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Background: Cataracts are a common eye disease and a major cause of blindness in China and worldwide. In China, the incidence of cataracts among people over 60 years old is as high as 80%. Surgery is the primary treatment for various types of cataracts, but such invasive procedures can affect corneal endothelial cells to some extent. Content: Cataract surgery can damage corneal endothelial cells, leading to complications such as corneal edema in mild cases. Severe damage can result in endothelial decompensation, necessitating secondary corneal endothelial transplantation. Preoperative thorough assessment of endothelial status, intraoperative endothelial protection measures, and postoperative active use of medications to prevent further damage to endothelial cells can reduce endothelial cell loss. Factors influencing endothelial cell status include whether the patient has related systemic diseases or ocular conditions, the hardness of the nucleus, the choice of surgical incision, the method of nuclear fragmentation, the type of viscoelastic agent used, the orientation of the phacoemulsification needle bevel, the duration and energy of ultrasound use, the choice of fluid control system, the use of protective auxiliary instruments, the application of intraocular lens scaffold technology, femtosecond laser assistance, and the use of certain medications. Conclusions: Actively regulating the factors affecting corneal endothelial cells to reduce damage related to cataract surgery is crucial. This paper reviews the existing literature on various factors affecting corneal endothelial cells during cataract surgery and explores future developments and research directions.

Abstract Exploring catalytic reaction mechanisms is crucial for understanding chemical processes, optimizing reaction conditions, and developing more effective catalysts. We present a reaction-agnostic framework based on high-throughput deep reinforcement learning with first principles (HDRL-FP) that offers excellent generalizability for investigating catalytic reactions. HDRL-FP introduces a generalizable reinforcement learning representation of catalytic reactions constructed solely from atomic positions, which are subsequently mapped to first-principles-derived potential energy landscapes. By leveraging thousands of simultaneous simulations on a single GPU, HDRL-FP enables rapid convergence to the optimal reaction path at a low cost. Its effectiveness is demonstrated through the studies of hydrogen and nitrogen migration in Haber-Bosch ammonia synthesis on the Fe(111) surface. Our findings reveal that the Langmuir-Hinshelwood mechanism shares the same transition state as the Eley-Rideal mechanism for H migration to NH2, forming ammonia. Furthermore, the reaction path identified herein exhibits a lower energy barrier compared to that through nudged elastic band calculation.

Ceftazidime-avibactam (CZA) is a recently approved combination synthetic β-lactamase inhibitor used in human clinical medicine. Cases of CZA resistance in humans have already been reported, but limited research has investigated CZA resistance in pets. This study explored the prevalence and transmission of CZA-resistant Escherichia coli (CZAREC) among pets, their owners, veterinarians, and the environment in animal hospitals. A total of 5,419 clinical samples were collected from dogs and cats, along with samples from the environment (n = 5,843), veterinarians (n = 557), and pet owners (n = 368) in animal hospitals. From these samples, 760 Escherichia coli (E. coli) isolates were obtained, out of which 60 were identified as CZAREC. These included 34 isolates from the environment (9.14 %, n = 372), three from veterinarians (8.11 %, n = 37), and 23 from animals (6.82 %, n = 337). No CZAREC isolates were found in pet owners. The predominant sequence types of CZARECs were ST156 (n = 20), ST410 (n = 19) and ST101 (n = 7). Bayesian analysis revealed six clusters comprising 47 isolates from the hospital environment, pets, and veterinaries, displaying genetic relatedness of less than 100 core genome single nucleotide polymorphisms (cgSNPs) between any two isolates in each cluster. Some CZAREC isolates with high genetic similarity persisted in the same animal hospital for four to six months. Moreover, discriminant analysis of principal components indicated that most isolates from different hosts shared a genetic source in the human/dog/cat merged cluster. Overall, evidence of CZARECs transmission was found among pets, the environment, and veterinarians in animal hospitals. The findings emphasize the importance of monitoring CZARECs in the veterinary clinical setting to ensure the health of both pets and humans.

The proven geological reserves of the Shenfu deep coalbed methane (CBM) field on the eastern margin of the Ordos Basin exceed 100 billion cubic meters. It is of great significance to realizing the efficient development of deep CBM in this region to ensure the national energy supply. However, the complexity of the geological environment which includes high stress, medium-high temperatures, low permeability, strong heterogeneity, and wide developed cleats and natural fractures, makes it challenging for the existed shallow and medium CBM fracturing techniques to be fully applicable to deep CBM resources. As a result, the stimulation scale and parameters for deep coalbed fracturing are still in the trial-and-error stage. In order to explore the stimulation techniques which are compatible with the geological conditions of deep coalbeds, the Shenfu block in the Ordos Basin was taken as the geological background and the large-scale hydraulic fracturing of deep coal seams was conducted as an engineering practice. The authors designed the idea of “Push the limit to the beyond + balanced propagation + effective support”, and proposed the massive hydraulic fracturing techniques based on “multi-stage multi-clusters with moderate-dense cutting + perforation with equal apertures, deep penetration and limited flow + integrated variable viscosity (rock breaking by higher viscous slick water + complex fracture network generating by lower viscous slick water) + high pumping rate with high proppant concentration + pre-acid treatment to reduce the breakdown pressure + graded proppants with multiple sizes to support fractures”. Then, the authors put forward an integrated “Geology-Engineering-AI” workflow to perform post-frac analysis, through double matching and correcting the fracturing pumping pressure and production rate automatically, accurately characterized the stimulated reservoir volume (SRV) and drained rock volume (DRV), and predicted the estimated ultimate recovery (EUR) under different fracturing scales and well types. Finally, by statistically analyzing the gas production characteristics of multiple wells in the Shenfu block and utilizing the random forest method, the primary controlling factors affecting the production capacity of deep CBM were quantitatively analyzed. The results demonstrate that after reservoir stimulation, directional wells can achieve a maximum daily gas production rate exceeding 10 000 m3/d, while horizontal wells can achieve a maximum daily gas production rate exceeding 20 000 m3/d. It indicates that the deep coal beds have good fracturing properties and great development potential. The primary impact factors for peak gas production rate are gas content, coalbed thickness and proppant concentration, while the major impact factors for cumulative gas production include gas content, proppant concentration, and total volume of proppants.

Abstract Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson’s disease, Essential Tremor, Dystonia, Essential Tremor, Huntington’s disease, and Tourette’s syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder – BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Abstract The reduction of interfacial interaction and the deterioration of processing properties of aluminum hydrides (AlH3) is the main challenges preventing its practical application. Here, a simple and effective core–shell structure aluminum hydrides@polydopamine (AlH3@PDA) complex was constructed through in-situ polymerization. The evolution of element states on the surface of AlH3 conducted by X-ray photoelectron spectroscopy indicated the successful introduction of PDA to form the core@shell structure, the thickness of the PDA coated layer increased with the increasing PDA dosage from 0.1 to 1.6% in mass fraction, and the maximum of thickness is 50 nm in TEM testing. Py GC/MS results proved that the increase of dopamine concentration leads to higher proportions of self-assemble units, whereas lower dopamine concentrations favor higher levels of chemical bonded components. Regarding whether PDA is a covalent polymer or a noncovalent aggregate of some species, the formation of intermediates, such as dopaminechrome and 5,6-dihydroxyindole played an important role to coordination interaction with AlH3 in FTIR, Raman, and UV–Vis spectra testing. Compared with pure AlH3, the formation of organic PDA coating improved AlH3 heat resistance. The adhesion work with GAP adhesive was also improved from 107.02 J/m2 of pure AlH3 to 111.13 mJ/m2 of AlH3@PDA-5 complex. This paper provides well support for further practical application of AlH3 in solid propellants.

