Search Results (2,572)

Flexible polyurethane (PUR) foams and latex rubber foams are widely used in furniture and mattress cushioning, yet conventional standardized mechanical tests only partially capture comfort-relevant behavior, particularly in layered constructions where material interactions and sequencing can alter elastic response. This study aimed to compare the mechanical (elastic) properties of selected three-layer composites of approximately 60 mm thickness (composed of conventional PUR, high-resilience PUR, low-resilience PUR, and latex foam) and to preliminarily assess whether combining foam types improves support of such setup and whether changing layer order modifies elasticity and support. Indentation hardness testing of multilayer cushions was conducted by ISO 2439:2008 Method E. Six three-layer systems (Alpha–Zeta) were assembled in two groups. Group X showed nearly identical support factors (2.6–2.7), high recovery (64.3–66.2%), low hysteresis loss (24.3–24.5%), and overlapping force–indentation (IFD) curves, indicating minimal effect of layer order and dominance of the PUR layers. Group Y exhibited higher but more sequence-dependent support (3.1–3.7), markedly reduced, wider range recovery (30.0–45.9%), increased hysteresis (33.0–34.7%), and more dispersed IFD curves. Placing high-resilience foam at the top partially improve recovery, whereas locating low-resilience foam at the surface increase energy loss. The research contributes in part to the body of knowledge about the behavior of the tested materials according to standardized rules. These preliminary results can be compared with other research findings and used in the preparation of testing models for multilayer foam composites, thereby generating new knowledge to improve the design of future experiments, which will result in increased sitting and lying comfort. Full article

The spatial organization of microscale fillers is critical for macroscopic performance, yet precise control over their distribution and orientation remains a major challenge in direct ink writing. Here, we present an acoustofluidic capillary nozzle that integrates acoustic manipulation into direct ink writing, enabling programmable in situ assembly of functional fillers during extrusion. By coupling a piezoelectric transducer with a commercial glass capillary, stable acoustic standing waves are established within the flow channel, driving suspended filler particles toward pressure nodes via acoustic radiation forces. Simulations and experiments systematically investigate how capillary geometry and material properties influence acoustic energy distribution and particle assembly behavior. In particular, rectangular capillaries generate stable multi-node standing waves, inducing periodic alignment of nickel-coated carbon fibers into ordered conductive bundles. This acoustically programmed microstructure reduces the percolation threshold from 8 wt% to 2 wt% and enhances electrical conductivity by up to 32.1-fold at identical filler contents. Meanwhile, the composites exhibit pronounced anisotropic conductivity and maintain excellent mechanical flexibility, with stable electromechanical performance under 16% bending strain and cyclic loading. This work demonstrates a simple and scalable acoustofluidic nozzle platform for programmable microstructure engineering in direct ink writing, offering new opportunities for fabricating high-performance multifunctional composites. Full article

In engineer-to-order (ETO) manufacturing environments, the high variability of final product configurations makes it difficult to consistently estimate material consumption and, consequently, to define appropriate inventory control policies. This paper proposes a data-driven framework based on unsupervised learning to identify product typologies from historical manufacturing orders in a real industrial context. The approach employs a fuzzy k-prototypes algorithm to cluster mixed-type data, allowing the simultaneous treatment of numerical and categorical variables. In the case study, the proposed crisp-BOM-based scenario achieved a 28.67% reduction in line-side WIP and a 10.79% reduction in linear storage space, corresponding to the release of approximately two to three assembly stations. From the resulting fuzzy memberships, probabilistic bill of materials (BOM) structures are constructed, capturing the inherent variability of material consumption across different product configurations. A defuzzification procedure is then applied to obtain a crisp BOM representation suitable for operational decision-making. Additionally, a material versatility indicator based on entropy is introduced to quantify the dispersion of each material across product typologies. This indicator, together with the estimated consumption per cluster, is used as input for an analytical inventory model that supports the classification of materials into kanban or kitting policies. The methodology is validated using real data from a high- and medium-voltage switchgear manufacturing plant, comprising over 60,000 order–material observations. The results show that the proposed framework enables a more structured characterization of material behavior, reducing reliance on planner experience and improving the consistency of inventory policy decisions. From an industrial perspective, the approach provides a practical and scalable tool for aligning inventory strategies with the actual consumption patterns of ETO systems. Full article

