We aimed to evaluate the feasibility and preliminary efficacy of trauma-focused group psychotherapy in adolescents who experienced traumatic events in Korea. Participants were assigned and recruited from two sites in Korea. Children in Disaster: Evaluation and Recovery (CIDER) V1.0 is a trauma-focused group psychotherapy approach consisting of psychoeducation, normalization, stabilization, and techniques of managing the traumatic memory. The CIDER intervention consists of eight 50-minute-long sessions. The effectiveness of the intervention was evaluated using the Korean version of the Children’s Response to Traumatic Events Scale-Revised (K-CRTES-R), the Beck Depression Inventory (BDI), the State Anxiety Inventory for Children (SAIC), and the Pediatric Quality of Life Inventory (PedQL). Data were analyzed by Wilcoxon signed-rank test. We recruited 22 traumatized adolescents (mean age 16 years; SD 1.43; range 13–18 years old; 71.4% boys) in this pilot study. The K-CRTES-R scores were significantly improved (Z = −2.85, p < 0.01). The BDI demonstrated the effectiveness of the therapy (Z = −2.35, p < 0.05). The assessment of the PedQL supported the effect of CIDER (Z = −3.08, p < 0.01). However, there was no statistically significant differences in the SAIC scores (Z = −1.90, p > 0.05). The results show that there is preliminary evidence that CIDER intervention reduces post-traumatic stress and depressive symptoms and improves quality of life. Our findings indicate that CIDER is feasible for treating adolescents exposed to traumatic events. Larger controlled trials are needed to establish the efficacy of this trauma-focused group psychotherapy and examine its impact on post-traumatic stress disorder.

Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, we apply the GRA theory to the HFSs and interval-valued hesitant fuzzy sets (IVHFS) domain. We propose the HFSs grey relational degree, HFSs slope grey relational degree, HFSs synthetic grey relational degree and IVHFSs grey relational degree, which describe the closeness, the variation tendency and both the closeness and variation tendency of HFSs and closeness of IVHFSs, respectively, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs and IVHFSs MADM problems. Finally, combined with two practical MADM examples about energy policy selection with HFSs information and emergency management evaluation with IVHFSs information, we obtain the most desirable decision results, and compared with the previous methods, the validity, effectiveness and accuracy of the proposed grey relational degree for HFSs and IVHFSs are demonstrated in detail.

Unavoidable exposure to radiosensitive normal tissues around cancerous tumor during the radiotherapy can cause side effects such as self-limited acute toxicities, mild chronic symptoms, or severe organ dysfunction. Nevertheless, clinical use of currently available radiation protective agents is limited because of their generic cytotoxicity. A study on radiation protective effect of delphinidin was conducted with proton-beam-exposed human colon cells (CCD-18Co). The measurement in changes of survival fractions of CCD-18Co with/without delphinidin administration at different radiation doses were measured by 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay. The changes in expression of reactive oxygen species (ROS) and in activities of antioxidant enzymes were measured by colorimetric assays using pertinent assay kits. The measurement of pro-apoptosis/pro-survival protein expressions using Western blot assay and the measurement of DNA damage using comet assay were also fulfilled to evaluate the molecular level of radiation damages in CCD-18Co cells. The experimental results revealed that the pre-administration of delphinidin regulated antioxidant enzymes, reduced ROS, decreased DNA damage, regulated pro-apoptosis/pro-survival proteins, and eventually reduced apoptosis of CCD-18Co cells. In conclusion, it is claimed that delphinidin is nontoxic natural radiation protective compound, and thus delphinidin can be used to protect normal colon tissues during the proton beam therapy.

The outbreak of recently identified 2019 novel coronavirus (2019-nCOV) infection has become a world-wide health threat. Currently, more information is needed for further understanding the transmission, clinical characteristics, and infection control procedures of 2019-nCOV. Recently, the role of the eye in transmitting 2019-nCOV has been intensively discussed. Previous investigations about other high infectious human COVs, that is, severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), may provide helpful information. In this review, we describe the genomics and morphology of human CoVs, the epidemiology, systemic and ophthalmic manifestations, mechanisms of human CoVs infection, and infection control procedures. The role of the eye in the transmission of SARS-CoV and 2019-nCOV is discussed. Although the conjunctiva is directly exposed to extraocular pathogens, and the mucosa of ocular surface and upper respiratory tract is connected by nasolacrimal duct and share same entry receptors for some respiratory viruses. The eye is rarely involved in human CoVs infection, conjunctivitis is quite rare in patients with SARS-CoV and 2019-nCoV infection, and COV RNA positive rate by RT-PCR test in tears and conjunctival secretions from patients with SARS-CoV and 2019-nCoV infection is also very low, which imply that the eye is neither a preferred organ of human COVs infection, nor is a preferred gateway of entry for human COVs to infect respiratory tract. However, pathogens exposed to the ocular surface might be transported to nasal and nasopharyngeal mucosa by constant tear rinsing through lacrimal duct, and then cause respiratory tract infection. Considering close doctor-patient contact is quite common in ophthalmic practice which are apt to transmit human COVs by droplets and fomites, hand hygiene and personal protection are still highly recommended for health care workers to avoid hospital-related viral transmission during ophthalmic practice.

Automobile industry is recognized as one of the most influential sectors shaping the global economies, societies, and individual lifestyles. Therefore, fierce competitions among different companies are continuously undergoing, and innovations deserve special attention to improve the competitiveness. In the past several years, additive manufacturing (AM) is emerging as an innovative technology in the applications of automobile industry with significant advantages over traditional techniques. As a result, increasing attention has been attracted to combining AM technology with the development of automobile industry. Currently, many automobile players are optimizing their industrial layout by incorporating with innovative AM techniques, and meanwhile, many research progresses have been achieved to meet the market demand. This article aims at presenting a timely review to conclude the recent advances in the application of AM techniques in automobile industry, focusing on the available AM techniques, printable materials, and the industry applications. The future research opportunities and challenges are also outlooked. Hopefully, this work can be useful to the related researchers, as well as the game players in the industry of this field.

We aimed to evaluate the survival benefits of coadministering statins and multityrosine kinase inhibitors (TKIs) in patients with advanced hepatocellular carcinoma (HCC). Data from the Health Insurance Review and Assessment Service in Korea (2010–2020) were utilized. Statin use (≥28 cumulative defined daily doses) was analyzed, with 1,534 statin users matched to 6,136 non-users (1:4 ratio) using propensity scores. Primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS). Statin use significantly improved OS (hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.72–0.82, P&lt;0.001) and PFS (HR 0.78, 95% CI 0.74–0.84, P&lt;0.001). Continuous or post-TKI statin users had better OS, while discontinuation after TKI use led to poorer OS. Both lipophilic and hydrophilic statins improved OS and PFS, particularly with ≥730 cumulative defined daily doses. In conclusion, combining statins and TKIs in patients with advanced HCC yielded significant survival benefits, influenced by statin dosage and duration. Continuous statin administration post-TKI treatment is crucial for improving outcomes in patients with HCC.

Low-energy cosmic rays (LECRs) play a crucial role in the formation of planetary systems, and detecting and reconstructing the properties of early LECRs is essential for understanding the mechanisms of planetary system formation. Given that LECRs interact with the surrounding medium to produce nuclear de-excitation line emissions with energy mainly within 0.1–10 MeV, which are unaffected by stellar wind modulation, these gamma-ray emissions can accurately reflect the properties of LECRs. This study introduces an innovative method for using gamma-ray emissions to infer LECR properties. We employed the Parker transport equation to simulate the propagation and spectral evolution of LECRs in a protoplanetary disk and calculated the characteristic gamma-ray emissions resulting from interactions between LECRs and disk material. These gamma-ray emissions encapsulate the spectral information of LECRs, providing a powerful tool to reconstruct the cosmic ray environment at that time. This method, supported by further theoretical developments and observations, will fundamentally enhance our understanding of the impact of CRs on the origin and evolution of planetary systems and address significant scientific questions regarding the cosmic ray environment at the origin of life.

Artificial intelligence provides a new research concept for digital image processing. However, at present, artificial intelligence is rarely introduced into the teaching of digital image processing in colleges and universities, and there are problems such as obsolete teaching content, single teaching methods, and simple course experiments, which affect the teaching effect and are not conducive to the cultivation of comprehensive and innovative talents. Digital image processing technology brings more possibilities to communication engineering and makes communication more convenient. For example, video calls and photo transmission make people's communication methods in daily life more and more diversified. Time and space limitations allow people to meet online, creating more communication possibilities. However, there are still many problems and methods worthy of in-depth exploration. Therefore, this paper has a comprehensive understanding and mastery of the traditional and deep learning methods of digital image processing to improve the relevant project practice and scientific research exploration ability and refer for similar research conclusions.

This research seeks to advance the understanding of ecological management in the Huaihe River Basin, China. The spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) and its underlying driving forces are examined utilizing SPOT-NDVI data covering the period 2000-2019. Linear regression analysis is employed to quantify trends and assess the statistical significance of NDVI variations. A differencing approach is subsequently applied to discern the variability in NDVI. The distribution of its spatial pattern stability over 20 years is explored through the coefficient of variation. Lastly, the Geodetector method is utilized to elucidate the driving factors influencing NDVI dynamics. The results indicate that the overall NDVI is generally high, with an overall growth rate of 0.00148/year, and 2010 is identified as a significant inflection point in the trend. NDVI values are notably lower in urban areas, corresponding to urban expansion, except for regions near rivers and lakes. Land use type emerges as the strongest explanatory factor for NDVI among single factors, with climate factors exhibiting a relatively weaker degree of explanatory force. These findings suggest that the overall NDVI in the Huaihe River Basin is high, indicative of a vegetation condition that continues to improve.

Ensuring bus priority is to improve traffic sustainability at the signalized intersection. To achieve this, the Bus Priority Lane (BPL) is adopted to provide exclusive right-of-way for buses. However, the BPL is underutilization if the frequency of buses is low. To address this issue, many studies focus on improving the BPL’s utilization efficiency by intermittently allowing general vehicles to access it. However, these studies still have some shortcomings: i) bus priority cannot be guaranteed if general vehicles run on the BPL; ii) the traffic system lacks resilience, especially when the traffic demand is unbalanced. This paper proposes a dynamic right-of-way allocation on the BPL considering traffic system resilience. On the one hand, it ensures absolute bus priority by controlling Connected Automated Vehicles (CAVs) to not interfere with buses. On the other hand, it can improve traffic system resilience by allocating right-of-way for CAVs with heavy turning-movement demand. To validate the effectiveness, the proposed control strategy is evaluated against the non-control baseline. Sensitivity analysis is conducted under seven unbalanced traffic demand levels, four congestion levels, and five CAV Penetration Rates. The results show that the proposed control strategy can ensure absolute bus priority and improve traffic efficiency and traffic system resilience.

Digital-Radio-Frequency-Memory (DRFM) has emerged as an advanced technique to achieve diverse jamming signals, due to its capability of intercepting waveforms within a short time. Multiple-Input Multiple-Output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to combat the DRFM-based jamming, where any two groups of waveform sets are also orthogonal. In order to design multiple groups of orthogonal waveform sets at the same time, this article formulates a group orthogonal waveforms optimal design model, whose objec-tive function is the weighted sum of the intra- and inter-group orthogonal performances metrics. To solve this optimization problem, this article proposes a group orthogonal waveforms design algorithm. Based on a primal-dual type method and proper relaxations, the proposed algorithm transforms the original problem into a series of simple sub-problems. Numerical results demonstrate that the proposed algorithm has the ability to balance the intra- and inter-group orthogonal performances by adjusting the weighting factors, which is not available using other state-of-the-art orthogonal waveform design algorithms.

The accumulation of waste plastics has a severe impact on the environment, and therefore, the development of efficient chemical recycling methods has become an extremely important task. In this regard, a new strategy of degradation product-promoted depolymerization process was proposed. Using N,N'-dimethyl-ethylenediamine (DMEDA) as depolymerization reagent, an efficient chemical recycling of poly(bisphenol A carbonate) (BPA-PC) material was achieved under mild conditions. The degradation product 1,3-dimethyl-2-imidazolidinone (DMI) was proven to be the critical factor in facilitating the depolymerization process. This strategy does not require catalysts or auxiliary solvents, which is truly green process. This method improves the recycling efficiency of BPA-PC and promotes the development of plastic reutilization.

