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Abstract The frigid and droughty climate of Xinjiang in China has given rise to unique indigenous sheep breeds with robust adaptability and resistance. To investigate the genetic mechanism of adaptability of Xinjiang sheep to the local extreme environment, we conducted population genetic structure analyses for three native Xinjiang sheep breeds: Altay sheep (ALT), Bashbay Sheep (BSBC), and Duolang sheep (DLC), as well as two foreign sheep breeds: Suffolk and Dorset, using the Ovine Infinium HD SNP BeadChip(680 K). Our findings revealed distinct genetic and evolutionary histories between Xinjiang and foreign sheep breeds. Principal Component Analysis (PCA) and phylogenetic tree effectively differentiate these five sheep breeds based on their geographical origins, and the domestication level of Xinjiang sheep is comparatively lower than that of foreign sheep breeds. Furthermore, by utilizing three selective signature methods, namely Fixation Index (Fst), Cross Population Extended Haplotype Homozygosity Test (XP-EHH), and Nucleotide Diversity (π), we have successfully identified 22 potential candidate genes. Among these genes, there are TBXT, PDGFD, and VEGFA, which are closely related to tail type and lipid metabolism; VIL1, SLC11A1, and ZBTB46, which are associated with immune function; and candidate genes such as BNC1, HDAC1, and BMP5, which impact sheep reproductive traits. This study establishes a foundation for conserving and utilizing local sheep germplasm resources in Xinjiang and provides molecular insights into the genetic mechanisms governing sheep adaptation to extreme cold and arid environments.

The objective of this study is to analyze environmental genetic selection signals in large-scale sheep populations with conflicting environmental adaptations, aiming to identify and isolate genes associated with environmental adaptations in sheep populations. Kirghiz sheep, which inhabit high-altitude environments year-round, demonstrate the ability to adapt to extreme conditions. In this study, 42 Kirghiz sheep, 24 Tien-Shan in Kyrgyzstan sheep, 189 Qira black sheep, and 160 Chinese Merino sheep were genotyped using Illumina Ovine SNP50K chip. Regions exhibiting a selection signal threshold of 5%, as well as PI analysis and haplotype statistical scanning gene data were annotated, and intersecting genes were identified as candidate genes. Through Fst and haplotype statistical analysis revealed the key gene PDGFD and its vicinity’s impact on fat deposition in sheep tails. Additionally, Fst and PI analysis uncovered genes related to high-altitude adaptation as well as those linked to animal growth and reproduction.Further GO and KEGG enrichment pathway analyses unveiled pathways associated with high-altitude adaptation such as negative regulation of peptidyl-tyrosine phosphorylation and xenobiotic metabolism processes.This investigation into the adaptability of Kirghiz sheep provides theoretical support and practical guidance for the conservation and genetic enhancement of Kirghiz sheep germplasm resources.

The hybrid reactive power compensation system, which connects different reactive power compensation devices to the same bus, will be essential equipment for future power systems. In a power grid with a high proportion of photovoltaic, wind turbines, and power electronic devices, it is significant to design a coordinated control strategy for the hybrid reactive power compensation system. In this paper, a kind of ping-pang variable amplitude limiter is used in the linear optimal controller. The ping-pang variable amplitude limiter can improve the transient stability of a hybrid reactive power compensation system. The effects of the coordinated controller are verified in simulation. Compared with the conventional linear optimal controller, the coordinated controller with the ping-pang variable amplitude limiter has a better optimization effect in large disturbance conditions.

Introduction: The rising incidence of type 2 diabetes has seriously affected international public health. The search for more drugs that can effectively treat diabetes has become a cutting-edge trend in research. Coenzyme Q10 (CoQ10) has attracted much attention in the last decade due to its wide range of biological activities. Many researchers have explored the clinical effects of CoQ10 in patients with type 2 diabetes. However, CoQ10 has low bio-availability due to its high lipophilicity. Therefore, we have structurally optimized CoQ10 in an attempt to exploit the potential of its pharmacological activity.Methods: A novel coenzyme Q10 derivative (L-50) was designed and synthesized by introducing a group containing bromine atom and hydroxyl at the terminal of coenzyme Q10 (CoQ10), and the antidiabetic effect of L-50 was investigated by cellular assays and animal experiments.Results: Cytotoxicity results showed that L-50 was comparatively low toxicity to HepG2 cells. Hypoglycemic assays indicated that L-50 could increase glucose uptake in IR-HepG2 cells, with significantly enhanced hypoglycemic capacity compared to the CoQ10. In addition, L-50 improved cellular utilization of glucose through reduction of reactive oxygen species (ROS) accumulated in insulin-resistant HepG2 cells (IR-HepG2) and regulation of JNK/AKT/GSK3β signaling pathway, resulting in hypoglycemic effects. Furthermore, the animal experiments demonstrated that L-50 could restore the body weight of HFD/STZ mice. Notably, the findings suggested that L-50 could improve glycemic and lipid metabolism in HFD/STZ mice. Moreover, L-50 could increase fasting insulin levels (FINS) in HFD/STZ mice, leading to a decrease in fasting blood glucose (FBG) and hepatic glycogen. Furthermore, L-50 could recover triglycerides (TG), total cholesterol (T-CHO), lipoprotein (LDL-C) and high-density lipoprotein (HDL-C) levels in HFD/STZ mice.Discussion: The addition of a bromine atom and a hydroxyl group to CoQ10 could enhance its anti-diabetic activity. It is anticipated that L-50 could be a promising new agent for T2DM.

