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The physical properties of fabric causing an uncomfortable tactile perception under certain clothing pressure has always been a difficult problem in the field of fabric comfort research. According to a large number of works in the literature, the amygdala was recognized as the key brain region for negative perceived emotions. In order to investigate the fabric factors causing the signal changes in the amygdala brain region, functional magnetic resonance imaging was used to monitor the amygdala brain region and its anatomical sub-brain region under the same degree of compression stimulation from several different corsets, and the percent signal changes (PSCs) were extracted and analyzed. The results showed that there was a significant positive correlation between the PSCs of the centromedial group of the amygdala and the average dynamic friction coefficient (MIU) of the fabric at the level of 0.05, and a general linear model was established ( R2 = 0.998, p = 0.019). These results indicated that the surface friction properties of the fabric successfully attracted the attention of the central amygdala, and the attention increased linearly with the increase of MIU. This finding not only laid a foundation for exploring the brain perception mechanism of fabric discomfort, but also provides a possibility for further quantification of fabric discomfort perception by using the amygdala brain region.

The integration of high conductive networks and textiles has become a favorable technical route to fulfill the objectives of wearable electronics. Herein, high stretchable and recoverable PET fabric coated with a layer of silver nanowire network by a simple and scalable polyol-method is provided. The electrothermal performance, resistance temperature-sensitivity, electromagnetic shielding performance, strain sensing, and washability of silver nanowire (AgNWs)/PET fabrics with different coating times were performed. The conductivity of the fabric coated AgNWs of 2.8 mg/cm2 is as high as 175 S/m, the EMI shielding effectiveness is 37 dB, and it gives a highly sensitive strain response to human movement (gauge factor of −6.16 under 10% strain) and an underwater oil repellent angle of 125°. The heating temperature can reach above 100°C within 27 s under an applied current of 0.10 A. In addition, an excellent linearity of the resistance temperature-sensitive behavior for AgNWs/PET fabrics is obtained, and fabric Ag-5 gives a negative temperature coefficient of resistance (TCR) of −0.05%/°C. Knitted fabric with multi-function is obtained by use of silver nanowire coating. This method provides a simple, low-cost and easy-to-scalable process for the production of electronic textiles, such as fabric heater, microwave blocker, sensor, and other technologies.

Wrinkling is one of the most common flaws of woven fabrics in domestic use and industrial applications. It is necessary to develop an objective evaluation method to quantify the smoothness appearance of fabrics effectively. Herein, a fabric multi-deformation tester (FMDT) was designed to evaluate the smoothness appearance of garment fabrics by one sequential mechanical test, overcoming the main difficulties of the existing visual measurement methods for wrinkling evaluation of fabrics with complex colors and patterns. The k-means clustering algorithm was used to objectively cluster the fabric samples based on the characteristic parameters, including the wrinkle-induced residual force ( F wr), hysteresis distance ( H fr), position deflection ( D fr) and stretching recovery slope ( S tr), from the testing curve and the thickness and weight of fabrics, and comparisons with subjective evaluation were also conducted. The results reveal that the k-means clustering is able to classify the smoothness appearance of fabrics using the selected characteristic parameters, showing a good consistency with the subjective clustering results. The feasibility of using the mechanical and deformation properties of textiles to characterize fabric smoothness appearance is proved, and the FMDT provides a potential method to analyze the wrinkling of fibrous materials in a convenient way.

The tactile perception of fabric surface properties in the brain has always been a major research issue in the study of the contact comfort of fabrics. This study introduced the concept of PSC (percent signal change) obtained by fMRI (functional Magnetic Resonance Imaging) technology to explore the perceptual brain regions concerned with the roughness of the fabric surface. Firstly, the PSCs of human somatosensory cortexes, including the SI (primary somatosensory cortex) and SII (secondary somatosensory cortex), under the stimulation of boneless corsets with different surface roughness, were extracted and analyzed. As the surface roughness of the fabric increased gradually from smooth to rough, the brain region in which the maximum PSC occurred gradually transited from the SI to the SII, which indicated that the SI brain region paid more attention to the contact of smooth fabrics, while the SII brain region laid emphasis on the fine tactile perception of rough fabrics. Furthermore, the result of sub-regions in the SI and SII showed that, with the increase of the roughness of the fabric surface, the PSC of the OP2 (Operculum Parietal 2) brain region increased significantly, and the brain region concerned with the fabric surface tactile stimulation was gradually transferred from the slow adaptive sensory projection Brain Area 3a in the SI to the fast adaptive sensory projection Brain Area 1 in the SI, and finally moved to OP2 in the deep cortex of the SII.

Planar frequency selective surface (FSS) fabrics with grids, strips or patches by simple methods of patching, embroidery, clipping and carving were fabricated. The periodic structures, laminated structures, processing method and materials pertaining to the electromagnetic shielding behaviors were investigated. Firstly, equivalent circuit and electromagnetic (EM) shielding behavior of basic frequency selective structure units and complex fretwork structure were provided, involving the decoupling of complex fretwork structure. In addition, various laminating structures of SPs and SGs were determined, one of superposition of SPs and SGs provides a SE peak of 40.2 dB (average SE of 25.1 dB in the whole frequency domain), the other presents a SE peak of 27.1 dB (average SE of 19.1 dB in the whole frequency regime). Furthermore, tunable selective electromagnetic shielding by a simple mechanical way was provided, which can realize a tunable SE peak varying from 730 MHz to 1580 MHz. This work might provide a perspective for the assemble and analytical approximation of FSS fabrics for scientists and engineers in this cross-disciplinary field.