This paper presents an efficient topology optimization approach considering fail-safe requirements in the framework of the solid isotropic material with penalization method. Existing methods either are computationally extremely expensive or do not consider fail-safe requirements in the optimization. The current approach not only obtains the fail-safe optimization structure, but also significantly improves the computational efficiency of fail-safe topology optimization. In this method, the worst-case compliance is considered to minimize as the optimization objective, using the Kreisselmeier–Steinhauser function to approximate the non-differentiable max-operator. The sensitivity is derived by the adjoint method, and a general fail-safe optimality criteria method is developed to update design variables. The damage scenarios greatly reduces in the process of failsafe strategy optimization by employing the density-based filter method. Finally, the effectiveness and computational efficiency of this method for fail-safe optimization is verified by several numerical examples.

We aim to examine how happiness modifies and mediates the impact of physical activity and nu-trition on cognitive function among 699 seniors aged 60 and above in Shanghai, China. Linear regression models were used to validate the effects of nutrition and exercise on cognitive function, and to test their interaction effects with happiness. When the interactions were significant, strati-fied analyses in sub-groups were conducted. Mediation effects of happiness were examined using two-step causal mediation models. We confirmed that better nutrition (p < 0.001) and exercise (p = 0.009) were significantly associated with less cognitive decline. Furthermore, the effects of nu-trition and exercise on cognitive decline were significant in the unhappy (happiness < 20) (p <0.001) and younger (age < 74) sub-groups (p = 0.015). Happiness partially mediated 11.5% of the negative association of cognitive decline with nutrition (p = 0.015) and 23.0% of that with exercise (p = 0.017). This study suggests that happiness moderates and also partially mediates the effects of exercise and nutrition on cognitive status. The beneficial effects of exercise and nutrition were stronger in less happy or younger seniors. Future intervention studies are required to confirm this path relationship.

Herpesvirus is a prevalent pathogen that primarily infects human epithelial cells and has the ability to reside in neurons. In the field of otolaryngology, herpesvirus infection primarily leads to hearing loss and vestibular neuritis, and is considered the primary hypothesis regarding the pathogenesis of vestibular neuritis. In this review, we provide a summary of the effects of herpes virus on cellular processes in both host cells and immune cells, with a focus on HSV-1 as illus-trative examples.

In recent years, ozone (O3) pollution has been rapidly spreading, restricting further improvement of air quality in China. Investigating the interaction of O3 concentration and identifying their driven cities are important for the prevention and control of O3 pollution in China. However, the complex interaction between O3 pollution between the cities and their driven cities has not yet been revealed. In this study, we address this gap based on complex network methods. Specifically, an ozone relational network is constructed using an association calculation method. The driven nodes and spatial clusters were analyzed based on the maximum matching algorithm and the Louvain algorithm. The findings of the study reveal an aggregation phenomenon in the ozone network concerning distance. Furthermore, as the threshold Tc varies, the proportion of driven nodes exhibits a positive correlation. Moreover, a closer threshold value corresponds to a higher coincidence ratio of the driven nodes. The results provide scientific guidance for national O3 pollution prevention and regional synergy formatting. Furthermore, the introduced network-based approaches offer a mythological framework for the study of air pollution in key cities and clusters.

In high-traffic harbor waters, marine radar frequently encounters signal interference stemming from various obstructive elements, thereby presenting formidable obstacles in the precise identification of ships. To achieve precise pixel-level ship identification in the complex environments, a customized neural network-based ship segmentation algorithm named MrisNet is proposed. MrisNet employs a lightweight and efficient FasterYOLO network to extract features from radar images at different levels, capturing fine-grained edge information and deep semantic features of ship pixels. To address the limitation of deep features in the backbone network lacking detailed shape and structured information, an adaptive attention mechanism is introduced after the FasterYOLO network to enhance crucial ship features. To fully utilize the multi-dimensional feature outputs, MrisNet incorporates a Transformer structure to reconstruct the PANet feature fusion network, allowing for the fusion of contextual information and capturing more essential ship information and semantic correlations. In the prediction stage, MrisNet optimizes the target position loss using the EIoU function, enabling the algorithm to adapt to ship position deviations and size variations, thereby improving segmentation accuracy and convergence speed. Experimental results demonstrate that MrisNet achieves high recall and precision rates of 94.8% and 95.2%, respectively, in ship instance segmentation, outperforming various YOLO and other single-stage algorithms. Moreover, MrisNet has a model parameter size of 13.8M and real-time computational cost of 23.5G, demonstrating notable advantages in terms of convolutional efficiency. In conclusion, MrisNet accurately segments ships with different spot features and under diverse environmental conditions in marine radar images. It exhibits outstanding performance, particularly in extreme scenarios and challenging interference conditions, showcasing robustness and applicability.

Retrogressive thaw slumps (RTSs) are becoming more common on the Qinghai-Tibet Plateau as permafrost thaws, but the hydraulic characteristics of these slumps have not been extensively studied. To fill this knowledge gap, we used the ''space-for-time substitution method'' to differentiate three stages of RTSs: original grassland, collapsing, and collapsed. Our study included on-site investigations, measurements, and simulated analyses of soil water characteristics, environmental factors, and hydrological properties. Our findings show that the measurements and simulated analyses of soil water characteristics were highly consistent across RTSs, indicating the accuracy of the V-G model in reproducing soil hydraulic parameters for different stages of RTSs. The original grassland stage had the highest soil water retention and content due to its high SOM content and fine-textured micropores. In contrast, the collapsed stage had higher soil water retention and content compared to the collapsing stage, primarily due to increased proportions of soil micropores, SOM content, and lower bulk density (BD). Freeze-thaw cycles had a significant impact on the soil texture and structure of RTSs, resulting in a decrease in SOM content and an increase in BD. However, the absence of soil structure and compaction led to the subsequent accumulation of organic matter, increasing SOM content. Changes in field capacity (FC), permanent wilting point (PWP), and soil micropore distribution aligned with variations in SOM content and water content.These findings highlight the importance of managing SOM content and water content to mitigate the adverse effects of freeze-thaw cycles on soil structure and stability at different stages of RTSs. Effective management strategies may include incorporating organic matter, reducing soil compaction, and maintaining optimal water content. Further research is needed to determine the most suitable management practices for different soil types and environmental conditions.

The growing adoption of distributed energy production technologies, and the potential of energy underutilization when it is produced by non-connected groups, has raised interest in ‘sharing economy’ concepts in the electricity sector. We suggest that mechanisms, such as peer-to-peer (P2P) energy trading, will allow users to exchange their surplus energy for mutual benefits, stimulate the adoption of renewable energy, encourage communities to ‘democratically’ control their own energy supplies for local development, and improved energy efficiency, and create many other benefits This approach is receiving increasing attention across the world, particularly in Germany, the Netherlands and Australia. Nevertheless, the actual development and implementation of these platforms is slow and mostly limited to trial activities. This study investigates the challenges and barriers facing P2P energy trading developments based on previous academic and industry studies. We provide a comprehensive multidimensional barrier analysis through a PESTLE approach to assess the barriers from a variety of perspectives, including the political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) aspects. This approach clarifies the many intersecting problem fields of P2P trading in renewable energy, and the paper identifies a list of such barriers, and discusses the prospects for addressing these issues. We also elaborate on the importance of incentive-based P2P market design.

Handwriting is a form of biometric behavioral characteristic with evident individual distinctiveness. With the surge of the deep learning trend and the demand for forensic identification, handwriting identification has become one of the focal points of research in the field of pattern recognition. The research on handwriting identification in major world languages has reached a mature stage. However, there is still a notable lack of relevant research in the field of Mongolian handwriting identification, despite the fact that Mongolian is used by over 4 million people in China. This paper embarks on an initial exploration of Mongolian handwriting identification by constructing a convolutional neural network named MWInet-12. In this paper, the model evaluation experiments were conducted using a dataset comprising 156,372 samples contributed by 125 authors from the MOLHW dataset. The dataset was divided into training, validation, and test sets in an 8:1:1 ratio. The final results of the experiments reveal impressive accuracy on the test set, achieving a top-1 accuracy of 89.60% and a top-5 accuracy of 97.53%. Furthermore, through comparative experiments involving Resnet, Fragnet, and GRRNN models, this paper establishes that the proposed model yields the most favorable results for Mongolian handwriting identification.

Changes in sea level exhibit nonlinearity, nonstationarity, and multivariable characteristics, making traditional time series forecasting methods less effective in producing satisfactory results. To enhance the accuracy of the predictions of changes in sea level, this study introduced an improved VMD–EEMD–LSTM hybrid model. This model decomposes satellite altimetry data from near the Dutch coast using VMD, resulting in components of the Intrinsic Mode Function (IMF) with various frequencies and a residual sequence. EEMD further dissects the residual sequence obtained from VMD into second-order components. These IMFs decomposed by VMD and EEMD are utilized as features in the LSTM model for making predictions, culminating in the final forecasted results. The experimental results demonstrated significant improvements in the predictive performance compared with the VMD–LSTM model. The RMSE (root mean square error) decreased by an average of 58.68%, the MAE (mean absolute error) reduced by an average of 59.96%, and the R2 (coefficient of determination) increased by an average of 49.85% compared with the VMD–LSTM model. In comparison with the EEMD–LSTM model, the RMSE decreased by an average of 26.95%, the MAE decreased by an average of 28.00%, and the R2 increased by an average of 6.53%. The VMD–EEMD–LSTM model exhibited significantly improved predictive performance.

Mucin glycans are important component of the mucus barrier and vital defence against physical and chemical damage as well as pathogens. Abnormal expression of mucin glycans can lead to disease, especially cancer. Here, we first summarize the main types of glycosylation on mucins and the mechanisms by which abnormal mucin glycans occur. We next describe the role of ab-normal mucin glycans in cancer. Finally, we describe MUC1-based antibodies, vaccines, radio-pharmaceuticals, and CAR-T therapies using the best characterized MUC1 as an example.

The combination of wet-lab experimental data on multi-site combinatorial mutations and machine learning is an innovative method in protein engineering. In this study, we present an improved innovative sequence–activity relationship (innov'SAR) methodology based on novel descriptors and digital signal processing (DSP) to construct a predictive model. In this improved approach, 21 experimental (R)-selective amine transaminases from Aspergillus terreus (AT-ATA) were used as an input to predict higher thermostability than that predicted using the existing data. We successfully improved the determination coefficient (R2) of the model from 0.66 to 0.92. In addition, root mean square deviation (RMSD) and root mean square fluctuation (RMSF) were estimated and conformation analysis based on molecular dynamics simulations was performed to verify the enhanced thermal stability of the screened mutants. The improved innov'SAR algorithm enhanced the predictive accuracy, suggesting a method for modifying the stability of AT-ATA, which may help in directed evolutionary screening and open up new avenues for protein engineering.

The determination of critical ventilation flow rate is significant for the risk control and the standard development during accidental hydrogen leakage in a confined space with hydrogen-related equipment. In this paper, an analytical model for calculating critical ventilation flow rate was proposed through the quantification and constraint solution of ventilation effect and ventilation cost. The experimental method was used to investigate the effects of nozzle diameter and stagnation pressure on diffusion and ventilation for horizontal hydrogen leakage in a cuboid chamber. Ventilations from 30m3/h to 180m3/h were carried out through the rectangular vent. It was shown that the peak concentration of the measuring point is positively correlated with the stagnation pressure and the nozzle diameter. The experimental data are used to verify the analytical model by calculating the effective ventilation time. The study demonstrates that the critical ventilation flow rate can be increased significantly at higher stagnation pressures and larger nozzle diameters. And the discrepancy of critical ventilation flow rates under different nozzle diameters will be enhanced with the increase of stagnation pressure. For the stagnation pressure of 0.4MPa, the critical ventilation flow rate under 4mm nozzle even increases by 52% relative to the 2mm nozzle.

