A review of more than 30 papers on the environmental applications of organic mass spectrometry in China in studies of environmental carcinogens, such as nitrosamines, polycyclic aromatic hydrocarbons (PAHs), and nitro-PAH, and trace organics in water, polychlorinated biphenyls, and reaction products and mechanism is presented.
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Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
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December 2024
Department of Agronomy, Faculty of Agriculture and Environment, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan.
Climate change has caused many challenges to soil ecosystems, including soil salinity. Consequently, many strategies are advised to mitigate this issue. In this context, biochar is acknowledged as a useful addition that can alleviate the detrimental impacts of salt stress on plants.
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December 2024
Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization (NARO), Tsukuba, Ibaraki, Japan.
Legume content (LC) in grass-legume mixtures is important for assessing forage quality and optimizing fertilizer application in meadow fields. This study focuses on differences in LC measurements obtained from unmanned aerial vehicle (UAV) images and ground surveys based on dry matter assessments in seven meadow fields in Hokkaido, Japan. We propose a UAV-based LC (LC) estimation and mapping method using a land cover map from a simple linear iterative clustering (SLIC) algorithm and a random forest (RF) classifier.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
Sustainability Solutions Research Lab, Faculty of Engineering, University of Pannonia, Egyetem Str. 10, Veszprém, 8200, Hungary.
Ensuring everyone enjoys healthy lifestyles and well-being at all ages, Progress has been made in increasing access to clean water and sanitation facilities and reducing the spread of epidemics and diseases. The synthesis of nano-particles (NPs) by using microalgae is a new nanobiotechnology due to the use of the biomolecular (corona) of microalgae as a capping and reducing agent for NP creation. This investigation explores the capacity of a distinct indigenous microalgal strain to synthesize silver nano-particles (AgNPs), as well as its effectiveness against multi-drug resistant (MDR) bacteria and its ability to degrade Azo dye (Methyl Red) in wastewater.
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