Miracle-dz/UniFAR-FTUs huggingface dataset:
A secreted salivary effector from Riptortus pedestris impairs soybean defense through modulating phytohormone signaling pathways

Riptortus pedestris (Fabricius), one of the major piercing‐sucking insects in soybeans, causes delayed plant senescence and abnormal pods, known as staygreen syndrome. Recent research has shown that direct feeding of this insect is the major cause of soybean staygreen syndrome. However, it remains unclear whether R. pedestris salivary proteins play vital roles in insect infestation. Here, we found that 4 secretory salivary proteins can induce cell death in Nicotiana benthamiana by transient heterologous expression. The cell death induced by Rp2155 relies on the nucleotide‐binding leucine‐rich repeat helper, HSP90. Tissue‐specificity assays indicated that Rp2155 is specifically expressed in the salivary gland of R. pedestris and is significantly induced during insect feeding. The expression of salicylic acid (SA)‐, jasmonic acid (JA)‐related genes was increased in soybean when fed by Rp2155‐silenced R. pedestris. More importantly, soybean staygreen symptoms caused by R. pedestris were significantly alleviated when Rp2155 was silenced. Together, these results suggest that the salivary effector Rp2155 is involved in promoting insect infestation by suppressing the JA and SA pathways, and it can be considered as a potential RNA interference target for insect control.
SARS-CoV-2 Seroprevalence and Cross-Variant Antibody Neutralization in Cats, United Kingdom

Anthropogenic transmission of SARS-CoV-2 to pet cats highlights the importance of monitoring felids for exposure to circulating variants. We tested cats in the United Kingdom for SARS-CoV-2 antibodies; seroprevalence peaked during September 2021–February 2022. The variant-specific response in cats trailed circulating variants in humans, indicating multiple human-to-cat transmissions over a prolonged period.
SARS-CoV-2 Vaccine Effectiveness against Omicron Variant in Infection-Naive Population, Australia, 2022

SARS-CoV-2 transmission in Western Australia, Australia, was negligible until a wave of Omicron variant infections emerged in February 2022, when >90% of adults had been vaccinated. This unique pandemic experience enabled assessment of SARS-CoV-2 vaccine effectiveness (VE) without potential interference from background immunity from prior infection. We matched 188,950 persons who had a positive PCR test result during February–May 2022 to negative controls by age, week of test, and other possible confounders. Overall, 3-dose VE was 42.0% against infection and 81.7% against hospitalization or death. A primary series of 2 viral-vectored vaccines followed by an mRNA booster provided significantly longer protection against infection >60 days after vaccination than a 3-dose series of mRNA vaccine. In a population free from non–vaccine-derived background immunity, vaccines against the ancestral spike protein were ≈80% effective for preventing serious outcomes from infection with the SARS-CoV-2 Omicron variant.
FIELD COORDINATION ANALYSIS OF CONVECTIVE HEAT TRANSFER IN THERMAL ENTRANCE REGION IN RECTANGULAR DUCTS WITH ONE SIDE HEATED

A numerical study is conducted for laminar flow heat transfer in rectangular ducts in the thermal entrance region with one side heated and three sides adiabatic. The local Nusselt numbers are obtained and compared for different aspect ratios. Field coordination equations are derived for the one side heated thermal boundary condition. Effects of thermal boundary condition and aspect ratio on Nusselt number are discussed and analyzed from the view of field coordination.
Framingham risk score conventional risk factors are potent to predict all-cause mortality using machine learning algorithms: a population-based prospective cohort study over 40 years in China

