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Structural composite materials have gained significant appeal because of their ability to be customized for specific mechanical qualities for various applications, including avionics, wind turbines, transportation, and medical equipment. Therefore, there is a growing demand for effective and non-invasive structural health monitoring (SHM) devices to supervise the integrity of materials. This work introduces a novel sensor design, consisting of three spiral resonators optimized to operate at distinct frequencies and excited by a feeding strip line, capable of performing non-destructive structural strain monitoring via frequency coding. The initial discussion focuses on the analytical modeling of the sensor, which is based on a circuital approach. A numerical test case is developed to operate across the frequency range of 100 to 400 MHz, selected to achieve a balance between penetration depth and the sensitivity of the system. The encouraging findings from electromagnetic full-wave simulations have been confirmed by experimental measurements conducted on printed circuit board (PCB) prototypes embedded in a fiberglass-based composite sample. The sensor shows exceptional sensitivity and cost-effectiveness, and may be easily integrated into composite layers due to its minimal cabling requirements and extremely small profile. The particular frequency-coded configuration enables the suggested sensor to accurately detect and distinguish various structural deformations based on their severity and location. [ABSTRACT FROM AUTHOR]

IntroductionSoft tissue sarcomas (STS) are rare, heterogenous malignancies with an unmet need for novel immunotherapies. Tumor infiltrating lymphocytes (TILs) have been linked with favorable outcomes in STS patients, though the contribution of natural killer (NK) cells and spatial relationships of TILs with MHC-I expressing cells lacks detailed characterization.Experimental designUsing archived and prospectively collected specimens, we evaluated intratumoral NK cells by immunohistochemistry (IHC), flow cytometry, and immunofluorescence (IF). We assessed spatial localization of NK and T cells by multiplex IF, analyzing the effects of MHC-I expression status on NK and T cell clustering.ResultsBoth intratumoral NKp46 and CD56dim expression were associated with significantly improved overall survival (P=0.05), while higher infiltrates of CD56bright NK cells predicted a worse prognosis (P=0.05). The presence of intratumoral NK cells was inversely proportional to CD3+ T cells. Spatial analyses showed NK cells preferentially clustering close to other NK cells with sparse CD3+ T and CD8+ T cells in range (P

A growing number of higher-education institutions are implementing synchronous hybrid delivery, which provides both online and on-campus learners with simultaneous instruction, especially for facilitating discussions in Active Learning (AL) contexts. However, learners face difficulties in picking up social cues and gaining free access to speaking rights due to the geometrical misalignment of individuals mediated through screens. We assume that the cultivation of discussions is allowed by ensuring the spatial localization of learners similar to that in a physical space. This study aims to design a synchronous hybrid learning environment, called Mirror Campus (MC), suitable for the AL scenario that connects physical and cyberspaces by providing spatial localization of learners. We hypothesize that the MC promotes discussion-oriented behaviors, and eventually enhances applied skills for group tasks, related to discussion, creativity, decision-making, and interdependence. We conducted an experiment with five different groups, where four participants in each group were asked to discuss a given topic for fifteen minutes, and clarified that the occurrences of facing behaviors, intervening, and simultaneous utterances in the MC were significantly increased compared to a conventional video conferencing. In conclusion, this study demonstrated the significance of the spatial localization of learners to facilitate discussion-oriented behaviors such as facing and speech. [ABSTRACT FROM AUTHOR]

To mitigate potential risks associated with terminal bud inhibitors on cotton plant growth, ecological environment, and human health during cotton topping operations, a lightweight model by integrating the GhostNetV2 network with an end-side neural network architecture based on the improved YOLOv7-tiny algorithm for cotton terminal bud detection. This approach reduces both the model’s parameter count and reasoning speed while minimizing accuracy loss. Additionally, an end-effector execution scheme and workflow for contactless targeted spraying is proposed using this model. The deployed model on a Jetson TX2 embedded computer achieved a computation load of only 1.0 G with an average accuracy of 98.2%. Moreover, the number of drug droplets attached to the end-effector per square centimeter meets national standards for targeted spraying. The experimental results show that this method is suitable for cotton topping operations.

Structural composite materials have gained significant appeal because of their ability to be customized for specific mechanical qualities for various applications, including avionics, wind turbines, transportation, and medical equipment. Therefore, there is a growing demand for effective and non-invasive structural health monitoring (SHM) devices to supervise the integrity of materials. This work introduces a novel sensor design, consisting of three spiral resonators optimized to operate at distinct frequencies and excited by a feeding strip line, capable of performing non-destructive structural strain monitoring via frequency coding. The initial discussion focuses on the analytical modeling of the sensor, which is based on a circuital approach. A numerical test case is developed to operate across the frequency range of 100 to 400 MHz, selected to achieve a balance between penetration depth and the sensitivity of the system. The encouraging findings from electromagnetic full-wave simulations have been confirmed by experimental measurements conducted on printed circuit board (PCB) prototypes embedded in a fiberglass-based composite sample. The sensor shows exceptional sensitivity and cost-effectiveness, and may be easily integrated into composite layers due to its minimal cabling requirements and extremely small profile. The particular frequency-coded configuration enables the suggested sensor to accurately detect and distinguish various structural deformations based on their severity and location.

