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Abstract Background PM2.5 can induce and aggravate the occurrence and development of cardiovascular diseases (CVDs). The objective of our study is to estimate the causal effect of PM2.5 on mortality rates associated with CVDs using the instrumental variables (IVs) method. Methods We extracted daily meteorological, PM2.5 and CVDs death data from 2016 to 2020 in Binzhou. Subsequently, we employed the general additive model (GAM), two-stage predictor substitution (2SPS), and control function (CFN) to analyze the association between PM2.5 and daily CVDs mortality. Results The 2SPS estimated the association between PM2.5 and daily CVDs mortality as 1.14% (95% CI: 1.04%, 1.14%) for every 10 µg/m3 increase in PM2.5. Meanwhile, the CFN estimated this association to be 1.05% (95% CI: 1.02%, 1.10%). The GAM estimated it as 0.85% (95% CI: 0.77%, 1.05%). PM2.5 also exhibited a statistically significant effect on the mortality rate of patients with ischaemic heart disease, myocardial infarction, or cerebrovascular accidents (P

Abstract Understanding the interplay between top–down and bottom–up attention in visual working memory (VWM) is crucial, although the specific challenges arising from this interaction remain ambiguous. In this study, we address this complexity by examining how cue informativeness and probe status of the salient items influence this interaction. Through three experiments, we manipulated top–down attention by varying probe frequencies using pre-cues and bottom–up attention by varying the visual salience of memory items. Experiment 1 explored cue informativeness at 100% and 50%, while Experiments 2 and 3 maintained cue informativeness at 80% and 50%. Additionally, Experiment 1 tested a few of the salient items, Experiment 2 excluded them, and Experiment 3 tested half of them in each cue condition. Across all experiments, we consistently observed cueing benefits for cue-directed items, albeit with costs to non-cued items. Furthermore, cue informativeness and the probe status of salient items emerged as critical factors influencing the interaction between top–down and bottom–up attention in VWM. These findings underscore the pivotal roles of cue informativeness and salient item relevance in shaping the dynamics of top–down and bottom–up attention within VWM.

Abstract Stratospheric aerosol injection (SAI) aims to reflect solar radiation by increasing the stratospheric aerosol burden. To understand how the background circulation influences stratospheric transport of injected particles, we use a Lagrangian trajectory model (lacking numerical diffusion) to quantify particles’ number, flux, lifetime, and tropospheric sinks from a SAI injection strategy under present-day conditions. While particles are being injected, stratospheric particle number increases until reaching a steady-state. During the steady-state, the time series of particle number shows a dominant period of ~2 years (rather than a 1-year cycle), suggesting modulation by the quasi-biannual oscillation. More than half of particles, injected in the tropical lower stratosphere (15° S to 15° N, 65 hPa), undergo quasi-horizontal transport to the midlatitude. We find a zonal asymmetry of particles’ tropospheric sinks that are co-located with tropopause folding beneath the midlatitude jet stream, which can help predict tropospheric impacts of SAI (e.g., cirrus cloud thinning).

Abstract Single cell RNA sequencing (scRNA-seq), a powerful tool for studying the tumor microenvironment (TME), does not preserve/provide spatial information on tissue morphology and cellular interactions. To understand the crosstalk between diverse cellular components in proximity in the TME, we performed scRNA-seq coupled with spatial transcriptomic (ST) assay to profile 41,700 cells from three colorectal cancer (CRC) tumor-normal-blood pairs. Standalone scRNA-seq analyses revealed eight major cell populations, including B cells, T cells, Monocytes, NK cells, Epithelial cells, Fibroblasts, Mast cells, Endothelial cells. After the identification of malignant cells from epithelial cells, we observed seven subtypes of malignant cells that reflect heterogeneous status in tumor, including tumor_CAV1, tumor_ATF3_JUN | FOS, tumor_ZEB2, tumor_VIM, tumor_WSB1, tumor_LXN, and tumor_PGM1. By transferring the cellular annotations obtained by scRNA-seq to ST spots, we annotated four regions in a cryosection from CRC patients, including tumor, stroma, immune infiltration, and colon epithelium regions. Furthermore, we observed intensive intercellular interactions between stroma and tumor regions which were extremely proximal in the cryosection. In particular, one pair of ligands and receptors (C5AR1 and RPS19) was inferred to play key roles in the crosstalk of stroma and tumor regions. For the tumor region, a typical feature of TMSB4X-high expression was identified, which could be a potential marker of CRC. The stroma region was found to be characterized by VIM-high expression, suggesting it fostered a stromal niche in the TME. Collectively, single cell and spatial analysis in our study reveal the tumor heterogeneity and molecular interactions in CRC TME, which provides insights into the mechanisms underlying CRC progression and may contribute to the development of anticancer therapies targeting on non-tumor components, such as the extracellular matrix (ECM) in CRC. The typical genes we identified may facilitate to new molecular subtypes of CRC.

Summary: With the advancement of autonomous driving, the industrial demand for 3D object detection has continuously increased, leading to the development of anchor-based LiDAR object detectors reliant on convolutional neural networks (CNN). However, on the one hand, the poor receptive field of CNN limits the understanding of the scene. On the other hand, anchor-based methods cannot accurately predict the posture of objects in the steering. Therefore, in this paper, we propose the voxel self-attention and center-point (VSAC). Firstly, a voxel self-attention network is designed into VSAC to capture extensive voxel relationship. Secondly, considering the impact of feature weight on prediction results, the pseudo spatiotemporal feature pyramid net (PST-FPN) is proposed. Finally, we employ a center-point detection head to make the prediction direction closer to the real object during steering. The experimental results of VSAC on the widely used KITTI dataset, Waymo Open Dataset, and nuScenes dataset demonstrate its positive performance.

Rapid detection of plant phenotypic traits is crucial for plant breeding and cultivation. Traditional measurement methods are carried out by rich-experienced agronomists, which are time-consuming and labor-intensive. However, with the increasing demand for rapid and high-throughput testing in tea plants traits, digital breeding and smart cultivation of tea plants rely heavily on precise plant phenotypic trait measurement techniques, among which hyperspectral imaging (HSI) technology stands out for its ability to provide real-time and rich-information. In this paper, we provide a comprehensive overview of the principles of hyperspectral imaging technology, the processing methods of cubic data, and relevant algorithms in tea plant phenomics, reviewing the progress of applying hyperspectral imaging technology to obtain information on tea plant phenotypes, growth conditions, and quality indicators under environmental stress. Lastly, we discuss the challenges faced by HSI technology in the detection of tea plant phenotypic traits from different perspectives, propose possible solutions, and envision the potential development prospects of HSI technology in the digital breeding and smart cultivation of tea plants. This review aims to provide theoretical and technical support for the application of HSI technology in detecting tea plant phenotypic information, further promoting the trend of developing high quality and high yield tea leaves.

Abstract Transcription attenuation in response to the availability of a specific amino acid is believed to be controlled by alternative configurations of RNA secondary structures that lead to the arrest of translation or the release of the arrested ribosome from the leader mRNA molecule. In this study, we first report a possible example of the DnaA‐dependent riboswitch for transcription attenuation in Escherichia coli. We show that (i) DnaA regulates the transcription of the structural genes but not that of the leader hisL gene; (ii) DnaA might bind to rDnaA boxes present in the HisL‐SL RNA, and subsequently attenuate the transcription of the operon; (iii) the HisL‐SL RNA and rDnaA boxes are phylogenetically conserved and evolutionarily important; and (iv) the translating ribosome is required for deattenuation of the his operon, whereas tRNAHis strengthens attenuation. This mechanism seems to be phylogenetically conserved in Gram‐negative bacteria and evolutionarily important.

