Surface Properties Of Objects Research Articles

Nanoparticles for stimulation of neutrophil extracellular trap-mediated immunity.

Neutrophil extracellular traps (NETs) have been identified as triggers for a self-limited inflammatory reaction upon contact with nanoparticles within our bodies. This typically results in entrapping potentially harmful nano- or micro-objects following an immune burst. The demand for potent adjuvants has led to research on particulate-based adjuvants, particularly those that act via NET formation. Various particles, including hydrophobic nanoparticles, needle-like microparticles, and other natural and artificial crystals, have been shown to induce NET formation, eliciting a robust humoral and cellular immune response toward co-injected antigens. The NET formation was found to be the basis of the efficient use of alum as a vaccine adjuvant. Thus, nanoparticles with specific surface properties serve as NET-stimulating adjuvants. In this mini-review, we aim to summarize the current knowledge about the surface properties of particulate objects and the molecular pathways involved in inducing NET formation by neutrophils. Additionally, we discuss the potential use of nanoparticles for activating neutrophils in the tissues and the exploitation of such activation for enhancing vaccine adjuvants.

An approach for considering the object surface properties in a TLS stochastic model.

The interaction between laser beams and backscattering object surfaces lies at the fundamental working principle of any Terrestrial Laser Scanning (TLS) system. Optical properties of surfaces such as concrete, metals, wood, etc., which are commonly encountered in structural health monitoring of buildings and structures, constitute an important category of systematic and random TLS errors. This paper presents an approach for considering the random errors caused by object surfaces. Two surface properties are considered: roughness and reflectance. The effects on TLS measurements are modeled stepwise in form of a so-called synthetic variance-covariance matrix (SVCM) based on the elementary error theory. A line of work is continued for the TLS stochastic model by introducing a new approach for determining variances and covariances in the SVCM. Real measurements of cast stone façade elements of a tall building are used to validate this approach and show that the quality of the estimation can be improved with the appropriate SVCM.

A Robust Incipient Slip Detection Method With Vision-Based Tactile Sensor Based on Local Deformation Degree

Incipient slip detection is important for manipulators to achieve stable grasping. In order to make manipulators adapted to unstructured environments better and realize a wider range of applications, it is necessary to achieve incipient slip detection with robustness to object surface properties. In this paper, we propose a novel incipient slip detection method with vision-based tactile sensor. The method only uses sensor deformation data and does not need any information about the grasped object. In addition, it has the advantages of intuitive principles and a wide range of applicable working conditions. In this paper, the local deformation degree of the sensor is proved to be related to the stick/slip state at the corresponding location by kinematic aspects. Based on this, a method is proposed to select reference points in the stick region with local deformation degree. These reference points are used to fit the rigid motion of the contacted object and the slip field. Furthermore, an iterative algorithm is proposed to delineate the stick/slip region based on the characteristic of the slip field. Afterward, complex contact conditions are constructed through finite element simulation. Curved surfaces, discontinuous surfaces, and surfaces with multiple friction coefficients distribution are used to verify the correctness and superiority of the proposed method compared to other methods. Finally, the slip detection experimental bench is built, and our self-developed vision-based sensor is used to contact common objects with complex surface properties. Through the real slip detection experiments, the adaptability and good application prospects of this method are demonstrated.

Study of event-related potentials by withdrawal friction on the fingertip.

The lack of understanding about the brain's reaction processes in perceiving touch and separation between skin and object surfaces is a barrier to the development of existing brain-computer interface technologies and virtual haptics. These technologies are limited in their ability to advance. It leaves prosthesis users with a limited amount of tactile information that they can feel. This study aims to determine whether distinct surface aspects of various items trigger different reactions from the brain when friction is removed from the surface. When friction is suddenly removed from the surface of an item, a technique called event-related potential, (ERP) is used to study the features of people's EEGs. It is done after the subject has actively explored the object's surface. A 64-channels EEG collecting system was utilized to acquire EEG data from the individuals. [Corrections added on 5 December 2022, after first online publication: The preceding sentence has been updated.] The event-related potentials for friction removal were generated using the Oddball paradigm, and the samples consisted of sandpaper with three distinct degrees of roughness. We utilized a total of 20 participants, 10 of whom were male, and 10 of whom were female, with a mean age of 21 years. It was discovered that the P3 component of event-related potentials, which is essential for cognition, was noticeably absent in the friction withdrawal response for various roughnesses. It was the case regardless of whether the surface was smooth or rough. Moreover, there was no statistically significant difference between the P1 andP2 components, which suggests that the brain could not recognize the surface properties of objects with varying roughness as the friction withdrawal was being performed. It has been demonstrated that tactile recognition does not occur after friction withdrawal. The findings of this paper could have significant repercussions for future research involving the study of haptic perception and brain-computer interaction in prosthetic hands. It is a step toward future research on the mechanisms underlying human tactile perception, so think of it as preparation.

