Search Results (2,471)

Action video games foster competitive environments that demand rapid spatial navigation and decision-making. Action video gamers often exhibit faster response times and slightly improved accuracy in vision-based sensorimotor tasks. Background/Objectives: However, the underlying functional and structural changes in the two visual streams of the brain that may be contributing to these cognitive improvements have been unclear. Methods: Using functional and diffusion MRI data, this study investigated the differences in connectivity between gamers who play action video games and nongamers in the dorsal and ventral visual streams. Results: We found that action video gamers have enhanced functional and structural connectivity, especially in the dorsal visual stream. Specifically, there is heightened functional connectivity—both undirected and directed—between the left superior occipital gyrus and the left superior parietal lobule during a moving-dot discrimination decision-making task. This increased connectivity correlates with response time in gamers. The structural connectivity in the dorsal stream, as quantified by diffusion fractional anisotropy and quantitative anisotropy measures of the axonal fiber pathways, was also enhanced for gamers compared to nongamers. Conclusions: These findings provide valuable insights into how action video gaming can induce targeted improvements in structural and functional connectivity between specific brain regions in the visual processing pathways. These connectivity changes in the dorsal visual stream underpin the superior performance of action video gamers compared to nongamers in tasks requiring rapid and accurate vision-based decision-making. Full article

The complexity and functional evolution of mammalian visual systems have always been a focal point in neuroscience and biological science research. The primary neurons that output motion direction signals have been a focal point of research in visual neuroscience for nearly 130 years. These neurons are widely present in the cortex and retina of mammals. Although the relevant pathways have been discovered and studied for almost 60 years due to experimental accessibility, research still remains at the cellular level. The specific functions and overall operational mechanisms of the component neurons in the motion direction-selective pathways are yet to be clearly elucidated. In this study, we modeled existing relevant neuroscience conclusions based on the symmetry and asymmetry of whole cells in the retina-to-cortex pathway and proposed a quantitative mechanism for motion direction selectivity pathways, called the Artificial Visual System (AVS). By tests based on 1 million instances of 2D, eight-direction grayscale moving objects, including 10 randomly shaped objects of various sizes, we confirm AVS’s high effectiveness on motion direction detecting. Furthermore, by comparing the AVS with two well-known convolutional neural networks, namely LeNet-5 and EfficientNetB0, we verify its efficiency, generalization, and noise resistance. Moreover, the analysis indicates that the AVS exhibits evident biomimetic characteristics and application advantages concerning hardware implementation, biological plausibility, interpretability, parameter count, and learning difficulty. Full article

As the importance of hygiene and safety management in food manufacturing has been increasingly emphasized, research on non-destructive and non-contact inspection technologies has become more active. This study proposes a real-time and non-destructive food inspection system with sub-terahertz waves which penetrates non-conducting materials by using a frequency of 0.1 THz. The proposed system detects not only the presence of foreign matter, but also the degree of depth to which it is mixed in foods. In addition, the system estimates water activity levels, which serves as the basis for assessing the freshness of seaweed by analyzing the transmittance of signals within the sub-terahertz image. The system employs YOLOv8n, which is one of the newest lightweight object detection models. This lightweight model utilizes the feature pyramid network (FPN) to effectively detect objects of various sizes while maintaining a fast processing speed and high performance. In particular, to validate the performance in real manufacturing facilities, we implemented a hardware platform, which accurately inspects seaweed products while cooperating with a conveyor device moving at a speed of 45 cm/s. For the validation of the estimation performance against various water activities and the degree of depth of foreign matter, we gathered and annotated a total of 9659 sub-terahertz images and optimized the learning model. The final results show that the precision rate is 0.91, recall rate is 0.95, F1-score is 0.93, and mAP is 0.97, respectively. Overall, the proposed system demonstrates an excellent performance in the detection of foreign matter and in freshness estimation, and can be applied in several applications regarding food safety. Full article

Effective Construction Site Layout Planning (CSLP) ensures the organized placement and sizing of temporary facilities, enhancing workflow and logistical efficiency. Poorly planned layouts, however, can increase material handling times, create bottlenecks, and reduce productivity, ultimately leading to higher costs. The main objective of this study is to introduce a BIM-based hybrid framework for CSLP that integrates Systematic Layout Planning (SLP) with a Genetic Algorithm (GA), developed through a Design Science Research approach. This Construction Site Optimization Framework (CSOF) addresses CSLP as a multi-objective optimization problem, prioritizing efficient positioning of facilities while accounting for workflow intensity, safety, and manager preferences. The framework’s continuous-space modeling supports a realistic approach, moving beyond fixed-location models. Exploratory case studies demonstrated CSOF’s effectiveness, achieving 30.79% to 40.98% reductions in non-value-adding travel distances and adaptability across varied site conditions. In this way, this research provides a decision-support tool that balances automation with decision-maker input, enhancing layout efficiency and operational flexibility in construction site management. Full article

