Altitude drives the divergence of rumen fungal communities between cattle and yak in Yunnan plateau.

The milk fatty acid (FA) profile is influenced by complex interactions among animal species, physiology, feeding, and management, resulting in modification to the nutritional and functional properties of milk fat. This study aimed to identify latent biological and nutritional factors influencing milk FA composition in ruminants using multivariate factor analysis (MFA), applied across 4 species: dairy cows (Holstein-Friesian and Brown Swiss), sheep (Sarda and Massese), Mediterranean buffaloes, and goats (Saanen). A total of 1,960 mid-lactation animals (150 ± 16 DIM for cows; 90 ± 5 DIM for sheep; 162 ± 14 DIM for buffalo; 86 ± 3 DIM for goats), raised under commercial farm conditions and subjected to diverse feeding regimens, were included in the study. All milk samples were analyzed by the same laboratory using GC under consistent analytical conditions. Factor analysis was carried out on 49 individual FA. An ANOVA on the factor scores was performed to assess the effects of species and feeding strategies, specifically lipid supplementation in cow milk and n-3 supplementation in sheep milk. The MFA was able to extract 7 latent factors with specific biologic meaning: synthesis of odd- and branched-chain fatty acids from ruminal bacteria (factor 1: "OBCFA"), de novo FA synthesis via acetate in mammary gland (factor 2: "Mammary activity"), biohydrogenation of linoleic acid (factor 3: "BH_1"), milk fluidity regulation (factor 4: "Milk fluidity"), mitochondrial Beta-oxidation of FA (factor 5: "Beta-oxidation"), biohydrogenation via vaccenic acid (factor 6: "BH_2"), ruminal 16:1c7 elongation (factor 7: "16:1c7 elongation"), regulation of branched (factor 8: "BCFA") and odd (factor 9: "OCFA") chain FA, n-6 metabolism (factor 10: "n-6 FA"), and synthesis of short-chain FA (factor 11: "SCFA"). According to a previous study on MFA, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. Several factors reflected established metabolic processes, such as "OBCFA," "Mammary activity," and "BH_1." Others, such as "Beta-oxidation" and "16:1c7 elongation," captured novel pathways not previously described in single-species analyses. Importantly, this multispecies MFA approach revealed both conserved and species-specific metabolic signatures. For example, whereas core factors such as "SCFA" and "OCFA" appeared across all species and aligned with prior bovine-focused studies, certain factors (e.g., "n-6 FA" and "BCFA") showed species-dependent variation, likely reflecting differences in animal diet and ruminal microbial ecosystems. The extracted factor scores were useful to evaluate the effects of species (cow, goat, sheep, and buffalo) and different feeding regimens (applying the scores only to Holstein-Friesian cows for lipid supplementation and Sarda sheep for n-3 source supplementation). This approach allowed us to assess the influence of these dietary interventions on the latent factors affecting milk fatty acid composition. The resulting factors offer biologically meaningful, synthetic variables that can be used for future phenotypic, genetic, or nutritional modeling. Moreover, this approach enhances our understanding of mammary lipid metabolism across species and underscores the value of integrative multivariate methods in dairy science. These findings have implications for animal selection, feeding practices, and management strategies aimed at improving the nutritional quality of milk fat.

A unified threshold-constrained optimization framework for consistent and interpretable cross-machine condition monitoring

Spatial curvature is one of the fundamental cosmological parameters that is routinely constrained from observations. The forward modelling of observations, in particular of large-scale structure, often relies on large cosmological simulations. While the so-called separate universe approach allows one to account for the effect of curvature on the expansion rate in small sub-volumes, the non-Euclidean geometry is harder to accommodate. It becomes important when observables are computed over large distances, e.g. when photons travel to us from high redshift. Here we present a fully relativistic framework to run cosmological simulations for curved spatial geometry. The issue of consistent boundary conditions is solved by embedding a spherical cap of the curved spacetime into a hole within a flat exterior, where it can undergo free expansion. The geometric nature of gravity is made explicit in our framework, allowing for a consistent forward modelling of observables inside the curved patch. Our methodology would also work with any Newtonian code to a good approximation, requiring changes only to the initial conditions and post-processing.