Accurate evaluation of patients with disorders of consciousness (DoC) is crucial for personalized treatment. However, misdiagnosis remains a serious issue. Neuroimaging methods could observe the conscious activity in patients who have no evidence of consciousness in behavior, and provide objective and quantitative indexes to assist doctors in their diagnosis. In the review, we discussed the current research based on the evaluation of consciousness rehabilitation after DoC using EEG, fMRI, PET, and fNIRS, as well as the advantages and limitations of each method. Nowadays single-modal neuroimaging can no longer meet the researchers` demand. Considering both spatial and temporal resolution, recent studies have attempted to focus on the multi-modal method which can enhance the capability of neuroimaging methods in the evaluation of DoC. As neuroimaging devices become wireless, integrated, and portable, multi-modal neuroimaging methods will drive new advancements in brain science research.

This study utilized panel data from 31 Chinese provinces over a period of nine years to investigate the impact of green finance on the upgrading of the agricultural industrial structure. A fixed-effect model was employed, and the findings indicate that green financing has a positive effect on the growth of China's agricultural industry. However, regional disparities exist, particularly in the uneven distribution of green financing across the eastern, central, and western regions. Moreover, it emphasizes the need to consider regional differences and tailor development strategies accordingly. To promote further development and transformation of China's agricultural industrial structure, the study recommends innovative green financial products, improved regulations and policies, and the integration of digital technologies.

Image fusion is the process of combining multiple input images from single or multiple imaging modalities into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. In this paper, we propose a novel method based on deep learning for fusing infrared images and visible images, named the LBP-based proportional input generative adversarial network (LPGAN). In the image fusion task, the preservation of structural similarity and image gradient information is contradictory, and it is difficult for both to achieve good performance at the same time. To solve this problem, we innovatively introduce Local Binary Patterns (LBP) into Generative Adversarial Networks (GANs), which effectively utilize the texture features of the source images, so that the network has stronger feature extraction ability and anti-interference ability. In the feature extraction stage, we introduce a pseudo-siamese network for the generator to extract the detailed features and the contrast features. At the same time, considering the characteristic distribution of different modal images, we propose a 1:4 scale input mode. Extensive experiments on the publicly available TNO dataset and CVC14 dataset show that the proposed method achieves the state-of-the-art performance. We also test the universality of LPGAN through the fusion of RGB and infrared images on the RoadScene dataset. In addition, LPGAN is applied to multi-spectral remote sensing image fusion. Both qualitative and quantitative experiments demonstrate that our LPGAN can not only achieve good structural similarity, but also retain rich detailed information.

With the advent of Neural Machine Translation, the more the achievement of human-machine parity is claimed at WMT, the more we come to ask ourselves if their evaluation environment can be trusted. In this paper, we argue that the low quality of the source test set of the news track at WMT may lead to an overrated human parity claim. First of all, we report nine types of so-called technical contaminants in the data set, originated from an absence of meticulous inspection after web-crawling. Our empirical findings show that when they are corrected, about 5% of the segments that have previously achieved a human parity claim turn out to be statistically invalid. Such a tendency gets evident when the contaminated sentences are solely concerned. To the best of our knowledge, it is the first attempt to question the “source” side of the test set as a potential cause of the overclaim of human parity. We cast evidence for such phenomenon that according to sentence-level TER scores, those trivial errors change a good part of system translations. We conclude that to overlook it would be a mistake, especially when it comes to an NMT evaluation.

The extant Keteleeria is endemic to East and Southeast Asia, while it is widely distributed in the northern hemisphere in Earth’s history. In this paper, we reported a novel wood fossil of Keteleerioxylon changchunense Shi, Sun, Meng et Yu sp. nov. collected from the middle member of Yingcheng Formation, Yingcheng Coal Mine, Changchun City, Jilin Province, Northeast China. The quantitative growth-ring analyses of K. changchunense indicate that it was evergreen and its leaf longevity was 1-3 years, which is consistent with the foliar retention of extant Keteleeria. Its high ring markedness index (RMI) indicates that the climate seasonality was pronounced during the early Albian in Songliao Basin, Northeast China. The fossil records of Keteleeria and closely related taxa indicate that this group might originate in Northeast China, spread and migrated northward during the Cretaceous, gradually decreased in the Cenozoic, and so far only survives in East and Southeast Asia.

The ridge line of the western Pacific subtropical high (WPSHRL) plays an important role in determining the shift of the summer rain belt in eastern China. In this study, we developed a forecast system for the June WPSHRL index based on the latest autumn and winter sea surface temperature (SST). Considering the adverse condition of the small observed sample size, a very simple neural network (NN) model was selected to extract the non-linear relationship between input predictors (SST) and target predictands (WPSHRL) in the forecast system. In addition, some techniques are used to deal with the adverse condition, enhance the stabilization of forecast skills, and analyze the interpretability of the forecast system. The forecast experiments show that the linear correlation coefficient between the predictions from the forecast system and their corresponding observations is around 0.6, and about three-fifths of the observed abnormal years (the years with an obviously high or low WPSHRL index) are successfully predicted. Furthermore, sensitivity experiments show that the forecast system is relatively stable in terms of forecast skill. The above evaluations suggest that the forecast system is valuable in a real application sense.

Nonlinear catastrophes caused by geological fluids are a fundamental issue in rock mechanics and the geoengineering hazard field. For the consideration of hydrodynamic force on red-bed mudstone softening damage, X-ray visualization test on the fissure flow in mudstone block failure under hydrodynamic force was performed in this study based on block scale and the physical phenomena of fissure seepage and nonlinear diffusion were further explored. A new method for evaluating the hydro-damage degrees of rocks using an X-ray image analysis was proposed, and the quantitative relation of diffusion coefficients of hydro-damage and seepage was established. The research results revealed that the hydrodynamic force promoted the fluid-filled fissure behavior in mudstone specimen failure. Also, the seepage and diffusion phenomena of fluid in rocks during failures were indicated using X-ray imaging. A dual mechanical behavior was presented in the nonlinear seepage and abnormal diffusion of a red mudstone geological body under hydrodynamic conditions. The damaged degree of mudstone was aggravated by the effect of hydrodynamic force, and the initial seepage–diffusion coefficient with respect to lower hydro-damage was larger than the final seepage–diffusion coefficient with respect to higher hydro-damage of rocks with a decreasing nonlinear trend.

The part transportation efficiency is a main factor of aircraft sortie generation rate. Part transportation is used to transport spare part from base to carrier. Transportation strategy depends on both demand on carrier and inventory in transportation base. The transportation time and stochastic demand will induce fluctuations of cost and inventory. Thus, a Takagi-Sugeno fuzzy system of dynamic part transportation is established considering transportation time and stochastic demand. And a novel Takagi-Sugeno fuzzy robust control is designed for dynamic part transportation, which will keep transportation cost and part inventory stable. First of all, a fuzzy model with stochastic demand and transportation time is proposed. Then, a novel robust control with cross rule groups is conducted according to production and transportation strategy, which will reduce fluctuations induced by strategies switch. Moreover, robust stability is guaranteed and part can be supplied in time under a low cost. Finally, simulation illustrates usefulness and quickness of the novel Takagi-Sugeno fuzzy robust control. Besides, the proposed method will be useful in other transportation electrification systems with delay time and uncertainty.

Inflammatory bowel disease (IBD) is a chronic inflammation of the gastrointestinal0 tract (GIT), including Crohn’s disease (CD) and ulcerative colitis (UC), which differ in the location and lesion extensions. Both diseases are associated with microbiota dysbiosis, with a reduced population of butyrate-producing species, abnormal inflammatory response, and micronutrient deficiency (e. g. vitamin D hypovitaminosis). Vitamin D (VitD) is involved in immune cell differentiation, gut microbiota modulation, gene transcription, and barrier integrity. Vitamin D receptor (VDR) regulates the biological actions of the active VitD (1α, 25-dihydroxyvitamin D3), and is involved in the genetic, environmental, immune, and microbial aspects of IBD. VitD deficiency is correlated with disease activity and its administration targeting a concentration of 30 ng/mL may have the potential to reduce disease activity. Moreover, VDR regulates functions of T cells and Paneth cells and modulates release of antimicrobial peptides in gut microbiota-host interactions. Meanwhile, beneficial microbial metabolites, e.g. butyrate, upregulate the VDR signaling. In this review, we summarize the clinical progress and mechanism studies on VitD /VDR related to gut microbiota modulation in IBD. We also discuss epigenetics in IBD and the probiotic regulation of VDR. Furthermore, we discuss the existing challenges and future directions. There is a lack of well-designed clinical trials exploring the appropriate dose and the influence of gender, age, ethnicity, genetics, microbiome, and metabolic disorders in IBD subtypes. To move forward, we need well-designed therapeutic studies to examine whether enhanced vitamin D will restore functions of VDR and microbiome in inhibiting chronic inflammation.

Because the development of the internet of things (IoT) requires technology that transfers information between objects without human intervention, the core of IoT security will be secure authentication between devices or between devices and servers. Software-based authentication may be a security vulnerability in IoT, but hardware-based security technology can provide a strong security environment. A physical unclonable functions (PUFs) are a hardware security element suitable for lightweight applications. PUFs can generate challenge-response pairs(CRPs) that cannot be controlled or predicted by utilizing inherent physical variations that occur in the manufacturing process. In particular, pulse width memristive PUF (PWM-PUF) improves security performance by applying different write pulse widths and bank structures. Bloom filter (BF) is probabilistic data structures that answer membership queries using small memories. Bloom filter can improve search performance and reduce memory usage and are used in areas such as networking, security, big data, and IoT. In this paper, we propose a structure that applies Bloom filters based on the PWM-PUF to reduce PUF data transmission errors. The proposed structure uses two different Bloom filter types that store different information and that are located in front of and behind the PWM-PUF, improving security by removing challenges from attacker access. Simulation results show that the proposed structure decreases the data transmission error rate and reuse rate as the Bloom filter size increases, the simulation results also show that the proposed structure improves PWM-PUF security with a very small Bloom filter memory.

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially in crop monitoring and disaster warning. Evaluating the dependability of those products before they can be used on a large scale is crucial. In this study, we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY-3C) radiometer against in situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from January 1 to December 31, 2016 in Henan, which is an agricultural province in China. Four statistical parameters were used to evaluate the products’ reliability: mean difference, root-mean-square error (RMSE), unbiased RMSE (ubRMSE), and the correlation coefficient. These statistical indicators revealed that the FY-3C L2 SM product generally did not agree with the in situ SM data from CASMOS. The time-series analysis further indicated that the correlations and estimated error were highly related to the growing periods of the crops in our study area. FY-3C L2 SM data tended to overestimate soil moisture during May, August, and September, when the crops reach their maximum vegetation density, and tended to underestimate the soil moisture content during the rest of the year. The averaged correlation coefficient between FY-3C SM and the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index was 0.55, which demonstrates that the vegetation water content of the crops considerably influences the SM product. To improve the accuracy of the FY-3C SM product, an improved algorithm that can filter out the influences of the crops should be applied in the future.

Identifying group movement patterns of crowds and understanding group behaviors is valuable for urban planners, especially when the groups are special such as tourist groups. In this paper, we present a framework to discover tourist groups and investigate the tourist behaviors using mobile phone call detail records (CDRs). Unlike GPS data, CDRs are relatively poor in spatial resolution with low sampling rates, which makes it a big challenge to identify group members from thousands of tourists. Moreover, since touristic trips are not on a regular basis, no historical data of the specific group can be used to reduce the uncertainty of trajectories. To address such challenges, we propose a method called group movement pattern mining based on similarity (GMPMS) to discover tourist groups. To avoid large amounts of trajectory similarity measurements, snapshots of the trajectories are firstly generated to extract candidate groups containing co-occurring tourists. Then, considering that different groups may follow the same itineraries, additional traveling behavioral features are defined to identify the group members. Finally, with Hainan province as an example, we provide a number of interesting insights of travel behaviors of group tours as well as individual tours, which will be helpful for tourism planning and management.