Introduction: Advances in machine vision and mobile electronics will be accelerated by the creation of sophisticated optoelectronic vision sensors that allow for sophisticated picture recognition of visual information and data pre-processing. Several new types of vision sensors have been devised in the last decade to solve these drawbacks, one of which is neuromorphic vision sensors, which have exciting qualities such as high temporal resolution, broad dynamic range, and low energy consumption. Neuromorphic sensors are inspired by the working principles of biological sensory neurons and would be useful in telemedicine, health surveillance, security monitoring, automatic driving, intelligent robots, and other applications of the Internet of Things.Methods: This paper provides a comprehensive review of various state-of-the-art AI vision sensors and frameworks.Results: The fundamental signal processing techniques deployed and the associated challenges were discussed.Discussion: Finally, the role of vision sensors in computer vision is also discussed.

The onset, development, diagnosis, and treatment of cancer involve intricate interactions among various factors, spanning the realms of mechanics, physics, chemistry, and biology. Within our bodies, cells are subject to a variety of forces such as gravity, magnetism, tension, compression, shear stress, and biological static force/hydrostatic pressure. These forces are perceived by mechanoreceptors as mechanical signals, which are then transmitted to cells through a process known as mechanical transduction. During tumor development, invasion and metastasis, there are significant biomechanical influences on various aspects such as tumor angiogenesis, interactions between tumor cells and the extracellular matrix (ECM), interactions between tumor cells and other cells, and interactions between tumor cells and the circulatory system and vasculature. The tumor microenvironment comprises a complex interplay of cells, ECM and vasculature, with the ECM, comprising collagen, fibronectins, integrins, laminins and matrix metalloproteinases, acting as a critical mediator of mechanical properties and a key component within the mechanical signaling pathway. The vasculature exerts appropriate shear forces on tumor cells, enabling their escape from immune surveillance, facilitating their dissemination in the bloodstream, dictating the trajectory of circulating tumor cells (CTCs) and playing a pivotal role in regulating adhesion to the vessel wall. Tumor biomechanics plays a critical role in tumor progression and metastasis, as alterations in biomechanical properties throughout the malignant transformation process trigger a cascade of changes in cellular behavior and the tumor microenvironment, ultimately culminating in the malignant biological behavior of the tumor.

Background The competencies of medical staff in the public health emergency system and evaluated the effects of system-based professional training were investigated. Material and Methods A competency model for individuals in a public health emergency management system was developed, which contained 33 items with 5 domains. A competency-based intervention was performed. A total of 68 participants from 4 health emergency teams in Xinjiang, China were recruited and randomly divided into 2 groups: the intervention (N = 38) and control groups (N = 30). Participants in the intervention group received competency-based training, while those in the control group received no training. All participants responded to the COVID-19 activities. The competencies of medical staff in the 5 domains were then analyzed in the pre-intervention, post-first training, and post-COVID-19 intervention using a self-designed questionnaire. Results Participants’ competencies were at the middle level at baseline. After the first training, competencies in the 5 domains significantly improved in the intervention group; in the control group, there was a significant increase in professional quality compared in the pre-training. After the response to COVID-19, the mean scores of competencies in the 5 domains significantly increased in both the intervention and control groups compared with those in the post-first training. Psychological resilience scores were higher in the intervention group than in the control group, whereas no significant differences in competencies were found in other domains. Conclusions Competency-based interventions provided practice and showed a positive effect on improving the competencies of medical staff in public health teams. Med Pr. 2023;74(1):19–26

Penalized Cox regression can efficiently be used for the determination of biomarkers in high-dimensional genomic data related to disease prognosis. However, results of Penalized Cox regression is influenced by the heterogeneity of the samples who have different dependent structure between survival time and covariates from most individuals. These observations are called influential observations or outliers. A robust penalized Cox model (Reweighted Elastic Net-type maximum trimmed partial likelihood estimator, Rwt MTPL-EN) is proposed to improve the prediction accuracy and identify influential observations. A new algorithm AR-Cstep to solve Rwt MTPL-EN model is also proposed. This method has been validated by simulation study and application to glioma microarray expression data. When there were no outliers, the results of Rwt MTPL-EN were close to the Elastic Net (EN). When outliers existed, the results of EN were impacted by outliers. And whenever the censored rate was large or low, the robust Rwt MTPL-EN performed better than EN. and could resist the outliers in both predictors and response. In terms of outliers detection accuracy, Rwt MTPL-EN was much higher than EN. The outliers who "lived too long" made EN perform worse, but were accurately detected by Rwt MTPL-EN. Through the analysis of glioma gene expression data, most of the outliers identified by EN were those "failed too early", but most of them were not obvious outliers according to risk estimated from omics data or clinical variables. Most of the outliers identified by Rwt MTPL-EN were those who "lived too long", and most of them were obvious outliers according to risk estimated from omics data or clinical variables. Rwt MTPL-EN can be adopted to detect influential observations in high-dimensional survival data.

Biopsy is recommended for definitive diagnosis of liver carcinoma, however, this process requires staining and expert pathologists to confirm diagnosis. Here, the authors employ a portable Raman spectroscopy system combined with deep learning to detect carcinoma from normal tissue in real time.

IntroductionThe identification and localization of tea picking points is a prerequisite for achieving automatic picking of famous tea. However, due to the similarity in color between tea buds and young leaves and old leaves, it is difficult for the human eye to accurately identify them.MethodsTo address the problem of segmentation, detection, and localization of tea picking points in the complex environment of mechanical picking of famous tea, this paper proposes a new model called the MDY7-3PTB model, which combines the high-precision segmentation capability of DeepLabv3+ and the rapid detection capability of YOLOv7. This model achieves the process of segmentation first, followed by detection and finally localization of tea buds, resulting in accurate identification of the tea bud picking point. This model replaced the DeepLabv3+ feature extraction network with the more lightweight MobileNetV2 network to improve the model computation speed. In addition, multiple attention mechanisms (CBAM) were fused into the feature extraction and ASPP modules to further optimize model performance. Moreover, to address the problem of class imbalance in the dataset, the Focal Loss function was used to correct data imbalance and improve segmentation, detection, and positioning accuracy.Results and discussionThe MDY7-3PTB model achieved a mean intersection over union (mIoU) of 86.61%, a mean pixel accuracy (mPA) of 93.01%, and a mean recall (mRecall) of 91.78% on the tea bud segmentation dataset, which performed better than usual segmentation models such as PSPNet, Unet, and DeeplabV3+. In terms of tea bud picking point recognition and positioning, the model achieved a mean average precision (mAP) of 93.52%, a weighted average of precision and recall (F1 score) of 93.17%, a precision of 97.27%, and a recall of 89.41%. This model showed significant improvements in all aspects compared to existing mainstream YOLO series detection models, with strong versatility and robustness. This method eliminates the influence of the background and directly detects the tea bud picking points with almost no missed detections, providing accurate two-dimensional coordinates for the tea bud picking points, with a positioning precision of 96.41%. This provides a strong theoretical basis for future tea bud picking.