Red deer milk is known for its high nutritional quality, containing elevated levels of protein, fat, and essential minerals compared with other ruminant milks. This study investigates the protein profile of red deer milk across various lactation stages, using advanced liquid chromatography-MS/MS techniques to enhance understanding of its nutritional composition. In this study, milk samples were collected from 120 lactating does at 8 distinct points during the lactation period, ensuring consistent dietary conditions. Through this comprehensive approach, a total of 73 proteins were identified, with 9 previously known in deer milk. Significant variations in protein concentrations were observed, highlighting 27 proteins with substantial changes throughout lactation. These proteins are crucial for supporting the physiological needs of the fawn. Key findings revealed the roles of specific proteins, such as osteopontin and lactotransferrin, in immune function, alongside transport proteins involved in nutrient delivery, reflecting the dynamic requirements during lactation. Bioinformatics analysis indicated significant quantitative changes in protein expression, with regression analysis confirming these findings. Gene Ontology analysis was conducted; however, limitations in genomic data for red deer necessitated reliance on related species for functional annotation. The results underscore the complex biochemical changes in deer milk, establishing a foundational understanding of its unique proteome. In conclusion, despite identifying fewer proteins than observed in studies of other ruminants, this research represents the most thorough analysis of proteins in red deer milk to date. It emphasizes the dynamic nature of milk composition throughout lactation and its implications for nutritional and functional attributes in cosmetic products and food, thereby contributing valuable insights into the dairy potential of red deer.

Nonlinear analysis of planar cracks in 2D piezoelectric semiconductors with energetically consistent crack-face boundary conditions

Honeycomb cooling pads are widely used in direct air-cooling systems due to their high wetted surface area and effective heat and mass transfer characteristics. However, the influence of honeycomb geometry on thermal performance has not been sufficiently quantified. In this study, a comparative thermo-structural finite element analysis of three honeycomb pad geometries (square, rectangular, and circular) is performed under identical steady-state operating conditions. Temperature distribution, thermal gradients, heat flux, and thermally induced stresses are evaluated using consistent material properties and boundary conditions. The results show that the rectangular honeycomb pad provides approximately 12–18% higher effective heat flux and more uniform temperature distribution compared to square and circular configurations. Structural stresses in all geometries remain within safe limits. The findings demonstrate that honeycomb geometry plays a critical role in cooling effectiveness and provide design guidance for selecting optimal pads in direct air-cooling systems.

This article examines refugee-related political violence (RRPV) in African host states between 2018 and May 2025. Drawing on an original dataset of 272 incidents across 39 countries and a refined six-fold typology, it documents substantial variation in the prevalence and forms of violence, with attacks involving transnational violent non-state actors (VNSAs) emerging as the most common pattern. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), the study identifies border porosity as the most consistent necessary condition across several RRPV types. For VNSA-related violence, two robust pathways arise: the joint presence of active armed groups and porous borders, and the combination of ethnically excluded refugee groups with restrictive rights regimes. Other forms of RRPV display fragmented, locally contingent causal patterns shaped by refugee population size, state fragility, camp isolation, and governance practices. The findings highlight the heterogeneous, multi-causal nature of RRPV and challenge security narratives that overstate refugees’ agency in producing violence. The article contributes new evidence on displacement-related insecurity and offers policy-relevant insights for mitigating violence in refugee-hosting areas.

