Estimating four-decadal variations of seagrass distribution using satellite data and deep learning methods in a marine lagoon.

Seagrasses are marine flowering plants that inhabit shallow coastal and estuarine waters and serve vital ecological functions in marine ecosystems. However, seagrass ecosystems face the looming threat of degradation, necessitating effective monitoring. Remote-sensing technology offers significant advantages in terms of spatial coverage and temporal accessibility.

Chronic Sacral Nerve Stimulation Inhibits Visceral Hypersensitivity in Diarrhea-Predominant Irritable Bowel Syndrome Rats Model.

Objective: Sacral nerve stimulation (SNS) is emerging as a novel treatment for irritable bowel syndrome (IBS). However, its effects are limited, and the underlying mechanisms remain largely unknown.

Materials And Methods: In this study, rats were divided into three groups (n = 12 rats per group): 1) the SNS group; 2) the sham SNS group (the sham group for short); and 3) the control group.

Remote sensing detection of seagrass distribution in a marine lagoon (Swan Lake), China.

Seagrass, a submerged flowering plant, is widely distributed in coastal shallow waters and plays a significant role in maintaining marine biodiversity and carbon cycles. However, the seagrass ecosystem is currently facing degradation, necessitating effective monitoring. Satellite remote sensing observations offer distinct advantages in spatial coverage and temporal frequency.

Multiple infections of zoonotic pathogens in wild Brandt's voles (Lasiopodomys brandtii).

Background: The frequent interactions of rodents with humans make them a common source of zoonotic infections. Brandt's vole is the dominant rodent species of the typical steppe in Inner Mongolia, and it is also an important pest in grassland.

Objectives: To obtain an initial unbiased measure of the microbial diversity and abundance in the blood and intestinal tracts and to detect the pathogens carried by wild Brandt's voles in Hulun Buir, Inner Mongolia.

Monkeypox outbreaks in the context of the COVID-19 pandemic: Network and clustering analyses of global risks and modified SEIR prediction of epidemic trends.

Background: Ninety-eight percent of documented cases of the zoonotic disease human monkeypox (MPX) were reported after 2001, with especially dramatic global spread in 2022. This longitudinal study aimed to assess spatiotemporal risk factors of MPX infection and predict global epidemiological trends.

Method: Twenty-one potential risk factors were evaluated by correlation-based network analysis and multivariate regression.

Size-Controllable Eu-MOFs through Machine Learning Technology: Application for High Sensitive Ions and Small-Molecular Identification.

Metal-organic frameworks (MOFs) with the aggregation-induced emission (AIE) activities exhibit potential applications in the fields of energy and biomedical technology. However, the controllable synthesis of MOFs in the varied particle sizes not only affects their AIE activities, but also restricts their application scenarios. In this work, the varied particle sizes of Eu-MOFs are synthesized by adjusting the synthesis process parameters, and their variation rules combining the single factor analysis method with machine learning technology are studied.

Analysis of laboratory and serological test results in patients with acute brucellosis during follow-up.

Background: The laboratory test results and serum-specific antibodies of patients with acute brucellosis initial infection were followed up and analyzed.

Methods: 70 patients in Hohhot City, Inner Mongolia Autonomous Region, with acute brucellosis were followed up for 360 days. Serum samples were collected at 0, 15, 30, 60, 90, 180, and 360 days after diagnosis and analyzed by Rose Bengal plate test (RBPT), colloidal gold test paper (GICA), and test tube agglutination test (SAT).

Synergistic CO reduction effects in Chinese urban agglomerations: Perspectives from social network analysis.

China has released its ambitious target for carbon neutrality by 2060. With decades of top-down energy conservation and pollutant mitigation policies, the techno-mitigation space has gradually shrunk, while more mitigation space is required for a systematic approach. To help to uncover CO mitigation effects, location and better pathways from a systematic perspective, this paper combines disparity analysis and social network analysis to investigate the synergistic emissions reduction effect of urban agglomerations in three representative Chinese urban agglomerations, namely the Yangtze River Delta urban agglomeration (YRD), Chengdu-Chongqing urban agglomeration (CY) and Guangdong-Hong Kong-Macao urban agglomeration (GHM).

Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea.

Euphotic zone depth (Z) plays an important role in studies of marine biogeochemical processes and ecosystems. Remote sensing techniques are ideal tools to investigate Z distributions because of their advanced observation ability with broad spatial coverage and frequent observation intervals. This study aims to develop a new approach that derives Z directly from remote sensing reflectance (R(λ)) values rather than by using other intermediate variables and then reveals the dynamic characteristics of Z in the Bohai Sea (BS) and Yellow Sea (YS).

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex.