Search Results (125)

This work presents a probabilistic methodology for the analysis and design of detonation sequences in non-electric blasting, considering both the statistical dispersion of pyrotechnic delays and the dependencies between detonation time intervals. These intervals are modeled as correlated multivariate normal random variables, allowing the estimation of blast success probability based on the simultaneous fulfillment of the desired firing order and the minimum time interval between consecutive detonations. The main contribution of this work is a general matrix formulation based on block matrices that provides a unified framework for representing and analyzing different non-electric initiation network configurations. The proposed formulation enables the direct computation of the mean vector and covariance matrix of detonation intervals from the statistical properties of connectors and detonators, while remaining readily scalable to complex layouts involving multiple rows and branching connection chains. Numerical examples demonstrate the strong influence of delay dispersion and network topology on blast reliability and illustrate the applicability of the proposed methodology to the probabilistic analysis and optimization of complex firing sequences. Full article

Immunosenescence is a major contributor to age-associated morbidity, yet microbiota-directed strategies capable of restoring immune homeostasis remain insufficiently validated. Medicinal plant polysaccharides (MPPs) are structurally diverse macromolecules that often resist host digestion and undergo microbial transformation in the colon, but their effects cannot be interpreted as those of a homogeneous intervention class. In this structured narrative review, we critically synthesize evidence across structural carbohydrate biology, microbial ecology, metabolite signaling, and immune aging and propose a structure–microbiota–metabolite–immunity framework for evaluating how MPPs may influence immunosenescence. Monosaccharide composition, glycosidic linkages, molecular-weight distribution, branching, uronic acid content, chemical substitutions, and higher-order conformation can shape microbial carbohydrate-active enzyme activity, polysaccharide utilization, and ecological cross-feeding. The resulting changes in short-chain fatty acids, secondary bile acids, tryptophan-derived indoles, and other metabolites may affect epithelial barrier integrity, regulatory T-cell/T helper 17-cell (Treg/Th17) balance, macrophage polarization, nuclear factor-κB (NF-κB) signaling, NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation, and systemic inflammatory tone. However, evidence from in vitro systems and young disease models primarily supports mechanistic plausibility and should not be treated as direct evidence of immunosenescence modification. Translation will require structurally defined preparations, causal validation in aging-relevant models, comparison with established fermentable fibers, identification of responder phenotypes, and adequately powered trials in older adults. Full article

Compression–torsion coupled metamaterials provide a geometry-driven approach for motion conversion and wave regulation. This study proposes a spatial curved-rod compression–torsion coupled metastructure and develops a reduced-order equivalent stiffness model with axial displacement and rotational angle as the generalized degrees of freedom. The equivalent stiffness matrix, derived from the curved-rod centerline geometry through a strain-energy formulation, is incorporated into a one-dimensional Bloch model to characterize low-frequency wave propagation. The results show that the off-diagonal coupling stiffness governs the compression-induced rotational response of the unit cell and significantly affects the frequencies and modal compositions of the two lowest dispersion branches. Finite element simulations and experiments validate the predicted stiffness and compression–torsion response, while acceleration transmissibility measurements of a finite periodic chain are consistent with the theoretical dispersion characteristics. The reduced-order model captures the overall behavior of the two lowest branches and clarifies the role of compression–torsion coupling stiffness in branch separation and modal composition, although the higher branch is less accurately predicted owing to the lumped inertia approximation. The proposed design provides a lightweight strategy for low-frequency wave regulation through structural coupling. Full article

