Search Results (5,906)

This study investigated the impact of green tea addition on microbial community dynamics during Daqu fermentation, a critical process in traditional baijiu production. Four Daqu variants (0%, 10%, 20%, 30% tea) were analyzed across six fermentation periods using 16S rRNA/ITS sequencing, coupled with STR, TDR, Sloan neutral model, and phylogenetic analyses. Results showed time-dependent increases in bacterial/fungal richness, with 30% tea maximizing species richness. Tea delayed bacterial shifts until day 15 but accelerated fungal reconstruction from day 6, expanding the temporal response window. While stochastic processes dominated initial assembly (77–94% bacteria, 88–99% fungi), deterministic processes intensified with tea concentration, particularly in fungi (1% → 12%). Tea increased bacterial dispersal limitation and reduced phylogenetic conservatism of endogenous factors. This work proposed a framework for rationally engineering fermentation ecosystems by decoding evolutionary-ecological rules of microbial assembly. It revealed how plant-derived additives can strategically adjust niche partitioning and ancestral constraints to reprogram microbiome functionality. These findings provided a theoretical foundation in practical strategies for optimizing industrial baijiu production through targeted ecological interventions. Full article

High-performance batteries for military and extreme environment applications require alternatives to conventional liquid lithium-ion batteries (LIBs), which suffer from poor low-temperature performance and safety risks. All-solid-state lithium batteries (ASSLBs) offer enhanced safety and superior low-temperature capability. In this work, we designed and fabricated composite solid-state electrolytes using polyvinylidene fluoride (PVDF) and polyacrylic acid (PAA) as polymer matrices, N,N-dimethylformamide (DMF) as the solvent, and lithium bis(trifluoromethane sulfonimide) (LiTFSI) as the lithium salt. Composite solutions with varying PAA mass ratios were prepared. Advanced three-dimensional (3D) printing technology enabled the rapid and precise fabrication of electrolyte membranes. An ionic conductivity of about 2.71 × 10⁻⁴ S cm⁻¹ at 25 °C, high mechanical strength, and good thermal properties can be achieved through component and 3D printing process optimization. Assembled LiCoO₂||PVDF@PAA||Li ASSLBs delivered an initial discharge capacity of 165.3 mAh/g at 0.1 mA cm⁻² (room temperature), maintaining 98% capacity retention after 300 cycles. At 0 °C, these cells provided 157.4 mAh/g initial capacity with 85% retention over 100 cycles at 0.1 mA cm⁻². This work identifies the optimal PAA ratio for enhanced electrochemical performance and demonstrates the viability of 3D printing for advanced ASSLB manufacturing. Full article

Shiga toxin-producing Escherichia coli (STEC) are genetically diverse foodborne pathogens of major global public health concerns. Serogroup-level identification is critical for effective surveillance and outbreak control; however, it is often challenged by STEC’s genome plasticity and frequent recombination. In this study, we employed a standardized pangenomic pipeline integrating Roary ILP Bacterial Core Annotation Pipeline (RIBAP) and Panaroo to analyze 160 complete, high-quality STEC genomes representing eight major serogroups at a 95% sequence identity threshold. Candidate serogroup-specific markers were identified using gene presence/absence profiles from RIBAP and Panaroo. Our analysis revealed several high-confidence markers, including metabolic genes (dgcE, fcl_2, dmsA, hisC) and surface polysaccharide-related genes (capD, rfbX, wzzB). Comparative pangenomic evaluation showed that RIBAP predicted a larger pangenome size than Panaroo. Additionally, some genomes from the O104:H1, O145:H28, and O45:H2 serotypes clustered outside their expected clades, indicating sporadic serotype misplacements in phylogenetic reconstructions. Functional annotation suggested that most candidate markers are involved in critical processes such as glucose metabolism, lipopolysaccharide biosynthesis, and cell surface assembly. Notably, approximately 22.9% of the identified proteins were annotated as hypothetical. Overall, this study highlights the utility of pangenomic analysis for potential identification of clinically relevant STEC serogroups markers and phylogenetic interpretation. We also note that pangenome analysis could guide the development of more accurate diagnostic and surveillance tools. Full article