Abstract Stratospheric Aerosol Injection (SAI) aims to offset some climate hazards by injecting aerosols into the stratosphere to reflect solar radiation. The lifetime of injected particles influences SAI's radiative efficacy—the ratio of radiative forcing to particle mass flux. We employ a Lagrangian trajectory model with particle sedimentation to simulate how background circulations influence the transport of passive particles (without microphysical growth) in the stratosphere and quantify sensitivities of particle lifetime to injection locations. At 20 km, optimizing injection locations can increase particle lifetime by >40%. Injection strategies can be constrained to maintain an interhemispheric balance of particle lifetime without significantly decreasing total lifetime. Generally, increasing injection altitude increases particle lifetime while also increasing costs and environmental impacts of deployment aircraft. Optimizing injection latitude and longitude can relax this altitude‐lifetime trade‐off by increasing lifetime without needing to increase altitude, which warrants further testing in global climate models with aerosol microphysics.

In the present research, a new optimal approach is suggested for optimal parameters estimation of the mathematical model in the Solid Oxide Fuel Cell (SOFC) stacks. The main purpose is to propose a method for minimization of the Sum of Squared Error (SSE) of the polarization profile of the estimated model with the extracted data from the experimental simulations. To realize this aim, a new metaheuristic technique, namely the Adaptive African vulture optimization (AAVO) algorithm is offered. The method is then verified with a comparison of its results with various approaches introduced in the literature. Finally, to confirm the approach’s effectiveness, this is investigated by sensitivity analysis by various pressure and temperature changes, and its achievements are put in comparison to different approaches introduced in the literature to show the superiority of the proposed method. The final achievement designates that the suggested approach with a minimum value of 7.85e−4 with 6.14e−4 standard deviation SSE for the temperature variations and 1.28e−3 with 2.15e−5 standard deviation SSE for the pressure variations has the best results for optimal estimation of the unknown parameters in the SOFC stacks.

Leaf development underlies crop growth and productivity and has been a major target of crop domestication and improvement. However, most genes controlling leaf development in barley remain unknown. We identified a dwarf and liguleless (dl) mutant derived by ethylmethane sulfonate mutagenesis. The dl mutant showed dramatic changes in shoot architecture compared with wild-type (Yangnongpi 5) plants. Besides lacking ligules, the dl mutant showed much shorter plant height (28 cm) than Yangnongpi 5 (78 cm). By map-based cloning, the dl gene was localized to a 56.58-kb genomic interval on the long arm of chromosome 7. A C-to-T single-nucleotide substitution was identified at exon position 790, and is a functional mutation resulting in a proline-to-serine substitution at the 264th amino acid residue of HORVU7Hr1G106960. Consequently, HORVU7Hr1G106960 was identified as the DL gene, encoding 269 amino acids and containing the Arabidopsis LSH1 and Oryza G1 (ALOG) domain. DL is highly similar to rice OsG1-LIKE 1/2 (OsG1L1/2) and sorghum AWN1/AWN1-10 at the amino acid level. Although the dl mutant allele showed no expression changes in selected tissues by real-time PCR, we propose HORVU7Hr1G106960 as a candidate gene conferring the dwarf and liguleless phenotype in barley.

Abstract Background In the present study, we attempted to develop and validate a participatory competency model for medical workers and then evaluate the current status of competency characteristics of Chinese medical workers. Methods The competency model was constructed in a multistage process, including literature review, expert consultation, critical incident and focus group interview. A pilot study was conducted to refine the initial model among 90 participators and the viability and reliability were evaluated by a questionnaire survey among 121 medical workers. Then, the current status of competency characteristics was measured based on the final version of competency model. Results In the pilot study, ten questionnaires were dropped for the poor quality and thus the eligible rate was 92% (138/150). KMO value was 0.785 and Bartlett test showed that the χ2 = 6464.546 (df = 903) and p value

Objective: This study aimed to identify the different associations between antiarrhythmic drugs (AADs) and arrhythmias, and to determine whether pharmacokinetic drug interactions involving AADs increase the risk of AAD-related arrhythmias compared to using AADs alone.Materials and methods: The disproportionality analysis of AAD-associated cardiac arrhythmias, including AAD monotherapies and concomitant use of pharmacokinetic interacting agents involving AADs, was conducted by using reporting odds ratio (ROR) and information component (IC) as detection of potential safety signals based on FAERS data from January 2016 to June 2022. We compared the clinical features of patients reported with AAD–associated arrhythmias between fatal and non-fatal groups, and further investigated the onset time (TTO) following different AAD regimens.Results: A total of 11754 AAD–associated cardiac arrhythmias reports were identified, which was more likely to occur in the elderly (52.17%). Significant signals were detected between cardiac arrhythmia and all AAD monotherapies, with ROR ranging from 4.86 with mexiletine to 11.07 with flecainide. Regarding four specific arrhythmias in High Level Term (HLT) level, the AAD monotherapies with the highest ROR were flecainide in cardiac conduction disorders (ROR025 = 21.18), propafenone in rate and rhythm disorders (ROR025 = 10.36), dofetilide in supraventricular arrhythmias (ROR025 = 17.61), and ibutilide in ventricular arrhythmias (ROR025 = 4.91). Dofetilide/ibutilide, ibutilide, mexiletine/ibutilide and dronedarone presented no signal in the above four specific arrhythmias respectively. Compared with amiodarone monotherapy, sofosbuvir plus amiodarone detected the most significantly increased ROR in arrhythmias.Conclusion: The investigation showed the spectrum and risk of AAD–associated cardiac arrhythmias varied among different AAD therapies. The early identification and management of AAD-associated arrhythmias are of great importance in clinical practice.

(1) Background: Rapid and accurate determination of the content of the chemical dye Auramine O(AO) in traditional Chinese medicines (TCMs) is critical for controlling the quality of TCMs. (2) Methods: Firstly, various models were developed to detect AO content in Dendrobium officinale (D. officinale). Then, the detection of AO content in Saffron and Curcuma using the D. officinale training set as a calibration model. Finally, Saffron and Curcuma samples were added to the training set of D. officinale to predict the AO content in Saffron and Curcuma using secondary wavelength screening. (3) Results: The results show that the sparrow search algorithm (SSA)-backpropagation (BP) neural network (SSA-BP) model can accurately predict AO content in D. officinale, with Rp2 = 0.962, and RMSEP = 0.080 mg/mL. Some Curcuma samples and Saffron samples were added to the training set and after the secondary feature wavelength screening: The Support Vector Machines (SVM) quantitative model predicted Rp2 fluctuated in the range of 0.780 ± 0.035 for the content of AO in Saffron when 579, 781, 1195, 1363, 1440, 1553 and 1657 cm−1 were selected as characteristic wavelengths; the Partial Least Squares Regression (PLSR) model predicted Rp2 fluctuated in the range of 0.500 ± 0.035 for the content of AO in Curcuma when 579, 811, 1195, 1353, 1440, 1553 and 1635 cm−1 were selected as the characteristic wavelengths. The robustness and generalization performance of the model were improved. (4) Conclusion: In this study, it has been discovered that the combination of surface-enhanced Raman spectroscopy (SERS) and machine learning algorithms can effectively and promptly detect the content of AO in various types of TCMs.