Quantitative phylogenetics in historical linguistics has relied almost entirely on lexical cognate data. This study asks a different question: how much genealogical signal can be recovered from structural features extracted from annotated corpora, and whether it survives at deep time depths. We compute 29 structural features—including Shannon entropies of dependency direction and of dependency-relation distributions, relation-specific directionality ratios, dependency-distance measures, and constructional ratios—across 25 Transeurasian languages from the five proposed groups (Turkic, Mongolic, Tungusic, Japonic, and Koreanic) and three outgroups (Chinese, Vietnamese, and Hindi), 28 languages in all. Most of the Tungusic and Mongolic languages have no running-text corpus, so we built new Universal Dependencies treebanks for them by glossing example sentences from reference grammars; thirteen are used here. Each feature was tested for phylogenetic signal (Pagel’s λ and Blomberg’s K, with FDR correction) under four competing reference topologies, and the features that passed were used for tree inference (Bayesian inference in MrBayes, with Neighbor-Joining as a check). The same pipeline was first run on Indo-European in a companion study, where it recovers only individual subgroups and does not resolve a stable tree. At the depth proposed for the Transeurasian family (a Proto-Transeurasian root of about 9000 years before present), the structural signal was not enough to reconstruct the family’s internal relationships. The signal tests favoured a flat three-way division of the major branches (7 strict/20 relaxed features) over any nested hypothesis (≤2 strict features each), and the strongest signal lay in core word-order parameters (e.g., object direction, λ = 1.00, K = 6.06). But both Bayesian and distance-based inference returned near-complete polytomies: although the chains converged (ASDSF < 0.01), no branch reached a posterior probability above 0.75, and none of the three multi-language branches (Turkic, Mongolic, or Tungusic) was recovered. The outgroup test made the reason clear: Hindi, which is Indo-European but SOV, grouped with the head-final Transeurasian languages rather than with the other two (head-initial) outgroups, so the features are tracking typological similarity, not shared descent, at this depth. The study contributes 13 new treebanks for poorly documented languages, a reproducible framework for testing how much genealogical signal structural features carry, and direct evidence that, at Transeurasian time depths, this signal reflects typology rather than genealogy. Full article

Understanding gene expression requires integrating multiple regulatory layers, because transcript abundance does not necessarily correspond to translational activity or protein abundance. Ribosome profiling and proteomics help distinguish increased translation from ribosome stacking or translational buffering, but no de facto standard framework exists for unsupervised integration of transcriptome, translatome, and proteome profiles. Here, we propose a four-dimensional tensor decomposition-based unsupervised feature extraction approach for tri-omics integration. We applied higher-order singular value decomposition to transcriptome, Ribo-seq, and proteome profiles measured under branched-chain amino acid starvation. The resulting singular value vectors captured relationships among the three omics layers, including a component consistent with ribosome stacking, where transcriptome and translatome signals increased while proteome signals decreased, and another consistent with translational buffering, where proteome variation was suppressed despite transcriptome and translatome changes. Gene selection identified 1781 genes associated with ribosome stacking and 227 genes associated with translational buffering. Enrichment analyses linked the former to translation, post-translational protein modification, RNA polymerase II transcription, cell cycle regulation, endoplasmic reticulum protein processing, ubiquitin-mediated proteolysis, and stress-related pathways, and the latter to ribosome, translation elongation and termination, spliceosome, immune- and stress-related pathways, and ribosomopathy-associated diseases. Robustness analyses indicated that the results were not substantially affected by the duplicated proteome replicate or missing-value handling. Under the tested settings, comparison with MOFA+ and mixOmics suggested that our approach more directly extracted components interpretable as ribosome stacking and translational buffering. These results demonstrate that tensor decomposition-based unsupervised feature extraction is useful for identifying functionally relevant gene clusters from tri-omics data. Full article