High-precision assembly plays a central role in aerospace, defense, and precision instrumentation, where errors in bolt preload or tightening sequences can directly degrade product reliability and lead to costly rework. Traditional finite element analysis (FEA) offers accuracy but is too computationally expensive for iterative or real-time optimization. Surrogate models are a promising alternative, yet conventional machine learning methods often neglect the sequential and constraint-aware nature of multi-bolt assembly. To overcome these limitations, this paper introduces an integrated framework that combines an Attention-based Bidirectional Long Short-Term Memory (AB-BiLSTM) surrogate with a stratified version of the Harris Hawks Optimizer (SEG-HHO). The AB-BiLSTM captures temporal dependencies in preload evolution while providing interpretability through attention–weight visualization, linking model focus to physical assembly dynamics. SEG-HHO employs an encoding–decoding mechanism to embed engineering constraints, enabling efficient search in complex and constrained design spaces. Validation on a gyroscope assembly task demonstrates that the framework achieves high predictive accuracy (Mean Absolute Error of 3.59 × 10⁻⁵), reduces optimization cost by orders of magnitude compared with FEA, and reveals physically meaningful patterns in bolt interactions. These results indicate a scalable and interpretable solution for precision assembly optimization. Full article

Wnt/β-catenin signaling is hyper-activated in several cancer cells and cancer stem cells. Dishevelled/Dvl is a key adapter protein that acts as a bridge between the Wnt receptor Frizzled (Fzd) and other cytosolic factors. In detail, the C-terminal cytosolic region is the ligand of the PSD-95, disks large, and zonula occludens-1 (PDZ) domain of Dvl. Therefore, the PDZ domain (Dvl-PDZ) is thought to be a potential drug target. In this paper, we determined the first crystal structure of the PDZ domain of human Dvl1 (hDvl1-PDZ) at a 2.4 Å resolution. The domain was adapted into a unique trimeric form in which all the canonical ligand-binding clefts were occupied by the β2-β3 loop of the neighbor molecule, like an auto-inhibiting trimer. We used solution nuclear magnetic resonance (NMR) experiments to assess the presence of the self-associated oligomer of hDvl1-PDZ in the solution. Introducing the Ala substitution at Asp 272, the key residue of the β2-β3 loop, partly abolished the concentration-dependent chemical shift change, which suggests that this residue is one of the key residues for formation. Based on these observations, we propose an auto-inhibiting trimer formation of Dvl-PDZ in a Dvl-Axin hetero-oligomerization model of Wnt/β-catenin signal transduction. Full article

Conductive polymer thin films have emerged as a versatile class of materials with immense potential in energy storage and conversion technologies due to their unique combination of electrical conductivity, mechanical flexibility, and tunable physicochemical properties. This review comprehensively explores the role of conductive polymer thin films in three critical energy applications: supercapacitors, batteries, and solar cells. The paper examines key polymers such as polyaniline (PANI), polypyrrole (PPy), and poly(3,4-ethylenedioxythiophene) (PEDOT), focusing on their synthesis techniques, structural modifications, and integration strategies to enhance device performance. Recent advances in film fabrication methods, including solution processing, electrochemical deposition, and layer-by-layer assembly, are discussed with regard to achieving optimized morphology, conductivity, and electrochemical stability. Furthermore, the review highlights current challenges such as scalability, long-term durability, and interfacial compatibility, while outlining future directions for the development of high-performance, sustainable energy systems based on conductive polymer thin films. Full article

