Somatic expressions of either heteromeric TASK1/3 or homomeric TASK1/1 channels have been reported in various neurons, while expression of homomeric TASK3/3 channels has been re-ported only in dendrites. However, it is not known why homomeric TASK3/3...
This paper proposes a novel 3D representation, namely, a latent 3D volume, for joint depth estimation and semantic segmentation. Most previous studies encoded an input scene (typically given as a 2D image) into a set of feature vectors arranged over...
Background/Objectives: Sequence learning, the ability to pick up on regularities in our environment to facilitate behavior, is critically dependent on striatal structures in the brain, with the putamen emerging as a critical hub for implicit sequence...
Background: Olfactory dysfunction (OD)—including anosmia and hyposmia—is a common and often persistent outcome of viral infections. This systematic review consolidates findings from structural and functional MRI studies to explore how COV...
To better understand the process of neuroplasticity, this study assesses brain changes observed by voxel-based morphometry (VBM) in response to two different learning conditions. Twenty-two young, healthy subjects learned slacklining, a complex balan...
It is commonly believed that alertness and attention decrease after sleep deprivation (SD). However, there are not enough studies on the changes in psychomotor vigilance testing (PVT) during SD and the corresponding changes in brain function and brai...
In social network big data scheduling, it is easy for target data to conflict in the same data node. Of the different kinds of entropy measures, this paper focuses on the optimization of target entropy. Therefore, this paper presents an optimized met...
Metacognitive knowledge has been little investigated in aMCI patients. The aim of this study is to examine whether there are specific deficits in knowledge of self, task and strategies in mathematical cognition, due its importance for everyday functi...
The production and assembly of large engineering structures, many requiring tight tolerances, demand accurate long-distance measurements. This poses a major challenge for metrologists across industries such as energy, aviation, automotive, and machin...
Estimating lung volume capacity is crucial in clinical medicine, especially in disease diagnostics. However, the existing estimation methods are complex and expensive, which require experts to handle and consequently are more error-prone and time-con...
Machine learning (ML) is increasingly useful as data grow in volume and accessibility. ML can perform tasks (e.g., categorisation, decision making, anomaly detection, etc.) through experience and without explicit instruction, even when the data are t...
In the task of lunar soil collection, estimating the volume of the collected soil is an important part of the sampling control of the lander. Due to the design constraints of the lander, there is no additional installation position for volume measure...
Verbal fluency (VF) is an informative cognitive task. Lesion and functional imaging studies implicate distinct cerebral areas that support letter versus semantic fluency and the understanding of neural and cognitive mechanisms underlying task perform...
With the improvement of satellite autonomy, multi-satellite cooperative mission planning has become an important application. This requires multiple satellites to interact with each other via inter-satellite links to reach a consistent mission planni...
To address the challenges of low automation in tunnel wet-spraying jumbos and the heavy reliance on manual expertise for ensuring the spraying quality, this study proposes a novel task planning method for tunnel spraying operations. First, the tunnel...
In the context of the relentless evolution of network and communication technologies, the need for enhanced communication content and quality continues to escalate. Addressing the demands of data collection from the abundance of terminals within Inte...
An important as well as challenging task in modern applications is the management and processing with very short delays of large data volumes. It is quite often, that the capabilities of individual machines are exceeded when trying to manage such lar...
The effectiveness of manual therapy in reducing the catabolic effects of performing repetitive intensive force tasks on bones has not been reported. We examined if manual therapy could reduce radial bone microstructural declines in adult female Sprag...
Stereo matching has been solved as a supervised learning task with convolutional neural network (CNN). However, CNN based approaches basically require huge memory use. In addition, it is still challenging to find correct correspondences between image...
In pediatric surgery, robotic technology is useful. However, it is difficult to apply this technology due to size-related problems. In our study, we proposed a mechanical design method using a human-in-the-loop type simulator, and the moving volume a...
The task of investing in financial markets to make profits and grow one’s wealth is not a straightforward task. Typically, financial domain experts, such as investment advisers and financial analysts, conduct extensive research on a target fina...
23 October 2022
With the increase in the number of waste power batteries and the occurrence of related environmental problems, battery recycling is receiving extensive attention. Driven by economic benefits, many companies have begun to deploy the waste battery proc...
It is well known that many chronic diseases are associated with unhealthy diet. Although improving diet is critical, adopting a healthy diet is difficult despite its benefits being well understood. Technology is needed to allow an assessment of dieta...
Semantic segmentation of medical images holds significant potential for enhancing diagnostic and surgical procedures. Radiology specialists can benefit from automated segmentation tools that facilitate identifying and isolating regions of interest in...
