Results 1 to 10 of about 11,200,376 (224)
Abstract models for heat engines [PDF]
Front. Phys. 16, 33202 (2021), 2020 We retrospect three abstract models for heat engines which include a classic abstract model in textbook of thermal physics, a primary abstract model for finite-time heat engines, and a refined abstract model for finite-time heat engines. The detailed models of heat engines in literature of finite-time thermodynamics may be mapped into the refined ...
arxiv +1 more source
Top-down Transformation Choice [PDF]
Statistical Modelling 2018, 2017 Simple models are preferred over complex models, but over-simplistic models could lead to erroneous interpretations. The classical approach is to start with a simple model, whose shortcomings are assessed in residual-based model diagnostics. Eventually, one increases the complexity of this initial overly simple model and obtains a better-fitting model.
arxiv +1 more source
A Physics Enhanced Residual Learning (PERL) Framework for Vehicle Trajectory Prediction [PDF]
arXiv, 2023 In vehicle trajectory prediction, physics models and data-driven models are two predominant methodologies. However, each approach presents its own set of challenges: physics models fall short in predictability, while data-driven models lack interpretability.
arxiv
Bethe Ansatz in Stringy Sigma Models [PDF]
J.Stat.Mech.0605:P05006,2006, 2006 We compute the exact S-matrix and give the Bethe ansatz solution for three sigma-models which arise as subsectors of string theory in AdS(5)xS(5): Landau-Lifshitz model (non-relativistic sigma-model on S(2)), Alday-Arutyunov-Frolov model (fermionic sigma-model with su(1|1) symmetry), and Faddeev-Reshetikhin model (string sigma-model on S(3)xR).
arxiv +1 more source
Non Proportional Odds Models are Widely Dispensable -- Sparser Modeling based on Parametric and Additive Location-Shift Approaches [PDF]
arXiv, 2020 The potential of location-shift models to find adequate models between the proportional odds model and the non-proportional odds model is investigated. It is demonstrated that these models are very useful in ordinal modeling. While proportional odds models are often too simple, non proportional odds models are typically unnecessary complicated and seem
arxiv
The dual nature of TDC – bridging dendritic and T cells in immunity
FEBS Letters, EarlyView.TDC are hematopoietic cells combining dendritic and T cell features. They reach secondary lymphoid organs (SLOs) and peripheral organs (liver and lungs) after FLT3‐dependent development in the bone marrow and maturation in the thymus. TDC are activated and enriched in SLOs upon viral infection, suggesting that they might play unique immune roles, since
Maria Nelli, Mirela Kuka
wiley +1 more source
FEBS Letters, EarlyView.In vivo IL‐10 produced by tissue‐resident tolDC is involved in maintaining/inducing tolerance. Depending on the agent used for ex vivo tolDC generation, cells acquire common features but prime T cells towards anergy, FOXP3+ Tregs, or Tr1 cells according to the levels of IL‐10 produced. Ex vivo‐induced tolDC were administered to patients to re‐establish/
Konstantina Morali +3 more
wiley +1 more source
Comparative Analysis of Machine Learning Models for Predicting Travel Time [PDF]
arXiv, 2021 In this paper, five different deep learning models are being compared for predicting travel time. These models are autoregressive integrated moving average (ARIMA) model, recurrent neural network (RNN) model, autoregressive (AR) model, Long-short term memory (LSTM) model, and gated recurrent units (GRU) model.
arxiv
FoxO1 signaling in B cell malignancies and its therapeutic targeting
FEBS Letters, EarlyView.FoxO1 has context‐specific tumor suppressor or oncogenic character in myeloid and B cell malignancies. This includes tumor‐promoting properties such as stemness maintenance and DNA damage tolerance in acute leukemias, or regulation of cell proliferation and survival, or migration in mature B cell malignancies.
Krystof Hlavac +3 more
wiley +1 more source
Model Validation in Ontology Based Transformations [PDF]
EPTCS 98, 2012, pp. 17-30, 2012 Model Driven Engineering (MDE) is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM) has been proposed as a profile for UML models of the Web Ontology Language (OWL).
arxiv +1 more source