As global manufacturing faces rising energy costs, environmental pressures, and machining precision, the development trends of the machine tools are moving towards lightweight and high-rigidity structures. While those approaches of increasing key component geometrical size or enhancing rib design do enhance rigidity performance, they also usually increase weight, which conflicts with the goals of achieving high performance and environmental sustainability. Therefore, how to achieve system lightweightness while maintaining or enhancing structural rigidity has become a key research challenge. This study adopts a biomimetic design approach, drawing inspiration from the natural growth features of biological structures. By integrating these natural structural features, the design aims to enhance rigidity while reducing weight. Static and modal analyses are conducted firstly by using FEM software to simulate the total deformation, natural frequency, and modal shape, respectively. The biomimetic designs are then performed on those subsystems in a grinding machine-tool, which exhibit larger deformation and weaker stiffness by incorporating the structural features of leaf veins, cacti, and bamboos. Single or multiple structural feature combinations are constituted during the biomimetic design processes for worktable, base, and column subsystems, and the natural frequencies and weight obtained from the numerical analysis were compared subsequently to identify the better bionic subsystems that replace the corresponding ones originally assembled in the grinding machine-tool finally. The results show that one of the first three mode natural frequencies of a better bionic worktable (leaf vein and cactus) is increased up to 7.07%, with a 1.12% weight reduction. A better bionic base (leaf vein) with corner trimming exhibits a 14.04% increase in natural frequency and a 2.04% weight reduction. Similarly, a better bionic column (bamboo) achieves a 5.58% increase in natural frequency and a 0.14% weight reduction. After these better bionic subsystems are substituted in the grinding machine-tool, one of the first three mode natural frequencies is increased up to 14.56%, the weight is reduced by 1.25%, and the maximum total deformation is decreased by 39.64%. The maximum total deformation for the headstock is reduced by 26.95% after the original grinding machine-tool is replaced by better bionic subsystems. The increases in the specific stiffness for these better bionic subsystems are also investigated in this study to illustrate the effectiveness of the biomimetic designs. Full article

This study explores the integration of circular design principles into automotive product development, focusing on the environmental implications of design decisions related to geometry, material selection, and assembly methods. A case study approach was used to iteratively redesign a plastic automotive component, incorporating structural reinforcements and glass fiber (GF) to enhance performance. While these changes improved mechanical properties, they negatively impacted recyclability due to increased material heterogeneity and irreversible assembly using ultrasonic welding. Circularity performance was evaluated using the Recycling Desirability Index (RDI), Material Circularity Indicator (MCI), and circular design guidelines (CDGs). Despite achieving 20% recycled content, recyclability remained limited. Alternative design strategies—such as eliminating GF, replacing welding with mechanical fasteners, and enabling take-back systems—led to significant improvements in circularity scores. Notably, MCI analysis indicated that energy recovery pathways offered better circularity outcomes than landfilling. The findings highlight the importance of early-stage material standardization and assembly planning to enhance end-of-life recovery. This study underscores the environmental trade-offs inherent in current automotive design practices and calls for stronger collaboration between engineers, designers, and sustainability experts to align product development with circular economy goals. Findings emphasize the need for systemic changes in product development processes and industrial mindsets, including overcoming resistance to design modifications and fostering cross-departmental collaboration, to effectively implement circular economy principles in the automotive sector. Full article

This study introduces a novel energy-based inverse method for estimating residual stresses in structures composed of one-dimensional elements undergoing elastic–plastic deformation. The problem is reformulated as a global optimization task governed by the principle of minimum total potential energy. Rather than solving equilibrium equations directly, the internal stress distribution is inferred by minimizing the structure’s total potential energy using a real-coded genetic algorithm. This approach avoids gradient-based solvers, matrix assembly, and incremental loading, making it suitable for nonlinear and history-dependent systems. Plastic deformation is encoded through element-wise stress-free lengths, and a dynamic fitness exponent strategy adaptively controls selection pressure during the evolutionary process. The method is validated on single- and multi-bar truss structures under axial tensile loading, using a bilinear elastoplastic material model. The results are benchmarked against nonlinear finite element simulations and analytical calculations, demonstrating excellent predictive capability with stress errors typically below 1%. In multi-material systems, the technique accurately reconstructs tensile and compressive residual stresses arising from elastic–plastic mismatch using only post-load geometry. These results demonstrate the method’s robustness and accuracy, offering a fully non-incremental, variational alternative to traditional inverse approaches. Its flexibility and computational efficiency make it a promising tool for residual stress estimation in complex structural applications involving plasticity and material heterogeneity. Full article