Experimental Investigation of the Supercavitation and Hydrodynamic Characteristics of High-Speed Projectiles with Hydrophobic and Hydrophilic Coatings

Supercavitation technology has important application value in military and national defence fields because of its huge potential in drag reduction, while the cavitation around underwater moving objects may be affected by the surface properties of objects. In this paper, the supercavitation characteristics and hydrodynamics of a projectile with hydrophobic and hydrophilic surface coatings were experimentally studied using a high-speed camera. The supercavitation evolution, cavitation size, velocity change, drag force coefficient, and ballistic deflection of projectiles in different water depths are compared and analyzed. The results show that the length and diameter of the supercavity increase with the decrease in water depth. At the same water depth and cavitation number, the length and diameter of the supercavitation of the projectile with hydrophobic coating were greater than those of the projectile with hydrophilic coating, and the drag force coefficient of the hydrophobic projectile was obviously smaller than that of the hydrophilic projectile. Under the working conditions of 6.67D, 16.7D, and 33.3D, the drag force coefficient of the hydrophobic projectile could be reduced by about 20–40% compared with that of the hydrophilic projectile. The maximal reduction in drag force coefficient was up to 40% at σ = 0.34 under a water depth of 33.3D. The velocity attenuation of hydrophobic projectile was about 20% slower than that of hydrophilic projectile. In addition, the ballistic stability of hydrophobic coated projectiles was better than that of hydrophilic coated projectiles in the different water depths observed in the paper.

MRS-Tex: A Magnetically Responsive Soft Tactile Device for Texture Display

Tactile devices provide an intuitive way for texture display, which allows users to perceive the detailed surface properties of virtual or remote objects. For existing tactile devices that create actual topographical transformations, it remains challenging to render surface textures with high spatial resolution due to the limitation of the size of actuators. To address this challenge, a magnetically responsive soft actuator with a diameter of 1 mm is proposed. Integrating the high-density soft actuator array and a soft membrane bracket, we develop a magnetically responsive soft tactile device (named MRS-Tex) for texture display. When a magnetic field is applied, the magnetic units will sink to form pits, and the soft membrane bracket resists the finger pressure so that users can perceive the rendered surface texture. Thanks to the proposed sunken solution, MRS-Tex is capable of rendering surface textures with millimeter-level resolution (1.5 mm) while providing a sufficient upward holding force. Moreover, we conduct quantitative experiments and two user studies to evaluate the performance of MRS-Tex. Experimental results show that MRS-Tex can generate pits with a depth of more than 0.20 mm, which is sufficient for rendering perceivable surface textures. The average discrimination accuracy of user study can reach up to 82% for both six basic texture patterns and four complex texture patterns.

Multimodal Sensors and ML‐Based Data Fusion for Advanced Robots

Nature has proved that multiple sense and processing capabilities are critical for target recognition and race survival. As such, advanced robots that perform missions in an unstructured environment highly need organism‐similar multimodal sensing and processing systems for sophisticated unstructured environmental stimuli. Herein, recent progress in multimodal sensing and processing systems for advanced robotics is reviewed. Multimodal sensors including tactile sensors that capture surface properties of objects (i.e., thermal conductivity, temperature, softness, and electron affinity), visual sensors that capture the color and size of objects, and gas sensors that capture object smell are summarized. The multimodal data fusion algorithms that process multimodal signals from multimodal sensors to achieve object recognition and decision making are also presented. The challenges and future development of multimodal sensors and data fusion algorithms are further discussed. Advances in these areas open new avenues for advanced robotics applications in human–robot collaboration, rescue missions, garbage sorting, and intelligent prosthetics.