Intramuscular fat (IMF) significantly influences meat quality, particularly flavor. The gastrointestinal microbiota can regulate lipid metabolism. The relationship between intramuscular fat metabolism, rumen microbiota, and beef quality remains unclear. This study enrolled 22 30-month-old Xinjiang Brown Beef cattle, which were randomly allocated to two groups: an intact bull group (n = 15) and a castrated bull group (n = 7). All experimental animals were housed and maintained under consistent feeding and management conditions throughout the entire experimental period. By combining in vivo ultrasonography, slaughter trials, rumen microbiome diversity analysis, and metabolomics techniques, and after adjusting for covariates including intramuscular fat (IMF) content, body weight, and backfat thickness, the present study demonstrated that castration regulates muscle lipid metabolism by reshaping the composition of the rumen microbial community, thereby exerting a cascading effect on key beef quality traits. (1) Production and meat quality: Live weight, carcass weight, eye muscle area, backfat thickness, and intramuscular fat (IMF) content were significantly higher in the YN group than in the GN group (p < 0.01). Conversely, dressing percentage, shear force value, and muscle protein content were significantly lower in the YN group than in the GN group (p < 0.01 or p < 0.05). (2) Rumen microbiota-metabolite correlation: Significant differences existed in microbial composition and community structure between groups (with significant differences in both α and β diversity). Core microbes regulated by castration exhibited distinct co-variation patterns with metabolites: genera such as Anaeroplasma showed significant positive correlations with hydroxy fatty acids, while Sharpea and others showed significant negative correlations with saturated fatty acids. (3) Microbial-metabolite axis and host phenotype correlation: Axes composed of Eubacterium uniforme and others showed significant positive correlations with IMF, while Docosapentaenoic acid (22n-3) exhibited significant negative correlations with IMF. Anaeroplasma and others showed significant positive correlations with oleic acid and others, as well as BFT, while saturated fatty acids showed significant negative correlations with BFT. (4) Covariate validation: After adjusting for covariates including body weight, backfat thickness, and IMF, castration was confirmed to significantly regulate the abundance/content of core genera such as Anaeroplasma, Eubacterium uniforme, as well as key metabolites such as hydroxy fatty acids and docosapentaenoic acid (22n-3) (p < 0.05 after adjustment), making it a core driver regulating rumen microbial composition and muscle lipid metabolism. After adjustment, the regulatory effects of IMF, body weight, and backfat thickness on the aforementioned microorganisms and metabolites were no longer significant (adjusted p > 0.05). Intramuscular fat (IMF), body weight, and backfat thickness are not independent drivers but rather indirect effects resulting from castration-induced physiological state remodeling. This study did not include feeding rate measurements, which represents a limitation. Future research should incorporate this data to further validate the conclusions. This study elucidates the interactive mechanisms between rumen microbiota and their metabolites, identifies the key pathways governing intramuscular fat (IMF) deposition, pinpoints potential regulatory targets for beef quality optimization, and clarifies the intermediate regulatory mechanisms underlying the modulation of meat quality traits by castration.

Abstract The viscoelastic coefficient of restitution (COR) is a functional of the entire constitutive law, including relaxation, retardation, memory kernels, impact velocity and its duration. This work predicts the viscoelastic COR by embedding hereditary material behavior into a Zener type wave model for sphere-plate impact. Impact generates both local deformation and stress waves, which attenuate rapidly in viscoelastic bodies due to intrinsic molecular dissipation. Existing contact models typically relate force to deformation and deformation rate through forms of stiffness and damping parameters, but they neglect true hereditary viscoelasticity. In contrast, hereditary behavior requires that stress depend on the full strain history, as described by Boltzmann's superposition principle and, for nonlinear intrinsics, the Volterra integral framework. Here, the Hertzian point contact force is reformulated to instill hereditary viscoelasticity into Zener's wave equation. A physically consistent separation condition is imposed to determine an effective coefficient of restitution, accounting for the residual deformation present at separation in viscoelastic impacts. The associated hysteretic energy loss is quantified, and a parametric study is conducted. Two solution strategies are developed: a direct numerical integration of the nonlinear ordinary integro-differential wave equation, and an internal variable evolution formulation that converts the problem into a system of ordinary differential equations for rapid time integration. Both approaches yield independently identical numerical results.

We study the algebraic structure of one-loop Bern-Carrasco-Johansson numerators in Yang-Mills and related theories. Starting from the propagator matrix that connects color-ordered integrands to numerators, we identify the consistency conditions that ensure the existence of Jacobi-satisfying numerator solutions and determine the unique construction. The relation between one-loop numerators and forward-limit tree numerators is clarified, together with the additional physical conditions required for a consistent double-copy interpretation. We propose a two-step expansion strategy for obtaining explicit one-loop numerators. The Yang-Mills integrand is first decomposed into scalar-loop Yang-Mills-scalar building blocks, which are then expanded into biadjoint scalar integrands. We derive explicit results for up to three external gluons, showing how the kinematic consistency conditions uniquely determine the coefficients in each case. Similar results for Einstein-Yang-Mills and gravity amplitudes are also presented.

ABSTRACT This study examines how social capital configurations, ecological rationality, and technology considerations shape the adoption of agricultural digitalization among 112 farmers in East and West Java, Indonesia. We use fuzzy-set Qualitative Comparative Analysis to identify five equifinal pathways to successful adoption. While technology enablement is present in all configurations, it remains insufficient on its own. It requires complementary social capital to translate potential into practice. Specifically, cognitive social capital, reflected in shared understanding, emerges as the most consistent core condition across pathways. Ecological rationality plays a secondary role, with adoption occurring primarily through social validation rather than through explicit environmental reasoning. The stability of configurations across specifications confirms genuine equifinality. These findings challenge technology-centered models. It demonstrates that effective agricultural digitalization depends on aligning initiatives with existing configurations of social capital. Our study offers practical guidance for designing context-sensitive digital agriculture strategies throughout the Global South.

