Baduanjin exercise is a traditional Chinese health-Qigong routine, created by an ancient physician for health promotion. Its mild-to-moderate exercise intensity is suitable for individuals with medical conditions. Recently, a large number of trials were conducted to investigate the effects of Baduanjin exercise in patients with chronic obstructive pulmonary disease (COPD). It needs to be determined whether Baduanjin exercise prescription is beneficial for the management of COPD patients. Thus, we conducted a systematic review to objectively evaluate the existing literature on this topic. We searched six databases (PubMed, Web of Science, Cochrane Library, Scopus, CNKI, and Wanfang) from its inception till early May, 2018. The adapted PEDro scale was used for study quality assessment of all randomized controlled trials (RCT). The pooled effect size (Hedge’s g) of exercise capability (6-Minute Walking Test, 6-MWT), lung function parameters (forced expiratory volume in first second, FEV1; forced volume vital capacity, FVC; FEV1/FVC ratio), and quality of life were calculated based on the random-effects model. Twenty RCTs (n = 1975 COPD patients) were included in this review, with sum scores of the adapted PEDro scale between 5 and 9. Study results of meta-analysis indicate that Baduanjin is effective in improving exercise capability (Hedge’s g = 0.69, CI 0.44 to 0.94, p < 0.001, I2 = 66%), FEV1 (Hedge’s g = 0.47, CI 0.22 to 0.73, p < 0.001, I2 = 68.01%), FEV1% (Hedge’s g = 0.38, CI 0.21 to 0.56, p < 0.001, I2 = 54.74%), FVC (Hedge’s g = 0.39, CI 0.22 to 0.56, p < 0.001, I2 = 14.57%), FEV1/FVC (Hedge’s g = 0.5, CI 0.33 to 0.68, p < 0.001, I2 = 53.49%), and the quality of life of COPD patients (Hedge’ s g = - 0.45, CI -0.77 to - 0.12, p < 0.05, I2 = 77.02%), as compared to control groups. Baduanjin exercise as an adjunctive treatment may potentially improve exercise capability and pulmonary function of COPD patients as well as quality of life. Baduanjin exercise could be tentatively prescribed for COPD in combination with the conventional rehabilitation program to quicken the process of recovery. To confirm the positive effects of Baduanjin exercise for COPD patients, future researchers need to consider our suggestions mentioned in this article.

Air traffic congestion is caused by the unbalance between increasing traffic demand and saturating capacity. Flight delay not only causes huge economical lost, but also has very negative environmental impact in the whole air transportation system. In order to identify the impact of extended TMA on airport capacity, an airspace capacity assessment method based on augmented cell transmission model was proposed. Firstly, the airspace structure was modeled with points, segments, layers, and cells. Secondly, mixed integer linear programming model was built up with maximum throughput or capacity as the objective function. Finally, genetic algorithm was used to find the optimal result, and the results were validated by comparing with the fast-time simulation results generated by total airspace and airport modeler (TAAM) software. It is found that the proposed method could achieve a relatively accurate result in a much affordable and fast way. The numerical results could be very helpful for air traffic controllers to analyze the dynamic traffic flow entering and exiting TMA, so as to make decisions via reasonable analysis and do planning in advance by referring to the airport capacity.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

Plant protein phosphatase 2Cs (PP2Cs) serve as negative regulators of protein kinase cascades activated in different processes and play important roles in plant development and abiotic-stress-mediated signaling pathways. In this study, a genome-wide study was conducted on the CqPP2C gene family. A total of putative 117 CqPP2C genes were identified. Comprehensive analyses of physical and chemical feature, chromosome localization and subcellular localization were conducted. According to phylogenetic analysis, CqPP2Cs were divided into 13 subfamilies. CqPP2Cs in the same subfamily had similar gene structure, conserved motif and all the CqPP2C proteins had the type 2C phosphatase domains. Gene duplication revealed that segmental duplication was the major driving force for CqPP2Cs expansion and all duplicated CqPP2Cs evolved from purifying selection. The expression of CqPP2Cs in various tissues under different abiotic stresses was analyzed using RNA-seq data. The results revealed that CqPP2C genes were involved in regulating development and stress responses of quinoa. Real-time quantitative reverse transcription PCR (qRT-PCR) analysis of six CqPP2C genes in subfamily A revealed that they were up-regulated or down-regulated under salt and drought treatments. Furthermore, the results of yeast two-hybrid assays revealed that subfamily A CqPP2Cs interacted not only with subclass III CqSnRK2s, but also with subclass II CqSnRK2s. Subfamily A CqPP2Cs could interact with CqSnRK2s in different combinations and intensities to respond to various biological processes and stresses. Overall, our results will be useful for understanding the functions of CqPP2C in regulating ABA signals and responding to abiotic stress.

The worldwide pandemic of coronavirus disease 2019 (COVID-19) has become an unprecedented challenge to global public health. With the intensification of the COVID-19 epidemic, the development of vaccines and therapeutic drugs against the etiological agent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are also widespread. To prove the effectiveness and safety of these preventive vaccines and therapeutic drugs, available animal models that faithfully recapitulate clinical hallmarks of COVID-19 are urgently needed. Currently, animal models including mice, golden hamsters, ferrets, nonhuman primates and other susceptible animals have been involved in the study of COVID-19. 92 vaccine candidates have entered clinical trials after the primary evaluation in animal models, of which inactivated vaccines, subunit vaccines, virus-vectored vaccines and mRNA vaccines are promising vaccine candidates. In this review, we summarize the landscape of animal models and advanced vaccines with efficacy range from about 50% to more than 95%. In addition, we point out future directions for animal models and vaccine development, aiming at providing valuable information and accelerating the breakthroughs confronting SARS-CoV-2.

In this paper, the catalytic combustion of DMDS (dimethyl disulfide, CH₃SSCH₃) over bimetallic supported catalysts were investigated. It was confirmed that Cu/γ-Al₂O₃-CeO₂ showed best catalytic performance among the five single-metal catalysts. Furthermore, six different metals were separately added into Cu/γ-Al₂O₃-CeO₂ to investigate the promoting effect. The experiments revealed Pt as the most effective promoter and the the best catalytic performance was achieved as the adding amount of 0.3 wt%. The characterization results indicated that high activity and resistance to sulfur poisoning of Cu-Pt/γ-Al₂O₃-CeO₂ could be attributed to the synergistic effect between Cu and Pt.

This paper considers the detection of fluctuating target in heavy-tailed clutter through the use of dynamic programming based on track-before-detect (DP-TBD) in radar systems. The clutter is modeled in terms of K-distribution, which can be widely used to describe non-Gaussian clutter received from high-resolution radars and radars working at small grazing angle. Swerling type 1 is considered to describe the target fluctuation between scans. Conventional TBD techniques suffer from significant performance loss in heavy-tailed environments due to the more frequent occurrences of target-like outliers. In this paper, we resort to DP-TBD algorithm based on prior information, which can enhance the detection performance by using the environment and target fluctuating information during the integration process of TBD. Under non-Gaussian background, the expressions of the likelihood ratio merit function for Swerling type 1 target are derived first. However, the closed analytical form of the merit function is difficult to be obtained. In order to reduce the complexity of evaluating the merit function and the computational load, an efficient approximation method as well as a two-stage detection approach is proposed and used in the integration process. Finally, several numerical simulations of the new strategy and the comparisons are presented to verify that the proposed algorithm can improve the detection performance, especially for fluctuating target in heavy-tailed clutter.

The spillover of a virus from an animal reservoir to humans requires both molecular and ecological risk factors to align. While extensive research both before and after the emergence of SARS-CoV-2 in 2019 implicates horseshoe bats as the significant animal reservoir for the new human coronavirus, it remains unclear why it emerged at this time. One massive disruption to animal-human contacts in 2019 is linked to the on-going African swine fever virus (ASFV) pandemic. Pork is the major meat source in the Chinese diet. We hypothesize that the dramatic shortage of pork following large-scale culling and restrictions of pig movement (resulting in marked price increases) led to alternative sources of meat and unusual animal and meat movements nationwide, e.g., involving wildlife, and thus greatly increased opportunities for human-sarbecovirus contacts. Pork prices were particularly high in southern provinces (Guangdong, Guangxi, Fujian, Jiangxi, Hunan, and Hubei), where wildlife is farmed and more frequently consumed. Major wildlife farming provinces are spread from Northern to Southern China, which overlaps with horseshoe bat host ranges, potential hosts of the proximal SARS-CoV-2 ancestor, and wildlife sourcing provinces of Wuhan Huanan market and possibly other markets. Trading of SARS-CoV-2 susceptible wildlife in these markets, such as minks, raccoon dogs, foxes and palm civets in Wuhan markets, could have increased the risk of SARS-CoV-2 from an intermediary host. Moreover, large quantities of animals raised for fur could have entered the human food chain undetected and significantly increased risks of animal-human contact. Performing retrospective testing of stored susceptible animals and their meat sold before December 2019 may be helpful in the next stage of tracing the animal origin of SARS-CoV-2 as spillover events are more likely to have taken place in 2019 when China was experiencing the worst effects of the ASFV pandemic.

Graph theory plays a crucial role in modeling and designing of chemical structure or chemical network. Chemical Graph theory helps to understand the molecular structure of molecular graph. The molecular graph consists of atoms as vertices and bonds as edges. Topological indices capture symmetry of molecular structures and give it a mathematical language to predict properties such as boiling points, viscosity, the radius of gyrations etc. In this article, we study the chemical graph of carbon Crystal structure of graphite and cubic carbon and compute several degree-based topological indices. Firstly we compute M-Polynomials of these structures and then from these M-polynomials we recover nine degree-based topological indices.

Gliomas, the most prevalent and lethal form of brain cancer, are known to exhibit metabolic alterations that facilitate tumor growth, invasion, and resistance to therapies. Peroxisomes, essential organelles responsible for fatty acid oxidation and reactive oxygen species (ROS) homeostasis, rely on the receptor PEX5 for the import of metabolic enzymes into their matrix. However, the prognostic significance of PEX5 for glioma patients remains unclear. We developed a robust prognosis model based on PEX5-dependent signature. This signature not only serves as a robust prognosis model capable of accurately predicting outcomes for glioma patients but also effectively distinguishes several clinicopathological features, including the grade, isocitrate dehydrogenase (IDH) mutation, and 1p19q codeletion status. Furthermore, we developed a nomogram that integrates the prognostic model with other clinicopathological factors, demonstrating highly accurate performance in estimating patient survival. Patients classified into the high-risk group based on our prognostic model exhibit an immunosuppressive microenvironment. Finally, we validated that the peroxisomal localization of the signature genes depends on PEX5 and demonstrated that PEX5 is required for cell growth, migration and invasion of glioma cells. These findings identify the PEX5-dependent signature as a promising prognostic tool for gliomas.

In this paper, a voice coil motor (VCM) actuated fast tool servo (FTS) system is developed for diamond turning. To guide motions of the VCM actuator, a crossed double parallelogram flexure mechanism is selected featuring totally symmetric structure with high lateral stiffness. To facilitate the determination of the multi-physical parameters, analytical models of both electromagnetic and mechanical systems are developed. The designed FTS with balanced stroke and natural frequency is then verified through the finite element analysis. Finally, the prototype of the VCM actuated FTS is fabricated and experimentally demonstrated to have a stroke of ±59.02 μm and a first natural frequency of 253 Hz. By constructing a closed-loop control using PID controller with the internal-model based resonant controller, the error for tracking a harmonic trajectory with ±10 μm amplitude and 120 Hz frequency is obtained to be ±0.2 μm, demonstrating the capability of the FTS for high accuracy trajectory tracking.

In a global context, the story of the Jesuit compound in Shanghai, since its establishment by French Jesuits in 1847, reflected not only conflicts between rival powers in Europe but also the fight for their interests in the Eastern world. The Pope, who was stuck without legal status in the Vatican after 1861, was also seeking the chance to save the authority of the Church in the face of questions regarding the extent of his temporal power and the status of Rome in the context of Italian unification. As in the Reformation, a break-through in the east seemed to offer a solution for losses in Europe. However, the Jesuits to the East in the late 19th century were not only troops working and fighting on behalf of the Pope; their identities under the French Protectorate added complexity to an already complicated story involving not just the Church, but the course of world history.The female Catholic orders at the east bank of Zi-ka-wei compound became a unique window to approach the complexity.