Fabric hand is most frequently used by consumers and researchers to evaluate the touch feeling of textiles. Academically, many methods have been developed to characterize it psychologically and physically, and the relationship between the hand attributes of fabrics and their physical properties are well understood. However, in physiological terms, the cognitive mechanism of the brain on different attributes of fabric hand is not clear. Previous studies have shown that the sensory or discrimination information from fabric touch can be detected by the technology of functional magnetic resonance imaging (fMRI). In this study, further fMRI experiments were carried out, attempting to find the relationship between the cerebral cortices of various brain areas and different hand attributes of fabrics. The subtle atlas of Automated Anatomical Labeling (AAL) was used to display and analyze the blood oxygenation level dependent signals completely and conveniently. The results showed that when the subjects touched two samples with distinct fabric hand in a specified way, activation information and the index of the mean signal in every related brain areas can distinguish them, and several brain regions in the AAL atlas are linked to different fabric hand attributes. The technology of fMRI was proved again to be a promising tool for studying the cognitive mechanism of the brain on fabric touch.

The present study was carried out with a new approach to evaluating the comfort of fabric contact pressure. Functional magnetic resonance imaging technology was conducted to monitor brain response when a comfortable fabric contact pressure, according to the subjective evaluation, was applied to the skin surface of the lower human chest. After a strict method of calibration with a family-wise error check analysis, the study we performed revealed the right secondary somatosensory cortex appeared prominently positively activated under a comfortable fabric pressure state. This suggested the secondary somatosensory cortex brain region, particularly the right secondary somatosensory cortex, was probably the characteristic brain region for fabric comfort perception. A reasonable explanation was that proper contact pressure facilitated the serial information flow from the primary somatosensory cortex to the secondary somatosensory cortex, and comfortable touch stimulated the firing of A-beta afferent nerves.

Bottle-recycled polyethylene terephthalate (R-PET) fibers were fabricated by the melt spinning method. Based on characteristics of R-PET chips, this study involved a primary exploration of the spinning parameters, including spinning temperature, spinning speed and spinneret plate. The properties of R-PET and original PET (O-PET) fibers were compared using scanning electron microscopy (SEM), tensile testing, sonic orientation, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR). Apparent morphological observation displays an irregular cross-sectional shape and a scattered diameter distribution for R-PET fibers. Compared with O-PET fibers, R-PET fibers demonstrate a greater breaking strength and smaller elongation at break, resulting from the lower crystallinity and higher degree of orientation. Furthermore, the R-PET fibers have the same chemical structure as that of O-PET fibers demonstrated by FTIR spectroscopy, but TGA results show that thermal stability of R-PET fibers is significantly inferior to that of O-PET fibers, as a result of too many impurities and oligomers during the recycling process.

The intelligent detection of distress in concrete is a research hotspot in structural health monitoring. In this study, Att-Unet, an improved attention-mechanism fully convolutional neural network model, was proposed to realize end-to-end pixel-level crack segmentation. Att-Unet consists of three parts: encoding module, decoding module, and AG (Attention Gate) module. The benefits associated with this module can effectively extract multi-scale features of cracks, focus on critical areas, and reconstruct semantics, to significantly improve the crack segmentation capability of the Att-Unet model. On the same data set, the mainstream semantic segmentation models (FCN and Unet) were trained simultaneously. Upon comparing and analyzing the calculated results of Att-Unet model with those of FCN and Unet, the results are as follows: for crack images under different conditions, Att-Unet achieved better results in accuracy, precision and F1-scores. Besides, Att-Unet showed higher feature extraction accuracy and better generalization ability in the crack segmentation task.

The glabrous and hairy skin of the human body contains different types of mechanoreceptive afferents. At present, consumers and researchers usually use hands (the glabrous palm) to evaluate and study the contact perception of fabric, which mainly contains two aspects of fabric performance, handle and comfort. However, in use, fabric in most cases contacts the hairy skin of the human body, rather than the glabrous skin. In order to investigate the cognitive differences in the brain for fabric touch on the two types of skin, we used the same silk fabric to touch the palm and forearm of nine subjects, and observed the brain responses simultaneously using functional magnetic resonance imaging. The results showed that for palm stimulation, activations were mainly evoked in somatosensory cortices, and deactivation in the insula cortex and, in contrast, for forearm stimulation, more activations were evoked in the insula cortex, and deactivation mainly in the primary somatosensory cortex. It is suggested that there are more sensory information arising from fabric touch on the glabrous skin, and more emotional information on the hairy skin. Therefore, for discriminating the physical properties (e.g. fabric hand) of fabric, it is better to receive fabric touch using glabrous skin, and for evaluating the emotional perception (e.g. fabric comfort) of fabric touch, it is better using hairy skin.