Single Sample Research Articles

Beam-Space Post-Doppler Reduced-Dimension STAP Based on Sparse Bayesian Learning

The space–time adaptive processing (STAP) technique can effectively suppress the ground clutter faced by the airborne radar during its downward-looking operation and thus can significantly improve the detection performance of moving targets. However, the optimal STAP requires a large number of independent identically distributed (i.i.d) samples to accurately estimate the clutter plus noise covariance matrix (CNCM), which limits its application in practice. In this paper, we fully consider the heterogeneity of clutter in real-world environments and propose a sparse Bayesian learning-based reduced-dimension STAP method that achieves suboptimal clutter suppression performance using only a single sample. First, the sparse Bayesian learning (SBL) algorithm is used to estimate the CNCM using a single training sample. Second, a novel angular Doppler channel selection algorithm is proposed with the criterion of maximizing the output signal-to-clutter-noise ratio (SCNR). Finally, the reduced-dimension STAP filter is constructed using the selected channels. Simulation results show that the proposed algorithm can achieve suboptimal clutter suppression performance in extremely heterogeneous clutter environments where only one training sample can be used.

Incomplete Cross-Modal Retrieval with Deep Correlation Transfer

Most cross-modal retrieval methods assume the multi-modal training data is complete and has a one-to-one correspondence. However, in the real world, multi-modal data generally suffers from missing modality information due to the uncertainty of data collection and storage processes, which limits the practical application of existing cross-modal retrieval methods. Although some solutions have been proposed to generate the missing modality data using a single pseudo sample, this may lead to incomplete semantic restoration and sub-optimal retrieval results due to the limited semantic information it provides. To address this challenge, this article proposes an Incomplete Cross-Modal Retrieval with Deep Correlation Transfer (ICMR-DCT) method that can robustly model incomplete multi-modal data and dynamically capture the adjacency semantic correlation for cross-modal retrieval. Specifically, we construct intra-modal graph attention-based auto-encoder to learn modality-invariant representations by performing semantic reconstruction through intra-modality adjacency correlation mining. Then, we design dual cross-modal alignment constraints to project multi-modal representations into a common semantic space, thus bridging the heterogeneous modality gap and enhancing the discriminability of the common representation. We further introduce semantic preservation to enhance adjacency semantic information and achieve cross-modal semantic correlation. Moreover, we propose a nearest-neighbor weighting integration strategy with cross-modal correlation transfer to generate the missing modality data according to inter-modality mapping relations and adjacency correlations between each sample and its neighbors, which improves the robustness of our method against incomplete multi-modal training data. Extensive experiments on three widely tested benchmark datasets demonstrate the superior performance of our method in cross-modal retrieval tasks under both complete and incomplete retrieval scenarios. Our used datasets and source codes are available at https://github.com/shidan0122/DCT.git .

Tissue-adjusted pathway analysis of cancer (TPAC): A novel approach for quantifying tumor-specific gene set dysregulation relative to normal tissue.

We describe a novel single sample gene set testing method for cancer transcriptomics data named tissue-adjusted pathway analysis of cancer (TPAC). The TPAC method leverages information about the normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies gene set dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data for 21 solid human cancers from The Cancer Genome Atlas (TCGA) and associated normal tissue expression data from the Human Protein Atlas (HPA), TPAC gene set scores are more strongly associated with patient prognosis than the scores generated by existing single sample gene set testing methods.

High activity pozzolan obtained from selection of excavation soils in a Construction and Demolition Waste landfill