The calcium-sensing receptor (CAS), as a chloroplast thylakoid membrane protein, involved in the process of [Ca2+] ext-induced [Ca2+]cyt increase (CICI) in the plant. However, the underlying mechanism regulating this process is lacking. Furthermore, recent evidence suggests that CAS may perform additional roles in the plant. Here, we provide an update covering the multiple roles of CAS in stomatal movement regulation and calcium signaling in the plant. We also analysis the possible phosphorylation mechanism of CAS by light and discuss the role of CAS in abiotic stress (drought, salt stress) and biotic stresses (plant immune signaling). Finally, we provide a perspective for future experiments which are required to fill gaps in our understanding of the biological function of CAS in the plant.

NiFe alloy nanoparticles/graphene oxide hybrid (NiFe/GO) was prepared for electrochemical glucose sensing. The as-prepared NiFe/GO hybrid was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The results indicated that NiFe alloy nanoparticles can be successfully deposited on GO. The electrochemical glucose sensing performance of the as-prepared NiFe/GO was studied by cyclic voltammetry and amperometric measurement. Results showed that NiFe/GO modified glassy carbon electrode had sensitivity of 173 μA mM⁻¹cm⁻² for glucose sensing with a linear range up to 5 mM, which was superior to commonly used Ni nanoparticles. Furthermore, high selectivity for glucose detection can be achieved by NiFe/GO. All the results demonstrated that NiFe/GO hybrid was promising for using in electrochemical glucose sensing.

Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.

The welding performance of shipbuilding steel under large heat input could be improved greatly by the Mg addition to the steel, but the impact toughness of the HAZ is not stable. According to the three different thickness steel plates obtained in the industrial experiment, the large heat input welding was carried out by different heat input, and the impact toughness analysis, impact fracture analysis, metallographic microstructure analysis and inclusions analysis were carried out. The results showed that, the HAZ of three kinds of thickness plates induced a lot of IAF, with Mg addition, the inclusion dimension had been reduced effectively, and the IAF induced ability of the inclusions had also been improved. The difference of HAZ impact toughness with different welding heat input and different impact temperature is significant, in consideration of the influence of welding heat input and metallographic microstructure on impact toughness of HAZ, the welding heat load had far greater effect than metallographic microstructure on ductile-brittle transition temperature. At the same time, if the original metallographic microstructure of steel was coarse, the pinning effect of the inclusions would be reduced significantly, and the microstructure of HAZ would be coarsened and the impact toughness of HAZ would be decreased, so there is a certain matching relationship between the metallographic microstructure and the inclusion dimension.

Information-theoretic measures such as the entropy, cross-entropy and the Kullback-Leibler divergence between two mixture models is a core primitive in many signal processing tasks. Since the Kullback-Leibler divergence of mixtures provably does not admit a closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration, approximated, or bounded using various techniques. We present a fast and generic method that builds algorithmically closed-form lower and upper bounds on the entropy, the cross-entropy and the Kullback-Leibler divergence of mixtures. We illustrate the versatile method by reporting on our experiments for approximating the Kullback-Leibler divergence between univariate exponential mixtures, Gaussian mixtures, Rayleigh mixtures, and Gamma mixtures.

As urbanization has accelerated, China has started to build smart cities, which have formed smart city clusters. It is critical to coordinate development within smart city clusters to enhance the efficiency of city cluster construction. From the perspective of demographic economics, this study innovatively constructed an evaluation system for the coordinated development of smart city clusters and utilized the coupled coordination degree model to conduct an in-depth study of smart city clusters in Jiangsu Province. The results show that there are clear differences in the development between the three regions of Jiangsu Province: Southern Jiangsu, Central Jiangsu, and Northern Jiangsu. The development within Jiangsu Province is imbalanced, where the overall development trend is high in the southern region and low in the northern region. The main driving factors include geography, the Matthew effect, game thinking, and industrial structure. Accordingly, the results suggest the following recommendations for the coordinated development of smart city clusters: strengthening cross-regional cooperation, promoting data sharing and interoperability, deepening synergistic industrial development, and expanding innovation capacity.

Partial differential equations (PDEs) are used to describe a wide range of phenomena, such as heat transfer, fluid dynamics, and quantum mechanics. By solving PDEs, we can ob- tain insights into the behavior of the system and make predictions about its future evolution. Conventional numerical methods for obtaining the approximate solutions of PDEs may re- quire extensive computational resources and time, especially for complex PDEs and large- scale problems. The recently developed physics-informed neural network (PINN) has shown promise in a variety of scientific and engineering fields by incorporating physical laws into the loss functions of the neural network (NN). In addition, the training of PINN does not require ground truth data, but it has poor generalization ability to unseen domains. On the other hand, a convolutional neural network (CNN) has fast inference and better generalization ability, but it requires a large amount of training data. Taking the advantages of PINN and CNN by using Legendre multiwavelets (LMWs) as basis functions, we introduce a new method to approach the PDEs in this paper, namely Physics-Informed Legendre Multiwavelets CNN (PiLMWs-CNN), in order to continuously approximate a grid-based state representation that can be handled by a CNN. PiLMWs-CNN enable us to train our models using only physics-informed loss functions without any pre- computed training data, simultaneously providing fast and continuous solutions that gener- alize to previously unknown domains. In particular, the LMWs can simultaneously possess compact support, orthogonality, symmetry, high smoothness, and high approximation order. Compared to orthonormal polynomial (OP) bases, the approximation accuracy can be greatly increased and computation costs can be significantly reduced by using LMWs. We applied PiLMWs-CNN to approximate the damped wave equation, incompressible Navier-Stokes (N- S) equation, and two-dimensional heat conduction equation. The experimental results show that this method provides more accurate, efficient, and fast convergence with better stability when approximating the solution of PDEs.

Grouting materials with good insulation and reinforcement performance are key factors in solving the temperature control problem of high temperature tunnels using curtain grouting, while existing grouting materials cannot balance their working performance and insulation performance in high-temperature environments. In response to the above issues, this article uses red mud to prepare high ground temperature red mud based grouting materials (RMGS), and conducts tests on the working performance (viscosity, setting time, compressive strength) and insulation performance (thermal conductivity, specific heat capacity) of grouting materials at different temperatures (20, 40, 60, and 80 ℃), and analyzes the variation patterns and micro mechanisms of various characteristics with temperature. The results indicate that an increase in temperature will accelerate the viscosity development and condensation of the grouting material, and lead to a decrease in thermal conductivity and specific heat capacity. In addition, an appropriate temperature can also improve the compressive strength of the material. The increase in temperature will accelerate the hydration reaction rate of the grouting material and the development of internal pores, which is the reason why temperature affects the performance of the grouting material. In engineering applications, cement slurry is suitable for static water grouting, cement-sodium silicate slurry is suitable for dynamic water grouting, and RMGS is suitable for high-temperature tunnel grouting.

The prefabricated ECC/RC combined shear wall structure is an innovative prefabricated composite structure with better seismic performance by using ECC materials with better ductility in the main force and energy consumption regions of the prefabricated reinforced concrete (RC) shear wall structure. The key factors controlling the seismic energy dissipation capacity of this kind of structure are the use regions of ECC in composite coupling beams, use regions of ECC in shear walls, strength of ECC, stirrup ratio of coupling beams, strength of longitudinal reinforcement and so on. The parameters affecting seismic energy consumption are quantified by the finite element analysis method. By comparing and analyzing the load-displacement curves, hysteresis curves, energy dissipation capacity and stiffness degradation of the prefabricated ECC/RC combined shear wall structure specimen under these parameters, it is proposed that the best use regions of ECC is the cast-in-situ zone of the coupling beams with the scope of no more than400 mm at the shear walls’ bottom. The strength grade, the strength grade of longitudinal reinforcement, and the stirrup ratio of coupling beams are suggested design as E40, HRB400 and 0.5%, respectively.

The recently identified Mulberry Mosaic Dwarf-associated Virus (MMDaV), associated with mosaic dwarf symptoms in Chinese mulberry leaves, is a newly discovered member of the Geminiviridae family. The MMDaV genome, a single or twin circular single-stranded DNA molecule measuring approximately 2.5-3.0 kb, encodes five proteins and two hypothetical proteins, including a coat protein (CP) and movement protein (MP). The co-evolutionary dynamics between viral and host codon usage significantly impact viral survival, fitness, immune evasion, and evolutionary pathways. This study applied bioinformatic analyses to examine the codon usage bias in thirty MMDaV genomes collected from mulberry leaves in four distinct Chinese provinces. We aimed to understand the drivers of preferred synonymous codon usage. The Effective Number of Codons (ENC) analysis revealed significant regional variations among MMDaV isolates, allowing their classification into two main categories: the southern China HNZX strain and the eastern China HDZX strain. The codon preference analysis displayed a viral preference for using A/U as the terminal base, indicating a bias towards A/U over G/C. Using a combination of position-specific base composition, ENC-Plot, RP2-Plot, Neutral plot, and correspondence analysis, we found that mutational pressure and natural selection substantially influence codon usage and drive MMDaV evolution. Our findings shed light on the complex interplay between MMDaV and its mulberry host and offer crucial insights into the virus's adaptive and evolutionary mechanisms.

The valley pseudospin properties of electrons in two–dimensional hexagonal materials result in lots of fascinating physical phenomena, which opens up the new field of valleytronics. The valley-contrasting physics aims at distinguishing the valley degree of freedom based on valley–dependent effects. Here, we theoretically demonstrate that both of the valley–selective high harmonic generation and valley–selective electronic excitation can be achieved by using an orthogonal two–color (OTC) laser field in gapped graphene. It is shown that the asymmetry degrees of harmonic yields in the plateaus, cutoff energies of generated harmonics and electron populations from two different valleys can be precisely controlled by the relative phase of the OTC laser field. Thus the selectivity of the dominant valley for the harmonic radiation and electronic polarization can be switched by adjusting the relative phase of the OTC laser field. Our work offers an all–optical route to produce the valley–resolved high harmonic emissions and manipulate the ultrafast valley polarization on a femtosecond timescale in condensed matter.

Buildings are responsible for approximately 40% of the world’s energy consumption and 36% of the total carbon dioxide emissions. Building occupancy is essential, enabling Occupant-Centric Control for zero emissions and decarbonization. Although existing machine learning and deep learning methods for building occupancy prediction have achieved remarked progress, their analyses remain limited when applied to complex real-world scenarios. Besides, there is a high expectation for Transformer algorithms to predict building occupancy accurately. Therefore, this paper presents an Occupancy Prediction Transformer network (OPTnet). We fuse and feed multi-sensor data (building occupancy, indoor environmental conditions, HVAC operations) into a Transformer model to forecast the future occupancy presence in multiple zones. We perform experimental analysis and compare it to different occupancy prediction methods (e.g., Decision Tree, Long Short-Term Memory networks, Multi-layer perceptron) and diverse time horizons (1,2,3,5,10,20,30mins). The performance metrics (e.g., Accuracy and Mean Squared Error) are employed to evaluate the effectiveness of prediction algorithms. Our OPTnet method achieves superior performance on our experimental two-week data compared to existing methods. The improved performance signifies its potential to enhance HVAC control systems and energy optimization strategies. We will make the code publicly available at https://github.com/kailaisun/occupancy-prediction-binary to promote transparency and reproducibility.

Dye wastewater containing bisphenol A (BPA) and dyes as pollutants have not been adequately studied. Our previous study revealed that thermoplastic polyurethane (TPU) nanofiber membranes (NFMs) modified by the addition of polyethyleneimine (PEI) and polydopamine (PDA) satisfactorily adsorb dyes. Herein, we first optimized the synthesis conditions for such membranes, noting a PEI:PDA monomer ratio of 2:2 and a deposition time of 48 h to be optimal. Experiments using these membranes revealed that binary systems containing BPA and the dyes (Congo red (CR), Eosin yellow (EY), or sunset yellow (SY)) exhibit three adsorption behaviors. CR and BPA compete with each other for adsorption sites, decreasing the maximum adsorption capacity (Qmax) for CR 208.3 mg/g (in a monomeric system) to 182.4 mg/g, whereas for BPA, it decreased from 26.7 to 22.8 mg/g. The adsorption rates for CR and BPA decreased from 0.002 min−1 and 0.331 min−1 in the monomeric systems to 8.37 × 10−4 min−1 and 0.072 min−1, respectively, in the binary CR–BPA system, exhibiting antagonistic effects. When EY and BPA coexist, Qmax for EY increased from 60.0 (monomeric) to 71.9 mg/g, whereas that for BPA increased from 35.6 to 43.2 mg/g, showing a synergistic effect due to the possible bridging effect. The adsorption sites for SY and BPA are independent of each other. Thus, PDA/PEI TPU NFMs exhibit the potential for removal of dye–BPA composites, whereas binary systems containing BPA with different dyes are adsorbed differently.