This study investigates integrating circular economy principles—such as closed-loop systems and economic decoupling—into industrial sectors, including refining, clean energy, and electric vehicles. The primary objective is to quantify the impact of circular practices on resource efficiency and environmental sustainability. A mixed-methods approach combines qualitative case studies with quantitative modelling using the Brazilian Land-Use Model for Energy Scenarios (BLUES) and Autoregressive Integrated Moving Average (ARIMA). These models project long-term trends in emissions reduction and resource optimization. Significant findings include a 20–25% reduction in waste production and an improvement in recycling efficiency from 50% to 83% over a decade. Predictive models demonstrated high accuracy, with less than a 5% deviation from actual performance metrics, supported by error metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). Statistical validations confirm the reliability of these forecasts. The study highlights the potential for circular economy practices to reduce reliance on virgin materials and lower carbon emissions while emphasizing the critical role of policy support and technological innovation. This integrated approach offers actionable insights for industries seeking sustainable growth, providing a robust framework for future resource efficiency and environmental management applications. Full article

Currently, the process of tracking moving objects and determining their indoor location is considered to be one of the most attractive applications that have begun to see widespread use, especially after the adoption of this technology in some smartphone applications. The great developments in electronics and communications systems have provided the basis for tracking and location systems inside buildings, so-called indoor positioning systems (IPSs). The ultra-wideband (UWB) technology is one of the important emerging solutions for IPSs. This radio communications technology provides important characteristics that distinguish it from other solutions, such as secure and robust communications, wide bandwidth, high data rate, and low transmission power. In this paper, we review the implementation of the most important real-time indoor positioning and tracking systems that use ultra-wideband technology for tracking and localizing moving objects. This paper reviews the newest in-market UWB modules and solutions, discussing several types of algorithms that are used by the real-time UWB-based systems to determine the location with high accuracy, along with a detailed comparison that saves the reader a lot of time and effort in choosing the appropriate UWB-module/method/algorithm for real-time implementation. Full article

Background/Objectives: Extensive and closely coordinated remodeling processes take place in the periodontal ligament (PDL) and the adjacent bone during orthodontic tooth movement. In complex orthodontic cases, it is necessary to move teeth into an augmented bony defect, for example, in patients with cleft lip, alveolus, and palate. The important role of the PDL during tooth movement is well accepted but not fully understood. Therefore, the present study investigated the PDL after 23 weeks of tooth movement into an augmented critical-sized defect. Methods: The second molars of four beagle dogs were moved into a critical-sized defect, which was filled with bovine xenograft or nanocrystalline hydroxyapatite. Autogenous bone served as control. After 23 weeks, histological samples were microscopically analyzed, and the dimension of the PDL was measured. For statistical calculations, a Wilcoxon–Mann–Whitney test was used. Results: The PDL was significantly wider on the tension side compared with the compression side for all replacement materials analyzed (p ≤ 0.05). These results apply to both the mesial and distal roots. Conclusions: The remodeling processes reached equilibrium within 23 weeks, resulting in a wider gap on the tension side, which contrasts with the situation a few days after the initial force application. Full article

The development of resource-efficient digital technologies is a critical challenge in the wastewater sector. This industrial case study, conducted in collaboration with the Veas Water Resource Recovery Facility in Norway, focused on creating data pre-processing methods and resource-efficient control strategies. Using data from the Veas biogas plant, dynamic models were developed to compare control outcomes. The primary objective was to maximize biogas production and hot water usage while maintaining optimal temperature and hydraulic retention time by adjusting inlet sludge and hot water flow rates. Sequential operations were approximated as continuous operations using a 30-min moving minimum/maximum for bimodal data and a 2-h moving average for noisy data. The data-driven dynamic models achieved an accuracy of up to $R^2$ of 0.85. The control strategy, which included one feedback controller, one ratio controller, and flow rate restrictions, was compared to real production data (baseline) and tested across six scenarios. The best improvement over the baseline scenario resulted in a 3% increase in total biogas production, a 6% increase in total organic loading, a 13% increase in hot water use, and a one-day reduction in hydraulic retention time. Future work should focus on control studies using extended datasets and nonlinear models. Full article