Objectives: The purpose of this study was to explore the association between multiple chronic conditions (MCCs) and depressive symptoms among older adults in China.Methods: We used the fourth round of data from the China Health and Retirement Longitudinal Study, and included 9789 older adults aged 60 years old and above.Results: Compared with the older adults without chronic disease, older adults with MCCs and those with one chronic disease had a high risk of depression (MCCs: OR-adjusted: 1.55, 95% CI: 1.37 to 1.75; one chronic disease: OR-adjusted: 1.20, 95% CI: 1.05–1.37). In urban areas, the prevalence among older adults with MCCs was 2.01 times higher than that among older adults without chronic disease (OR-adjusted: 2.01, 95% CI: 1.56–2.60), while it was 1.44 times higher in rural areas (OR-adjusted:1.44, 95% CI: 1.25–1.65). Self-reported health, duration of sleep, social activities, and type of medical insurance were the influencing factors of depressive symptoms in older adults.Conclusion: This study contributed to enriching the research on the relationship between MCCs and depressive symptoms in older adults in China.

Introduction: The proper operation of wastewater treatment plants is a key factor in maintaining a stable river and lake environment. Low purification efficiency in winter is a common problem in high-altitude wastewater treatment plants (WWTPs), and analysis of the microbial community involved in the sewage treatment process at high-altitude can provide valuable references for improving this problem.Methods: In this study, the bacterial communities of high- and low-altitude WWTPs were investigated using Illumina high-throughput sequencing (HTS). The interaction between microbial community and environmental variables were explored by co-occurrence correlation network.Results: At genus level, Thauera (5.2%), unclassified_Rhodocyclaceae (3.0%), Dokdonella (2.5%), and Ferribacterium (2.5%) were the dominant genera in high-altitude group. The abundance of nitrogen and phosphorus removal bacteria were higher in high-altitude group (10.2% and 1.3%, respectively) than in low-altitude group (5.4% and 0.6%, respectively). Redundancy analysis (RDA) and co-occurrence network analysis showed that altitude, ultraviolet index (UVI), pH, dissolved oxygen (DO) and total nitrogen (TN) were the dominated environmental factors (p < 0.05) affecting microbial community assembly, and these five variables explained 21.4%, 20.3%, 16.9%, 11.5%, and 8.2% of the bacterial assembly of AS communities.Discussion: The community diversity of high-altitude group was lower than that of low-altitude group, and WWTPs of high-altitude aeras had a unique microbial community structure. Low temperature and strong UVI are pivotal factors contributing to the reduced diversity of activated sludge microbial communities at high-altitudes.

In this paper, aiming at the problem of high-precision trajectory tracking of the gantry welding robot system under the influence of uncertain factors, a composite adaptive fuzzy compensation controller based on the computed torque control strategy has been proposed. The controller is composed of an adaptive fuzzy feedback control strategy and a dead zone adaptive fuzzy control strategy, which realizes high-precision trajectory tracking of the gantry welding robot, improves the solving speed of the control algorithm, and its tracking errors has been reduced. Screw theory and Lie group lie algebra are used to solve the problem of high algorithm complexity of controllers in multi-degree-of-freedom robot systems due to Newton-Euler dynamics modeling. Based on the computed torque control, the adaptive fuzzy feedback control strategy is adopted to compensate for the modeling errors and external disturbances in the gantry welding robot system, and the dead zone adaptive fuzzy control strategy is designed to compensate for the nonlinear dead zone structure with unknown parameters. The Lyapunov equation is introduced to prove the stability of the controller. Finally, the controller designed in this paper is compared with the conventional controller through simulation and experiment on the gantry welding robot platform, which verifies the effectiveness and superiority of the controller.

Abstract Hypoxia causes neonatal neuronal damage. However, the underlying mechanism remains unclear. This study aimed to explore the changes in succinate levels and identify the mechanisms underlying their contribution to hypoxia-induced damage in newborn mice. The neonatal C57BL/6J mouse hypoxia model was used in our study. We evaluated the levels of succinate, iron, reactive oxygen species (ROS), and mitochondrial ROS, and assessed mitophagy, neuronal damage, and learning and memory function, after hypoxia treatment. The neonatal mice showed increased succinate levels in the early hypoxia stage, followed by increased levels of oxidative stress, iron stress, neuronal damage, and cognitive deficits. Succinate levels were significantly reduced following treatment with inhibitors of succinate dehydrogenase (SDH), purine nucleotide cycle (PNC), and malate/aspartate shuttle (MAS), with the corresponding attenuation of oxidative stress, iron stress, neuronal damage, and cognitive impairment. Reversal catalysis of SDH through fumarate from the PNC and MAS pathways might be involved in hypoxia-induced succinate accumulation. Succinate accumulation in the early period after hypoxia may crucially contribute to oxidative and iron stress. Relieving succinate accumulation at the early hypoxia stage could prevent neuronal damage and cognitive impairment in neonatal hypoxia.

Abstract Background Cervical cancer is the most fatal gynecological carcinoma in the world. It is urgent to explore novel prognostic biomarkers and intervention targets for cervical cancer. Methods Through integrated quantitative proteomic strategy, we investigated the protein expression profiles of cervical cancer; 28 fresh frozen tissue samples (11 adenocarcinoma (AC), 12 squamous cell carcinoma (SCC) and 5 normal cervixes (HC)) were included in discover cohort; 45 fresh frozen tissue samples (19 AC, 18 SCC and 8 HC) were included in verification cohort; 140 paraffin-embedded tissues samples of cervical cancer (85 AC and 55 SCC) were used for immunohistochemical evaluation (IHC) of coatomer protein subunit alpha (COPA) as a prognostic biomarker for cervical cancer; how deficiency of COPA affects cell viability and tumorigenic ability of cervical cancer cells (SiHa cells and HeLa cells) were evaluated by cell counting kit-8 and clone formation in vitro. Results We identified COPA is a potential prognostic biomarker for cervical cancer in quantitative proteomics analysis. By retrospective IHC analysis, we additionally verified the proteomics results and demonstrated moderate or strong IHC staining for COPA is an unfavourable independent prognostic factor for cervical cancer. We also identified COPA is a potential pharmacological intervention target of cervical cancer by a series of in vitro experiments. Conclusion This study is the first to demonstrate that COPA may contribute to progression of cervical cancer. It can serve as a potential prognostic biomarker and promising intervention target for cervical cancer.

Tea bud target detection is essential for mechanized selective harvesting. To address the challenges of low detection precision caused by the complex backgrounds of tea leaves, this paper introduces a novel model called Tea-YOLOv8s. First, multiple data augmentation techniques are employed to increase the amount of information in the images and improve their quality. Then, the Tea-YOLOv8s model combines deformable convolutions, attention mechanisms, and improved spatial pyramid pooling, thereby enhancing the model’s ability to learn complex object invariance, reducing interference from irrelevant factors, and enabling multi-feature fusion, resulting in improved detection precision. Finally, the improved YOLOv8 model is compared with other models to validate the effectiveness of the proposed improvements. The research results demonstrate that the Tea-YOLOv8s model achieves a mean average precision of 88.27% and an inference time of 37.1 ms, with an increase in the parameters and calculation amount by 15.4 M and 17.5 G, respectively. In conclusion, although the proposed approach increases the model’s parameters and calculation amount, it significantly improves various aspects compared to mainstream YOLO detection models and has the potential to be applied to tea buds picked by mechanization equipment.