BackgroundTraditional Chinese opera, such as Pingju, requires actors to master sophisticated performance skills and cultural knowledge, potentially influencing brain function. This study aimed to explore the effects of long-term opera training on the dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC).MethodsTwenty professional well-trained Pingju actors and twenty demographically matched untrained subjects were recruited. Resting-state functional magnetic resonance imaging (fMRI) data were collected to assess dALFF differences in spontaneous regional brain activity between the actors and untrained participants. Brain regions with altered dALFF were selected as the seeds for the subsequent dFC analysis. Statistical comparisons examined differences between groups, while correlation analyses explored the relationships between dALFF and dFC, as well as the associations between these neural measures and the duration of Pingju training.ResultsCompared with untrained subjects, professional Pingju actors exhibited significantly lower dALFF in the right lingual gyrus. Additionally, actors showed increased dFC between the right lingual gyrus and the bilateral cerebellum, as well as between the right lingual gyrus and the bilateral midbrain/red nucleus/thalamus, compared with untrained subjects. Furthermore, a negative correlation was found between the dALFF in the right lingual gyrus and its dFC, and a significant association was found between dFC in the bilateral midbrain/red nucleus/thalamus and the duration of Pingju training.ConclusionLong-term engagement in Pingju training induces neuroplastic changes, reflected in altered dALFF and dFC. These findings provide evidence for the interaction between artistic training and brain function, highlighting the need for further research into the impact of professional training on cognitive functions.

Xinjiang is a major province of sheep breeding in China, which plays an important role in meeting people’s needs for meat products, increasing farmers’ income and sustainable development of animal husbandry. However, the genetic differentiation relationship between breeds was not clear, and most sheep had low fecundity, which seriously restricted the efficient development of sheep industry. Therefore, this study used the whole genome resequencing to detect the genetic variation of Dexin mutton and fine-wool sheep, explored the selected regions and important genes of the litter size traits, analyzed the genetic mechanism of reproductive traits, and provided new insights for the high fecundity breeding of sheep. A total of 5,236.338 G genome data and 35,884,037 SNPs were obtained. Furthermore, we identified 39 selection signals spanning candidate genes, 99 genes were significantly associated related to growth, reproduction and immunity, among which, BRIP1, BMPR1B, BMP4, NGF, etc. genes, and MAKP signaling pathway, Fanconi anemia pathway and Thyroid hormone signaling pathway and other signaling pathways were significantly correlated with litter size trait. Among them, we identified NGF, TrKA and BRIP1 genes was the important genes for sheep litter size traits and the mutation frequencies of 9 SNPs in BRIP1 gene were significantly different in domestic sheep in the world. The research provided new insights for the breeding of self-cultivated meat fine-wool sheep.

Abstract The relationship between the immune cell and tumor occurrence and progression remains unclear. Profiling alterations in the tumor immune microenvironment (TIME) at high resolution is crucial to identify factors influencing cancer progression and enhance the effectiveness of immunotherapy. However, traditional sequencing methods, including bulk RNA sequencing, exhibit varying degrees of masking the cellular heterogeneity and immunophenotypic changes observed in early and late-stage tumors. Single-cell RNA sequencing (scRNA-seq) has provided significant and precise TIME landscapes. Consequently, this review has highlighted TIME cellular and molecular changes in tumorigenesis and progression elucidated through recent scRNA-seq studies. Specifically, we have summarized the cellular heterogeneity of TIME at different stages, including early, late, and metastatic stages. Moreover, we have outlined the related variations that may promote tumor occurrence and metastasis in the single-cell era. The widespread applications of scRNA-seq in TIME will comprehensively redefine the understanding of tumor biology and furnish more effective immunotherapy strategies.

Abstract A novel variant of rabbit haemorrhagic disease virus, designated RHDV2/b/GI.2, was first discovered in France in 2010. Subsequently, RHDV2 rapidly spread to Africa, North America, Australia, and Asia. RHDV2 outbreaks have resulted in significant economic losses in the global rabbit industry and disrupted the balance of natural ecosystems. Our study investigated the seasonal characteristics of RHDV2 outbreaks using seasonal indices. RHDV2 is prone to causing significant outbreaks within domestic and wild rabbit populations during the spring season and is more likely to induce outbreaks within wild rabbit populations during late autumn in the Southern Hemisphere. Furthermore, based on outbreak data for domestic and wild rabbits and environmental variables, our study established two MaxEnt models to explore the relationship between RHDV2 outbreaks and the environmental factors and conducted outbreak risk predictions for RHDV2 in global domestic and wild rabbit populations. Both models demonstrated good predictive performance, with AUC values of 0.960 and 0.974, respectively. Road density, isothermality, and population density were identified as important variables in the outbreak of RHDV2 in domestic rabbits, while road density, normalized difference vegetation index, and mean annual solar radiation were considered key variables in the outbreak of RHDV2 in wild rabbits. The environmental factors associated with RHDV2 outbreaks identified in our study and the outbreak risk prediction maps generated in our study will aid in the formulation of appropriate RHDV2 control measures to reduce the risk of morbidity in domestic and wild rabbits.

The adaptive cutting technology of the shearer is a key technology for achieving intelligent mining in fully mechanized working faces. In order to solve the problem of low automatic cutting precision of the shearer in complex coal seams, a prediction method for the height adjustment of shearer drum based on improved gated recurrent neural network (GRU) is proposed. Considering the correlation between adjacent data in the longitudinal and transverse directions of the cutting trajectory, the fixed length sliding time window method is used to obtain the height data of the shearer drum. The input data is divided into continuous and adjustable subsequences, while processing the feature information in the transverse and longitudinal directions. To improve the prediction efficiency of the model and meet the real-time requirements of cyclic cutting, causal convolution gated recurrent unit(CC-GRU) is proposed to perform dual feature extraction and dual data filtering on input data. CC-GRU utilizes causal convolution to focus on the local temporal features in the longitudinal direction of the sequence in advance, in order to reduce computational costs and improve computational speed. CC-GRU uses gating mechanism to serialize and model the features obtained from convolution to capture long-term dependencies between elements. The experimental results show that using the CC-GRU model to predict the height adjustment of the shearer drum, the MAE is 43.80 mm, MAPE is 1.90%, RMSE is 50.35 mm, the determination coefficient is 0.65, and the prediction time is only 0.17 seconds. Compared to long short term memory (LSTM) neural networks, GRU, and temporal convolutional network (TCN), the CC-GRU model has a faster prediction speed and higher prediction precision. It can more accurately predict the height adjustment trajectory of the shearer in real time. This provides a basis for the establishment of coal seam models in the working face and the prediction of the height adjustment trajectory of the shearer.