We present an open, vendor-neutral BOLD SMS-EPI protocol tailored for multi-site fMRI studies, intended as a drop-in replacement for conventional vendor-specific acquisition and reconstruction pipelines. Built on Pulseq—an emerging standard for cross-platform MRI pulse sequence development—our protocol ensures identical SMS-EPI pulse sequences and image reconstruction across scanner vendors. This provides, for the first time, known and consistent experimental conditions across sites and scanner software versions. We begin by reviewing the current capabilities of the Pulseq framework, including vendor support and safety considerations. We then detail our SMS-EPI implementation and demonstrate its performance using resting-state fMRI pilot data from healthy volunteers, showing reduced site variance compared to corresponding vendor protocols on Siemens and GE scanners. To support adoption, we provide practical resources to help researchers integrate Pulseq fMRI into their studies, including example text for grant proposals and IRB submissions. These resources are freely available at https://github.com/HarmonizedMRI/Functional (https://github.com/HarmonizedMRI/Functional). Our vision is for Pulseq fMRI to become the standard for multi-site research, enabling more reproducible science and serving as a reference for the development of novel acquisition and reconstruction methods.

Abstract High-performance liquid chromatography (HPLC) is a critical analytical technique in the pharmaceutical sector, valued for its accuracy, speed and efficiency in drug quantification. This study aimed to develop and validate a novel reversed-phase HPLC (RP-HPLC) method for quantifying triamcinolone base (TRb) in solid pharmaceutical forms, using consistent chromatographic conditions for both dosage determination and dissolution studies. The method was validated in accordance with regulatory guidelines and demonstrated excellent precision, accuracy, and robustness. The mobile phase consisted of methanol and water (50:50), with a flow rate of 1.5 mL min −1 , detection at 254 nm and a column temperature of 30 °C. Key performance parameters included selectivity, linearity ( R = 0.9998 across 2–12 μg mL −1 ), precision (RSD &lt; 2%), accuracy (98–102% recovery in the presence of two placebo matrices), and robustness (seven variables evaluated without significant impact). The retention time was 4.61 min. The method proved effective for both dosage quantification and formulation dissolution studies. Applying the same methodology across various stages of pharmaceutical development enhances standardization, traceability, and data reliability. As such, this RP-HPLC method is highly recommended for quality control laboratories seeking practical, sustainable, and scientifically robust analytical solutions.

Reliable hydrologic modeling in arid, topographically complex watersheds depends on accurate land-use/land-cover (LULC) representation. This study evaluates how different LULC categorization methods affect simulated runoff for the Wadi Hatta watershed (UAE) using a GIS-driven machine learning framework that combines high-resolution remote sensing with hydrologic modeling. LULC maps were generated in Google Earth Engine using Random Forest (RF) and Support Vector Machine (SVM) classifiers applied to Sentinel-2 (10 m) and Landsat 8/9 (30 m) imageries and compared with the 10 m ESRI predefined LULC dataset. The resulting LULC classifications were converted to SCS Curve Numbers and used in HEC-HMS hydrologic modeling to simulate runoff under a 50-year design storm, under consistent meteorological and physical conditions. Results show that Sentinel-2 + SVM achieved the highest classification accuracy (overall accuracy up to 0.86) and produced the earliest and highest simulated peak discharge (11.4 m3/s), reflecting improved detection of impervious surfaces. In contrast, the Landsat-9 + RF scenario yielded the lowest peak (7.5 m3/s), consistent with a higher proportion of pervious land covers. LULC change analysis between 2017 and 2024 showed increases in forest cover (1.0–3.3%) and built-up areas (6.0–7.9%) driven by afforestation and urban expansion. These results demonstrate that LULC input resolution and classifier selection significantly influence hydrologic model sensitivity and runoff estimates, underscoring the need for carefully selected, high-resolution LULC products in flood risk assessment and water resource planning in data-scarce arid environments.

