas9. The mutant florets exhibited obvious morphological defects, which were categorized into five phenotypic classes. Yeast two-hybrid screening identified two OsMADS1-interacting proteins: OsMADS22, an STMADS11-like protein, and OsYABBY5, a YABBY transcription factor. Their physical interactions were validated both in vitro and in vivo, and were important for floral organ specification and meristem maintenance. Transcriptomic analysis revealed that OsMADS1 regulates numerous genes involved in hormone signaling and panicle/flower development. Furthermore, OsMADS1 acts together with OsMADS22 and OsYABBY5 to modulate the expression of the downstream target OsMADS55, thereby controlling rice spikelet development. Together, our results reveal that OsMADS1 executes diverse regulatory functions in floral organ specification and meristem identity by interacting with multiple developmental regulators, providing new insights into the molecular mechanisms of plant flower development. Full article

Dwarf bananas are an important tropical fruit crop. They are particularly susceptible to cold stress, which often leads to quality deterioration. Although previous studies have examined the effects of cold stress on dwarf bananas, research on effective regulatory strategies and underlying mechanisms remains limited. This study investigates the mechanistic regulatory effects of chitosan (CTS) on cold stress in postharvest dwarf bananas, revealing that CTS mitigates cold-induced injury and improves fruit quality. Using an integrated approach of metabolomics, lipidomics, and enzyme activity assays, this study explored the potential mechanisms by which CTS alleviates chilling injury. Lipidomic results showed that CTS enhances cold tolerance by regulating the metabolism of glycerides, glycerophospholipids, linoleic acid, and linolenic acid. Metabolomics data further indicated that CTS increases the levels of amino acids, carbohydrates, and key substrates and intermediates of the tricarboxylic acid (TCA) cycle in cold-stressed dwarf bananas. Collectively, these effects enhance respiration, energy homeostasis, and antioxidant capacity, enabling dwarf bananas to better tolerate low-temperature stress. Full article

To evaluate the psycho-behavioral interaction during Ro-Ro ship evacuations, this paper proposes a coupled simulation model integrating psychological stress with behavior. The model quantifies stress through a function of local density, dwelling time, exit distance, and lifejacket retrieval waiting time, specifically accounting for the bottleneck effects during the donning phase. Using a psychological stress factor to dynamically adjust weight coefficients in the exit choice cost function, the study utilizes the AnyLogic platform to compare five scenes: shortest distance (S1), stress-induced acceleration (S2), perceptual-decay herding (S3), dynamic congestion avoidance (S4), and without retrieving lifejackets (S5). Results indicate: (1) S4 improves evacuation efficiency by 7.58% over S3 by maintaining perceptual intensity, while stress-driven acceleration (S2) shows limited effectiveness. (2) Early preparation exerts critical feedback; S4 enhances lifejacket retrieval efficiency by 14.31% over S3, alleviating initial stress and its cross-stage negative impacts. (3) Dynamic avoidance improves system resilience, keeping stressed passengers within 8.5% and breaking the “congestion-stress” vicious cycle. This study demonstrates that moderate stress must be coupled with rational exit choices. S4 effectively intervenes in stress accumulation, and S5 verified the necessity of the simulation process for retrieving lifejackets, providing a quantitative basis for resilient and robust Ro-Ro ship emergency planning and crew guidance. Full article

Understanding the dynamics of soil organic carbon (SOC) in farmland is crucial for assessing soil health, quantifying ecosystem potential for SOC enrichment, and guiding sustainable agricultural management. Existing research on SOC sequestration and mineralization has focused mainly on the topsoil layer (0–20 cm), whereas systematic evidence on how deep SOC (>20 cm) responds to agricultural management, and on strategies to enhance deep carbon sequestration, remains limited. This study uses long-term fixed-site monitoring data from 120 farmland plots across 21 typical farmland ecosystem stations and farmland–complex ecosystem stations within the Chinese Ecosystem Research Network (CERN) over 17 years (2004–2020). Using spatial analysis, we characterize the spatiotemporal dynamics of SOC below 20 cm along soil profiles across seven major geographical zones in China. We then estimate the heterogeneous effects of fertilization and straw-management practices (S, straw returning; SCF, straw returning with chemical fertilizer; OF, organic fertilizer; OCF, organic fertilizer with chemical fertilizer), tillage modes, and farmland types on SOC in the 20–40 cm, 40–60 cm, and 60–100 cm layers using a panel fixed-effects model. The results indicate pronounced vertical heterogeneity in SOC below 20 cm and a clear spatial gradient. The 60–100 cm layer shows a significant increase in SOC content during the study period, with a cumulative increase of 4.07%. Relative to single organic inputs, the co-application of organic and inorganic materials improves deep soil SOC enhancement efficiency. Compared with reduced tillage and no-tillage, conventional tillage is less conducive to SOC enhancement in layers shallower than 60 cm, yet it has a significant positive impact on SOC in the 60–100 cm layer. Compared with dryland and irrigated land, paddy fields are less favorable for SOC enhancement below 20 cm. Consequently, regarding agricultural practice, a composite tillage regime combining “surface conservation tillage with periodic deep tillage” should be promoted to foster deep SOC enhancement. Full article

