Related papers: A new simulation-based model for calculating post-…
In this study, the first-of-its-kind use of active learning (AL) framework in thermal spray is adapted to improve the prediction accuracy of the in-flight particle characteristics and uses Gaussian Process (GP) ML model as a surrogate that…
This work introduces MAYA, a sequential imitation learning model based on multi-armed bandits, designed to reproduce and predict individual bees' decisions in contextualized foraging tasks. The model accounts for bees' limited memory…
With the advancement of large language models (LLMs), solving complex reasoning tasks has gained increasing attention. Inference-time computation methods (e.g., Best-of-N, beam search, et al.) are particularly valuable as they can enhance…
Suicide remains a pressing global health crisis, with over 720,000 deaths annually and millions more affected by suicide ideation (SI) and suicide attempts (SA). Early identification of suicidality-related factors (SrFs), including SI, SA,…
Quantitative assessment of the growth of biological organisms has produced many mathematical equations. Many efforts have been given on statistical identification of the correct growth model from experimental data. Every growth equation is…
Alzheimer's disease (AD) progresses through distinct stages, from early mild cognitive impairment (EMCI) to late mild cognitive impairment (LMCI) and eventually to AD. Accurate identification of these stages, especially distinguishing LMCI…
While likelihood-based inference and its variants provide a statistically efficient and widely applicable approach to parametric inference, their application to models involving intractable likelihoods poses challenges. In this work, we…
The 1mm roundworm C. elegans is a model organism used in many sub-areas of biology to investigate different types of biological processes. In order to complement the n-vivo analysis with computer-based investigations, several methods have…
Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This task is especially difficult in the pre-launch and early post-launch phases, when…
Patients resuscitated from cardiac arrest (CA) face a high risk of neurological disability and death, however pragmatic methods are lacking for accurate and reliable prognostication. The aim of this study was to build computational models…
We consider a lognormal diffusion process having a multisigmoidal logistic mean, useful to model the evolution of a population which reaches the maximum level of the growth after many stages. Referring to the problem of statistical…
It was recently demonstrated that feeding a silicon-in-silica coaxial fibre into a flame$\mathord{-}$imparting a steep silica viscosity gradient$\mathord{-}$results in the formation of silicon spheres whose size is controlled by the feed…
Length-based methods are the cornerstone of many population studies and stock assessments. This study tested two widely used methods: the Powell-Wetherall (P-W) plot and the Lmax approach, i.e., estimating Linf directly from Lmax. In most…
The cooling histories of individual meteorites can be empirically reconstructed by using ages from different radioisotopic chronometers with distinct closure temperatures. For a group of meteorites derived from a single parent body such…
The hypothetical impact of aerial spraying on tsetse fly populations is investigated. Spray cycles are scheduled at intervals two days short of the first interlarval period and halted once the last of the female flies that originated from…
The purpose of this paper is to implement a random death process into a persistent random walk model which produces subballistic superdiffusion (L\'{e}vy walk). We develop a Markovian model of cell motility with the extra residence variable…
Area per lipid (APL) is an important property of biological and artificial membranes. Newly constructed bilayers are characterized by their APL and newly elaborated force fields must reproduce APL. Computer simulations of APL are very…
In the constantly changing field of data-driven decision making, accurately predicting future events is crucial for strategic planning in various sectors. The emergence of Large Language Models (LLMs) marks a significant advancement in this…
The maximum ${\log}_q$ likelihood estimation method is a generalization of the known maximum $\log$ likelihood method to overcome the problem for modeling non-identical observations (inliers and outliers). The parameter $q$ is a tuning…
We present an improved statistical method for calculation of mean lifetime of nuclei in a decay chain with uncertain relation between mother and daughter nuclei. The method is based on formation of time distribution of intervals between…