Recent advancements in autonomous mobile robots (AMRs), such as aerial drones, ground vehicles, and quadrupedal robots, have significantly impacted the fields of infrastructure inspection, emergency response, and surveillance. Many of these settings contain multiple moving elements usually neglected in the planning process. While a large body of work covers topics addressing scenarios with stationary objects, promising work with dynamic points of interest has only recently gained traction due to computational complexity. The nature of the problem brings with it the challenges of motion prediction, real time adaptability, efficient decision-making, and uncertainty. Concerning aerial drones, while significantly constrained computationally, good understanding and the relative simplicity of their platform gives way to more complex prediction and planning algorithms needed to work with multiple moving objects. This paper presents a survey of the current state-of-the-art solutions to the path planning problem for multiple moving object inspection using aerial drones. The presented algorithms and approaches cover the challenges of motion and intention prediction, obstacle avoidance, planning in dynamic environments, as well as scenarios with multiple agents. Potential solutions and future trends were identified primarily in the form of heuristic and learning methods, state-of-the-art probabilistic prediction algorithms, and further specialization in regard to every scenario. Full article

Rapidly changing digital technologies are reconfiguring the way human society lives, indicating that more and more middle-aged and older adults will lead a digital life in the future. Whether digital technology for today can effectively improve the quality of digital life of this cohort is the focus of this study. This study proposed a “cognitive–emotional–behavioral” model and situated the use of the Extreme Edition App as a cross-sectional research object. The study also explored the relationship between middle-aged and older adults’ perceptions of the benefits of cash subsidies, the pleasure and worry generated by the use of the app, and their continued use of the app. It has become a fact that human beings are walking side by side with digital technology; digital technology still moves forward and upward. Thus, it is forward-looking to pay attention to the digital life adaptation of the current middle-aged and older groups. A total of 1200 valid questionnaires were obtained, and regression analysis showed that (1) the more comprehensive and in-depth the cohort’s knowledge of the benefits of cash subsidies is, and the more sustainable their continuous use of the Extreme Edition App is, the more pleasure they experience, and the less worry they feel during its use. (2) The more pleasure middle-aged and older adults feel while using the Extreme Edition App, the more likely they are to continue using it. Conversely, the more worry they feel, the less likely they are to maintain its use. (3) Emotions generated during the use of the Extreme Edition App mediate the relationship between this cohort’s perceptions of cash subsidy benefits and their continued-use behavior. Full article

Background/Objectives: Overall priorities of the international pediatric-onset spinal cord injury (SCI) population are unknown. The purpose was to describe and compare Life and Health (L&H) domain overall priorities of European youth with SCI and their parents and caregivers (P&C). Methods: A survey with a cross-sectional design, prepared by the PEPSCI Collaboration, was conducted in six European countries. In total, 202 participants, including youth with SCI (n = 101) and their P&C (n = 101), were included. Overall priorities were calculated based on unhappiness, importance, and research. Results: The sample included youth aged 8–12 years (30.7%) and 13–25 years (69.3%; 38.6% 13–17-year-olds and 30.7% youth aged 18–25 years), in addition to their P&C. The top three L&H priorities highlighted by P&C of the youth aged 8–12 years were “bladder” function (78%), “leg/foot movement” (77%), or “bowel” function (74%), compared with “leg/foot movement” (79%), “sit-to-stand” (76%), or “walking/ability to move” (75%) reported by P&C of the youth aged 13–25 years. The youth aged 13–25 years considered “leg/foot movement” (68%), “bowel” (66%), or “bladder” function (65%) as priorities. The top 10 priorities highlighted by the youth aged 13–25 years compared to the top 10 priorities rated by P&C were issues related to “personal needs”. Nevertheless, “pressure injuries”, “pain”, “bowel function”, or “mobility in the community” were highlighted as top preferences of priorities for the youth aged 13–25 years compared to their P&C. Conclusions: Adolescents/young adults highlighted health domain priorities compared with their P&C, who equally considered L&H domains. Life domains, which were previously unaddressed, were highlighted by P&C, including “adulthood expectations” and “parenthood expectations”. This survey will promote the involvement of stakeholders for comprehensive rehabilitation management for this population. Full article