This article explores the structural paradox of the byeong-gut (Korean shamanic healing ritual): why it adheres to the rigid and canonical format of the jaesu-gut (shamanic blessing ritual) instead of adopting a specialized clinical procedure. Critiquing the instrumental trap of previous scholarship that reduces shamanic healing to psychological comfort or social liberation, this study proposes a relational displacement model by integrating Roy Rappaport’s theory of ritual invariance with the relational ontologies of Bruno Latour and Tim Ingold. The article demonstrates that shamanic healing operates through a dual mechanism. First, at the non-discursive (material) level, the ritual functions as an ontological technology that objectifies and displaces individual suffering onto external surrogates. Second, at the discursive (linguistic) level, a meticulous analysis of the manse-baji (invocation chant) illustrates how the patient’s fragmented life is re-assembled into a meshwork of human and non-human agencies. Ultimately, this article argues that the byeong-gut transcends mere functional curing; it serves as a sophisticated knowledge system that re-maps the isolated ego onto a relational cosmology, transforming the Geertzian bafflement of suffering into an intelligible event within a shared and sacred cosmic order. Full article

In order to optimize the sealing structure of the electrolytic cell for hydrogen production by electrolysis of water and enhance its sealing performance, a finite element model of the electrolytic cell sealing was established using software. The influence of different parameters of the sealing rib structure on the sealing performance was studied, and the variation law of gasket compressive stress under different sealing rib slot widths, angles, and spacings was explored. The results show that under the material constants of C10 = 7.0 × 10⁻³ and C01 = 6.05 in the Mooney–Rivlin constitutive model of the gasket, the gasket will deform and embed into the sealing rib groove after compression. At the same time, two parts of stress concentration will occur at the contact area between the gasket and the sealing rib groove, namely tensile stress concentration and compressive stress concentration. This stress concentration is the main source of sealing effect in practical work. After adding the sealing rib groove, the contact area between the sealing rib area and the gasket increases. When maximizing the peak sealing compressive stress serves as the optimization criterion, the optimal pitch settles at 0.4 mm; if the optimization objective shifts to attaining the utmost contact area, the preferable spacing amounts to 1 mm, accompanied by a maximum contact area increment of 34.31 percent. After comprehensive deliberation over sealing stress magnitude, functional sealing area, gas tightness efficiency as well as practical engineering applicability, 0.8 mm is pinpointed in this dissertation as the globally optimal spacing dimension. With a sealing rib pitch of 0.8 mm, a breadth of 1 mm, and an inclined angle of 20 degrees, the gasket yields substantial sealing stress alongside optimized post-assembly sealing contact area, wherein 26.44 percent of the overall gasket area contributes to effective sealing performance. Full article

Finite element model updating (FEMU) is critical for structural damage identification. However, applying it to large intricate structures with abundant structural parameters is often computationally prohibitive. The substructuring method enhances computational efficiency by combining model reduction with a divide-and-conquer strategy. Its integration with FEMU can significantly accelerate the updating procedure. Nevertheless, even substructure strategies remain computationally inefficient when abundant unknown parameters are updated. This study develops a multi-level substructure-based FEMU framework for efficient and accurate structural damage identification. The proposed FEMU method first partitions the entire structure into a series of local substructures. It then condenses substructures using modal reduction and assembles them into a reduced-order global model. Subsequently, substructure-level updating is applied to localize damaged substructures. This is followed by element-level updating within the identified substructure to pinpoint specific damaged elements. Numerical validation on a frame and a high-rise building demonstrates that the proposed multi-level framework drastically improves computational efficiency compared to the conventional one-level substructure-based method. It decreases the parametric quantity in each iterative updating step and simultaneously preserves a high damage detection accuracy. Full article