Prediction model for perceptual gloss by physical measurement of flat objects

Although a physical gloss exists as a physically measurable index, people can also perceive a perceptual gloss on object surfaces. However, the physical gloss does not always match the perceptual gloss. Because the physical gloss is calculated based only on the specular gloss and does not reflect other physical features that affect the perceptual gloss. Thus, we analysed the relationships between physical features and perceptual gloss by measuring many physical properties of object surfaces, including their physical gloss. We prepared 127 flat objects comprising three materials: paper, resin and metal plating. The perceptual gloss was visually evaluated for observation angles of 20°, 60° and 85° using a magnitude estimation method. Multiple measurements were conducted to obtain physical features such as the gloss unit (GU), haze, distinctness of image and high dynamic range luminance. We then constructed prediction models for the perceptual gloss using these physical features and multiple regression analyses. By combining these multiple physical quantities and using the GU in the power scale, the prediction accuracy was improved. By the optimal power index (0.33 for physical gloss in the common prediction model, independent of the observation angle), we found that human gloss perception may be related to brightness perception.

Multifunctional biomimetic tactile system via a stick-slip sensing strategy for human–machine interactions

A tactile sensor system enables natural interaction between humans and machines; this interaction is crucial for dexterous robotic hands, interactive entertainment, and other smart scenarios. However, the lack of sliding friction detection significantly limits the accuracy and scope of interactions due to the absence of sophisticated information, such as slippage, material and roughness of held objects. Here, inspired by the stick-slip phenomena in the sliding process, we have developed a multifunctional biomimetic tactile system based on the stick-slip sensing strategy, which is a universal method to detect slippage and estimate the surface properties of objects by sliding. This system consists of a flexible fingertip-inspired tactile sensor, a read-out circuit and a machine-learning module. Based on the stick-slip sensing strategy, our system was endowed with high recognition rates for slippage detection (100.0%), material classification (93.3%) and roughness discrimination (92.8%). Moreover, robotic hand manipulation, interactive games and object classification are demonstrated with this multifunctional system for comprehensive and promising human–machine interactions.

Spectral measurement of daylights and surface properties of natural objects in Japan.

We present a spectral dataset of daylights and surface reflectances and transmittances of natural objects measured in Japan. Daylights were measured under the sun and under shadow from dawn to dusk on four different days to capture their temporal spectral transition. We separately measured daylight spectra at five different locations (including an open space and a forest) with minimum time difference to reveal whether a local environment alters daylight spectra reaching the ground. We found that colors of natural objects were spread in a limited area of color space, and data points were absent around saturated green regions. Daylight spectra were found to have a larger variation across time, weather, and local environments than previously thought. Datasets are made freely available, expanding past public datasets mainly collected in Northern America and Europe.

Comparative study on 3D optical sensors for short range applications

The increasing availability of commercial 3D optical sensors drastically benefits the application fields including the mechatronics where providing affordable sensing means for perception and control is vital. Yet, to our knowledge, there is no thorough comparable study to the state-of-the-art 3D optical sensors, making it difficult for users to select for their specific applications. This paper evaluates the performance of each sensor for short range applications (i.e., ≤ 1 m). Specifically, we present our findings on the measurement accuracy of each sensor under “ideal” situations, compare the influence of various lighting conditions, object surface properties (e.g., transparency, shininess, contrast), and object locations. In addition, we developed software APIs and user instructions that are available for the community to easily use each of the evaluated commercially available 3D optical sensor.

Accuracy Assessment On Point Cloud Dataset from Terrestrial Laser Scanner with Different Objects Surface Properties

Terrestrial laser scanner is the instrument used for generating and receiving point cloud data from the ground either using tripod or handheld. This study focused on identifying the effect of different object surface properties in most standard building materials used towards the accuracy of point cloud captured using TLS that is important for guiding the observer before making measurement. Practically, all the captured data for each surface used the similar aspects in terms of resolution, quality, and point cloud distance using a single scan method. Next, all data processing were processed and computed using FARO Scene, ArcScene and AutoDesk Recap software that are capable to analyse through the reconstructed 3D model. It had been found that cement wall reacts better with the point clouds even the wood expected to give a good result as a few factors had given big impacts towards each of the object surfaces. The finding from this study had identified the reaction of the point clouds on each different object surfaces with various properties varies depending on the roughness, reflectivity strength, colors, textures and type of surfaces that became major indicator to determine accuracy of the distributions and arrangements of point clouds on each surface.

Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements

Accurately modeling local surface properties of objects is crucial to many robotic applications, from grasping to material recognition. Surface properties like friction are however difficult to estimate, as visual observation of the object does not convey enough information over these properties. In contrast, haptic exploration is time consuming as it only provides information relevant to the explored parts of the object. In this work, we propose a joint visuo-haptic object model that enables the estimation of surface friction coefficient over an entire object by exploiting the correlation of visual and haptic information, together with a limited haptic exploration by a robotic arm. We demonstrate the validity of the proposed method by showing its ability to estimate varying friction coefficients on a range of real multi-material objects. Furthermore, we illustrate how the estimated friction coefficients can improve grasping success rate by guiding a grasp planner toward high friction areas.

Exploring the Determinants of Color Perception Using #Thedress and Its Variants: The Role of Spatio-Chromatic Context, Chromatic Illumination, and Material-Light Interaction.

The colors that people see depend not only on the surface properties of objects but also on how these properties interact with light as well as on how light reflected from objects interacts with an individual’s visual system. Because individual visual systems vary, the same visual stimulus may elicit different perceptions from different individuals. #thedress phenomenon drove home this point: different individuals viewed the same image and reported it to be widely different colors: blue and black versus white and gold. This phenomenon inspired a collection of demonstrations presented at the Vision Sciences Society 2015 Meeting which showed how spatial and temporal manipulations of light spectra affect people’s perceptions of material colors and illustrated the variability in individual color perception. The demonstrations also explored the effects of temporal alterations in metameric lights, including Maxwell’s Spot, an entoptic phenomenon. Crucially, the demonstrations established that #thedress phenomenon occurs not only for images of the dress but also for the real dress under real light sources of different spectral composition and spatial configurations.

The limited contribution of early visual cortex in visual working memory for surface roughness.

Are visual representations in the human early visual cortex necessary for visual working memory (VWM)? Previous studies suggest that VWM is underpinned by distributed representations across several brain regions, including the early visual cortex. Notably, in these studies, participants had to memorize images under consistent visual conditions. However, in our daily lives, we must retain the essential visual properties of objects despite changes in illumination or viewpoint. The role of brain regions-particularly the early visual cortices-in these situations remains unclear. The present study investigated whether the early visual cortex was essential for achieving stable VWM. Focusing on VWM for object surface properties, we conducted fMRI experiments, while male and female participants performed a delayed roughness discrimination task in which sample and probe spheres were presented under varying illumination. By applying multi-voxel pattern analysis to brain activity in regions of interest, we found that the ventral visual cortex and intraparietal sulcus were involved in roughness VWM under changing illumination conditions. In contrast, VWM was not supported as robustly by the early visual cortex. These findings show that visual representations in the early visual cortex alone are insufficient for the robust roughness VWM representation required during changes in illumination.

Measurement method of a slipping condition by center of pressure to evaluate a haptic feeling

Humans perceive the surface properties of objects by sliding their fingertips on the object. We have proposed the method to measure the changes in the contact area by a camera and evaluate the haptic feeling of a human. However, the obtained images are affected by the color of an object and the lighting condition of the environment. To solve this problem, we propose to evaluate the slippage based on the center of pressure (CoP) by using a 6-axis force sensor. In this paper, we report the CoP data for different surface texture and discuss the results.

Approaches for Characterizing Surfaces Damaged by Disinfection in Healthcare

Healthcare-Associated Infections (HAIs) are a significant cause of morbidity and mortality and occur in many healthcare facilities including hospitals, surgery centers and long-term care facilities. It is well known that some pathogens can persist on healthcare surfaces for weeks to months and spread readily to new surfaces. It is current practice to disinfect or clean surfaces routinely in order to reduce the risk of HAIs. However, routine cleaning can damage the surface chemically or mechanically, which may actually increase the surface contamination. Fundamental knowledge is therefore needed to understand the influence of cleaning and disinfection on healthcare surfaces in order to mitigate pathogen persistence. In this study, materials and objects found in healthcare facilities were selected and exposed to disinfection procedures including wiping and soaking with readily available chemical disinfectants. A variety of chemical disinfectants were selected which contain hydrogen peroxide, quaternary ammonia, and chlorine, respectively. Optical microscopy, contact angle measurement, atomic force microscopy (AFM), Fourier Transform Infrared (FTIR) spectroscopy and nanoindentation are used to analyze surface characteristics before and after disinfection in order to study the effect of disinfection on material properties. Disinfection procedures are found to cause changes to surface properties of materials and objects which can be detected and observed or quantified by the approaches used in this study. The methods should become regular practice in the studies of healthcare surfaces and their role in HAIs. Each method in this study may not be reliably applied to every object or disinfection scenario. Sample geometry and features may influence response during measurement and affect results. The combination of the approaches is able to sufficiently characterize chemical, mechanical, and topological changes to the surface.