Alum sludge, an inevitable by-product from the water purification process, which had been applied as substrates in some constructed wetlands with good performance, especially for phosphorus (P) adsorption. The raw alum sludge is like clay lump with irregular shape and has a leaching concern used in the water. For a better reuse, herein, sludge was fired to produce alum sludge ceramsite (ASC) with a uniform spherical shape via four-step process of kneading sludge ball, air drying, preheating at 400°C for 10 min and firing at 600℃ for 5 min. Thereafter the physicochemical properties and P adsorption ability of ceramsite were investigated. Through XRD and FT-IR tests, there was no obvious difference between ASC and air-dried alum sludge ball (adASB) on the phase structure, but a certain amount of Al-OH group loss on the surface of ASC. The structure of ASC was still amorphous as same as adASB, while ASC possessed more micropore structure and bigger specific surface area than those of adASB. Adsorption experiments showed the P adsorption behaviors of ASC and adASB were much similar, and their adsorption kinetics all accorded with the two-step adsorption kinetics rate equation and pseudo-second-order kinetics equation. The maximum adsorption capacities of ASC and adASB fitted by Langmuir model were 1.66 mg/g and 1.89 mg/g respectively. It should be pointed that, compared with other adsorbents, ASC produced in this study still had a higher ability to adsorb P. Therefore, ASC should have a great application potential for P removal in the wastewater treatment in China.

The synthesis 2-tert-butyl-4-methylphenol is of great significance because of its widely application in industry, and the development of highly efficient catalyst is necessary to the alkylation of p-cresol and tert-butyl alcohol. Here, an efficient and mild method was established, caprolactam was chosen as hydrogen-bonding acceptor, p-toluenesulfonic acid was employed as hydrogen-bonding donor, and deep eutectic solvent (DES) was prepared to catalyze the alkylation reaction. The structure of the DES catalyst was characterized by 1H NMR spectra, thermogravimetric analysis and fourier transform infrared spectra (FT-IR). In addition, response surface design based on Box-Behnken method was employed to optimize the alkylation reaction process parameters, the study of reaction kinetics was also carried out subsequently. The recycle performance of the catalyst was evaluated by recovery experiments, and a good result was obtained. Comparing with the literature reported, we here provide a mild method to the synthesis of 2-tert-butyl-4-methylphenol.

The influence of pH, temperature, biopolymer ratio, total concentration, and ionic concentration on the interaction between egg white protein (EWP) and chitosan (CS) was investigated through turbidity, zeta potential, and state diagram in our research. In addition, phase behavior was observed under various conditions. The turbidity of EWP remained low (turbidity&lt;0.03) and basically unchanged at a wide range of pH (4.0-8.0), while the turbidity of CS was slightly higher (turbidity&lt;0.2) after pH 7.0 than before. Moreover, under the same conditions, a sharply rising peak pattern was observed for the complex between EWP and CS. The maximum turbidity value was observed at 55°C, and the temperature had a mild effect on turbidity. The optimum EWP to CS ratio was found to be 12:1 based on the experiment of the turbidity curves and state diagrams influenced by different biopolymer mixing ratios. With the enhanced concentrations of total biopolymer, the maximum turbidity rose insignificantly above 0.1%.

Intense thermoacoustic oscillations may lead to severe deterioration due to the induced intolerable damage to combustors. A better understanding of unstable behaviors is important to prevent or suppress these oscillations. Active thermoacoustic coupling in practical combustors is caused primarily by two approaches: inherent turbulent fluctuations and the flame response to acoustic waves. Turbulent fluctuations are generally characterized by random noise. This paper experimentally expands on previous analytic studies regarding the influence of colored disturbances on the thermoacoustic response near the supercritical bifurcation point. Therein, a laboratory-scale Rijke-type thermoacoustic system is established, and both supercritical and subcritical bifurcations are observed. Then, Ornstein–Uhlenbeck (OU)-type external colored noise is introduced near the supercritical bifurcation point, and the effects of the corresponding correlation time τc and noise intensity D are studied. The experimental results show that these variables of the colored noise significantly influence the dynamics of thermoacoustic oscillations in terms of the most probable amplitude, autocorrelation, and correlation time. A resonance-like behavior is observed as the noise intensity or the autocorrelation time of the colored noise is continuously varied, which means that the coherent resonance occurs in the thermoacoustic system. Finally, when the system is configured closer to the stability boundary, the extent of the coherence motion is intensified in the stochastic system response. Meanwhile, the Signal to Noise Ratios (SNRs) of the colored-noise-induced response are found to become more distinguished, the optimal colored noise intensity decreases, and the optimal autocorrelation time increases. This provides valuable guidance to predict the onset of thermoacoustic instabilities.

On the basis of the force and safety factor analysis of traditional retaining wall, a new analytical method of force and displacement of slope is suggested, the numerical theoretical solution of the stress distribution of the sliding body can be obtained under the conditions, which the stresses distribution are satisfied with the differential equilibrium equations, the boundary conditions, the compatibility equation and the macroscopic equilibrium equations. The interface stresses between the sliding body and the retaining wall are continuous, the theoretical solution of retaining wall stress distributions can be gotten, while the stress differential equilibrium equation, the compatibility equation, macroscopic force and moment balance equations are satisfied. The strain and displacement solutions can be obtained by using Duncan Chang and Hooke constitutive equations for the slope and the retaining wall respectively. The transfer station of landfill in the Guandukou Town of Badong County is taken as an example, the results of the sliding body and retaining wall analysis show: The stress and strain solutions of a slope and a retaining wall can be obtained by the proposed method, the forces between the retaining wall and the sliding body include shear stress and normal stress, and the stress distributions change with the deformation of the sliding body, the shape and material of retaining wall can be optimized according to the calculation results，it is feasible for the proposed analysis method of slope with retaining wall design to be run many years.

This paper proposes an encryption scheme for high pixel density images. Based on the application of the quantum random walk algorithm, the Long short-term memory (LSTM) can effectively solve the problem of low efficiency of the quantum random walk algorithm in generating large-scale pseudorandom matrices, and further improve the statistical properties of the pseudorandom matrices required for encryption. The LSTM is then divided into columns and fed into the LSTM in order for training. Due to the randomness of the input matrix, the LSTM cannot be trained effectively, so the output matrix is predicted to be highly random. The LSTM prediction matrix of the same size as the key matrix is generated based on the pixel density of the image to be encrypted, which can effectively complete the encryption of the image. In the statistical performance test, the proposed encryption scheme achieves an average information entropy of 7.9992, an average number of pixels changed rate (NPCR) of 99.6231%, an average uniform average change intensity (UACI) of 33.6029% and an average correlation of 0.0032. Finally, various noise simulation tests are also conducted to verify its robustness in real-world applications where common noise and attack interference are encountered.

In addition to provide an extremely clean environment for primary loop of high-temperature gas-cooled reactor (HTR), the primary helium circulator (PHC) using electromagnetic levitation technology also provides an effective means for vibration control. Besides synchronous vibration produced by mass imbalance and sensor runout, double-frequency vibration produced by unbalanced magnetic pull (UMP) is serious in PHC engineering prototype (PHC-EP). In this paper, we firstly analyzed the mechanism of UMP and the multi-frequency vibration characteristics in combination with the PHC-EP. Then we put forward a distributed iterative learning control (ILC) algorithm and a parallel control scheme to suppress the periodic vibrations. Finally, we verified the methods by carrying out experimental researches on the active magnetic bearing (AMB) bench of PHC-EP. The results show that the methods put forward in this paper have significant control effect on the double-frequency vibration generated by UMP of the PHC-EP, and provide theoretical and practical references for the PHC safe operation in HTR.

In this paper, the methodology using Insect Intelligent Building (I^2B) technology for establishing energy consumption monitoring system of public buildings is prevailed. The computing process node and distributed algorithm are utilized to implement the energy consumption collection and data transmission and data pre-processing. Taking a commercial building as a case study, CPNs are applied to set up the building energy consumption monitoring system, with the Spanning Tree Algorithm for generating network topology，and BPNN method for solving abnormal data and recovering missing data. The research results demonstrate the proposed method can effectively improve the performance of plug-and-play and self-identified and self-configuration of energy consumption monitoring system.

In this paper, PEN3 electronic nose was used to detect and recognize fresh and moldy apples (inoculated with Penicillium expansum and Aspergillusniger) taken Golden Delicious apples as model subject. Firstly, the apples were divided into two groups: apples only inoculated with different molds (Group A) and mixed apples of inoculated apples with fresh apples (Group B). Then the characteristic gas sensors of the PEN3 electronic nose that were most closely correlated with the flavor information of the moldy apples were optimized and determined, which can simplify the analysis process and improve the accuracy of results. Four pattern recognition methods, including linear discriminant analysis (LDA), backpropagation neural network (BPNN), support vector machines (SVM) and radial basis function neural network (RBFNN), were then applied to analyze the data obtained from the characteristic sensors, respectively, aiming at establishing the prediction model of flavor information and fresh/moldy apples. The results showed that only the gas sensors of W1S, W2S, W5S, W1W and W2W in the PEN3 electronic nose exhibited strong signal response to the flavor information, indicating were most closely correlated with the characteristic flavor of apples and thus the data obtained from these characteristic sensors was used for modeling. The results of the four pattern recognition methods showed that BPNN presented the best prediction performance for the training and validation sets for both the Group A and Group B, with prediction accuracies of 96.29% and 90.00% (Group A), 77.70% and 72.00% (Group B), respectively. Therefore, it first demonstrated that PEN3 electronic nose can not only effectively detect and recognize the fresh and moldy apples, but also can distinguish apples inoculated with different molds.

Actively controlling the camber angle to improve energy efficiency has recently gained interest due to the importance of reducing energy consumption and the driveline electrification trend that makes cost-efficient implementation of actuators possible. To analyse how much energy that can be saved with camber control, the effect of changeing the camber angles on the forces and moments of the tyre under different driving conditions should be considered. In this paper, Magic Formula tyre models for combined slip and camber are used for simulation of energy analysis. The components of power loss during cornering are formulated and used to explain the influence that camber angles have on the power loss. For the studied driving paths and the assumed driver model, the simulation results show that active camber control can have considerable influence on power loss during cornering. Different combinations of camber angles are simulated, and a camber control algorithm is proposed and verified in simulation. The results show that the camber controller has very promising application prospects for energy-efficient cornering.

At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.

Background Despite the high vaccination coverage rate, in-hospital transmission of measles continues to occur in South Korea. We present a measles outbreak in which two healthcare workers (HCWs) with presumptive evidence of measles immunity were infected by a patient with typical measles at a single hospital in South Korea. This facilitated the evaluation of measles seroprevalence in all HCWs. Methods In 2018, suspected patients and contacts exposed during a measles outbreak were investigated based on their medical histories and vaccination status. Cases were confirmed by the detection of measles-specific immunoglobulin M or RNA. After the measles outbreak, all HCWs underwent measles IgG testing for point-prevalence surveillance. In addition, we have routinely performed measles IgG tests on new HCWs since 2019. The measles vaccine was administered to HCWs who tested negative or equivocally negative for IgG antibodies. Results An index patient who returned from China with fever and rash was diagnosed with measles at a hospital in Korea. Two additional HCWs were revealed as measles cases: one was vaccinated with the 2-dose measles–mumps–rubella (MMR) vaccine, and the other, who was born in 1967, was presumed to have immunity from natural infection in South Korea. All three patients harbored the same D8 genotype. No additional measles cases were identified among the 964 contacts of secondary patients. After the measles outbreak, 2,310 HCWs underwent measles IgG tests. The average age at the time of the test was 32.6 years, and 74.3% were female. The overall seropositivity of measles was 88.9% (95% confidence interval, 87.5 –90.1). Although the birth cohorts between 1985 and 1994 were presumed to have received the measles-rubella (MR) catch-up vaccination in 2001, 175 (89.3%) HCWs were born after 1985 among the 195 seronegative cases. Conclusion Despite high population immunity, imported measles transmission occurred among HCWs, with presumed immunity. This report underscores the importance of understanding the prevalence of measles susceptibility among newly employed HCWs. This is important for policymaking regarding hospital-wide vaccinations to prevent vaccine-preventable diseases.

