Ruminal microbiota and muscle metabolome characteristics of Tibetan plateau yaks fed different dietary protein levels

IntroductionThe dietary protein level plays a crucial role in maintaining the equilibrium of rumen microbiota in yaks. To explore the association between dietary protein levels, rumen microbiota, and muscle metabolites, we examined the rumen microbiome and muscle metabolome characteristics in yaks subjected to varying dietary protein levels.MethodsIn this study, 36 yaks were randomly assigned to three groups (n = 12 per group): low dietary protein group (LP, 12% protein concentration), medium dietary protein group (MP, 14% protein concentration), and high dietary protein group (HP, 16% protein concentration).Results16S rDNA sequencing revealed that the HP group exhibited the highest Chao1 and Observed_species indices, while the LP group demonstrated the lowest. Shannon and Simpson indices were significantly elevated in the MP group relative to the LP group (P < 0.05). At the genus level, the relative abundance of Christensenellaceae_R-7_group in the HP group was notably greater than that in the LP and MP groups (P < 0.05). Conversely, the relative abundance of Rikenellaceae_RC9_gut_group displayed an increasing tendency with escalating feed protein levels. Muscle metabolism analysis revealed that the content of the metabolite Uric acid was significantly higher in the LP group compared to the MP group (P < 0.05). The content of the metabolite L-(+)-Arabinose was significantly increased in the MP group compared to the HP group (P < 0.05), while the content of D-(-)-Glutamine and L-arginine was significantly reduced in the LP group (P < 0.05). The levels of metabolites 13-HPODE, Decanoylcarnitine, Lauric acid, L-(+)-Arabinose, and Uric acid were significantly elevated in the LP group relative to the HP group (P < 0.05). Furthermore, our observations disclosed correlations between rumen microbes and muscle metabolites. The relative abundance of NK4A214_group was negatively correlated with Orlistat concentration; the relative abundance of Christensenellaceae_R-7_group was positively correlated with D-(-)-Glutamine and L-arginine concentrations.DiscussionOur findings offer a foundation for comprehending the rumen microbiome of yaks subjected to different dietary protein levels and the intimately associated metabolic pathways of the yak muscle metabolome. Elucidating the rumen microbiome and muscle metabolome of yaks may facilitate the determination of dietary protein levels

MODIS-Derived Spatiotemporal Changes of Major Lake Surface Areas in Arid Xinjiang, China, 2000–2014

Inland water bodies, which are critical freshwater resources for arid and semi-arid areas, are very sensitive to climate change and human disturbance. In this paper, we derived a time series of major lake surface areas across Xinjiang Uygur Autonomous Region (XUAR), China, based on an eight-day MODIS time series in 500 m resolution from 2000 to 2014. A classification approach based on water index and dynamic threshold selection was first developed to accommodate varied spectral features of water pixels at different temporal steps. The overall classification accuracy for a MODIS-derived water body is 97% compared to a water body derived using Landsat imagery. Then, monthly composites of water bodies were derived for the months of April, July, and September to identify seasonal patterns and inter-annual dynamics of 10 major lakes (\u3e100 km2) in XUAR. Our results indicate that the changing trends of surface area of major lakes varied across the region. The surface areas of the Ebinur and Bosten Lakes showed a significant shrinking trend. The Ulungur-Jili Lake remained relatively stable during the entire period. For mountain lakes, the Barkol Lake showed a decreasing trend in April and July, but the Sayram Lake showed a significant expanding trend in September. The four plateau lakes exhibited significant expanding trends in all three seasons except for Arkatag Lake in July. The shrinking of major lakes reflects severe anthropogenic impacts due to agricultural and industrial needs, in addition to the impact of climate change. The pattern of lake changes across the XUAR can provide insight into the impact of climate change and human activities on regional water resources in this arid and semi-arid region

Microstructural and functional impairment of the basal ganglia in Wilson’s disease: a multimodal neuroimaging study

ObjectivesMagnetic susceptibility changes in brain MRI of Wilson’s disease (WD) patients have been described in subcortical nuclei especially the basal ganglia. The objectives of this study were to investigate its relationship with other microstructural and functional alterations of the subcortical nuclei and the diagnostic utility of these MRI-related metrics.MethodsA total of 22 WD patients and 20 healthy controls (HCs) underwent 3.0T multimodal MRI scanning. Susceptibility, volume, diffusion microstructural indices and whole-brain functional connectivity of the putamen (PU), globus pallidus (GP), caudate nucleus (CN), and thalamus (TH) were analyzed. Receiver operating curve (ROC) was applied to evaluate the diagnostic value of the imaging data. Correlation analysis was performed to explore the connection between susceptibility change and microstructure and functional impairment of WD and screen for neuroimaging biomarkers of disease severity.ResultsWilson’s disease patients demonstrated increased susceptibility in the PU, GP, and TH, and widespread atrophy and microstructural impairments in the PU, GP, CN, and TH. Functional connectivity decreased within the basal ganglia and increased between the PU and cortex. The ROC model showed higher diagnostic value of isotropic volume fraction (ISOVF, in the neurite orientation dispersion and density imaging model) compared with susceptibility. Severity of neurological symptoms was correlated with volume and ISOVF. Susceptibility was positively correlated with ISOVF in GP.ConclusionMicrostructural impairment of the basal ganglia is related to excessive metal accumulation in WD. Brain atrophy and microstructural impairments are useful neuroimaging biomarkers for the neurological impairment of WD