In the development of deep shale gas horizontal wells, precise geo-steering relies heavily on downhole sensor networks to acquire extensive formation and engineering parameters. Coiled tubing (CT) provides a promising acoustic waveguide for downhole sensing systems, but conventional acoustic sources rely on gravity-induced interfacial preload. Under highly deviated or horizontal well conditions, the loss of the axial gravity component may induce contact–nonlinearity instability, resulting in waveform distortion and spectral pollution. To address this limitation, a constant-stiffness preloading method based on elastic compliance control is proposed, together with a modal reconstruction strategy achieved by removing high-density tungsten blocks. A fluid–solid coupled dynamic model incorporating contact nonlinearity is established to reveal the dynamic separation mechanism of the acoustic source interface under varying gravity-vector conditions. Wave spring assemblies are then used to reconstruct the mechanical boundary and physically suppress time-domain clipping. Full-scale ground circulation experiments on a 1500 ft CT string show that the proposed method decouples acoustic-source performance from wellbore trajectory. Waveform asymmetry is reduced from 18.4% to 2.1%, and total harmonic distortion decreases from 12.5% to 1.8%. In addition, the first-order longitudinal natural frequency is shifted from 420 Hz to 2850 Hz, avoiding low-frequency pump noise and achieving a 12 dB SNR improvement. This physical-layer gain provides an optimized signal baseline for receiver-end demodulation algorithms. Ultimately, this study provides a robust physical-layer solution for acoustic telemetry in complex deep-earth environments, advancing the reliability of data interaction in downhole sensing systems. Full article

The stingless bee Geniotrigona thoracica is an ecologically and economically important pollinator in Southeast Asia, yet comprehensive genomic resources for this species remain limited. In this study, we sequenced, assembled, and annotated the complete mitochondrial genome (mitogenome) of G. thoracica to investigate its genomic architecture and phylogenetic position. The circular mitogenome is 16,061 bp in length and comprises the typical set of 37 genes, including 13 protein-coding genes (PCGs), 22 transfer RNA genes, and two ribosomal RNA genes. The genome exhibits a strong A + T bias, consistent with other hymenopteran mitogenomes, and codon usage patterns reflect this nucleotide composition. Most tRNAs display the canonical cloverleaf secondary structure, although minor structural variations were observed. Comparative analyses revealed several gene rearrangements, including transposition and inversion events, suggesting lineage-specific rearrangements, including transposition of the cox1–trnL–cox2–trnD–atp8–atp6–cox3 block and transposition with inversion of the trnF–nad5–nad4–nad4l–trnP block, relative to the ancestral hymenopteran gene order. Phylogenomic analyses based on concatenated mitochondrial genes strongly supported the monophyly of Meliponini and placed G. thoracica within a well-supported Indo-Malayan clade, closely related to Tetragonula, Heterotrigona, and Lepidotrigona. Furthermore, stingless bees were recovered as more closely related to bumblebees than to honeybees, consistent with previous studies. Overall, this study provides a complete, annotated mitogenomic resource for G. thoracica and contributes to a better understanding of mitochondrial genome evolution, phylogenetic relationships, and biogeographic patterns in stingless bees. Full article

SYNGAP1-related intellectual disability presents a therapeutic paradox where genetic rescue is highly effective in neonates but limited in adults, suggesting that deficiency represents a developmental trajectory violation rather than a static biochemical defect. By synthesizing molecular, biophysical, and clinical evidence, this review proposes the “Synaptic Clock” framework, redefining SynGAP1 as a critical developmental regulator. We hypothesize that SynGAP1 operates through a strictly ordered temporal sequence: Phase I (Scaffold Assembly) utilizes the α1 isoform and phase separation to establish the structural postsynaptic density, while Phase II (Catalytic Refinement) involves isoform switching to enable activity-dependent plasticity and homeostatic scaling. This model characterizes synaptic maturation as a biophysical transition from a fluid scaffold to a consolidated gel, potentially marking the biological closure of structural rescue windows. Based on this hypothesized temporal mapping, we establish a phase-stratified therapeutic roadmap—transitioning from early-stage “reset” strategies like gene replacement to late-stage “refinement” and “compensation” via pharmacological and neuromodulatory interventions. Ultimately, validating phase-specific biomarkers, including gamma oscillations and isoform stoichiometry, is essential for shifting from generic interventions toward precision, phase-matched medicine for neurodevelopmental timing. Full article

