Types Of Fabrics Research Articles

Unravelling the Interplay between Materials, Senses and Perception in Magdalena Abakanowicz’s Weaving Art

This article comprehensively studies the multisensual experience in Magdalena Abakanowicz’s weaving art. While previous research in this context has focused on the erotic nature of her works, this study addresses the broader aspect of multisensual engagement. Drawing on a phenomenological approach and the philosophical contributions of Maurice Merleau-Ponty, it explores Abakanowicz’s involvement in creative and exhibition practices. The research incorporates insights from scholars such as Richard Shusterman, Mark Paterson and art historians. Using art historical analysis and direct haptic contact with Abakanowicz’s works, the study analyses the materials and techniques of three fabric types. The findings reveal that the enduring interest in the artist’s work lies in anthropomorphising quality that activates viewers’ senses, fostering a profound connection between the audience and art. The article demonstrates how Abakanowicz skilfully influences viewers’ senses and emotions through material choices, techniques, and personal involvement. Ultimately, it highlights the significance of considering sensory reflection as a crucial aspect of art historical analysis.

City-scale analysis of PV potential and visibility in heritage environment using GIS and LiDAR

Increasing the share of renewables, especially utilizing solar power in our energy mix is a highly prioritized aim of the EU. Budapest, the largest city and the capital of Hungary, contains almost 1 million flats in more than 190 thousand buildings, organized in various characteristic urban fabric types. Although on-site renewable energy production is severely limited in dense urban environments, the roofs offer a considerable potential to generate energy on-site.The present paper introduces a method to estimate the PV potential of rooftops on a large scale applying a GIS approach. Using LiDAR data, a Digital Surface Model (DSM) was created. The DSM was utilized to evaluate roof slope, orientation, and global irradiation. Solar potentials, available roof area, photovoltaic (PV) system capacities and estimated annual electricity production were derived from the GIS model. The method was used to develop an open access website called the Budapest Solar Map, which provides decision-makers with solar PV data. However, the nominal PV potential is limited by layers of heritage protection regulations that safeguard the sight of our case study area, Budapest, which is a World Heritage Site. Visibility is also surveyed with GIS and geometrical modeling from designated high points and from the street level, respectively.

Bioactive polyethylene-coated nonwovens for wound healing application

Bioactive non-woven dressings can be prepared by dip coating of non-woven cloth in solutions containing bioactive polyethylene bearing pendant arms of polyethylene (PE5000) and modified PEG3400-biomolecules including linear Arg-Gly-Asp (RGD), collagen fragment (Gly-Pro-Hyp)3, laminin-derived peptide (AGQWHRVSVRWGC) (A5G81) and hyaluronic acid (HA). Obtainment of ultimate coating concentration for each type of non-woven cloth is achieved such that the technically demanding bioactive polyethylene does not delaminate from the non-woven cloth itself but is of sufficient quantity for bioactivity. Scanning electron microscopy images show uniform polyethylene deposition on the non-woven cloth. Good water absorption and permeability allow the use of such bioactive polyethylene coated non-woven cloth as wound dressings. Material biocompatibility is demonstrated using in vitro human skin fibroblast assays. In vivo porcine full thickness excisional wound model shows PE5000-coated non-woven cloth can remarkably accelerate skin regeneration to close the wounds faster than clinical gold standard dressing. Thus, the results presented here may provide a promising guide for bioactive polyethylene-modified non-woven materials for wound dressing applications.

Analysis of the properties of bast raw materials as a component of fabric for military uniforms

