This paper examines whether standard price-discovery measures can reliably identify directional predictive precedence in a highly correlated commodity-equity system. Using 21 years of daily data for Petrobras and the Ibovespa (2005–2026), the s...
The auditory mismatch negativity (MMN) has been considered a preattentive index of auditory processing and/or a signature of prediction error computation. This study tries to demonstrate the presence of an MMN to deviant trials included in complex au...
Legal systems evolve continuously in response to legislative reforms, emerging judicial interpretations, and shifting societal expectations, making it increasingly difficult to anticipate changes in legal precedent using conventional analytical metho...
In order to improve the adaptability of the lane keeping control system to complex environments, a dynamic lane tracking control strategy of the commercial vehicle based on the robust model predictive control (RMPC) algorithm is proposed considering...
The cooperative lane change among several connected and automated vehicles (CAVs) provides ideas for enhancing the traffic safety and efficiency issues caused by lane changes. However, most of the existing studies mainly focus on the independent anal...
This study evaluates the applicability of the Advanced Predictor of Electrical Parameters (APEP) methodology to predict the degradation of key electrical parameters in analog-to-digital converters (ADCs) exposed to ionizing radiation, from measuremen...
Preceding vehicles have a significant impact on the safety of the vehicle, whether or not it has the same driving direction as an ego-vehicle. Reliable trajectory prediction of preceding vehicles is crucial for making safer planning. In this paper, w...
Continuous cropping of Brassica napus impairs sustainable production via soil nutrient imbalance and microecological degradation. We evaluated rhizosphere soil properties and microbial communities under rotations crops (Triticum aestivum [TaBn], Beta...
Given the current focus on anticipation in perception, action and cognition, including language processing, there is a need for a method to tap into predictive processing in situations in which cue and feedback stimuli are not explicitly marked as su...
Winter loss rates of honey bee colonies may fluctuate highly between years in temperate climates. The present study combined survey data of autumn and winter loss rates in Germany (2012–2021) with estimates of honey flow—assessed with aut...
Unusual animal behaviors (UABs) have been observed before large earthquakes (EQs), however, their mechanisms are unclear. While information on UABs has been gathered after many EQs, few studies have focused on the ratio of emerged UABs or specific be...
The problem of dynamic adaptation of prediction algorithms in chaotic environments based on identification of the situations-analogs in the database of retrospective observations is considered. Under conditions of symmetrical and unsymmetrical chaoti...
Natural ventilation has been used widely in buildings to deliver a healthy and comfortable indoor environment for occupants. It also reduces the consumption of energy in the built environment and dilutes the concentration of carbon dioxide. Various m...
Drivers’ behaviors and decision making on the road directly affect the safety of themselves, other drivers, and pedestrians. However, as distinct entities, people cannot predict the motions of surrounding vehicles and they have difficulty in pe...
The paper describes the algorithm and the results of the seismic hazard estimate based on the data of the seismological catalog of the US Geological Survey (USGS). The prediction algorithm is based on the search for clusters of seismic activity in wh...
Understanding the intricate relationships between diseases is critical for both prevention and recovery. However, there is a lack of suitable methodologies for exploring the precedence relationships within multiple censored time-to-event data, result...
Adjacent, multi-working face mining can expand the range of disturbed overburden, increasing the risk of triggering roof water inrush, which threatens the safe operation of coal mines. In this paper, we propose a risk identification method for roof w...
There is an increasing interest in machine learning (ML) algorithms for predicting patient outcomes, as these methods are designed to automatically discover complex data patterns. For example, the random forest (RF) algorithm is designed to identify...
To decrease human and economic damage owing to earthquakes, it is necessary to discover signals preceding earthquakes. We focus on the concept of “early warning signals” developed in bifurcation analysis, in which an increase in the varia...
Modern industrial mining and mineral processing applications are characterized by large volumes of historical process data. Hazardous events occurring in these processes compromise process safety and therefore overall viability. These events are reco...
The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By dia...
Non-neural machine learning (ML) and deep learning (DL) are used to predict system failures in industrial maintenance. However, only a few studies have assessed the effect of varying the amount of past data used to make a prediction and the extension...
The current paper presents a forecasting methodology for short-term water demand forecasting in the context of the Battle of Water Demand Forecasting. The methodology considers five distinct forecasting techniques, which are compared in terms of thei...
The early prediction of changes in disease state allows timely treatment of patients with inflammatory bowel disease (IBD) to be performed, which improves disease outcome. The aim of this pilot study is to explore the potential of fecal volatile orga...
Defects occurring during the maintenance phase of residential buildings not only undermine the quality of life of residents but also lead to disputes with contractors, which often escalate into litigation rather than being resolved through alternativ...