Heart rate is a key vital sign that can be used to understand an individual's health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system's accuracy in sensing two users' heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity. [ABSTRACT FROM AUTHOR]

The advancement of spatial interaction technology has greatly enriched the domain of consumer electronics. Traditional solutions based on optical technologies suffers high power consumption and significant costs, making them less ideal in lightweight implementations. In contrast, ultrasonic solutions stand out due to their lower power consumption and cost-effectiveness, capturing widespread attention and interest. This paper addresses the challenges associated with the application of ultrasound sensors in spatial localization. Traditional ultrasound systems are hindered by blind spots, large physical dimensions, and constrained measurement ranges, limiting their practical applicability. To overcome these limitations, this paper proposes a miniature ultrasonic spatial localization module employing piezoelectric micromechanical ultrasonic transducers (PMUTs). The module is comprised of three devices each with dimension of 1.2 mm × 1.2 mm × 0.5 mm, operating at a frequency of around 180 kHz. This configuration facilitates a comprehensive distance detection range of 0–800 mm within 80° directivity, devoid of blind spot. The error rate and failure range of measurement as well as their relationship with the SNR (signal-to-noise ratio) are also thoroughly investigated. This work heralds a significant enhancement in hand spatial localization capabilities, propelling advancements in acoustic sensor applications of the meta-universe. [ABSTRACT FROM AUTHOR]

A head-mounted display could potentially restrict users' visual fields and thereby impair their spatial cognitive ability. Spatial cognition can be assisted with immersive visual guidance. However, whether this technique is useful for individuals with autism-spectrum disorder (ASD) remains unclear. Given the recent virtual reality (VR) contents targeting individuals with ASD, the relationship between ASD-related traits and the effectiveness of immersive visual guidance should be clarified. This pilot study evaluated how ASD-related traits (autistic traits and empathizing-systemizing cognitive styles) among typically developing individuals are related to the effectiveness of visual guidance. Participants performed visual search and spatial localization tasks while using immersive visual guidance. In the visual search task, participants searched immersive VR environments for a target object and pushed a button according to the target color as quickly as possible. In the localization task, they viewed immersive visual guidance for a short duration and localized the guided direction via a controller. Results showed that visual search times were hastened with systemizing cognition. However, ASD-related traits were not significantly related to localization accuracy. These findings suggest that immersive visual guidance is generally useful for individuals with higher ASD-related traits. [ABSTRACT FROM AUTHOR]

Introduction. The study of the history of the appearance of the Belgorod line, its historical significance for the economic development and settlement of a large historical region of the Central Chernozem region and adjacent territories was the focus of many domestic researchers.Materials and methods. With the advent of modern computer technologies, it has become possible to process large arrays of historical sources of various typologies. Results. Based on the information received, you can create various databases, but without proper visualization, the information obtained turns into dry statistics, endless tables, graphs, charts, etc., which is completely unacceptable in the modern digital age. The use of a geographic information system (GIS), that is, a system for collecting, storing, analyzing and graphical visualization of spatial (geographical) data and related information about the necessary objects within the framework of a large historical study, helps scientists to "revive", visualize the evolution of historical -cesses both over a long chronological period and in a wide geographical framework. In fact, GIS is just a tool, a software product that allows you to analyze, edit and create digital maps of the area and additional information about objects in their historical retrospective. mass documentation of the 17th-first half of the 19th centuries. gives a wide layer of various information on the socio-economic development of the region under study.Conclusion. The use of modern research methods and technical capabilities in creating GIS allow a comprehensive look at the historical processes that took place over a large area for several centuries, which allows you to take a fresh look at the history of the Central Chernozem region in the context of its settlement and economic development.

Introduction: Soft tissue sarcomas (STS) are rare, heterogenous malignancies with an unmet need for novel immunotherapies. Tumor infiltrating lymphocytes (TILs) have been linked with favorable outcomes in STS patients, though the contribution of natural killer (NK) cells and spatial relationships of TILs with MHCI expressing cells lacks detailed characterization. Experimental design: Using archived and prospectively collected specimens, we evaluated intratumoral NK cells by immunohistochemistry (IHC), flow cytometry, and immunofluorescence (IF). We assessed spatial localization of NK and T cells by multiplex IF, analyzing the effects of MHC-I expression status on NK and T cell clustering. Results: Both intratumoral NKp46 and CD56dim expression were associated with significantly improved overall survival (P=0.05), while higher infiltrates of CD56bright NK cells predicted a worse prognosis (P=0.05). The presence of intratumoral NK cells was inversely proportional to CD3+ T cells. Spatial analyses showed NK cells preferentially clustering close to other NK cells with sparse CD3+ T and CD8+ T cells in range (P<0.0001). Additionally, CD3+ T and CD8+ T cells showed significantly greater co-localization with MHC-I+ cells, compared to NK cells (P<0.0001). After neoadjuvant radiotherapy, there was greater CD8 clustering, while after neoadjuvant chemotherapy, there was overall lower TIL clustering. Conclusion: Intratumoral NK cells are prognostic in STS and localize closer to MHC-I-cells than T cells. Although both NK and T cells are associated with improved survival in STS, their differential distribution in the TME based on MHC-I expression status may serve as a biomarker for improved immunotherapy treatment selection. [ABSTRACT FROM AUTHOR]

Perceiving the positions of objects is a prerequisite for most other visual and visuomotor functions, but human perception of object position varies from one individual to the next. The source of these individual differences in perceived position and their perceptual consequences are unknown. Here, we tested whether idiosyncratic biases in the underlying representation of visual space propagate across different levels of visual processing. In Experiment 1, using a position matching task, we found stable, observer-specific compressions and expansions within local regions throughout the visual field. We then measured Vernier acuity (Experiment 2) and perceived size of objects (Experiment 3) across the visual field and found that individualized spatial distortions were closely associated with variations in both visual acuity and apparent object size. Our results reveal idiosyncratic biases in perceived position and size, originating from a heterogeneous spatial resolution that carries across the visual hierarchy.