Excavations soils from construction sites, when included as Construction and Demolition Waste (CDW) can double waste amount and represent up to 80 % of waste composition. Limited recycling strategies are available for the material. In this work, soils with higher kaolinite contents were selected by X-ray diffraction (XRD) to produce high activity pozzolan. Twenty soil samples were collected in an inert CDW landfill, and seven samples (one-third of the total) containing higher kaolinite content were composed as a single sample for thermal and mechanical activation as pozzolan. At the temperature of 600 °C, low crystallinity kaolinite was transformed into amorphous material (37 % g/g) achieving the highest pozzolanic activity [consumption of 519 mg Ca(OH)2/g of the sample]. The replacement of Portland cement by calcined soil (6, 10 and 18 %) had no significant rheological impact on the water to solid ratio and optimal dispersant content and affected slightly the heat and setting time of the pastes; therefore, workable, and technically applicable. The Portland cement replacement by calcined soil, despite a fixed water to solid ratio of 0.3 led to an increase in the water to cement ratios and in the porosities of the pastes. Due to the pozzolanic reaction, 6 and 10%-replacement of Portland cement by calcined soil did not impair the tensile strength of the pastes when compared to that of Portland cement paste. A 42-MPa 28-day age blended Portland with calcined soil might be feasible to produce regarding Brazilian cement industry standard.

Personalized differential expression analysis in triple-negative breast cancer.

Identification of individual-level differentially expressed genes (DEGs) is a pre-step for the analysis of disease-specific biological mechanisms and precision medicine. Previous algorithms cannot balance accuracy and sufficient statistical power. Herein, RankCompV2, designed for identifying population-level DEGs based on relative expression orderings, was adjusted to identify individual-level DEGs. Furthermore, an optimized version of individual-level RankCompV2, named as RankCompV2.1, was designed based on the assumption that the rank positions of genes and relative rank differences of gene pairs would influence the identification of individual-level DEGs. In comparison to other individualized analysis algorithms, RankCompV2.1 performed better on statistical power, computational efficiency, and acquired coequal accuracy in both simulation and real paired cancer-normal data from ten cancer types. Besides, single sample GSEA and Gene Set Variation Analysis analysis showed that pathways enriched with up-regulated and down-regulated genes presented higher and lower enrichment scores, respectively. Furthermore, we identified 16 genes that were universally deregulated in 966 triple-negative breast cancer (TNBC) samples and interacted with Food and Drug Administration (FDA)-approved drugs or antineoplastic agents, indicating notable therapeutic targets for TNBC. In addition, we also identified genes with highly variable deregulation status and used these genes to cluster TNBC samples into three subgroups with different prognoses. The subgroup with the poorest outcome was characterized by down-regulated immune-regulated pathways, signal transduction pathways, and apoptosis-related pathways. Protein-protein interaction network analysis revealed that OAS family genes may be promising drug targets to activate tumor immunity in this subgroup. In conclusion, RankCompV2.1 is capable of identifying individual-level DEGs with high accuracy and statistical power, analyzing mechanisms of carcinogenesis and exploring therapeutic strategy.

Platform-independent estimation of human physiological time from single blood samples.

Abundant epidemiological evidence links circadian rhythms to human health, from heart disease to neurodegeneration. Accurate determination of an individual's circadian phase is critical for precision diagnostics and personalized timing of therapeutic interventions. To date, however, we still lack an assay for physiological time that is accurate, minimally burdensome to the patient, and readily generalizable to new data. Here, we present TimeMachine, an algorithm to predict the human circadian phase using gene expression in peripheral blood mononuclear cells from a single blood draw. Once trained on data from a single study, we validated the trained predictor against four independent datasets with distinct experimental protocols and assay platforms, demonstrating that it can be applied generalizably. Importantly, TimeMachine predicted circadian time with a median absolute error ranging from 1.65 to 2.7 h, regardless of systematic differences in experimental protocol and assay platform, without renormalizing the data or retraining the predictor. This feature enables it to be flexibly applied to both new samples and existing data without limitations on the transcriptomic profiling technology (microarray, RNAseq). We benchmark TimeMachine against competing approaches and identify the algorithmic features that contribute to its performance.

