Impact of agricultural activities on pesticide residues in soil of edible bamboo shoot plantations

Edible bamboo shoot is one of the most important vegetables in Asian countries. Intensive agricultural management measures can cause many negative influences, such as soil acidification and excessive pesticide residues. In the present study, more than 300 soil samples were collected from edible bamboo shoot plantations in six areas throughout Zhejiang province, China, to investigate the soil pesticide pollution and its change after different agricultural activities. Thirteen organic chemicals were detected; nine less than that detected during a similar study executed in 2003–2004. All the detected residues were far below the Chinese national environmental standards for agricultural soils. The pesticide residues in bamboo plantations showed a decline over the past decade. Organic materials used for mulching and plantation’s background of being formerly a paddy field are two important factors increasing the pesticide residues. Conversely, lime application to acidified soil and mulching with uncontaminated new mountain soil could decrease the residues significantly. Our results indicated that the current agricultural activities are efficient in reducing pesticide residues in the soil of bamboo shoot plantations and should be further promoted

Zero-shot Preference Learning for Offline RL via Optimal Transport

Preference-based Reinforcement Learning (PbRL) has demonstrated remarkable efficacy in aligning rewards with human intentions. However, a significant challenge lies in the need of substantial human labels, which is costly and time-consuming. Additionally, the expensive preference data obtained from prior tasks is not typically reusable for subsequent task learning, leading to extensive labeling for each new task. In this paper, we propose a novel zero-shot preference-based RL algorithm that leverages labeled preference data from source tasks to infer labels for target tasks, eliminating the requirement for human queries. Our approach utilizes Gromov-Wasserstein distance to align trajectory distributions between source and target tasks. The solved optimal transport matrix serves as a correspondence between trajectories of two tasks, making it possible to identify corresponding trajectory pairs between tasks and transfer the preference labels. However, learning directly from inferred labels that contains a fraction of noisy labels will result in an inaccurate reward function, subsequently affecting policy performance. To this end, we introduce Robust Preference Transformer, which models the rewards as Gaussian distributions and incorporates reward uncertainty in addition to reward mean. The empirical results on robotic manipulation tasks of Meta-World and Robomimic show that our method has strong capabilities of transferring preferences between tasks and learns reward functions from noisy labels robustly. Furthermore, we reveal that our method attains near-oracle performance with a small proportion of scripted labels

Kinematic Design of a Seven-Bar Linkage with Optimized Centrodes for Pure-Rolling Cutting

A novel method for designing a seven-bar linkage based on the optimization of centrodes is presented in this paper. The proposed method is applied to the design of a pure-rolling cutting mechanism, wherein close interrelation between the contacting lines and centrodes of two pure-rolling bodies is formulated and the genetic optimization algorithm is adopted for the dimensional synthesis of the mechanism. The optimization is conducted to minimize the error between mechanism centrodes and the expected trajectories, subject to the design requirements of the opening distance, the maximum amount of overlap error, and peak value of shearing force. An optimal solution is obtained and the analysis results show that the horizontal slipping and standard deviation of the lowest moving points of the upper shear blade have been reduced by 78.0% and 80.1% and the peak value of shear stress decreases by 29%, which indicate better cutting performance and long service life

VEGF Is Involved in the Increase of Dermal Microvascular Permeability Induced by Tryptase

Tryptases are predominantly mast cell-specific serine proteases with pleiotropic biological activities and play a critical role in skin allergic reactions, which are manifested with rapid edema and increases of vascular permeability. The exact mechanisms of mast cell tryptase promoting vascular permeability, however, are unclear and, therefore, we investigated the effect and mechanism of tryptase or human mast cells (HMC-1) supernatant on the permeability of human dermal microvascular endothelial cells (HDMECs). Both tryptase and HMC-1 supernatant increased permeability of HDMECs significantly, which was resisted by tryptase inhibitor APC366 and partially reversed by anti-VEGF antibody and SU5614 (catalytic inhibitor of VEGFR). Furthermore, addition of tryptase to HDMECs caused a significant increase of mRNA and protein levels of VEGF and its receptors (Flt-1 and Flk-1) by Real-time RT-PCR and Western blot, respectively. These results strongly suggest an important role of VEGF on the permeability enhancement induced by tryptase, which may lead to novel means of controlling allergic reaction in skin