This study presents an innovative, intelligent obstacle avoidance module intended to significantly enhance the collision prevention capabilities of the robotic arm mechanism onboard a high-speed rail tunnel lining inspection train. The proposed module employs a fusion of ORB-SLAM3 and Normal Distribution Transform (NDT) point cloud registration techniques to achieve real-time point cloud densification, ensuring reliable detection of small-volume targets. By leveraging spatial filtering, cluster computation, and feature extraction, precise obstacle localization information is further obtained. A fusion of multi-modal data is achieved by jointly calibrating 3D LiDAR and camera images. Upon validation through field testing, it is demonstrated that the module can effectively detect obstacles with a minimum diameter of 0.5 cm, with an average deviation controlled within a 1–2 cm range and a safety margin of 3 cm, effectively preventing collisions. Compared to traditional obstacle avoidance sensors, this module provides information across more dimensions, offering robust support for the construction of powerful automated tunnel inspection control systems and digital twin lifecycle analysis techniques for railway tunnels. [ABSTRACT FROM AUTHOR]

A growing number of higher-education institutions are implementing synchronous hybrid delivery, which provides both online and on-campus learners with simultaneous instruction, especially for facilitating discussions in Active Learning (AL) contexts. However, learners face difficulties in picking up social cues and gaining free access to speaking rights due to the geometrical misalignment of individuals mediated through screens. We assume that the cultivation of discussions is allowed by ensuring the spatial localization of learners similar to that in a physical space. This study aims to design a synchronous hybrid learning environment, called Mirror Campus (MC), suitable for the AL scenario that connects physical and cyberspaces by providing spatial localization of learners. We hypothesize that the MC promotes discussion-oriented behaviors, and eventually enhances applied skills for group tasks, related to discussion, creativity, decision-making, and interdependence. We conducted an experiment with five different groups, where four participants in each group were asked to discuss a given topic for fifteen minutes, and clarified that the occurrences of facing behaviors, intervening, and simultaneous utterances in the MC were significantly increased compared to a conventional video conferencing. In conclusion, this study demonstrated the significance of the spatial localization of learners to facilitate discussion-oriented behaviors such as facing and speech.

IntroductionSoft tissue sarcomas (STS) are rare, heterogenous malignancies with an unmet need for novel immunotherapies. Tumor infiltrating lymphocytes (TILs) have been linked with favorable outcomes in STS patients, though the contribution of natural killer (NK) cells and spatial relationships of TILs with MHC-I expressing cells lacks detailed characterization.Experimental designUsing archived and prospectively collected specimens, we evaluated intratumoral NK cells by immunohistochemistry (IHC), flow cytometry, and immunofluorescence (IF). We assessed spatial localization of NK and T cells by multiplex IF, analyzing the effects of MHC-I expression status on NK and T cell clustering.ResultsBoth intratumoral NKp46 and CD56dim expression were associated with significantly improved overall survival (P=0.05), while higher infiltrates of CD56bright NK cells predicted a worse prognosis (P=0.05). The presence of intratumoral NK cells was inversely proportional to CD3+ T cells. Spatial analyses showed NK cells preferentially clustering close to other NK cells with sparse CD3+ T and CD8+ T cells in range (P

Motion is influenced by many different aspects of a micromotor's design, such as shape, roughness and the type of materials used. When designing a motor, asymmetry is the main requirement to take into account, either in shape or in catalyst distribution. It influences both speed and directionality since it dictates the location of propulsion force. Here, we combine asymmetry in shape and asymmetry in catalyst distribution to study the motion of soft micromotors. A microfluidic method is utilized to generate aqueous double emulsions, which upon UV-exposure form asymmetric microgels. Taking advantage of the flexibility of this method, we fabricated micromotors with homogeneous catalyst distribution throughout the microbead and micromotors with different degrees of catalyst localization within the active site. Spatial control over catalyst positioning is advantageous since less enzyme is needed for the same propulsion speed as the homogeneous system and it provides further confinement and compartmentalization of the catalyst. This proof-of-concept of our new design will make the use of enzymes as driving forces for motors more accessible, as well as providing a new route for compartmentalizing enzymes at interfaces without the need for catalyst-specific functionalization. [ABSTRACT FROM AUTHOR]

Heart rate is a key vital sign that can be used to understand an individual’s health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system’s accuracy in sensing two users’ heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity.

The advancement of spatial interaction technology has greatly enriched the domain of consumer electronics. Traditional solutions based on optical technologies suffers high power consumption and significant costs, making them less ideal in lightweight implementations. In contrast, ultrasonic solutions stand out due to their lower power consumption and cost-effectiveness, capturing widespread attention and interest. This paper addresses the challenges associated with the application of ultrasound sensors in spatial localization. Traditional ultrasound systems are hindered by blind spots, large physical dimensions, and constrained measurement ranges, limiting their practical applicability. To overcome these limitations, this paper proposes a miniature ultrasonic spatial localization module employing piezoelectric micromechanical ultrasonic transducers (PMUTs). The module is comprised of three devices each with dimension of 1.2 mm × 1.2 mm × 0.5 mm, operating at a frequency of around 180 kHz. This configuration facilitates a comprehensive distance detection range of 0–800 mm within 80° directivity, devoid of blind spot. The error rate and failure range of measurement as well as their relationship with the SNR (signal-to-noise ratio) are also thoroughly investigated. This work heralds a significant enhancement in hand spatial localization capabilities, propelling advancements in acoustic sensor applications of the meta-universe.

