Search Results (7,934)

P-wave velocity is a non-destructive test (NDT) used directly and indirectly in different disciplines. In recent years, portable equipment that can indirectly ascertain P-wave velocity has gained popularity for in situ measurements across multiple disciplines, including archeology, geology, and civil engineering. As the sample size effect has not been previously researched for portable indirect P-wave velocity (V_PI) measurement devices, this study researched the size-factor effect in magmatic rocks commonly used as building stones. Within this scope, 684 prism samples with 2 × 2, 3 × 3, 4 × 4, 5 × 5, 6 × 6, and 7 × 7 cm² square basal area and height of 17 cm, and 190 (38 × 5) cube samples with a side length of 7 cm were prepared from 38 different rocks (plutonic, volcanic, pyroclastic, and sedimentary). The variations in indirect P-wave velocity (V_PI) were experimentally determined on prismatic samples with different base areas. According to the results, the optimum sample cross-sectional area where the indirect P-wave velocity value did not change was determined to be 6 × 6 cm². Furthermore, the direct P-wave velocity (V_PD) values of the rocks were determined using cubic samples. The simple regression relationship between V_PD and V_PI measurements was investigated, and a very strong positive linear correlation (R² = 0.966) was identified. Full article

This Special Issue based on eight Articles/Reviews focuses on low-cost chemical sensor technologies, bio-chemical sensors, advanced active materials, sensing nanomaterials, sensor nodes, wireless sensor networks for chemical sensing, functional characterization, miniaturized transducers, advanced proofs of concept, and chemical detection applications. Promising advanced materials such as metal oxide nanostructures, carbon nanomaterials, composite heterostructures, multilayered coatings, and more have been explored for chemical sensing applications and environmental sustainability. Sensing solutions have been applied in the context of bio-chemical detection and gas monitoring, representing the current state of the art. Full article

Implementation remains a central challenge in urban policy, yet the knowledge formats designed to bridge the gap between policy goals and on-the-ground delivery remain under-examined. This study treats 250 UN-Habitat Best Practice reports not as proof of effectiveness but as a standardized genre through which local interventions are narrated, compressed, and made portable for replication. We extract three focal sections, namely Results, Lessons Learned, and Transferability, apply systematic thematic coding with 906 open codes consolidated into axial categories, and compute co-occurrence networks using Jaccard similarity and Lift to detect thematic bundles, holes, and silos within and across sections. Three findings emerge. First, the reporting repertoire narrows progressively, as mean thematic richness declines by 28.2% from Results to Transfers while concentration increases 4.2 times, with substantive dimensions such as governance, equity, sustainability, and evidence losing prevalence to circulation-oriented themes. Second, formal bundle detection yields zero qualifying pairs across all six matrices, indicating a loosely coupled reporting grammar anchored by generic silos rather than integrated implementation packages. Third, structural holes concentrate at the pipeline’s end, where infrastructure transfer and sustainability as transferable value are the most systematically disconnected themes. These patterns reveal a portability paradox in which the reporting format achieves institutional legibility, making practices comparable within a shared vocabulary, but progressively filters out the physical, evidentiary, and context-sensitive content that operational reproduction would require. Full article

Micro- and nanoplastic (MNP) pollution has emerged as a global environmental and health concern, driving the rapid development of sensor technologies for faster, more sensitive, and field-deployable detection. This review synthesizes recent advances in optical, electrochemical, and biosensor platforms for MNP analysis and compares their analytical performance and practical feasibility. Optical sensors, including plasmonic, spectroscopic, and colorimetric systems, enable label-free and often rapid detection with material discrimination capability, and are well-suited for screening applications, though they commonly exhibit higher detection limits and matrix interference. Electrochemical sensors demonstrate the highest analytical sensitivity overall, frequently reaching low µg L⁻¹ to ng mL⁻¹ levels, with strong potential for miniaturization and on-site deployment; performance is further enhanced by nanostructured electrodes, photoelectrochemical designs, and signal amplification strategies. Biosensors incorporating peptides, aptamers, enzymes, or engineered proteins provide improved polymer selectivity and enable targeted detection, but face challenges related to stability, cross-reactivity, and reproducibility in complex samples. Practically, portable electrochemical and simple optical colorimetric platforms are currently the most feasible for field use, while hybrid bio-electrochemical systems show the highest performance potential. Future research should prioritize robust selective recognition elements, antifouling interfaces, standardized validation protocols, mixed-polymer quantification models, and integration with machine learning to enable reliable, real-world MNP monitoring. Full article