This study uses electrochemical impedance spectroscopy (EIS) to investigate coupled effects of mechanical deformation depth and size on impedance responses of large-format prismatic lithium-ion batteries (LIBs). Stepwise out-of-plane deformations were applied using hemispherical impactors of two different diameters (30 mm and 180 mm), representing localized and global mechanical loading while maintaining consistent contact conditions. Cells were deformed to 25%, 50%, 75%, and 95% of the internal short-circuit deformation depth, with EIS measurements conducted at each level. Relative changes of measured impedance parameters and fitted equivalent circuit model (ECM) parameters were analyzed. Results show that localized deformation decreases charge transfer resistance ΔR1 up to 8.0% and total impedance ΔZ up to 1.6%, indicating enhanced charge mobility due to internal structural damage. In contrast, global compression increases ohmic resistance ΔR0 up to 2.1% and ΔZ up to 2.0%, likely due to reduced separator porosity. Phase angle ΔPhase showed opposite trends under localized and global loading, reflecting different capacitive responses. These results reveal that deformation depth and size significantly influence EIS measurements, with non-linear interactions and transition points indicative of irreversible damage. These results support the use of EIS as a non-destructive diagnostic tool for identifying mechanical damage in LIBs.

A bstract Recent studies by Copetti, Córdova and Komatsu have revealed that when non-invertible symmetries are spontaneously broken, the conventional crossing relation of the S-matrix is modified by the effects of the corresponding topological quantum field theory (TQFT). In this paper, we extend these considerations to (1 + 1)-dimensional quantum field theories (QFTs) with boundaries. In the presence of a boundary, one can define not only the bulk S-matrix but also the boundary S-matrix, which is subject to a consistency condition known as the boundary crossing relation. We show that when the boundary is weakly-symmetric under the non-invertible symmetry, the conventional boundary crossing relation also receives a modification due to the TQFT effects. As a concrete example of the boundary scattering, we analyze kink scattering in the gapped theory obtained from the Φ (1,3) -deformation of a minimal model. We explicitly construct the boundary S-matrix that satisfies the Ward-Takahashi identities associated with non-invertible symmetries.

Microgreens are nutrient-dense functional foods whose yield and phytochemical composition can be regulated through light management in controlled-environment agriculture. This study evaluated species-specific responses to light intensity by analysing growth, nutrient uptake, and phytochemical accumulation in carrot, basil, arugula, and radish microgreens grown under LED lighting at four photosynthetic photon flux densities (PPFD: 67, 100, 140, and 174 μmol·m−2·s−1). Drainage pH and electrical conductivity remained stable across treatments, indicating consistent fertigation conditions. Increasing light intensity enhanced water, nitrate, and potassium uptake and promoted biomass accumulation in all species, although responses varied in magnitude. Phytochemical profiles were strongly modulated by irradiance. Intermediate PPFD levels (100–140 μmol·m−2·s−1) generally maximised carotenoid, sterol, and squalene accumulation, whereas lower irradiance (67 μmol·m−2·s−1) increased vitamin C and tocopherol contents, indicating activation of antioxidant defence mechanisms. Principal component analysis showed that species identity was the primary driver of phytochemical variability, with light intensity acting as a secondary modulator. Carrot and basil responded most strongly to intermediate irradiance, while arugula and radish exhibited greater vitamin C accumulation under lower light. These results support the use of species-specific light strategies to optimise microgreen yield and nutritional quality.

Malaria remains a major public health problem in Indonesia, particularly in eastern regions such as East Nusa Tenggara. Gaura Village in West Lamboya District has the highest malaria incidence in West Sumba Regency. Insecticide-treated nets (ITNs) are a key prevention strategy, but their effectiveness depends on consistent use, net condition, and adequate household coverage. Objective to assess the relationship between ITN usage and malaria occurrence among residents of Gaura Village. Methods: This cross-sectional study included 252 participants. Data on malaria history, ITN use frequency, net condition, duration of use, washing frequency, and household coverage were collected through questionnaires and home observations. Statistical analyses included the Chi-square test and logistic regression. Results: Consistent ITN use was significantly associated with lower malaria incidence (p &lt; 0.05). Net condition, bedroom coverage, and household member coverage also showed significant relationships with malaria occurrence. Multivariate analysis indicated that ITN usage remained the most influential variable. ITN usage is significantly associated with malaria incidence in Gaura Village. Ensuring consistent use, maintaining good net condition, and improving household coverage may strengthen malaria prevention efforts.

Detecting spatial patterns is fundamental to scientific discovery, yet current methods lack statistical consensus and face computational barriers when applied to large-scale spatial omics datasets. We unify major approaches through a single quadratic form and derive general consistency conditions. We reveal that several widely used methods, including Moran's I, are inconsistent, and propose scalable corrections. The resulting test enables robust pattern detection across millions of spatial locations and single-cell lineage-tracing datasets.