In order to formulate a reasonable water input model for cotton fields in southern Xinjiang, scientific and rational fertilization, reduce soil carbon leaching, and improve soil carbon sequestration capacity, the undisturbed soil column leaching test was used to simulate the current field management method in the study area. Two methods of drip irrigation and flood irrigation were set up, and three irrigation and three nitrogen fertilizer levels were used to carry out the undisturbed soil column leaching test. The results showed that the amount and mode of water and nitrogen input affected the distribution and leaching loss of organic carbon and inorganic carbon in soil. When the nitrogen application rate increased from 270 kg·hm-2 to 450 kg·hm-2, the leaching loss of soluble organic carbon and soluble inorganic carbon increased significantly. When the water input increased from 6000 m3·hm-2 to 9000 m3·hm-2, the leaching loss of DOC and DIC increased significantly. The carbon leaching loss under drip irrigation was higher than that under flood irrigation. The leaching rates of DOC and DIC were the fastest under the conditions of high water ( 9000 m3·hm-2 ) and high fertilizer ( 450 kg·hm-2 ). It shows that water and nitrogen input and irrigation methods are important factors affecting soil carbon leaching. In the case of excessive water input, long-term high-frequency irrigation is the main factor affecting carbon leaching.

In the past decades, the world is actively working towards the global goal of net-zero emission. To decrease emissions, there is a notable trend of electrification in transportation, which is a transition from traditional fuel-based systems to electrical power systems onboard different transportation platforms. For this transition, it is important to study the electrical structure, specifically the onboard microgrid, powered by various energy sources. In this paper, traditional energy management strategies for onboard microgrid systems are discussed, which usually require complicated optimization algorithms and high computation capabilities. Driven by the recent advancements in information technologies, artificial intelligence and digital twin have gained much interest within the transportation sector. These technologies can effectively utilize data to achieve intelligent decision-making, optimize resource utilization, and save energy consumption. This paper presents an overview of the usage of these emerging information technologies in energy management strategies, providing an overall summary and classification of the practical applications. In addition, after examining the potential challenges associated with artificial intelligence and digital twin, this paper also discusses future trends in this field.

This study chose the indoor soil column test as the main method and the field test as the validation test to investigate the effects of various straw mulching techniques (surface, deep and straw mulching + deep burial) on evaporation and salt dynamics in saline soils. The results showed that straw mulching treatment could effectively reduce soil water evaporation, promote desalination in the stage of leaching infiltration and alleviate salt return in the stage of water evaporation, and the effect of straw mulching + deep burial treatment was better than that of single-layer straw mulching treatment. The indoor soil column test showed that S2D1 treatment (a 2:1 ratio of soil surface cover to the amount of straw buried 40cm below the soil surface) had the best effect on the suppression of soil moisture evaporation, and the cumulative evaporation of soil moisture was reduced by 65.85% compared with that of the CK, and the rate of salinity return in the evaporation stage was effectively reduced by 92.04% compared with that of the CK. In addition, there is a significant positive correlation between cumulative evaporation of soil moisture and cumulative soil salinity, which implies that cumulative soil salinity increases with cu-mulative evaporation of soil moisture. The results of the field experiment were consistent with the soil column test, and the S2D1 treatment was able to maintain high soil moisture content in all soil layers in all periods of the experiment and kept soil salinity in the 0-40 cm soil layer at a low level. However, in the 40-80 cm soil layer, the soil salinity suppression effect of DB treatment (straw buried at 40 cm below soil surface) was the best. So in summary, the S2D1 treatment had the best salinity and evapo-transpiration suppression effect in saline soils. This study is of great significance for the resource uti-lization of straw waste, improvement of water utilization and efficiency, and soil salinization manage-ment.

The globose scale (GS) (Sphaerolecanium prunastri Boyer de Fonscolombe) is a sucking insect that feeds on saps of wild apricot tree (Prunus armeniaca L.) in the Xinjiang Uygur Autonomous Region of northwestern China. It feeds on branches of wild apricot leading to poor growth, leaf yellowing and leaf drop, and sometimes mortality. Since the initial infestation in 2018, all the main valleys of wild apricot trees have been affected, but there is little research on the host’s physiological response to GS infestation. We measured the differences in growth between infested and non-infested wild apricots. The results showed that the diameter of shoot branches, the fresh weight, dry weight, length, width, area, and chlorophyll content of leaves, and the longitudinal diameter of fruit, were all significantly less for infested wild apricot trees than for un-infested wild apricot. The branch length of shoots, cross diameter, and weight of fruit also decreased, although the differences were not significant. Overall, GS infestation significantly reduced the growth of wild apricot trees, and may accelerate the damage by GS to wild apricot over time.

Microbial community succession in raw milk determines its quality and storage period. In this study, carbon dioxide (CO2) at 2000 ppm was used to treat raw milk to investigate the mechanism of extending the shelf life of raw milk by CO2 treatment from the viewpoint of microbial colonies and metabolites. The results showed that the shelf life of CO2-treated raw milk was extended to 16 days at 4 ℃, while that of the control raw milk was only 6 days. Microbiomics analysis identified 221 Amplicon Sequence Variants (ASVs) in raw milk, and the alpha diversity of microbial communities increased (P < 0.05) with the extension of storage time. Among them, Pseudomonas, Actinobacteria and Serratia were the major microbial genus responsible for the deterioration of raw milk, with a percentage of 85.7%. A combined metagenomics and metabolomics analysis revealed that microorganisms altered the levels of metabolites, such as pyruvic acid, glutamic acid, 5'- cmp, arginine, 2-propenoic acid, and phenylalanine in the raw milk through metabolic activities, such as ABC transporters, pyrimidine metabolism, arginine and proline metabolism and phenylalanine metabolism, and reduced the shelf life of the raw milk. CO2 treatment prolonged the shelf life of the raw milk by inhibiting the abundance of Gram-negative aerobic bacteria, such as Acinetobacter guillouiae, Pseudomonas fluorescens, Serratia liquefaciens and Pseudomonas simiae.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. In this report, we study the silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q]. We compute several Zagreb polynomials and Redefined Zagreb indices of these silicon-carbons.

A series of novel sulfonylurea benzothiazoline were designed by splicing active groups and bioisosterism. A solvent-free synthetic route was developed for the sulfonylurea benzothiazoline derivatives via the cyclization and carbamylation. All the compounds were characterized by IR, 1H-NMR, 13C-NMR, HRMS. The biological activity tests indicated the compounds could protect maize against the injury caused by chlorsulfuron to some extent. The molecular docking result showed that the new compound competed with chlorosulfuron to bind with the herbicide target enzyme active site to attain detoxification.

With the proliferating of video surveillance system deployment and related applications, real-time video analysis is very critical to achieve intelligent monitoring, autonomous driving, etc. It is non-trivial to achieve high accuracy and low latency video stream analysis through the traditional cloud computing. In this paper, we propose a non-orthogonal multiple access (NOMA) based edge real-time video analysis framework with one edge server (ES) and multiple user equipments (UEs). A cost minimization problem composed of delay, energy and accuracy is formulated to improve the QoE of UEs. In order to efficiently solve this problem, we propose the joint video frame resolution scaling, task offloading, and resource allocation algorithm based on the Deep Q-Learning Network (JVFRS-TO-RA-DQN), which effectively overcomes the sparsity of the single-layer reward function and accelerates the training convergence speed. JVFRS-TO-RA-DQN consists of two DQN networks to reduce the curse of dimension, which respectively select the offloading and resource allocation action, the resolution scaling action. Experimental results show that JVFRS-TO-RA-DQN can effectively reduce the cost of transmission and computation, and have better performance in convergence compared to other baseline.

With the rapid development of satellite remote sensing technology, the volume of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming hard to efficiently and intelligently retrieve the change information that users need from massive image databases. In this paper, content-based image retrieval is successfully applied to change detection and a content-based remote sensing image change information retrieval model is introduced. First, the construction of a new model framework for change information retrieval in a remote sensing database is described. Then, as the target content cannot be expressed by one kind of feature alone, a multiple-feature integrated retrieval model is proposed. Thirdly, an experimental prototype system that was set up to demonstrate the validity and practicability of the model is described. The proposed model is a new method of acquiring change detection information from remote sensing imagery and so can reduce the need for image pre-processing, deal with problems related toseasonal changes as well as other problems encountered in the field of change detection. Meanwhile, the new model has important implications for improving remote sensing image management and autonomous information retrieval.

In the seasonally frozen regions, during the grouting of prestressed bridge ducts in low-temperature environments, incompletely cured grout materials undergo volumetric changes due to the freeze-thaw cycling, resulting in structural cracks along the prestressing ducts of the bridge, thereby diminishing the bridge's operational lifespan. To investigate the frost heaving characteristics of grout materials under freeze-thaw cycles and propose potential enhancements, this study was devised to conduct frost heaving stress tests on grout materials. Through this research, we gained insights into how various additives affect the frost heaving stress characteristics of grout materials under freeze-thaw cycles. Incorporating analyses of free water content, setting time, compressive strength, as well as macroscopic examinations such as XRD and SEM, this study delves into the mechanisms for enhancing frost heaving characteristics of grout materials. Furthermore, it proposes a research approach that utilizes multiple admixtures to improve the frost heaving properties of grout materials. Through frost heaving stress tests and other macroscopic experiments, the study investigates the influence of these combined admixtures on frost heaving stress in grout materials and elucidates the underlying improvement mechanisms. The results indicate that reducing the water-cement ratio, incorporating calcium formate, sulfoaluminate cement, air-entraining agents, and carbamide all have a positive impact on mitigating frost heaving stress in grout materials. However, the improvement mechanisms differ, and employing a single measure alone is insufficient to effectively reduce frost heaving stress while meeting performance criteria such as compressive strength, setting time, and flowability. Free water content emerges as a crucial indicator determining the magnitude of frost heaving stress in grout materials, with 11.5% of free water content representing the critical threshold for frost heaving in grout materials. Utilizing composite admixtures can simultaneously decrease free water content, lower the freezing point of free water, and alleviate frost heaving deformation, resulting in more efficient reduction of frost heaving stress. When the admixture content reaches 9.9%, frost heaving stress is eliminated, and the comprehensive performance parameters including compressive strength, setting time, and flowability meet the specified requirements.

Background: After allogeneic hematopoietic stem cell transplantation (allo-HSCT), acute leukemia relapse is common, and asymmetric bone marrow recurrence hasn’t been reported. Because the anatomical distribution of acute leukemia clones in the bone marrow after allo-HSCT is presumed to be diffuse, bone marrow aspirations are performed in single site. Case presentation: We identified two acute leukemia patients, whose leukemic burden in bilateral bone marrow specimens differed significantly. The first case was a 20-year-old man who was diagnosed with acute myelomonocytic leukemia and received haploidentical allo-HSCT. He had been in complete remission for two years and off immunosuppressive medications for a year, with normal peripheral blood count. Routine bone marrow biopsy of his left posterior iliac bone marrow showed 52% leukemia blasts, while the right side had 0% blasts ten days later. Due to the discordant results, the patient refused further intervention and died of high leukocyte syndrome four months later. The second case was a 23-year-old woman who was diagnosed with acute B lymphoblastic leukemia and received HLA-identical sibling allo-HSCT. Although 62% of blasts were found in her left iliac marrow on day +122, 0 % of blasts were found on a sample obtained from the right iliac crest on day +128. Whole-body 18F-FDG PET/CT scans confirmed that the leukemic infiltration in her bone marrow was asymmetric. Considering the higher leukemic burden on the left, we chose the left posterior iliac crest aspiration for further response evaluation. After chemotherapy combined with donor lymphocyte infusion, she achieved transient hematologic complete remission. She died of septic shock with heart failure at +258 days after allo-HSCT before infusion of anti-CD19 donor chimeric antigen receptor T cells. Conclusions: To our knowledge, these are the first case reports of asymmetric bone marrow infiltration of blasts in acute leukemia patients after allo-HSCT. Bilateral posterior iliac crest aspirations or 18F-FDG-PET/CT scans may help distinguish such distribution. If discordant bone marrow specimens are observed, physicians should restrict future bone marrow studies to the more involved side.

