Results 151 to 160 of about 1,294,477 (268)

Complementary cardiac functional assessment using systolic time intervals and bioelectrical impedance analysis. [PDF]

Open Heart
Nishikawa T, Higaki A, Kurokawa K, Abe A, Horie R, Miyabe R, Nakao Y, Fujisawa T, Akazawa Y, Miyoshi T, Kawakami H, Higashi H, Tamaki S, Nishimura K, Inoue K, Ikeda S, Yamaguchi O.   +16 more
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Effects of microbial inoculants and planting density on soybean summer-sown growth, nutrients accumulation and yield in Southern Xinjiang. [PDF]

Front Plant Sci
Wang W, Li M, Li K, Li X, Liu J, Mao T, Yin X, Ma L, Wang D, Yang L, Zhai Y.   +10 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Assessing body position through experimental cremation: A pilot study using colorimetry and FTIR-ATR analyses. [PDF]

PLoS One
Becerra Fuello P, Lescure J, Lackinger A, Ráez MS, Caro JG, Jiménez GA.   +5 more
europepmc   +1 more source

Microstructure, Thermal Transport, and Dry‐Sliding Tribology of Powder‐Metallurgy Al7075 Composites Reinforced With Sol–Gel‐Derived ZnO–rGO Hybrid Nanoparticles

Advanced Engineering Materials, EarlyView.
Sol–gel‐derived ZnO–rGO hybrid nanoparticles enable Al7075 powder‐metallurgy composites to achieve concurrent gains in hardness and thermal conductivity while markedly lowering friction and wear. The hybrid architecture couples ZnO‐based load support with rGO‐assisted lamellar sliding and heat spreading, revealing a promising route toward lightweight ...
Bunyamin Aksakal, Cevher Kursat Macit, Merve Ayık, Hakan Tutumlu   +3 more
wiley   +1 more source

Driven by climate change, sudden swings between wet and dry create "hydrologic whiplash". [PDF]

Proc Natl Acad Sci U S A
McDermott A.
europepmc   +1 more source

Active Corrosion Protection of Sintered AA7075 Aluminum Alloy via Mn Powder Addition

Advanced Engineering Materials, EarlyView.
AA7075 containing Mn‐rich particles is fabricated via spark plasma sintering using AA7075 and Mn powders. Corrosion resistance is evaluated through dip‐and‐dry tests using 0.1 M NaCl (pH 6.0), and mass loss decreases with increasing Mn addition. Mn‐rich particles function as a source of Mn ions, and formation of Mn‐accumulation films on Cu‐containing ...
Ko Ebina, Masashi Nishimoto, Izumi Muto
wiley   +1 more source

Nitrogen supply mitigates heat-driven potato yield loss by sustaining radiation use efficiency and dry matter partitioning to tubers. [PDF]

Front Plant Sci
He Y, Li C, Si J, Zhang L, Zhou Z.
europepmc   +1 more source

Extrusion‐Based Additive Manufacturing of Advanced Ceramics: Strengthening Mechanisms and Process Optimization Review

Advanced Engineering Materials, EarlyView.
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari, Mohammad Hadi Sheikh‐Ansari, Avinash Borgaonkar, Mehran Dadkhah, Abdollah Saboori   +4 more
wiley   +1 more source