The relevance of the present research is determined by the need to replace imported raw materials for manufacturing military clothing with Ukrainian raw materials of industrial hemp and oilseed flax. The aim was to analyse the quality properties of bast raw materials and determine their potential for use in military uniforms. In the course of solving the set goals, the methods of complex analysis, synthesis, observation, measurement, comparison and generalisation of the obtained results and information were applied, as well as standard methods generally accepted in the light industry were implemented. It is noted that hemp cottonin and oilseed flax fiber, in contrast to other natural fibers, are more durable, resistant to abrasion, decay, and are characterised by sanitary, antistatic, hypoallergenic and antibacterial properties. It has been revealed that fabrics made of these fibers are durable, have high resistance to ultraviolet radiation, hold colour well, do not fade, etc. The academic paper analyses scientific studies on the use of this raw material for various types of military clothing, protective body armour, and gunpowder production. By determining the main properties of the bast raw materials under study, the possibility of using this raw material in some types of military uniforms was established. The main feature of the structure and components of the research was the systematic and comprehensive study of the quality properties of bast raw materials at all stages of its processing. It was proposed to use oilseed flax fibers and hemp cottonin instead of cotton fibers in fabrics for military purposes. This will reduce the state’s material expenditures on the purchase of fabric for the defense sector and, at the same time, it will help bring the Ukrainian light industry to a new quality level and increase the competitiveness of Ukrainian manufactured goods in the global market. Knowledge of the properties of bast raw materials can help manufacturers improve the quality of fabrics for military purposes

Evaluation of tactile sensation for fabric handle – evidence from event related potentials

PurposeIn this paper, the brain potential changes caused by touching fabrics for handle evaluation were recorded by event related potential (ERP) method, compared with subjective evaluation scores and physical index of KES, explore the cognitive mechanism of the transformation of tactile sensation into neural impulses triggered by subtle mechanical stimuli such as material, texture, density and morphology in fabrics. By combining subjective evaluation of fabric tactile sensation, objective physical properties of fabrics and objective neurobiological signals, explore the neurophysiological mechanism of tactile cognition and the signal characteristics and time process of tactile information processing.Design/methodology/approachThe ERP technology was first proposed by a British psychologist named Grey Walter. It is an imaging technique of noninvasive brain cognition, whose potential changes are related to the human physical and mental activities. ERP is different from electroencephalography (EEG) and evoked potentials (EP) on the fact that it cannot only record stimulated physical information which is transmitted to brain, but also response to the psychological activities which related to attention, identification, comparison, memory, judgment and cognition as well as to human’s neural physiological changes which are caused by cognitive process of the feeling by stimulation.FindingsAccording to potential changes in the cerebral cortex evoked by touching four types of silk fabrics, human brain received the physical stimulation in the early stage (50 ms) of fabrics handle evaluation, and the P50 component amplitude showed negative correlation with fabric smoothness sensations. Around 200 ms after tactile stimulus onset, the amplitude of P200 component show positive correlation with the softness sensation of silk fabrics. The relationship between the amplitude of P300 and the sense of smoothness and softness need further evidence to proof.Originality/valueIn this paper, the brain potential changes caused by touching fabrics for handle evaluation were recorded by event related potential (ERP) method, compared with subjective evaluation scores and physical index of KES, the results shown that the maximum amplitude of P50 component evoked by fabric touching is related to the fabrics’ smoothness and roughness emotion, which means in the early stage processing of tactile sensation, the rougher fabrics could arouse more attention. In addition, the amplitude of P200 component shows positive correlation with the softness sensation of silk fabrics.

ShapeBoost: Boosting Human Shape Estimation with Part-Based Parameterization and Clothing-Preserving Augmentation

Accurate human shape recovery from a monocular RGB image is a challenging task because humans come in different shapes and sizes and wear different clothes. In this paper, we propose ShapeBoost, a new human shape recovery framework that achieves pixel-level alignment even for rare body shapes and high accuracy for people wearing different types of clothes. Unlike previous approaches that rely on the use of PCA-based shape coefficients, we adopt a new human shape parameterization that decomposes the human shape into bone lengths and the mean width of each part slice. This part-based parameterization technique achieves a balance between flexibility and validity using a semi-analytical shape reconstruction algorithm. Based on this new parameterization, a clothing-preserving data augmentation module is proposed to generate realistic images with diverse body shapes and accurate annotations. Experimental results show that our method outperforms other state-of-the-art methods in diverse body shape situations as well as in varied clothing situations.

Effects of textile type on the flexural properties of prefabricated hollow-core slabs strengthened with PVA fibers-improved TRM

In this study, the utilization of textile-reinforced mortar (TRM) in the strengthening and rehabilitation field is investigated. To regulate crack width, polyvinyl alcohol (PVA) fibers were incorporated into the TRM matrix. Nine prefabricated hollow-core slabs strengthened with TRM, along with one reference slab, were subjected to static loading using a 4-point bending apparatus. The experimental variables consisted of the type of textile (glass, basalt, and carbon) and the number of textile layers (one, two, and three layers). The experimental findings demonstrated that the inclusion of PVA fibers improved the TRM by effectively controlling crack width and increasing energy absorption capacity. Among the textile types, carbon TRM-strengthened slabs exhibited the highest flexural capacity. This capacity increased by 74%, 119%, and 132% for slabs strengthened with one, two, and three layers of textile, respectively. Glass TRM-strengthened slabs demonstrated superior deformability, with an increase rate ranging from 202% to 331%. Finally, to predict the flexural capacity and deflection of the tested slabs, a theoretical analysis was conducted and validated by comparing the theoretical predictions to the actual test results for accuracy and reliability.

Matrix deformation of marls in a foreland fold-and-thrust belt: The example of the eastern Jaca basin, southern Pyrenees

In this study, we used the Anisotropy of Magnetic Susceptibility (AMS) to investigate the matrix strain record of two calcareous shale formations, the Eocene Larrès and Pamplona Marls, along the eastern Jaca foreland fold-and-thrust belt (Southern Pyrenees). More than 1000 unoriented fragments, collected from 62 sites along 4 sub-parallel sections in the footwall of the regional Oturia thrust and through local Yebra anticline, were measured. The analysis of the degree of anisotropy (P’) and shape parameter (T) allowed to identify four types of magnetic fabrics. Type II fabrics associated with poorly deformed rocks are characterized by a relatively high anisotropy and an oblate shape. In contrast, type III fabrics, associated with strongly fractured rocks are characterized by the lowest anisotropy and a triaxial shape. Type IV and type V fabrics are characterized by increasing anisotropy and shape parameters, and are associated with the development of a weak to a slaty cleavage in rocks. The distribution of the magnetic fabric is roughly similar along the four studied sections. In the footwall of the Oturia thrust, magnetic fabrics evolve from the type V to type II over a 1000 m-long interval. By contrast, the distribution of magnetic fabric is roughly symmetric across the Yebra anticline, evolving from a dominating type II fabric in both limbs to mixed type III-type V fabrics within the 1 km-large hinge zone. The succession of the magnetic fabrics is interpreted as recording various degrees of matrix strain in response to thrusting and folding. The correlation of magnetic fabrics between the four sections highlights some along-strike variations in the extension of fabric domains that are interpreted as reflecting the local influence of 2nd-order factors, such as the syn-tectonic sedimentation. Results are integrated within the tectono-sedimentary framework of the studied area to propose a model of matrix strain related to the tectonic and sedimentary evolution of a foreland fold and thrust belt.

Programming mechanics in knitted materials, stitch by stitch

Knitting turns yarn, a 1D material, into a 2D fabric that is flexible, durable, and can be patterned to adopt a wide range of 3D geometries. Like other mechanical metamaterials, the elasticity of knitted fabrics is an emergent property of the local stitch topology and pattern that cannot solely be attributed to the yarn itself. Thus, knitting can be viewed as an additive manufacturing technique that allows for stitch-by-stitch programming of elastic properties and has applications in many fields ranging from soft robotics and wearable electronics to engineered tissue and architected materials. However, predicting these mechanical properties based on the stitch type remains elusive. Here we untangle the relationship between changes in stitch topology and emergent elasticity in several types of knitted fabrics. We combine experiment and simulation to construct a constitutive model for the nonlinear bulk response of these fabrics. This model serves as a basis for composite fabrics with bespoke mechanical properties, which crucially do not depend on the constituent yarn.