With the rapid development of industry, Cr has become one of the major heavy metal pollutants in soil, which has caused serious effects on the soil's ecological environment. However, the effects of Cr stress on bacterial communities in plant rhizosphere soils remain unclear. In this study, I. tectorum was selected as the research object, and 16S rRNA high-throughput sequencing technology was used to analyze the effects of Cr stress on the structure and diversity of the bacterial community in the rhizosphere soil of I. tectorum. The results showed that I. tectorum had strong tolerance and enrichment to Cr. However, under Cr stress, the diversity and abundance index of rhizosphere bacteria decreased by 8.5% and 6.8% on average, and the Sobs index decreased by 7.6%. Moreover, the bacterial community changed by 20.1% due to the addition of Cr, further leading to a 15.9% decrease in the common species of the bacterial community, among which Proteobacteria, Actinobacteria, Chloroflexi and Acidobacteriota accounted for more than 74.8% of the total sequence. According to the symbiosis network diagram, it was found that under a two-cultivated pattern, the synergizing effect between dominant bacteria was significantly enhanced, and the soil microenvironment was improved. Redundancy analysis showed that C, N, and P nutrient elements and Cr contents in uncontaminated and contaminated soils were the primary driving factors for the succession of I. tectorum rhizosphere bacterial community, and the response was stronger after Cr(Ⅵ) was added. In conclusion, the results of this study will provide insights into the response of rhizosphere bacterial communities to heavy metal Cr and the interactions between wetland plants and rhizosphere bacteria in wetland phytoremediation.Keywords: Cr stress; rhizosphere bacterial community; Iris tectorum; 16S rRNA sequencing technology; Phytoremediation

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

The total ionizing dose (TID) effect significantly impacts the electrical parameters of fully depleted silicon on insulator (FDSOI) devices and even invalidates the on-off function of devices. At present, most of the irradiation research on the circuit level is focused on the single event effect, and the research on the total ionizing dose effect is very little. Therefore, this study mainly analyzes the influence of TID effects on a CMOS inverter circuit based on 22 nm FDSOI transistors. First, we constructed and calibrated an N-type FDSOI metal-oxide semiconductor (NMOS) structure and P-type FDSOI metal-oxide semiconductor (PMOS) structure. The transfer characteristics and trapped charge distribution of these devices were studied under different irradiation doses. Next, we studied the TID effect on an inverter circuit composed of these two MOS transistors. The simulation results show that when the radiation dose is 400 krad (Si), the logic threshold drift of the inverter is approximately 0.052 V. These results help further investigate the impact on integrated circuits in the irradiation environment.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

Background: Coronavirus Disease 2019 (COVID-19) has been demonstrated to be the cause of pneumonia. Nevertheless, it has not been reported as the cause of acute myocarditis or fulminant myocarditis. Case presentation: A 63-year-old male was admitted with pneumonia and cardiac symptoms. He was genetically confirmed as having COVID-19 according to sputum testing on the day of admission. He also had elevated troponin I (Trop I) level (up to 11.37 g/L) and diffuse myocardial dyskinesia along with a decreased left ventricular ejection fraction (LVEF) on echocardiography. The highest level of interleukin-6 was 272.40 pg/ml. Bedside chest radiographs showed typical ground-glass changes indicative of viral pneumonia. Laboratory test results for viruses that cause myocarditis were all negative. The patient conformed to the diagnostic criteria of the Chinese expert consensus statement for fulminant myocarditis. After receiving antiviral therapy and mechanical life support, Trop I was reduced to 0.10 g/L, and interleukin-6 was reduced to 7.63 pg/ml. Moreover, the LVEF of the patient gradually recovered to 68%. The patient died of aggravation of secondary infection on the 33^rd day of hospitalization. Conclusion: COVID-19 patients may develop severe cardiac complications such as myocarditis and heart failure. This is the first report of COVID-19 complicated with fulminant myocarditis. The mechanism of cardiac pathology caused by COVID-19 needs further study.

Grain shape and chalkiness are important appearance quality traits of rice, which also affect the yield and milling quality. In this study, 190 F2 families derived from the cross between Hua 5178S and Hua 611 were sequenced to construct a genetic linkage map. Combined with F2 and F2:3 generations grain shape and chalkiness phenotype, a total of 15 QTL were detected. There are 8 grain shape QTL distributed on chromosomes 2, 5, 6, 8, and 10; 7 chalkiness QTL distributed on chromosomes 2, 3, and 6. A QTL cluster affecting multiple chalkiness traits was found on chromosome 6, qWBR6.1, qWCR6 and qCR6 were selected for genetic effect verification. It was found that qWBR6.1, qWCR6 and qCR6 explained 13% and 24%, and 29% of the phenotypic variations respectively, and qWCR6 and qCR6 were co-mapped. This study laid a foundation for further cloning of rice appearance quality genes.

With the growth of air traffic demand in busy airspace, there is an urgent need for airspace sectorization to increase air traffic throughput and ease the pressure on controllers. The purpose of this paper is to develop a method framework that can perform airspace sectorization automatically, reasonably, which can be used as an advisory tool for controllers as an automatic system, especially for eliminating irregular sector shapes generated by simulated annealing algorithm (SAA) based on region growth method. Two graph cutting method, dynamic Monte Carlo method by changing location of flexible vertices (MC-CLFV) and Monte Carlo method by radius changing (MC-RC) were developed to eliminating irregular sector shapes generated by SAA in post-processing. The experimental results show that the proposed method framework of AS can automatically and reasonably generate sector design schemes that meet the design criteria. Our methodology framework and software can provide assistant design and analysis tools for airspace planners to design airspace, improve the reliability and efficiency of airspace design, and reduce the burden of airspace planners. In addition, this lays the foundation for reconstructing airspace with more intelligent method.

Production of silkworm silk is the most economically important traits in the silk industry. Silk protein synthesis is regulated by juvenile hormone (JH) and 20-Hydroxyecdysone (20E). Therefore, it is important to understand the genetic regulation of silk production is thus a priority. JH binding protein (JHBP) transports JH from the hemolymph to target organs and cells and protects JH. In a previous study, we identified 41 genes containing a JHBP domain in the Bombyx mori genome. Only one JHBP gene, that is, BmJHBPd2, is highly expressed in the posterior silk gland (PSG) and its function remains unknown. In the present study, we investigated the expression levels of BmJHBPd2 and the major silk protein genes in the high silk-producing practical strain 872 (S872) and the low silk-producing local strain Dazao. Our results have shown that BmJHBPd2 was more highly expressed in S872, than in the Dazao strain, which is consistent with the expression pattern of fibroin genes. A subcellular localization assay indicated that BmJHBPd2 is located in the cytoplasm. In vitro hormone induction experiments showed that BmJHBPd2 was upregulated by treatment with juvenile hormone analogue (JHA). BmKr-h1 upregulation was significantly inhibited by overexpression of BmJHBPd2 at the cell level when induced by JHA. However, overexpression of BmJHBPd2 in the posterior silk gland by transgenic methods led to the inhibition of the expression of the silk fibroin gene, resulting in a reduction in silk yield. Further investigation has shown that in the BmJHBPd2OE individual, the key transcription factor Krüppel homolog 1 (Kr-h1) of the JH signaling pathway was inhibited, and 20E signaling pathway genes, such as broad complex (Brc), E74A, and ultraspiracle protein(USP), were upregulated. Our results have indicated that BmJHBPd2 plays an important role in the JH signaling pathway and was important for silk protein synthesis. Furthermore, our findings have helped to elucidate the mechanisms by which JH regulates silk protein synthesis.

To the best of the author’s knowledge, studies of mature plasmacytoid dendritic cell proliferation associated with T lymphoblastic lymphoma were extremely rare in the literature. Here, we report a patient who underwent both mature plasmacytoid dendritic cell proliferation and T lymphoblastic lymphoma. With the findings of lymph node biopsy taken from the right cervical and inguinal regions, we identified eye-catching mature plasmacytoid dendritic cells that were considered to be responsible for this lesion at the beginning, until the immunostaining of Ki67 and TDT showed a small group of positive cells hiding in these plasmacytoid dendritic cells. Bone marrow biopsy was also performed in this patient. Microscopically, the hematopoietic tissue was almost completely replaced by lymphoblastoid cells with condensed chromatin, inconspicuous nucleoli and scanty cytoplasm, which were basically the same as those seen in the lymph nodes in morphology. However, there was no sign of plasmacytoid dendritic cells or Langerhans cells in the bone marrow biopsy. With the help of bone marrow biopsy, our final diagnosis of the lymph node was T lymphoblastic lymphoma coexisting with mature plasmacytoid dendritic cell proliferation . Although accumulations of plasmacytoid dendritic cells may occur in some infections or reactive lymphadenopathy, the presence of extensive nodules or infiltration of plasmacytoid dendritic cells strongly reminds the pathologist to carefully evaluate the bone marrow or peripheral blood status of the patient to exclude a hidden myeloid or other neoplasm.

A series of penta-1,4-dien-3-one containing a H-phosphonate scaffold were designed and synthesized. The structures of all title compounds were determined by 1H-NMR, 13C-NMR, 31P-NMR, and HRMS. Bioassay results showed that several of the title compounds exhibited remarkable antibacterial and antiviral activities. Among these, compounds 3c and 3o exhibited substantial antibacterial activities against Xanthomonas oryzae pv. Oryzae (Xoo) and Xanthomonas axonopodis pv. citri (Xac). In addition, compounds 3c, 3f, and 3r showed remarkable curative activities against tobacco mosaic virus (TMV), with 50% effective concentration (EC50) values of 290.0, 234.0, and 373.6 μg/mL, respectively. These were superior to that of ningnanmycin (386.2 μg/mL). Compound 3r exhibited comparative protective activity against TMV, with an EC50 value of 291.1 μg/mL, which was better than that of ningnanmycin (297.1 μg/mL). Notably, the solubility of all title compounds improved relative to the lead compound curcumin. These results suggest that penta-1,4-dien-3-one containing a H-phosphonate scaffold may be considered as an activator for antibacterial and antiviral agents.

In this paper, a method is developed for presenting a novel virtual torque sensor based on precise model and position measurements avoids the need of traditional strain gauges and amplifiers. More specifically, the harmonic drive compliance model and the Gaussian process regression (GPR) technique are used together to achieve virtual torque sensor measurement. While the harmonic drive compliance model provides the analytic part, the Gaussian process regression method is used to reconstruct the unmolded part based on motor-side and link-side joint angles as well as motor current. After an automatic offline calibration, the method allows for a lean online implementation. The virtual torque sensor measurement is compared with measurements of a commercial torque sensor, and the results have attested the effectiveness of the proposed method.

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

Maize, a crop of international relevance, frequently undergoes xylem embolism due to water shortage, negatively impacting growth, yield, and quality. Consequently, a refined comprehension of xylem embolism is vital for enhancing maize cultivation. Notwithstanding extensive research and the generation of analytical models for embolism mechanisms, prevalent models often disregard crop-specific hydraulic processes and the formation of embolisms via air bubbles in the xylem conduit. In this research, we present an inventive model applying pipe cavitation parameters to discern water potential and bubble formation in maize leaf xylem. The model integrates pivotal physiological traits of maize—leaf count, leaf vein count, and average leaf radius—demonstrating robust correlations. Furthermore, we constructed a percentage conductivity loss (PLC) curve based on pre-dawn leaf water potential and compared it with our model, offering interval data to observe embolisation events triggered by air bubbles. Utilizing experimental data, our novel cavitation-parameters based model effectively corresponds with observed bubble phenomena and appropriately characterizes water transport in plant xylem conduits. This method enabled us to observe the transition from bubble occurrence to cavitation embolism microscopically, which aligned with the embolism intervals provided by the model. This procedure reveals potential trends in bubble-induced embolism and deepens our knowledge of microscopic plant hydraulics and crop embolism. This work establishes a basis for understanding the generation of bubble embolisms in maize, assists in evaluating maize plant water status for efficient water supply management throughout the growth cycle, and contributes towards potential water management strategies for maize.

Two algorithms of data processing are proposed to shorten the unmeasurable dead-zone close to the zero-position of measurement, i.e., the minimum working distance of a dispersive interferometer using optical frequency comb, which is a critical issue in millimeter-order short-range absolute distance measurement. After demonstrating the limitation of the conventional data processing algorithm, the principles of the proposed algorithms, namely the spectral fringe algorithm, and the combined algorithm that combines the spectral fringe algorithm with the excess fraction method, are presented, together with simulation results for demonstrating the possibility of the proposed algorithms for shortening the dead-zone with a high accuracy. An experimental setup of dispersive interferometer is also constructed for implementing the proposed data processing algorithms over spectral interference signals. Experimental results demonstrate that the dead-zone by the proposed algorithms can be as small as half of that by the conventional algorithm while the measurement accuracy can be further improved with the combined algorithm.

The color changes corresponding to chromophore structures in lignin caused by exposure of Eucalyptus（Eucalyptus grandis and E. urophylla）to heat were investigated. Eucalyptus wood samples were heated in saturated steam atmospheres for 10 h at 110℃, 130℃, and 150℃. The lignin was isolated before and after heat treatment. The physicochemical properties of the lignin and changes in chromophore structures during heat treatment was evaluated through wet chemical analysis, FTIR, UV-Vis, GPC, XPSand 13C-NMR. The color of the wood became darker and redder with the increase in pressure and temperature. Depolymerization and dehydration reactions occurred via demethoxylation with heat treatment in saturated steam at 110℃ or 130℃. Lignin condensed to form insoluble compounds after heat treatment in saturated steam at 150℃. G units increased and S units decreased through demethylation during heat treatment, as revealed by FTIR and 13C-NMR analysis.