Shallow eutrophic lakes recover from nutrient loading on time scales ranging from less than one year to many decades, yet whether this range is set by the lake or by the biological response group has rarely been quantified within a single monitoring framework. We assembled a five-year (2020–2025) quarterly monitoring panel from three shallow Yangtze-floodplain lakes (Lake Changhu, Lake Liangzihu, and Lake Honghu; 15 stations, 21 quarters) and applied a panel mixed-effect distributed lag model (PME-DLM) to estimate the lag-response windows of phytoplankton and benthic macroinvertebrate densities against five water-quality drivers. Cross-lake consistency was tested with a station-resampled bootstrap, and the contributions of water quality, season, and lake identity to community variation were resolved by three-table variation partitioning. The PME-DLM resolved a 3-month temperature window for phytoplankton and 9–15 month chlorophyll a and temperature windows for benthic communities, while total nitrogen and total phosphorus were non-significant in either group. Cross-lake bootstrap intervals on window width overlapped substantially across the three lakes, whereas cross-group differences in window centre and shape were an order of magnitude greater. Variation partitioning further showed a mirror-image structure in which phytoplankton variation was dominated by the pure water-quality fraction (12.2%) and benthic variation by the water-quality × season joint fraction (5.8%). Within the resolution of this five-year, three-lake panel, group-level differences in lag-response time scale were more apparent than lake-level differences and provide a quantitative basis for matching restoration assessment cadence to pelagic versus benthic recovery. Full article

The white rhinoceros (Ceratotherium simum) offers a unique model for investigating the genomic consequences of extreme demographic bottlenecks. However, the fragmented southern white rhinoceros genome assembly has limited chromosome-scale structural and evolutionary comparisons with the functionally extinct northern subspecies. Here, we report a chromosome-scale genome assembly for the southern white rhinoceros by integrating Oxford Nanopore Technology long-read sequencing, Illumina short-read polishing and high-throughput chromosome conformation capture (Hi-C) scaffolding. The final assembly spans 2.48 Gb and achieves a contig N50 of 42.06 Mb, representing a 452-fold improvement in contiguity over the previous assembly. In total, 2.46 Gb of sequence was anchored to 40 autosomes plus the X and Y chromosomes. Genome annotation identified 1.13 Gb of repetitive elements (45.7% of the assembly), 22,593 protein-coding genes, and 100.68 Mb of segmental duplications. Inspection of the major histocompatibility complex class II gene region further supported the local assembly and annotation reliability, revealing conserved gene composition and order between the southern and northern white rhinoceroses. Whole-genome comparison with the northern white rhinoceros assembly indicated extensive chromosome-scale synteny, along with localized structural variants between the two subspecies, including 111 inversions spanning 33.48 Mb and 497 translocations spanning 36.48 Mb. Furthermore, coalescent demographic reconstruction indicated asynchronous Pleistocene population dynamics for southern and northern white rhinoceroses, reflecting divergent responses to historical climate oscillations. Both subspecies also exhibit lower recent effective population sizes than estimated Pleistocene ancestral levels, underscoring persistent conservation concern. This assembly provides a useful resource for evaluating the genomic consequences of historical bottlenecks, informing future genomic-rescue plans, and strengthening the comparative framework for rhinoceros conservation and evolutionary genomics. Full article

