Browse Articles

A cross sectional study of the diabetes mediated GGT to HDL ratio and cognitive function in older adults

Host range expansion of Helicoverpa armigera to apple orchards in the Himalayan region

Correction for Chihoub et al., The evolution of robustness and fragility during long-term bacterial adaptation

Endoplasmic reticulum stress involved in age-related nuclear cataract induced by sodium selenite

Impact of craniofacial skeletal characteristics on temporomandibular joint’s articular disc position in temporomandibular disorders

S100A8 regulated by estrogen improves injured endometrial epithelium reconstruction by promoting tight junction formation and stromal cell transformation

Abstract Estrogen is used for endometrial repair; however, it has limited effectiveness. Cytokine S100A8 expression is affected by estrogen and is involved in regulating the damage repair. We aimed to confirm the effects of S100A8 and explore its mechanisms during the reconstruction of the injured endometrium. We investigated the effects of estrogen on S100A8 expression in healthy endometrium. A rat model of endometrial injury and cultured primary endometrial cells were used to determine the pleiotropic effects of S100A8 on endometrial epithelial repair. Estrogen regulated the recruitment of S100A8-positive immune cells (S100A8-PICs) and the release of S100A8 in the healthy endometrium, but estrogen plays a limited role in regulating seriously injured endometrium via self-S100A8. S100A8 administration to the uterine cavity significantly improved the morphology of injured epithelium; influenced the reverse migration of S100A8-PICs; and promoted epithelial localization of proliferating cells, cell junction formation, and transformation of stromal cells to epithelial cells. S100A8 in the uterine cavity has pleiotropic effects that improve endometrial epithelial reconstruction and can compensate for the deficiency in estrogen repair regulation.

EEG based real time classification of consecutive two eye blinks for brain computer interface applications

Numerical simulation of ventilated supercavitating flow structure

Predicting autism from written narratives using deep neural networks

The missing cue problem in hetero associative memory retrieval

Abrupt shifts in the concentration, composition, and reactivity of dissolved organic carbon from terrestrial to aquatic compartments across boreal watersheds

Influence of inner meshing profile on noise of hybrid electric vehicles coupler chain based on vibration analysis

Abstract Chain noise is an important factor affecting the ride comfort of hybrid electric vehicles (HEVs) with chain coupler. The inner meshing profile can effectively reduce the polygonal action, which has already been proved, but its influence on the noise is controversial. In this paper, the basic vibration locus, velocities, and acceleration for HEVs coupler chain are analyzed. Based on a specific example, under the action of the inner meshing profile, the indicators that represent the low, medium and high frequency vibration are proved to be reduced. Based on meshing relations, it is proved that the error of the inner meshing profile will cause the deviation of the chain pitch line and the meshing disorder, which may weaken the influence of inner meshing profile on reducing noise. Through conducting the dynamics simulation and the noise and wear experiment, the results show that the influence of the inner meshing profile on the noise has dual effect, and it can only reduce the noise after running-in. Moreover, under the action of the inner meshing profile, the noise level will be decreased with the increase of running time. This paper not only resolves the controversy but also provides an effective method for chain noise.

Identification of key genes associated with cellular aging and mitochondria in acute myocardial infarction

Retrospective analysis of clinical and epidemiological characteristics of Chinese cobra bites in a South China emergency department

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures

Broadband circularly polarized dielectric rod antenna excited by a cavity backed spiral

Development and evaluation of an automated classification and counting system for rice planthoppers captured on survey boards

Abstract Rice planthoppers are the most economically important insect pests of rice in Asia. Traditional surveys to examine their abundance and composition in paddy fields involve human visual inspection, which requires considerable time and effort by expert entomologists. We previously developed a deep learning-based object detection system which can detect rice planthopper individuals from scanned images of survey boards, categorize, and count planthopper individuals by 18 categories, based on species, developmental stages, adult sexes, and adult wing-forms, with a mean average precision (mAP) of 79%. In this study, we modified the system by reconsidering the categories of planthopper individuals to be counted and by additional supervised training. The modified system can count rice planthopper individuals captured on survey boards across 17 categories with a mAP of 91%. We also showed that by using the system developed here, classification and counting of rice planthopper individuals can be completed in approximately six minutes per survey board, which can take more than an hour for human experts. Thus, this high-performance system can greatly save time and reduce labor costs for monitoring the occurrence, reproduction, and population growth of the rice planthoppers in paddy fields, which could increase the efficiency of their management.

Cross-sectional associations between meal timing patterns and diet quality indices in Iranian women

Macro and micro damage characteristics of Red-bed sandstone in Urumqi under freeze–thaw cycles

Anterior cruciate ligament tear detection based on Res2Net modified by improved Lévy flight distribution