Predicting all-cause mortality using available or conveniently modifiable risk factors is potentially crucial in reducing deaths precisely and efficiently. Framingham risk score (FRS) is widely used in predicting cardiovascular diseases, and its conventional risk factors are closely pertinent to deaths. Machine learning is increasingly considered to improve the predicting performances by developing predictive models. We aimed to develop the all-cause mortality predictive models using five machine learning (ML) algorithms (decision trees, random forest, support vector machine (SVM), XgBoost, and logistic regression) and determine whether FRS conventional risk factors are sufficient for predicting all-cause mortality in individuals over 40 years. Our data were obtained from a 10-year population-based prospective cohort study in China, including 9143 individuals over 40 years in 2011, and 6879 individuals followed-up in 2021. The all-cause mortality prediction models were developed using five ML algorithms by introducing all features available (182 items) or FRS conventional risk factors. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the predictive models. The AUC and 95% confidence interval of the all-cause mortality prediction models developed by FRS conventional risk factors using five ML algorithms were 0.75 (0.726–0.772), 0.78 (0.755–0.799), 0.75 (0.731–0.777), 0.77 (0.747–0.792), and 0.78 (0.754–0.798), respectively, which is close to the AUC values of models established by all features (0.79 (0.769–0.812), 0.83 (0.807–0.848), 0.78 (0.753–0.798), 0.82 (0.796–0.838), and 0.85 (0.826–0.866), respectively). Therefore, we tentatively put forward that FRS conventional risk factors were potent to predict all-cause mortality using machine learning algorithms in the population over 40 years.
Validity of chronometric TMS for probing the time-course of word production: a modified replication

Abstract In the present study, we used chronometric TMS to probe the time-course of 3 brain regions during a picture naming task. The left inferior frontal gyrus, left posterior middle temporal gyrus, and left posterior superior temporal gyrus were all separately stimulated in 1 of 5 time-windows (225, 300, 375, 450, and 525 ms) from picture onset. We found posterior temporal areas to be causally involved in picture naming in earlier time-windows, whereas all 3 regions appear to be involved in the later time-windows. However, chronometric TMS produces nonspecific effects that may impact behavior, and furthermore, the time-course of any given process is a product of both the involved processing stages along with individual variation in the duration of each stage. We therefore extend previous work in the field by accounting for both individual variations in naming latencies and directly testing for nonspecific effects of TMS. Our findings reveal that both factors influence behavioral outcomes at the group level, underlining the importance of accounting for individual variations in naming latencies, especially for late processing stages closer to articulation, and recognizing the presence of nonspecific effects of TMS. The paper advances key considerations and avenues for future work using chronometric TMS to study overt production.
Effect of fruit on glucose control in diabetes mellitus: a meta-analysis of nineteen randomized controlled trials

Objective Diabetes mellitus is a worldwide health problem, and it remains unclarified whether fruit is beneficial in glycemic control. This study aimed to analyze evidence from randomized controlled trials evaluating the effect of fruit consumption on glucose control. Methods We searched the PubMed, EMBASE, Ovid, Web of Science, and Cochrane Central Register of Controlled Trials databases from the respective database inception dates to December 30, 2022, to identify randomized controlled trials that evaluated the effects of fruit consumption on glucose control. Two researchers independently screened the studies in accordance with the inclusion and exclusion criteria, and performed the literature quality evaluation and data extraction. RevMan 5.4 software was used to perform the data analysis. Results Nineteen randomized controlled trials with 888 participants were included. Fruit consumption significantly decreased the fasting blood glucose concentration (MD -8.38, 95% CI -12.34 to -4.43), but it showed no significant difference in the glycosylated hemoglobin (MD -0.17, 95% CI -0.51 to 0.17). Subgroup analyses further suggested that the consumption of both fresh and dried fruit decreased the fasting blood glucose concentration. Conclusions Increasing the fruit intake reduced fasting blood glucose concentration. Therefore, we recommend that patients with diabetes eat more fruits while ensuring that their total energy intake remains unchanged.
The development of a 6 degree of freedom quasi-zero stiffness Maglev vibration isolator with adaptive-passive load support