Controlling Factors of Groundwater Salinization and Pollution in the Oasis Zone of the Cherchen River Basin of Xinjiang

Groundwater is a vital resource for local human life and production in the oasis zone of the Cherchen River Basin of Xinjiang. Understanding the controlling factors of groundwater salinization and pollution is of great significance for the sustainable utilization of groundwater resources and protection of the ecological environment in desert oasis areas. In light of this, a total of 36 single structure unconfined groundwater samples and 54 multi-layered structure unconfined and confined groundwater samples were collected from the oasis zone of the Cherchen River Basin and evaluated for the distribution characteristics and pollution status of major ions. Hydrogeochemical methods (e.g., Piper diagram, multivariate statistics, Gibbs model, and relationships among ions) were used to determine the main controlling factors of groundwater salinization and pollution. Differences in hydrogeochemical zonation were found from the single structure unconfined aquifers in sloping plains of piedmont areas to the multi-layered structure unconfined and confined aquifers in alluvial-proluvial plain areas, and Cl-Na (87.8%) was the main hydrochemical type in the groundwater of the study area. The quality of single structure unconfined groundwater was starkly better than that of the multi-layered unconfined and confined groundwater, which was mainly caused by Na+ (mean value of 9 969 mg·L-1), Cl- (13 687 mg·L-1), and SO42- (5 840 mg·L-1). Moreover, the natural hydrogeochemical process was the main reason for the deterioration of groundwater quality. The hydrochemistry was mainly controlled by the water-rock interaction and evaporation processes. The mineral dissolution of silicates and evaporites was an important source of chemical ions in the groundwater. Furthermore, the chemical weathering of evaporites combined with the processes of evaporation and cation exchange had a significant influence on the salinization of multi-layered unconfined and confined groundwater in alluvial-proluvial plain areas. In addition, synthetic fertilizers were the main pollution sources of NO3- in groundwater in the intensive agricultural zones.

Construction of a 12-gene prognostic model for colorectal cancer based on heat shock protein-related genes

Some heat shock proteins (HSPs) have been shown to influence tumor prognosis, but their prognostic significance in colorectal cancer (CRC) remains unclear. This study explored the prognostic significance of HSP-related genes in CRC. Transcriptional data and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) database, and a literature search was conducted to identify HSP-related genes. Using Least Absolute Selection and Shrinkage Operator (LASSO) regression and univariate/multivariate Cox regression analyses, 12 HSP-related genes demonstrating significant associations with CRC survival were successfully identified and employed to formulate a predictive risk score model. The efficacy and precision of this model were validated utilizing TCGA and Gene Expression Omnibus (GEO) datasets, demonstrating its reliability in CRC prognosis prediction. gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed significant disparities between high- and low-risk groups in chromatin remodeling biological functions and neutrophil extracellular trap formation pathways. Single sample gene set enrichment analysis (ssGSEA) further revealed differences in immune cell types and immune functional status between the two risk groups. Differential analysis showed higher expression of immune checkpoints within the low-risk group, while the high-risk group exhibited notably higher Tumor Immune Dysfunction and Exclusion (TIDE) scores. Additionally, we predicted the sensitivity of different prognosis risk patients to various drugs, providing potential drug choices for tailored treatment. Combined, our study successfully crafted a novel CRC prognostic model that can effectively predict patient survival, immune landscape, and treatment response, providing important support and guidance for CRC patient prognosis.

Controllable strain-driven topological phase transition and dominant surface-state transport in HfTe5

The fine-tuning of topologically protected states in quantum materials holds great promise for novel electronic devices. However, there are limited methods that allow for the controlled and efficient modulation of the crystal lattice while simultaneously monitoring the changes in the electronic structure within a single sample. Here, we apply significant and controllable strain to high-quality HfTe5 samples and perform electrical transport measurements to reveal the topological phase transition from a weak topological insulator phase to a strong topological insulator phase. After applying high strain to HfTe5 and converting it into a strong topological insulator, we found that the resistivity of the sample increased by 190,500% and that the electronic transport was dominated by the topological surface states at cryogenic temperatures. Our results demonstrate the suitability of HfTe5 as a material for engineering topological properties, with the potential to generalize this approach to study topological phase transitions in van der Waals materials and heterostructures.

Multiplexed miRNA and Protein Analysis Using Digital Quantitative PCR in Microwell Arrays.

