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Mining microbial and metabolic dark matter in extreme environments: a roadmap for harnessing the power of multi-omics data.
Adv Biotechnol (Singap)
August 2024
State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Stress Biology and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, PR China.
Extreme environments such as hyperarid, hypersaline, hyperthermal environments, and the deep sea harbor diverse microbial communities, which are specially adapted to extreme conditions and are known as extremophiles. These extremophilic organisms have developed unique survival strategies, making them ideal models for studying microbial diversity, evolution, and adaptation to adversity. They also play critical roles in biogeochemical cycles.
View Article and Find Full Text PDFsp. nov. and var. var. nov. (Zingiberaceae) from Northern Thailand.
Heliyon
January 2025
Institute of Applied Technology, Thu Dau Mot University, no. 06, Tran Van on Street, Phu Hoa, Thu Dau Mot, Binh Duong, Vietnam.
Thailand hosts a diverse array of plants in the Zingiberaceae family, with over 150 endemic species, highlighting its significance in global biodiversity. The genus stands out for its ornamental and medicinal value. During a research expedition in Northern Thailand, a previously unknown species was discovered in Sukhothai province, expanding the known distribution range.
View Article and Find Full Text PDFApplication of the modified RIAM method in assessing the environmental impact of municipal solid waste management scenarios (A case study).
Heliyon
January 2025
School of Engineering, Mining Engineering Department, Urmia University, Urmia, Iran.
The rapid impact assessment matrix (RIAM) is a widely utilized tool for evaluating environmental impacts in municipal solid waste management. However, the traditional RIAM (T-RIAM) method includes ambiguities in its scoring classification, which can hinder decision-making accuracy. This study introduces a modified RIAM approach, enhancing classification precision by refining impact categories, making it particularly valuable for projects constrained by time and resources.
View Article and Find Full Text PDFA comprehensive dataset of above-ground forest biomass from field observations, machine learning and topographically augmented allometric models over the Kashmir Himalaya.
Data Brief
February 2025
Department of Geoinformatics, University of Kashmir, Hazratbal Srinagar 190006, Jammu and Kashmir, India.
Accurate estimates of forest dynamics and above-ground forest biomass for the topographically challenging Himalaya are crucial for understanding carbon storage potential, assessing ecosystem services, and guiding conservation efforts in response to climate change. This dataset provides a manually delineated multi-temporal forest inventory and a comprehensive record of above-ground biomass (AGB) across the Kashmir Himalaya, generated from field observations, advanced remote sensing and machine learning. Data were collected and generated through remote sensing techniques and extensive in-situ measurements of 6220 trees (n=275 plots), including tree diameter at breast height, species composition, and tree density to map forest area and model AGB across varied terrain.
View Article and Find Full Text PDFThe Effects of Self-Monitoring Using a Smartwatch and Smartphone App on Stress Awareness, Self-Efficacy, and Well-Being-Related Outcomes in Police Officers: Longitudinal Mixed Design Study.
JMIR Mhealth Uhealth
January 2025
Department of Learning and Workforce Development, The Netherlands Organisation for Applied Scientific Research, Soesterberg, Netherlands.
Background: Wearable sensor technologies, often referred to as "wearables," have seen a rapid rise in consumer interest in recent years. Initially often seen as "activity trackers," wearables have gradually expanded to also estimate sleep, stress, and physiological recovery. In occupational settings, there is a growing interest in applying this technology to promote health and well-being, especially in professions with highly demanding working conditions such as first responders.
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