Research on the Collinear Equation Model of Visual Positioning Based on Visible Light Communication

A positioning method based on visible light communication is proposed, which receiving visible light information by low-resolution photodiode array and receiving visual information by the front camera of mobile phone. The terminal position is determined by matching spot information provided by photodiode array with visual information and position information provided by visible light communication. A collinear equation model is derived which based on mobile phone front camera. A hardware-in-loop simulation has been conducted to verify the collinear equation. The three-dimensional positioning error is on the level of decimeter. Moreover, the main factors which affect the positioning accuracy are analyzed in order to further improve the positioning accuracy

Research on the Collinear Equation Model of Visual Positioning Based on Visible Light Communication

A positioning method based on visible light communication is proposed, which receiving visible light information by low-resolution photodiode array and receiving visual information by the front camera of mobile phone. The terminal position is determined by matching spot information provided by photodiode array with visual information and position information provided by visible light communication. A collinear equation model is derived which based on mobile phone front camera. A hardware-in-loop simulation has been conducted to verify the collinear equation. The three-dimensional positioning error is on the level of decimeter. Moreover, the main factors which affect the positioning accuracy are analyzed in order to further improve the positioning accuracy

A Predictive Model for Student Achievement Using Spiking Neural Networks Based on Educational Data

Student achievement prediction is one of the most important research directions in educational data mining. Student achievement directly reflects students’ course mastery and lecturers’ teaching level. Especially for the achievement prediction of college students, it not only plays an early warning and timely correction role for students and teachers, but also provides a method for university decision-makers to evaluate the quality of courses. Based on the existing research and experimental results, this paper proposes a student achievement prediction model based on evolutionary spiking neural network. On the basis of fully analyzing the relationship between course attributes and student attributes, a student achievement prediction model based on spiking neural network is established. The evolutionary membrane algorithm is introduced to learn hyperparameters of the model, so as to improve the accuracy of the model in predicting student achievement. Finally, the proposed model is used to predict student achievement on two benchmark student datasets, and the performance of the prediction model proposed in this paper is analyzed by comparing with other experimental algorithms. The experimental results show that the model based on spiking neural network can effectively improve the prediction accuracy of student achievement

Simulation Research for the Influence of Mining Sequence on Coal Pillar Stability under Highwall Mining Method

Highwall mining, which is referred to the technique of extracting coal from the bottom of an exposed highwall, features safety, efficiency, and economy. According to existing highwall mining methods, the mining sequence has a great influence on highwall stability. Based on a highwall mining project in Australia, this study adopted the FLAC3D numerical simulation method to investigate the stability of coal pillars with different mining sequences. The results show that different mining sequences of boreholes exert a great effect on highwall stability. Compared with sequential mining, the skip mining method achieves higher speed of highwall stabilization and smaller plastic zone of coal pillar with its maximum strength decreasing by 12%. By adjusting the mining sequence scientifically, the coal pillar failure and roof collapse caused by the deviation of mining angle can be avoided. The results may provide a new angle for the studies on the coal pillar layout and stability design in highwall mining

Numerical Analysis and Deformation Mechanism Study on an Excavated High-Steep Slope of a Hydropower Station

The high-steep rock slope stability is one of the key technologies in the construction of water conservancy and hydropower projects, which affects and restricts the development of hydraulic resources and the construction of hydropower projects. In this paper, a three-dimensional numerical model was built incorporating stratigraphy, geological structures, and the inverted rock mechanical parameters to perform displacement, stress, and plastic zone analyses for an excavated slope in China using the FLAC3D software. The numerical simulation results after slope excavation show that the deformation near the fault fracture zone is the largest, ranging from 350 mm to 380 mm. The compressive stress is concentrated on the slope foot and the connecting part, the stress value is 2 MPa∼5 MPa, there is a large tensile stress area in the slope, and the tensile stress value is 0 MPa∼0.4 MPa. The plastic zone of the slope is concentrated near the fault F6 and the structural influence zone, and the rock mass of the slope basically enters the plastic state. On this basis, the deformation mechanism of slope was analyzed, while the internal and external factors affecting the slope deformation were described in detail. This work would provide an effective reference basis for slope stability evaluation and treatment of similar hydropower stations