Antiphospholipid syndrome (APS) is an autoimmune disease characterized by recurrent arteriovenous thrombosis and pathological pregnancy, accompanied by persistent antiphospholipid antibodies, (aPL). The incidence of APS is increasing year by year, clinicians lack of understanding of this type of disease, easy to misdiagnose and miss the diagnosis. Therefore, it is extremely important to establish a suitable animal model to reduce the process of disease development as much as possible and improve clinicians’ understanding and understanding. This review will summarize the animal models of APS from the aspects of modeling methods, modeling mechanism, evaluation indicators and advantages and disadvantages of methods, providing a reference for finding an animal model highly similar to human APS, helping researchers to further clarify the pathogenesis of APS and find potential therapeutic targets, so as to achieve early diagnosis, early intervention, and ultimately improve the prognosis of patients.

A novel wire-arc additive manufacturing (WAAM) process utilising titanium flux-cored wire (FCW) containing TiB2, Al60V40 and Ti6Al4V powders was proposed for fabricating TiB/Ti6Al4V composites. The FCW exhibited the capability in customising the composition of TiB/Ti6Al4V composites from hypoeutectic to hypereutectic by tailoring the proportion of TiB2 in blended powders. The comprehensive influence of TiB2 content on molten pool flow, compositional homogeneity and porosity of as-printed composites was attributed to the reduction of melt flowability, driven by viscosity escalation. It was unravelled the porosity was the intrinsic deficiency for the FCW-WAAM process, originating from the gases within FCW, while the interlayered TiB clusters were caused by the lagging melt of TiB2 powders. Due to directional solidification, TiB whiskers possessed a large aspect ratio and were partial to upward growth in hypoeutectic composites, which enhanced the load transfer strengthening. However, the porosity degraded the ductility of composites and caused the variation in mechanical performance.

The restoring force model (RFM) is the basis of elasto-plastic time-history analysis and forms a critical part of the seismic response analysis of structures. Based on the previous research results of a novel modular steel-concrete composite column, this paper qualitatively processed the test data through dimensionless and regression analyses. A three-fold line skeleton curve model (SCM) suitable for modular steel-concrete composite columns was proposed, and the stiffness degradation and hysteretic rule of the novel modular steel-concrete composite column were presented. Based on these results, a three-fold line RFM considering the stiffness degradation was established. Comparing the calculated results of the resilience model with the test results showed that the yield point moment obtained from the test was 0.84−1.34 times the calculated moment of the RFM, with an average value (AVG) of 1.01 and a coefficient of variation (COV) of 0.02. The peak moment obtained from the test was 0.96−1.01 times the calculated moment of the RFM, with an AVG of 0.99 and a COV of 0.00. Thus, the reliability of the RFM of the novel modular steel-concrete composite column was verified.

High pressure has traditionally been considered essential for the transformation of graphite into diamond. However, reducing the transition pressure required for this graphite-to-diamond (G2D) conversion holds significant appeal in both scientific research and engineering applications. In this study, we conducted large-scale molecular dynamics (MD) simulations using an environment-dependent interaction potential (EDIP) to examine the shear deformation of nanocrystalline graphite (n-graphite) with a grain size of approximately 6.5 nm. We discovered that the G2D transition pressure in n-graphite can be reduced to 2–3 GPa, significantly lower than the ∼90 GPa uniaxial stress required in crystalline graphite. This reduction is primarily due to concentrated local shear stresses at grain boundaries (GBs), which induce substantial rotations of graphite layers. These rotations facilitate the initial formation of diamond bonds at sites of pre-existing imperfections at the GBs, assisted by shear. Once initiated at the GBs, the G2D transition rapidly propagates within grains aligned parallel to the shear components, resulting in the formation of nanocrystalline diamond. Our findings underscore the critical roles of GBs and shear stress in enabling the G2D transition in n-graphite.

The mechanical behavior of splitting tensile damage and the law of stress wave propagation of rock-like materials (RLM) are of great significance to further reveal the dynamic disaster mechanism of the deep rock mass. The meso-damage mechanical behavior and stress wave propagation characteristics of RLM disks under impact splitting were studied by using a large diameter split Hopkinson pressure bar (SHPB). In terms of dynamic damage, the splitting tensile stress-compression strain curves of RLM disks obviously showed three stages of mechanical behavior evolution: initial elastic-plastic deformation, pre-peak plastic damage, and post-peak brittle fracture failure. The macro-damage of RLM disks increased with the increase of strain rate. The meso-tensile fracture was the result of both the initial meso-damage and the impact splitting meso-damage. The dynamic splitting damage variable defined based on the damage fracture energy can accurately describe the damage evolution characteristics of impact splitting on RLM disks. In the aspect of stress wave propagation, the peak value of transmission stress showed an advanced effect with the increase of incident stress wave. In the early stage (0–50 μs), the transmission stress wave ratio (σT/σI) increased with the increase of strain rate, while in the later stage (82–200 μs), the transmission stress wave ratio (σT/σI) decreased with the increase of strain rate. The stress wave propagation law in the process of impact splitting on RLM disks was clearly revealed based on the stress wave propagation model established by the one-dimensional elastic stress wave theory. Finally, the dynamic mechanical mechanism of splitting damage and fracture of RLM disks under different strain rates was discussed deeply.

ObjectiveEphedra, widely used in clinical practice as a medicinal herb, belongs to the genus Ephedra in the family Ephedraceae. However, the presence of numerous Ephedra varieties and variants requires differentiation for accurate identification.MethodsIn this study, we employed headspace gas chromatography mass spectrometry (HS-GC-MS), ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and global natural products social molecular networking (GNPS) for chemical component identification. Chemometric analysis was used to analyze the differential components. Metabolic analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment were utilized to explore the synthesis pathways of different components.ResultA total of 83 volatile and 79 non-volatile components were identified in Ephedra species. Differential analysis revealed that among the eight Ephedra stems, 18 volatile and 19 non-volatile differential compounds were discovered, whereas Ephedra roots exhibited 21 volatile and 17 non-volatile markers. Volatile compounds were enriched in four synthetic pathways, while non-volatile components were enriched in five pathways among the differentiated components.ConclusionThis study is the first to conduct a comparative analysis of chemical components in different Ephedra species and parts. It provides a foundational reference for authenticating Ephedra herbs, evaluating medicinal resources, and comparing quality in future studies.

Introduction: Facial nerve injury significantly impacts both the physical and psychological] wellbeing of patients. Despite advancements, there are still limitations associated with autografts transplantation. Consequently, there is an urgent need for effective artificial grafts to address these limitations and repair injuries. Recent years have witnessed the recognition of the beneficial effects of chitosan (CS) and graphene in the realm of nerve repair. Dental pulp stem cells (DPSCs) hold great promise due to their high proliferative and multi-directional differentiation capabilities.Methods: In this study, Graphene/CS (G/CST) composite tubes were synthesized and their physical, chemical and biological properties were evaluated, then DPSCs were employed as seed cells and G/CST as a scaffold to investigate their combined effect on promoting facial nerve injury repair.Results and Disscussion: The experimental results indicate that G/CST possesses favorable physical and chemical properties, along with good cyto-compatibility. making it suitable for repairing facial nerve transection injuries. Furthermore, the synergistic application of G/CST and DPSCs significantly enhanced the repair process for a 10 mm facial nerve defect in rabbits, highlighting the efficacy of graphene as a reinforcement material and DPSCs as a functional material in facial nerve injury repair. This approach offers an effective treatment strategy and introduces a novel concept for clinically managing facial nerve injuries.