Background and Objectives: Oropharyngeal dysphagia is a common swallowing disorder, characterized by difficulties in moving food and liquids from the mouth to the esophagus; it is particularly prevalent among older adults with neurological conditions. This study aimed to evaluate the effectiveness of a short-term complex treatment protocol combining dietary modifications, swallowing exercises, and transcutaneous neuromuscular electrostimulation in reducing the oropharyngeal dysphagia severity and aspiration risk among geriatric patients. Materials and Methods: A total of 64 participants aged 60 and older, with oropharyngeal dysphagia, at LSMU Kaunas Hospital between May 2021 and April 2023, were included in the study after excluding those with significant comorbidities. Diagnostic assessments included the water swallow test and Fiberoptic Endoscopic Evaluation of Swallowing, conducted before and after treatment. Results: The results indicated a statistically significant reduction in the severity of oropharyngeal dysphagia, with 18.8% of patients showing improvements from moderate to mild dysphagia and 33.3% from severe to moderate. Additionally, the median PAS score was four points (IQR 3–6) before treatment and significantly decreased to three points (IQR 2–4) after treatment (p < 0.001). Conclusions: These findings suggest that even a short-term multidisciplinary approach that lasts 10 days can effectively alleviate the symptoms of oropharyngeal dysphagia, enhance patient safety, and improve swallowing among geriatric patients suffering from this condition. Full article

The idea of introducing a robot into an Ambient Assisted Living (AAL) environment to provide additional services beyond those provided by the environment itself has been explored in numerous projects. Moreover, new opportunities can arise from this symbiosis, which usually requires both systems to share the knowledge (and not just the data) they capture from the context. Thus, by using knowledge extracted from the raw data captured by the sensors deployed in the environment, the robot can know where the person is and whether he/she should perform some physical exercise, as well as whether he/she should move a chair away to allow the robot to successfully complete a task. This paper describes the design of an Ambient Assisted Living system where an IoT scheme and robot coexist as independent but connected elements, forming a cyber-physical system-of-systems architecture. The IoT environment includes cameras to monitor the person’s activity and physical position (lying down, sitting…), as well as non-invasive sensors to monitor the person’s heart or breathing rate while lying in bed or sitting in the living room. Although this manuscript focuses on how both systems handle and share the knowledge they possess about the context, a couple of example use cases are included. In the first case, the environment provides the robot with information about the positions of objects in the environment, which allows the robot to augment the metric map it uses to navigate, detecting situations that prevent it from moving to a target. If there is a person nearby, the robot will approach them to ask them to move a chair or open a door. In the second case, even more use is made of the robot’s ability to interact with the person. When the IoT system detects that the person has fallen to the ground, it passes this information to the robot so that it can go to the person, talk to them, and ask for external help if necessary. Full article

Offshore wind power resources in the Red Sea waters of Saudi Arabia are yet to be explored. The objective of the present study is to assess offshore wind power resources at 49 locations in the Saudi waters of the Red Sea and prioritize the sites based on wind characteristics. To accomplish the set objective, long-term hourly mean wind speed (WS) and wind direction (WD) at 100 m above mean sea level, temperature, and pressure data near the surface were used at sites L1-L49 over 43 years from 1979 to 2021. The long-term mean WS and wind power density (WPD) varied between 3.83 m/s and 66.6 W/m², and 6.39 m/s and 280.9 W/m² corresponding to sites L44 and L8. However, higher magnitudes of WS >5 m/s were observed at 34 sites and WPD of > 200 W/m² at 21 sites. In general, WS, WPD, annual energy yield, mean windy site identifier, plant capacity factor, etc. were found to be increasing from east to west and from south to north. Similarly, the mean wind variability index and cost of energy were observed to be decreasing as one moves from east to west and south to north in the Saudi waters of the Red Sea. Full article

Navigation skills are essential for most social and service robotics applications. The robots that are currently in practical use in various complex human environments are generally very limited in their autonomous navigational abilities; while they can reach the proximity of objects, they are not efficient in approaching them closely. The new solution described in this paper presents a system to solve this context-specific navigation problem. The system handles locations with differing contexts based on the use of LiDAR and URF sensors, allowing for the avoidance of people and obstacles with a wide margin, as well as for approaching target objects closely. To quantify the efficiency of our solution we compared it with the ROS contextless standard navigation (move_base) in two different robot platforms and environments, both with real-world tests and simulations. The metrics selected were (1) the time the robot needs to reach an object, (2) the Euclidean distance, and (3) the orientation between the final position of the robot and the defined goal position. We show that our context-specific solution is superior to the standard navigation both in time and Euclidean distance. Full article