Reducing the carbon footprint of the textile sector: an overview of impacts and solutions

The clothing, footwear, and household textiles sectors play a significant role, providing employment opportunities on a global scale. However, they are also associated with a considerable consumption of natural resources, leading to high levels of water pollution and emissions of greenhouse gases, contributing to climate change. The carbon footprint (CF) of textiles depends generally on fabric types and production processes. Natural fibers such as cotton, wool, and silk, generally have a lower CF when compared to synthetic fabrics such as polyester and nylon, requiring more energy and chemicals during production. In addition, fabrics manufactured through eco-friendly methods, such as closed-loop systems and sustainable production processes, have a significantly lower CF than those produced using conventional means. Accordingly, there is a perceived need for comprehensive studies that investigate the environmental and climate implications of the textile sector. Considering these concerns, a study was undertaken on the topic, encompassing a literature review and data collection so as to present an overview of the environmental impacts and CF associated with the textile sector. The results from the research show that the resource consumption associated with the textile sector, particularly its CF, demands urgent action in order to reduce its impacts. Also, actionable measures are needed so as to reduce the CF of the textile industry. These are described in the paper, along with the obstacles that need to be overcome so as not only to reduce the CF of this sector, but also to pursue the objectives outlined in the sustainable development goals.

Синтез механизма привода ремиз

Introduction. Domestic enterprises in various industries use a variety of process equipment, including weaving machines. Modern weaving machines have several unique features, including a close relationship between technical condition, productivity, and product quality. Weaving machines are widely used in the textile industry in Russia and other countries. To produce cotton, silk, wool, linen, and other types of fabrics, appropriate machines are designed, including shuttle, shuttleless, pneumatic, and hydraulic machines. One of the most crucial parts of the machine is the heddle lifting mechanism, which determines the weave pattern and the quality of the fabric produced. The purpose of the work is to reduce the dimensions of the loom by changing the design parameters of the heddle lifting mechanism. The research methods are based on the theory of machines and mechanisms. They enable the development of a method for synthesizing the heddle lifting mechanism and designing a device with reduced dimensions. The paper presents the synthesis and analysis of the Assur group algorithm, which can determine the kinematic characteristics of the mechanism. Results and discussion. Following the proposed methodology, the mechanism design was modified by removing the fixing device from the lever mechanism operating area. This allowed for a reduction in interaxial distances and a change in the kinematic scheme. As a result of the new position of the fixed axes, some levers, the connecting rod, and the angle of the double-arm lever were also altered. The synthesis of the mechanism is proposed to begin with the last Assur group, setting it a specific value for the G-point motion equal to 75 mm. (motion of the fourth heddle shaft). As a limitation, the equality of arcs (chords) E´E = F´F ` was accepted. By assigning these values to the input element for the second-class first-type Assur group and bearing in mind the accepted conditions, the motions for point D were obtained. Thus, the value of the swing angle  of the roller shaft equal to 22.46° was obtained, which is 27.44 mm along the chord. Applying the interpolation principle, we found the initial motion value of 28 mm. Since the loom is planned to produce interlacing fabric patterns using 10 heddles, the design provides for a variable parameter that allows changing the motion of the heddles depending on their location in the depth of the machine. This role was assigned to the lever B03D. A cam pair synthesis was performed after determining the maximum and minimum values of the center of the roller motion. In total, 5 types of laws of motion were considered: straight-line, harmonic, double harmonic, power-law, cycloidal ones. For the center of the roller, the cycloidal law of motion was selected since it better corresponds to the specified conditions. The synthesis's accuracy was confirmed by the constructed cam profile and conducted kinematic studies for the Assur groups.

CNN Classifier Parameter Optimization with Genetic Algorithms: A Case Study of Indonesian Batik Patterns

Batik is one of Indonesia’s most famous and commonly encountered cultural heritage sites. Batik is a type of Indonesian specialty cloth where the pattern is drawn on the cloth using wax. The number of batik pattern varieties produced by Indonesia introduces challenges in recognizing and differentiating between batik patterns. Various previous works have been done to research how to use computer vision to recognize and differentiate between batik patterns. Some of the methods used in previous works involve convolutional neural networks; previous studies use pre-trained models or manually design the model, which may not be suitable for recognizing batik patterns. This study focuses on developing a convolutional neural network model optimized and designed automatically using genetic algorithms using more unique images than previous works. Genetic algorithms have been proven in previous works from other fields to produce better models compared to pre-trained and manually designed models. The experiment results show that a model design using genetic algorithms outperforms pre-trained models by a significant margin. The model automatically achieved an accuracy of 0.8654 with a parameter ∼1% of the VGG-19 model, whereas the VGG-19 model achieved an accuracy of 0.7596.

