Assessment of the influence of using green tea waste and fish waste as soil amendments for biosolarization on the growth of lettuce (Lactuca sativa L. var. ramosa Hort.)

IntroductionSafe and efficient treatment of organic waste is crucial to developing a sustainable food system around the world. Soil biosolarization (SBS) is a soil treatment technique that can use organic solid wastes to treat the soil in a way that is alternative to the use of chemical fumigants to improve soil fertility in agriculture.MethodsIn this study, two types of organic food wastes, green tea waste (GTW) and fish waste (FW), were evaluated for the feasibility of being applied as soil amendments within simulations of high-temperature cycle SBS. The evaluation was conducted by execution of three groups of measurements: gas and organic volatile emission profile, residual soil phytotoxicity and weed suppression, and cultivar growth (Lactuca sativa L. var. ramosa Hort.).Results and DiscussionGreen tea waste contributed to elevated levels of soil respiration and the evolution of signature volatile organic compounds during the simulated SBS. In the soil amended with green tea waste and then undergoing SBS the phyto compatibility was restored after residual phytotoxicity dissipation and a complete weed suppression was achieved. By using an application rate of 2.5% (w/w, mass fraction of green tea waste in total soil-waste mixture) green tea waste cultivar growth comparable to that of the non-treated soil (NTS) group was attained, with a more efficient nitrogen utilization and higher residual soil nitrogen content enabling the improvement of the continuous cropping system. FW at 1% (w/w, mass fraction of FW in total soil-waste mixture) promoted cultivar growth despite the significant reduction of the nitrogen (p value=0.02) and phosphorus (p value=0.03) contents in the cultivar leaves. A significant increase of the sodium content together with an increase of iron and chromium, which exceeded the permissible limit, were observed. These results provide new information about amendment selection for the SBS process

Scene Reconstruction for Simulated Grasp Search in Structured Clutter

Robotic grasping in a complex environment is one of the fundamental challenges for home-assistant robots. Complex environment grasping has been extensively studied in industrial bin-picking scenarios, where reliably grasping objects from unorganized heaps is challenging due to sensor noise, obstructions, and occlusions. However, bin picking is still relatively easier than grasping common household objects from a structured clutter in a home environment because the robot cannot knock over neighboring objects during the grasping motion. Recently, there have been several attempts to tackle the grasping-in-structured-clutter problem. In our experiments, we found these methods either hard to adapt to our simulated environment without extra tuning or generate too few stable grasps to successfully grasp the objects. The overviews and detailed analyses of these existing grasping approaches will appear in the first half of this thesis.In the second half of this thesis, we investigate the idea of using a physical simulator as an intermediate step to generate a grasp trajectory proposal. At a high level, we propose a two-step approach to solve the grasping-in-structured-clutter problem. First, we collect RGB-D observations to reconstruct the environment in a physical simulator via 9 degree-of-freedom (DoF) category-level object pose estimation, CAD model matching, and physical support refinement. Then, we perform antipodal grasp sampling, collision-free motion planning, and grasp execution in the simulator and directly transfer the robot arm’s motion trajectory to the original environment. To generate a 9-DoF category-level object pose estimate, we extend a state-of-the-art 6-DoF instance-level object pose estimation network. In our experiments, we found the 9-DoF pose estimation network can reach performance comparable to the state-of-the-art on a category-level object pose estimation dataset. Relying on only the top-down view of the environment, we reconstructed the environment using the proposed two-step approach and evaluated the grasp transfer success. The results show further room for improvements in the model matching process. Future directions and some ideas will be discussed towards the end of this thesis.We hope the work of scene reconstruction for simulated grasp search and trajectory transfer will help future research of robotics manipulation in complex environments

Influencing Factor Research of Kerr Effect

This paper presents a model of Kerr effect for the influencing factors research. The influencing factors proposed are Kerr cell voltage, charging duration time and electrode material. The experimental results show that refractive index of transformer oil will rise when Kerr cell voltage become larger; there is a period of 15 minutes called ‘polarization time’ after the beginning of the experiment and electrode material indeed has an obvious effect on the transformer oil

Clopidogrel versus ticagrelor in East Asian patients aged 75 years or older with acute coronary syndrome: observations from the GF-APT registry