Comparison with conventional reservoirs, the prediction of pressure in ultra-deep tight sandstone formations is difficult. The prediction of seismic pressure is more challenging than well logging pressure prediction. The main methods for seismic pressure prediction include equivalent depth method, Eaton method, Fillippone formula, and its modified versions. Among them, the Eaton method is widely used and has good effectiveness. However, this method relies on difficult-to-obtain normal compaction trend line, which leads to low prediction accuracy in space. To address this issue, a method combining the Eaton method and Collocated cokriging is proposed. The Eaton formula is used to predict formation pressure at the well, with compressional wave velocity as the covariate for predicting the main variable, formation pressure. By simulating the shear wave velocity based on seismic compressional wave velocity, the influence of various parameters on the prediction results is analyzed, and the accuracy of this method is verified by comparing it with other methods. The proposed method is then applied to predict formation pressure in the ultra-deep formations of the Junggar Basin. The simulation results show that the Collocated cokriging method achieves higher planar accuracy and better matches the experimental expectations in terms of prediction results. The application results also demonstrate the scientific effectiveness of the combined method, which has achieved good results in practical production applications.

Neonicotinoids (NEOs) have become the most widely used insecticides in the world since the mid-1990s. According to Chinese dietary habits, rice and water are usually heated before being consumed, but the information about the alteration through the heat treatment process is very limited. In this study, the parents of NEOs (p-NEOs) accounted for >99% of the total NEOs mass (∑NEOs) in both uncooked (median: 66.8 ng/g) and cooked (median: 41.4 ng/g) rice samples from Guangdong Province, China, while the metabolites of NEOs (m-NEOs) involved in this study accounted for less than 1%. We aimed to reveal the concentration changes of NEOs through heat treatment process, thus, several groups of rice and water samples from Guangdong were cooked and boiled, respectively. Significant (p < 0.05) reductions in acetamiprid, imidacloprid (IMI), thiacloprid, and thiamethoxam (THM) have been observed after the heat treatment of the rice samples. In water samples, the concentrations of THM and dinotefuran decreased significantly (p < 0.05) after the heat treatment. These results indicate the degradation of p-NEOs and m-NEOs during the heat treatment process. However, the concentrations of IMI increased significantly in tap water samples (p < 0.05) after heat treatment process, which might be caused by the potential IMI precursors in those industrial pesticide products. The concentrations of NEOs in rice and water can be shifted by the heat treatment process, so this process should be considered in relevant human exposure studies.

The detrital compositions in sandstone are important recorders of sedimentary provenance and transport, both of which have significant implications for the lithology, age and tectonic evolution of provenance. Through detailed identification and analysis, a high content of volcanogenic compositions (27.6%) was discovered in Shanxi formation of Daniudi Gas Field, Ordos Basin, which is much higher than that of the previous study. The volcanogenic compositions include volcanogenic quartz, lava fragments (dominated by various kinds of rhyolite fragments), tuff fragments, and tuffaceous matrix. In addition, at least 2 volcanic ash layers were discovered. Although the metamorphic rocks of the Precambrian succession in the ancient land of Yin Mountain are usually considered the primary source of the Shanxi formation, it is most likely that the volcanogenic compositions were derived from intermediate-acidic volcanic materials that accumulated in the Daqingshan area during the Late Carboniferous to Early Permian. Those volcanogenic compositions are mainly transported by flowing water rather than by air from provenance to basin. And the accumulation of volcanic materials in the Daqingshan area was controlled by volcanic eruptions occurring solely in this area, rather than by the Inner Mongolia Orogenic Belt. Those volcanic eruptions related to the southward subduction of the Paleo-Asian Ocean Plate beneath the northern margin of the North China Plate in Late Carboniferous to Early Permian. The active continental margin related to the subduction of the Paleo-Asian Ocean Plate lasted until at least the Early Permian, and the closure of the Paleo-Asian Ocean must have occurred later than the Early Permian.

Polymer adhesives have emerged as a promising dielectric passivation layer in hybrid bonding for 3D integration while they raise misalignment problems during curing. In this work, the synergistic effect of oxygen plasma surface activation and wetting is utilized to achieve bonding between completed cured polyimides. The optimized process achieves a void-less bonding with a maximum shear strength of 35.3 MPa at a low temperature of 250 °C in merely 2 min, significantly shortening the bonding period and decreasing thermal stress. It is found that the plasma activation generated hydrophilic groups on the polyimide surface, and the wetting process further introduced more -OH groups and water molecular on the activated polyimide surface. The synergistic process of plasma activation and wetting facilitate bridging polyimide interfaces to achieve bonding, providing an alternative path for adhesive bonding in 3D integration.

It is very difficult to accurately divide farmland and woodland in Gaofen 2 (GF-2) remote sensing image, because their single plant coverage is very small, and their spectra are very similar. The ratio of spatial resolution and one plant’s coverage area must be fully taken into account when designing the Convolutional Neural Network structure for extracting them from GF-2 image. We establish a Convolutional Encode Neural Networks model (CENN), The first layer has two sets of convolution kernels to learn the characteristics of farmland and woodland respectively, while the second layer is the encoder to encode the characteristics by transfer function, which can map the results to the corresponding category number. In the training stage, samples of farmland, woodland, and other categories are categorically used to train CENN, as soon as training is accomplished, CENN would acquire enough ability to accurately extract farmland and woodland from remote sensing images. The final extraction result is obtained by implementing per-pixel segmentation of images used to train the CENN. CENN is compared and analyzed with others such as Deep Belief Network (DBN), Full Convolutional Network (FCN), Deeplab Model. The results of experiments show that CENN can more accurately mine the characteristics of farmland and woodland, and it achieves its goal of extracting farmland and woodland with high precision from GF-2 images.

The accompanying mechanical behavior during the flow of ore-rock dispersion is an important factor leading to the instability and failure of the orepass in the ore storage section. It is of great significance to accurately understand the instability characteristics of the well wall in the ore section, during the ore drawing process by understanding the flow characteristics and internal mechanical transfer mechanism of ore-rock dispersion. Using the discrete element method to analyze the flow characteristics, contact compactness, stress distribution characteristics and contact force probability distribution of the ore-rock dispersion, it realizes the quantitative characterization of the damage degree of ore-rock flow, and reveals the damage mechanism of mine storage wall. The results show that: (1) The friction between ore-rock particles, between ore-rock and well wall is an important reason for the change of the macroscopic flow form of ore-rock from “one” to “V” type. (2) The compactness and stress concentration of ores are increasing with the increase of storage depth, which is shown that with the increase of storage depth, the greater the probability of well wall instability. (3) The probability distribution of contact force strength between particles decreases exponentially in the whole process of ore drawing, in which the strong chain plays a major role in the stability of the dispersion system. (4) The number of overpressure and the overpressure coefficient can be used to quantitatively characterize the wall damage degree under the action of ore-rock flow. The dynamic side pressure decreases periodically in the form of exponential fluctuations, and the dynamic load formed by the ore-rock flow mainly played a role in the lower area of the ore storage section.

Biotic and abiotic factors influence the formation of fungal-algal pairings in lichen symbiosis. It is poorly known which factors determine the specific associations, especially when distantly related fungi are considered. Here, we investigated the effect of different drivers on the association patterns of taxonomically diverse lichenized fungi and their trebouxioid symbiotic partners. In 200 samples collected across three biomes, we found 41 species of lichenized fungi, associating with 16 species of trebouxioid green algae, of which 62% were previously unreported. Species identity of the fungal and algal partner had the greatest effect on the outcome of the symbiosis compared with abiotic factors such as climatic variables and geographic distance. Partner specificity was found to be higher in tropical regions than in temperate and arctic regions. Co-phylogenetic analyses indicated congruent phylogenies of trebouxioid algae and associated fungi, rejecting their random associations. Evolutionary mechanisms contributing most to the observed phylogenetic patterns were ‘loss’ and ‘failure to diverge’ of the algal partners. This study broadens our knowledge of fungi-algae symbiotic patterns in view of Trebouxia-associated fungi.

The ADP-ribosylation factor 6 (Arf6), as the only member of the Arf family III protein, has been extensively studied for its diverse biological functions in animals. Previously, the Arf6 protein in Magnaporthe oryzae was found to be crucial for endocytosis and polarity establishment during asexual development. However, its role remains unclear in Sclerotinia sclerotiorum. Here, we identified and characterized SsArf6 in S. sclerotiorum using a reverse genetic approach. Deletion of SsArf6 impaired hyphal growth and development, and produced more branches. Interestingly, knockout of SsArf6 enhanced the tolerance of S. sclerotiorum to oxidative stress but the sensitivity to osmotic stress, and increased melanin accumulation, indicative of different roles of SsArf6 in various stress responses. Moreover, the appressorium formation was severely impaired, and fungal virulence to host plants was significantly reduced. Overall, our findings demonstrate the essential role of SsArf6 in hyphal development, stress responses, appressorium formation, and fungal virulence to host plants.

The microstructure and solidification behavior of nickel based GTD222 superalloy at different cooling rates are studied. The solidification of the GTD222 superalloy proceeds as follows: L→L+γ, L→L+γ+MC, L→L+(γ/γ ′)-Eutectic and L→η phase. The temperature of liquidus of GTD222 superalloy is 1360 °C while the solidus is slightly lower at 1310 °C, which due to the alloying elements redistribution. It was found that the dendrite arm spacing of the alloy decreased with the increase of cooling rate (From 200 μm at 2.5 K/min to 100 μm at 20 K/min).

Green-space resources, in the context of urbanisation, cannot meet the actual needs of residents well, and the study of the balance of green-space resource allocation from the relationship between supply and demand is an urgent problem to be solved. This study quantitatively evaluates the green-space supply level from four dimensions by constructing a framework for assessment in the community life circle. It also evaluates the matching of green space supply and demand, resource distribution fairness, and distribution equilibrium under group differentiation through the supply–demand coupling matrix, Gini coefficient, and the Kruskal–Wallis H non-parametric rank-sum test, respectively. This study shows that (1) a significant spatial imbalance exists in green-space resource allocation in community life circles in different dimensions. (2) The comprehensive green-space supply level in the community life circle matched the total demand of residents to a low degree. (3) There was significant inequality in green-space resource allocation within the community life circle (the Gini coefficient of each evaluation perspective was > 0.4). Based on the study results, we were able to identify community life circles with spatial mismatches, different supply and demand, and other green-space resource allocation problems, which is of great significance to urban green-space research and planning practice under the "green justice" framework.

The data assimilation method to improve sea fog forecast over the Yellow Sea is usually three-dimensional variational assimilation (3DVAR), whereas ensemble Kalman filter (EnKF) has not yet been applied on this weather phenomenon. In this paper, two sea fog cases over the Yellow sea, one spread widely and the other spread narrowly along the coastal area, are studied in detail by a series of numerical experiments with 3DVAR and EnKF based on the Grid-point Statistical Interpolation (GSI) system and the Weather Research and Forecasting (WRF) model. The results show that the assimilation effect of EnKF outperforms that of 3DVAR: for the widespread-fog case, the probability of detection and equitable threat scores of the forecasted sea fog area get improved respectively by ~57.9% and ~55.5%; the sea fog of the other case completely mis-forecasted by 3DVAR is produced successfully by EnKF. These improvements of EnKF relative to 3DVAR are benefited from its flow-dependent background error, resulting in more realistic depiction of sea surface wind for the widespread-fog case and better moisture distribution for the other case in the initial conditions. More importantly, the correlation between temperature and humidity in the background error of EnKF plays a vital role in the response of moisture to the assimilation of temperature, which leads to a great improvement on the initial moisture conditions for sea fog forecast.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Previous control methods developed by our research team cannot satisfy the high-accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) guidance law for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle, with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain a high-accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS guidance law can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, and reduce the average cross-track error by 10.91%, and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional method.

Ionic gel electrolyte retains the characteristics of non-volatilization, non-flammability and outstanding electrochemical stability of ionic liquid, and shows good electrochemical performance combined with the excellent characteristics of different matrix materials, which is considered to be the best choice to achieve the high energy density and safety at the same time. In this paper, a flexible and self-healing ionic gel electrolyte is prepared by solvent-assisted method based on a zteric ion (ZI) copolymer. Abundant hydrogen bonds and synergistic interaction of ions in the electrolyte system endowed it with wonderful self-healing ability. The ionic conductivity of 9.06×10-4 S cm-1 at room temperature was achieved. Besides, the tLi+ was also increased to 0.312. The self-healing function of the ionic gel electrolyte ensured the long-term tolerance of the SHIGE. The capacity retention rate of the Li//LiFePO4 battery is 96% after 155 cycles at 0.1 C at 60 oC. This polymer electrolyte is expected to solve the problem of increasing polarization，which is caused by the low lithium ions migration number in ionic liquid electrolyte. And ultimately, it gives rise to a good rate performance.