Orchidaceae is among the most diverse and widely distributed families of angiosperms, with significant ecological, ornamental, and medicinal value. However, the structure, function, and environmental associations of rhizosphere soil bacterial communities associated with Orchidaceae remain poorly characterized. This study selected five common Orchidaceae species in the transitional zone between the warm temperate and subtropical regions of China (Changnienia amoena, Cypripedium macranthos, Cremastra appendiculata, Cymbidium faberi, and Gastrodia elata). Using high-throughput sequencing technology, we characterized the bacterial diversity of the rhizosphere soil associated with these species and investigated their relationships with soil physicochemical properties. The results show significant differences in the structure of rhizosphere soil bacterial communities among the five Orchidaceae species. The principal environmental factors influencing these communities differ across species. Fermentation functional bacteria dominate the rhizosphere bacterial communities. The community assembly processes of specialized and generalized species are governed by deterministic and stochastic processes, respectively, indicating complex ecological mechanisms. This study clarifies the structural characteristics, functional differentiation, and environmental response mechanisms of rhizosphere soil bacterial communities across Orchidaceae species. It provides a theoretical foundation for the conservation and sustainable utilization of Orchidaceae from a microbiological perspective. Full article

In high-precision fields such as advanced manufacturing, semiconductor processing, aerospace assembly, and precision machining, motion control systems often face challenges such as large tracking errors and low control efficiency due to complex dynamic environments. To address this, this paper innovatively proposes a data-driven feedforward compensation control strategy based on a Parallel Gated Recurrent Unit (GRU)–Transformer. This method does not require an accurate model of the controlled object but instead uses motion error data and controller output data collected from actual operating conditions to complete network training and real-time prediction, thereby reducing data requirements. The proposed feedforward control strategy consists of three main parts: first, a Parallel GRU–Transformer prediction model is constructed using real-world data collected from high-precision sensors, enabling precise prediction of system motion errors after a single training session; second, a nonlinear PD controller is introduced, using the prediction errors output by the Parallel GRU–Transformer network as input to generate the primary correction force, thereby significantly reducing reliance on the main controller; and finally, the output of the nonlinear PD controller is combined with the output of the main controller to jointly drive the precision motion platform. Verification on a permanent magnet synchronous linear motor motion platform demonstrates that the control strategy integrating Parallel GRU–Transformer feedforward compensation significantly reduces the tracking error and fluctuations under different trajectories while minimizing moving average (MA) and moving standard deviation (MSD), enhancing the system’s robustness against environmental disturbances and effectively alleviating the load on the main controller. The proposed method provides innovative insights and reliable guarantees for the widespread application of precision motion control in industrial and research fields. Full article

Due to persistent poaching and habitat fragmentation, wild forest musk deer (Moschus berezovskii) in China have sharply declined; although captive breeding helps, frequent gut diseases limit further expansion. This study used high-throughput 16S rRNA sequencing to analyze the effects of age, season variation, and compound probiotics on the gut microbiota of captive individuals. The results demonstrated that compound probiotics exerted a significantly greater influence on gut microbial composition, α-diversity, and functional variation compared to the effects of age or seasonal factors. β-diversity analysis confirmed greater differences between probiotic-treated and control groups than among age or seasonal groups. Microbial community assembly was mainly driven by deterministic processes, with stochastic processes also playing a role in winter. Compound probiotics markedly reshaped dominant bacterial taxa at both phylum and genus levels, with Acinetobacter identified as a key biomarker. They also significantly modulated metabolic and phenotypic traits, decreasing functions related to Gram-positive and aerobic bacteria while enhancing those linked to Gram-negative characteristics. Environmental correlation analysis further demonstrated that compound probiotics exerted a stronger influence than both age and seasonal factors. The findings underscore the value of dietary and probiotic strategies for enhancing gut health and resilience in endangered forest musk deer. Full article

