Results 231 to 240 of about 19,221,438 (289)

Data Compression of the D1200 Suite: Achieving the Optimal Balance Between Size and Accuracy with the Diet-D200 Subset. [PDF]

J Comput Chem
Soriano-Agueda L.
europepmc   +1 more source

Real‐world effectiveness and safety of secukinumab in giant cell arteritis: an Italian multicentre cohort study

Arthritis Care &Research, Accepted Article.
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in giant cell arteritis (GCA) patients. Methods This multicentre retrospective study included patients with GCA who received secukinumab at 14 Italian centres with at least 6 months of follow‐up.
Luca Iorio, Federica Davanzo, Caterina Ricordi, Milena Bond, Ruggiero Mascolo, Jacopo Mora, Alessandro Tomelleri, Angelo Fassio, Francesca Cuzzocrea, Sara Monti, Edoardo Conticini, Fabiola Atzeni, Paolo Delvino, Carlotta Nannini, Augusta Ortolan, Francesco Pollastri, Ester Vivaldelli, Chiara Marvisi, Paola Toniati, Antonio Brucato, Alessandra Milanesi, Francesca Regola, Enrico Tombetti, Lorenzo Dagna, Roberta Ramonda, Christian Dejaco, Luca Quartuccio, Carlo Salvarani, Roberto Padoan, The Italian Society of Rheumatology Vasculitis Study Group   +29 more
wiley   +1 more source

A study on risk assessment and system development of tunnel lighting facilities based on XGBoost and Bayesian optimization. [PDF]

Sci Rep
Xiao H, Yang W, Tang J, Wang ZL.
europepmc   +1 more source

Generative AI Utilization and Perspectives Among Reproductive‐Age Women with Systemic Autoimmune and Rheumatic Diseases

Arthritis Care &Research, Accepted Article.
Objective Reproductive‐age women with systemic autoimmune and rheumatic diseases (SARDs) have unique information needs related to their SARDs and reproductive health. We sought to understand their use of and receptivity to current and hypothetical generative artificial intelligence (AI) tools for health information‐seeking. Methods We conducted a cross‐
Mariam Arif, Catherine Wright, Samantha Rodriguez, Sarah Graves, Tamar Krishnamurti, Mehret Birru Talabi   +5 more
wiley   +1 more source

Metrological Evaluation of Dimensional and Surface Roughness of Thermoplastic PLA Parts in High-Speed MEX 3D Printing Using a Dodecahedron Benchmark Geometry. [PDF]

Materials (Basel)
Bazan A, Turek P, Kubik P.
europepmc   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

Mapping coastal forest retreat using convolutional neural networks and different satellite imagery. [PDF]

PLoS One
Tajudeen TT, Ardon M, Tulbure M, Martin KL.   +3 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Deep learning framework for predicting measurement error drift in smart meter sensors under harsh coastal environments. [PDF]

PLoS One
Huang T.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source