Dust storms play a crucial role in the climate system and the space environment of Mars and have a great impact on human’s Mars exploration activities. The Martian dust storms exhibit significant regional, seasonal and interannual variations due to various controlling factors such as the large-scale atmospheric circulation, varying solar radiation forcing, and Martial orbital and rotational motions and their coupling to the atmospheric dynamics. This paper focuses on the review of cur-rent understandings on Martian dust storms. This paper begins by elucidating the basic properties of dust storms, and their driving mechanisms and impacts on atmospheric dynamics, atmospheric electric property, space environment, topography, and Mars explorations. Then it introduces the observation methods on different platforms including orbiters and landers/rovers, and the da-tasets constructed based on these historical observations for Martian dust storms. Finally, we pro-posed the dust storm monitoring and forecasting for the upcoming Chinese Tianwen-3 Mars sam-pling returning mission. It concludes by depicting the future research topics to systematically un-derstand the Martian dust storms.

We tested selecting data randomly or proportionally in class imbalanced sample. Collecting data into the training and test set according to the initial ratio of QSOs, galaxies and stars were rec-ommended. We experimented using the original imbalanced data or introducing the class balance technologies: SMOTE, SMOTEENN, SMOTETomek, ADASYN, BorderlineSMOTE1, Border-lineSMOTE2, and RandomUndersampling. The SMOTEENN performed the best in the Sample 1. The LightGBM, CatBoost, XGBoost, and RF were compared when adopting the SMOTEENN using the petroMag_u, petroMag_g, petroMag_r, petroMag_i, petroMag_z, J, H, Ks, W1, W2, W3, W4 magnitudes as features. All of the precisions or recalls exceeded 0.94. The RF cost a little more time than the other three algorithms, but resulted in the best evaluating indicators. Utilizing the SMOTEENN +RF technology, the precision, recall and f1-score for QSOs (galaxies, stars) could achieve 0.98 (0.99, 0.98), 0.99 (0.96, 1.00), 0.98 (0.97, 0.99) respectively in Sample 1. Utilizing the SMOTEENN +RF technology, the precision, recall and f1-score for QSOs (galaxies, stars) could achieve 0.94 (0.96, 0.96), 0.98 (0.90, 0.97), 0.96 (0.93, 0.97) using the petroMag_u, petroMag_g, petroMag_r, petroMag_i, petroMag_z, W1, W2, W3, W4 magnitudes as features.

Cadmium (Cd) is a major heavy metal pollutant and a significant cause of abiotic stress in the environment. Organisms have developed various pathways to protect themselves against Cd stress. MYB protein is a large transcription factor family in plants. Many members of the family have been found to regulate developmental processes and stress responses. However, the function and mechanism of MYB116 are far from clear. In a recent study, we found that MYB116 of Chinese cabbage enhances Cd tolerance in yeast. BrMYB116 is transiently inducible by Cd treatment in Chinese cabbage. When expressed in yeast cells, it enhances tolerance against Cd stress and reduces Cd accumulation in the cells. Further analysis shows that BrMYB116 protein enhances Cd tolerance in yeast cells by activating one target gene that encodes the facilitator of iron transport 3 (FIT3). ScFIT3 is activated through specific binding with its promoter. More importantly, the expression of ScFIT3, leads to a substantial reduction of Cd accumulation in both yeast and Chinese cabbage. This finding implies that a similar network may exist in other biological systems, which presents a promising avenue for enhancing Cd tolerance in plants and developing Cd-resistant crops.

ABSTRACT Background It is important to be able to predict, for each individual patient, the likelihood of later metastatic occurrence, because the prediction can guide treatment plans tailored to a specific patient to prevent metastasis and to help avoid under- or over-treatment. Deep Neural Network (DNN) learning, commonly referred to as deep learning, has become popular due to its success in image detection and prediction, but questions such as whether deep learning outperforms other machine learning methods when using non-image clinical data remain unanswered. Grid search has been introduced to deep learning hyperparameter tunning for the purpose of improving its prediction performance, but the effect of grid search on other machine learning methods are under-studied. In this research, we take the empirical approach to study the performance of deep learning and other machine learning methods when using non-image clinical data to predict the occurrence of breast cancer metastasis (BCM) 5, 10, or 15-years after the initial treatment. We developed DNN models as well as models using 9 other machine learning methods including Naive Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), LASSO, Decision Tree (DT), k-Nearest Neighbors (KNN), Random Forrest (RF), AdaBoost (ADB), and XGBoost (XGB). We used grid search to tune hyperparameters for all methods. We then compared the deep learning models to the models trained using the 9 other machine learning methods. Results Based on the mean test AUC results, DNN ranks 6th, 4th, and 3rd when predicting 5-year, 10-year, and 15-year BCM respectively, out of 10 machine learning methods. The top performing methods in predicting 5-year BCM are XGB(1^st), RF(2^nd), and KNN(3^rd). For predicting 10-year BCM the top performers are XGB (1^st), RF(2^nd), and NB(3^rd) . Finally, for 15-year BCM the top performers are SVM (1^st), LR and LASSO (tied for 2^nd), and DNN (3^rd). The ensemble methods RF and XGB outperform other methods when data are less balanced, while SVM, LR, LASSO, and DNN outperform other methods when data are more balanced. Our statistical testing results show that at a significance level of 0.05 DNN overall performs no worse than other machine learning methods when predicting 5-year, 10-year, and 15-year BCM. Conclusions Our results show that deep learning with grid search overall performs at least as well as other machine learning methods when using non-image clinical data. It is interesting to note that some of the other machine learning methods such as XGB, RF, and SVM are very strong competitors of DNN when incorporating grid search. It is also worth noting that the computation time required to do grid search with DNN is way more than that required to do grid search with the other 9 machine learning methods.

Xinjiang, as a climate-sensitive region in northwest China, holds significant importance in studying extreme weather events for agricultural production and socioeconomic development. Based on data from 52 meteorological stations and 23 extreme climate indicators in Xinjiang from 1960 to 2021, the 5a moving average, linear trend estimation, climate tendency rate, and GIS spatial analysis methods are used to analyze the distribution and change characteristics of extreme climate. The results revealed that from 1960 to 2021, TXx, TNx, TXn, TNn, FD, ID, TN10p, TX10p, and WSDI showed a significant upward trend, while SU, TR, TN90p, TX90p, and CSDI showed a significant downward trend. What is more, the range of changes in the extreme temperature indexes from 1990 to 2021 is higher than that of 1960 to 1989. The high-value areas of extreme indexes are primarily concentrated in the northern part, while the high-value areas of cold event indexes are mainly distributed in the southern part. The upward/downward trends all accounting for over 80.00% of the entire region. The Rx1day, Rx5day, PRCPTOT, R95p, R99p, R10, R20, and R25 showed a significant growth trend from 1960 to 2021, and the range of change in the extreme precipitation indexes from 1990 to 2021 was lower than that from 1960 to 1989. Moreover, their high-value areas and high climate tendency areas are mainly concentrated in the northern and western parts of Xinjiang, with upward trends all accounting for over 71.00% of the entire region. The research results provide theoretical foundations for formulating climate risk strategies in the northwest region of China.

Hypochlorite (ClO−) and viscosity both affect the physiological state of mitochondria, and their abnormal levels are closely related to many common diseases. Therefore, it is of great significance to develop a mitochondria-targeting fluorescent probes for the dual sensing of ClO− and viscosity. Herein, we have explored a new fluorescent probe XTAP−Bn, which responds sensitively to ClO− and viscosity with off-on fluorescence changes at 558 and 765 nm, respectively. Because the emission wavelength gap is more than 200 nm, XTAP−Bn can effectively eliminate the signal crosstalk during the simultaneous detection of ClO− and viscosity. In addition, XTAP−Bn exhibits a series of advantages, including high selectivity, rapid response, good water solubility, low cytotoxicity, and excellent mitochondrial targeting ability. More importantly, probe XTAP−Bn has been successfully employed to monitor the dynamic change of ClO− and viscosity levels in mitochondria of living cells and zebrafish. Taken together, this work not only provides a reliable tool for identifying mitochondrial dysfunction, but also offers a potential approach for the early diagnosis of mitochondrial-related diseases.

When extract building from high resolution remote sensing image with meter/sub-meter accuracy, the shade of trees and interference of roads are the main factors of reducing the extraction accuracy. Proposed a Bayesian Convolutional Neural Networks(BCNET) model base on standard fully convolutional networks(FCN) to solve these problems. First take building with no shade or artificial removal of shade as Sample-A, woodland as Sample-B, road as Sample-C. Set up 3 sample libraries. Learn these sample libraries respectively, get their own set of feature vector; Mixture Gauss model these feature vector set, evaluate the conditional probability density function of mixture of noise object and roofs; Improve the standard FCN from the 2 aspect:(1) Introduce atrous convolution. (2) Take conditional probability density function as the activation function of the last convolution. Carry out experiment using unmanned aerial vehicle(UVA) image, the results show that BCNET model can effectively eliminate the influence of trees and roads, the building extraction accuracy can reach 97%.

Chemical investigation of the Chinese soft coral Lobophytum sp. has resulted in the isolation of six new compounds, namely lobosteroids A–F (1–6), along with four known compounds. Their structures were determined by extensive spectroscopic analysis and comparison with the spectral data reported in the literature. Among them, the absolute configuration of 1 was determined by X-ray diffraction analysis. These steroids characterized by either the presence of an α,β-αꞌ,βꞌ-unsaturated carbonyl or an α,β-unsaturated carbonyl moiety in ring A, or the existence of a 5α,8α-epidioxy system in ring B, as well as diverse oxidation sites of side chains. The prelimi-nary antibacterial bioassay showed all compounds exhibited significant antibacterial activities against the fish pathogenic bacteria Streptococcus parauberis FP KSP28 and Phoyobacterium damselae FP2244 with all inhibition rates more than 90% at the concentration of 150 µM. And at the same concentration, compounds 2, 6–10 also displayed potent inhibitory effects against vancomy-cin-resistant Enterococcus faecium bacteria G7 with all inhibition rates more than 90%.

The three-pronged sliding universal coupling is a new kind of three-pronged coupling. To study its kinematic and dynamic characteristics, directional cosine matrices are utilized as tools to analyze the coordinate systems by establishing simplified geometric models and corresponding motions. Through the analysis of the motions of the input and output shafts and employing the method of single-force element, a set of equilibrium equations for the forces acting on the output shaft and the input shaft are formulated for solution analysis. The research indicates that during the rotation process, there exists a small angular difference between the input shaft and the intermediate shaft, demonstrating the quasi-constant angular velocity characteristics of the new tripod sliding universal coupling. The curves of the forces and torques acting on each component of the coupling approximate sinusoidal curves. The optimal operating angle range for the new tripod universal coupling is at angle , during which the system exhibits good transmission and mechanical performance.

Forest ecosystems make a greater contribution to carbon (C) stocks than any other terrestrial ecosystem. To understand the role of regional forest ecosystems in global climate change and carbon exchange, forest C stock and its spatial distribution within the small (2,300 km2) Liuxihe River basin were analyzed to determine the different contributors to the C stock. Forest C stocks were quantified by measuring the biomass of trees, understory vegetation, litter and roots, as well as soil organic C, using data from field samples and laboratory experiments. The results showed that forests stored 38.04 Tg C in the entire basin, with secondary and planted forests accounting for 89.82% and 10.18%, respectively, of the stored C. Five types of forests, a subtropical evergreen broad-leaved forest, a subtropical coniferous and broad-leaved mixed forest, a subtropical coniferous forest, a timber forest, and a non-wood forest, stored 257.55 ± 15.01, 218.92 ± 9.59, 195.24 ± 18.29, 177.42 ± 17.55, and 117.86 ± 6.04 Mg C ha−1, respectively. In the forest ecosystem C stocks of the basin, soils averagely contribute about 73.78%, not including root underground biomass. It provides a comprehensive method for forest ecosystem carbon investigation and forest management in small basin scale.