Learning and memory in color perception

We often have the experience of perceiving the colors and materials of objects in our environment effortlessly. But estimating the surface properties of objects is in fact a computationally hard problem for the visual system, because the light signal that reaches our eyes from surfaces in our environment depends not only on the reflectance of the surface, but also on the illumination impinging on the surface. Statistical regularities about surfaces and illuminants, learned through interacting with our environment and through social communication, may contribute to our ability to compensate for changes in illumination when estimating object color. These statistical regularities may be learned at different timescales from species evolution to individual development to something akin to temporary adaptation. For instance, the typical colors of objects, as well as color categories -- both learned through experience -- may anchor color perception under illumination changes. More short-term learning may also stabilize color perception under more abrupt changes in the environment. In this talk, I will present research on the influence of long-term and short-term color knowledge on color appearance, and link this with color constancy in a probabilistic estimation framework. I will end by discussing ongoing research to push the study of color constancy to more realistic scenes and tasks.

IDENTIFIKASI SERAT BAMBU MENGGUNAKAN EKSTRAKSI CIRI STATISTIK ORDE 2 (GLCM) DAN PENGUKURAN JARAK K-NN

Indonesia is a large bamboo producer. Many benefits can be taken from bamboo trees, among others, as an alternative material for environmentally friendly construction, handicraft, and even become a safe material for use. Based on the property of its mechanical strength, bamboo has high tensile strength and fiber content, including fiber length, inter-fiber adhesive, namely lignin and the higher diameter of bamboo fiber, causing bamboo stems to become stronger and stiffer so that bamboo quality is getting better. One objective is to use a texture analysis of statistical features extraction of digital image processing. Feature extraction is a process to get the characteristics of visual perception. Texture information can be used to distinguish the surface properties of objects in images that are related to coarse and fine. This research uses a second-order statistical calculation of Gray Level Co-occurrence Matrices (GLCM) by measuring contrast, energy, homogeneity, and correlation levels to determine roughness from bamboo image textures that have irregular patterns. The second method is to use similarity measurements with the K-NN method in which in this study K = 3 with testing images of 28 images obtained an accuracy of 0.8, precission of 0, 8 and f-measurement of 0.9.

Microneedle Patterning of 3D Nonplanar Surfaces on Implantable Medical Devices Using Soft Lithography.

Micropatterning is often used to engineer the surface properties of objects because it allows the enhancement or modification of specific functionalities without modification of the bulk material properties. Microneedle arrays have been explored in the past for drug delivery and enhancement of tissue anchoring; however, conventional methods are primarily limited to thick, planar substrates. Here, we demonstrate a method for the fabrication of microneedle arrays on thin flexible polyurethane substrates. These thin-film microneedle arrays can be used to fabricate balloons and other inflatable objects. In addition, these thin-filmed microneedles can be transferred, using thermal forming processes, to more complex 3D objects on which it would otherwise be difficult to directly pattern microneedles. This function is especially useful for medical devices, which require effective tissue anchorage but are a challenging target for micropatterning due to their 3D nonplanar shape, large size, and the complexity of the required micropatterns. Ultrathin flexible thermoplastic polyurethane microneedle arrays were fabricated from a polydimethylsiloxane (PDMS) mold. The technique was applied onto the nonplanar surface of rapidly prototyped soft robotic implantable polyurethane devices. We found that a microneedle-patterned surface can increase the anchorage of the device to a tissue by more than twofold. In summary, our soft lithographic patterning method can rapidly and inexpensively generate thin-film microneedle surfaces that can be used to produce balloons or enhance the properties of other 3D objects and devices.