The bearingless induction motor (BIM) relies on accurate displacement feedback to maintain stable magnetic suspension, but sensor faults, degradation, and noise can distort feedback and induce transients during branch switching. This paper proposes a confidence-fusion-based fault-tolerant displacement measurement method for the BIM suspension feedback chain. A four-channel asymmetric redundant sensor configuration is developed, and channel state evaluation functions are constructed from sampling-difference terms and geometric-consistency residuals. A decreasing Sigmoid mapping with first-order smoothing generates continuous confidence coefficients to represent channel health. Combined with discrete fault flags of the primary channels, four reconstruction branches, AB, BC, AC, and CD, are adaptively weighted to obtain the reconstructed displacement, which is connected to the original suspension controller through a smooth feedback access mechanism. A MATLAB/Simulink closed-loop suspension model is used to evaluate the method under fault-free operation, an abrupt fault of primary channel A, simultaneous and sequential faults of primary channels A and B, abrupt and gradual degradation, constant bias, intermittent signal dropouts, and noise disturbance of primary channel B. Results show that the method identifies abnormal primary channels, redistributes reconstruction weights according to sensor conditions, and maintains a fallback path through the CD branch under dual-primary-channel failure. Under channel-B degradation, the confidence coefficient tracks the deterioration and supports the subsequent AB-to-AC branch transfer, whereas under noise disturbance, the fault flag remains inactive and unnecessary branch switching is avoided. The method improves feedback continuity without changing the main suspension controller. Full article

Locally sourced roughages constitute the dietary foundation of donkey production in northern China, yet their fermentation behavior in the donkey hindgut remains poorly characterized. The present study employed in vitro batch cultures to compare the dry matter disappearance (IVDMD), gas production (GP) kinetics and short-chain volatile fatty acid (VFA) profiles of five locally available feedstuffs—peanut vine (PNV), soybean straw (SBS), wheat shell (WS), reed grass (RG) and bamboo leaf (BL)—when incubated separately with cecal or colonic microbial inocula obtained from Dezhou donkeys. After 40 h incubation, both IVDMD and total VFA concentrations ranked identically across the two hindgut segments: PNV > SBS > WS > RG > BL (p < 0.05), and all indices were consistently higher in the cecal than in the colonic fermentation system (p < 0.05). The asymptotic gas production (A) and the time required to reach half of A (T₁/₂) followed the same ranking as IVDMD (p < 0.01), indicating that feedstuffs with greater fermentable substrate availability sustained fermentation for longer periods. In contrast, the fractional gas production rate (c) and the average gas production rate (AGPR) in RG and BL exceeded those of PNV, SBS, and WS under cecal incubation (p < 0.05), reflecting rapid utilization of a small pool of readily fermentable components in these fibrous substrates. Regarding VFA stoichiometry, BL yielded the highest molar proportion of acetate and PNV the lowest in the colonic system (p < 0.05), whereas the propionate proportion followed the order PNV > SBS > WS > RG > BL (p < 0.01). Consequently, the acetate-to-propionate (A:P) ratio and the non-glucogenic-to-glucogenic (NGR) ratio were highest in BL (p < 0.05). The molar proportions of butyrate and branched-chain VFAs (BCVFAs) in WS, RG, and BL were greater than those in PNV (p < 0.05). Collectively, the five feedstuffs differed markedly in their fermentability, kinetic behavior, and VFA yield profiles, reflecting distinct energy-supply potentials for the donkey host. PNV and SBS exhibited superior overall in vitro fermentation performance and are therefore recommended as preferred roughage sources, whereas BL and RG may serve complementary roles by supporting hindgut epithelial health through elevated butyrate production. These findings provide a mechanistic basis for the rational selection and combination of locally sourced roughages to optimize feeding strategies and improve feed-use efficiency in donkey production. Full article

ASP flooding wastewater contains crude oil, suspended solids, anionic polymers and surfactants, with high viscosity, high zeta potential, difficult demulsification, flocculation and slow separation and sedimentation. In order to solve the problem of wastewater treatment of ASP flooding in oil fields, a magnetic branched core was prepared from ethyl silicate (TEOS), nano Fe₃O₄ and aminopropyl triethoxysilane (APTES), and then reacted with polyamine and methyl acrylate to synthesize the magnetic hyperbranched molecule FSNMN with demulsification ability. Using acrylamide (AM), acryloxyethyl trimethylammonium chloride (DAC) and maleic anhydride (MA) as raw materials, cationic polymer long chain (CAMHA) with flocculating properties was synthesized and grafted with hyperbranched molecules. The demulsification flocculation ability of the product regarding ASP flooding wastewater was evaluated, and the demulsification flocculation mechanism was summarized. The results showed that the average molecular weight of 3-FSNMN₄-C was 4.7 million, the cationic degree was 20.5%, and the saturation magnetization was 20 EMU/g. The removal rate of oil and suspended solids was 93.82% and 91.95% respectively when the simulated sewage was treated by magnetic field for 30 min. Magnetic hyperbranched star chain polymer provides a solution to the serious ecological environment problems caused by ASP flooding. Full article

