Results 171 to 180 of about 7,265 (241)

Technical wildness: Modernity, romanticism, and the technocratic turn in Scottish rewilding

People and Nature, EarlyView.
Abstract Technical wildness is a new and increasingly influential culture of nature. This paper marks its emergence in Scotland in the early 2020s. Focusing on Scotland's rapidly evolving land management sector, the paper traces how private rewilding companies position science‐led land management and natural capital markets as the most effective ...
Theo Stanley
wiley   +1 more source

Experimental and mechanistic analysis of deformation modulus enhancement in soilbag. [PDF]

Sci Rep
Liao J, Song Y, Tao Y, Xu S, Liu S, Fan K.   +5 more
europepmc   +1 more source

The role of community‐level institutions in smallholder land restoration

People and Nature, EarlyView.
Abstract This review focuses on the role of community‐level institutions in the adoption of land restoration practices by smallholder farmers. Based on a systematic review of 72 peer‐reviewed articles from 33 low‐ and middle‐income countries, the review synthesizes recent empirical evidence on the various roles these institutions play in supporting ...
Daniel Wiegant, Soumya Balasubramanya
wiley   +1 more source

Probabilistic Aseismic Performance Assessment of Rubber-Sand-Concrete Tunnel Linings Considering Spatial Variability of Rock Mass. [PDF]

Materials (Basel)
Li K, Mei X, Li B, Sheng H, Cui Z, Wang Y, Wu H, Wang T.   +7 more
europepmc   +1 more source

Remote sensing and citizen science for habitat mapping: A machine learning approach to lowland heathland in Surrey, UK

People and Nature, EarlyView.
Abstract In a time of extensive global biodiversity loss, conservation efforts increasingly rely on high‐resolution, accurate, up‐to‐date habitat maps to guide decision‐making and strategic interventions. Many products have been developed in response, using machine learning (ML) methods to automate habitat classification, often relying on satellite ...
Victoria Webster, Ana Andries, Daniel Banks, Andrew Jamieson, Ben Siggery, Mike Waite, Richard Murphy, Stephen Morse   +7 more
wiley   +1 more source

Dynamic damage evolution mechanism of buried cast iron pipeline under corrosion-blast coupling effects. [PDF]

Sci Rep
Yuqing X, Nan J, Yingkang Y, Zhenxing L, Tingyao W.   +4 more
europepmc   +1 more source

Lichen‐Derived Mineral Residue as a Renewable Particulate Filler in Polylactic Acid Biocomposites: Structure, Melt Rheology, Viscoelastic, and Flexural Behavior

Polymer Composites, EarlyView.
Lichen residue, a renewable mineral‐organic material, was melt compounded with polylactic acid and triacetin in a twin‐screw extruder. ABSTRACT A lichen‐derived natural material, known as “höllük” in southeastern Turkey, is introduced as a renewable filler for polylactic acid (PLA).
Huseyin Esen, Necip Elbir, Mine Begum Alanalp, Ali Durmus   +3 more
wiley   +1 more source

Geomechanical performance of a novel L-shaped wellbore design for hot dry rock geothermal reservoirs: insights from fully coupled thermo-hydro-mechanical modeling. [PDF]

Sci Rep
Aliakbari Khoei M, Pak A.
europepmc   +1 more source

Leucaena Oil Functionalized With Osmium Tetroxide as a Precursor for Polyol‐Based Polyurethane

Journal of Polymer Science, EarlyView.
Leucaena leucocephala seed oil is converted into a hydroxyl‐functional biopolyol through OsO4‐mediated dihydroxylation. The resulting biopolyol shows a hydroxyl number of 160–175 mg KOH g−1 and is successfully used to produce flexible, open‐cell polyurethane foams, highlighting a renewable route for converting underutilized biomass into value‐added ...
Giovanni Miraveti Carriello, Lucas Repecka Alves, Guilherme Manassés Pegoraro, Henrique Solowej Medeiros Lopes, Amanda Stefanie Jabur de Assis, Thaís de Agrella Janolla, David Rodrigues Gomes, Diego Aleixo da Silva, Beatriz Merillas, Fabiana Aparecida Lobo, Fabio Minoru Yamaji, Maira de Lourdes Rezende, Aparecido Junior de Menezes, Giovanni Pimenta Mambrini   +13 more
wiley   +1 more source

Quantitative characterization of crack coalescence mechanisms in granite at the mesoscopic scale using deep learning. [PDF]

Sci Rep
Xiao P, Pan PZ, Liu Z, Li D.
europepmc   +1 more source