The precise and timely diagnosis of grapevine diseases is paramount for ensuring food security and mitigating economic losses within the viticulture sector. While existing deep learning models offer high accuracy, their computational intensity and hardware requirements often hinder their use in portable or low-power field systems. This study addresses this gap by proposing GrapeLeafNet, a lightweight convolutional neural network optimized for efficient feature extraction. GrapeLeafNet introduces a strategic hybrid approach that combines the low parameter efficiency of models like SqueezeNet with the rapid feature propagation advantages offered by shallow architectures such as AlexNet. By eliminating the sequential processing latency caused by SqueezeNet’s 18-layer deep structure and the excessive 61-million-parameter memory burden of AlexNet, this model establishes a critical balance between low latency and high accuracy through its optimized 7-layer architecture. Characterized by an original integration of standard convolutional layers, batch normalization, and max pooling, GrapeLeafNet achieves high computational efficiency with only 1.6 million parameters and a 6.26 MB memory footprint. This structural optimization enhances deep feature hierarchies, enabling the model to focus on distinctive pathological signs within complex leaf patterns and maximize classification sensitivity by filtering out irrelevant features. The evaluation was conducted using the Niphad Grape Leaf Disease (NGLD) dataset, incorporating data augmentation to mitigate inherent class imbalances. Additionally, data augmentation techniques were employed to mitigate inherent class imbalances within the dataset. Experimental results demonstrate that GrapeLeafNet achieved 97.06% accuracy and a 94.77% F1-score on the original dataset, outperforming recent benchmarks by 2.46%. Following augmentation, performance reached 98.29% accuracy and a 98.16% F1-score, representing a 6.16% higher F1-score than contemporary models. GrapeLeafNet exhibits high robustness against asymmetric class distributions and establishes a significant performance margin over existing architectures. Its lightweight nature, combined with superior accuracy and F1-score metrics, makes it an ideal candidate for integration into mobile devices and real-time agricultural monitoring systems. Full article

This paper presents the Goddard RISC-V (GRV) a compact, portable, and highly customizable fault-tolerant 32-bit RISC-V processor, specifically designed for embedded space applications. The design integrates advanced fault-tolerance mechanisms to mitigate arbitrary Single Event Transient (SET) and Single Event Upset (SEU) errors while ensuring data integrity. Importantly, fault tolerance is achieved entirely at the design level, eliminating the need for SEU-hardened semiconductor processes, custom cell libraries, or specialized back-end tools. The implementation prioritizes portability and resource efficiency, enabling compatibility with various FPGA and ASIC technologies. This initiative aims to provide NASA with a suite of portable, modular, and scalable alternatives to proprietary solutions. These solutions are designed for broad adaptability across multiple platforms, such as compact scientific instruments, miniaturized deep-space technologies, CubeSats, control and automation systems, and other applications constrained by low-resource processing environments. Full article

Soil eco-enzymes (i.e., microbial extracellular enzymes) play essential roles in terrestrial nutrient cycling and support ecosystem services. In this regard, their activities serve as indicators of soil health. However, conventional spectrophotometric and microplate fluorometric assays are often limited by lengthy reaction procedures, relatively high reagent consumption, and insufficient compatibility with complex soil matrices. In this investigation, we developed a portable, centrifugally driven microfluidic chip for the rapid and sensitive determination of multiple soil extracellular enzyme activities. This integrated platform automated sample aliquoting, reagent metering, mixing, and sedimentation, enabling the parallel measurement of eight enzymes. Such system demonstrated precise liquid control via capillary valves and high optical uniformity (<5% fluorescence variation). 4-methylumbelliferone (MUF)-based calibration exhibited strong linearity (R² > 0.99) across diverse soil types. Compared with conventional microplate assays, the microfluidic method improved reproducibility (CV < 15%), enhanced the detection of weak fluorescence signals, and increased throughput while reducing reagent consumption. This field-ready platform provides a robust solution for standardized soil enzyme assessment and offers future potential for integration with AI-driven data analytics and large-scale ecological monitoring frameworks. Full article

This paper proposes a unified methodological framework for evaluating heterogeneous approaches to avatar-based sign language visualization. The study introduces a four-dimensional analytical framework based on four independent criteria: (A1) pipeline architecture and degree of automation, (A2) data and annotation requirements, (A3) portability across sign languages and domains, and (A4) integration and accessibility. The framework is applied to a comparative analysis of three dominant paradigms: (P1) notation → animation (e.g., HamNoSys), (P2) writing-based representation → animation (e.g., SignWriting), and (P3) keypoint-based animation and Artificial Intelligence (AI) methods. The comparative assessment shows that the differences between the paradigms are structural and reflect trade-offs among linguistic accuracy, automation level, scalability, and user accessibility, rather than the superiority of any one technology. Overall, the structured comparative framework (A1–A4) is applied for analyzing three paradigms of sign language avatar generation. It enables a systematic evaluation of architectural, data-related, and practical characteristics, highlighting key trade-offs between linguistic accuracy, scalability, and accessibility. Full article