Abstract Parkinson’s disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients. These results contrast with previous work limited by small sample sizes and small numbers of sites. Our bradykinesia estimation corresponded well with clinician ratings (interclass correlation 0.74). This agreement was consistent across four clinical sites. This result demonstrates how such technology can be successfully deployed into existing clinical workflows, with consumer-grade smartphone or tablet devices, adding minimal equipment cost and time.

As the proportion of new energy in power systems continues to increase, the widespread use of solar and wind-based distributed generation (DG) power in DC distribution networks will face problems such as new energy consumption, grid stability, and economical benefits in the future. At present, energy management strategies for photovoltaic (PV) grid-connected power generation systems are mainly researched in the field of AC–DC distribution network. This paper provides an advanced energy management strategy of the DC multiport energy router. Considering the battery state of charge (SOC), real-time electricity price (EP), and user-side electricity charge (EC), an energy management scheme based on the fuzzy coordinated control strategy is designed to improve the utilization of energy storage batteries and the economic benefits. A 20 kVA multi-port DC energy router simulation platform is established and verified in MATLAB/Simulink. The results show that the energy management strategies based on fuzzy coordinated controller can solve the multi-objective problem. Compared with traditional control strategies, the fuzzy collaborative energy management strategy has a more comprehensive optimization effect.

In recent years, hydrogels have been widely used as drug carriers, especially in the area of protein delivery. The natural silk fibroin produced from cocoons of the Bombyx mori silkworm possesses excellent biocompatibility, significant bioactivity, and biodegradability. Therefore, silk fibroin-based hydrogels are arousing widespread interest in biomedical research. In this study, a process for extracting natural silk fibroin from raw silk textile yarns was established, and three aqueous solutions of silk fibroin with different molecular weight distributions were successfully prepared by controlling the degumming time. Silk fibroin was dispersed in the aqueous solution as “spherical” aggregate particles, and the smaller particles continuously accumulated into large particles. Finally, a silk fibroin hydrogel network was formed. A rheological analysis showed that as the concentration of the silk fibroin hydrogel increased its storage modulus increased significantly. The degradation behavior of silk fibroin hydrogel in different media verified its excellent stability, and the prepared silk fibroin hydrogel had good biocompatibility and an excellent drug-loading capacity. After the protein model drug BSA was loaded, the cumulative drug release within 12 h reached 80%. We hope that these investigations will promote the potential utilities of silk fibroin hydrogels in clinical medicine.

As for the fault diagnosis of rolling bearings under strong background noises, whether the fault feature extraction is comprehensive and accurate is critical, especially for the data-driven fault diagnosis methods. To improve the comprehensiveness and accuracy of the fault feature extraction, a fault diagnosis method of rolling bearings is proposed based on parameter optimization and Adaptive Generalized S-Transform (AGST). The AGST is used to solve the problem of incomplete feature extraction of bearing faults. The Particle Swarm Brain Storm Optimization algorithm based on the Discussion Mechanism (PSDMBSO) is used for the parameter optimization of VMD, which can better separate the complete fault components. The effectiveness of the fault diagnosis method proposed in this paper is verified by comparison with other methods.

