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Cities are the places where the greatest technological changes will take place during the next few decades. Some years from now, important investments will be destined towards elaborating and implementing urban solutions. However, people with sensorial disabilities will still have to overcome the problem of autonomy in urban areas. Autonomy presumes the existence of the right conditions for complete relocation towards the desired destination. This is closely related to the process of planning buildings, sidewalks and signaling, among others and it is supported by legal measures, promoting accessibility. However, several barriers and the lack of information in urban areas should be faced meanwhile. In this paper, the features of a travel aid previously designed, were enhanced based on the Internet of Things—IoT. This approach has a goal to better suit the device to the smart cities’ context. To this end, an architecture combining both haptic feedback (tactile and auditory), acquiring relevant information from the environment, was designed. Quantitative and quantitative assessments obtained from experimental tests shows satisfactory results.

This paper presents a comprehensive approach to evaluating the ability of multi-legged robots to traverse confined and geometrically complex unstructured environments. The proposed approach utilizes advanced point cloud processing techniques integrating voxel-filtered cloud, boundary and mesh generation, and dynamic traversability analysis to enhance the robot’s terrain perception and navigation. The proposed framework was validated through rigorous simulation and experimental testing with humanoid robots, showcasing the potential of the proposed approach for use in applications/environments characterized by complex environmental features (navigation inside collapsed buildings). The results demonstrate that the proposed framework provides the robot with an enhanced capability to perceive and interpret its environment and adapt to dynamic environment changes. This paper contributes to the advancement of robotic navigation and path-planning systems by providing a scalable and efficient framework for environment analysis. The integration of various point cloud processing techniques into a single architecture not only improves computational efficiency but also enhances the robot’s interaction with its environment, making it more capable of operating in complex, hazardous, unstructured settings.

Falls have a global impact, affecting people worldwide, with a notably high occurrence among the elderly. This study employs machine learning techniques to analyze falls and simulate Activities of Daily Living (ADL). The objective is to predict human falls by leveraging signals from accelerometers and gyroscopes as wearable sensors. By deriving statistical features such as mean, standard deviation, and range the authors successfully trained and assessed six machine learning models allowing them to compare solutions based on both wrist and waist data. The combination of these characteristics and sensors resulted in the Random Forest waist model achieving the most favorable metrics, with an accuracy rate of 97.22% in a 5‐s window. Falls are a widespread issue affecting people worldwide, regardless of their social status. This study presents various ML models, which can predict human falls using signals of a wearable sensor located on the wrist or the waist. The combination of these characteristics and sensors resulted in the RF waist model achieving the most favorable metrics, achieving an accuracy rate of 97.22%.

Visual space perception has been a topic of sustained research since the nineteenth century. Much of this research into the geometry of visual space, however, required observers to make judgments about spatial relationships between isolated points in total darkness. While a sizeable number of previous investigations have now explored visual space perception in outdoor natural environments, nearly all of the previous investigations evaluating the curvature of visual space have utilized only small numbers of observers. In the current experiment, a large number (30) of observers adjusted triangular configurations of markers in an outdoor field until they appeared either as equilateral or right triangles in depth. There was a wide range of outcomes, such that the observers’ judgments were consistent with elliptic, Euclidean, and hyperbolic geometry. There is thus no single consistent relationship between physical space and perceived space. Furthermore, the geometry of visual space frequently changes as the size of spatial configurations is varied—for many observers, judgments for small configurations are consistent with elliptic or Euclidean geometry while judgments for large configurations are frequently consistent with hyperbolic geometry.

Perceptual grouping by common fate has been studied for more than one hundred years: visible stimulus elements that move together (e.g., with the same speed and direction) are perceptually grouped into a single entity distinct from its background. Yet other forms of common fate also exist. In the current study we evaluated the potential informativeness of common appearance and disappearance. In common appearance, a textured object that was not present in an initial view (which contained a textured background identical in nature to that of the object) suddenly appeared in a second view. In common disappearance, a textured object that was perfectly camouflaged in the initial view disappeared in a second view (revealing background texture that had previously been occluded). In both events in the current experiment, the rectangular object was not visible in either the first or second image -- nevertheless, the common appearance or disappearance of stimulus texture elements permitted the perception of object shape. Thirty younger and older adults effectively discriminated shape (horizontal versus vertical rectangles) defined by common appearance and disappearance. The duration of an interstimulus interval and age significantly modulated the visibility of stimulus objects defined by common appearance and disappearance.

