This tutorial aims to provide an intuitive introduction Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due their representation flexibility and inherent capability quantify uncertainty over predictions. The starts with explaining the basic concepts that a is built on, including multivariate normal distribution, kernels, nonparametric models, joint conditional probability. It then provides concise description of implementation standard...

To investigate the relation between work environmental factors and risk of major depressive disorder (MDD) over 1 year, authors conducted a population-based longitudinal study randomly selected employees in Alberta, Canada (January 2008 to November 2011). Participants without current or lifetime diagnosis MDD at baseline (n = 2,752) were followed for year. was assessed using World Health Organization's Composite International Diagnostic Interview-Auto 2.1. The overall 1-year incidence 3.6%...

This tutorial aims to provide an intuitive introduction Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due their representation flexibility and inherent capability quantify uncertainty over predictions. The starts with explaining the basic concepts that a is built on, including multivariate normal distribution, kernels, non-parametric models, joint conditional probability. It then provides concise description of implementation standard...

Abstract This paper proposes a high‐performance path following algorithm that combines Gaussian processes (GP) based learning and feedback linearization (FBL) with model predictive control (MPC) for ground mobile robots operating in off‐road terrains, referred to as GP‐FBLMPC. The uses nominal kinematic learns unmodeled dynamics GP models by using observation data collected during field experiments. Extensive outdoor experiments Clearpath Husky A200 robot show the proposed GP‐FBLMPC...

As autonomous vehicles (AVs) become more common on public roads, their interaction with human-driven (HVs) in mixed traffic is inevitable. This requires new control strategies for AVs to handle the unpredictable nature of HVs. study focused safe mixed-vehicle platoons consisting both and HVs, particularly during longitudinal car-following scenarios. We introduce a novel model that combines conventional first-principles Gaussian process (GP) machine learning-based better predict HV behavior....

Abstract Quantum logic gates are the fundamental operational units in quantum computing. The SWAP gate, as an important two‐qubit has long been focus of scholars for seeking to achieve high‐fidelity implementations. This study proposes a scheme realizing gate using Rydberg atoms. ingeniously utilizes interactions between atoms construct model and combines “transitionless driving” algorithm design control laser. Numerical simulations show that this not only achieves but also robust against...

The rising presence of autonomous vehicles (AVs) on public roads necessitates the development advanced control strategies that account for unpredictable nature human-driven (HVs). This study introduces a learning-based method modeling HV behavior, combining traditional first-principles approach with Gaussian process (GP) learning component. hybrid model enhances accuracy velocity predictions and provides measurable uncertainty estimates. We leverage this to develop GP-based predictive...

Neurofilament (NF) protein [high molecular mass (NF-H)] is extensively phosphorylated in vivo. The phosphorylation occurs mainly its characteristic KSP (Lys-Ser-Pro) repeat motifs. There are two major types of motifs the NF-H tail domain: KSPXKX and KSPXXX. Recent studies by different laboratories have demonstrated presence a cdc2-like kinase [cyclin-dependent kinase-5 (cdk5)] nervous tissue that selectively phosphorylates XS/TXK lysine-rich histone (H1). This article describes...

Along with the advancement of light-weight sensing and processing technologies, unmanned aerial vehicles (UAVs) have recently become popular platforms for intelligent traffic monitoring control. UAV-mounted cameras can capture traffic-flow videos from various perspectives providing a comprehensive insight into road conditions. To analyze flow remotely captured videos, reliable accurate vehicle detection-and-tracking approach is required. In this paper, we propose deep-learning framework...

Underground gas storage reservoirs are vital to China's energy infrastructure, facilitating natural peak shaving and supply security. However, cyclic alternating loads from significant pressure fluctuations during injection production operations lead severe erosion wear of tubing strings, complicating safe operation. This study developed a custom jet flow gas–solid–liquid experimental apparatus analyze the effects impact angle, velocity, particle size on rates. An model was established data....

Abstract Chemical flooding has great potential for enhancing heavy oil recovery, especially reservoirs where thermal methods are not feasible. It been shown that the formation of emulsions during chemical can effectively improve sweep efficiency and, consequently, increase recovery. The mechanism flow oil-in-water (O/W) emulsion in porous media extensively studied and simulated using filtration theory. Few studies have done modelling water-in-oil (W/O) reservoirs. This study experimentally...

Abstract W states play an important role in quantum information processing and computing. Here, it proposes a scheme for preparing by designing the evolution operators with Rydberg superatoms. It encodes on effective energy level of superatom, construct shortcuts to adiabatic passages (STAP) operators. Combined Quantum Zeno dynamics STAP, can prepare three‐particle quickly efficiently. In addition, Rabi frequency this be described as linear superposition Gaussian functions, which reduces...

A large semantic gap between a high-level synthesis (HLS) design and low-level RTL simulation environment often creates barrier for those who are not field-programmable gate array (FPGA) experts. Moreover, such takes long time to complete. Software HLS simulators can help bridge this accelerate the process; but their shortcoming is that they do provide performance estimation. To make matters worse, we found current FPGA commercial software sometimes produce incorrect results. In order solve...

With the increasing presence of autonomous vehicles (AVs) on public roads, developing robust control strategies to navigate uncertainty human-driven (HVs) is crucial. This paper introduces an advanced method for modeling HV behavior, combining a first-principles model with Gaussian process (GP) learning enhance velocity prediction accuracy and provide measurable uncertainty. We validated this innovative using real-world data from field experiments applied it develop GP-enhanced predictive...

Abstract The paper presents a sand production model for deforming oil matrix. deformability of the matrix is an important issue given that in situ and well pumping induced stresses impact on susceptibility to produce sand. formulated consistent manner within framework mixture theory with porosity as one main field state variables. latter split into two parts: related volume changes result erosion matrix, other due deformations subjected stress field. coupling made through bulk volumetric...

Freshly formed Ru/Ti oxide anodes, containing between 5 and 40 atom % Ru, have been examined for their Tafel behavior during chlorine evolution, as well cyclic voltammetric (CV) ac impedance response at the open-circuit potential, in chlorine-free NaCl solutions. Also, 30 Ru electrodes electrochemically deactivated, seen by an increase anode potential slope evolution reaction long-term electrolysis. A comparison of data fresh deactivated anodes suggests that similar electrochemical...