Results 251 to 260 of about 3,774,779 (338)

Hydrogel‐Based Capacitive Sensor Model for Ammonium Monitoring in Aquaculture

Advanced Engineering Materials, EarlyView.
Traditional techniques for monitoring aquaculture water quality, particularly ammonium levels, harm fish. This work presents a novel capacitive sensor with an ionic hydrogel transducer to monitor ammonium concentration in real time based on the ammonium‐induced hydrogel dissociation and osmotic pressure. Monitoring aquaculture water quality, especially
Mohammad Mirzaee, Mahdi Askari‐sedeh, Ali Zolfagharian, Mostafa Baghani   +3 more
wiley   +1 more source

Signatures of natural selection may indicate a genetic basis for the beneficial effects of oily fish intake in indigenous people from coastal Ecuador. [PDF]

G3 (Bethesda)
Brandt DYC, Del Brutto OH, Nielsen R.
europepmc   +1 more source

Soft‐Layered Composites with Wrinkling‐Activated Multi‐Linear Elastic Behavior, Stress Mitigation, and Enhanced Strain Energy Storage

Advanced Engineering Materials, EarlyView.
In this study, exciting new bi‐/multi‐linear elastic behavior of soft elastic composites that accompany the activation of wrinkling in the embedded interfacial layers is analyzed. The new features and performance of these composite materials, including dramatic enhancements in energy storage, can be tailored by the concentration of interfacial layers ...
Narges Kaynia, Nicholas Xuanlai Fang, Mary C. Boyce   +2 more
wiley   +1 more source

Leveraging ancient DNA to uncover signals of natural selection in Europe lost due to admixture or drift. [PDF]

Nat Commun
Pandey D, Harris M, Garud NR, Narasimhan VM.   +3 more
europepmc   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

Assessing the Ecological Value: Monetizing Process Innovations in Tailored Forming

Advanced Engineering Materials, EarlyView.
This article introduces a method for evaluating the sustainability of innovations, even with limited data. The method is illustrated through an analysis of the “Tailored Forming” technology, which explores the impact of sustainability on economic value added.
Jonas Schneider, Jan Westing, Matthias Schmidt, Peter Nyhuis, Vivian Katharina Kuprat   +4 more
wiley   +1 more source

Natural selection on floral volatiles and other traits can change with snowmelt timing and summer precipitation. [PDF]

New Phytol
Powers JM, Briggs HM, Campbell DR.
europepmc   +1 more source

Non‐Destructive and Mechanical Characterization of the Bond Quality of Co‐Extruded Titanium‐Aluminum Profiles

Advanced Engineering Materials, EarlyView.
This study investigates the bond quality of co‐extruded aluminum–titanium hybrid profiles, focusing on the lateral angular co‐extrusion (LACE) process. It examines how heat treatments (HT) affect intermetallic phase formation, bond strength, and material properties.
Norman Mohnfeld, Ahmed Dewidar, Karim Qarbi, Hendrik Wester, Florian Patrick Schäfke, Alexej Verschinin, Hans Jürgen Maier, Sebastian Barton, Christian Klose, Johanna Uhe   +9 more
wiley   +1 more source

Maternal risk-management elucidates the evolution of reproductive adaptations in sharks by means of natural selection. [PDF]

Sci Rep
Deeken D, Macdonald C, Gainsbury A, Green ML, Cassill DL.   +4 more
europepmc   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source