Accurate estimation of global terrestrial evapotranspiration (ET) is fundamental for understanding the Earth’s water and energy cycles, yet existing multi-source ET products inevitably contain uncertainties that require spatially explicit characterization for optimal data merging or data assimilation. While Quadruple Collocation Analysis (QCA) offers a robust and reference-free approach to quantify uncertainties, its reliability in the ET discipline remains underexplored, and algorithmic non-convergence frequently results in substantial spatial data gaps. To address these limitations, this study evaluated the accuracy of the QCA method using validation errors derived from high-quality FLUXNET sites (N = 55). Moreover, we employed a Random Forest (RF) framework that is driven by 17 environmental variables to generate spatially seamless error maps for four mainstream ET products, i.e., ERA5, GLDAS, GLEAM, and MERRA2, from 2000 to 2020. Results demonstrate that QCA-based errors strongly correlated with ground-based errors as Pearson’s correlation coefficient was >0.3 for all four ET products. Furthermore, the RF model successfully reconstructed the spatial gaps in QCA errors, achieving an exceptionally low mean prediction error of approximately 0.03 mm/day. Based on these seamless maps, the global mean ET error is estimated at roughly 0.3 mm/day, with pronounced high-error clusters emerging in regions such as central Canada and northern Argentina driven by underlying land cover heterogeneity. Ultimately, this seamless gap-filling redefined the global map of product with the lowest estimated collocation error. ERA5 emerged as the superior choice across approximately 45% of the land surface (predominantly in the tropics and mid-to-high latitudes). Meanwhile, before algorithmic gap-filling, GLEAM was optimal across approximately 28% of the valid land pixels; after spatial gap-filling, it proved most effective across approximately 30% of the globe, particularly within arid deserts and glaciated regions. Our work provides useful geographic guidance for optimizing multi-source data merging and land data assimilation frameworks in future global hydrological studies. Full article

Distributed generation (DG) exhibits inherent volatility and intermittency, and its grid-integration expansion presents formidable challenges to microgrid regulation and control. Conventional control strategies often neglect the uncertainties associated with renewable energy generation and the coordinated management of flexible resources. This paper proposes a multi-time-scale optimal control strategy for microgrids that explicitly accounts for uncertainty. The strategy integrates a collaborative scheduling framework for assets, including electric vehicles (EVs) and energy storage systems, alongside a stochastic optimization model for microgrids that comprehensively incorporates uncertainties from wind and solar power generation, EV operations, and load forecasting errors. The improved Archimedean chaotic adaptive whale optimization algorithm is utilized to solve the optimal scheduling model, while the Latin hypercube sampling (LHS) technique is employed to address uncertainty-related problems in the optimization process. Case study results demonstrate that, in comparison with traditional optimal scheduling strategies, the proposed approach more effectively mitigates uncertainties in real-world operations, reduces microgrid operational risks, achieves a significant reduction in scheduling costs, and concurrently fulfills the dual objectives of microgrid economic efficiency and operational security. Full article

Background/Objectives: With the acceleration of global industrialization and continuous population growth, the world is increasingly confronted with the dual challenges of food insecurity and cultivated land contamination. The screening and breeding of rice varieties with superior agronomic traits and low heavy metal accumulation have therefore become important strategies for ensuring food safety and sustainable agricultural production. Methods: In this study, rice varieties carrying the Gn1a-i gene and exhibiting specific cadmium (Cd) accumulation characteristics were screened using a combination of molecular marker detection and cadmium accumulation evaluation. Specific loop-mediated isothermal amplification (LAMP) primers targeting the Gn1a-i gene were designed and combined with a lateral flow dipstick (LFD) assay to enable rapid genetic screening of rice varieties. A six-day hydroponic experiment under cadmium stress was conducted across three temperature ranges (15–20 °C, 22–27 °C, and 30–35 °C), and cadmium accumulation in different plant organs (roots, stem sheath, and leaves) was analyzed. Results: Seven varieties carrying the Gn1a-i gene, including Xiangwanxian 12, were identified among ten tested rice varieties. Xiangwanxian 12 was subsequently selected for further evaluation, with the high-cadmium-accumulating variety Yuzhenxiang used as a control. At 144 h, the total Cd content in the measured organs of Xiangwanxian 12 was 9.6%, 4.0%, and 23.2% lower than that of Yuzhenxiang under low, medium, and high temperatures, respectively (one-tailed t-test, p < 0.01 for all three temperatures). Conclusions: The integration of LAMP-based genotyping and physiological evaluation provides a novel and reliable strategy for identifying low-Cd rice germplasm. Xiangwanxian 12, which carries the Gn1a-i allele and exhibits consistently lower Cd accumulation than Yuzhenxiang, suggests potential as a candidate for breeding high-yield, low-Cd rice cultivars. Full article