Rigid-body chain following on piecewise analytic paths is a fundamental subroutine in motion planning and multibody simulation. The problem is nontrivial when only the leader trajectory of the first node is available: enforcing fixed inter-node distances reduces to circle–curve intersection, which is generally multi-valued and becomes particularly challenging near non-smooth junctions. We present a Dichotomy Geometric Path Search (DGPS) framework that converts each constraint into a one-dimensional root-finding task and resolves the branch selection through no-backtracking ordering: at every time step, the admissible solution for the current node is the nearest feasible root in the past relative to its immediately preceding node. DGPS combines backward bracketing with bisection, achieving robust convergence. Compared with the inverse Jacobian method, which maps end-effector velocities to joint velocities via explicit inversion, the proposed approach avoids Jacobian inversion and globally coupled nonlinear solves. We further characterize the local structure of the zero set and establish monotonicity/uniqueness conditions that justify stable root selection across piecewise junctions. Extensive tests on representative piecewise trajectories (line–arc–line, polylines with corners, piecewise sinusoids, and time reparameterization) show that DGPS enforces distance constraints to near machine precision, produces interpretable speed/acceleration transients around non-smooth events, and exhibits computational costs consistent with iteration difficulty. The results support DGPS as a general, efficient solver requiring only the prescribed leader trajectory. Full article

Climate variability represents a growing challenge for livestock systems; however, its indirect economic effects remain insufficiently understood, particularly in data-scarce contexts. This study evaluates whether satellite-derived bioclimatic indices propagate into short-term variability of livestock-related sales from a digital agriculture perspective. Weekly commercial records from two geographically proximate livestock branches in Ecuador were integrated with meteorological data provided from NASA POWER to compute the Temperature Humidity Index (THI). A basal temperature index, defined as a four-week moving average of THI, and a corresponding thermal anomaly were derived in order to represent both cumulative and short-term thermal conditions. Linear time series models incorporating exogenous variables (ARIMAX) and a non-linear machine learning approach (Random Forest) were employed using lagged climatic and economic features. The results showed that linear models had limited explanatory capacity, indicating that short-term sales variability was primarily driven by market dynamics and logistical processes rather than direct climatic forcing. While the Random Forest model achieved better predictive performance, this was mainly due to its ability to capture systemic inertia and autoregressive structure in the sales series; climatic variables only provided a secondary, indirect signal. These findings highlight the value of artificial intelligence in identifying weak and delayed climate-related patterns in aggregated commercial indicators and support of satellite-based climate data in market-level decision making in livestock supply chains where animal-level measurements are unavailable. Full article

