Results 81 to 90 of about 12,301 (257)

SPINEX-symbolic regression: similarity-based symbolic regression with explainable neighbors exploration

The Journal of Supercomputing
Abstract This article introduces a new symbolic regression algorithm based on the SPINEX (similarity-based predictions with explainable neighbors exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach to identifying high-merit expressions that satisfy accuracy- and structural similarity metrics.
M. Z. Naser, Ahmad Z. Naser
openaire   +1 more source

Globally Optimal Symbolic Regression

, 2017
In this study we introduce a new technique for symbolic regression that guarantees global optimality. This is achieved by formulating a mixed integer non-linear program (MINLP) whose solution is a symbolic mathematical expression of minimum complexity that explains the observations. We demonstrate our approach by rediscovering Kepler's law on planetary
Austel, Vernon, Dash, Sanjeeb, Gunluk, Oktay, Horesh, Lior, Liberti, Leo, Nannicini, Giacomo, Schieber, Baruch   +6 more
openaire   +2 more sources

siRNA Delivery via Cross‐Linked Gelatin Microparticles Enables Targeted Modulation of Osteogenic‐Vascular Cross‐Talk: An Advanced Human 3D in Vitro Test System for Therapeutic siRNA

Advanced Healthcare Materials, EarlyView.
Osteogenic‐angiogenic cross‐talk is a vital prerequisite for vascularized bone regeneration. In this study, we investigated the effects of siRNA‐mediated silencing of two inhibitory proteins, Chordin and WWP‐1, via CaP‐NP‐loaded gelatin microparticles in osteogenically differentiated microtissues.
Franziska Mitrach, Jonas Kubat, Stefan Simm, Alexandra H. Springwald, Burak Demir, Anton Liebezeit, Michael C. Hacker, Michaela Schulz‐Siegmund   +7 more
wiley   +1 more source

Discovering equations from data: symbolic regression in dynamical systems

Journal of Physics: Complexity
The process of discovering equations from data lies at the heart of physics and in many other areas of research, including mathematical ecology and epidemiology.
Beatriz R Brum, Luiza Lober, Isolde Previdelli, Francisco A Rodrigues   +3 more
doaj   +1 more source

Start, Stop, Rewind, Repeat—Cyclic Exposure of Adipose Stromal Cells‐derived Cartilage Organoids to Chondrogenic and Proliferative Cues to Achieve Scaled‐up and Customizable Bone Formation by Endochondral Ossification

Advanced Healthcare Materials, EarlyView.
This study exploits the plasticity of ASCs‐derived cartilage organoids which generate a perichondrial layer of MSCs when exposed to cyclic chondrogenic/proliferative cues. Using these organoids as building blocks, we develop (i) Phalange Shaped Tissue Engineered Cartilage (Pa‐TECs), recapitulating endochondral ossification suitable for the treatment of
Pablo Pfister, Emilien Lhospice, Andrés García‐García, Robert Paillaud, Sebastian Jung, Romain Schaller, Elisabeth A. Kappos, Claude Jaquiéry, Tarek Ismail, Dirk J. Schaefer, Michael de Wild, Ivan Martin, Alexandre Kaempfen, Arnaud Scherberich, Adrien Moya   +14 more
wiley   +1 more source

Taming the Immiscibility of Gold, Iron, and Boron to Craft Chemodegradable Nanoparticles for Multimodal Imaging and Radiotherapy

Advanced Healthcare Materials, EarlyView.
Over half of cancer patients undergo radiotherapy. Laser ablation enabled the synthesis of immiscible Au‐Fe‐B nanoparticles designed as degradable bimodal radiosensitizers for X‐ray radiotherapy (XRT), boron neutron capture therapy (BNCT), and bimodal imaging for X‐ray computed tomography (CT) and magnetic resonance imaging (MRI). These nanosensitizers
Michael Bissoli, Clara M.G. de Faria, Veronica Torresan, Maria Assunta Lacavalla, Mattia Cattelan, Denis Badocco, Paolo Pastore, Pasquina Marzola, Laura Cansolino, Cinzia Ferrari, Ian Postuma, Riccardo Vago, Silva Bortolussi, Antonello E. Spinelli, Daniel Forrer, Vincenzo Amendola   +15 more
wiley   +1 more source

Inferring interpretable models of fragmentation functions using symbolic regression

Machine Learning: Science and Technology
Machine learning is rapidly making its path into the natural sciences, including high-energy physics. We present the first study that infers, directly from experimental data, a functional form of fragmentation functions.
Nour Makke, Sanjay Chawla
doaj   +1 more source

3D‐Printed Titanium Implants with Bioactive Peptide‐Polysaccharide Scaffolds for Personalized Bone Reconstruction

Advanced Healthcare Materials, EarlyView.
Porous 3D‐printed titanium implants are made bioactive by integration with a supramolecular peptide‐hyaluronic acid nanofibrillar scaffold, without the addition of exogenous cells or growth factors. Uniform filling of the implant architecture promotes vascularized, spatially homogeneous bone regeneration, significantly enhancing osteogenesis throughout
Noam Rattner, Vladimir Perlis, Eran Golden, Ariel Pokhojaev, Rachel Sarig, Itzhak Binderman, Michal Halperin‐Sternfeld, Solomon Dadia, Lihi Adler‐Abramovich   +8 more
wiley   +1 more source

Angular coefficients from interpretable machine learning with symbolic regression

Journal of High Energy Physics
We explore the use of symbolic regression to derive compact analytical expressions for angular observables relevant to electroweak boson production at the Large Hadron Collider (LHC).
Josh Bendavid, Daniel Conde, Manuel Morales-Alvarado, Veronica Sanz, Maria Ubiali   +4 more
doaj   +1 more source

SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration

This article introduces a new symbolic regression algorithm based on the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach to identifying high-merit expressions that satisfy accuracy- and structural similarity metrics.
Naser, MZ, Naser, Ahmed Z
openaire   +2 more sources