How artificial intelligence (AI) reshapes the internal structure of firm-level skill demand remains largely uncharted. Using approximately 67 million online job postings from two major Chinese recruitment platforms (2019–2024), we construct firm-by-year potential AI exposure via semantic matching between AI patent texts and detailed occupation task descriptions, decompose exposure into displacement and augmentation components based on task routineness, and measure four skill-category demand shares and their within-category importance from job-description text, with identification from within-firm variation under firm and city-by-year fixed effects. Displacement and augmentation exposure exhibit opposing relationships with skill demand: displacement is negatively associated with the routine cognitive share, while augmentation is positively associated with the nonroutine analytical share. Both forms of exposure are associated with a de-coring pattern, a shallower and more dispersed skill portfolio with within-category importance diverging from share movements, concentrated among low entry-threshold, small firms. Reskilling policy should therefore emphasize portfolio breadth and portable competency frameworks rather than deeper single-track specialization, particularly for workers in small, lower-threshold firms. Full article

This study presents a multi-analytical investigation of two Baroque gilded terracotta sculptures—Hercules and the Nemean Lion (Hercules A) and Hercules and the Lernaean Hydra (Hercules B)—attributed to Lorenzo Vaccaro (1655–1706) and preserved at the Museo Civico Gaetano Filangieri in Naples. This research aimed to reconstruct the original manufacturing technique, characterize materials introduced by successive restoration interventions, and identify active degradation mechanisms. A systematic diagnostic approach integrating UV fluorescence imaging, digital optical microscopy, portable energy-dispersive X-ray fluorescence spectroscopy (EDXRF), Raman spectroscopy, Fourier-transform infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and spectrocolorimetry was applied. The original gilding system—comprising a ferruginous silico-aluminous terracotta substrate, a calcium sulfate ground, a lead-white imprimitura, an iron-rich bole, and a thin gold leaf—is consistent with documented Baroque mission gilding practices in Southern Italy. Analytical evidence further documented extensive non-original interventions, including copper-based artificial patination, bronze powder (porporina) integration, poly (vinyl acetate) adhesives, and acrylic protective coatings. Raman spectroscopy identified the in situ conversion of intentionally applied tenorite (CuO) to malachite (Cu₂CO₃(OH)₂) as an active degradation pathway. Spectrocolorimetric measurements quantified chromatic alterations of up to ΔE = 52 attributable to accumulated surface deposits. The proposed integrated methodology constitutes a replicable diagnostic framework for investigating gilded terracotta artefacts in museum collections. Full article

Palaeolithic engraved portable art provides a valuable record for investigating the technical aspects of Palaeolithic graphic production. In this study, we analyse an engraved portable art object from the Epigravettian sequence of Grotta Paglicci (southern Italy): a Bos primigenius mandible bearing a figurative representation interpreted as a waterbird, possibly a swan. The analysis combines 3D digital microscopy and geometric morphometrics to reconstruct the sequence of engraving gestures and to quantitatively characterise the morphological variability of the incisions. Archaeological engravings are compared with experimentally produced marks obtained using different lithic tools displaying similar trihedral active edges (burins and unretouched flakes). In addition, experimental and archaeological cut marks from the same Epigravettian context are included for comparative purposes. The results allow the reconstruction of the sequence of gestures involved in the production of the figure, revealing a structured execution comprising contour engraving, internal filling and the addition of secondary elements. Morphological and morphometric analyses show low variability among the engravings, pointing to a high degree of motor control throughout the engraving process. The predominance of U-shaped cross-sections in the archaeological sample, compared with the experimental engravings, is consistent with the use of a previously used and/or partially smoothed cutting edge. These results highlight the potential of integrated technological and morphometric approaches for investigating gestures, technical choices and operational organisation underlying the production of Upper Palaeolithic portable art. Full article

Millions of persons worldwide experience varying degrees of hearing loss, traditionally addressed through prosthetic solutions such as hearing aids and cochlear implants. However, a significant proportion of individuals cannot benefit from these technologies, cannot access them, or choose not to use them. In this context, non-prosthetic assistive technologies have emerged as a complementary paradigm, leveraging advances in sensing, artificial intelligence, and wearable computing to transform acoustic information into alternative perceptual representations rather than restoring auditory function. This survey provides a review of such systems, focusing on technologies that enhance environmental awareness, communication, and social interaction. Existing approaches are categorized along two main dimensions: the tasks they perform and the platforms on which they operate. Task-oriented analysis includes sound recognition (speech and non-speech), sound source localization, emotion recognition, sign language recognition, and related emerging functionalities. Platform-based analysis emphasizes wearable devices and mobile solutions enabling real-time and context-aware assistance. The survey further highlights key research trends, including real-time auditory scene analysis, portable processing, and artificial intelligence. It shows that recent studies increasingly demonstrate that combining auditory, visual, and haptic modalities improves robustness and usability in real-world conditions, particularly in noisy and dynamic environments. Finally, open challenges such as energy efficiency, latency, evaluation methodologies, and user acceptance are discussed. By synthesizing existing work and identifying open research directions, this survey aims to provide a structured foundation for future developments in intelligent, non-prosthetic assistive systems that redefine how auditory information is accessed and interpreted. Full article