There is undoubtedly a spatial component to our experience of gustatory stimulus qualities such as sweet, bitter, salty, sour, and umami, however its importance is currently unknown. Taste thresholds have been shown to differ at different locations within the oral cavity where gustatory receptors are found. However, the relationship between the stimulation of particular taste receptors and the subjective spatially-localized experience of taste qualities is uncertain. Although the existence of the so-called ‘tongue map’ has long been discredited, the psychophysical evidence clearly demonstrates significant (albeit small) differences in taste sensitivity across the tongue, soft palate, and pharynx (all sites where taste buds have been documented). Biases in the perceived localization of gustatory stimuli have also been reported, often resulting from tactile capture (i.e., a form of crossmodal, or multisensory, interaction). At the same time, varying responses to supratheshold tastants along the tongue's anterior-posterior axis have putatively been linked to the ingestion-ejection response. This narrative review highlights what is currently known concerning the spatial aspects of gustatory perception, considers how such findings might be explained, given the suggested balanced distribution of taste receptors for each basic taste quality where taste papillae are present, and suggests why knowing about such differences may be important.

We study the effect of structural disorder on the transition from the bound states in the continuum (BICs) to quasi-BICs by the example of the periodic photonic structure composed of two layers of parallel dielectric rods. We uncover the specificity in the robustness of the symmetry-protected and accidental BICs against various types of structural disorder. We analyze how the spatial mode localization induced by the structural disorder results in an effective reduction of the system length and limits the Q factor of quasi-BICs. Our results are essential for the practical implementation of BICs especially in natural and self-assembled photonic structures, where the structural disorder plays a crucial role.

This study presents an innovative, intelligent obstacle avoidance module intended to significantly enhance the collision prevention capabilities of the robotic arm mechanism onboard a high-speed rail tunnel lining inspection train. The proposed module employs a fusion of ORB-SLAM3 and Normal Distribution Transform (NDT) point cloud registration techniques to achieve real-time point cloud densification, ensuring reliable detection of small-volume targets. By leveraging spatial filtering, cluster computation, and feature extraction, precise obstacle localization information is further obtained. A fusion of multi-modal data is achieved by jointly calibrating 3D LiDAR and camera images. Upon validation through field testing, it is demonstrated that the module can effectively detect obstacles with a minimum diameter of 0.5 cm, with an average deviation controlled within a 1–2 cm range and a safety margin of 3 cm, effectively preventing collisions. Compared to traditional obstacle avoidance sensors, this module provides information across more dimensions, offering robust support for the construction of powerful automated tunnel inspection control systems and digital twin lifecycle analysis techniques for railway tunnels.

The modular organization of a cell which can be determined by its interaction network allows us to understand a mesh of cooperation among the functional modules. Therefore, cellular-level identification of functional modules aids in understanding the functional and structural characteristics of the biological network of a cell and also assists in determining or comprehending the evolutionary signal. We develop ProMoCell that performs real-time Web scraping for generating clusters of the cellular level functional units of an organism. ProMoCell constructs the Protein Locality Graphs and clusters the cellular level functional units of an organism by utilizing experimentally verified data from various online sources. Also, we develop ProModb, a database service that houses precomputed whole-cell protein-protein interaction network-based functional modules of an organism using ProMoCell. Our Web service is entirely synchronized with the KEGG pathway database and allows users to generate spatially localized protein modules for any organism belonging to the KEGG genome using its real-time Web scraping characteristics. Hence, the server will host as many organisms as is maintained by the KEGG database. Our Web services provide the users a comprehensive and integrated tool for an efficient browsing and extraction of the spatial locality-based protein locality graph and the functional modules constructed by gathering experimental data from several interaction databases and pathway maps. We believe that our Web services will be beneficial in pharmacological research, where a novel research domain called modular pharmacology has initiated the study on the diagnosis, prevention, and treatment of deadly diseases using functional modules. [ABSTRACT FROM AUTHOR]

Visual and auditory localization abilities are crucial in real-life tasks such as navigation and social interaction. Aging is frequently accompanied by vision and hearing loss, affecting spatial localization. The purpose of the current study is to elucidate the effect of typical aging on spatial localization and to establish a baseline for older individuals with pathological sensory impairment. Using a verbal report paradigm, we investigated how typical aging affects visual and auditory localization performance, the reliance on vision during sound localization, and sensory integration strategies when localizing audiovisual targets. Fifteen younger adults (N = 15, mean age = 26 years) and thirteen older adults (N = 13, mean age = 68 years) participated in this study, all with age-adjusted normal vision and hearing based on clinical standards. There were significant localization differences between younger and older adults, with the older group missing peripheral visual stimuli at significantly higher rates, localizing central stimuli as more peripheral, and being less precise in localizing sounds from central locations when compared to younger subjects. Both groups localized auditory targets better when the test space was visible compared to auditory localization when blindfolded. The two groups also exhibited similar patterns of audiovisual integration, showing optimal integration in central locations that was consistent with a Maximum-Likelihood Estimation model, but non-optimal integration in peripheral locations. These findings suggest that, despite the age-related changes in auditory and visual localization, the interactions between vision and hearing are largely preserved in older individuals without pathological sensory impairments. [ABSTRACT FROM AUTHOR]