Abstract Background Hydromorphone hydrochloride has a satisfactory postoperative analgesic effect for patients with colorectal cancer but is accompanied by a relatively high incidence of adverse events. Low-doses of naloxone combined with opioids for patient-controlled analgesia can reduce the incidence of drug-related adverse events. Nalmefene is a more selective opioid receptor antagonist than naloxone. The aim of this study was to determine the impact of low-doses of nalmefene on the analgesic effect and incidence of adverse events of patients with hydromorphone patient-controlled analgesia (PCA) undergoing colorectal radical surgery. Methods Ninety-nine patients undergoing elective laparoscopic or hand-assisted laparoscopic radical surgery under general anaesthesia were randomly divided into three groups. Group N1 received hydromorphone hydrochloride 0.15 mg/kg + nalmefene 2 µg/kg; Group N2 received hydromorphone hydrochloride 0.15 mg/kg + nalmefene 0.5 µg/kg; and the control group (Group C) received hydromorphone hydrochloride 0.15 mg/kg. All medications were diluted to 100 ml with normal saline. The primary outcome was pain intensity at 12 h after surgery; the secondary outcomes were the occurrence of nausea, vomiting and pruritus and the total analgesic consumption of the PCA pump at 1 h, 6 h, 12 h, 24 and 48 h after surgery. Results The NRS scores of Group N1 (2 µg/kg) were significantly lower than those of Group C (P = 0.025), and no difference was found between group N2 and group C (P > 0.05). Among the three groups, the NRS scores of Group N1 (2 µg/kg) were significantly lower than those of Group C at 12 h (P = 0.01) and 48 h (P = 0.01) postoperatively. Compared with 12 h postoperatively, the NRS scores were lower at 24 h postoperatively in Group N1 and Group C (P

In order to obtain high quality AZ31B/stainless steel resistance spot welded joints, the FeCoNiCrMn high entropy alloy was used as the interlayer. The reaction-diffusion behavior of the transition zone and the base material on both sides was analyzed, and the joint performance and the welding process were investigated. The results show that the transition zone consists of FeCoNiCrMn particles which successfully connects two base materials of AZ31B and stainless steel. The interface near AZ31B is mainly Fe4Al13 intermetallic compounds generated by the reaction around the particles; while the boundary of stainless steel is mainly composed of (Fe, Ni) solid solution and Fe4Al13 intermetallic compounds. The tensile shear load F shows a tendency that increases first and then decreases with the increase of welding current I, welding force P, and the prolongation of welding time t. The tensile shear load of the added high entropy alloy magnesium/steel spot welded joints are above 3.2 kN in the test process range of 18.2-22.5 kA, 15-35 cycle, and 2.0-10.6 kN, and the maximum tensile shear load is 5.605 kN, which is 397% higher than that of Mg/steel spot welded joints without high entropy alloy. A large number of (Fe, Ni) solid solution are formed in the high entropy alloy transition layer, which reduces the generation of Fe4Al13 brittle intermetallic compounds and effectively improves the mechanical properties of the joint.

In this paper, a novel fractal model for the contact resistance based on axisymmetric sinusoidal asperity is proposed, which focuses on the resistance characteristics of the rough interface at a microscopic scale. By introducing the unique geometric shape of axisymmetric sinusoidal asperity, and combining it with a three-dimensional fractal theory, the micro-morphology characteristics of the rough interface can be characterized more precisely. Subsequently, by conducting a theoretical analysis and numerically solving the deformation mechanisms of asperities on the rough interface, a refined model for contact resistance is constructed. This research comprehensively employs theoretical analysis, numerical simulation, and experimental testing methods to deeply explore the current transmission mechanisms during the contact process of the rough interface. The findings suggest that the proposed model is capable of precisely capturing the intricate interplay of various factors, including contact area, contact load, and material properties, with the contact resistance. Compared to the existing models, the presented model demonstrates significant advantages in terms of prediction accuracy and practicality. This research provides an important theoretical basis and design guidance for optimizing the electrical performance of the rough interface, which has great significance for engineering applications.

In order to obtain the contact resistance of relay contacts more accurately, a novel contact resistance model for the spherical–planar joint interface is constructed based on the three-dimensional fractal theory. In this model, three-dimensional fractal theory is adopted to generate a rough surface at microscopic scale. Then, using contact mechanics theory, the deformation mechanism of asperities on rough surfaces is explored. Combined with the distribution of asperities, a contact resistance model for the planar joint interface is established. Furthermore, by introducing the surface contact coefficient, cross-scale coupling between the macro-geometric configuration and micro-surface topography is achieved, and a contact resistance model for the spherical–planar joint interface is constructed. After that, experiments are conducted to verify the accuracy of the proposed model, and the maximum relative error of the proposed model is 8.44%. Ultimately, combining numerical simulation analysis, the patterns of variation in contact resistance influenced by factors such as macroscopic configuration and microscopic topography are discussed, thereby revealing the influence mechanism of the contact resistance for the spherical–planar joint interface. The proposed model provides a solid theoretical foundation for the optimization of relay contact structures and improvements in manufacturing processes, which is of great significance for ensuring the safe and stable operation of power systems and electronic equipment.

Abstract With various potential health-promoting bioactivities, genistein has great prospects in treatment of a series of complex diseases and metabolic syndromes such as cancer, diabetes, cardiovascular diseases, menopausal symptoms and so on. However, poor solubility and unsatisfactory bioavailability seriously limits its clinical application and market development. To optimize the solubility and bioavailability of genistein, the cocrystal of genistein and piperazine was prepared by grinding assisted with solvent based on the concept of cocrystal engineering. Using a series of analytical techniques including single-crystal X-ray diffraction, powder X-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimetry and thermogravimetric analysis, the cocrystal was characterized and confirmed. Then, structure analysis on the basis of theoretical calculation and a series of evaluation on the stability, dissolution and bioavailability were carried out. The results indicated that the cocrystal of genistein and piperazine improved the solubility and bioavailability of genistein. Compared with the previous studies on the cocrystal of genistein, this is a systematic and comprehensive investigation from the aspects of preparation, characterization, structural analysis, stability, solubility and bioavailability evaluation. As a simple, efficient and green approach, cocrystal engineering can pave a new path to optimize the pharmaceutical properties of natural products for successful drug formulation and delivery. Graphical Abstract

BackgroundThis study aimed at exploring unique population genetic characteristics of Albizia odoratissima (Linn. f) Benth on Hainan Island to provide a scientific basis for its rational utilization and protection.MethodsIt analyzed the genetic diversity and structure of 280 individuals from 10 subpopulations of A. odoratissima from Hainan Island and Baise City using 16 expression sequence markers - simple sequence repeat markers.ResultsThe genetic diversity of Hainan population (I = 0.7290, He = 0.4483) was lower than that of the Baise population (I = 0.8722, He = 0.5121). Compared with the Baise population (Nm = 2.0709, FST = 0.1077), the Hainan Island population (Nm = 1.7519, FST = 0.1249) exhibited lower gene flow and higher degree of genetic differentiation. Molecular variance and genetic differentiation analyses showed that the main variation originated from individuals within the subpopulation. There were significant differences in the genetic structure between Hainan and Baise populations. It grouped according to geographical distance, consistent with the Mantel test results (R2 = 0.77, p = 0.001). In conclusion, the genetic diversity of the island A. odoratissima population was lower than that distributed on land, the two populations exhibited obvious genetic structure differences. Both the degrees of inbreeding and genetic differentiation were higher in the island population than in the land population.