Background: Severe coronavirus disease 2019 (COVID-19) disease courses are characterized by immuno-inflammatory, thrombotic, and parenchymal alterations. Prediction of individual COVID-19 disease courses to guide targeted prevention remains challengi...
We evaluated whether predictive alerts improve recovery in DriftGuard-SLA, a bounded controller for the Kubernetes-based DeathStarBench Hotel Reservation application. A logistic model trained on 35 monitoring runs was frozen before evaluation in 350...
In response to the widespread adoption of vehicle-following systems in autonomous applications, the demand for collision warning to enable safer functionalities is increasing. This study provides an approach for automated vehicle guidance to follow t...
The middle reaches of the Yellow River (MRYR) are an important base for agricultural and husbandry production and coal and coal-based power and chemical industries. Understanding the variability of autumn (especially September) precipitation over the...
25 June 2018
Health-risks from contaminated soils are assessed all over the world. An aspect that many risk assessments share is the heterogeneity in the distribution of contaminants. In a preceding study, we assessed potential health-risks for mothers and childr...
As autonomous vehicle technology advances, the development of energy-efficient control methodologies emerges as a critical area in the literature. This includes the behavior control of vehicles near signalized intersections, which still needs compreh...
In the past, the social and economic impacts of industrial revolutions have been clearly identified. The current Fourth Industrial Revolution (Industry 4.0) is characterized by robotization, digitization, and automation. This will transform the produ...
Deep neural networks have been widely applied in architectural analysis and design research, supporting tasks such as facade recognition, floor-plan analysis, and architectural visual classification. However, although existing models possess strong p...
27 August 2021
The flow in a transonic turbine stage still poses a high challenge for the correct prediction of turbulence using an eddy viscosity model. Therefore, an unsteady RANS simulation with the k-ω SST model, based on a preceding study of turbulence inlet c...
As both satellite imagery and image-based machine learning methods continue to improve and become more accessible, they are being utilized in an increasing number of sectors and applications. Recent applications using convolutional neural networks (C...
Wastewater-based epidemiology is a robust, scalable, cost-effective, and high-performing tool to monitor and predict SARS-CoV-2 trends. We aimed to investigate whether this approach could be applied to influenza A/B viruses and respiratory syncytial...
The rapid increase in the number of vehicles has brought significant challenges to energy conservation and environmental sustainability. To solve these problems, various frameworks and models based on intelligent connected vehicles (ICVs) have been i...
Groundwater is an essential water resource and plays a crucial role, especially in areas with limited surface water availability. However, the exacerbation of groundwater droughts, fueled by phenomena such as climate change, urbanization, and industr...
To address energy management challenges for intelligent connected automated range-extended electric vehicles under vehicle-road cooperative environments, a hierarchical energy management strategy (EMS) based on speed prediction is proposed from the p...
Reinforcement learning (RL)–based car-following (CF) control strategies have attracted significant attention in academia, emerging as a prominent research topic in recent years. Most of these control strategies focus solely on the motion status...
Background/Objectives: Survival models can retain their ability to rank patients while their absolute-risk predictions become less accurate over time. We compared temporal calibration drift and updating across statistical and machine-learning models...
A strong seismic swarm occurred in the south Aegean Sea from late January to March 2025. Here, we apply natural time analysis (NTA), which can identify the critical stage before strong earthquakes, and find that all earthquakes of magnitude five or l...
In this study, we obtain the comparative analysis of methods of quick approximate analytical prediction of Mach shock height in planar steady supersonic flows (for example, in supersonic jet flow and in narrowing channel between two wedges), that are...
We assessed the nature and spatial and temporal patterns of deformation over the Miami Park bluffs on the eastern margin of Lake Michigan and investigated the factors controlling its observed deformation. Our approach involved the following steps: (1...
The worldwide global increase in serum 25-hydroxyvitamin D (25(OH)D) measurements has led some countries to restrict reimbursement for certain clinical situations only. Another approach could consist in providing physicians with screening tools in or...
Background: Cognitive impairment is a common feature of schizophrenia spectrum disorders and has been associated with functional disruption preceding the onset of psychosis. Understanding how cognitive deficits interact with clinical symptoms and fun...
Central to the debate on the production–comprehension relationship in prosodic development is the acquisition of the focus-to-prosody mapping in West Germanic languages. Past research primarily examined the production–comprehension relati...
Context modeling has always been the groundwork for the dialogue response generation task, yet it presents challenges due to the loose context relations among open-domain dialogue sentences. Introducing simulated dialogue futures has been proposed as...
This study forecasts unusually large daily Bitcoin price movements and examines whether the resulting warnings improve investment decisions. We compare simple volatility signals, a benchmark based on the previous day’s return magnitude, logisti...
Case order effects, where decision-makers resolve dilemmas differently depending on the order in which cases are presented, are well established in the psychology of moral decision-making. Yet this type of order effect has rarely been studied in a le...
of 18