This study aimed to use spatiotemporal tensor data to measure the level of employment quality in China's provinces and analyzed the magnitude and direction of its influencing factors in the spatiotemporal dimension. Taked 30 provinces, autonomous regions and municipalities directly under the central government in China from 2011 to 2020 as the research object, the employment quality evaluation system was constructed from six dimensions of employment environment, employment status, employability, labor remuneration, social security, and labor relations. The employment quality index data was expressed as a three-order high-dimensional tensor spatio-temporal data form, and the employment quality of China's provinces was measured from the spatio-temporal perspective by using principal tensor analysis, and the visual analysis of the development and change process of employment quality was carried out. The spatial autocorrelation analysis of employment quality was carried out, and the time-space dual fixed effect model of the spatial Dubin model was selected to analyze the direction and magnitude of the influence factors of employment quality on itself and its neighboring provinces. The research showed that: (1) The overall level of employment quality in China was not high and the employment quality varies greatly among provinces, and the employment quality development gap among provinces showed a trend of widening. (2) The development of employment quality in western China was relatively fast, while the development of employment quality in central China showed insufficient stamina. (3) Sichuan Province had a strong radiation effect on the development of employment quality in neighboring provinces, and Beijing and Tianjin had a strong siphon effect on the development of employment quality in neighboring provinces. (4) The level of industrialization and informatization promoted the development of employment quality in China's provinces, while the industrial structure had a significant negative effect on the development of employment quality.

Litsea cubeba, an important medicinal plant, is widely used as traditional Chinese medicine and spice. Using cytotoxicity-guided fractionation, nine new lignans (1-9) and eleven known analogues (10-19) were obtained from the EtOH extract of the twigs of L. cubeba. Their structures were assigned by extensive 1D and 2D NMR experiments, and the absolute configurations were resolved by specific rotation and a combination of experimental and theoretically calculated electronic circular dichroism (ECD) spectra. In the cytotoxicity assay, 7',9-epoxylignans with feruloyl or cinnamoyl group (7-9, 13 and 14) were selectively cytotoxic against NCI-H1650 cell line, while the dibenzylbutyrolactone lignans (17-19) exerted cytotoxicities against HCT-116 and A2780 cell lines. The results highlighted the structure-activity relationship importance of a feruloyl or a cinnamoyl moiety at C-9′ or/and C-7 ketone in 7',9-epoxylignans. Furthermore, compound 11 was moderate active toward protein tyrosine phosphatase 1B (PTP1B) with an IC50 value of 13.5 μM, and compounds 4-6, 11 and 12 displayed inhibitions against LPS-induced NO production in RAW264.7 macrophages, with IC50 values of 46.8, 50.1, 58.6, 47.5, and 66.5 μM, respectively.

In order to better understand the source-sink flow and relationships of Zinc (Zn) and other nutrients in wheat (Triticum aestivum L.) plants for biofortification and improving grain nutritional quality, effects of reducing photoassimilate source (through the flag leaf removal and spike shading) or sink (through 50% spikelets removal) in the field on accumulation of Zn and other nutrients in wheat grains of two cultivars (Jimai 22 and Jimai 44) were investigated under two soil Zn application levels. The single panicle weight (SPW), kernel number per spike (KNPS), thousand kernel weight (TKW), total grain weight (TGW), concentrations and yields of various nutrient elements (Zn, Fe, Mn, Cu, N, P, K, Ca and Mg), phytate phosphorus (phytate-P), phytic acid (PA) and phytohormones (ABA: abscisic acid, and the ethylene precursor ACC: 1-aminocylopropane-1-carboxylic acid), and C/N ratios were determined. Soil Zn application significantly increased concentrations of grain Zn, N and K. Cultivars showing higher grain yields had lower grain protein and micronutrient nutritional quality. SPW, KNPS, TKW (with an exception of TKW in half spikelets removal), TGW, and nutrient yields in wheat grains were most severely reduced by half spiklets removal, secondly by spike shading, and slightly by flag leaf removal. Grain concentrations of Zn, N and Mg consistently showed negative correlations with SPW, KNPS and TGW, but positively with TKW. There were general positive correlations among grain concentrations of Zn, Fe, Mn, Cu, N and Mg, and bioavailability of Zn and Fe (estimated by molar ratios of PA/Zn, PA × Ca/Zn, PA/Fe, or PA × Ca/Fe). Although concentrations of Zn and Fe were increased and Ca was decreased in treatments of half spikelets removal and spike shading, the simultaneously increased PA limited the increase in bioavailability of Zn and Fe. In general, different nutrient elements interact with each other and are affected to different degrees by source-sink manipulations. Elevated endogenous ABA levels and ABA/ACC ratios were associated with increased TKW and grain-filling of Zn, Mn, Ca and Mg, and inhibited K in wheat grains. However, effects of ACC were diametrically opposite. These results provide basis for wheat grain biofortification to alleviate human malnutrition.

Surface-enhanced Raman spectroscopy (SERS) can boost the pristine Raman signal by ~ 108 times that could be exploited for producing innovative sensing devices with advanced properties. However, the inherent complexity of SERS systems restricts their further applications in rapid detection, especially in situ detection in narrow aera. Here, we construct an efficient and flexible SERS-based LOP sensor by integrating Ag/Au nanocap arrays obtained by Ag/Au coating polystyrene nanospheres on the optical fiber face. We obtain rich “hotspots” at the nanogaps between neighboring nanocaps and further achieve the excellent SERS performance with the assistance of laser induced thermophoresis on the metal film that can achieve high efficiency aggregation of detected molecules. We achieve a high Raman enhancement with a low detection limitation of 10-7 mol/L for the most efficient samples based on the above sensor. This sensor also exhibits good repeatability and stability under multiple detections, revealing the potential application in situ detection based on the reflexivity of optical fiber.

Objective: Rett syndrome (RTT) is an X-linked neurodevelopmental disorder caused by mutations in MeCP2, a transcription factor. MeCP2 mutations cause abnormal expression of downstream genes and eventually lead to brain dysfunction. The role of MeCP2 in brain neural development remains unclear. To further elucidate this role, a MeCP2-null rat model was created with the CRISPR/cas9 system. Method: A MeCP2-cas9 vector was constructed and then microinjected into fertilized rat ova in vitro. Two mutations by CRISPR/cas9 were confirmed to cause deletions in exon 2 of MeCP2 via DNA sequencing, and protein expression was measured by Western blotting. Transcriptome data for three brain tissues, the cerebellum, cerebral cortex and hippocampus, were obtained via next-generation sequencing. Results: MeCP2-null rats were successfully obtained, and preliminary analysis showed that the MeCP2-null rats exhibited motor dysfunction and anxious and depressed behaviour. In addition, differentially expressed genes (DEGs) were identified in the three MeCP2-null brain tissues compared to wild-type rat brain tissues. In the rat cerebellum, 388 downregulated DEGs were mainly involved in the calcium ion signalling pathway and the PI3K-Akt signalling pathway. In the cerebral cortex, 386 upregulated DEGs were primarily involved in intracellular signal transduction, protein phosphorylation and the MAPK signalling pathway. In the hippocampus, the DEGs were related to the MAPK signalling pathway. Conclusion: We constructed a MeCP2-null rat model with unique features with CRISPR/cas9 technology to study RTT and analysed DEGs in three rat brain tissues to highlight potential targets for the development of new medicines.

The increasing demand for higher power in rocket launchers is driving the development of higher power nozzles, achieved essentially by increasing the expansion ratio. However, this can lead to flow separation and resulting unsteady, asymmetrical forces, called side loads, which can limit the life of both the nozzle itself and other engine components. If this problem can be overcome, engine performance can be significantly increased. Therefore, various separation control methods have been proposed, but none have been fully implemented to date due to the uncertainties associated with modeling and predicting the flow phenomena. A numerical study of high area ratio rocket engine is presented to analyze the aeroelastic performance of the structure under the condition of flow separation. The finite volume method, the 2nd order upwind scheme and the extended wall function are used to analyze the flow inside the rocket nozzle and the transition of the Free Shock Separation (FSS) to Restricted Shock Separation (RSS) separation pattern ) to be discussed in detail. Since the location of the flow separation point depends heavily on the flow.

Poverty alleviation is a hallmark of post-revolution Chinese policymaking. Since 1978, the Communist Party of China (CPC) has implemented successive waves of poverty alleviation policies whose effects have become the focus of an ever-increasing body of academic literature. This paper reviews this diverse but limited literature that evaluates the impact of the CPC’s poverty reduction programs through four major channels, namely fiscal investment programs, social safety nets, rural governance on the village-, county- and provincial level, and the relocation of rural populations from destitute regions. This paper aims to synthesize results and evaluate whether and how the abovementioned poverty alleviation programs have had distinct positive or negative impacts on regional development outcomes. Furthermore, I highlight contradictions in empirical findings to motivate the discussion about contextual importance when designing and implementing future poverty alleviation programs. Finally, I suggest that an exhaustive and critical appraisal of the empirical strategies used in this literature would further the development and application of more accurate and informative methodologies.

In human body, carboxylesterases (CEs) play the crucial roles in xenobiotic metabolism and lipid homeostasis. But the abnormal CEs expression is highly associated with some diseases, such as hyperlipidemia, diabetes and liver cancer. Therefore, it is of great significance to develop an efficient tool for the accurate detection of CEs in living organisms. Herein, an innovative near-infrared (NIR) fluorescent probe TTAP−AB has been designed for CEs detection based on aggregation-induced emission (AIE) mechanism. This probe exhibits rapid response (2 min), excellent sensitivity (limit of detection = 8.14×10−6 U/mL), and high selectivity towards CEs. Additionally, owing to the good biocompatibility, probe TTAP−AB enables to monitor the dynamic changes of CEs level under drug-induced modulation in living cells and zebrafish. More importantly, probe TTAP−AB is successfully employed to image the liver tumor and assist tumor resection by the real-time monitoring of CEs, indicating that TTAP−AB is promising to guide liver cancer surgery. Therefore, probe TTAP−AB can not only enrich the strategies for CEs detection in biological systems, but also has great potential for some clinical imaging applications, including medical diagnosis, preclinical research, and imaging-guided surgery.

Energy Measurement and Verification (M&V) aims to make inferences about the savings achieved in energy projects, given the data and other information at hand. Traditionally, a frequentist approach has been used to quantify these savings and their associated uncertainties. We demonstrate that the Bayesian paradigm is an intuitive, coherent, and powerful alternative framework within which M&V can be done. Its advantages and limitations are discussed, and two examples from the industry-standard International Performance Measurement and Verification Protocol (IPMVP) are solved using the framework. Bayesian analysis is shown to describe the problem more thoroughly and yield richer information and uncertainty quantification than the standard methods while not sacrificing model simplicity. We also show that Bayesian methods can be more robust to outliers. Bayesian alternatives to standard M&V methods are listed, and examples from literature are cited.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

Sensory descriptive analysis was used to evaluate the aged Feng-flavored baijiu. The results indicated that there are notable differences in the samples of different ages. The samples with shorter storage times and fresh distilled Baijiu present bran flavor, and fresh green flavor. with the increase of storage time, the fragrance of honey, sweetness, flowers, and aging gradually increases. The samples of Feng-flavored baijiu were dected by Headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC–TOFMS) , in total, 496 sustances were identified in all samples, mainly containing 14 types of substances, such as esters, aldehydes etc., of which 42 substances were found in Feng-flavored baijiu for the first time. Chemometrics was used to analyze the key differential compounds. 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these samples were separated by year. 65 differential compounds were selected out by partial least squares discriminant analysis(PLS-DA). Furthermore, 43 key differential compounds were selected from the aged Feng-flavored baijiu combined with variable importance in projection and Pearson correlation coefficients. Partial least squares regression (PLSR) was used to research the correlation of sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aged Baijiu . This study afford theoretical basis and reference for flavor research of Feng-flavored baijiu.