The benefits of potent antithrombotic therapy usually come at the expense of a higher risk of bleeding. The efficacy and safety of ticagrelor in elderly East Asian populations remains debated due to the concerns about the imbalance of ischemic and bleeding risks. This study aimed to compare the impact of clopidogrel with ticagrelor on clinical outcomes in East Asian patients aged ≥75 years with acute coronary syndrome (ACS) using data from an institutional registry. We assessed the treatment effect of ticagrelor versus clopidogrel based on propensity scores and multivariate Cox proportional hazards models. A total of 2775 ACS patients were included, of which 235 (8.5%) were treated with ticagrelor. The primary efficacy outcome occurred in 11.9% of patients treated with ticagrelor versus 8.8% treated with clopidogrel. There was no significant association between treatment with ticagrelor and a lower risk of the primary efficacy outcome (p = .156). However, the incidences of all-cause death (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.02 to 2.79) and major bleeding (adjusted HR 2.20, 95% CI 1.06 to 4.56) were significantly higher in patients treated with ticagrelor than clopidogrel. In elderly patients with ACS from East Asia, the efficacy of clopidogrel was comparable to ticagrelor, while ticagrelor is associated with an increased risk of mortality and major bleeding

BrainSec: Automated Brain Tissue Segmentation Pipeline for Scalable Neuropathological Analysis.

As neurodegenerative disease pathological hallmarks have been reported in both grey matter (GM) and white matter (WM) with different density distributions, automating the segmentation process of GM/WM would be extremely advantageous for aiding in neuropathologic deep phenotyping. Standard segmentation methods typically involve manual annotations, where a trained researcher traces the delineation of GM/WM in ultra-high-resolution Whole Slide Images (WSIs). This method can be time-consuming and subjective, preventing a scalable analysis on pathology images. This paper proposes an automated segmentation pipeline (BrainSec) combining a Convolutional Neural Network (CNN) module for segmenting GM/WM regions and a post-processing module to remove artifacts/residues of tissues. The final output generates XML annotations that can be visualized via Aperio ImageScope. First, we investigate two baseline models for medical image segmentation: FCN, and U-Net. Then we propose a patch-based approach, BrainSec, to classify the GM/WM/background regions. We demonstrate BrainSec is robust and has reliable performance by testing it on over 180 WSIs that incorporate numerous unique cases as well as distinct neuroanatomic brain regions. We also apply gradient-weighted class activation mapping (Grad-CAM) to interpret the segmentation masks and provide relevant explanations and insights. In addition, we have integrated BrainSec with an existing Amyloid-β pathology classification model into a unified framework (without incurring significant computation complexity) to identify pathologies, visualize their distributions, and quantify each type of pathologies in segmented GM/WM regions, respectively

Equal contributors

Correction: Cisplatin-induced epigenetic activation of miR-34a sensitizes bladder cancer cells to chemotherap

Meta‐Analysis Global Group in Chronic Heart Failure score for the prediction of mortality in valvular heart disease

Abstract Aims Valvular heart disease (VHD) is one of the leading causes of heart failure. Clinically significant VHD can induce different patterns of cardiac remodelling, and risk stratification is challenging in patients with various degrees of cardiac dysfunction. The study aimed to investigate the prognostic implications of Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) score in patients with VHD. Methods and results This study used data from the China Valvular Heart Disease (China‐VHD) registry, which was a multicentre, prospective, observational cohort study for patients with significant (at least moderate) VHD. In total, 10 446 patients with moderate or greater VHD from the China‐VHD study were included in the present analysis. The primary outcome of interest was all‐cause mortality within 2 years. Among 10 446 patients with VHD, the mean age was 61.98 ± 13.47 years, and 5819 (55.7%) were male. During 2 years of follow‐up, 895 (8.6%) patients died. The MAGGIC score was monotonically and independently associated with mortality in both total cohort [adjusted hazard ratio: 1.095, 95% confidence interval (CI): 1.084–1.107, P < 0.001] and most types of VHD (aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid regurgitation, mixed aortic stenosis and aortic regurgitation, and multiple VHD). The score was also an independent prognostic factor in patients with or without symptoms or preserved left ventricular ejection fraction (LVEF) and exhibited both satisfactory discrimination and calibration properties in predicting mortality. The prognostic value of MAGGIC score was robust in most quartiles of N‐terminal pro‐brain natriuretic peptide level, with no significant interaction observed (Pinteraction = 0.498). Compared with the EuroSCORE II, the MAGGIC score achieved significantly better predictive performance in overall population [C index: 0.769 vs. 0.727; net reclassification improvement index (95% CI): 0.354 (0.313–0.396), P < 0.001; integrated discrimination improvement index (95% CI): 0.069 (0.052–0.085), P < 0.001] and in subgroups of patients divided by therapeutic strategy, LVEF, symptomatic status, stage of VHD, and aetiology of VHD. Conclusions The MAGGIC score is a reliable prognostic factor across the range of cardiac dysfunction in VHD and may assist in risk stratification and guide clinical decision‐making