Automating system-level nuclear thermal-hydraulic (T-H) model construction remains challenging because platform-specific API syntax, graph connectivity, parameter dependency ordering, and solver admissibility must be satisfied simultaneously. This study develops a closed-loop modeling framework on the SAFRI platform by combining supervised fine-tuning (SFT), a Plan-and-Act agent with retrieval-grounded parameter completion, and reinforcement learning based on group relative policy optimization (GRPO). The SFT stage uses a 6003-record domain corpus derived from expert-authored or expert-verified SAFRI modeling exemplars, while system-level generalization is evaluated on a held-out 50-case in-house evaluation set separated at the case-template level. At the component level, LoRA-adapted Qwen3-8B achieves 100% code accuracy, compared with 50% for zero-shot and 74% for one-shot prompting. At the system level, the SFT agent attains a 100% syntax success rate (SSR), 90% topology success rate (TSR), and 72.4% physical convergence rate (PCR), showing that local API correctness is insufficient for solver-valid model assembly. After GRPO training with schema, topology, physics, and sequence rewards, the full SAFRI-SFT-RL agent reaches a 100% SSR, 100% TSR, and 88.8% PCR on the in-house evaluation set, while an error self-healing loop resolves execution-time failures in an average of 2.3 corrective iterations. These results show that solver-grounded reinforcement learning is effective for closing the gap between syntactically correct script generation and physically convergent nuclear T-H model construction. Full article

Liquid crystals are intermediate states of matter, between the isotropic liquid and solid crystal. In this review we will focus on the lyotropic mixtures of materials that present ordering of their basic units and originate remarkable mesomorphic states. We discuss lyotropic materials made of amphiphilic molecules, chromonic molecules, inorganic materials and living systems. We also discuss the relations of lyotropics with biological systems and different applications of lyotropics in the food and cosmetic industry, and in drug delivery. These materials are also used as nanoreactors to produce nanomaterials on this length scale. In summary, lyotropics show a rich set of structures, obtained by their basic units self-assembly, with different symmetries, that allow their application and approach in many branches of science and technology. Moreover, lyotropics still present challenges from the theoretical point of view that are interesting to be studied, for example, the nano segregation occurring in their structure where more than one type of amphiphilic molecule is present in the mixture. Full article

The AC rotary head, serving as a dual-axis direct-drive rotary actuation unit in five-axis CNC machine tools, integrates torque motors for A- and C-axis actuation, and its structural static and dynamic characteristics directly govern the actuation accuracy, dynamic response, and stability of the electromechanical system. Its complex spatial pose variations further complicate performance prediction. To overcome the difficulty of existing local optimization methods in balancing stiffness-mass matching for such complex actuation assemblies, this paper proposes a static and dynamic performance optimization method based on stiffness-mass matching. First, a pose-dependent semi-analytical dynamic model is established using dynamic condensation and component mode synthesis (CMS) to reveal performance distribution laws across the workspace and identify weak poses. Then, Sobol’ sensitivity analysis identifies key joints and structural components, and the NSGA-II algorithm optimizes their stiffness-mass matching. Finally, a surrogate model performs dimensional parameter optimization targeting the optimized matrices. Results show that the first-order natural frequency increases by 10.5%, translational static stiffness in the X and Y directions improves by over 20%, and other directions by 4.2–18.6%. The proposed method effectively enhances global static and dynamic performance, providing theoretical guidance for the structural design of direct-drive rotary actuators in electromechanical actuation systems. Full article

The electrochemical performance of hydrogen compressors (EHCs) depends critically on the hierarchical microstructure of their catalyst layers (CLs), where platinum, carbon, and ionomer phases govern coupled charge and mass transport across nanometric (Nano) and mesoporous (Meso) scales, the latter characterized by agglomerate and pore phases. This work presents an experimental–computational framework to establish quantitative microstructure–transport–performance relationships in EHC CLs. CLs were fabricated by electrospray deposition on Nafion^® 117 membranes and characterized by scanning electron microscopy, from which 33 representative Meso MCs were extracted and used to assemble an EHC cell for experimental polarization curves. Statistically equivalent Nano MCs resolved phase connectivity within the agglomerate phase and determined the effective catalyst area from neighboring phase configurations. Effective transport coefficients for electronic conductivity, protonic conductivity, and H₂ diffusivity were computed via the finite volume method and multiscale-coupled into an analytical polarization model. Electronic and protonic conductivities are controlled by conductive-phase connectivity at the Nano scale, while H₂ diffusivity is governed by the pore fraction and spatial distribution at the Meso scale, with variations exceeding three orders of magnitude. Multiscale transport coupling factors obtained via inverse calibration reduced model–experiment discrepancies to 0.05 V, validating the framework for EHC electrode design. Full article