Vibration isolation systems are widely used in many engineering applications. In some of the advanced fields, stringent isolation requirements are often necessary for achieving satisfactory results, such as in semiconductor manufacturing and gravitational wave monitoring. This paper presents a novel design of a 6-DOF maglev isolation system. This design incorporates the quasizero stiffness levitation principle to achieve low resonance frequency and high isolation performance without sacrificing the load capacity of the isolation system. An onboard adaptive-passive load support system maintains the vertical levitation force to be identical to the actual payload weight so that zero constant power consumption is required to counteract the isolator gravity force. In this paper, design principles of each system component are described, followed by the implementation of each design concept. Experimental results of isolator acceleration transmissibility are also presented.
Impact of landscape configuration and composition on pollinator communities across different European biogeographic regions

Introduction Heterogeneity in composition and spatial configuration of landscape elements support diversity and abundance of flower-visiting insects, but this is likely dependent on taxonomic group, spatial scale, weather and climatic conditions, and is particularly impacted by agricultural intensification. Here, we analyzed the impacts of both aspects of landscape heterogeneity and the role of climatic and weather conditions on pollinating insect communities in two economically important mass-flowering crops across Europe. Methods Using a standardized approach, we collected data on the abundance of five insect groups (honey bees, bumble bees, other bees, hover flies and butterflies) in eight oilseed rape and eight apple orchard sites (in crops and adjacent crop margins), across eight European countries (128 sites in total) encompassing four biogeographic regions, and quantified habitat heterogeneity by calculating relevant landscape metrics for composition (proportion and diversity of land-use types) and configuration (the aggregation and isolation of land-use patches). Results We found that flower-visiting insects responded to landscape and climate parameters in taxon- and crop-specific ways. For example, landscape diversity was positively correlated with honey bee and solitary bee abundance in oilseed rape fields, and hover fly abundance in apple orchards. In apple sites, the total abundance of all pollinators, and particularly bumble bees and solitary bees, decreased with an increasing proportion of orchards in the surrounding landscape. In oilseed rape sites, less-intensively managed habitats (i.e., woodland, grassland, meadows, and hedgerows) positively influenced all pollinators, particularly bumble bees and butterflies. Additionally, our data showed that daily and annual temperature, as well as annual precipitation and precipitation seasonality, affects the abundance of flower-visiting insects, although, again, these impacts appeared to be taxon- or crop-specific. Discussion Thus, in the context of global change, our findings emphasize the importance of understanding the role of taxon-specific responses to both changes in land use and climate, to ensure continued delivery of pollination services to pollinator-dependent crops.
Research on the network substitution effect of Mask R-CNN algorithm for fuzzy input images

Mask R-CNN is a relatively mature method for instance segmentation at this stage, aiming at the problems of segmentation boundary accuracy and poor robustness to blurry pictures in the Mask R-CNN algorithm, an improved Mask R-CNN instance segmentation method is proposed. Use the SegNeXt network structure to optimize the mask branch for further segmentation of candidate regions, and then use new anchor size and IOU standards so that the candidate box can cover all instance regions. Finally, a method is used to add partially transformed data from a transformation network for training. Compared with the original algorithm, the total mAP value is increased by 2.2%, and the accuracy and robustness of the segmentation boundary are improved.
Offloading strategy for UAV power inspection task based on deep reinforcement learning

Due to the limitation of computer capacity and energy of equipment, unmanned equipment cannot perform intensive computer tasks well during emergency failure inspection. In order to solve the above problems, this paper proposes a task waste strategy based on Deep Reinforcement Learning (DRL), which is mainly applicable to several UAVs and individual ES scenarios. First of all, an end edge cloud cooperative unloading architecture is built in the edge environment of UAV, and the problem of unloading tasks is classified as an optimization problem to achieve the minimum delay under the limit of the computing and communication resources of the Edge Server (ES). Secondly, the problem is constructed as Markov decision, and Deep Q Network (DQN) is used to solve the optimization problem, and experience playback mechanism and greedy algorithm are introduced into the learning process. Experiments show that the mitigation strategy has lower latency and higher reliability.
Dimension-Reduced Hyperbolic Moment Method for the Boltzmann Equation with BGK-Type Collision