This paper presents an integrated workflow for smart manufacturing, combining CAD modeling, Digital Twin synchronization, and automated visual inspection to detect defective fuses in industrial electrical panels. The proposed system connects Onshape CAD models with a collaborative robot via the ThingWorx IoT platform and leverages computer vision with HSV color segmentation for real-time fuse validation. A custom ROI-based calibration method is implemented to address visual variation across fuse types, and a 5-s time-window validation improves detection robustness under fluctuating conditions. The system achieves a 95% accuracy rate across two fuse box types, with confidence intervals reported for statistical significance. Experimental findings indicate an approximate 85% decrease in manual intervention duration. Because of its adaptability and extensibility, the design can be implemented in a variety of assembly processes and provides a foundation for smart factory systems that are more scalable and independent. Full article

Aqueous two-phase systems (ATPSs) based on two incompatible polymers have recently garnered considerable attention due to the promising characteristics of all-aqueous emulsions for a range of applications. Recent investigations have indicated strong potential for interfacial assemblies of oppositely charged components in the stabilization of these emulsions. The formation of these confined assemblies is likely to depend on the size of the ATPS-constituting polymers; however, the role of this parameter remains to be elucidated. The primary objective of this study was to examine the effect of polyethylene oxide (PEO) molecular weight on the aging processes of PEO/dextran emulsions that are stabilized by the interfacial association of oppositely charged silica particles and polycations. It has been demonstrated that the stability of emulsions containing one high-molecular-weight dextran is significantly enhanced by increasing the size of the PEO molecules. Furthermore, a compression-induced bijel formation was observed in the ATPS with the largest molecular weight PEO sample. The observations were explained by the impact of the rheology of the aqueous phases on the aggregation, adsorption, and network formation capabilities of polycation/silica assemblies. These findings may facilitate the design of stable all-aqueous emulsions with optimal molecular weights for the ATPS-forming polymers. Full article

To reveal how the altitude gradient regulates the effects of rhizosphere microbial dynamics on ecosystem multifunctionality in Hylodesmum podocarpum, a field experiment was conducted across four elevation transects (a.s. 896–1805 m) in the Qinling Mountains. The results showed that rhizosphere soil exhibited peak microbial diversity richness at 1805 m (HB4), with bacterial communities showing a strong interspecific cooperative relationship, while the fungal communities showed a competitive relationship. In addition, this study found the assembly process to be different. Bacterial assemblages changed from random processes (HB1, HB2, HB3) to deterministic processes (HB4), whereas fungal assemblages remained stochastic processes across all elevations. Our results also revealed that synergistic interactions among soil carbon, phosphorus, and nitrogen nutrient functions collectively enhanced nutrient-centered soil multifunctionality. Notably, carbon and phosphorus nutrient functions emerged as the primary drivers of soil multifunctionality. Further mechanistic analysis revealed that while soil pH exerted significant control over both carbon and nitrogen nutrient functions, microbial mediation exhibited functional specialization: bacterial communities predominantly regulated carbon cycling, whereas fungal communities played a more comprehensive role in modulating carbon, nitrogen, and phosphorus dynamics along with overall ecosystem multifunctionality. This finding suggested that altitude gradients indirectly affect the characteristics of the microbial community by regulating soil nutrient status, thereby driving changes in ecosystem multifunctionality. This finding provides new insights into how nutrients regulate ecosystem functions through microbial pathways. Full article