Sims: An interactive tool for geospatial matching and clustering. [PDF]
Zaytar A +8 more
europepmc +1 more source
Does Participating in Agricultural Global Value Chains Promote Agricultural Growth?
ABSTRACT This study examines the relationship between GVC participation and agricultural value‐added growth in 43 countries over the period 1995–2022. In contrast to prior literature, we disaggregate the agricultural sector into four sub‐sectors namely crop cultivation, animal production, forestry and fishing.
Taner Turan +2 more
wiley +1 more source
Detecting gaps between urban expansion and lighting infrastructure growth using daytime and nighttime satellite imagery. [PDF]
Chen TK, Chen W, Stokes EC, Zhou Y.
europepmc +1 more source
Erosion of granular sediments by submerged impinging jets: Particle size effects and cohesion onset
Abstract This study investigates the erosion behavior and modeling of glass particle beds under impinging jet conditions, with a focus on particle size effects and the onset of cohesion. Ultrasonic profiling is implemented to scan and measure static crater profiles.
Ahmad Mohamadiyeh +4 more
wiley +1 more source
Atmospheric moisture transport anomalies and vegetation response in arid coastal ecosystems: insights from the 2017 coastal El Niño in northern Peru. [PDF]
Zhang C, Huang G.
europepmc +1 more source
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Owned House Cats Show No Preference for Specific Land Cover Types When Roaming Outdoors. [PDF]
Wolovelsky L, Kadosh N, Gish M.
europepmc +1 more source
Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source