Forest fires have the characteristics of strong unpredictability and extreme destruction. Hence, it is difficult to carry out effective prevention and control. Once the fire spreads, devastating damage will be caused to natural resources and the ecological environment. In order to detect early forest fires in real-time and provide firefighting assistance, we propose a vision-based detection and spatial localization scheme and develop a system carried on the unmanned aerial vehicle (UAV) with an OAK-D camera. During the high incidence of forest fires, UAVs equipped with our system are deployed to patrol the forest. Our scheme includes two key aspects. First, the lightweight model, NanoDet, is applied as a detector to identify and locate fires in the vision field. Techniques such as the cosine learning rate strategy and data augmentations are employed to further enhance mean average precision (mAP). After capturing 2D images with fires from the detector, the binocular stereo vision is applied to calculate the depth map, where the HSV-Mask filter and non-zero mean method are proposed to eliminate the interference values when calculating the depth of the fire area. Second, to get the latitude, longitude, and altitude (LLA) coordinates of the fire area, coordinate frame conversion is used along with data from the GPS module and inertial measurement unit (IMU) module. As a result, we experiment with simulated fire in a forest area to test the effectiveness of this system. The results show that 89.34% of the suspicious frames with flame targets are detected and the localization error of latitude and longitude is in the order of 10−5 degrees; this demonstrates that the system meets our precision requirements and is sufficient for forest fire inspection. [ABSTRACT FROM AUTHOR]

Visual and auditory localization abilities are crucial in real-life tasks such as navigation and social interaction. Aging is frequently accompanied by vision and hearing loss, affecting spatial localization. The purpose of the current study is to elucidate the effect of typical aging on spatial localization and to establish a baseline for older individuals with pathological sensory impairment. Using a verbal report paradigm, we investigated how typical aging affects visual and auditory localization performance, the reliance on vision during sound localization, and sensory integration strategies when localizing audiovisual targets. Fifteen younger adults (N = 15, mean age = 26 years) and thirteen older adults (N = 13, mean age = 68 years) participated in this study, all with age-adjusted normal vision and hearing based on clinical standards. There were significant localization differences between younger and older adults, with the older group missing peripheral visual stimuli at significantly higher rates, localizing central stimuli as more peripheral, and being less precise in localizing sounds from central locations when compared to younger subjects. Both groups localized auditory targets better when the test space was visible compared to auditory localization when blindfolded. The two groups also exhibited similar patterns of audiovisual integration, showing optimal integration in central locations that was consistent with a Maximum-Likelihood Estimation model, but non-optimal integration in peripheral locations. These findings suggest that, despite the age-related changes in auditory and visual localization, the interactions between vision and hearing are largely preserved in older individuals without pathological sensory impairments.

Motion is influenced by many different aspects of a micromotor’s design, such as shape, roughness and the type of materials used. When designing a motor, asymmetry is the main requirement to take into account, either in shape or in catalyst distribution. It influences both speed and directionality since it dictates the location of propulsion force. Here, we combine asymmetry in shape and asymmetry in catalyst distribution to study the motion of soft micromotors. A microfluidic method is utilized to generate aqueous double emulsions, which upon UV-exposure form asymmetric microgels. Taking advantage of the flexibility of this method, we fabricated micromotors with homogeneous catalyst distribution throughout the microbead and micromotors with different degrees of catalyst localization within the active site. Spatial control over catalyst positioning is advantageous since less enzyme is needed for the same propulsion speed as the homogeneous system and it provides further confinement and compartmentalization of the catalyst. This proof-of-concept of our new design will make the use of enzymes as driving forces for motors more accessible, as well as providing a new route for compartmentalizing enzymes at interfaces without the need for catalyst-specific functionalization.

Similar to most visual animals, the crab Neohelice granulata relies predominantly on visual information to escape from predators, to track prey and for selecting mates. It, therefore, needs specialized neurons to process visual information and determine the spatial location of looming objects. In the crab Neohelice granulata, the Monostratified Lobula Giant type1 (MLG1) neurons have been found to manifest looming sensitivity with finely tuned capabilities of encoding spatial location information. MLG1s neuronal ensemble can not only perceive the location of a looming stimulus, but are also thought to be able to influence the direction of movement continuously, for example, escaping from a threatening, looming target in relation to its position. Such specific characteristics make the MLG1s unique compared to normal looming detection neurons in invertebrates which can not localize spatial looming. Modeling the MLG1s ensemble is not only critical for elucidating the mechanisms underlying the functionality of such neural circuits, but also important for developing new autonomous, efficient, directionally reactive collision avoidance systems for robots and vehicles. However, little computational modeling has been done for implementing looming spatial localization analogous to the specific functionality of MLG1s ensemble. To bridge this gap, we propose a model of MLG1s and their pre-synaptic visual neural network to detect the spatial location of looming objects. The model consists of 16 homogeneous sectors arranged in a circular field inspired by the natural arrangement of 16 MLG1s' receptive fields to encode and convey spatial information concerning looming objects with dynamic expanding edges in different locations of the visual field. Responses of the proposed model to systematic real-world visual stimuli match many of the biological characteristics of MLG1 neurons. The systematic experiments demonstrate that our proposed MLG1s model works effectively and robustly to perceive and localize looming information, which could be a promising candidate for intelligent machines interacting within dynamic environments free of collision. This study also sheds light upon a new type of neuromorphic visual sensor strategy that can extract looming objects with locational information in a quick and reliable manner.