Proteins and microRNAs (miRNAs) act in tandem within biological pathways to regulate cellular functions, and their misregulation has been correlated to numerous diseases. Because of their interconnectedness, both miRNAs and proteins must be evaluated together to obtain accurate insights into the molecular pathways of pathogenesis. However, few analytical techniques can measure both classes of biomolecules in parallel from a single biological sample. Here, microfluidic digital quantitative PCR (dqPCR) was developed to simultaneously quantify miRNA and protein targets in a multiplexed assay using a single detection chemistry. This streamlined analysis was achieved by integrating base-stacking PCR and immuno-PCR in a microfluidic array platform. Analyses of let-7a (miRNA) and IL-6 (protein) were first optimized separately to identify thermocycling and capture conditions amenable to both biomolecules. Singleplex dqPCR studies exhibited the expected digital signals and quantification cycles for both analytes over a range of concentrations. Multiplexed analyses were then conducted to quantify both let-7a and IL-6 with high sensitivity (LODs ∼ 3 fM) over a broad dynamic range (5-5000 fM) using only standard PCR reagents. This multiplexed dqPCR was then translated to the analysis of HEK293 cell lysate, where endogenous let-7a and IL-6 were measured simultaneously without sample purification or pretreatment. Collectively, these studies demonstrate that the integration of BS-PCR and immuno-PCR achieves a sensitive and streamlined approach for multiplexed analyses of miRNAs and proteins, which will enable researchers to gain better insights into disease pathogenesis in future applications.

Bridgman-Grown (Cd,Mn)Te and (Cd,Mn)(Te,Se): A Comparison of Suitability for X and Gamma Detectors.

This study explores the suitability of (Cd,Mn)Te and (Cd,Mn)(Te,Se) as room-temperature X-ray and gamma-ray detector materials, grown using the Bridgman method. The investigation compares their crystal structure, mechanical and optical properties, and radiation detection capabilities. Both crystals can yield large-area single crystal samples measuring approximately 30 × 30 mm2. In low-temperature photoluminescence analysis, both materials showed defect states, and annealing in cadmium vapors effectively eliminated donor-acceptor pair luminescence in (Cd,Mn)Te but not in (Cd,Mn)(Te,Se). Moreover, harder (Cd,Mn)(Te,Se) exhibited a higher etch pit density compared to softer (Cd,Mn)Te. X-ray diffraction examination revealed uniform lattice constant distribution in both compounds, with variations at a part per million level. (Cd,Mn)Te crystals demonstrated excellent single crystal properties with narrower omega scan widths, while (Cd,Mn)(Te,Se) exhibited a high contribution of block-like structures with significantly larger misorientation angles. Spectroscopic evaluations revealed better performance of a pixelated (Cd,Mn)Te detector, in comparison to (Cd,Mn)(Te,Se), achieving a mean full width at half maximum of 14% for the 122 keV gamma peak of Co-57. The reduced performance of the (Cd,Mn)(Te,Se) detector may be attributed to deep trap-related luminescence or block-like structures with larger misorientation angles. In conclusion, Bridgman-grown (Cd,Mn)Te emerges as a more promising material for X-ray and gamma-ray detectors when compared to (Cd,Mn)(Te,Se).

Mechanical and electromagnetic wave dissipation features of bilayer absorber filled with hierarchical porous CoNi magnetic alloy and BiVO4/VOOH nanocomposite

Designing absorbers with efficient critical parameters is required to address the problems caused by electromagnetic pollution. In this context, this study focuses on the chemical synthesis of hierarchical mesoporous microspheres CoNi magnetic alloy particles, and BiVO4/VOOH nanocomposite as a source of dielectric dissipation for constructing bilayer absorbers that are optimized in their absorption properties using MATLAB simulation. Single layer and constructed bilayer absorber sample's mechanical and X band microwave absorption performance were investigated, compared, and optimized. It is found that the prepared bilayer absorber sample's mechanical characteristics are comparable to those of the two bulk single-layer samples of CN and BVH, indicating that the interface in the double-layer sample not only has little to no effect on the majority of BVH or CN samples but also enhances the dissipation feature. Bilayer absorber sample with reasonable design and layer thickness optimization outperform single layer samples in terms of absorption efficiency, with the ideal sample having a minimum reflection loss (RLmini) of −37.5 dB and an effective absorption bandwidth (EAB) of 3.6 GHz with only a total thickness of 1.6 mm. The exceptional microwave absorption capabilities of the bilayer absorber sample are the consequence of the beneficial impacts of interfacial polarization between layers.