Aiming at the problem of small size of some spots on apple leaves and the difficulty of accurate detection of spot targets brought by the complex background of the orchard, this paper takes the alternaria leaf spot, rust, brown spot, grey spot and frog eye leaf spot on apple leaves as the research object, and proposes a high-accuracy detection model YOLOv5-Res and lightweight detection model YOLOv5-Res4 are proposed. Firstly, a multiscale feature extraction module ResBlock is designed by combining the Inception multi-branch structure and ResNet residual idea. Secondly, a lightweight feature fusion module C4 is designed to reduce the number of model parameters while improving the detection ability of small targets. Finally, a parameter streamlining strategy based on optimized model architecture is proposed. The experimental results show that the performance of YOLOv5-Res model and YOLOv5-Res4 model is significantly improved, the [email protected] value is improved by 2.8% and 2.2% compared with YOLOv5s model and YOLOv5n model, respectively, and the size of YOLOv5-Res model and YOLOv5-Res4 model is only 10.8MB and 2.4MB, and the number of model parameters is reduced compared with YOLOv5s model and YOLOv5n model. counts are reduced by 22% and 38.3% compared to the YOLOv5s model and YOLOv5n model.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rain water. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima (2019). The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increases approximately 17%~18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

Background: This study investigated how the expression of heat shock protein 27 (HSP27), cellular FLICE-like inhibitory protein (cFLIP) and clusterin (CLU) affects the progression of cancer cells and their susceptibility to doxazosin-induced apoptosis. By silencing each of these genes individually, their effect on prostate cancer cell viability after doxazosin treatment was investigated. Methods: PC-3 prostate cancer cells were cultured and then subjected to gene silencing using siRNA targeting HSP27, cFLIP, and CLU, either individually, in pairs, or all together. Cells were then treated with doxazosin at various concentrations and their viability was assessed by MTT assay. Results: The study found that silencing the CLU gene in PC-3 cells significantly reduced cell viability after treatment with 25 µM doxazosin. In addition, dual silencing of cFLIP and CLU decreased cell viability at 10 µM doxazosin. Notably, silencing all three genes of HSP27, cFLIP, CLU was most effective and reduced cell viability even at a lower doxazosin concentration of 1 µM. Conclusions: Taken together, these findings suggest that simultaneous silencing of HSP27, cFLIP, and CLU genes may be a potential strategy to promote apoptosis in prostate cancer cells, which could inform future research on treatments for malignant prostate cancer.

Natural alkaloids of actinomycetes origin and synthetic derivatives have always been among the important suppliers of small-molecule drugs. Among their biological sources, Streptomyces is the highest and most extensively researched genus. Marine-derived Streptomyces strains harbor unconventional metabolic pathways and have been demonstrated to be efficient producers of biologically active alkaloids since more than 60% of these compounds exhibit valuable activity such as antibacterial, antitumor, anti-inflammatory activity, etc. This review comprehensively summarizes novel alkaloids produced by marine Streptomyces discovered in the past decade, focusing on their structural features, biological activity and pharmacological mechanisms. Future perspectives on the discovery and development of novel alkaloids from marine Streptomyces are also provided.

Folk residence in the cold region of Northeast China is an important part of China's traditional folk residence, with significant geographical representation. In this paper, we take the residential compounds of villages and towns in the cold region of Northeast China as the research object, summarize four typical layout forms of residential compounds of villages and towns in the cold region of Northeast China, simulate the wind environment of compounds of different layout forms in winter by using the computer numerical simulation software Fluent, and then analyze and evaluate the wind environment of compounds by combining with the evaluation standard of wind speed ratio and considering the area of wind shadows, number of vortices and other factors.

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Hydraulic fracturing is an efficient method to develop oil/gas resources economically. Temporary plugging and diverting fracturing (TPDF) can generate diversion fractures perpendicular to the initial fractures and enhance the stimulated area. The aperture of the diversion fractures determines its conductivity and the oil/gas production. This work established a fluid-solid fully coupled simulation model to investigate the fracture aperture influenced by various factors during TPDF. The factors include the permeability of the tight plug, the length of the tight plug, Young’s modulus, rock tensile strength, in-situ stress contrast, the leak-off coefficient of the fracture surface, and fluid injection rate. Results show that the aperture of the previous fracture can be enlarged, and the aperture of the diversion fracture can be decreased by the tight plug. The aperture at the diversion fracture mouth is much smaller than that along the diversion fracture. Reservoirs with low Young’s modulus and high rock tensile strength can generate the diversion fracture with a wider aperture. Moreover, increasing the fluid injection rate can effectively increase the fracture mouth aperture. In this way, the risk of screenout can be lowered. This work is beneficial for the design of the TPDF and ensures safe construction.

Building heterojunction is promising strategy for the achievement of highly efficient photocatalysis. In this study, a novel SnIn4S8@ZnO Z-scheme heterojunction with tight contact interface was successfully constructed through a facile two-step hydrothermal method. The phase composition, morphology, and photophysical properties of SnIn4S8@ZnO were studied through a series of characterization methods, respectively. Methylene blue (MB) was selected as the target pollutant for photocatalytic degradation and the degradation process was fitted with pseudo-first order kinetics. The as-prepared SnIn4S8@ZnO heterojunctions exhibited outstanding photocatalytic activities for the degradation of MB. The optimized sample (ZS800), in which the molar ratio of ZnO to SnIn4S8 was 800, displayed the highest photodegradation efficiency of MB (91%) within 20 min. Furthermore, the apparent rate constant of photodegradation for MB of ZS800 (0.121 min−1) was 2.2 times higher than that of pure ZnO (0.054 min−1). The improvement of photocatalytic activity could be attributed to the effective spatial separation of photogenerated charge carriers through a Z-scheme heterojunction with intimate contact interface. This work will provide a new insight into constructing excellent ZnO-based photocatalytic systems for wastewater purification.

As one of the most critical parameters to evaluate the quality and performance of mobile phones, real-time temperature monitoring of the mobile phone integrated chips is vitally important in the electronics industry. Although several different strategies for chip surface temperature measurement have been proposed in recent years, distributed temperature monitoring with the high spatial resolution is still a hot issue to be solved urgently. In this work, a fluorescent film material with photothermal properties containing thermosensitive upconversion nanoparticles (UCNPs) and polydimethylsiloxane (PDMS) is fabricated for chip surface temperature monitor-ing. The presented fluorescent films have thicknesses ranging from 23 to 90 μm and are both flexible and elastic. Using the fluorescence intensity ratio (FIR) technique, the temperature sens-ing properties of these fluorescent films are investigated. The maximum sensitivity of the fluo-rescent film was measured to be 1.43% K-1 at 299 K. By testing the temperature at different posi-tions of the optical film, a distributed temperature monitoring with a high spatial resolution down to 10 μm on the chip surface is successfully achieved. It is worth mentioning that the film maintains stable performance even under pull stretch up to 100%. The correctness of the method is verified by taking infrared images of the chip surface with an infrared camera. These results demonstrate that the as-prepared optical film is a promising anti-deformation material for high spatial resolution temperature monitoring on-chip surfaces.

Blind deconvolution (BD) is one of the effective methods that help pre-process vibration signals and assist in bearing fault diagnosis. Currently, most BD methods design an optimization criterion and use frequency or time domain information independently to optimize a deconvolution filter. It recovers weak periodic impulses related to incipient faults. However, the random noise interference may cause the optimizer to overfit. The time-domain-based BD methods tend to extract fault-unrelated single peak impulse, and the frequency-domain-based BD methods tend to retain the maximum energy frequency component, which will lose the fault-related harmonics frequency components. To solve the above issue, we propose a hybrid criterion that combines the kurtosis for time domain optimization and the $G-l_1/l_2$ norm for the frequency domain. These two criteria are monotonically increasing and decreasing, so they mutually constrain to avoid overfitting. After that, we design a multi-task one-dimensional convolutional neural network with time and frequency branches to achieve an optimal solution for this hybrid criterion. The multi-task neural network realizes the simultaneous optimization of two domains. Experimental results show that our proposed method outperforms other state-of-the-art methods.

The processes of soliton generation and interference focus on the complex nonlinear soliton dynamics resembling matter particles. In order to further understand the dynamic process of solitons from a multidimensional perspective, here we report the vectorial solitons nature under two-sets pulse splitting in a single cavity induced by dual-core fiber assisted ultrafast fiber lasers. Owing to the weakly coupled cores in symmetrical dual core fiber (SDCF), two pulse groups interaction are formed in a cavity. By using the dispersive Fourier transformation technique (DFT), it was found that the four-component polarized rotation vector solitons (PRVS) generate. Moreover, gradually increasing the power can obtain the locked soliton bound state in two core space, and the corresponding evolution is similar to that of non-degenerate bright solitons in Bose Einstein condensates (BEC). In addition, by properly controlling the soliton phase offset in SDCF, the soliton rain state of multi pulse evolution can be obtained. The related experimental results would be fruitful to the communities interested in soliton dynamics and frequency comb lasers.

Fusarium oxysporum f. sp. lycopersici (Fol) causes vascular wilt disease in tomato. Upon colonization of the host, Fol secretes many small effector proteins into the xylem sap to facilitate infection. Besides known SIX (Secreted In Xylem) proteins, the identity of additional effectors that contribute to Fol pathogenicity remains largely unexplored. We have performed a deep RNA-sequencing analysis of Fol race 2-infected tomato, used the sequence data to annotate a published genome assembly generated via PacBio SMRT sequencing of the Fol race 2 reference strain Fol4287, and analysed the resulting transcriptome to identify Fol effector candidates among the newly annotated genes. We examined the Fol-infection expression profiles of all 13 SIX genes present in Fol race 2 and identified 27 new candidate effector genes that were likewise significantly upregulated upon Fol infection. Using Agrobacterium-mediated transformation, we tested the ability of 22 of the new candidate effector genes to suppress or induce cell death in leaves of Nicotiana benthamiana. One effector candidate designated Fol-EC19, encoding a secreted guanyl-specific ribonuclease, was found to trigger cell death and two effector candidates designated Fol-EC14 and Fol-EC20, encoding a glucanase and a secreted trypsin, respectively, were identified that can suppress Bax-mediated cell death. Remarkably, Fol-EC14 and Fol-EC20 were also found to suppress I-2/Avr2- and I/Avr1-mediated cell death. Using the yeast secretion-trap screening system, we showed that these three biologically-active effector candidates each contain a functional signal peptide for protein secretion. Our findings provide a basis for further understanding the virulence functions of Fol effectors.

Background: We aimed to assess the risk of chemotherapy- and radiotherapy-related cognitive impairment in colorectal cancer patients. Methods: We randomly selected 40% of colorectal cancer patients from Korean National Health Insurance Database (NHID), 2004-2018 (N=148,848). Patients with one or more ICD-10 diagnostic codes for dementia or mild cognitive impairment was defined as cognitive impairment cases. Patients who were aged 18 or younger, diagnosed with cognitive impairment before colorectal cancer (N=8,225) and did not receive primary resection (N=45,320) were excluded. The effects of each chemotherapy agent on cognitive impairment were estimated. We additionally estimated the effect of radiotherapy in rectal cancer patients. Time-dependent competing risk Cox regression was conducted to estimate overall and age-specific hazard ratios (HR) separately for colon and rectal cancer. Results: In colon cancer, capecitabine and irinotecan was associated with higher cognitive im-pairment, while 5-fluorouracil was not. In rectal cancer, no chemotherapy agents increased the risk of cognitive impairment, nor did radiotherapy. Hazardous association of irinotecan was estimated larger in elderly patients compared with younger counterparts. Conclusion: Heterogeneous associations between various chemotherapy agents and cognitive impairment were observed. Elderly patients were more vulnerable to possible adverse cognitive effects. Radiotherapy did not increase the risk of cognitive impairment.