Abstract Blockchain technology has the characteristics of decentralization and tamper resistance, which can store data safely and reduce the cost of trust effectively. However, the existing blockchain system has weak performance in data management, and only supports traversal queries with transaction hashes as keywords. The query method based on the account transaction trace chain (ATTC) improves the query efficiency of historical transactions of the account. However, the efficiency of querying accounts with longer transaction chains has not been effectively improved. Given the inefficiency and single method of the ATTC index in the query, we propose a subchain-based account transaction chain (SCATC) index structure. First, the account transaction chain is divided into subchains, and the last block of each subchain is connected by a hash pointer. The block-by-block query mode in ATTC is converted to the subchain-by-subchain query mode, which shortens the query path. Multiple transactions of the same account in the same block are merged and stored, which simplifies the construction cost of the index and saves storage resources. then, the construction algorithm and query algorithm is given for the SCATC index structure. Simulation analysis shows that the SCATC index structure significantly improves query efficiency.

Dendrobium candidum (DC) is an agricultural product for both food and medicine. It has a variety of beneficial effects on the human body with antioxidant, anti-inflammatory, antitumor, enhancing immune function, and other pharmacological activities. Due to less natural distribution, harsh growth conditions, slow growth, low reproduction rate, and excessive logging, wild DC has been seriously damaged and listed as an endangered herbal medicine variety in China. At present, the quality of DC was uneven in the market, so it is very necessary to detect its quality. This article summarized the methods of DC quality detection with traditional and rapid nondestructive, and it also expounded the correlation between DC quality factor and endophytes, which provides a theoretical basis for a variety of rapid detection methods in macromolecules. At last, this article put forward a variety of rapid nondestructive detection methods based on the emission spectrum. In view of the complexity of molecular structure, the quality correlation established by spectral analysis was greatly affected by varieties and environment. We discussed the possibility of DC quality detection based on the molecular dynamic calculation and simulation mechanism. Also, a multimodal fusion method was proposed to detect the quality. The literature review suggests that it is very necessary to understand the structure performance relationship, kinetic properties, and reaction characteristics of chemical substances at the molecular level by means of molecular chemical calculation and simulation, to detect a certain substance more accurately. At the same time, several modes are combined to form complementarity, eliminate ambiguity, and uncertainty and fuse the information of multiple modes to obtain more accurate judgment results.

Post-traumatic stress disorder (PTSD) is a debilitating mental disorder with high morbidity and great social and economic relevance. However, extant pharmacotherapies of PTSD require long-term use to maintain effectiveness and have enormous side effects. The glutamatergic system, especially the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR), is an important target of current research on the mechanism of PTSD. Postsynaptic AMPAR function and expression are known to be increased by (2R, 6R)-hydronorketamine (HNK), the primary metabolite of ketamine. However, whether (2R,6R)-HNK alleviates PTSD-like effects via AMPAR upregulation is yet to be known.In the present study, rats were exposed to single prolonged stress and electric foot shock (SPS&S). Afterwards, gradient concentrations of (2R,6R)-HNK (20, 50, and 100 μM) were administered by intracerebroventricular (i.c.v.) injection. Open field, elevated plus maze, freezing behavior, and forced swimming tests were used to examine PTSD-like symptoms. In addition, the protein levels of GluA1, BDNF and PSD-95 were analyzed using western blotting and immunofluorescence, and the synaptic ultrastructure of the prefrontal cortex (PFC) was observed by transmission electron microscopy.We found that (2R,6R)-HNK changed SPS&S-induced behavioral expression, such as increasing autonomous activity and residence time in the open arm and decreasing immobility time. Likewise, (2R,6R)-HNK (50 μM) increased GluA1, BDNF, and PSD-95 protein expression in the PFC. Changes in synaptic ultrastructure induced by SPS&S were reversed by administration of (2R,6R)-HNK. Overall, we find that (2R,6R)-HNK can ameliorate SPS&S-induced fear avoidance in rats, as well as rat cognates of anxiety and depression. This may be related to GluA1-mediated synaptic plasticity in the PFC.

The cell wall plays an important role in plant mechanical strength. Cellulose is the major component of plant cell walls and provides the most abundant renewable biomass resource for biofuels on earth. Mutational analysis showed that cellulose synthase (CESA) genes are critical in cell wall biosynthesis in cereal crops like rice. However, their role has not been fully elucidated in barley. In this study, we isolated a brittle culm mutant brittle culm 3 (bc3) derived from Yangnongpi 5 ethyl methanesulfonate (EMS) mutagenesis in barley. The bc3 mutants exhibited reduced mechanical strength of the culms due to impaired thickening of the sclerenchyma cell wall and reduced cellulose and hemicellulose content in the culms. Genetic analysis and map-based cloning revealed that the bc3 mutant was controlled by a single recessive gene and harbored a point mutation in the HvCESA5 gene, generating a premature stop codon near the N-terminal of the protein. Quantitative real-time PCR (qRT-PCR) analysis showed that the HvCESA5 gene is predominantly expressed in the culms and co-expressed with HvCESA4 and HvCESA8, consistent with the brittle culm phenotype of the bc3 mutant. These results indicate that the truncated HvCESA5 affects cell wall biosynthesis leading to a brittle culm phenotype. Our findings provide evidence for the important role of HvCESA5 in cell wall biosynthesis pathway and could be a potential target to modify cell wall in barley.

Immunity plays an important role in tumor development. In this study, we aimed to investigate molecular classification and its prognostic value in hepatocellular carcinoma (HCC) based on immune signature. Gene set enrichment analysis (GSEA) was used to calculate scores of immune pathways for HCC and hierarchical clustering in two databases (The Cancer Genome Atlas [TCGA], Liver Cancer-RIKEN, JP [LIRI_JP]). The scores of the immune microenvironment and the proportions of 22 immune cells were also calculated. Single-sample GSEA (ssGSEA) was used to screen survival prognosis-related immune pathways and calculate the hazard radio of differentially expressed immune-related genes (IRGs), which were validated in clinical samples and multiple datasets. Based on the immune characteristics, we identified three HCC subtypes, namely immunity high (Immunity_H), immunity medium (Immunity_M), and immunity low (Immunity_L), and confirmed that the classification was reliable and predictable. Immunity_H with a higher immune and stromal score indicated better survival rate. Cox regression analysis showed that IL18RAP and IL7R were the protective genes. Immune risk score was the independent risk factor of overall survival in HCC patients. These results indicated that immunogenomic classification could distinguish HCC patients with different immune status, which could impact the prognosis of the patients with HCC.

To improve its ductility and clarify the mechanism, the AlSi7Mg alloy fabricated by a novel casting-forging process was solid-soluted at 535 °C for 5 h, followed by aging at 170 °C for 2 h. Phase component, microstructure were observed and mechanical properties were tested. The results show that the alloy contains Al, Si and Al–Si intermetallics. The eutectic Si particles present equiaxed and the Al–Si precipitations present filamentous morphorgy in the alloy. The eutectic Si particles present quasi-continuous network distribution, dividing the matrix into equiaxed units. When the deformation degree increased from 15% to 35%, the units are refined and the precipitation of Al–Si intermetallics is prevented. The difference of ultimate strength between surface and center was decreased, while the elongation improved obviously with the increase of deformation degree. The most excellent elongation reached 12% when the deformation degree was 35%, with the improvement of 7%. The improvement of ductility is owed to the fine, equiaxed eutectic Si particles, the refined units and the prevented precipitations.