ObjectiveTo investigate the relationships between perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposure and glucose metabolism indices.MethodsData from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 waves were used. A total of 611 participants with information on serum PFASs (perfluorononanoic acid (PFNA); perfluorooctanoic acid (PFOA); perfluoroundecanoic acid (PFUA); perfluorohexane sulfonic acid (PFHxS); perfluorooctane sulfonates acid (PFOS); perfluorodecanoic acid (PFDeA)), glucose metabolism indices (fasting plasma glucose (FPG), homeostasis model assessment for insulin resistance (HOMA-IR) and insulin) as well as selected covariates were included. We used cluster analysis to categorize the participants into three exposure subgroups and compared glucose metabolism index levels between the subgroups. Least absolute shrinkage and selection operator (LASSO), multiple linear regression analysis and Bayesian kernel machine regression (BKMR) were used to assess the effects of single and mixed PFASs exposures and glucose metabolism.ResultsThe cluster analysis results revealed overlapping exposure types among people with higher PFASs exposure. As the level of PFAS exposure increased, FPG level showed an upward linear trend (p 50 years-old group: β = 0.059, p 50 years-old group: insulin β = 0.191, p = 0.018, HOMA-IR β = 0.220, p = 0.013) showed positive correlation with HOMA-IR/insulin, which was essentially the same as results that obtained for the univariate exposure-response map in the BKMR model. Association of exposure to PFASs on glucose metabolism indices showed positive interactions between PFOS and PFHxS and negative interactions between PFOA and PFNA/PFOS/PFHxS.ConclusionOur study provides evidence that positive and negative correlations between PFASs and FPG and HOMA-IR/insulin levels are observed, respectively. Combined effects and interactions between PFASs. Given the higher risk of glucose metabolism associated with elevated levels of PFAS, future studies are needed to explore the potential underlying mechanisms.

BackgroundThe data report of a large sample, dynamic epidemiology, and characteristic analysis of pediatric tuberculosis (TB) in Southwest China is not clear. Herein, we conducted descriptive dynamic epidemiology, characteristic analysis and geographical distribution study of pediatric TB inpatients in Southwest China for more than 20 years.MethodsPatients with pediatric TB were recruited from October 2002 to September 2022 in Southwest of China based on etiology or clinical confirmation. Extract hospitalization medical record information for each patient. The geographical distribution chart of cases is used to display the trend of case flow segmented every 5 years.ResultsAmong 3,024 pediatric TB patients with an average age of 9.11 ± 4.39, 17.49% (529) had pulmonary tuberculosis (PTB), 9.06% (274) had extrapulmonary tuberculosis (EPTB), and 73.45% (2,221) had combined TB. The most common form of EPTB is disseminated TB (28.98%), followed by TB lymphadenitis (20.56%), pleural TB (19.72%), and TB meningitis (19.68%). Children aged 0–4 years had a high risk of TB meningitis and a severe symptoms, while children in the elderly age group had a high risk of pleural TB. In the past 20 years, hospitalized TB pediatric cases mainly came from Sichuan, Tibet, Qinghai, Yunnan and other places. The number of patients from ethnic minorities, especially Tibetans, showed an upward trend on a yearly basis (χ2 = 401.43, P

The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.

PICO Question In cats with chronic gingivostomatitis, does using intravenous mesenchymal stem cell therapy, compared to not using it, lead to the improvement of clinical signs? Clinical bottom line Category of research Treatment. Number and type of study designs reviewed Five interventional studies (clinical trials). Strength of evidence Moderate. Outcomes reported The reviewed studies indicate intravenous mesenchymal stem cell (MSC) therapy is safe to administer and can be effective in remission or alleviating the clinical signs of refractory, chronic gingivostomatitis in cats that have undergone full-mouth tooth extraction. Conclusion The collective evidence supports the intravenous administration of mesenchymal stem cell (MSC) therapy in cats with chronic gingivostomatitis following dental extraction. However, conducted clinical trials are prone to different degrees of bias due to the lack of independent control groups, the small number of subjects, and enrolling subjects with various severity of the disease. Therefore, more robust evidence can be obtained through well-designed randomised controlled trials to confirm the observed positive effects of the treatment in cats with a broader range of characteristics. How to apply this evidence in practice The application of evidence into practice should take into account multiple factors, not limited to: individual clinical expertise, patient’s circumstances and owners’ values, country, location or clinic where you work, the individual case in front of you, the availability of therapies and resources. Knowledge Summaries are a resource to help reinforce or inform decision making. They do not override the responsibility or judgement of the practitioner to do what is best for the animal in their care.

Abstract Parkinson’s disease (PD) is associated with excessive beta activity in the basal ganglia. Brain sensing implants aim to leverage this biomarker for demand-dependent adaptive stimulation. Sleep disturbance is among the most common non-motor symptoms in PD, but its relationship with beta activity is unknown. To investigate the clinical potential of beta activity as a biomarker for sleep quality in PD, we recorded pallidal local field potentials during polysomnography in PD patients off dopaminergic medication and compared the results to dystonia patients. PD patients exhibited sustained and elevated beta activity across wakefulness, rapid eye movement (REM), and non-REM sleep, which was correlated with sleep disturbance. Simulation of adaptive stimulation revealed that sleep-related beta activity changes remain unaccounted for by current algorithms, with potential negative outcomes in sleep quality and overall quality of life for patients.

ABSTRACT: Objectives: The aim of the study was to update the classification of drugs used in multidrug-resistant tuberculosis (MDR-TB) regimens. Group A drugs (fluoroquinolones, bedaquiline (BDQ), and linezolid (LZD)) are crucial drugs for the control of MDR-TB. Molecular drug resistance assays could facilitate the effective use of Group A drugs. Methods: We summarised the evidence implicating specific genetic mutations in resistance to Group A drugs. We searched PubMed, Embase, MEDLINE, and the Cochrane Library for studies published from the inception of each database until July 1, 2022. Using a random-effects model, we calculated the odds ratios and 95% confidence intervals as our measures of association. Results: A total of 5001 clinical isolates were included in 47 studies. Mutations in gyrA A90V, D94G, D94N, and D94Y were significantly associated with an increased risk of a levofloxacin (LFX)-resistant phenotype. In addition, mutations in gyrA G88C, A90V, D94G, D94H, D94N, and D94Y were significantly associated with an increased risk of a moxifloxacin (MFX)-resistant phenotype. In only one study, the majority of gene loci (n = 126, 90.65%) in BDQ-resistant isolates were observed to have unique mutations in atpE, Rv0678, mmpL5, pepQ, and Rv1979c. The most common mutations occurred at four sites in the rrl gene (g2061t, g2270c, g2270t, and g2814t) and at one site in rplC (C154R) in LZD-resistant isolates. Our meta-analysis demonstrated that there were no mutations associated with BDQ- or LZD-resistant phenotypes. Conclusion: The mutations detected by rapid molecular assay were correlated with phenotypic resistance to LFX and MFX. The absence of mutation-phenotype associations for BDQ and LZD hindered the development of a rapid molecular assay.