In this work, the recently proposed cracking elements method (CEM) is used for simulating the damaging processes of structures with initial imperfections. CEM is built in the framework of conventional FEM which is formally like a special type of finite element. The disconnected piecewise cracks are used for representing crack paths. Taking the advantages of CEM that both the initiations and propagations of cracks can be naturally captured, we numerically study the uni-axial compression tests of specimens with multiple joints and fissures, where the cracks may propagate from the tips, or from some other unexpected positions. Though uni-axial compression tests are considered, mainly tensile damage criteria are used in the numerical model. On one hand, the results demonstrate the robustness and effectiveness of the CEM while on the other hand, some drawbacks of the present model are demonstrated, showing the future work.

Corporate governance is widely suggested by economists and regulators as a solution to reduce agency problems and improve firm performance. However previous studies have failed to generate consistent results. Using a dynamic panel system GMM estimator to alleviate endogeneity concerns we determine the effect of corporate board structure on the performance of a panel of 1265 Chinese firms listed on the Shanghai and Shenzhen stock exchanges from 2010 to 2016. We compare the dynamic system GMM estimator to some commonly used estimators; ordinary least squares (OLS), fixed effects (FE) and the dynamic OLS, and show that these estimates are biased due to endogeneity. The dynamic system GMM estimator incorporates the dynamic nature of internal governance choices to provide valid and powerful instruments that address unobserved heterogeneity and simultaneity. Our results show support for the board model corporate governance mechanism. We find that board size is positive and significantly related to both return on assets and total net profit margin. In addition board independence is positive and significantly related to return on assets but insignificantly related to total net profit margin. Duality was found to have a negative but statistically insignificant relation with firm performance.

The underground injection and geological sequestration of carbon dioxide (CO₂) is a promising approach for reducing the levels of CO₂ in the atmosphere. To mitigate the leakage of CO₂ resulting from natural fracture networks in rock masses, the sequestration process is commonly accompanied by the injection of reactive Portland cement representing a coupled hydro-chemo-mechanical process. In this work, a numerical approach based on the unified pipe network method (UPM) is presented that considers the coupled permeation and diffusion processes with chemical precipitation. Most input parameters are derived from the published literature. The proposed approach is validated through a comparison with analytical solutions, which are applied to simulate the CO₂ sequestration process in a fractured rock mass. The results indicate that the long-term sequestration effect, which is highly influenced by the fracture distribution, can be captured effectively by the model. Consequently, the presented approach can assist engineers in properly designing the arrangement of boreholes and determining the concentration of the grouting material.

Cu,N-TiO₂ nanotube (Cu,N-TNT) is prepared through a novel magnetron sputtering and anodic oxidation method. Then the morphology, structure and physicochemical property of Cu,N-TNT was analyzed by XRD, SEM, TEM, EDX and UV-vis-DR. The results indicate that the evenly doped copper is beneficial to the transformation of the TNT from anatase to rutile and play a key role in the morphology of the Cu,N-TNT. The doped Cu and N in the TNT influence the growth orientation of the TiO₂ crystals, which result in the lattice distortion and wider the interplanar spacing 60s-Cu,N-TNT has less band gap and stronger absorption intensity in visible region than other Cu,N-TNT samples, which make the combination rate of photogenerated electron and photogenerated hole decrease greatly, thus beneficial to its physicochemical property.

The surface planarity and asperity removal behaviors of atomic scale under the ultrathin water environment was studied for the nanoscale process by molecular dynamics simulation. The monolayer atomic removal was achieved under the noncontact and monoatomic layer contact conditions with different water film thickness, and the newly formed surface is relatively smooth and no deformed layer and plastic defects exist. The nanoscale processing is governed by the interatomic adhering action during which the water film transmits the loading forces to Cu surface and thereby result in the migration and removal of surface atoms. With scratching depth ≥ 0.5 nm, the abrasive particle squeezed out the water film from scratching region and scratched Cu surface directly, leading to the surface quality deterioration mainly governed by the plowing action. This study brings the goals of “0 nm planarity, 0 residual defects and 0 polishing pressure” closer to us in the nanoscale process for the development of ultra-precision manufacture technology.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

The effect of Al or Cu content on the microstructure and mechanical properties of continuous casting and extrusion Zn alloys has been studied by room temperature tensile test, X-ray diffraction, and scanning electron microscope. With the increase of Al content, the microstructure of continuous casting and extrusion Zn alloys slightly coarsens and the lamellar eutectic structure increases. The changes in the above structural factors result in a slight decrease in strength and a significant increase in elongation of Zn-Al alloys. The strength of Zn alloys increases as the Cu content increases, due to the increased content and size of the second phase in the Zn alloys. This means that the mechanical properties of Zn alloys can be adjusted by continuous casting and extrusion process, and the improvement of equipment capacity can improve the structure and morphology of the alloys.

This paper proposes a solution for the problem of mobile robot navigation and trajectory interpolation in dynamic environments with large scenes. The solution combines a semantic laser SLAM system that utilizes deep learning and a trajectory interpolation algorithm. The paper first introduces some open-source laser SLAM algorithms and then elaborates in detail on the general framework of the SLAM system used in this paper. Secondly, the concept of voxel is introduced into the occupation probability map to enhance the ability of local voxel maps to represent dynamic objects. Then, in this paper, we propose a PointNet++ point cloud semantic segmentation network combined with deep learning algorithms to extract deep features of dynamic point clouds in large scenes and output semantic information of points on static objects. A descriptor of the global environment is generated based on its semantic information. Closed-loop completion of global map optimization is performed to reduce cumulative error. Finally, T-trajectory interpolation is utilized to ensure the motion performance of the robot and improve the smooth stability of the robot trajectory. The experimental results indicate that the combination of the semantic laser SLAM system with deep learning and the trajectory interpolation algorithm proposed in this paper yields better graph building and loop closure effects in large scenes at SIASUN large scene campus. The use of T-trajectory interpolation ensures vibration-free and stable transitions between target points.

a sensorless control scheme based on novel power converging law sliding mode observer is suggested to realize the sensorless control for the permanent magnet synchronous motor (PMSM). Firstly, by introducing a new power converging law, the problem of slow converging speed/large chattering value dilemma in the conventional converging law is solved; Secondly, in view of the shortcomings of the conventional position and speed estimation algorithm, the high-frequency buffeting in the sliding mode observer will be expanded, a phase-locked loop (PLL) velocity and position estimation strategy is adopted to replace it. Finally, through Matlab/Simulink modeling and motor speed regulation platform experimental results, the sensorless position and speed estimation technology proposed in this paper can respond to the starting speed command of 1000 r/min within 0.05 s, and the starting process has no overshoot. When disturbed by 10Nm loading, the speed fluctuation value can be controlled within 1%.

Few-shot fine-grained image classification (FSFGIC) methods refer to machine learning methods which aim to classify images (e.g., bird species, flowers, and airplanes) belonging to subordinate object categories of the same entry-level category with only a few samples. It is worth to note that feature representation learning is used not only to represent training samples, but also to construct classifiers for performing various FSFGIC tasks. In this paper, starting from the definition of FSFGIC, a taxonomy of feature representation learning for FSFGIC is proposed. According to this taxonomy, we discuss key issues on FSFGIC (including data augmentation, local or/and global deep feature representation learning, class representation learning, and task specific feature representation learning). The existing popular datasets and evaluation standards are introduced. Furthermore, a novel classification performance evaluation mechanism is designed with a 0.95 confidence interval for judging whether the classification accuracy obtained by a certain specified method is good or bad. Moreover, current challenges and future trends of feature representation learning on FSFGIC are elaborated.

The aim of our present study was to investigate the effects of Gln supplementation on liver inflammatory responses and protein synthesis and degradation in muscle of LPS-challenged broilers. A total of 120 1d-old male broilers (Arbor Acres Plus) were randomly arranged in a 2 × 2 factorial design with five replicates per treatment and six broilers per replicate, containing two main factors: immune challenge (injected with LPS in a dose of 0 or 500 µg/kg of body weight) and dietary treatments (supplemented with 1.22% alanine or 1% Gln). After feeding with alanine or Gln diet for 15 days, broilers were respectively administrated with LPS or saline injection at 16 and 21 d. The results showed that Gln supplementation significantly reversed the adverse effects of LPS administration on growth performance, as evidenced as the increased ADFI and ADG, as well as the lowered F/G. Furthermore, Gln supplementation alleviated the increased mRNA expression of interleukin-6, interleukin-1β and tumor necrosis factor-α in liver induced by LPS. Moreover, the increased activities of aspartate aminotransferase, combined with the decreased expression of glutaminase in muscle, were observed by Gln addition. In addition, in comparison with saline treatment, LPS challenge altered signaling molecules mRNA expressions associated with protein synthesis and degradation. However, Gln supplementation reversed the negative effects on protein synthesis and degradation in muscle of LPS-challenged broilers. Taken together, Gln supplementation had benefit effects on improving growth performance, alleviating inflammatory responses, promoting protein synthesis and inhibiting protein degradation of LPS-challenged broilers.

Building energy consumption is the main urban energy consumption component, which mainly serves people-centered work and living energy demands. Based on the physical requirements of humans in urban buildings and to determine the comfortable body temperature in each season, this paper establishes a sizing optimization model of building-type integrated energy systems (IES), where the cooling and heating loads required to maintain indoor somatosensory body comfortable temperature are calculated. Depending on the external energy price, internal power balance and other constraints, the model develops an optimal sizing and capacity panning method of energy conversion and storage unit in a building-type IES with PV generation. The operating principle is described as follows: the PV generation is fully consumed, a gas engine satisfies the electric and thermal base load requirements, while the power system and a heat pump supply the remaining loads. The gas price, peak-valley electricity price gap and heat-topower ratio of gas engines are considered as important factors for the overall techno-economic analysis. The developed method is applied to optimize the economic performance of building-type IES and verified by practical examples. The results show that using the complementary characteristics of different energy conversion units is important to the overall IES cost.

Wencheng waxy yam is famous for its glutinous and resilient taste, similar to waxy rice, but there is currently a lack of systematic research on the quality of this featured product, and little is known about its pesticide residues. We carried out a 2-year investigation of Wencheng waxy yam at seven sites from 2021 to 2022 to determine the oxidase content and phytochemical characteristics, namely amylose, amylopectin, protein, reducing sugar, and mineral contents such as K, Fe, and Zn, , including the status of pesticide residues. The results showed that oxidase content was affected by rainfall, and adequate water reduced the production of oxidase, including polyphenol oxidase (PPO), peroxidase (POD), and superoxide dismutase (SOD), during the late growth stage of waxy yam, which was beneficial for reducing browning in yam processing. Radar map analysis showed that, with comprehensive evaluation, standardized production sites 1 and 2 had a relatively higher quality than 3–7 with small farmers. The results of pesticide multi-residue testing showed that no pesticides were detected in 64.29% samples, and the detected residues samples were very low, making the consumption of yam safe for consumers. These findings could be beneficial for the exploitation of the health benefits of waxy yam tubers and the innovation of yam-based functional products.

TiC particles were prepared from Ti and C powders, and TiC-reinforced Cu-based composites were prepared by powder metallurgy with SPS sintering. The effects of SPS sintering temperature and TiC particle reinforcement phase content on the electrical and mechanical properties of Cu-based composites were investigated. The reinforcement of TiC particles by thermal mismatching at increasing sintering temperature has a significant strengthening effect on the composites, but the high temperature causes softening of the Cu matrix and the growth of grains reduces the properties of the composites. In this study, the effects of porosity and density on the composite properties were not significant.

Effective oral care is a critical requirement to maintain high quality of life. Most oral diseases are caused by plaque (oral biofilm), which is also correlated with systemic diseases. A common method to remove biofilm is brushing teeth with a toothpaste. However, 3.5 billion people in the world have oral diseases, meaning that more efficient methods of removing biofilms are needed. We have developed a toothbrush applying bioelectric effect (BE) utilizing an electric force for biofilm removal. It demonstrated significantly higher biofilm removal efficiency than non-BE manual toothbrushes. Tests were performed in saline and toothpaste conditions using various pressure. Results showed that the BE toothbrush had a significantly higher biofilm removal efficiency in saline (0.5 N: 215.43 ± 89.92 %, 2.5 N: 116.77 ± 47.02 %) and in a toothpaste slurry (0.5 N: 104.96 ± 98.93 %, 2.5 N: 96.23 ± 35.16 %) than non-BE manual toothbrushes. Results also showed that BE toothbrushes were less dependent on toothpaste. This study suggests that the application of BE can be a new solution to plaque problems in oral care.