Abstract The purpose of this study was to examine the changes in severity of anxiety and depression symptoms, stress and sleeping quality after three months of mass quarantine for COVID-19 among undergraduate fresh students compared to their pre-COVID-19 measures. We used participants from the Chinese Undergraduate Cohort (CUC), a national prospective longitudinal study to examine the changes in anxiety and depression symptoms severity, stress and sleep quality after being under mass quarantine for three months. Wilcoxon matched pair signed-rank test was used to compare the lifestyle indicators. Severity of anxiety, depression symptoms, stress and sleep quality were compared with Wilcoxon signed-rank test. We used generalized estimating equation (GEE) to further quantify the change in mental health indicators and sleep quality after the COVID-19 mass quarantine compared to baseline. This study found that there was no deterioration in mental health status among Chinese new undergraduate students in 2020 after COVID-19 mass quarantine compared with the baseline measures in 2019. There was an improvement in sleep quality and anxiety symptoms. After adjusting for age, sex, exercise habit, time spent on mobile gadgets, and time spent outdoors, year 2020 was significantly associated with severity of depression symptoms in males (OR:1.52. 95%CI:1.05–2.20, p-value = 0.027). Year 2020 was significantly associated with the improvement of sleeping quality in total (OR:0.45, 95%CI:0.38–0.52, p

Abstract Bacillus thuringiensis (Bt) is an important biological insecticide used to management of different agricultural pests by producing toxic parasporal crystals proteins. Strain HD521 has an antagonistic effect against Rhizoctonia solani AG1IA, the causal agent of rice sheath blight. This strain with three cry7 genes can the formation of bipyramidal parasporal crystals (BPCs). BPCs are used for insecticidal activities against Henosepilachna vigintioctomaculata larva (Coleoptera). Strain HS18-1 contains different types of BPCs encoding genes and has effective toxicity for Lepidoptera and Diptera insects. Here we report the whole genome sequencing and assembly of HD521 and HS18-1 strains and analyzed the genome constitution covering virulence factors, types of plasmid, insertion sequences, and prophage sequences. The results showed that the genome of strain HD521 contains a circular chromosome and six circular plasmids, encoding eight types of virulence protein factors [Immune Inhibitor A, Hemolytic Enterotoxin, S-layer protein, Phospholipase C, Zwittermicin A-resistance protein, Metalloprotease, Chitinase, and N-acyl homoserine lactonase (AiiA)], four families of insertion sequence, and comprises six pro-phage sequences. The genome of strain HS18-1 contains one circular chromosome and nine circular plasmids, encoding five types of virulence protein factors [Hemolytic Enterotoxin, S-layer protein, Phospholipase C, Chitinase, and N-acyl homoserine lactonase (AiiA)] and four families of insertion sequence, and comprises of three pro-phage sequences. The obtained results will contribute to deeply understand the B. thuringiensis strain HD521 and HS18-1 at the genomic level.

IntroductionMental health nurses are often exposed to stressful events which may lead to feeling of stress in their daily work, and this feeling has a profound impact on nurses' mental health.AimThis study aimed to evaluate the relationship between job stress, thinking style and symptoms of post-traumatic stress disorder (PTSD) of mental health nurses, and to explore the mechanism of job stress and thinking style on symptoms of PTSD.MethodThis cross-sectional study collected related data of 351 mental health nurses in China, and the data was analyzed by PROCESS macro for SPSS.ResultsThe results showed that 18.2% of mental health nurses had the symptoms of PTSD. Thinking style (monarchic thinking style, anarchic thinking style and external thinking style) played a moderating role in the predictive effects of job stress on the symptoms of PTSD.DiscussionThe research pointed out the relationship between job stress and symptom of PTSD, and clarified the critical role of thinking style among mental health nurses.Implications for practiceIt is recommended that organizations should enact effective policy and intervention programs to reduce job stress and PTSD symptoms of mental health nurses which may improve their mental health level.

With the increasing popularity of modular buildings, many manufacturers have made BIM objects for use by designers. However, these BIM objects must satisfy specific regulations and requirements, and their quality needs to be verified. In this study, the authors propose an automated checking system for modular BIM object quality verification. The system includes three parts, which are modular BIM object guideline, pre-checking module and automated code checking module. The modular BIM object quality verification system is proposed to be applied to government modular product certification site for checking the modular BIM objects. It is expected that the use of this automated checking system will make it possible to connect users and manufacturers to promote the circulation of modular building products, as well as provide designers with standardized modular BIM objects for design purposes.

The clinical efficacy of current therapies for Hepatocellular carcinoma (HCC) are unsatisfactory. In recent years, chimeric antigen receptor (CAR) T-cell therapies have been developed for solid tumors including advanced HCC (aHCC), but limited progress has been made. Glypican-3 is a promising immunotherapeutic target for HCC since it is specifically highly expressed in HCC. A previous study indicated that GPC3-targeted CAR T-(CAR-GPC3) cells were well-tolerated and had prolonged survival for HCC patients and that Sorafenib could increase the antitumor activities of CAR-GPC3 T-cells against HCC in mouse models. Here, we report a patient with aHCC who achieved a complete response (CR) and a long survival period after the combination therapy of CAR-GPC3 T-cell plus sorafenib.A 60-year-old Asian male diagnosed with hepatitis B virus (HBV) related HCC developed liver recurrence and lung metastasis after liver tumor resection and trans-arterial chemoembolization therapy. The patient also previously received microwave ablation therapy for lung metastasis. After the enrollment, the patient underwent leukapheresis for CAR-GPC3 T-cells manufacturing. Seven days after leukapheresis, the patient started to receive 400 mg of Sorafenib twice daily. The patient received 4 cycles of CAR-GPC3 T cells (CT011) treatment and each cycle was divided into two infusions. Prior to each cycle of CT011 treatment, lymphodepletion was performed. The lymphodepletion regimen was cyclophosphamide 500 mg/m2/day for 2 to 3 days, and fludarabine 20-25 mg/m2/day for 3 to 4 days. A total of 4×109 CAR-GPC3 T cells were infused. The CT011 plus Sorafenib combination therapy was well tolerated. All the ≥ grade 3 AEs were hematological toxicities which were deemed an expected event caused by the preconditioning regimen. This patient obtained partial responses from the 3rd month and achieved CR in the 12th month after the first cycle of CT011 infusion according to the RECIST1.1 assessment. The tumor had no progression for more than 36 months and maintained the CR status for more than 24 months after the first infusion.

In shipbuilding, welds in sub-assemblies and unit-assemblies are long and various type. The robot arm needs the gantry movement to cooperate with the welding operation. However, there are joint redundancy and double-arm coordination problems, which cause difficulties in the welding trajectory planning. This paper proposes a strategy of decoupling the dual-arm system into a single-arm system for separate planning and prioritizing joint motion, and conducts welding trajectory planning research based on Matlab’s Simscape Multibody. Firstly, the 3D model of the welding workstation is established, its structure, the operation mode of the joint link and the degree of freedom are analyzed. The 17-DOF welding workstation is decoupled into a single-arm 9-DOF system, a kinematic model is established, kinematic analysis is carried out. The Matlab robot toolbox is used for simulation verification. Then the discretization of weld types and poses in sub-assemblies and unit-assemblies workpieces is analyzed. Finally, the welding workstation and workpiece model are imported into Simscape Multibody of Matlab to simulate the trajectory planning of different types of welds. The simulation results prove the effectiveness of the strategy and have certain reference significance for on-site welding in shipbuilding.