We develop the dimension-reduced hyperbolic moment method for the Boltzmann equation, to improve solution efficiency using a numerical regularized moment method for problems with low-dimensional macroscopic variables and highdimensional microscopic variables. In the present work, we deduce the globally hyperbolic moment equations for the dimension-reduced Boltzmann equation based on the Hermite expansion and a globally hyperbolic regularization. The numbers of Maxwell boundary condition required for well-posedness are studied. The numerical scheme is then developed and an improved projection algorithm between two different Hermite expansion spaces is developed. By solving several benchmark problems, we validate the method developed and demonstrate the significant efficiency improvement by dimension-reduction. AMS subject classifications: 35L25, 65M08, 76P05, 78M05
The role of cytology in patients undergoing pressurized intraperitoneal aerosol chemotherapy (PIPAC) treatment for peritoneal carcinomatosis

Abstract Objectives Cytology of ascites or peritoneal washing is a routine part of staging of peritoneal metastases (PM). We aim to determine value of cytology in patients undergoing pressurized intraperitoneal aerosol chemotherapy (PIPAC). Methods Single-center retrospective cohort study included consecutive patients having PIPAC for PM of different primary between January 2015 and January 2020. Results A total of 75 patients (median 63 years (IQR 51–70), 67 % female) underwent a total of 144 PIPAC. At PIPAC 1 59 % patients had positive and 41 % patients had negative cytology. Patients with negative and positive cytology only differed in terms of symptoms of ascites (16% vs. 39 % respectively, p=0.04), median ascites volume (100 vs. 0 mL, p=0.01) and median PCI (9 vs. 19, p<0.01). Among 20 patients who completed 3 PIPACs (per protocol), cytology changed in one from positive to negative, and in two from negative to positive. Median overall survival was 30.9 months in the per protocol group and 12.9 months in patients having <3 PIPACs (=0.519). Conclusions Positive cytology under PIPAC treatment is more frequently encountered in patients with higher PCI and symptomatic ascites. Cytoversion was rarely observed and cytology status had no impact on treatment decisions in this cohort.
Dynamic path planning for ships in pirate attack areas

In this thesis, the path planning for the pirate attack incidents encountered during the navigation of the ship is firstly carried out. On this basis, the path planning of other dynamic obstacles in the pirate attack area is further considered. On this basis, the path planning of other dynamic obstacles in the pirate attack area is further considered. The grid method is used to model the research sea area, and the dual-objective model is constructed to ensure the minimum fuel cost and risk cost at the same time. The grid method is used to model the research sea area, and the dual-objective particle swarm algorithm to solve the problem. calculation results based on the optimal solution of pareto are better than the results obtained by the weight method, and the results are simulated on a It is concluded that the calculation results based on the optimal solution of pareto are better than the results obtained by the weight method, and the results are simulated on a large-scale navigation simulator, which proves the validity and feasibility of the model. The results are simulated on a large-scale navigation simulator, which proves the validity and feasibility of the model.
Towards numerical control of machine tools from the edge cloud

Abstract A concept has been developed which enables the virtualization and consolidation of NC controllers for machine tools. By decoupling control hardware and software, dynamic scaling of computing power depending on the complexity of the control functions becomes possible. The use of monolithic and over-dimensioned control systems, which are most often not fully exploited but no longer sufficient when new requirements arise, is avoided. Additionally, economic advantages might be exploited by consolidating multiple controllers in an edge cloud. Initial experiments have shown that purely software-based solutions on standard IT hardware are suitable for reliably achieving the required cycle times.
Soil community catabolic profiles for a semiarid reclaimed surface coalmine