Degradation and dislocation evolution of the nickel-based single crystal superalloy DD6 under the coupling high-speed rotating and high temperature environments

To model the centrifugal loads and complex geometries experienced by turbine blades during service, the nickel-based single crystal superalloy DD6 samples with a groove structure are designed and tested under the coupling conditions of high-speed rotating of 20,000 r/min and high temperature of 980 ℃. Scanning electron microscopy and transmission electron microscopy are used to analyze the microstructural evolution of γ-γ' phases and dislocation morphologies of 400 h and 1000 h samples. The results indicate that microstructural degradation of the γ-γ' phase attributes to the larger centrifugal tensile stress S11 in the applied physical stress compositions until deformation occurs. Our observations suggest that a/2 < 101 > -type dislocations initiate plastic deformation by slipping within the γ phase. However, their movement is constrained at the interface between the γ and γ' phases, resulting in their tendency to aggregate at this boundary. After the formation of stable interfacial dislocation networks, these dislocations then react to generate either a< 010 > -type dislocations or a/2 < 112 > -type dislocations, which cut into the γ' phase. However, under high stress conditions, the a/2 < 101 > -type dislocations are primarily cut directly in the form of dislocation pairs.

Geometry optimization of microwavable food to improve heating uniformity

Food geometry affects microwave heating, posing a challenge for uniform heating. In this study, numerical geometry optimization models of 3-D microwave heating were developed using the coefficient of variation of the absorbed power as the optimization objective to obtain the best geometry. These models were verified by comparing the surface temperature distribution and point temperatures from the experiments and simulations. The optimized geometry exhibited better heating uniformity than the non-optimized geometry. After geometry optimization, the static heating uniformity of a single sample and multiple sample combinations was improved by up to 109.93% and 53.95%, respectively. Similar geometry features were obtained after geometry optimization of potato, beef, and tilapia samples at defined positions. In addition, rotational heating enhanced temperature uniformity for each sample during simultaneous heating. This study provides a flexible and effective method for designing microwaveable food and container geometries.

Multi-tier dynamic sampling weak RF signal estimation theory

This paper presents a theoretical analysis in discrete time for a multi-tier weak radiofrequency (RF) signal estimation process with N simultaneous signals. Discrete time dynamic sampling is introduced and is shown to provide the capability to extract signal parameter values with increased accuracy compared with accuracy of estimates obtained in prior work. This paper advances phase measurement approaches by proposing discrete time dynamic sampling which our paper shows offers the desirable capability for more accurate weak signal parameter estimates. For N=2 simultaneous signals with a strong signal at 850 MHz and a weak signal at 855 MHz, the results show that dynamically sampling the instantaneous frequency at 24 times the Nyquist rate provides weak signal frequency estimates that are within 1.7 times 10^{-5} of the actual weak signal frequency and weak signal amplitude estimates that are within 428 PPM of the actual weak signal amplitude. Results are also presented for situations with N=2 simultaneous 5G signals. In one case, the strong signal is 3950 MHz, and the weak signal is 3955 MHz; in the other case the strong case is 5950 MHz, and the weak signal is 5955 MHz. The results for these cases show that estimates obtained with dynamic sampling are more accurate than estimates provided using a single sample rate of 65 MSPS. This work has promising applications for weak signal parameters estimation using instantaneous frequency measurements.