PurposeThe main purpose of our systematic review was to investigate the effect of peer-led intervention on self-stigma in individuals with mental health problems. Secondary purpose was investigating the impact of peer intervention on clinical symptoms, recovery-related outcomes, and disclosure-related outcomes.MethodsFive electronic databases were searched from 1975 to 2021. Literature databases were searched for randomized controlled trials. From the perspective of key outcomes, a meta-analysis of the effects of peer-led interventions on changing stigma was conducted.ResultsA meta-analysis of randomized controlled trials targeting different target groups with mental health problems (e.g., adolescents, college students, family members of mentally ill persons, unemployed persons, etc.) was conducted. It was found that, at the end of the intervention, intervention had a positive effect on main outcomes such as self-stigma and stress from stigma. As for secondary outcomes, there was no significant influence on clinical symptoms. There was a positive effect on rehabilitation and empowerment, but without a statistical significance. There was a statistically significant effect on self-efficacy and professional help seeking. There was a statistically significant effect on confidentiality and disclosure-related distress in the Honest Open Proud (HOP) subgroup. There was no significant influence on confidentiality and withdrawal in the non-HOP subgroup.ConclusionPeer-led intervention can reduce self-stigma and stigma pressure and might improve recovery and empowerment. It increases self-efficacy and willingness to seek professional help, but has no significant effect on clinical symptoms and withdrawal. HOP intervention has positive effects on disclosure-related confidentiality and pain.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier: CRD42021287584.

Aiming at the problem that the traditional inverse solution optimization method is not comprehensive and does not consider the robot structure and actual working conditions, an inverse solution multi-objective optimization method is proposed. This method comprehensively considers the structural size and working state of the welding robot, establishes the stiffness performance evaluation index, optimizes the performance index of the subsequent connecting rod movement area caused by joint rotation, and selects the optimal inverse solution combined with the principle of “minimum joint displacement.” Compared with the traditional method, this method is more comprehensive. It makes the variation range of the rear three small joints of the welding robot larger than the front three large joints, which reduces the power consumption. In addition, it also improves the stiffness of the welding robot at the trajectory point, which ensures the reliability of the welding robot. On this basis, for linear and arc welds, the position interpolation of cartesian space line and arc trajectory based on the S-shaped acceleration and deceleration curve and the posture interpolation of spherical linear interpolation based on unit quaternion are realized. MATLAB simulation results show that the combination of the inverse optimization method and the interpolation method makes the end trajectory, velocity, acceleration, posture curve, and joint displacement curve of the welding robot continuous, smooth, and without mutation.

Artificial modification of Bacillus thuringiensis (Bt) proteins can effectively improve their resistance to target pests, but the effect of such modification on the diversity of rhizosphere microorganisms remains unclear. Transgenic maize 2A-7 contains two artificially modified Bt proteins, mCry1Ab and mCry2Ab. These proteins can enter soil and pose a potential threat to soil microbial diversity. To assess their impacts on rhizosphere bacteria communities, the contents of the two Bt proteins and changes in bacterial community diversity in the rhizosphere soils of transgenic maize 2A-7 and its control variety were analyzed at different growth stages in 2020. The results showed that the two Bt proteins were detected at low levels in the rhizosphere soils of 2A-7 plants. No significant differences in soil bacterial diversity were detected between 2A-7 and its control variety at any of the growth stages. Bioinformatics analysis indicated that the growth stage, rather than the cultivar, was the main factor causing changes in bacterial communities. This research provides valuable data for understanding the impact of Bt crops on the soil microbiome, and establishes a theoretical basis for evaluation of their safety.

Chloroquine phosphate (CQP) is effective in treating coronavirus disease 2019 (COVID-19); thus, its usage is rapidly increasing, which may pose a potential hazard to the environment and living organisms. However, there are limited findings on the removal of CQP in water. Herein, iron and magnesium co-modified rape straw biochar (Fe/Mg-RSB) was prepared to remove CQP from the aqueous solution. The results showed that Fe and Mg co-modification enhanced the adsorption efficiency of rape straw biochar (RSB) for CQP with the maximum adsorption capacity of 42.93 mg/g (at 308 K), which was about two times higher than that of RSB. The adsorption kinetics and isotherms analysis, as well as the physicochemical characterization analysis, demonstrated that the adsorption of CQP onto Fe/Mg-RSB was caused by the synergistic effect of pore filling, π-π interaction, hydrogen bonding, surface complexation, and electrostatic interaction. In addition, although solution pH and ionic strength affected the adsorption performance of CQP, Fe/Mg-RSB still had a high adsorption capability for CQP. Column adsorption experiments revealed that the Yoon–Nelson model better described the dynamic adsorption behavior of Fe/Mg-RSB. Furthermore, Fe/Mg-RSB had the potential for repeated use. Therefore, Fe and Mg co-modified biochar could be used for the remediation of CQP from contaminated water.

The application of fungicides (such as tebuconazole) can impose harmful impacts on the ecosystem and humans. In this study, a new calcium modified water hyacinth-based biochar (WHCBC) was prepared and its effectiveness for removing tebuconazole (TE) via adsorption from water was tested. The results showed that Ca was loaded chemically (CaC2O4) onto the surface of WHCBC. The adsorption capacity of the modified biochar increased by 2.5 times in comparison to that of the unmodified water hyacinth biochar. The enhanced adsorption was attributed to the improved chemical adsorption capacity of the biochar through calcium modification. The adsorption data were better fitted to the pseudo-second-order kinetics and the Langmuir isotherm model, indicating that the adsorption process was dominated by monolayer adsorption. It was found that liquid film diffusion was the main rate-limiting step in the adsorption process. The maximum adsorption capacity of WHCBC was 40.5 mg/g for TE. The results indicate that the absorption mechanisms involved surface complexation, hydrogen bonding, and π–π interactions. The inhibitory rate of Cu2+ and Ca2+ on the adsorption of TE by WHCBC were at 4.05–22.8%. In contrast, the presence of other coexisting cations (Cr6+, K+, Mg2+, Pb2+), as well as natural organic matter (humic acid), could promote the adsorption of TE by 4.45–20.9%. In addition, the regeneration rate of WHCBC was able to reach up to 83.3% after five regeneration cycles by desorption stirring with 0.2 mol/L HCl (t = 360 min). The results suggest that WHCBC has a potential in application for removing TE from water.

Abstract The composition and function of intestinal microbial communities are important for human health. However, these intestinal floras are sensitive to changes in the environment. Adverse changes to intestinal flora can affect the health of astronauts, resulting in difficulties in implementing space missions. We randomly divided mice into three groups and placed each group in either a normal environment, simulated microgravity environment or a combined effects environment, which included simulated microgravity, low pressure and noise. Fecal samples of the mice were collected for follow-up analysis based on metagenomics technology. With the influence of different space environmental factors, the species composition at the phylum and genus levels were significantly affected by the combined effects environment, especially the abundance of the Firmicutes and Bacteroidetes. Furthermore, screening was conducted to identify biomarkers that could be regarded as environmental markers. And there have also been some noticeable changes in the function of intestinal floras. Moreover, the abundance of antibiotic resistance genes (ARGs) was also found to be changed under different environmental conditions, such as bacitracin and vancomycin. The combined effects environment could significantly affect the species composition, function, and the expression of ARGs of intestinal flora of mice which may provide a theoretical basis for space medical supervision and healthcare.