Per- and polyfluoroalkyl substances (PFASs), as a class of “permanent chemicals” with high environmental persistence and bioaccumulation, have attracted much attention. In this study, we focused on the molecular mechanism of the interaction between perfluoroalkyl acids (PFAAs) and peroxisome proliferator-activated receptor δ (PPARδ). Using molecular docking, binding free energy calculation, and structural analysis, we systematically investigated the binding modes, key amino acid residues, and binding energies of 20 structurally diverse PFAAs with PPARδ. The results showed that the binding energies of PFAAs with PPARδ were significantly affected by the molecular weight, the number of hydrogen bond donors, and the melting point of PFAAs. PFAAs with smaller molecular weights and fewer hydrogen bond donors showed stronger binding affinity. The binding sites were concentrated in high-frequency amino acid residues such as TRP-256, ASN-269, and GLY-270, and the interaction forces were dominated by hydrogen and halogen bonds. PFAAs with branched structure of larger molecular weight (e.g., 3m-PFOA, binding energy of −2.92 kcal·mol⁻¹; 3,3m₂-PFOA, binding energy of −2.45 kcal·mol⁻¹) had weaker binding energies than their straight-chain counterparts due to spatial site-blocking effect. In addition, validation group experiments further confirmed the regulation law of binding strength by physicochemical properties. In order to verify the binding stability of the key complexes predicted by molecular docking, and to investigate the dynamic behavior under the conditions of solvation and protein flexibility, molecular dynamics simulations were conducted on PFBA, PFOA, 3,3m₂-PFOA, and PFHxA. The results confirmed the dynamic stability of the binding of the high-affinity ligands selected through docking to PPARδ. Moreover, the influence of molecular weight and branched structure on the binding strength was quantitatively verified from the perspectives of energy and RMSD trajectories. The present study revealed the molecular mechanism of PFAAs interfering with metabolic homeostasis through the PPARδ pathway, providing a theoretical basis for assessing its ecological and health risks. Full article

Copper and nickel ions play pivotal, albeit distinct, roles as essential trace elements in living systems, and primarily serve as co-factors for a range of enzymes. However, as with all trace metal ions, excessive concentrations can exert adverse toxicological properties. Interestingly, the incorporation of these in cell culture media can establish novel chemical interactions, with their speciation status markedly influencing characteristics, including cell maturation, and cellular uptake mechanisms. Thus, the primary objective of this study was to investigate and determine the speciation status (i.e., complexation) of nickel(II) and copper(II) ions by biomolecules present in RPMI 1640 mammalian cell culture medium using virtually non-invasive high-resolution proton NMR analysis, an investigation of much relevance to now routine studies of their toxicological actions towards cultured cells. Samples of the above aqueous culture medium were ¹H NMR-titrated with increasing added concentrations of 71–670 µmol/L Ni(II)(aq.), and 0.71–6.7, 7.1–67 and 71–670 µmol/L Cu(II)(aq.), in duplicate or triplicate. ¹H NMR spectra were acquired on a JEOL ECZ-600 spectrometer at 298 K. Results demonstrated that addition of increasing concentrations of Ni(II) and Cu(II) ions to the culture medium led to the selective broadening of a series of biomolecule resonances, results demonstrating their complexation by these agents. The most important complexants for Ni(II) were histidine > glutamine > acetate ≈ methionine ≈ lysine ≈ threonine ≈ branched-chain amino acids (BCAAs) > asparagine ≈ aspartate > tyrosine ≈ tryptophan, whereas for Cu(II) they were found to be histidine > glutamine > phenylalanine ≈ tyrosine ≈ nearly all remaining aliphatic metabolites (particularly the wealth of amino acids detectable) > 4-hydroxyphenylacetate (trace culture medium contaminant), in these orders. However, Cu(II) had the ability to influence the linewidths of these signals at much lower added levels (≤7 µmol/L) than that of Ni(II), the broadening effects of the latter occurring at concentrations which were approximately 10-fold greater. Virtually all of these added metal ion-induced resonance modifications were, as expected, reversible on addition of equivalent or excess levels of the chelator EDTA. From this study, changes in the co-ordination sphere of metal ions in physiological environments can give rise to marked modifications in their physicochemical properties (e.g., redox potentials, electronic charges, the potential catalytic generation of reactive oxygen species (ROS), and cell membrane passages). Moreover, given that the above metabolites may also function as potent hydroxyl radical (^●OH) scavengers, these findings suggest that generation of this aggressively reactive oxidant directly from Cu(II) and Ni(II) ions in physiologically-relevant complexes may be scavenged in a ‘site-dependent’ manner. This study is of further relevance to trace metal ion research in general since it enhances our understanding of the nature of their interactions with culture medium biomolecules, and therefore provides valuable information regarding their overall chemical and biological activities, and toxicities. Full article