Objectives: In this study, based on the known vestibulo-hippocampal connections, we asked whether mild chronic vestibulopathy leads only to vestibular-related deficits or whether there are effects on hippocampal function, structure, and cognition in...
Clustering high-dimensional and structural data remains a key challenge in computational biology, especially for complex single-cell and multi-omics datasets. In this study, we present K-volume clustering, a novel algorithm that uses the total convex...
Today’s business environments face rapid digital transformation, engendering the continuous emerging of new technologies. Robotic Process Automation (RPA) is one of the new technologies rapidly and increasingly grabbing the attention of businesses. R...
With the explosive growth of multimedia services and the continuous emergence of new space tasks, the spatial task scheduling timeliness problem is of great concern. The high computational cost of existing task scheduling methods is not suitable for...
Accurate prediction of fracture volume and morphology in horizontal wells is essential for optimizing reservoir development. Traditional methods struggle to capture the intricate relationships between fracturing effects, geological variables, and ope...
9 June 2022
This systematic review formulated a research question based on the PICO method in accordance with the Guidelines for Systematic Reviews and Meta-Analyses (PRISMA), “What is the effect of juggling as dual-task activity on neuroplasticity in the...
Balancing is a complex task requiring the integration of visual, somatosensory and vestibular inputs. The vestibular system is linked to the hippocampus, a brain structure crucial for spatial orientation. Here we tested the immediate and sustained ef...
Many living beings show the ability and necessity to develop invertible, tubular structures to enable additional functions temporarily. The biological archetypes always demonstrate a high change of volume of the structure between an inactive and acti...
Recently, machine learning-based task automation framework have been gaining attention in human resource management of Multi-National Companies (MNCs). Task automation framework helps MNCs to automate repetitive HR tasks, analyse data quickly and acc...
The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable de...
Skid trails constructed for timber extraction in steep terrain constitute a serious environmental concern if not well planned, executed and ameliorated. Carrying out post-harvest surveys in monitoring constructed trails in such terrain is an onerous...
In this paper, we have undertaken the challenging and novel task of establishing the existence of weak solutions for four types of hyperbolic Kirchhoff-type problems: the classical hyperbolic Kirchhoff problem, the problem with a free boundary, the p...
The rapid development of the Internet of Vehicles (IoV) and intelligent transportation systems has led to increased demand for real-time data processing and computation in vehicular networks. To address these needs, this paper proposes a task offload...
Prior studies have shown that performance on standardized measures of memory in children with autism spectrum disorder (ASD) is substantially reduced in comparison to matched typically developing controls (TDC). Given reported deficits in face proces...
Maximum entropy adversarial inverse reinforcement learning (ME-AIRL) has garnered widespread attention for its ability to learn rewards and optimize policies from expert demonstrations. In complex multi-task environments, applying meta-learning ME-AI...
In today’s uncertain and competitive market, where manufacturing enterprises are subjected to increasingly shortened product lifecycles and frequent volume changes, reconfigurable manufacturing system (RMS) applications play significant roles i...
Benefiting from the rapid development of big data and high-performance computing, more data is available and more tasks could be solved by machine learning now. Even so, it is still difficult to maximum the power of big data due to each dataset is is...
The goal of the few-shot learning method is to learn quickly from a low-data regime. Structured output tasks like segmentation are challenging for few-shot learning, due to their being high-dimensional and statistically dependent. For this problem, w...
Measuring the volume of bird eggs is a very important task for the poultry industry and ornithological research due to the high revenue generated by the industry. In this paper, we describe a prototype of a new metrological system comprising a 3D ran...
The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned s...
Railway infrastructure monitoring is crucial for transportation reliability and travelers’ safety. However, it requires plenty of human resources that generate high costs and is limited to the efficiency of the human eye. Integrating machine le...
Identifying and diagnosing cognitive impairment remains challenging. Some diagnostic procedures are invasive, expensive, and not always accurate. Meanwhile, evidence suggests that cognitive impairment is associated with changes in gait parameters. Ce...
The aim of this study was to analyse the relationship between fine motor skills (FMSs) and visual performance. Thirty young participants with normal binocular vision performed five fine motor tasks: Purdue, Grooved, and O’Connor pegboards, a ne...
The article investigates the problem of task assignment of vehicles for a production company. The presented problem is a complex decision-making issue which has not been analyzed in the literature before. Two stages must be passed through in order to...
Border patrol object detection is an important basis for obtaining information about the border patrol area and for analyzing and determining the mission situation. Border Patrol Staffing is now equipped with medium to close range UAVs and portable r...
Data imbalance is often encountered in deep learning process and is harmful to model training. The imbalance of hard and easy samples in training datasets often occurs in the segmentation tasks from Contrast Tomography (CT) scans. However, due to the...
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