Examining the clustering characteristics and fluctuations within urban areas during peak hours through the lens of bike-sharing is of utmost importance in the optimization of bike-sharing systems and urban transportation planning. This investigation adopts the principles of urban spatial interaction network construction and employs streets as the fundamental units of analysis to model bike-sharing activities during morning and evening peak hours within Beijing's six central districts. Subsequent to this, a comprehensive analysis of the network's structural attributes was carried out. A walktrap method rooted in modularity analysis was introduced to discern and scrutinize the clustering patterns and characteristics of communities within the network across different temporal intervals. Empirical findings reveal a predominant usage pattern of shared bicycles for short-distance travel during both morning and evening peak hours. Notably, distinctive community structures manifest during these periods, characterized by two large communities and multiple smaller ones during the morning peak, while the evening peak showcases a single large community alongside several medium-sized and smaller ones. Moreover, the extended interaction radius points to an expanded geographic range of interactions among streets. These findings bear significant implications for the management of urban transportation, bike-sharing enterprises, and urban residents, proffering valuable insights for the optimization of bike-sharing schemes and transportation strategies.

In response to the issue of vehicle escape guidance, this manuscript proposes a unified intelligent control strategy synthesizing optimal guidance and Meta Deep Reinforcement Learning (DRL). Optimal control with minor energy consumption is introduced to meet terminal latitude, longitude and altitude. Maneuvering escape is realized by adding longitudinal and lateral direction maneuver overloads. Maneuver command decision model is calculated based on Soft-Actor-Critic (SAC) networks. Meta learning is introduced to enhance autonomous escape capability, which improves generalization performance to time-varying scenarios not encountered in the training process. In order to obtain training samples at a faster speed, this manuscript uses the prediction method to solve reward values, which avoiding a large number of numerical integration. The simulation results manifest that the proposed intelligent strategy can achieve high precise guidance and effective escape.

Polycyclic aromatic hydrocarbons (PAHs) have been reported to cause oxidative stress in metabolic processes. This study aimed to evaluate the relationship between exposure to PAHs, including benzo[a]pyrene (BaP) and 1-nitropyrene (1-NP), in the atmosphere and oxidative stress levels in the human body. This study included 44 Korean adults who lived in Cheongju, South Korea. Atmospheric BaP and 1-NP concentrations and urinary 6-hydroxy-1-nitropyrene (6-OHNP), N-acetyl-1-aminopyrene (1-NAAP), and 1-hydroxypyrene (1-OHP) concentrations were measured. The oxidative stress level was assessed by measuring urinary thiobarbituric acid reactive substances (TBARS) and 8-hydroxydeoxyguanosine (8-OHdG) concentrations. Urinary TBARS and 6-OHNP concentrations significantly differed between winter and summer. BaP exposure was significantly associated with urinary 8-OHdG concentrations in summer. However, atmospheric 1-NP did not show a significant correlation with oxidative stress marker concentrations. Urinary 1-NAAP concentration was a significant determinant for urinary 8-OHdG concentration in summer. Oxidative stress in the body increases in proportion to inhalation exposure to BaP, and more 8-OHdG is produced in the body as the amount of 1-NP, which is metabolized to 1-AP or 1-NAAP, increases.

Global warming is increasing the frequency and intensity of compound drought-heat events (CDHEs), potentially leading to larger and more extreme fire seasons in mesic forests. Wildfire activity in subtropical China, under the influence of monsoonal rainfall, was historically limited to dry winters and rare in rainy summers. Here we seek to test that this area is on the brink of a major change in its fire regime characterized by larger fire seasons, extending into the summer, leading to increases in burned area. We analyze fire activity in Chongqing Municipality (46,890 km2), an important area in subtropical China hosting the Three Gorges Reservoir Area. We observed significant increases in summer forest fires under anomalous dry-hot summer conditions, where total burned area was 3-6 higher than the historical annual mean (largely confined to the winter season). Vapor pressure deficit, an indicator of hot and dry conditions, was a strong predictor of fire activity, with major wildfires occurring on days where VPD was higher than 3.5kPa. Results indicate that major wildfire activity may occur in the area as a result of climate change, unless strong fire prevention policies are implemented.

Aiming at the problem of low charging efficiency caused by the scattered sensor nodes in traditional wireless rechargeable sensor networks (WRSNs), a UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means (UOCS) is proposed. The scheme assumes that the energy consumption of nodes is unpredictable, and only generates charging requests when the energy is lower than a threshold, and performs on-demand responses to nodes that issue charging requests. The scheme combines the characteristics of one-to-one charging of UAVs, the selection and allocation timing of waiting queues and the number of UAVs, and the improved K-means partitioning based on space-time coordination(SPKM), which simplifies the problem of coordinated charging of multiple UAVs and maximizes energy. Using the efficiency and charging success rate, the optimal charging trajectory can be found under the constraint that the node will not starve to death due to power shortage. Finally, a simulation comparison experiment is carried out with the existing UAV charging scheduling strategy. UOCS achieves the optimal node survival rate with low algorithm complexity.

Photosynthetic function, photoprotection, and the response of related proteomics of mulberry (Morus alba L.) seedling leaves under NaCl and NaHCO3 stress with the same Na+ concentration (100 mmol•L-1) were studied by using photosynthetic gas exchange and chlorophyll fluorescence techniques combined with TMT proteomics. The results showed that NaCl stress had no significant effect on photosystem II (PSII) activity in mulberry seedling leaves, and the expressions of the related proteins, OEE3-1 and PPD4, of the PSII oxygen-evolving complex (OEC) and the antenna proteins, CP24 10A, CP26, and CP29, of LHCII in the leaves also increased to varying degrees. The photosystem I (PSI) activity in the leaves of mulberry seedling also increased, and the expressions of some proteins, PsaF, PsaG, PsaH, PsaL, PsaN, and Ycf4, in PSI increased significantly under NaCl stress. Under NaHCO3 stress, the activity of PSII and PSI and the expression of their protein complexes and the electron transfer-related proteins significantly decreased. NaCl stress had little effect on RuBP regeneration during dark reaction in the leaves and the expressions of glucose synthesis related proteins and net photosynthetic rate (Pn) did not decrease significantly. The leaves could adapt to NaCl stress by reducing stomatal conductance (Gs) to increase water use efficiency (WUE). Under NaHCO3 stress, the expression of dark reaction-related proteins was mostly down-regulated, and Gs was significantly reduced, which indicated that non-stomatal factors were important reasons for the significant inhibition of carbon assimilation. In the photoprotective mechanism under NaCl stress, the expression of cyclic electron flow (CEF) related proteins, ndhH, ndhI, ndhK, and ndhM, involved in NAD(P)H dehydrogenase (NDH) and the key enzyme of the xanthophyll cycle, violaxanthin de-epoxidase (VDE) were up-regulated. In addition, the ratio of xanthophyll cycle components (A+Z)/(V+A+Z) was increased. The expressions of proteins FTR and Fd-NiR, which are related to Fd-dependent ROS metabolism and nitrogen metabolism, were also significant up-regulated under NaCl stress, which can effectively reduce the electronic pressure on Fd. Under NaHCO3 stress, the expressions of CEF-related proteins, VDE, ZE, FTR, Fd-NiR, Fd-GOGAT, SGAT, and GGAT, were significant down-regulated, and the photoprotective mechanism, like the xanthophyll cycle, CEF, and photorespiration, might be damaged, resulting in the inhibition of PSII activity and carbon assimilation in leaves of mulberry seedling under NaHCO3 stress.

Murine herpesvirus-68 (MHV-68) productively infects the mouse lungs, exhibiting a complex pathology characteristic of both acute viral infections and chronic respiratory diseases. We sought to discover proteins differentially expressed in bronchoalveolar lavage (BAL) from mice infected with MHV-68. Mice were infected intranasally with MHV-68. After 9 days, as the lytic phase of infection resolved, differential BAL proteins were identified by 2D electrophoresis and mass spectrometry. Of 23 unique proteins, acute phase proteins, vitamin A transport, and oxidative stress response factors Pdx6 and EC-SOD (Sod3) were enriched. Correspondingly, iNOS2 was induced in lung tissue by 7 days post infection. Oxidative stress was partly a direct result of MHV-68 infection, as reactive oxygen species (ROS) were induced in cultured murine NIH3T3 fibroblasts and human lung A549 cells infected with MHV-68. Finally, mice were infected with a recombinant MHV-68 co-expressing inflammatory cytokine murine interleukin 6 (IL6) showed exacerbated oxidative stress and soluble type I collagen characteristic of tissue recovery. Thus, oxidative stress appears to be a salient feature of MHV-68 pathogenesis, in part caused by lytic replication of virus and IL6. Proteins and small molecules in lung oxidative stress networks therefore may provide new therapeutic targets to ameliorate respiratory virus infections.

Effect of abrasive shape on the three-body abrasion behaviors of monocrystalline silicon was investigated by Molecular dynamics modelling. The axial ratio of abrasive particle was varied from 1.00, i.e., a complete sphere, to 0.40 to mimic abrasive shape. The particle’s movement turns toward sliding from rolling when the axial ratio becomes less than a critical value 0.46. In the abrasion process, the friction force and normal force showed an approximately sinusoid-like fluctuation for the rolling ellipsoidal particles, while the front cutting of particle caused that friction force increased and became larger than normal force for sliding particles. The phase transformation process was tracked under different particle’ movement patterns. The Si-II and Bct5 phase producing in loading process can partially transform to Si-III/Si-XII phase and backtrack to original crystal silicon under pressure release, which also occurred in the abrasion process. The secondary phase transformation showed difference for particles’ rolling and sliding movements after three-body abrasion. The rolling of particle induced the periodical and inhomogeneous deformation of substrates, while the sliding benefited producing high-quality surface in CMP process. This study aiming to construct more precise model to understand the wear mechanism benefits evaluating the MEMS wear and CMP process of crystal materials.

Watermelon fusarium wilt caused by Fusarium oxysporum f.sp. niveum (FON) is a destructive soil-borne disease throughout the world leading to serious economic losses and limit watermelon production. Cuminic acid, extracted from the seed of Cuminum cyminum L., belongs to benzoic acid analogues. In this study, the median effective concentration (EC₅₀) values for cuminic acid in inhibiting mycelial growth of FON was 22.53μg/mL. After treatment with cuminic acid, mycelial morphology was seriously influenced; cell membrane permeability and glycerol content were increased markedly, but pigment and mycotoxin (mainly fusaric acid) were significantly decreased. Synthesis genes of bikaverin and fusaric acid both were down regulated compared with the control confirmed by quantitative RT-PCR. In greenhouse experiments, cuminic acid at all concentrations displayed significant bioactivities against FON. Importantly, significant enhancement of activities of SOD, POD, CAT and decrease of MDA content after cuminic acid treatment in watermelon leaves were observed in vivo. These indicated that cuminic acid not only showed high antifungal activity, but also could enhance the self-defense system of the host plant. Above all, cuminic acid showed the potential as a biofungicide to control FON.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

Real-time strategy (RTS) game has proposed many challenges for AI research for its large state spaces, enormous branch factors, limited decision time and dynamic adversarial environment. To tackle above problems, the method called Adversarial Hierarchical Task Network planning (AHTN) has been proposed and achieves favorable performance. However, the HTN description it used cannot express complex relationships among tasks and impacts of environment on tasks. Moreover, the AHTN cannot handle task failures during plan execution. In this paper, we propose a modified AHTN planning algorithm named AHTNR. The algorithm introduces three elements essential task, phase and exit condition to extend the HTN description. To deal with possible task failures, the AHTNR first uses the extended HTN description to identify failed tasks. And then a novel task repair strategy is proposed based on historical information to maintain the validity of previous plan. Finally, empirical results are presented for the μRTS game, comparing AHTNR to the state-of-the-art search algorithms for RTS games.