Organic materials with high C/N ratio: more beneficial to soil improvement and soil health.

In order to figure out the effect of organic fertilizers with different carbon-nitrogen (C/N) ratios on the soil improvement and the healthy cultivation, the pot experiment method was used to study effects on the physical and chemical properties and the bacterial community structure of sandy loam soil using five treatments of chemical fertilizer application with the C/N ratios of 15 (CN15), 20 (CN20), 25 (CN25), 30 (CN30) and the control (CK) respectively. Results show that the organic materials with different C/N ratios significantly improve the soil porosity and water content, which all show a linear change rule with the C/N ratio. It can also significantly increase the soil total carbon, total nitrogen, soil C/N ratio, soil microbial biomass carbon, microbial biomass nitrogen and microbial biomass C/N ratio.

Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks.

This article considers predicting future statuses of multiple agents in an online fashion by exploiting dynamic interactions in the system. We propose a novel collaborative prediction unit (CoPU), which aggregates the predictions from multiple collaborative predictors according to a collaborative graph. Each collaborative predictor is trained to predict the agent status by integrating the impact of another agent.

Intensity-Modulated Polymer Optical Fiber-Based Refractive Index Sensor: A Review.

The simple and highly sensitive measurement of the refractive index (RI) of liquids is critical for designing the optical instruments and important in biochemical sensing applications. Intensity modulation-based polymer optical fiber (POF) RI sensors have a lot of advantages including low cost, easy fabrication and operation, good flexibility, and working in the visible wavelength. In this review, recent developments of the intensity modulation POF-based RI sensors are summarized.

Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction.

We propose a multiscale spatio-temporal graph neural network (MST-GNN) to predict the future 3D skeleton-based human poses in an action-category-agnostic manner. The core of MST-GNN is a multiscale spatio-temporal graph that explicitly models the relations in motions at various spatial and temporal scales. Different from many previous hierarchical structures, our multiscale spatio-temporal graph is built in a data-adaptive fashion, which captures nonphysical, yet motion-based relations.

Symbiotic Graph Neural Networks for 3D Skeleton-Based Human Action Recognition and Motion Prediction.

3D skeleton-based action recognition and motion prediction are two essential problems of human activity understanding. In many previous works: 1) they studied two tasks separately, neglecting internal correlations; and 2) they did not capture sufficient relations inside the body. To address these issues, we propose a symbiotic model to handle two tasks jointly; and we propose two scales of graphs to explicitly capture relations among body-joints and body-parts.

Simultaneous determination of 20 bioactive components in Chuanxiong Rhizoma from different production origins in Sichuan province by ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry combined with multivariate statistical analysis.

Chuanxiong Rhizoma is a commonly used in traditional Chinese medicine. Chuanxiong Rhizoma is widely distributed in Sichuan province, China, including the cities of Dujiangyan, Pengzhou, Meishan, Qionglai, and Shifang. However, reports on the comparisons of quality of Chuanxiong Rhizoma of different production origins are limited.

[Study on the Relationship between susceptibility of stomach neoplasm cancer and polymorphism of inducible nitric oxide synthase gene].

Objective: To study the relationship between polymorphism of inducible Nitric Oxide Synthase (iNOS) gene and the susceptibility of intestinal type stomach cancer and stomach cardia cancer in Chinese people.

Methods: A community-based case-control study was designed. Ninety-three intestinal type of stomach cancer and 50 stomach cardia cancer patients with endoscopy and pathology diagnosis were identified as cases.

[The distributive features of three kinds of metabolic genes polymorphisms in population of Han nationality in south area of China].

Objective: To find out the distributive features of some metabolic genes polymorphisms in Han population of south area of China.

Methods: Study population was obtained from the controls of a community based case-control study, which included 290 blood relatives (inner control) and 404 non-blood relatives (outer control).

Results: Frequencies of CYP1A1, GSTM1 and GSTT1 polymorphisms had no significant difference among confounding factors, such as sex, living areas, stomach cancer family history and history of tobacco smoking etc.