The Effect of Mn Doping and Ti3+ Defects at TiO2 Surfaces in NO and SO2 Gas Capture Investigated Using Near-Ambient Pressure X-ray Photoelectron Spectroscopy

The removal of air pollutants is an important research topic in order to improve the environment. In addition, many common pollutants can affect human health to varying degrees. In this work, we investigate NO and SO2 conversion by reaction with a commonly used metal oxide catalyst, TiO2. Rutile TiO2(110) single crystals and industrial powder samples used in sunscreen are studied using near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) as a main tool. This allows in situ monitoring of the gas conversion process. We find Ti3+ defects (oxygen vacancies) or Mn oxides/cations (MnO) at the TiO2 surfaces can improve the conversion of NO and SO2 to surface-bound species. MnO and Ti3+ defects at the surface of rutile TiO2(110) exhibit a synergistic effect on the conversion of NO and SO2 that is significantly improved by nearly an order of magnitude. The by-products are mainly in the form of NO3−, SO32−, and SO42−. We find the main oxidation products formed on the single crystals are subtly different from those on the industrial powder samples. For TiO2 nanopowders (undoped and Mndoped), the presence of Mn also shows improvement in toxic gas adsorption capacity. Overall, it is believed that the outcome obtained from NAP-XPS in this research provides useful insights for the future use of TiO2 in pollutant gas capture.

A simple, effective and inexpensive method to isolate the nucleic acid (DNA/RNA) from a single tick for molecular detection of various pathogens

Objectives: Ticks are vectors of a number of pathogens, which cause diseases with fatal consequences, therefore it is essential to detect such pathogens from single tick. Molecular methods like polymerase chain reaction (PCR) are offering such possibilities. At present, cumbersome methods involving liquid nitrogen, cutting ticks with scalpels as well as pooled ticks are being used worldwide. Our goal is to develop a reliable and fast method to obtain nucleic acid (DNA/RNA) from the single tick shipped at room temperature to detect various pathogens. Methods: We developed a mechanical crushing method with mini column nucleic acid isolation from a single tick shipped at room temperature with postal or currier service in a letter. PCR detection was done for Borrelia burgdorferi and tick-borne encephalitis virus as examples. Results: This method was used successfully for the isolation of nucleic acid from single tick and later used for PCR detection of B. burgdorferi and tick-borne encephalitis virus on 17 single tick samples as examples, but for last 18 years, this method was used on more than 250 ticks from Germany. Spectrometric values indicate the presence of sufficient yield of DNA and RNA (up to 900 µg/mL per tick) during the isolation. Conclusions: This may be the first report about a number of one single tick cases, which were sent at room temperature in letters with postal services for isolation of the nucleic acid with mini column kit and used later on for PCR detection of various pathogens. This inexpensive and simple method may be used in any laboratory worldwide for monitoring the presence of tick-borne pathogens.

Are peppery notes the main negative driver of liking for young French consumers in a Duras red wine made from a cool and wet season?

It has been shown that rotundone, the only identified aroma compound imparting peppery notes in red wine, was neutrally or positively perceived by consumers, except for young non-anosmic respondents who disliked it. This work aimed to explore the main negative driver of liking for this target of consumers in a peppery Duras red wine from a cool and wet season and for which other penalties might apply. A convenience panel of one-hundred and thirty-four young French consumers from Ecole d’Ingénieurs de Purpan in Toulouse (18–24 years) was recruited for the study. Panellists were asked to rate their overall liking on a 9-point hedonic scale of such wine and their perception of seven sensory attributes on a 5-point just-about-right (JAR) scale, with 3 corresponding to the central just-about-right word anchor. Results from penalty analysis demonstrated that a lack of fruity notes followed by an excessive sourness and an excessive intensity of peppery notes were the main penalising sensory characteristics. The findings, that are still preliminary and would deserve to be confirmed using a panel composed of young consumers with other social and cultural background, highlight that the intensity of peppery notes was not the main negative driver of young consumers’ liking of Duras wine produced during a vintage year with unfavourable cool and rainy climate conditions. However, the results of this study encourage Duras producers targeting such consumers to propose a wine exhibiting a good balance between fruity and peppery notes and a moderate acidity level that could be achieved during such season through deacidification. This research is a good illustration of the fact that the penalty analysis method can be implemented on a single wine sample.

Epidemiological investigation of insulin dysregulation in Shetland and Welsh ponies in Australia.