Chronic Disease Patients Involved in Shared-decision Making in General Outpatient Care in the Community：Current Status and Associated Factors

BackgroundThe general practice clinic in community health centers is facing increasingly complex challenges to meet the medical needs of patients with chronic diseases. To improve chronic disease patients' health outcome and healthcare satisfaction, it will be of great significance to use shared decision-making (SDM) in the diagnostic and therapeutic process in the community, since SDM is a model based on doctor-patient mutual respect and cooperation and shows great promise as a possible major medical decision-making model.ObjectiveTo understand the status and associated factors of chronic disease patients involved in SDM in general outpatient care in the community, aiming to provide evidence for promoting the implementation of SDM in primary care.MethodsWe used cluster sampling to select seven general practitioners (GPs) in the clinic of Shuangyushu Community Health Center, Beijing, and 149 chronic disease patients seen by them between October 2019 and January 2020 as the participants. Through non-participant observation at the clinic, we used the Chinese version of the Observer OPTION 5 (OPTION-5) as an assessment tool to evaluate the extent to which GPs facilitated patient participating in SDM during the consultation. We used a self-developed general demographic questionnaire to collect patients' demographics, status of illness and treatment, as well as GPs' demographics. We compared the OPTION-5 score of the patients by demographic factors, and used stepwise multiple linear regression to explore the factors affecting patients' participation in SDM.ResultsThe mean visit length, and OPTION-5 score for the 149 patients were (4.1±2.7) minutes, and〔6.00 (3.00) 〕, respectively. The OPTION-5 score varied significantly across patients by age group and visit length (P<0.05) . Multiple linear regression analysis showed that patient visit length, prevalence of interruption of counseling due to other people, and prevalence of family member accompaniment to medical visits were associated with patients' participation in SDM (P<0.05) .ConclusionThe participation of these patients in SDM was relatively low. Prolonging GP-patient communication time, ensuring that the diagnosis and treatment process is not interrupted, and giving patients a private space during diagnosis and treatment process may be feasible interventions to improve the participation of chronic disease patients in SDM in primary care

Progressive Object Transfer Detection

Recent development of object detection mainly depends on deep learning with large-scale benchmarks. However, collecting such fully-annotated data is often difficult or expensive for real-world applications, which restricts the power of deep neural networks in practice. Alternatively, humans can detect new objects with little annotation burden, since humans often use the prior knowledge to identify new objects with few elaborately-annotated examples, and subsequently generalize this capacity by exploiting objects from wild images. Inspired by this procedure of learning to detect, we propose a novel Progressive Object Transfer Detection (POTD) framework. Specifically, we make three main contributions in this paper. First, POTD can leverage various object supervision of different domains effectively into a progressive detection procedure. Via such human-like learning, one can boost a target detection task with few annotations. Second, POTD consists of two delicate transfer stages, i.e., Low-Shot Transfer Detection (LSTD), and Weakly-Supervised Transfer Detection (WSTD). In LSTD, we distill the implicit object knowledge of source detector to enhance target detector with few annotations. It can effectively warm up WSTD later on. In WSTD, we design a recurrent object labelling mechanism for learning to annotate weakly-labeled images. More importantly, we exploit the reliable object supervision from LSTD, which can further enhance the robustness of target detector in the WSTD stage. Finally, we perform extensive experiments on a number of challenging detection benchmarks with different settings. The results demonstrate that, our POTD outperforms the recent state-of-the-art approaches.Comment: TIP 201

Quantum PT-Phase Diagram in a Non-Hermitian Photonic Structure

Photonic structures have an inherent advantage to realize PT-phase transition through modulating the refractive index or gain-loss. However, quantum PT properties of these photonic systems have not been comprehensively studied yet. Here, in a bi-photonic structure with loss and gain simultaneously existing, we analytically obtained the quantum PT-phase diagram under the steady state condition. To characterize the PT-symmetry or -broken phase, we define an Hermitian exchange operator expressing the exchange between quadrature variables of two modes. If inputting several-photon Fock states into a PT-broken bi-waveguide splitting system, most photons will concentrate in the dominant waveguide with some state distributions. Quantum PT-phase diagram paves the way to the quantum state engineering, quantum interferences, and logic operations in non-Hermitian photonic systems.Comment: 6 pages, 3 figure