In advanced technology nodes, mixed-cell-height circuit designs have become increasingly prevalent, posing significant challenges for legalization. We first formulate the legalization as a class of variational inequality (VI) problems defined over convex sets and then employ an existing self-adaptive inertial projection and contraction algorithm (SIPCA) to solve it. Building upon this framework, we further propose an improved self-adaptive inertial projection and contraction algorithm (SIPCA_IP) by incorporating the subgradient extragradient technique to enhance convergence efficiency and numerical stability. The proposed method preserves the advantages of projection and contraction schemes for handling VIs with nonsymmetric positive semidefinite system matrices while demonstrating faster convergence and improved robustness compared with the baseline SIPCA. Moreover, a rigorous convergence analysis is established to provide theoretical guarantees for the effectiveness of the proposed method. Numerical experiments demonstrate that the proposed method effectively addresses the mixed-cell-height legalization problem and provides a rigorous and extensible framework for solving related quadratic optimization problems. Full article

As a representative form of extreme weather, typhoons inflict widespread and systemic damage, posing a severe threat to the livestock industry. The stress they induce, typhoon stress (TS), is an unavoidable and complex environmental challenge that severely disrupts the ovarian function of Wenchang chickens. In this preliminary study, we employed a two-group comparison design (n = 6 per group) integrating behavioral observations, serum biochemical assays, histopathological examinations, and molecular analyses (qPCR, 16S rDNA sequencing, and transcriptome sequencing) to explore the role of the microbiota–gut–brain–ovarian axis (MGBOA) in this process. The findings revealed that TS markedly reduced water intake and locomotor activity, while it elevated serum corticosterone (CORT) and oxidative stress markers. It also induced shifts in gut microbiota composition, including a decrease in Bacteroides and an increase in Escherichia–Shigella. Furthermore, TS compromises duodenal intestinal barrier integrity, as evidenced by downregulation of the tight junction proteins TJP1 and CLDN1, structural damage to intestinal villi, and a reduced villus-to-crypt ratio. In the hypothalamus, VIP mRNA expression was upregulated, while GHSR expression was downregulated; the expression of the tight junction protein CLDN5 was also reduced. In the ovary, reproductive potential was suppressed, manifested by a reduction in follicle number and downregulation of STAR expression. Ovarian transcriptome analysis highlighted enrichments in pathways associated with inflammation (e.g., Toll-like receptor signaling) and lipid metabolism (e.g., PPAR signaling). These results support the hypothesis that TS impairs egg production via the MGBOA, providing preliminary mechanistic insights into how environmental stressors might disrupt animal productivity through MGBOA-mediated pathways. Full article

Wearable neurotechnology depends critically on continuous movement monitoring to characterize motor impairment and recovery in real-world settings. While joint torque serves as a clinically essential kinetic marker, estimating it directly on-device from inertial signals remains challenging due to stringent computational, memory, and energy constraints. Lightweight pipelines typically omit computationally expensive time–frequency processing; however, this omission degrades the observability of dynamics encoded in 1D IMU signals and diminishes the effectiveness of standard knowledge distillation strategies. To enable reliable on-device torque inference, we propose a Physically Guided Dual-Consistency Knowledge Distillation (PDC-KD) framework that explicitly integrates biomechanical priors into the learning process through two collaborative pathways: parameter-manifold alignment and physics-guided compensation. The student network receives guidance through Fisher-information-weighted parameter transfer, ensuring robust knowledge distillation despite significant model capacity mismatch. Furthermore, the framework incorporates a physics-guided regularization term that enforces dynamically consistent torque trajectories via a numerically stable Cholesky-parameterized constraint. Experiments demonstrate that the student model preserves teacher-level predictive accuracy while operating within the stringent resource constraints of edge devices (achieving a 98% parameter reduction, ∼2× faster inference, and ∼1 ms latency). Moreover, the proposed method yields torque estimates with enhanced dynamical consistency, providing an efficient biosignal-processing solution for wearable neurotechnology platforms demanding real-time movement analytics. Full article