Similar to most visual animals, the crab Neohelice granulata relies predominantly on visual information to escape from predators, to track prey and for selecting mates. It, therefore, needs specialized neurons to process visual information and determine the spatial location of looming objects. In the crab Neohelice granulata , the Monostratified Lobula Giant type1 (MLG1) neurons have been found to manifest looming sensitivity with finely tuned capabilities of encoding spatial location information. MLG1s neuronal ensemble can not only perceive the location of a looming stimulus, but are also thought to be able to influence the direction of movement continuously, for example, escaping from a threatening, looming target in relation to its position. Such specific characteristics make the MLG1s unique compared to normal looming detection neurons in invertebrates which can not localize spatial looming. Modeling the MLG1s ensemble is not only critical for elucidating the mechanisms underlying the functionality of such neural circuits, but also important for developing new autonomous, efficient, directionally reactive collision avoidance systems for robots and vehicles. However, little computational modeling has been done for implementing looming spatial localization analogous to the specific functionality of MLG1s ensemble. To bridge this gap, we propose a model of MLG1s and their pre-synaptic visual neural network to detect the spatial location of looming objects. The model consists of 16 homogeneous sectors arranged in a circular field inspired by the natural arrangement of 16 MLG1s' receptive fields to encode and convey spatial information concerning looming objects with dynamic expanding edges in different locations of the visual field. Responses of the proposed model to systematic real-world visual stimuli match many of the biological characteristics of MLG1 neurons. The systematic experiments demonstrate that our proposed MLG1s model works effectively and robustly to perceive and localize looming information, which could be a promising candidate for intelligent machines interacting within dynamic environments free of collision. This study also sheds light upon a new type of neuromorphic visual sensor strategy that can extract looming objects with locational information in a quick and reliable manner. [ABSTRACT FROM AUTHOR]

Background and Aim: Age related changes in cognitive functioning have been shown to vary depending on the task used. Thus, the study aimed to compare the responses of young and older adults to an auditory Stroop test that assessed spatial (responses to location of the stimuli) and semantic (responses to meaning of the stimuli) localization. Methods: The “Auditory spatial and semantic localization Stroop test”, developed as a part of the study was administered on 30 young adults aged 18 to 30 years and 30 older adults aged 58 to 70 years having normal hearing. The response accuracy and reaction time of the participants were determined for the words “right”, “left”, “front”, and “back.” Results: The older adults had significantly poorer response accuracy and reaction time than the young adults for both spatial and semantic localization tasks. Within each participant group, semantic localization had better response accuracy than spatial localization, while such differences in reaction time were found only in the older adults. In both groups, a congruency effect was seen for spatial but not for semantic localization when response accuracy was calculated, whereas it was observed only for semantic and not for spatial localization when reaction time was measured. Conclusion: The auditory Stroop test, which measures stimulus interference and cognitive skills, could be used as a simple tool to assess the same for stimuli presented through the auditory modality. This would be especially helpful in older adults who may demonstrate cognitive decline with ageing to auditory stimuli. [ABSTRACT FROM AUTHOR]

Summary: The hepatitis B virus (HBV) infects 257 million people worldwide. HBV infection requires establishment and persistence of covalently closed circular (ccc) DNA, a viral episome, in nucleus. Here, we study cccDNA spatial localization in the 3D host genome by using chromosome conformation capture-based sequencing analysis and fluorescence in situ hybridization (FISH). We show that transcriptionally inactive cccDNA is not randomly distributed in host nucleus. Rather, it is preferentially accumulated at specialized areas, including regions close to chromosome 19 (chr.19). Activation of the cccDNA is apparently associated with its re-localization, from a pre-established heterochromatin hub formed by 5 regions of chr.19 to transcriptionally active regions formed by chr.19 and nearby chromosomes including chr.16, 17, 20, and 22. This active versus inactive positioning at discrete regions of the host genome is primarily controlled by the viral HBx protein and by host factors including the structural maintenance of chromosomes protein 5/6 (SMC5/6) complex.

We describe multiscale geometrical changes via structured deformations (g , G) and the non-local energetic response at a point x via a function Ψ of the weighted averages of the jumps [ u n ] (y) of microlevel deformations u n at points y within a distance r of x. The deformations u n are chosen so that lim n → ∞ u n = g and lim n → ∞ ∇ u n = G. We provide conditions on Ψ under which the upscaling " n → ∞ " results in a macroscale energy that depends through Ψ on (1) the jumps [ g ] of g and the "disarrangement field" ∇ g − G , (2) the "horizon" r, and (3) the weighting function α r for microlevel averaging of [ u n ] (y). We also study the upscaling " n → ∞ " followed by spatial localization " r → 0 " and show that this succession of processes results in a purely local macroscale energy I (g , G) that depends through Ψ upon the jumps [ g ] of g and the "disarrangement field" ∇ g − G alone. In special settings, such macroscale energies I (g , G) have been shown to support the phenomena of yielding and hysteresis, and our results provide a broader setting for studying such yielding and hysteresis. As an illustration, we apply our results in the context of the plasticity of single crystals. [ABSTRACT FROM AUTHOR]