Abstract Background Mosquitoes play an absolute role in the spread of epidemic arbovirus diseases. Worldwide, Aedes aegypti and Aedes albopictus are the main vectors responsible for the spread of these mosquito-borne diseases. Aedes vexans, a mosquito species native to China, also carries mosquito-borne viruses, such as dengue fever virus and Japanese encephalitis virus, but research on this mosquito has been inadequate. Mapping the potential distribution range of and monthly change in the distribution of these three Aedes species is of particular importance for mosquito surveillance, eradication and disease control. Methods Monitoring data were collected for the three Aedes species in China. Long-term temperature and precipitation data (2001–2021) and land cover data were used to represent various climate and environmental conditions. An ecological niche model was developed using a maximum entropy modeling method to predict the current optimum habitat areas for the three Aedes species and to obtain important variables influencing their monthly distribution. Results The distribution model for the three Aedes species performed well, with an area under the receiver operating characteristic curve value of 0.991 for Ae. aegypti, 0.928 for Ae. albopictus and 0.940 for Ae. vexans. Analysis of the distribution change and mapping of the optimum habitat range for each Aedes species for each month demonstrated that temperature, precipitation and construction land were important factors influencing the distribution of these three Aedes species. Conclusions In China, Aedes aegypti is mainly concentrated in a few tropical regions and along the Yunnan border; Aedes albopictus is widely distributed throughout most of the country, except for the arid and semi-arid regions of northwest China; and Aedes vexans is mainly found in the northern regions. Our results provide a basis for the timing and location of surveillance efforts for high-priority mosquitoes. Graphical abstract

Abstract Background Cat-scratch disease typically presents with various ocular manifestations such as uveitis, vitritis, retinitis, retinochoroiditis, and optic neuritis. However, fundus nodular lesions was rarely reported. In our study, we reported a case of Cat-Scratch disease with binocular fundus nodular lesions. Case presentation An 11-year old male presented with uveitis in the right eye and bilateral fundus nodular lesions after indirect contact with unvaccinated cats. Comprehensive ancillary examinations including wide-angle fundus photography, ultrasonography, fluorescein fundus angiography, optical coherence tomography, and orbital magnetic resonance imaging were performed to elucidate the multidimensional features of the binocular lesions. Metagenomics next-generation sequencing was utilized to confirm the diagnosis of Cat-scratch disease. The patient’s condition showed improvement after a 6-month combination treatment regimen involving systemic administration of doxycycline hyclate and methylprednisolone tablets, as well as local application of mydriatic and corticosteroid eye drops. Conclusions We firstly reported a case of Cat-scratch disease presenting simultaneously with uveitis and fundus nodular lesions caused by Bartonella henselae infection in a child. Timely diagnosis and treatment with antibiotics and corticosteroids showed promising outcomes for the prognosis of these ocular disorders.

The joint action of human activities and environmental changes contributes to the frequent occurrence of landslide, causing major hazards. Using Interferometric Synthetic Aperture Radar (InSAR) technique enables the detailed detection of surface deformation, facilitating early landslide detection. The growing availability of SAR data and the development of artificial intelligence have spurred the integration of deep learning methods with InSAR for intelligent geological identification. However, existing studies using deep learning methods to detect landslides in InSAR deformation often rely on single InSAR data, which leads to the presence of other types of geological hazards in the identification results and limits the accuracy of landslide identification. Landslides are affected by many factors, especially topographic features. To enhance the accuracy of landslide identification, this study improves the existing geological hazard detection model and proposes a multi-source data fusion network termed MSFD-Net. MSFD-Net employs a pseudo-Siamese network without weight sharing, enabling the extraction of texture features from the wrapped deformation data and topographic features from topographic data, which are then fused in higher-level feature layers. We conducted comparative experiments on different networks and ablation experiments, and the results show that the proposed method achieved the best performance. We applied our method to the middle and upper reaches of the Yellow River in eastern Qinghai Province, China, and obtained deformation rates using Sentinel-1 SAR data from 2018 to 2020 in the region, ultimately identifying 254 landslides. Quantitative evaluations reveal that most detected landslides in the study area occurred at an elevation of 2500–3700 m with slope angles of 10–30°. The proposed landslide detection algorithm holds significant promise for quickly and accurately detecting wide-area landslides, facilitating timely preventive and control measures.

The optical image sub-pixel correlation (SPC) technique is an important method for monitoring large-scale surface deformation. RapidEye images, distinguished by their short revisit period and high spatial resolution, are crucial data sources for monitoring surface deformation. However, few studies have comprehensively analyzed the error sources and correction methods of the deformation field obtained from RapidEye images. We used RapidEye images without surface deformation to analyze potential errors in the offset fields. We found that the errors in RapidEye offset fields primarily consist of decorrelation noise, orbit error, and attitude jitter distortions. To mitigate decorrelation noise, the careful selection of offset pairs coupled with spatial filtering is essential. Orbit error can be effectively mitigated by the polynomial fitting method. To address attitude jitter distortions, we introduced a linear fitting approach that incorporated the coherence of attitude jitter. To demonstrate the performance of the proposed methods, we utilized RapidEye images to extract the coseismic displacement field of the 2019 Ridgecrest earthquake sequence. The two-dimensional (2D) offset field contained deformation signals extracted from two earthquakes, with a maximum offset of 2.8 m in the E-W direction and 2.4 m in the N-S direction. A comparison with GNSS observations indicates that, after error correction, the mean relative precision of the offset field improved by 92% in the E-W direction and by 89% in the N-S direction. This robust enhancement underscores the effectiveness of the proposed error correction methods for RapidEye data. This study sheds light on large-scale surface deformation monitoring using RapidEye images.

Aiming at the problem that dynamic targets in indoor environments lead to low accuracy and large errors in the localization and position estimation of visual SLAM systems and the inability to build maps containing semantic information, a semantic visual SLAM algorithm based on the semantic segmentation network DeepLabV3+ and LK optical flow is proposed based on the ORB-SLAM2 system. First, the dynamic target feature points are detected and rejected based on the lightweight semantic segmentation network DeepLabV3+ and LK optical flow method. Second, the static environment occluded by the dynamic target is repaired using the time-weighted multi-frame fusion background repair technique. Lastly, the filtered static feature points are used for feature matching and position calculation. Meanwhile, the semantic labeling information of static objects obtained based on the lightweight semantic segmentation network DeepLabV3+ is fused with the static environment information after background repair to generate dense point cloud maps containing semantic information, and the semantic dense point cloud maps are transformed into semantic octree maps using the octree spatial segmentation data structure. The localization accuracy of the visual SLAM system and the construction of the semantic maps are verified using the widely used TUM RGB-D dataset and real scene data, respectively. The experimental results show that the proposed semantic visual SLAM algorithm can effectively reduce the influence of dynamic targets on the system, and compared with other advanced algorithms, such as DynaSLAM, it has the highest performance in indoor dynamic environments in terms of localization accuracy and time consumption. In addition, semantic maps can be constructed so that the robot can better understand and adapt to the indoor dynamic environment.

