WO Nanoplates Decorated with Au and SnO Nanoparticles for Real-Time Detection of Foodborne Pathogens.

Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT.

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops.

Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties.

SGR-YOLO: a method for detecting seed germination rate in wild rice.

Seed germination rate is one of the important indicators in measuring seed quality and seed germination ability, and it is also an important basis for evaluating the growth potential and planting effect of seeds. In order to detect seed germination rates more efficiently and achieve automated detection, this study focuses on wild rice as the research subject. A novel method for detecting wild rice germination rates is introduced, leveraging the SGR-YOLO model through deep learning techniques.

Spatiotemporal dynamics of wetlands and their future multi-scenario simulation in the Yellow River Delta, China.

Wetlands, known as the "kidney of the earth", are an important component of global ecosystems. However, they have been changed under multiple stresses in recent decades, which is especially true in the Yellow River Delta. This study examined the spatiotemporal change characteristics of wetlands in the Yellow River Delta from 1980 to 2020 and predicted detailed wetland changes from 2020 to 2030 with the patch-generating land use simulation (PLUS) model under four scenarios, namely, the natural development scenario (NDS), the farmland protection scenario (FPS), the wetland protection scenario (WPS) and the harmonious development scenario (HDS).

Research on Six-Axis Sensor-Based Step-Counting Algorithm for Grazing Sheep.

Step counting is an effective method to assess the activity level of grazing sheep. However, existing step-counting algorithms have limited adaptability to sheep walking patterns and fail to eliminate false step counts caused by abnormal behaviors. Therefore, this study proposed a step-counting algorithm based on behavior classification designed explicitly for grazing sheep.

Grazing Sheep Behaviour Recognition Based on Improved YOLOV5.

Fundamental sheep behaviours, for instance, walking, standing, and lying, can be closely associated with their physiological health. However, monitoring sheep in grazing land is complex as limited range, varied weather, and diverse outdoor lighting conditions, with the need to accurately recognise sheep behaviour in free range situations, are critical problems that must be addressed. This study proposes an enhanced sheep behaviour recognition algorithm based on the You Only Look Once Version 5 (YOLOV5) model.

Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters.

This paper presents an autonomous unmanned-aerial-vehicle (UAV) tracking system based on an improved long and short-term memory (LSTM) Kalman filter (KF) model. The system can estimate the three-dimensional (3D) attitude and precisely track the target object without manual intervention. Specifically, the YOLOX algorithm is employed to track and recognize the target object, which is then combined with the improved KF model for precise tracking and recognition.

The Income Elasticities of Food, Calories, and Nutrients in China: A Meta-Analysis.

Estimating food- and nutrient-income elasticities is important for making food and nutrition policies to combat malnutrition. There are many studies that have estimated the relationship between income growth and food/nutrient demand in China, but the results are highly heterogeneous. We conducted a meta-analysis in China to systematically review the elasticity of food, calories, and other nutrients to income.

Wearable Crop Sensor Based on Nano-Graphene Oxide for Noninvasive Real-Time Monitoring of Plant Water.

Real-time noninvasive monitoring of crop water information is an important basis for water-saving irrigation and precise management. Nano-electronic technology has the potential to enable smart plant sensors to communicate with electronic devices and promote the automatic and accurate distribution of water, fertilizer, and medicine to improve crop productivity. In this work, we present a new flexible graphene oxide (GO)-based noninvasive crop water sensor with high sensitivity, fast responsibility and good bio-interface compatibility.

Association of dietary diversity and cognition in preschoolers in rural China.

Objectives: We sought to investigate the cognition of preschoolers in rural China and examine the relationship between dietary diversity and cognition.

Methods: We performed a cross-sectional survey analysis. In 1334 preschoolers ages 3 to 5, from 26 preschools in two nationally designated poverty counties in Hunan Province in China, we calculated the dietary diversity score (DDS) using a 24-h recall method.

Socioeconomic and Geographic Pattern of Food Consumption and Dietary Diversity among Children Aged 6-23 Months Old in Ghana.

Dietary inadequacy is a major challenge among young children in Ghana. Nutritional policies are required for optimum child nutrition and development. This study explored food consumption and dietary diversity by socioeconomic status and geographical location among children aged 6-23 months in Ghana.

Dietary diversity and mental health in preschoolers in rural China.

Objective: To investigate the prevalence of mental health problems among preschoolers in rural China and examine the relationship between dietary diversity and mental health.

Design: A cross-sectional survey analysis was performed. Child mental health was assessed with the Strengths and Difficulties Questionnaire (SDQ).

Social-Psychological Factors in Food Consumption of Rural Residents: The Role of Perceived Need and Habit within the Theory of Planned Behavior.

To address the problem of malnutrition in poor rural areas of China, this study aims to examine the effects of social-psychological factors in food consumption of rural residents in poor counties of Southwest China. In addition, it investigates the role of perceived need and habit within the theory of planned behavior (TPB) in predicting food consumption. A survey with random sampling was conducted on rural residents ( = 424), and the theoretical frameworks of both the standard and extended TPB were applied for comparison purposes.

Strip rotary tillage with a two-year subsoiling interval enhances root growth and yield in wheat.

Excessive tillage and soil compaction threaten the sustainable farmlands in the Huang-Huai-Hai Plains of China. Our study explores tillage practices to improve soil and root ecology and promote productivity in the winter wheat fields. We tested the impact of plowing, rotary, strip rotary tillage and strip rotary tillage with a two-year subsoiling interval (SRS) on wheat yield and root quality.

Dietary Diversity among Preschoolers: A Cross-Sectional Study in Poor, Rural, and Ethnic Minority Areas of Central South China.

The aim of this study was to document the dietary diversity status of preschool children in poor, rural, and ethnic minority areas of Central South China and examine its associated factors both at home and in preschools. A cross-sectional study including 1328 preschool children aged three or five years from two nationally designated poverty counties in Hunan Province was conducted. A dietary diversity score (DDS) was constructed to measure the dietary patterns based on the 24 h recall method.

Covalent immobilization of Kluyveromyces fragilis β-galactosidase on magnetic nanosized epoxy support for synthesis of galacto-oligosaccharide.

The novel magnetic nanobeads with epoxy groups on the surface were prepared from glycidyl methacrylate (GMA), ethylene glycol dimethacrylate (EGDMA) and hydroxyethyl methacrylate (HEMA) via emulsifier-free emulsion polymerisation, and they were characterized by scanning electron microscopy and vibrating sample magnetometer. The magnetic poly(GMA-EDGMA-HEMA) nanobeads were used as support for covalent immobilization of Kluyveromyces fragilis β-galactosidase, the maximum amount enzyme attached onto the support was 145.6 mg/g with activity recovery of 72.