Managing land sustainably is a huge challenge, especially under harsh climatic conditions such as those found in drylands. The socio-economic situation can also pose challenges, as dryland regions are often characterized by remoteness, marginality, low-productive farming, weak institutions, and even conflict. With threats from climate change, disputes over water, competing claims on land, and migration increasing worldwide, the demands for sustainable land management (SLM) measures will only increase in the future. Within the EU-funded DESIRE project, researchers and stakeholders jointly identified existing SLM technologies and approaches in 17 dryland study sites located in the Mediterranean and around the world. In order to evaluate and share this valuable SLM experience, local researchers documented the SLM technologies and approaches in collaboration with land users, utilizing the internationally recognized WOCAT questionnaires. This article provides an analysis of 30 technologies and 8 approaches, enabling an initial evaluation of how SLM addresses prevalent dryland threats, such as water scarcity, soil degradation, vegetation degradation and low production, climate change, resource use conflicts, and migration. Among the impacts attributed to the documented technologies, those mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Favorable local-scale cost-benefit relationships were mainly found when considered over the long term. Nevertheless, SLM was found to improve people's livelihoods and prevent further outmigration. More field research is needed to reinforce expert assessments of SLM impacts and provide the necessary evidence-based rationale for investing in SLM.
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http://dx.doi.org/10.1007/s00267-013-0071-3 | DOI Listing |
JMIR Serious Games
January 2025
School of Computing, Engineering and Mathematical Sciences, Optus Chair Digital Health, La Trobe University, Melbourne, Australia.
Background: This review explores virtual reality (VR) and exercise simulator-based interventions for individuals with attention-deficit/hyperactivity disorder (ADHD). Past research indicates that both VR and simulator-based interventions enhance cognitive functions, such as executive function and memory, though their impacts on attention vary.
Objective: This study aimed to contribute to the ongoing scientific discourse on integrating technology-driven interventions into the management and evaluation of ADHD.
Phys Rev Lett
December 2024
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Chalmers University of Technology, Department of Physics, 412 96 Göteborg, Sweden.
The phonon inverse Faraday effect describes the emergence of a dc magnetization due to circularly polarized phonons. In this work we present a microscopic formalism for the phonon inverse Faraday effect. The formalism is based on time-dependent second order perturbation theory and electron phonon coupling.
View Article and Find Full Text PDFRheumatology (Oxford)
January 2025
Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Objectives: The 2022 European Society of Cardiology and European Respiratory Society (ESC/ERS) Guidelines for pulmonary arterial hypertension (PAH) recommend risk stratification to optimize management. However, the performance of generic PAH risk stratification tools in patients with systemic sclerosis (SSc)-associated PAH remains unclear. Our objective was to identify the most accurate approach for risk stratification at SSc-PAH diagnosis.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.
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