The Influence of Textile Type, Textile Weight, and Detergent Dosage on Microfiber Emissions from Top-Loading Washing Machines.

The use of washing machines to wash textiles gradually breaks down synthetic fibers like polyethylene terephthalate (PET) or polyester (PES) in diverse clothing materials, a process that is growing in notoriety because it generates microplastics (MPs). In this study, we investigated the emission of microfibers, including both microplastic fibers (MPFs) and natural fibers (MFs), from top-loading washing machines. Our investigation focused on four popular textiles with prevalent weave structures (plain, satin, and twill): (i) PES, (ii) tetron cotton (TC), (iii) chief value cotton (CVC), and (iv) cotton (CO) fabrics. This study also examined the effects of textile weight and detergent dosage on MF emissions. After washing, MFs were collected through filtration, and their concentrations were determined using micro-Fourier Transform Interferometry (μFTIR). The results showed varying concentrations of MFs in the washing effluent depending on the type of textile. Specifically, CVC exhibited the highest emission at 4022 particles/L, followed by TC, PES, and CO at 2844 particles/L, 2382 particles/L, and 2279 particles/L, respectively. The hydrophobic nature of PES makes this type of textile prone to rapid degradation in detergent-rich environments, leading to high MF emissions. Additionally, the mechanical properties of textiles, such as tensile and bending strengths, may play a crucial role in the generation of MFs in washing machines. Textiles made of CO with twill weaves demonstrated superior strength and correlated with lower emissions of MFs. In comparison, textiles made of CVC and satin weave exhibited lower mechanical properties, which could explain their high emissions of MFs. Finally, the MF emissions of textiles composed of PES and TC, which are plain weaved, could be attributed to their intermediate mechanical properties compared with those of CVC and CO.

FORMATION AND WAYS OF IMPROVEMENT OF CONTINUOUS TEXTILE ORNAMENT

The article discusses the main properties and features of continuous textile ornament, formed in the process of its changes during the change of historical periods. On the basis of concrete examples, the methods of its production are described, and the principles of its plastic organisation are outlined. Special attention is paid to the search for imagery in a continuous ornament based on the plastic connections of compositional construction. The text of the article analyses in detail the plant ornament of modernity, in which a continuous ornament is externally manifested in the form of an endless interweaving of leaves, shoots and flowers on the surface of the fabric, creating images of a blooming meadow, impenetrable swamps or jungles. The modern continuous ornament is considered in the context of stylistic changes of postmodernism and possibilities of computer technologies. The possibilities of improving continuous ornament by using new types of artificial and synthetic fabrics with effects arising from the peculiarities of weaving technologies are determined.

Novel Fabrication Method for Pressure-Sensing Polymeric Optical Fiber (POF) Fabric with Non-Direct-Contact Conductive System

Considering the current limitations of intelligent interactive in electronic integration and luminescent modes, this paper proposes a novel fabrication method for pressure-sensing POF fabrics with a non-direct-contact conductive system. In this system, conductive materials are concealed in the fabric structure to avoid direct contact with the human body. It was enabled by integrating layered weave structure, POFs, conductive yarns, and fabric patches within the fabric. Laser engraving was also applied on the fabric surface to achieve intricate pattern design. Experimental tests were conducted on sensing and luminescent properties of this POF fabric. The circuit module and software were developed to support the interactive function. The potential application of this fabric in the interior components of intelligent cockpits was envisioned. The research results show that the POF fabric integrated with conductive yarns and conductive fabric patches has good pressure sensitivity, enabling control of the fabric’s luminescent color by pressing the fabric surface. The non-direct-contact conductive system developed in this study offers the advantage of electrical signal stability by avoiding interference from human body resistance and grounding conditions. The development of this type of interactive luminescent textile holds promising prospects for application and development in various fields, including intelligent cockpits.