A novel analytical model based on the generalized ubiquitiformal Sierpinski carpet is proposed which can more accurately obtain the normal contact stiffness of the grinding joint surface. Firstly, the profile and the distribution of asperities on the grinding surface are characterized. Then, based on the generalized ubiquitiformal Sierpinski carpet, the contact characterization of the grinding joint surface is realized. Secondly, a contact mechanics analysis of the asperities on the grinding surface is carried out. The analytical expressions for contact stiffness in various deformation stages are derived, culminating in the establishment of a comprehensive analytical model for the grinding joint surface. Subsequently, a comparative analysis is conducted between the outcomes of the presented model, the KE model, and experimental data. The findings reveal that, under identical contact pressure conditions, the results obtained from the presented model exhibit a closer alignment with experimental observations compared to the KE model. With an increase in contact pressure, the relative error of the presented model shows a trend of first increasing and then decreasing, while the KE model has a trend of increasing. For the relative error values of the four surfaces under different contact pressures, the maximum relative error of the presented model is 5.44%, while the KE model is 22.99%. The presented model can lay a solid theoretical foundation for the optimization design of high-precision machine tools and provide a scientific theoretical basis for the performance analysis of machine tool systems.

Abstract Owing to the advantages of low cost, flexibility, and the transmission characteristics of air–ground (AG) channels, using the unmanned aerial vehicle (UAV) as mobile relay to assist wireless communication has received significant interest recently. A green non‐orthogonal multiple access (NOMA)‐based multi‐UAV‐enabled relaying system with different rate requirements is proposed here. To improve energy efficiency (EE) of the UAV relays, an optimization problem for user grouping, UAV trajectory design and resource allocation under the constraints of information causality constraint, UAVs' maximum service capacity, maximum transmit power constraint, and different communication rate requirements of the mobile users (MUs) is formulated. According to the grouping results, the UAVs' trajectory and power allocation by Dinkelbach method, successive convex approximation, and condensation algorithm are alternately optimized. To solve this highly coupled non‐linear mixed integer programming problem, a graph‐based grouping algorithm is proposed to reduce the relative distance between the UAV relay and the MU. Simulation results show that the proposed optimization algorithm can effectively improve the EE performance of this NOMA‐based multi‐UAV‐enabled relaying system.

Abstract Hepatic mitochondrial dysfunction contributes to the progression of nonalcoholic fatty liver disease (NAFLD). However, the factors that maintain mitochondrial homeostasis, especially in hepatocytes, are largely unknown. Hepatocytes synthesize various high-level plasma proteins, among which albumin is most abundant. In this study, we found that pre-folding albumin in the cytoplasm is completely different from folded albumin in the serum. Mechanistically, endogenous pre-folding albumin undergoes phase transition in the cytoplasm to form a shell-like spherical structure, which we call the “albumosome”. Albumosomes interact with and trap pre-folding carnitine palmitoyltransferase 2 (CPT2) in the cytoplasm. Albumosomes control the excessive sorting of CPT2 to the mitochondria under high-fat-diet-induced stress conditions; in this way, albumosomes maintain mitochondrial homeostasis from exhaustion. Physiologically, albumosomes accumulate in hepatocytes during murine aging and protect the livers of aged mice from mitochondrial damage and fat deposition. Morphologically, mature albumosomes have a mean diameter of 4μm and are surrounded by heat shock protein Hsp90 and Hsp70 family proteins, forming a larger shell. The Hsp90 inhibitor 17-AAG promotes hepatic albumosomal accumulation in vitro and in vivo, through which suppressing the progression of NAFLD in mice.

Abstract The quality of green tea changes rapidly due to the oxidation and degradation of polyphenols during storage. Herein, a simple and fast Surface-enhanced Raman spectroscopy (SERS) strategy was established to predict changes in green tea during storage. Raman spectra of green tea with different storage times (2020–2015) were acquired by SERS with silver nanoparticles. The PCA-SVM model was established based on SERS to quickly predict the storage time of green tea, and the accuracy of the prediction set was 97.22%. The Raman peak at 730 cm−1 caused by myricetin was identified as a characteristic peak, which increased with prolonged storage time and exhibited a linear positive correlation with myricetin concentration. Therefore, SERS provides a convenient method for identifying the concentration of myricetin in green tea, and myricetin can function as an indicator to predict the storage time of green tea.

Abstract This paper studies unmanned aerial vehicle (UAV)‐assisted cognitive network, where the UAV can improve the communication quality of edge users. Short packet communication (SPC) is widely used due to its low delay transmission characteristic. Unlike long packet communication in conventional wireless networks, SPC has a non‐negligible packet error rate and its data transmission rate is less than Shannon capacity. Considering the fact that the UAV is usually powered by battery, the energy efficiency (EE) maximisation problem is investigated based on short packet transmission in the UAV‐assisted cognitive network. Firstly, the closed‐form expression of EE is analysed, and then the optimisation problem is formulated by jointly optimising the spectrum sensing time, packet error rate, the flight speed, and the coverage range of UAV. Secondly, the optimisation problem is solved by dividing it into four subproblems. Then, an efficient iterative algorithm is proposed to tackle this problem. Simulation results show that the proposed optimisation scheme can evidently improve the EE performance compared with other benchmark schemes. In addition, the proposed joint optimisation algorithm not only has better convergence than exhaustive method, but also has higher stability than PSO algorithm.

The inhomogeneity of joints during superplastic deformation greatly limits the application of laser beam welding/superplastic forming (LBW/SPF). In order to adjust the deformation uniformity of the joint, Yb2O3 with different mass fractions was added to the laser welded joint of TC4 titanium alloy, and the effect of Yb2O3 on the superplastic deformation behavior of the laser welded joint of TC4 titanium alloy was studied. The results showed that the addition of Yb2O3 can effectively refine β grains. At Yb2O3 content of 6 wt%, the refinement effect of Yb2O3 on the weld grains is the most obvious. At this time, the peak flow stress of the longitudinal weld sample reaches a minimum value of 25.6 MPa, and the superplasticity of the joint is significantly improved. The elongation of the transverse welded sample reached 29% of that of the base metal and the joint deformation uniformity was significantly improved. The prior β grain of weld broke during superplastic deformation, and the acicular martensite structure in the weld was gradually transformed into a lamellar structure. After the addition of Yb2O3, the lamellar structure inside the weld becomes short and disordered, which promotes occurrence of superplastic deformation.