Background: Accurate three-dimensional positioning of dental implants is critical for ensuring biomechanical stability, prosthetic passivity, and long-term clinical success. While computer-assisted navigation systems achieve high precision, their complexity and cost often limit accessibility. This study presents the development and preclinical experimental validation of a low-cost prototype designed to enhance angular accuracy in dental implant placement within a controlled 3D haptic simulation environment. Methods: A preclinical experimental design was implemented using a 3D haptic simulator (Virteasy, Montpellier, France). The prototype incorporated high-precision inertial measurement units (IMUs) and an Extended Kalman Filter (EKF) for real-time angular feedback. Ninety-seven simulated implant placements were performed—both freehand and with prototype assistance—under identical virtual conditions by a single experienced operator. Angular deviations in mesiodistal and buccolingual planes were recorded, combined into a composite 3D index, and analyzed using paired t-tests and linear mixed-effects models. The study was conducted in a controlled simulation environment, which does not fully replicate clinical conditions. Results: The prototype significantly reduced angular deviation from 13.49° to 2.99° in the mesiodistal plane (−77.8%) and from 13.56° to 5.59° in the buccolingual plane (−58.8%), achieving an overall 67% improvement in three-dimensional orientation (p < 0.001; Cohen’s d = 1.47). Agreement with an optical reference system (OptiTrack) was excellent (bias = +0.36°, RMSE = 0.39°). Intra-operator reliability exceeded 0.95 (ICC), confirming strong reproducibility and measurement stability. Conclusions: The proposed inertial sensor-based prototype achieved angular accuracy within the range reported for computer-guided systems while maintaining advantages of portability, low cost, and usability. Its integration into haptic simulators provides a valid tool for both educational and preclinical applications, offering real-time feedback that enhances spatial perception and psychomotor learning. Future clinical studies should validate its performance in cadaveric and patient-based contexts to determine its practical impact on surgical precision and implant success. Full article

Screw withdrawal force is a key mechanical property related to the load-bearing capacity and reliability of mechanically fastened timber structures. This study investigates the screw withdrawal performance of cross-laminated timber (CLT) manufactured from spruce, beech, and poplar, including both homogeneous and hybrid layups. The selected species represent materials with different densities and regional availability in Hungary. A one-component polyurethane adhesive was used for panel manufacturing. Screw withdrawal force was determined using two methods: a universal testing machine (UTM) and a manual portable device (MPD). The highest withdrawal forces were observed in beech-based configurations, while the lowest values were measured for spruce. Poplar-based configurations demonstrated intermediate but competitive performance, exceeding the reference spruce values. Statistical evaluation confirmed a significant effect of layup configuration on withdrawal resistance. The MPD measurements were on average approximately 9% higher than UTM results, indicating a consistent and quantifiable inter-method difference. The results demonstrate that hybrid CLT configurations can be optimized by combining species of different densities and that portable testing methods provide reliable estimates of withdrawal performance. These findings contribute to the understanding of connection behavior in hybrid CLT and support the practical application of semi-destructive testing methods for in-situ assessment. Full article

Disinfection is essential to ensure safe drinking water and hygienic conditions in environmental, industrial, and clinical settings. However, conventional methods for monitoring free residual chlorine are often laboratory-based and not suited for decentralized analysis. Here, we report a novel paper-based colorimetric biosensing platform that translates the ISO 7393-2 standard, a method based on the reaction of chlorine with N,N-diethyl-p-phenylenediamine (DPD), into a portable and user-friendly format. The proposed device integrates the DPD chemistry within a paper architecture, enabling reagent-free operation at the point of need. The sensor provides a rapid visual readout that is detectable by the naked eye, while quantitative analysis is achieved within 3 min through smartphone-based image acquisition. This work constitutes the first implementation of the ISO standard in a portable paper-based format suitable for both environmental and clinical matrices. The sensor provided a detection limit of 12 μM for sodium hypochlorite and was successfully validated in real samples, including bottled water and exhaled breath condensate, with satisfactory recoveries. Furthermore, the stability of the paper-based sensor was assessed under storage conditions of 4 °C and room temperature (23 °C), demonstrating excellent performance over 30 days in both cases, indicating that refrigeration is not required for maintaining sensor performance. Full article