Recent research investigating the principles governing human perception has provided increasing evidence for probabilistic inference in human perception. For example, human auditory and visual localization judgments closely resemble that of a Bayesian causal inference observer, where the underlying causal structure of the stimuli are inferred based on both the available sensory evidence and prior knowledge. However, most previous studies have focused on characterization of perceptual inference within a static environment, and therefore, little is known about how this inference process changes when observers are exposed to a new environment. In this study we aimed to computationally characterize the change in auditory spatial perception induced by repeated auditory-visual spatial conflict, known as the ventriloquist aftereffect. In theory, this change could reflect a shift in the auditory sensory representations (i.e., shift in auditory likelihood distribution), a decrease in the precision of the auditory estimates (i.e., increase in spread of likelihood distribution), a shift in the auditory bias (i.e., shift in prior distribution), or an increase/decrease in strength of the auditory bias (i.e., the spread of prior distribution), or a combination of these. By quantitatively estimating the parameters of the perceptual process for each individual observer using a Bayesian causal inference model, we found that the shift in the perceived locations after exposure was associated with a shift in the mean of the auditory likelihood functions in the direction of the experienced visual offset. The results suggest that repeated exposure to a fixed auditory-visual discrepancy is attributed by the nervous system to sensory representation error and as a result, the sensory map of space is recalibrated to correct the error.

Perceiving the positions of objects is a prerequisite for most other visual and visuomotor functions, but human perception of object position varies from one individual to the next. The source of these individual differences in perceived position and their perceptual consequences are unknown. Here, we tested whether idiosyncratic biases in the underlying representation of visual space propagate across different levels of visual processing. In Experiment 1, using a position matching task, we found stable, observer-specific compressions and expansions within local regions throughout the visual field. We then measured Vernier acuity (Experiment 2) and perceived size of objects (Experiment 3) across the visual field and found that individualized spatial distortions were closely associated with variations in both visual acuity and apparent object size. Our results reveal idiosyncratic biases in perceived position and size, originating from a heterogeneous spatial resolution that carries across the visual hierarchy. [ABSTRACT FROM AUTHOR]

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology. Image 1 • A MATLAB-based image analysis pipeline that subgroups cells in tissues according to volumetric, morphological features. • Complements tissue analysis from 3D microscopy data in addition to traditional fluorescent biomarker-based information. • Allows visualization of the spatial location of selected subgroups or individual cells within the original tissue image. • User-friendliness of the tool aims to reach broad usership and to meet modern needs for single cell level data acquisition. • Step by step instructions provided for users with limited computational skills. [ABSTRACT FROM AUTHOR]

The article analysed and systematized the theory and the paradigm of regional development. Opportunities for the optimum development of the regional economy in Ukraine are identified because the functioning of the market system is accompanied by crisis phenomena and requires deep scientific study of the contemporary economic theory and practice of going out of the crisis using the latest concepts of region development. Polarized space concept in the economy of the regions of Ukraine with the identifying of measures for its implementation is an important and insufficiently developed scientific research. The result of the transformation of economic transitions in the national economy is the dominance of so-called “point development”. Despite the positive effect of the presence of the growth poles in a separate area, this situation reinforces the asymmetry in economic development in comparison with the other regions. A result of this is the differentiation of the main economic and social indicators of regional economic development. In this regard, the study of regional concepts and theories of regional economic development is urgent theoretical and practical task, because the lack of a unified approach to the foundations of the theory of economic space, and especially its regional component, does not allow to start solving some of the practical issues of systematic formation of common economic space of the country. These issues raise many questions of applied character, which economic theory may not always give a definite answer. Such questions are certainly of theoretical interest but, most importantly, their answers can contribute to the formation of an effective competitive economy in the region. The object of the study is the regions of Ukraine, with their resource potential and absence of a polarized space. The main objective is the formation on this basis of anti-crisis measures of region development. The subject of research is theoretical principles and methodology of formation of a polarized space with the low quality of economic space. The methodological base of this research is the dialectical method of cognition, systemic approach, fundamental provisions of economic theory and the theory of the polarized space. The following research methods are applied: logical generalization, systemic and structural analysis, comparison, statistical, expert, etc. The aim is to study the imperatives for the effective development of the locally-spatial system, taking into account its resource potential, determination of possible ways of its implementation with the aim of regional economic space development and ensuring strategic guidelines and goals for socio-economic development. The obtained results gave a possibility to determine necessary methodological bases of the improvement of regional development, to focus on the most influential directions in the theory of the economic development of a region, to substantiate the conceptualization of an optimal model of economic development of the region.