Single-cell RNA sequencing reveals dynamic changes in A-to-I RNA editome during early human embryogenesis

BACKGROUND: A-to-I RNA-editing mediated by ADAR (adenosine deaminase acting on RNA) enzymes that converts adenosine to inosine in RNA sequence can generate mutations and alter gene regulation in metazoans. Previous studies have shown that A-to-I RNA-editing plays vital roles in mouse embryogenesis. However, the RNA-editing activities in early human embryonic development have not been investigated. RESULTS: Here, we characterized genome-wide A-to-I RNA-editing activities during human early embryogenesis by profiling 68 single cells from 29 human embryos spanning from oocyte to morula stages. We demonstrate dynamic changes in genome-wide RNA-editing during early human embryogenesis in a stage-specific fashion. In parallel with ADAR expression level changes, the genome-wide A-to-I RNA-editing levels in cells remained relatively stable until 4-cell stage, but dramatically decreased at 8-cell stage, continually decreased at morula stage. We detected 37 non-synonymously RNA-edited genes, of which 5 were frequently found in cells of multiple embryonic stages. Moreover, we found that A-to-I editings in miRNA-targeted regions of a substantial number of genes preferably occurred in one or two sequential stages. CONCLUSIONS: Our single-cell analysis reveals dynamic changes in genome-wide RNA-editing during early human embryogenesis in a stage-specific fashion, and provides important insights into early human embryogenesis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3115-2) contains supplementary material, which is available to authorized users

Base Detection Research of Drilling Robot System by Using Visual Inspection

This paper expounds the principle and method of calibration and base detection by using the visual measurement system for detection and correction of installation error between workpiece and the robot drilling system. This includes the use of Cognex Insight 5403 high precision industrial camera, a light source, and the KEYENCE coaxial IL-300 laser displacement sensor. The three-base holes method and two-base holes method are proposed to analyze the transfer relation between the basic coordinate system of the actual hole drilling robot and the basic coordinate system of the theoretical hole drilling robot. The corresponding vision coordinates calibration and the base detection experiments are examined and the data indicate that the result of base detection is close to the correct value

TPPP3 Promotes Cell Proliferation, Invasion and Tumor Metastasis via STAT3/ Twist1 Pathway in Non-Small-Cell Lung Carcinoma

Background/Aims: Non-small-cell lung carcinoma (NSCLC) is the leading cause of cancer death, with tumor metastasis being mainly responsible for lung cancer-associated mortality. Our previous studies have found that tubulin polymerization promoting protein family member 3 (TPPP3) acted as a potential oncogene in NSCLC. Little is known about the function of TPPP3 in tumor metastasis. Methods: RT-qPCR and IHC were used to investigate the expression of TPPP3 in NSCLC tissues. CCK8 assay and transwell assay were used to measure proliferation and migration of NSCLC cells in vitro and xenograft model was performed to assess the tumor growth and metastasis in vivo. Results: In the present study, upregulation of TPPP3 was found to correlate with an increased metastasis capability of NSCLC. Ectopic expression of TPPP3 significantly enhanced cell proliferation in vitro and promoted tumor growth in vivo. Furthermore, overexpression of TPPP3 remarkably promoted NSCLC cell migration and invasion along with the upregulation of Twist1 both in vitro and in vivo. Further investigations showed that activation of STAT3 was required for TPPP3-mediated upregulation of Twist1, cell migration and invasion. A strong positive correlation between TPPP3 and Twist1 expression was identified in NSCLC tissues. Patients with low TPPP3 or low Twist1 in NSCLC tissues had a better prognosis with longer overall survival (OS) and disease-free survival (DFS). Conclusion: Overall, this study demonstrates that TPPP3 promotes the metastasis of NSCLC through the STAT3/Twist1 pathway