Understanding how environmental factors modulate starch structure and functionality in sorghum is critical for optimizing its application in the food processing and fermentation industries. In this study, two sorghum cultivars with distinct starch types—Liaonian 3 (LN3, waxy) and Liaoza 82 (LZ82, non-waxy)—were cultivated across four major ecological regions in China to systematically investigate the combined effects of temperature and precipitation on grain composition, starch molecular structure, and processing properties. Comprehensive analyses, including scanning electron microscopy, molecular weight profiling, chain-length distribution, crystallinity, molecular order, and thermal/pasting behaviors, demonstrated that precipitation is the predominant environmental factor driving starch biosynthesis and structural assembly. High precipitation levels promoted amylopectin accumulation, shorter chain formation, increased branching degree, and higher crystallinity and molecular order, ultimately enhancing starch thermal stability and paste consistency. Genotypic differences further modulated starch structural patterns and environmental responsiveness, with LN3 consistently exhibiting higher amylopectin content, crystallinity, double-helix proportion, and gelatinization enthalpy compared to LZ82. Correlation analyses revealed genotype-dependent regulatory relationships linking environmental cues to starch structure and processing functionality. These findings provide a comprehensive framework elucidating the environmental regulation of starch structure–function relationships in sorghum, offering theoretical insights for climate-resilient breeding and functional starch development. Full article

Ischemia–reperfusion is a rapidly evolving cascade that involves a variety of metabolic shifts whose precise timing and sequential order are still poorly understood. Clarifying these dynamics is critical for understanding the core injury trajectory of stroke and for refining time-delimited therapeutic interventions. More broadly, continuous in situ monitoring of the middle-cerebral-artery occlusion process at the system level has not yet been achieved. Here, we report the first single-subject high-resolution spatiotemporal resolution metabolic maps of the ultra-early phase of ischemic stroke in a rodent model. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging mapped a metabolic abnormality area in the ischemic hemisphere that propagates from the striatum to the cortex. Microdialysis probes were then stereotaxically implanted within this metabolic abnormality area, capturing 10,429 metabolites that resolved into 16 temporally distinct trajectories aligned with probe insertion, ischemic injury, and reperfusion injury. Analysis of specific metabolic pathways mainly revealed that the delayed clearance of metabolic waste (urea and tryptamine) during early reperfusion, the transient attenuation of the citrate-to-oxaloacetate buffering gradient within the TCA cycle, and the accumulation of extracellular branched-chain amino acids all play crucial roles in shaping the injury trajectory. Simultaneously, the depletion of cellular repair mechanisms (pyrimidine synthesis) in the early phase of reperfusion also warrants our attention. These findings provide novel insights into the molecular basis and mechanisms of ischemia–reperfusion and offer a comprehensive resource for further investigation. Full article

4,6-Diamino-1,3,5-triazine (DT) derivatives typically exhibit excellent liquid crystal properties, attracting numerous researchers interested in enhancing their performance. In this paper, two DT molecules (DT−10 and DT−12) are employed to elucidate the effects of their backbone length and number of branches in the tail chains on self-assembled nanostructures using scanning tunneling microscopy (STM) at the 1-octanoic acid/highly ordered pyrolytic graphite interface, compared to our previous report (2TDT−n, n = 10,12,16,18). DT−10 features a short backbone and a trialkoxy chain tail, whereas DT−12 possesses a long backbone and bifurcated chain tails. STM results reveal that DT−10 assembles into a cross-shaped nanostructure with DT head groups arranged in a head-to-head configuration stabilized by a pair of N–H···N hydrogen bindings (HBs). In contrast, DT−12 assembles into a two-row linear pattern, where DT head groups exhibit a side-by-side arrangement mediated by a pair of N–H···N HBs. Comparison with our previous findings indicates that although variations in backbone length and tail chain branching can modulate the nanostructural features of DT derivatives, the chain length of DT molecules emerges as a pivotal factor governing their assembly architecture. Full article