Automated code compliance checking is an effective approach for assessing the quality of building information modeling (BIM) models. Various automated code compliance checking systems have emerged, wherein users need to input all information accurately according to BIM modeling guidelines, in order to ensure the accuracy of checking results. However, as this process involves human inputs, it is difficult to ensure that each input is accurate. In the case of errors or missing inputs, the checking results will be erroneous. Although automated checking systems can be developed accurately, it is difficult to apply these systems practically. Therefore, this paper proposes the application of AI technology to recognize BIM objects and visible properties, in order to improve the operability of automated code compliance checking. The two necessary elements – object names and properties – could be automatically extracted to a certain extent, following the application of the proposed method to the automated code checking process. The error rate of the input could also be reduced, thus making the application of the code checking system more practically feasible. The proposed recognition method for BIM objects and visible properties is also expected to be used widely in BIM-based building e-submission systems and BIM-based forward designs.

Abstract Stratospheric emissions from aircraft or rockets are important sources of chemical perturbations. Small‐radius high‐aspect‐ratio plumes from stratospheric emissions are smaller than global Eulerian models' grid cells. To help global Eulerian models resolve subgrid plumes in the stratosphere, a Lagrangian plume model, comprising a Lagrangian trajectory model and an adaptive‐grid plume model with a sequence of plume cross‐section representations (from a highly resolved 2‐D grid to a simplified 1‐D grid based on a tradeoff between the accuracy and computational cost), is created and embedded into a global Eulerian (i.e., GEOS‐Chem) model to establish a multiscale Plume‐in‐Grid (PiG) model. We compare this PiG model to the GEOS‐Chem model based on a 1‐month simulation of continuous inert tracer emissions by aircraft in the stratosphere. In the PiG results, the final injected tracer is more concentrated and approximately 1/3 of the tracer is at concentrations 2–4 orders of magnitude larger compared to the GEOS‐Chem results. The entropy of injected tracer in the PiG results is 6% lower than the GEOS‐Chem results, indicating less tracer mixing. The total product mass from a hypothetical second‐order process (applied to the injected tracer) in the PiG results is 2 orders of magnitude larger than the GEOS‐Chem results. Increasing the GEOS‐Chem model's horizontal resolution 4‐fold is insufficient to resolve this product difference, while requiring over seven times the computational resources of the PiG model. This paper describes the PiG model framework and parameterization of plume physical processes. Chemical and aerosol processes will be introduced in the future.

Background: Ischemic stroke is a highly complex disorder. This study aims to identify novel methylation changes in ischemic stroke.Methods: We carried out an epigenome-wide study of ischemic stroke using an Infinium HumanMethylation 850K array (cases:controls = 4:4). 10 CpG sites in 8 candidate genes from gene ontology analytics top-ranked pathway were selected to validate 850K BeadChip results (cases:controls = 20:20). We further qualified the methylation level of promoter regions in 8 candidate genes (cases:controls = 188:188). Besides, we performed subgroup analysis, dose-response relationship and diagnostic prediction polygenic model of candidate genes.Results: In the discovery stage, we found 462 functional DNA methylation positions to be associated with ischemic stroke. Gene ontology analysis highlighted the “calcium-dependent cell-cell adhesion via plasma membrane cell adhesion molecules” item, including 8 candidate genes (CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB6/PCDHB9). In the replication stage, we identified 5 differentially methylated loci in 20 paired samples and 7 differentially methylated genes (CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB9) in 188 paired samples. Subgroup analysis showed that the methylation level of above 7 genes remained significantly different in the male subgroup, large-artery atherosclerosis subgroup and right hemisphere subgroup. The methylation level of each gene was grouped into quartiles, and Q4 groups of the 7 genes were associated with higher risk of ischemic stroke than Q1 groups (p < 0.05). Besides, the polygenic model showed high diagnostic specificity (0.8723), sensitivity (0.883), and accuracy (0.8777).Conclusion: Our results demonstrate that DNA methylation plays a crucial part in ischemic stroke. The methylation of these 7 genes may be potential diagnostic biomarker for ischemic stroke.

The direct addition of an O–H (hydroalkoxylation) or an N–H (hydroamination) bond across an alkene is a useful strategy to access biologically relevant heterocycles. Here, the authors report “donor–acceptor”-type platinum catalysts that are effective for both hydroalkoxylation and hydroamination of unactivated alkenes, with broad substrate scope and use of mild conditions.

Recently designed dipolar Halbach magnets used in portable MRI systems are much lighter and more compact than standard permanent or superconductive magnets. However, improved designs and manufacturing techniques aiming at lower weight and smaller external size are an area of continual interest especially for application to space flight. Most Halbach magnet design techniques aim to optimize homogeneity suitable for MRI over a diameter-spherical volume (DSV) that requires the aspect ratio (length/inner diameter) to be larger than 1.5:1. Furthermore, current magnet construction techniques often use low-coercivity magnetic pieces and imperfect formers that produce a mismatch in the intended designs. As a result, Halbach magnets require complex shimming methods to improve the magnetic field homogeneity, causing further size and weight increase. Here, we propose to reduce the weight and the aspect ratio of the Halbach magnet by optimizing homogeneity over a cylindrical region of interest (ROI) rather than a DSV, applying a genetic algorithm, high-coercivity ferromagnets (N40UH) and a robust construction technique. The assembled 67 mT magnet, with aspect ratio ~ 1:1, produces almost identical homogeneity (11152 ppm) as simulations (11451 ppm) within a 12.7 cm diameter, 1 cm long cylinder ROI. The magnet structure was 3D printed ring-by-ring and assembled coaxially. The magnet can be disassembled for transportation.

To remove typical herbicide diuron effectively, a novel sludge-derived modified biochar (SDMBC600) was prepared using sludge-derived biochar (SDBC600) as raw material and Fe-Zn as an activator and modifier in this study. The physico-chemical properties of SDMBC600 and the adsorption behavior of diuron on the SDMBC600 were studied systematically. The adsorption mechanisms as well as practical applications of SDMBC600 were also investigated and examined. The results showed that the SDMBC600 was chemically loaded with Fe-Zn and SDMBC600 had a larger specific surface area (204 m2/g) and pore volume (0.0985 cm3/g). The adsorption of diuron on SDMBC600 followed pseudo-second-order kinetics and the Langmuir isotherm model, with a maximum diuron adsorption capacity of 17.7 mg/g. The biochar could maintain a good adsorption performance (8.88–12.9 mg/g) under wide water quality conditions, in the pH of 2–10 and with the presence of humic acid and six typical metallic ions of 0–20 mg/L. The adsorption mechanisms of SDMBC600 for diuron were found to include surface complexation, π–π binding, hydrogen bonding, as well as pore filling. Additionally, the SDMBC600 was tested to be very stable with very low Fe and Zn leaching concentration ≤0.203 mg/L in the wide pH range. In addition, the SDMBC600 could maintain a high adsorption capacity (99.6%) after four times of regeneration and therefore, SDMBC600 could have a promising application for diuron removal in water treatment.