The mammalian or mechanistic target of rapamycin (mTOR) integrates multiple intracellular and extra-cellular upstream signals involved in the regulation of anabolic and catabolic processes in cells, and plays a key regulatory role in cell growth and metabolism. Activation of the mTOR signaling pathway has been reported to be associated with a wide range of human diseases. A growing number of in vivo and in vitro studies have demonstrated that the gut microbes and its complex metabolites can regulate host metabolic and immune responses through the mTOR pathway, and result in disorders of host phys-iological functions. In this review, we summarize the regulatory mechanisms of gut microbes and mTOR in different diseases, and discuss the crosstalk between gut microbes and their metabolites and mTOR in the disorders in gastrointestinal tract, liver, heart and other organs. We also discuss the promising appli-cation of multiple potential drugs that can adjust the gut microbiota and mTOR signal pathways. Despite the limited findings between gut microbes and mTOR, elucidating their relationship may provide new clues for the prevention and treatment of various diseases.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

Microcystis aeruginosa is a common cyanobacteria found in water blooms and often causes ecological harm. Antibiotics are also increasingly used for the prevention and treatment of bacterial infections in aquaculture. However, since most antibiotics cannot be fully metabolized, they enter the water environment and cause ecological impacts. In this paper, the effects of the two quinolone antibiotics (enrofloxacin and ciprofloxacin) on the population density and microcystins (MCs) production of Microcystis aeruginosa were studied. It is of great significance for the ecological risk assessment of antibiotics to the water environment. The results showed that the 96h EC50 values of enrofloxacin and ciprofloxacin to Microcystis aeruginosa were 56.10mg/L and 49.80mg/L respectively, and the toxicity of ciprofloxacin to Microcystis aeruginosa was slightly stronger than that of enrofloxacin. With the increase of the two quinolone antibiotic concentration, the growth inhibition rate (IR) increased, but when the concentration reached a certain height, the IR would reach its threshold. Long-term exposure to low concentrations of these two quinolone antibiotics is not only more likely to lead to the outbreak of Microcystis aeruginosa, but also increase its toxin production capacity. The highest contents of MCs in enrofloxacin and ciprofloxacin groups were 95.539 μg/g and 93.720 μg/g, respectively. The MCs value of these three enrofloxacin treatment groups was more than above 51.8 times that of control group (CK) on the 4th day; from 8th day to 14th day, the MCs value of these three enrofloxacin treatment groups was more than above 3.2 times that of CK group. For another ciprofloxacin, the MCs value of the treatment group was more than 64.98 times that of the CK group on the 4th day, and from 8th day to 14th day, the MCs value of the treatment group was more than 2.7 times that of the CK group. These findings provide crucial management rationale.

The rapid development of the Industrial Internet of Things (IIoT) has brought enormous opportunities to the industrial environment but has also posed significant challenges to network security, especially the physical layer security challenges,which is crucial for the reliable transmission of messages interconnected devices and sensors. Focus on the enhancing the physical layer security in the IIoT communication, this paper proposed a mechanism of Spatial Secrecy Outage Probability (SSOP) to ensure the secure transmission of data. The SSOP algorithm assumes that the location of legitimate device is known, while eavesdropper on the random distribution of device locations, forming the SSOP model related to device locations from the perspective of insecure regions (ISR) and secure regions (SR), and deduce the closed-form expression for its upper bound. Subsequently under the constraint of SSOP conditions, establish an optimization model with the objective of system throughput maximization based on Spatial Secrecy Outage Probability(SRM-SSOP). By optimizing the transmission rate of legitimate channels or controlling the transmission power, the maximization of system throughput can be achieved, thus reducing the consumption of communication resources. Through sophisticated modeling and simulation in the MATLAB, we verified the accuracy of the definition and derived upper bound of SSOP. The experimental results also show that SSOP algorithm gradually converges to a specific value as the number of antenna elements increases. In addition, we observed that when the receiver device is aligned with the normal direction of the transmit antenna array, the SSOP reaches a minimum value. These performance are crucial for understanding and optimizing the security performance of IIoT communication systems.

The study comprehensively evaluated the prognostic roles of PLR, NLR, MLR, BLR, and ELR in patients with acute exacerbation chronic obstructive pulmonary disease (AECOPD). 619 patients with AECOPD and 300 healthy volunteers were retrospectively included into the study. The clinical characteristics containing laboratory findings of the AECOPD patients and the blood cell counts (CBCs) of the healthy volunteers were collected. Compared with the healthy volunteers, PLR, NLR, and MLR were elevated in COPD patients in stable condition, and were further ele-vated during exacerbation. ELR showed the opposite trend. PLR, NLR, and MLR were all posi-tively correlated with hospital LOS as well as CRP. In contrast, ELR was negatively correlated with hospital LOS as well as CRP. Elevated PLR, NLR, and MLR were all associated with more serious airflow limitation in AECOPD. Elevated PLR, NLR, and MLR were all associated with increased in-hospital mortality while Elevated ELR was associated with decreased in-hospital mortality in AECOPD. A nomogram was construct to predict in-hospital mortality in AECOPD. The nomo-gram had a C-index of 0.850 (95% CI: 0.799 – 0.901) with good predictive value and clinical ap-plicability. In summary, PLR, NLR, MLR, and ELR served as predictors for clinical outcomes in patients with AECOPD.

The dynamic factors in the environment violate the static environment assumption of the SLAM algorithm, leading to a decrease in the accuracy of camera positioning. In recent years, many studies have attempted to address dynamic objects by combining semantic constraints and geometric constraints, but issues such as poor real-time performance, the potential for mistakenly treating humans as rigid objects, and subpar performance in high-dynamic scenes still persist. This paper proposes a dynamic scene visual SLAM algorithm called Dynamic SLAM based on target tracking and multi-view geometry (TKG-SLAM), based on object detection, Kalman filters, and multi-view geometry. This algorithm takes into consideration both real-time performance and algorithm accuracy. It combines semantic constraints and multi-view geometry constraints, selectively running the algorithm in different scenarios, filtering and preserving static points for camera pose estimation. Experimental results demonstrate that, compared to current state-of-the-art dynamic SLAM methods, our approach achieves optimal performance in some scenarios and exhibits stronger real-time capabilities.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

For Lentinula edodes, its characteristic flavor is the key determinant for consumer pref-erences. However, the tissue-specific volatile flavor variations of the fruiting body have been overlooked. Here, we comprehensively investigated volatile flavor profiles of different tissues including the pileus skin, context, gill and stipe of the fruiting body of two widely cultivated L. edodes strains (T2 and 0912). We show that the eight-carbon and sulfur com-pounds, which represented 43.2-78.0% and 1.4-42.9% to the total volatile emissions for strain 0912 and T2, dominated their volatiles profiles. The sulfur compounds could rep-resent 32.2% and 42.9% to the total volatile emissions for the context of the strain 0912 and T2, respectively, whereas only represented 1.4% for the stipes of the strain 0912 and 9.0% for the skin of strain T2. Proportions of the predominant C8 compounds (1-Octen-3-one, 1-Octen-3-ol and 3-Octanone) and sulfur compounds (Lenthionine, 1,2,4-Trithiolane, Di-methyl disulfide and Dimethyl trisurfide) changed depending on tissues and strains. We further reveal that the overall volatile flavor profiles varied greatly in different tissues and strains. With machine learning algorithm, we show that volatile profiles could 100% pre-dict strains 0912 and T2. The prediction accuracy for different tissues could also reach 100%. Our results highlight the tissue-specific volatile flavor variations of the L. edodes fruiting body.

ABSTRACT Background Ubiquitination plays an important role in protein post-translational processes and has been found to be involved in a number of regulatory functions including proteasome degradation, DNA repair, transcription, signal transduction, endocytosis, and sorting. As the identification of ubiquitination site is critical to furthering our understanding of the mechanism of ubiquitination, various experimental and machine learning methods have been used to conduct this task. It has been an important but challenging task to improve the accuracy of ubiquitination site prediction. In this research, we explore the possibility of improving the prediction performance of machine learning by incorporating grid search in the training process. Method We developed grid search procedures for each of six widely used machine learning methods including NB, LR, DT, SVM, LASSO, and KNN, and applied them to ubiquitination site prediction using the six PCP datasets that were previously developed. For each of the ML methods, we developed a set of values for each of the tunable hyperparameters available to the method. These sets of values then can be combined to form a large grid of hyperparameter settings, and each of these settings is used in the grid search. We integrated 5-fold cross-validation in grid search to train and test ML models and applied an additional independent validation procedure by conducting a pre-training 80-20 sample split. We evaluated the performance of the six methods by comparing them side by side for each of the six datasets. We also compared the grid search results with the results that were previously published without doing grid search. To optimize the prediction performance, we trained 1.1 million ML models in total through grid search. Results We compared the overall prediction performance of these six methods, as well as their prediction performance when working with balanced vs. imbalanced data, and large-scale vs. small-scale data. From the perspective of dataset, we find that the overall performance of every PCP dataset has been significantly improved in this study compared to the previous study, with the percentage increase of the average AUC of all six datasets ranging from 7.9% (PCP-4) up to 17.0% (PCP-1). From the perspective of method, we find that three out of four methods significantly benefit from grid search comparing to their previously published non-grid search results, with the maximum AUC improvement as high as 47% (LASSO on PCP-5), 43.3% (NB on PCP-1), and 33.7% (SVM on PCP-6). SVM overall ranks number one, followed by KNN as the number two performer based on their average AUCs on all datasets. But these two also ranked the top two (KNN 76 days and SVM 15 days) in terms of the total running time that they need to do grid search. We also find that SVM, KNN, and DT tend to handle small-scale and imbalanced datasets better, while LR, and LASSO are doing well with large-scale and balanced datasets. NB is more sensitive to data imbalance while less sensitive to the size of a dataset. Conclusions Our results show that using grid search has improved the performance of ubiquitination prediction significantly. We find that the performance of a method is closely related to its hyperparameter setting and the type of data it handles. Even though SVM is on average an outperformer, none of the methods can provide the best performance for all datasets. When sufficient computing resources are well accessible, grid search is an effective way to identify both a top performing model for a machine learning method and a suitable machine learning method for a particular dataset.

We developed an ovarian cancer-targeted drug delivery system based on a follicle-stimulating hormone receptor (FSHR) peptide. The lipophilic chemotherapeutic drug SN38 and the photosensitizer IR820 were loaded into the phospholipid bilayer of liposomes. Near-infrared laser irradiation stimulated the generation of reactive oxygen species, causing short-term reactive molecular species and spatial-temporal restricted photodamage to the biological targets. The reactive molecular species and spatial-temporal restricted photodamage enhanced the release and uptake of chemotherapy drugs and increased the sensitivity to chemotherapy drugs in ovarian cancer cells. FSH liposomes loaded with SN38 and IR820 (SN38/IR820-Lipo@FSH) were prepared using thin-film hydration-sonication. FSH peptide binding was analyzed using 1H NMR spectrum and Maldi-Tof. The average size and zeta potential of SN38/IR820-Lipo@FSH were 105.1 ± 1.15 nm (PDI: 0.204 ± 0.03) and −27.8 ± 0.42 mV, respectively. SN38/IR820-Lipo@FSH exhibited good drug-loading properties and the in vitro release was slow. FSH significantly increased the uptake of liposomes, inhibited cell proliferation, and induced apoptosis in A2780 cells. Moreover, SN38/IR820-Lipo@FSH exhibited good tumor-targeting ability and anti-ovarian cancer activity in vivo. The SN38/IR820-Lipo@FSH exhibited specific targeting to A2780 ovarian cancer cells. The combination of chemotherapy and photodynamic treatment based on an FSH peptide-targeted delivery system may be an effective approach to treating ovarian cancer.

Permanent magnet brushless DC motor (BLDCM) is usually controlled by six step commutation method, and flux-weakening method is used to make the motor run higher above the base speed. For now, it is considered that the weak magneto-electric angle range is 0-pi/3, and that of deep weakening is pi/3-pi/2. In the field- weakening control, the forward shift of commutation point will form inverter circulating current in the three-phase bridge of inverter and the stator winding of the motor. In this paper, the principle of inverter circulating current formed by inverter is analyzed. Through magnetic potential analysis and Simulink simulation, it is concluded that flux-weakening control will generate inverter circulating current in the inverter and motor stator winding. The inverter circulating current affects the magnetic potential of motor, and magnetic potential will move to the rotating direction of motor rotor. When the forward shift angle of inverter commutation point is 0-pi/6 electrical angle, the movement amplitude of current circulating current of inverter is less than pi/6, which plays the role of weakening magnetic field and driving effect; when the forward moving angle is pi/6-pi/3, the movement amplitude of inverter circulating current exceeds pi/6, which plays the role of magnetic weakening and braking. When the braking effect occurs, the reverse torque will appear, resulting in the decrease of motor torque and efficiency. Therefore, the range of weak magneto-electric angle should be between 0-pi/6.

In this study, we demonstrate a high luminous efficacy of 118 lm/W and high reliability through 450°C thermal aging of white LEDs (WLEDs) utilizing four-inch YAG: Ce3+ phosphor-in-glass (PiG) plates designed for vehicle headlights. The sintering process of mixing glass and phosphor typically generates pores, which can scatter light and reduce the luminous efficacy of the fabricated PiG. In this study, we produced four-inch PiG plates under four different fabrication conditions to evaluate their luminous efficacy. Our results revealed that the PiG plate with a thin thickness of 0.08 mm exhibited a 16.83% increase in luminous efficacy compared to the 0.15 mm plate, attributed to reduced light interaction with the pores. Unlike silicone-based phosphor WLEDs, which offer high performance but lower reliability due to the silicone resin's low transition temperature (150°C), our novel thin PiG plate achieves high performance and reliability. This advancement suggests that the proposed thin PiG plate could replace traditional silicone-based phosphors, enabling the development of high-quality WLEDs for vehicle headlights in automotive applications.

