Results 91 to 100 of about 136,993 (252)

Quantifying South Africa’s sulphur dioxide emission efficiency in coal-powered electricity generation by fitting the three-parameter log-logistic distribution

Journal of Energy in Southern Africa, 2017
This paper fits the three-parameter log-logistic (3LL) distribution to sulphur dioxide (SO2) monthly emissions in kilograms per gigawatt hour (kg/GWh) and in milligrams per cubic nano metre (mg/Nm3), at 13 of Eskom’s coal fired power-generating stations ...
Maseapei Elizabeth Girmay, Delson Chikobvu   +1 more
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Pareto exponentiated log-logistic distribution (PELL) with an application to Covid-19 data

AIP Advances
Recently, the Covid-19 pandemic has caused tremendous trauma over the world, leading to psychological and behavioral harm in addition to social and economic instabilities.
Shumaila Ihtisham, Sadaf Manzoor, Alamgir, Osama Abdulaziz Alamri, Muhammad Nouman Qureshi   +4 more
doaj   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

Advanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee, Jumi Kim, Taehan Yoon, So Hyun Kwon, Su Chan Park, Dohyun Chun, Dohyeong Kim, Eun Jung Park, Hyunwoo Kim, Ji Min Lee   +9 more
wiley   +1 more source

De Novo Designed Minibinders Targeting the GDF15–GFRAL Axis Reverse Cancer Cachexia and Restore Anti‐Tumor Immunity

Advanced Science, EarlyView.
Tumor‐derived GDF15 drives cancer cachexia and suppresses antitumor immunity. Here, de novo designed minibinders targeting the GDF15–GFRAL interface achieve picomolar affinity and potent pathway blockade. The minibinders alleviate cachexia, restore CD8+ T‐cell infiltration, enhance anti–PD‐1 responsiveness, and provide survival benefits across tumor ...
Haitao Wang, Tianzhen Hua, Meiling Wang, Bingbing Meng, Yue Zhang, Chengxu Jiang, Yunhe Gao, Hongqi Yang, Jian Bo   +8 more
wiley   +1 more source

CHCHD10 Mitigates Alzheimer's Disease‐Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons

Advanced Science, EarlyView.
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas, Ching‐Yao Yang, Kexin Zhang, Liam Wetzel, Dina Bugybayeva, Julia Ferguson, Md Mahmudul Hasan, William Samsa, Nandita Patil, Anshul Dash, Tarini Gowda, Xiongwei Zhu, Feixiong Cheng, Tian Liu   +13 more
wiley   +1 more source

CD177 Deficiency Defines a Stable Subtype of Human Neutrophil Granulocytes with Tumor Promoting Activity

Advanced Science, EarlyView.
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung, Alexander Beer, Susmita Ghosh, Ekaterina Pylaeva, Belal Alshaar, Tobias Tertel, Nils Bastian Leimkühler, Thomas Schroeder, Janine Gronewold, Nina Hagemann, Ayan Mohamud Yusuf, Benedikt Frank, Yiqiao Zhang, Dennis Nagel, Kim Schloeßer, Laura Karsch, Emily Hedtfeld, Sabrina Lohmann, Kathrin Blank, Andreas Kraus, Max Krumbein, Nastassia Kabankova, Hongxiao Wang, Almke Bader, Mathis Richter, Fengjun Zhang, Raphael Chevre, Bernd Giebel, Stephan Lang, Anika Grüneboom, Daniela Maier‐Begandt, Anja Hasenberg, Oliver Soehnlein, Hans Christian Reinhardt, Sven Heiles, Jianxu Chen, Jadwiga Jablonska, Albert Sickmann, Dirk M. Hermann, Matthias Gunzer   +39 more
wiley   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

Advanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo, Yangyang Zhang, Yongcheng Jin, Siwei Deng, Yongqi Chen, Zheng Feng, Hao Wen, Liu Wang, Yilin Li, Fanghong Ou, Yong Shen, Haiming Li, Tianyao Zhou, Xingzhu Ju, Xiaohua Wu   +14 more
wiley   +1 more source