Insulin dysregulation (ID) is central to equine metabolic syndrome. There are limited epidemiological studies investigating dynamic testing of ID in ponies. To evaluate prevalence and risk factors for ID through dynamic testing of hyperinsulinaemia (DHI) and insulin resistance (IR). Cross-sectional. Sex, age, breed, height, cresty neck score (CNS), body condition score (BCS), laminitis, HMGA2:c.83G>A genotype and pituitary pars intermedia dysfunction (PPID) status were documented. Dynamic hyperinsulinaemia was diagnosed with an oral sugar test (OST) and IR with an insulin tolerance test (ITT). Owners completed surveys reporting activity, laminitis history and perception of body condition using a (1-9) visual analogue scale (VASo). Ordinal scores were converted to binary outcomes for CNS (≤2/5 or ≥3/5), BCS and VASo (≤6/9 or ≥7/9). Variables associated with insulin concentrations, glucose reduction after the ITT and laminitis were evaluated with mixed effects regression models accounting for random effects of farms. Among 167 ponies tested, median (range) age was 9 (4-21) years and BCS was 6 (4-8). Prevalence (95% confidence interval [CI]) of ID was 61 (53-68)%. Factors associated with insulin concentrations (estimate [95% CI]; μIU/mL) 60 min post-OST were: age (1.07 [1.02-1.11]), CNS (≥3/5, 1.52 [1.04-2.23]) and VASo (≥7/9, 1.75 [1.09-2.79]); and 90 min post-OST were: age (1.08 [1.03-1.12]), CNS (≥3/5, 1.80 [1.22-2.64]), VASo (≥7/9, 2.49 [1.52-4.08]) and sex (male, 0.64 [0.45-0.91]). Factors associated with glucose reduction after the ITT (estimate [95% CI]; %) were: age (-1.34 [-2.01 to -0.67]), sex (female, -6.21 [-11.68 to -0.74]) and VASo (≥7/9, -1.74 [-18.89 to -4.78]). Factors associated with laminitis (odds ratio [95% CI]) were DHI (4.60 [1.68-12.58]), IR (3.66 [1.26-10.61]) and PPID (11.75 [1.54-89.40]). Single time-point sampling, laminitis definition and diet analysis. Ageing, being female and owner-perceived obesity were associated with ID.

Mechanical behaviors and failure characteristics of coal-rock combination under quasi-static and dynamic disturbance loading: a case based on a new equipment

The dynamic disasters of deep mining coal and rock mass are frequent and easy to be instable. Aiming at the deformation of coal-rock roadway under the coupled static and dynamic load, a new equipment which can simulate the actual situation dynamic environment is used to carry out the coupled static-dynamic loading test of coal-rock combination. The failure law and mechanical behavior of combination are studied. Test results show that weak structure significantly affects mechanical response of coal-rock combination. The coal part with lower strength firstly reaches the crack initiation stress. The strength of the combination is dominated by the coal part. The post-peak stage of the stress–strain curve under the coupled static and dynamic load presents a stepped reduction, which shows yield process. The dynamic load level has a significant effect on the mechanical behaviors of the combination. The elastic modulus decreases under dynamic loading. The peak stress of the combination is positively correlated with the dynamic load level in a certain range, and the peak strain was negatively correlated. The energy accumulation and dissipation are closely related to the failure of the samples. The strain energy is more concentrated in the area where the failure occurs first. The AE energy under dynamic load is developed from the traditional “four-stages” characteristic under static load to three stages. The interval release stage appears because of the appearance of intermittent disturbance load makes the AE energy of the sample change intermittently. The dynamic instability of samples accompanies a sudden increase in AE energy rate, hysteresis loop area and strain. Compared with the shear failure of single lithology sample, the failure mode of the combinations is mainly tensile, and it turns into tensile-shear failure under dynamic load. The fragmentation of samples is different under different failure modes. The fragmentation index can characterize the failure mode and crack propagation characteristics of coal-rock combination. The research provides reference for large deformation dynamic disasters of surrounding rock.