Analysis of Education and Knowledge’s Relationship on Worker Behavior in Waste Processing and Disposal in The Sasirangan Home Industry in Banjarmasin

Sasirangan is a typical cloth from the South Kalimantan which is produced by the Banjarist people in home industries. The production of sasirangan has a very positive impact on the welfare of Banjarist people. However, the processing and liquid waste resulting from the production process can have a negative impact on workers' health and the environment because it contains synthetic dyes and heavy metals. This is caused by poor worker behavior in processing and disposing of liquid waste from sasirangan cloth. Worker behavior can be related to worker education and knowledge. This research aims to analyze the relationship between education, knowledge and the behavior of sasirangan workers in processing and disposing of waste in the home-based sasirangan industry in Banjarmasin. This research is an analytical observational study with a cross sectional approach, carried out at 3 (three) sasirangan production locations: Sungai Jingah, Seberang Masjid Village and Surgi Mufti subdistricts. Sampling used a purposive sampling technique with a sample size of 30 workers. Data analysis was carried out using descriptive and statistical analysis using the Chi Square test with the alternative Fisher Exact Test. The results of data analysis show the p value of the education variables (p=0.032) and knowledge (p=0.049). There is a significant relationship between education and knowledge and worker behavior in processing and disposing of waste in the sasirangan home industry in Banjarmasin. This is in accordance with Lawrence Green's theory, the better the worker's education and knowledge, the better the worker's behavior. The existence of a significant relationship between education and knowledge and workers' behavior in processing and disposing of waste in the sasirangan home industry in Banjarmasin requires follow-up in the form of efforts to increase education and knowledge regarding the processing and disposal of sasirangan waste for workers in the sasirangan home industry in Banjarmasin.

FabricFolding: learning efficient fabric folding without expert demonstrations

AbstractAutonomous fabric manipulation is a challenging task due to complex dynamics and potential self-occlusion during fabric handling. An intuitive method of fabric-folding manipulation first involves obtaining a smooth and unfolded fabric configuration before the folding process begins. However, the combination of quasi-static actions like pick & place and dynamic action like fling proves inadequate in effectively unfolding long-sleeved T-shirts with sleeves mostly tucked inside the garment. To address this limitation, this paper introduces an enhanced quasi-static action called pick & drag, specifically designed to handle this type of fabric configuration. Additionally, an efficient dual-arm manipulation system is designed in this paper, which combines quasi-static (including pick & place and pick & drag) and dynamic fling actions to flexibly manipulate fabrics into unfolded and smooth configurations. Subsequently, once it is confirmed that the fabric is sufficiently unfolded and all fabric keypoints are detected, the keypoint-based heuristic folding algorithm is employed for the fabric-folding process. To address the scarcity of publicly available keypoint detection datasets for real fabric, we gathered images of various fabric configurations and types in real scenes to create a comprehensive keypoint dataset for fabric folding. This dataset aims to enhance the success rate of keypoint detection. Moreover, we evaluate the effectiveness of our proposed system in real-world settings, where it consistently and reliably unfolds and folds various types of fabrics, including challenging situations such as long-sleeved T-shirts with most parts of sleeves tucked inside the garment. Specifically, our method achieves a coverage rate of 0.822 and a success rate of 0.88 for long-sleeved T-shirts folding. Supplemental materials and dataset are available on our project webpage at https://sites.google.com/view/fabricfolding.

Autoclaved aerated concrete masonry wallettes strengthened using TRC overlay under out-of-plane load

The objective of this study is to assess the out-of-plane flexural responses of autoclaved aerated concrete (AAC) masonry wallettes externally strengthened with textile reinforced concrete (TRC) overlay. This method can be applied as a retrofitting technique for existing AAC masonry walls or as a constructive technique for new constructions. Sixteen AAC masonry specimens (shear span ratio = 5) were subjected to monotonic four-point bending loads. The design variables were the textile types and number of textile layers (reinforcement ratio). The load–deflection responses and corresponding flexural performances of specimens were assessed to quantify the influences of different test parameters. Results showed that the higher tensile strength of TRC would change the failure mode of AAC masonry wallettes from bending to shear. Finally, according to the different failure pattern observed in the tests, flexural and shear models available in the literatures were examined to assess their applicability to predict the load-carrying capacity of AAC masonry wallettes strengthened with TRC.