CX3CR1 + cells play a crucial role in liver fibrosis progression. However, changes in the migratory behavior and spatial distribution of spleen-derived and hepatic CX3CR1 + cells in the fibrotic liver as well as their influence on the liver fibrosis remain unclear., Methods: The CX3CR1 GFP/+ transgenic mice and CX3CR1-KikGR transgenic mice were used to establish the CCl4-induced liver fibrosis model. Splenectomy, adoptive transfusion of splenocytes, in vivo photoconversion of splenic CX3CR1 + cells and intravital imaging were performed to study the spatial distribution, migration and movement behavior, and regulatory function of CX3CR1 + cells in liver fibrosis., Results: Intravital imaging revealed that the CX3CR1 GFP cells accumulated into the fibrotic liver and tended to accumulate towards the central vein (CV) in the hepatic lobules. Two subtypes of hepatic CX3CR1 + cells existed in the fibrotic liver. The first subtype was the interacting CX3CR1 GFP cells, most of which were observed to distribute in the liver parenchyma and had a higher process velocity; the second subtype was mobile CX3CR1 GFP cells, most of which were present in the hepatic vessels with a faster moving speed. Splenectomy ameliorated liver fibrosis and decreased the number of CX3CR1 + cells in the fibrotic liver. Moreover, splenectomy rearranged CX3CR1 GFP cells to the boundary of the hepatic lobule, reduced the process velocity of interacting CX3CR1 GFP cells and decreased the number and mobility of mobile CX3CR1 GFP cells in the fibrotic liver. Transfusion of spleen-derived classical monocytes increased the process velocity and mobility of hepatic endogenous CX3CR1 GFP cells and facilitated liver fibrosis progression via the production of proinflammatory and profibrotic cytokines. The photoconverted splenic CX3CR1 + KikRed + cells were observed to leave the spleen, accumulate into the fibrotic liver and contact with hepatic CX3CR1 + KikGreen + cells during hepatic fibrosis., Conclusion: The splenic CX3CR1 + monocytes with classical phenotype migrated from the spleen to the fibrotic liver, modifying the migratory behavior of hepatic endogenous CX3CR1 GFP cells and exacerbating liver fibrosis via the secretion of cytokines. This study reveals that splenic CX3CR1 + classical monocytes are a key driver of liver fibrosis via the spleen-liver axis and may be potential candidate targets for the treatment of chronic liver fibrosis., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The purpose of the study is to develop a learning system for internal representation of the events localization space to realize orientation and navigation of autonomous mobile systems. The task of the research is the development of simulation models of the semantics of the event localization space based on multi-agent neurocognitive architectures. The paper proves that the multi-agent neurocognitive architecture is an effective formalism for describing the semantics of the spatial localization of events. Main theoretical foundations have been developed for the simulation of spatial relations using the so-called multi-agent facts, consisting of software agents-concepts, reflecting semantic categories corresponding to parts of speech. It is shown that locative software agents that describe the spatial location of objects and events, forming homogeneous connections, compose the so-called field locations. The latter describes a holistic view of the intellectual agent about the environment. The paper defines conceptual foundations of multi-agent modeling of the semantics of subjective reflexive mapping of the interaction between real objects, space and time. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have become important tools for power transmission line inspection. Cameras installed on the platforms can efficiently obtain aerial images containing information about power equipment. However, most of the existing inspection systems cannot perform automatic real-time detection of transmission line components. In this paper, an automatic transmission line inspection system incorporating UAV remote sensing with binocular visual perception technology is developed to accurately detect and locate power equipment in real time. The system consists of a UAV module, embedded industrial computer, binocular visual perception module, and control and observation module. Insulators, which are key components in power transmission lines as well as fault-prone components, are selected as the detection targets. Insulator detection and spatial localization in aerial images with cluttered backgrounds are interesting but challenging tasks for an automatic transmission line inspection system. A two-stage strategy is proposed to achieve precise identification of insulators. First, candidate insulator regions are obtained based on RGB-D saliency detection. Then, the skeleton structure of candidate insulator regions is extracted. We implement a structure search to realize the final accurate detection of insulators. On the basis of insulator detection results, we further propose a real-time object spatial localization method that combines binocular stereo vision and a global positioning system (GPS). The longitude, latitude, and height of insulators are obtained through coordinate conversion based on the UAV’s real-time flight data and equipment parameters. Experiment results in the actual inspection environment (220 kV power transmission line) show that the presented system meets the requirement of robustness and accuracy of insulator detection and spatial localization in practical engineering.

During the last decade, intracellular actin waves have attracted much attention due to their essential role in various cellular functions, ranging from motility to cytokinesis. Experimental methods have advanced significantly and can capture the dynamics of actin waves over a large range of spatio-temporal scales. However, the corresponding coarse-grained theory mostly avoids the full complexity of this multi-scale phenomenon. In this perspective, we focus on a minimal continuum model of activator–inhibitor type and highlight the qualitative role of mass conservation, which is typically overlooked. Specifically, our interest is to connect between the mathematical mechanisms of pattern formation in the presence of a large-scale mode, due to mass conservation, and distinct behaviors of actin waves.

The advancement of spatial interaction technology has greatly enriched the domain of consumer electronics. Traditional solutions based on optical technologies suffers high power consumption and significant costs, making them less ideal in lightweight implementations. In contrast, ultrasonic solutions stand out due to their lower power consumption and cost-effectiveness, capturing widespread attention and interest. This paper addresses the challenges associated with the application of ultrasound sensors in spatial localization. Traditional ultrasound systems are hindered by blind spots, large physical dimensions, and constrained measurement ranges, limiting their practical applicability. To overcome these limitations, this paper proposes a miniature ultrasonic spatial localization module employing piezoelectric micromechanical ultrasonic transducers (PMUTs). The module is comprised of three devices each with dimension of 1.2 mm × 1.2 mm × 0.5 mm, operating at a frequency of around 180 kHz. This configuration facilitates a comprehensive distance detection range of 0-800 mm within 80° directivity, devoid of blind spot. The error rate and failure range of measurement as well as their relationship with the SNR (signal-to-noise ratio) are also thoroughly investigated. This work heralds a significant enhancement in hand spatial localization capabilities, propelling advancements in acoustic sensor applications of the meta-universe.

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