Arthropods, the most abundant group in ecosystems, play crucial roles in human production. Soil physicochemical properties reflect soil health and are linked to arthropods through cascading effects. Gravel-sand mulching, commonly practiced in dry farming regions, initially aids in water retention and temperature regulation. However, long-term cultivation can lead to land degradation and habitat fragmentation. This study aimed to investigate field systems using multiple comparison, linear, and nonlinear correlation analyses to explore the effects of different tillage durations on soil properties and arthropod diversity under gravel-sand mulching. Results indicate that arthro-pod diversity was lower while the fields maintained better soil fertility than the desert steppe. Both soil fertility and arthropod diversity declined significantly with increased years of cultivation. Mantel tests revealed no significant response of desert steppe arthropods to the altered soil properties of gravel-sand mulched fields. However, the Generalized Additive Model analysis indicated significant linear correlations between arthropod occurrence and total nitrogen (positive), available phosphorus, and water content (negative). Arthropod abundance showed significant nonlinear correlations with total potassium, alkali hydrolyzable nitrogen, and organic matter (OM), with OM changes having the most pronounced impact. Thus, gravel-sand mulching can maintain soil fertility over time but at the expense of local arthropod diversity.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

Real estate industry is related to the national economy and people's livelihood，characterized by a high degree of financial intensity. The enterprises in this industry need certain financial ability and large shareholder controlling ability to support their survival. However，due to the multiple adverse impacts of current state policies，banks and private capital，the credit crunch，the sudden decrease in withdrawn funds and the limitation of internal financing，the problem of capital restraint of real estate enterprises has become more and more serious. From the perspective of corporate governance，this paper studies the interaction among financial constraints，ownership concentration and corporate performance under different shareholding states by analyzing the quantitative characteristics of equity structure，and looks for the appropriate range of the largest shareholder holding ratio，which has considered the financial performance and risk. It is found that raising the ownership concentration can effectively ease the financing constraints and improve the performance of enterprises，both of which are significant under the state of high ownership concentration， while the financial constraints play a significant intermediary effect under the State of absolute holding， while in the decentralized state of ownership，there is a significant regulatory effect，and the interaction of the three will be different due to the size of the enterprise.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Asian giant hornet, Vespa mandarinia, is an invasive species that could potentially destroy local honeybee industry in North America. It has been observed to nest in the coastal regions of British Columbia in Canada and Washington State in USA. What is the source population of the immigrant hornets? The identification of the source population can not only shed light on the route of immigration, but also on the similarity between the native habitat and the potential new habitat in the Pacific Northwest. We analyzed mitochondrial COX1 sequences of specimens sampled from multiple populations in China, South Korea, Japan and the Russian Far East. V. mandarinia exhibits phylogeographic patterns, forming monophyletic clades for 16 specimens from China, six specimens from South Korea and two specimens from Japan. The two mitochondrial COX1 sequences from Nanaimo, British Columbia are identical to the two sequences from Japan. The COX1 sequence from Blaine, Washington State, clustered with those from South Korea, and is identical to one sequence from South Korea (GenBank accession MN716828). Our geophylogeny, which allows visualization of genetic variation over time and space, provides evolutionary insights on the evolution and speciation of three closely related vespine species (V. tropica, V. soror and V. mandarinia). The geophylogeny also highlights a strong insufficiency in sample collection in China. The existing sequenced specimens from mainland China with geographic coordinates were represent only four provinces, missing populations along the coastal regions in East China. One therefore cannot exclude the possibility that the Asian giant hornet found in Canada and USA may also be identical to V. mandarinia in Eastern China. We strongly recommend more extensive DNA barcoding data with geographic information and longer DNA barcode (e.g., the entire mitochondrial genome) so that critical questions on invasive species and environmental conservation can be addressed more accurately than what is possible with existing data.

Aiming at the problem of hypersonic morphing vehicle avoiding no-fly zones and reaching the target, an improved predictor-corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given, the Q-learning method is used to design the attack angle and sweep angle scheme to ensure that the aircraft can fly over the low-altitude zones. The B-spline curve is used to design the location of flight path points and the bank angle scheme is designed according to the predictor-corrector method, so that the aircraft can fly around to avoid high-altitude zones. Next, Monte Carlo reinforcement learning(MCRL) method is used to improve predictor-corrector method and Deep Neural Network(DNN) is used to fit reward function. The improved method can generate trajectory with better performance. Simulation results verify the effectiveness of the proposed algorithm.

Natural disasters are showing an increase in the magnitude, frequency, and geographic distribution. Studies have shown that individuals’ self-sufficiency, which largely depends on household preparedness, is very important for hazard mitigation in at least the first 72 hours following a disaster. However, for factors that influence a household’s disaster preparedness, though there are many studies trying to identify from different aspects, we still lack an integrative analysis on how these factors contribute to a household’s preparation. This paper aims to build a classification model to predict whether a household has prepared for a potential disaster based on their personal characteristics and the environment they located. We collect data from the Federal Emergency Management Agency’s National Household Survey in 2018 and train four classification models - logistic regression, decision trees, support vector machines, and multi-layer perceptron classifier models- to predict the impact of personal characteristics and the environment they located on household prepare for the potential natural disaster. Results show that the multi-layer perceptron classifier model outperforms others with the highest scoring on both recall (0.8531) and f1 measure (0.7386). In addition, feature selection results also show that among other factors, a household’s accessibility to disaster-related information is the most critical factor that impacts household disaster preparation. Though there is still room for further parameter optimization, the model gives a clue that we could support disaster management by gathering publicly accessible data.

Background: With the trend of intelligent display, the interface design of in-vehicle HUD is an expanding research field; Methods: To solve the subjectivity and uncertainty in the optimization of HUD interface design schemes, this paper proposed a hybrid scheme evaluation and optimization method based on entropy weight and VIKOR. The entropy weight method was used to reduce the subjectivity the decision-maker's weighting and obtain the objective weight of each indicator; The VIKOR method was used to obtain the best ranking of alternative schemes, and then the optimal interface design scheme was selected; Results: The evaluation of in-vehicle HUD interface design schemes were taken as an example for verification and calculation. The results showed that this method considers the subjectivity and uncertainty of the decision-making process in the optimization of design scheme, which can effectively improve the objectivity and accuracy of the evaluation results, and provide a reference for designers to optimize interface design schemes.

Water resources are threatened nowadays by pollution that comes from domestic, industrial and agricultural discharges without prior treatment. This pollution causes the degradation of water quality. Surface pollutants can seep through the soil into water tables. The objective of our work is to assess and control the physicochemical quality of the Chari Baguirmi groundwater, to protect human health. The quality of 83 boreholes was assessed, while performing analysis for 12 physicochemical parameters at the National Water Laboratory and at the Center for Quality Control of Foodstuffs in Chad. These parameters are: pH, EC, Ca2+, Mg2+, Na+, K+, Cl-, SO42-, NH4+ and NO3- , Fe2+ and HCO3-. Also, the results obtained were compared with WHO standards. The geochemical statistical approach has made it possible to characterize the hydro geochemical properties and to understand the major processes of the mineralization of groundwater resources in Chari Baguirmi region in Chad. Some of its waters are acidic and weakly mineralized, rich in Fe2+ and NH4+. The origin of the mineralization is due to the alteration of the host rocks and to the hydrolysis of silicate and ferromagnesian minerals as well as anthropogenic pollution. The ammonium concentrations in N’Djamena boreholes are higher than WHO standards, indicating the presence of pollution which may come from organic waste. These results constitute a preliminary step in understanding hydro geochemical functioning and a basis for monitoring the physicochemical quality of the water in the study area.

The microglia, displaying diverse phenotypes, play a significant regulatory role in the development, progression, and prognosis of Parkinson's disease. Research has established that glycolytic reprogramming serves as a critical regulator of inflammation initiation in pro-inflammatory macrophages. Furthermore, the modulation of glycolytic reprogramming has the potential to reverse the polarized state of these macrophages. Previous studies have shown that levetistilide A (LA), a phthalide component derived from Angelica sinensis, possesses a range of pharmacological effects, including anti-inflammatory, antioxidant, and neuroprotective properties. In our study, we have examined the impact of LA on inflammatory cytokines and glucose metabolism in microglia induced by lipopolysaccharide (LPS). Furthermore, we explored the effects of LA on the AMPK/mTOR pathway and assessed its neuroprotective potential both in vitro and in vivo. The findings revealed that LA notably diminished the expression of M1 pro-inflammatory factors induced by LPS in microglia, while leaving M2 anti-inflammatory factor expression unaltered. Additionally, it reduced ROS production and suppressed IκB-α phosphorylation levels as well as NF-κB p65 nuclear translocation. Notably, LA exhibited the ability to reverse microglial glucose metabolism reprogramming and modulate the phosphorylation levels of AMPK/mTOR. In vivo experiments further corroborated these findings, demonstrating that LA mitigated the death of TH-positive dopaminergic neurons and reduced microglia activation in the ventral SNpc brain region of the midbrain and the striatum. In summary, LA exhibited neuroprotective benefits by modulating the polarization state of microglia and altering glucose metabolism, highlighting its therapeutic potential.

There are four subtypes of adenosine receptors (ARs), named A1, A2A, A2B and A3, all of which are G protein-coupled receptors. The A2BAR, coupled to both Gαi and Gαq G proteins, is one of the several G-protein-coupled receptors that are expressed in a significantly higher level in some cancer tissues in comparison to adjacent normal tissues. There is growing evidence that the A2BAR plays an important role in tumor cell proliferation, angiogenesis, metastasis, and immune suppression. Thus, A2BAR antagonists are potentially novel attractive anticancer agents. Several antagonists targeting at the A2BAR are currently in clinical trials for various types of cancers. In this review, we first describe the signaling, agonists, and antagonists of the A2BAR. We further discuss the role of the A2BAR in the progression of various types cancers, and the rationale of using A2BAR antagonists in cancer therapy

Skeletal muscle atrophy is one of the major side effects of high dose or sustained usage of glucocorticoids. Pyroptosis is a novel form of pro-inflammatory programmed cell death that may contribute to skeletal muscle injury. Trimetazidine, a well-known anti-anginal agent, can also improve skeletal muscle performance both in human and mice. We here showed that dexamethasone induced atrophy, evidenced by the increase of muscle atrophy F-box (Atrogin-1) and muscle ring finger 1 (MuRF1) expression , and the decrease of myotube diameter in C2C12 myotubes. Dexamethasone also induced pyroptosis, indicated by upregulated pyroptosis-related protein NLRP3, Caspase-1 and GSDMD. Knockdown of NLRP3 or GSDMD attenuated dexamethasone-induced myotube pyroptosis and atrophy. Trimetazidine administration ameliorated dexamethasone-induced muscle atrophy both in vivo and in vitro. Moreover, trimetazidine improved exercise tolerance, as evidenced by increased running distance and running time, as well as increased skeletal muscle mass in dexamethasone-treated mice. Mechanically, trimetazidine could reverse dexamethasone-induced activation of pyroptosis both in C2C12 myotubes and in mice. Taken together, our present study demonstrated that NLRP3/GSDMD pathway-mediated pyroptosis was involved in dexamethasone-induced skeletal muscle atrophy. Trimetazidine could partially alleviate dexamethasone-induced skeletal muscle atrophy, and increase the diameter of C2C12 myotubes via inhibiting pyroptosis. Thus, trimetazidine might be a potential therapeutic compound for the prevention of muscle atrophy in glucocorticoid-treated patients.

In view of the fact that the field monitoring information can more intuitively and accurately reflect the stability state of slopes, this paper takes the warning threshold of slope deformation rate monitoring as the slope stability evaluation standard, and puts forward a method for solving the safety coefficient of rocky slopes. The discrete element method 3DEC, which is suitable for rocky slopes, is selected as the numerical calculation tool, and the convergence criterion of its strength reduction method is modified to the slope deformation rate threshold, and the method is realized by the bifurcation method through its built-in FISH programming language. The results of the classical case show that, by selecting the slope deformation rate threshold in the appropriate interval, the results of this paper's method are very close to those of the finite unit stress method and the limit equilibrium method, which verifies the reliability of this paper's method. Further, the method of this paper is applied to an open-pit mine slope project, based on the slope deformation on-site monitoring data, through the time series prediction method to determine the slope deformation rate warning threshold, using the threshold as an evaluation criterion to solve the slope's coefficient of safety, the calculation results show that: the slope's coefficient of safety in natural working conditions is 1.086, basically stable, suffered from continuous rainfall, the slope body is gradually saturated, the slope's coefficient of safety is reduced to 0.987, the slope's safety is reduced to 0.987. After continuous rainfall and gradual saturation of the slope, the coefficient of safety decreased to 0.987, destabilizing and destroying, which is consistent with the site conditions.