PurposeTo explore the association between type 2 diabetes mellitus (T2DM) and body composition based on magnetic resonance fat fraction (FF) mapping.MethodsA total of 341 subjects, who underwent abdominal MRI examination with FF mapping were enrolled in this study, including 68 T2DM patients and 273 non-T2DM patients. The FFs and areas of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and abdominal muscle (AM) were measured at the level of the L1-L2 vertebral. The FF of bone marrow adipose tissue (BMAT) was determined by the averaged FF values measured at the level of T12 and L1 vertebral, respectively. The whole hepatic fat fraction (HFF) and pancreatic fat fraction (PFF) were measured based on 3D semi-automatic segmentation on the FF mapping. All data were analyzed by GraphPad Prism and MedCalc.ResultsVAT area, VAT FF, HFF, PFF of T2DM group were higher than those of non-T2DM group after adjusting for age and sex (P < 0.05). However, there was no differences in SAT area, SAT FF, BMAT FF, AM area and AM FF between the two groups (P > 0.05). VAT area and PFF were independent risk factors of T2DM (all P < 0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) for VAT area and PFF in differentiating between T2DM and non-T2DM were 0.685 and 0.787, respectively, and the AUC of PFF was higher than VAT area (P < 0.05). Additionally, in seemingly healthy individuals, the SAT area, VAT area, and AM area were found to be significantly associated with being overweight and/or obese (BMI ≥ 25) (all P < 0.05).ConclusionsIn this study, it was found that there were significant associations between T2DM and VAT area, VAT FF, HFF and PFF. In addition, VAT area and PFF were the independent risk factors of T2DM. Especially, PFF showed a high diagnostic performance in discrimination between T2DM and non-T2DM. These findings may highlight the crucial role of PFF in the pathophysiology of T2DM, and it might be served as a potential imaging biomarker of the prevention and treatment of T2DM. Additionally, in individuals without diabetes, focusing on SAT area, VAT area and AM area may help identify potential health risks and provide a basis for targeted weight management and prevention measures.

Summary: The increasing demand for chemical raw materials has provided opportunities for the ammonia (NH3) industry. However, little attention has been devoted to the economic feasibility of renewable-to-ammonia (RE2A). Therefore, this paper proposes a technoeconomic model to research the optimal capacity configuration and quantify the levelized cost of ammonia (LCOA) for RE2A, which is a retrofitted plant based on coal-to-ammonia (C2A). A cost model of C2A is established as a benchmark to evaluate the economic feasibility of RE2A. A case study in Inner Mongolia is adopted, which shows that the monthly NH3 output is 7–11×103t, which satisfies actual industrial production. The LCOA of RE2A is 469$/t, with investment in wind turbines accounting for 58%, which is lower than the NH3 market price (605$–650$/t). The LCOA of RE2A will equal that of C2A with a carbon tax of 47.1$/t CO2, which confirms the economic advantages of RE2A in the future.

Bioelectric phenomena play important roles in living organisms and are essential for regulating cellular and tissue behavior. Electroactive assemblies can facilitate tissue repair and/or regulate neural activity by simulating the tissue microenvironment, while providing electrical signals and biocompatible component niches. Self-powered nanogenerators including TENG and PENG are essential part in electroactive assemblies. Assemblies incorporating TENG or PENG can present the advantages of controllable morphology, portability, low cost, and flexibility, making them a new and promising research content in the biomedical field. Herein, we describe in detail the basic physical rules underlining electric field generations in assemblies, and discuss constructing rules and research progress of self-powered assemblies in tissue engineering. Their applications in the fields of bone tissue repair and regeneration, nerve modulation and injury repair, skin wound healing, and antibacterial are sequentially discussed. Finally, current challenges and possible solutions of self-powered artificial assemblies are discussed, expecting to promote the research efforts and advance the self-powered assemblies from laboratory to clinical applications.

ABSTRACTObjective: The clinical and genetic characteristics of a child with inherited bone marrow failure syndrome as prominent clinical manifestations and special facial features were analyzed, and the etiology and mechanism were explored in, combination with clinical practice. Methods: Blood samples and clinical information were collected separately from the proband and their biological parents. The pathogenic variant was verified using next-generation sequencing technology screening, and the candidate variable sites were confirmed by using Sanger sequencing among all members of the family. Results: A heterozygous nonsense mutation in exon 17 of KAT6A (NM_006766), c.4177G > T (p.E1393*) predicted to cause truncation within the acidic domain of the protein was identified. Pedigree analysis did not reveal any variation in this locus between the proband's father and mother. No report of this pathogenic variant was found in a literature search of domestic and foreign databases, indicating that it is a newly discovered mutation. According to the guidelines of the American College of Medical Genetics, the variation was preliminarily determined to be a pathogenic. The newly discovered heterozygous mutation in KAT6A may be the cause of the disease in this child. Additionally, inherited bone marrow failure syndrome is a prominent manifestation. Conclusion: This study not only provides us with an in-depth understanding of this rare syndrome but also deepens our understanding of the function of KAT6A.

Coriolopsis trogii and Cerrena unicolor were investigated for laccase production in submerged fermentation with different nutrient medium containing metal ions and lignocellulosic materials. The maximum laccase activity of C. trogii Han751 was 8584.44 ± 98.45 U/L and was obtained from nutrient medium 7. However, the maximum laccase activity of C. unicolor Han 849 was 16144.26 ± 635.30 U/L from nutrient medium 9. Thus, the capacity of secreting laccase of C. unicolor Han 849 was superior to that of C. trogii Han751. Different fungal species have different medium components suitable for laccase production. The content of CuSO4·5H2O and MnSO4 in nutrient medium with the concentration of 0.25 g/L and 0.151 g/L, respectively, was more beneficial to C. trogii Han751 secreting laccase. However, the vital components of nutrient medium that contribute to the laccase activity of C. unicolor Han 849 were corncob, glucose, and CuSO4·5H2O, with the corresponding concentrations of 1 g/flask, 5 g/L, and 0.25 g/L, respectively. The results will contribute to the development of new methods to produce low-cost laccase.

Abstract With an increasing frequency of natural disasters and security attacks, the safe and stable operation of smart grid has been challenged unprecedently. To reduce the economic loss and social impact caused by power outage accidents, it is urgent to develop and improve the smart grid technology, and strengthen the disaster resistance and recovery capability of smart grids when faced with extreme events. As an efficient and flexible secondary energy source, hydrogen is crucial in improving the resilience of smart grid and supporting energy security. To further promote the deep integration of hydrogen systems and smart grid and improve the energy system resilience, the resilience of smart grids supported by hydrogen is assessed in this study. First, a technical framework of hydrogen‐powered smart grid resilience is established, and the value of hydrogen‐powered smart grid resilience is analysed considering different time frames (before, during and after an extreme event) of smart grids facing extreme events. Then, hydrogen‐powered smart grid resilience is investigated from perspectives of pre‐prevention regulation, in‐process correction regulation, and post‐recovery regulation. Finally, future direction for hydrogen‐powered smart grid resilience is investigated and related policy suggestions are provided.

Abstract Autoimmune/inflammatory diseases affect many people and are an important cause of global incidence and mortality. Mesenchymal stem cells (MSCs) have low immunogenicity, immune regulation, multidifferentiation and other biological characteristics, play an important role in tissue repair and immune regulation and are widely used in the research and treatment of autoimmune/inflammatory diseases. In addition, MSCs can secrete extracellular vesicles with lipid bilayer structures under resting or activated conditions, including exosomes, microparticles and apoptotic bodies. Among them, exosomes, as the most important component of extracellular vesicles, can function as parent MSCs. Although MSCs and their exosomes have the characteristics of immune regulation and homing, engineering these cells or vesicles through various technical means, such as genetic engineering, surface modification and tissue engineering, can further improve their homing and other congenital characteristics, make them specifically target specific tissues or organs, and improve their therapeutic effect. This article reviews the advanced technology of engineering MSCs or MSC-derived exosomes and its application in some autoimmune/inflammatory diseases by searching the literature published in recent years at home and abroad.