Fabric and Fluid Inclusions Characterization of a Stalagmite from Eastern Spain: A Precondition for Noble Gas Analysis by Step-Crushing Methodology

Fluid inclusions in stalagmites are becoming increasingly important for paleoclimate research. Within this framework, noble gas thermometry, based on noble gases dissolved in water from fluid inclusions, provides quantitative estimations of cave air paleotemperature. Two major issues of Noble Gas Temperature (NGT) determination on speleothems are (1) the potential lack of enough water for the analysis and (2) the presence of trapped gas not dissolved in water that can be released during the analysis from biphasic or all-gas fluid inclusions, as its contribution to the bulk noble gas signal can hinder NGT results. Although the step-crushing method helps to reduce the second issue, it also decreases the amount of water available for the calculations. In order to obtain reliable NGT results with low uncertainties, a major challenge is still to reach a balance between sufficient water for analysis and a small amount of “atmospheric” gas. The difficulty is that the extraction process cannot be standardized since it strongly depends on the type of sample. The objective of this work is to investigate how the characteristics of the speleothem can determine the adequacy of the extraction process. For this purpose, we consider a stalagmite from a Mediterranean cave that consists of columnar elongated calcite and contains a significant quantity of fluid inclusions, which suggests good potential for NGT analysis. Results, however, were poorly satisfactory. Trying to understand the source of the problems, an integrated study of petrography and petrophysical features was performed. The samples were found to be different depending on the stage of coalescence of crystals and thus separated into “open” and “closed” fabrics. Classic petrographic analysis and non-destructive (nuclear magnetic resonance) techniques were used to characterize the type and amount of fluid inclusions present in both types of fabrics. The study indicates that the closed fabric (total coalescence of calcite crystals) has most water trapped in water-filled, small intracrystalline fluid inclusions that usually contain very little gas. This fabric is very suitable for NGT determination, but since the amount of water is quite small, the sample should be crushed in only one step with a large number of beats to break all the inclusions. In contrast, samples with open fabric (partial coalescence of calcite crystals) contain a higher amount of water and, also, gas-filled large intercrystalline fluid inclusions. For this fabric, step-crushing of the sample is necessary. However, the low amount of water left for the second and third crushings could lead to flawed NGT results. Thus, we suggest modifying the method to get rid of part of the gas in the first crushing while leaving enough water for the following steps. This work shows the importance of characterizing speleothems and fluid inclusions, including their petrography and petrophysical characteristics, before starting NGT analysis, allowing the selection of the most favorable samples and the customization of the step-crushing procedure.

Dual circular complementary split ring resonator based metamaterial sensor with high sensitivity and quality factor for textile material detection

In this paper, a novel metamaterial sensor with excellent sensitivity and quality factor for microwave sensing applications is presented. The designed metamaterial sensor is assembled on a 1.575 mm thickness of low-cost dielectric substrate material (Rogers RT5880), and the copper is used as a resonator. Computer Simulation Technology version 2019 (CST-2019) software is employed to design and analyze the proposed metamaterial sensor. In addition, the Advanced Design System version 2016 (ADS 2016) software is used to validate the CST simulated model. Subsequently, the simulated results were validated using laboratory measurements. The optimized cell is small; its dimension is 10 × 10 mm2, and the obtained resonances are 3.85 and 6.85 GHz with notches of −26.29 and −40.03 dB, respectively. The textile material is detected by the resonance frequency change, and this frequency is dependent on the material’s permittivity values. To test the developed sensor’s sensing capabilities, three types of textiles—wool, fleece, and denim—are used. The effective medium ratio, sensitivity, and Q-factor of the structure are evaluated, and the obtained values are 8.96, 14.57%, and 345, respectively. The sensor for detecting textile materials works in the S and C bands. The resonances are shifted 530 MHz between the air and wool, 420 MHz between the air and fleece, and 640 MHz between the air and denim. The simulated outcomes and laboratory results almost matched. The projected sensor can be employed in the apparel sector to identify textile materials because it is small, inexpensive, has a high quality factor, and has high sensitivity.