Pharmaceuticals and personal care products are being increasingly reported in a variety of biological matrices, including fish tissue; however, screening studies have presently not encompassed broad geographical areas. A national pilot study was initiated in the United States to assess the accumulation of pharmaceuticals and personal care products in fish sampled from five effluent-dominated rivers that receive direct discharge from wastewater treatment facilities in Chicago, Illinois; Dallas, Texas; Orlando, Florida; Phoenix, Arizona; and West Chester, Pennsylvania, USA. Fish were also collected from the Gila River, New Mexico, USA, as a reference condition expected to be minimally impacted by anthropogenic influence. High performance liquid chromatography-tandem mass spectrometry analysis of pharmaceuticals revealed the presence of norfluoxetine, sertraline, diphenhydramine, diltiazem, and carbamazepine at nanogram-per-gram concentrations in fillet composites from effluent-dominated sampling locations; the additional presence of fluoxetine and gemfibrozil was confirmed in liver tissue. Sertraline was detected at concentrations as high as 19 and 545 ng/g in fillet and liver tissue, respectively. Gas chromatography-tandem mass spectrometry analysis of personal care products in fillet composites revealed the presence of galaxolide and tonalide at maximum concentrations of 2,100 and 290 ng/g, respectively, and trace levels of triclosan. In general, more pharmaceuticals were detected at higher concentrations and with greater frequency in liver than in fillet tissues. Higher lipid content in liver tissue could not account for this discrepancy as no significant positive correlations were found between accumulated pharmaceutical concentrations and lipid content for either tissue type from any sampling site. In contrast, accumulation of the personal care products galaxolide and tonalide was significantly related to lipid content. Results suggest that the detection of pharmaceuticals and personal care products was dependent on the degree of wastewater treatment employed.

Low‐cost air pollutant sensors suffer several interferences due to the variation of climatic elements. Recent studies look for calibration solutions based on different regression and classification machine learning algorithms. The present work brings together the implementation and extraction of performance metrics from these algorithms in a single open‐source tool. Both the input data and parameters for each algorithm are automatically configured. This feature makes the tool compatible with any input dataset and removes the need to interact with complex codes. In this paper the structure of an open‐source tool is introduced for evaluation of calibration techniques used in low‐cost air pollutant monitors. Different algorithms can be configured and used, such as regression techniques and machine learning classifiers. In addition, this tool was implemented to be compatible with any input dataset. These features remove the need for the user to interact with complex codes.

Nonrigid forms of motion are commonplace in everyday life. Given previously documented age-related deteriorations in various tasks involving motion (discriminating speed, identifying motion direction, etc.), an experiment was conducted to evaluate the potential effect of age upon the visual ability to detect rigid and nonrigid object motion. Thirty younger and older observers participated in the experiment (mean ages were 19.9 and 75.8 years, respectively). As has been done multiple times in the past, the individual motions of object vertices were manipulated to simulate either rigid motion (rotation in depth, with or without precession) or two different types of nonrigid motion (also rotation in depth with or without precession, but with added object deformation). In confirmation of previous research, there were large effects of nonrigid motion type and precession upon the ability to differentiate between rigid and nonrigid object motion. There was also a large effect of age, such that the discrimination performance of the younger observers was 49.6% higher than that exhibited by the older observers. In this first ever study of aging and nonrigid object motion perception, we thus find that aging is associated with a substantial impairment in the ability to visually perceive object nonrigidity.

Antimicrobial peptides are small amphiphilic proteins found in animals and plants as essential components of the innate immune system and whose function is to control bacterial infectious activity. In order to accomplish their function, antimicrobial peptides use different mechanisms of action which have been deeply studied in view of their potential exploitation to treat antibiotic-resistant bacterial infections. One of the main mechanisms of action of these peptides is the disruption of the bacterial membrane through pore formation, which, in some cases, takes place via a monomer to oligomer cooperative transition. Previous studies have shown that lipid composition, and the presence of exogenous components, such as cholesterol in model membranes or carotenoids in bacteria, can affect the potency of distinct antimicrobial peptides. At the same time, considering the membrane as a two-dimensional material, it has been shown that membrane composition defines its mechanical properties which might be relevant in many membrane-related processes. Nevertheless, the correlation between the mechanical properties of the membrane and antimicrobial peptide potency has not been considered according to the importance it deserves. The relevance of these mechanical properties in membrane deformation due to peptide insertion is reviewed here for different types of pores in order to elucidate if indeed membrane composition affects antimicrobial peptide activity by modulation of the mechanical properties of the membrane. This would also provide a better understanding of the mechanisms used by bacteria to overcome antimicrobial peptide activity.

Many previous studies have investigated visual distance perception, especially for small to moderate distances. Few experiments, however, have evaluated the perception of large distances (e.g., 100 m or more). The studies that have been conducted have found conflicting results (diametrically opposite conclusions). In the current experiment, the functions relating actual and perceived distance were obtained for sixteen adult observers using the method of equal appearing intervals. These functions relating perceived and actual distance were obtained for outdoor viewing in a typical University environment—the experiment was conducted along a sidewalk adjacent to a typical street where campus buildings, trees, street signs, etc., were visible. The overall results indicated perceptual compression of distances in depth so that the stimulus distance intervals appeared significantly shorter than the actual (physical) distance intervals. It is important to note, however, that there were sizeable individual differences—the judgments of half of the observers were relatively accurate, whereas the judgments of the remaining half were inaccurate to varying degrees. The results of the experiment demonstrate that there is no single function that describes how human observers visually perceive large distance intervals in outdoor environments.