ABSTRACT Recovery of soil health offers insights into the mechanisms underpinning the stability of remediated ecosystems. Indirect assessment of enzymatic activity potential using substrate induced respiration (SIR), is commonly used to evaluate changes in soil microbial activity profiles, with their links to environmental and management factors. In this study, community level physiological profiling (CLPP) was employed to assess the impact of time on surface coal mine soil remediation. When compared with an adjoining control site, analysis of CLPP parameters offer useful insights and prospective tools for assessing soil health, following mining and remediation activities.
Prediction of car license auction prices using an LSTM neural network for Guangzhou, Shenzhen, Hangzhou, and Tianjin

Car license auction price prediction has been identified as a novel practical problem in the economics field for several large Chinese cities. However, making predictions based on the corresponding time-series data is generally regarded as challenging due to the noise and volatility of car license auctions. The prediction capacity of the time-series model is likely to decay over time. Long short-term memory (LSTM) is regarded as a powerful approach for the price prediction of time series. Here, we build LSTM models for predicting the average price of car licenses auctioned in Guangzhou, Shenzhen, Hangzhou, and Tianjin using LSTM neural networks. Our LSTM neural network based on a time series is constructed considering the time characteristics, cities, license quotas, lagged lowest price, lagged average price, price announcements of license auctions, and short-term price trends. We propose a dynamic leave-one-out cross-validation method to address the difficulty in time-series prediction. The optimal models achieve suitably accurate performance; the average prediction errors of car license auctions are found to 861.71 CNY, 1648.57 CNY, 689.29 CNY, and 689.29 CNY for Guangzhou, Shenzhen, Hangzhou, and Tianjin, respectively.
Pocket: ML Serving from the Edge

One of the major challenges in serving ML applications is the resource pressure introduced by the underlying ML frameworks. This becomes a bigger problem at resource-constrained, multi-tenant edge server locations, where it is necessary to scale to a larger number of clients with a fixed resource envelope. Naive approaches which simply minimize the resource budget allocation of each application result in performance degradation that voids the benefits expected from operating at the edge. This paper presents Pocket - a new approach for serving ML applications in settings like the edge, based on a shared ML runtime backend as a service and lightweight ML application pocket containers. Key to realizing Pocket is use of lightweight IPC, support for cross-client isolation, and a novel resource amplification method which inlines resource reallocation with IPC. The latter ensures just-in-time assignment of the limited edge resources where they're most needed, thereby reducing contention effects and boosting overall performance and efficiency. Experimental evaluations demonstrate that Pocket can scale to 1.3--20× more clients with the same amount of resources while reducing response time by 20--80% compared to monolithic designs.
The Use of Mobile Phones by Women Livestock Keepers in Zimbabwe

This paper reports research conducted in Zimbabwe during 2017 and 2018 that investigated how women livestock keepers endeavoured to cope with a rapidly changing socio-political environment and new vulnerabilities that followed relocation due to the Zimbabwean Government ‘land reform and resettlement programme’ which resulted in the resettlement of farmers to new locations countrywide and the emergence and growth of new local economic activity linked to new cadres of smallholder farmers in resettlement areas. In particular, the research sought to understand how women livestock keepers were assimilating new and emerging digital technologies and mobile phones in order to: a) mitigate vulnerabilities and strengthen their position in livestock keeping; b) expand their social networks in order to interact more effectively with livestock markets; and c) diversify their livelihood strategies and lessen the risks associated with vulnerability. The research highlights the developmental benefits and constraints of empowering women livestock farmers through the use of mobile phone networks and draws a series of conclusions that can inform intervention strategies and policy making concerning livestock farming and use of mobile phones in Zimbabwe.
Near field to equivalent currents transformation with radome applications

Knowledge about the equivalent currents distribution on a radome can be used to improve radome design, detect manufacturing errors, and to verify numerical simulations. In this paper, the transformation from near-field data to the equivalent currents distribution is analyzed. The transformation is based on a singular value decomposition of the surface integral equation that relates the equivalent currents to the near-field data. The mathematical model can easily be used for arbitrary geometric structures. The symmetries of a specific problem are utilized to reduce the computational complexity. Both synthetic data and measured data are used to verify the algorithm