The flexible excitation system (FES) is a kind of novel excitation system with two channels for damping control. Besides the basic functions of traditional excitation systems, flexible excitation systems can provide reactive power support for the terminal voltage, and the large-capacity FES can improve the voltage stability and power-angle stability of synchronous generator units. However, with the increase in system capacity and the complication of control objectives, the difficulty of controller design will be increased. The randomness and fluctuation of new energy resources such as photovoltaic and wind turbines may cause disturbance and fault to the power system, which requires the coordinated control strategy for the FES to achieve stability in voltage and power angle. In this paper, the basic characteristics of FES are analyzed, and the mathematic model of the single machine infinite bus (SMIB) system based on FES is derived. The coordinated control strategy based on decoupling control of stator and rotor is proposed according to the optimal objectives of voltage stability and power-angle stability, and the linear optimal excitation control (LOEC) is adopted with the adaptive amplitude limiter (AAL) determined by fuzzy rules. The MATLAB/Simulink platform is established and the results verify the superiority of the proposed LOEC + AAL control strategy in large disturbance working conditions, which showed better robustness. The proposed coordinated control strategy provides an effective solution for industrial application and performance improvement of FES.

Gait is a core motor function and is impaired in numerous neurological diseases, including Parkinson’s disease (PD). Treatment changes in PD are frequently driven by gait assessments in the clinic, commonly rated as part of the Movement Disorder Society (MDS) Unified PD Rating Scale (UPDRS) assessment (item 3.10). We proposed and evaluated a novel approach for estimating severity of gait impairment in Parkinson’s disease using a computer vision-based methodology. The system we developed can be used to obtain an estimate for a rating to catch potential errors, or to gain an initial rating in the absence of a trained clinician—for example, during remote home assessments. Videos (n=729) were collected as part of routine MDS-UPDRS gait assessments of Parkinson’s patients, and a deep learning library was used to extract body key-point coordinates for each frame. Data were recorded at five clinical sites using commercially available mobile phones or tablets, and had an associated severity rating from a trained clinician. Six features were calculated from time-series signals of the extracted key-points. These features characterized key aspects of the movement including speed (step frequency, estimated using a novel Gamma-Poisson Bayesian model), arm swing, postural control and smoothness (or roughness) of movement. An ordinal random forest classification model (with one class for each of the possible ratings) was trained and evaluated using 10-fold cross validation. Step frequency point estimates from the Bayesian model were highly correlated with manually labelled step frequencies of 606 video clips showing patients walking towards or away from the camera (Pearson’s r=0.80, p<0.001). Our classifier achieved a balanced accuracy of 50% (chance = 25%). Estimated UPDRS ratings were within one of the clinicians’ ratings in 95% of cases. There was a significant correlation between clinician labels and model estimates (Spearman’s ρ=0.52, p<0.001). We show how the interpretability of the feature values could be used by clinicians to support their decision-making and provide insight into the model’s objective UPDRS rating estimation. The severity of gait impairment in Parkinson’s disease can be estimated using a single patient video, recorded using a consumer mobile device and within standard clinical settings; i.e., videos were recorded in various hospital hallways and offices rather than gait laboratories. This approach can support clinicians during routine assessments by providing an objective rating (or second opinion), and has the potential to be used for remote home assessments, which would allow for more frequent monitoring.

Excessive CO2 content will reduce the natural gas calorific value and increase the energy consumption of the regenerator in natural gas desulfurization and decarbonization. This paper uses Aspen HYSYS to model a novel two-stage flash process of acid gas removal process from natural gas. According to the results from the simulation, as well as running experiences in a natural gas processing plant in the middle east, it can be demonstrated that this new process, which has been used in the field of natural gas desulfurization and decarbonization, can meet the requirement of product specifications. Based on the steady state simulation, Aspen HYSYS sensitivity function is used to evaluate influence of key operating parameters, such as the second flash pressure and temperature, on the energy consumption. Compared to the traditional acid gas removal process and acid gas enrichment process, the new two-stage flash acid gas removal process has less energy consumption (2.2 × 109 kJ·h−1). In addition, two-stage flash acid gas removal process also improves the efficiency of acid gas enrichment, while the overall energy consumption is less than combination process of traditional process and acid gas enrichment process.

With the rapid development of GIS and computer techniques, vector map data has been widely used in many fields. Since the production of map data is very costly, illegal copying will result in huge loss for data owners. In order to protect the copyright of vector data, digital watermarking has been employed in recent years. In this paper, a zero-watermarking scheme for vector map data is proposed. In the proposed scheme, FVDR (feature vertex distance ratio) is constructed based on the feature vertices of objects. The feature data, FVDR, is combined with watermark to generate the zero-watermark. Due to the specially designed cover data, the proposed scheme is robust to geometrical attacks, vertex attacks, and object attacks. The results of extensive experiments also demonstrate the robustness of the proposed scheme.