Search Results (69)

This article puts Christina Sharpe’s theories of “the wake” and “wake work” and Kevin Quashie’s theory of “Black aliveness” in conversation with Peace Peloton, a nonprofit organization promoting Black businesses and community through the activities of cycling and neighborhood events. The author reads Peace Peloton’s gatherings and the draft of turbulent air produced by their pelotons, or groups of bicyclists in motion, as radical Black performances and what Sharpe calls “wake work.” Acts of resistance and resilience enacted in the aftermath—the wake—of the Transatlantic slave trade, Peace Peloton’s rides and gatherings as “wake work” reject the ontological othering of Black bodies and being and dynamize what it means to be in a wake. Enacting Quashie’s sense of “worldmaking,” Peace Peloton’s “wake work” challenges presumptions of the outdoors and road cycling as white spaces, for white people, and reclaims for Black worldmaking once majority Black, now gentrified spaces of commerce and leisure. An interdisciplinary look into a cultural expression that has heretofore gone unexamined, this chapter weaves into its application of contemporary Afrodiasporic theory the history of redlining, cycling physics, writing on Blackness and the outdoors, Alexis Pauline Gumb’s short story “Bluebellow,” and Fedeke N. Castor’s Spiritual Citizenship: Transnational Pathways from Black Power to Ifa in Trinidad. It is through this ambitious and innovative interpretative lens that the author illuminates Peace Peloton’s “wake work” and Black worldmaking and situates them within the broader corpus of Afrodiasporic literature and cultural expressions. Full article

The firing of traditional gray pottery relies on complex physicochemical reactions governing its color, dimensional accuracy, and structural stability. Unclear kiln-transformation mechanisms restrict standardized and digital production of this Chinese intangible cultural heritage. Herein, direct ink writing (DIW) was used to fabricate Hejin gray pottery green bodies from local ternary raw materials. Thermodynamic calculations, TG–DTG/DSC, XRD, XRF, and atmosphere-controlled firing tests were combined to reveal coupled phase evolution and reduction color-forming mechanisms during sintering. Two interrelated kiln-transformation processes were identified. First, sequential mineral reconstruction occurs at four critical temperatures: free water loss at 119.8 °C, two-stage dehydroxylation of hydrous silicates at 270.5 °C and 767.9 °C, and CaCO₃ decomposition at 547.9 °C. Uneven shrinkage and gas release at these temperatures induce cracking, blistering, and deformation of printed bodies. Micron-sized CaCO₃ (equivalent radius ≈ 1.31 μm) exhibits high surface energy and significantly reduces its decomposition temperature, consistent with experimental observations. Second, reducing atmospheres trigger competitive phase formation. Distinct from the conventional Fe₂O₃ → Fe₃O₄ → FeO reduction pathway, Fe oxides preferentially react with abundant Al₂O₃ to form thermodynamically stable FeAl₂O₄ spinel, yielding uniform celadon-gray tones. The final color is nearly independent of 20–90 vol% CO, and air-isolated cooling below 600 °C is mandatory to prevent secondary oxidation and reddening. This work establishes a thermodynamic framework for DIW-printed Hejin gray pottery kiln transformation, clarifies microscale defect and color-evolution mechanisms, and offers theoretical guidance for atmosphere-controlled firing and digital mass production of heritage ceramics. Full article

This study develops an automatic dispatch system for quadrotor UAVs that integrates air-writing gesture recognition with a graphical user interface (GUI). The DJI RoboMaster quadrotor UAV (DJI, Shenzhen, China) was employed as the experimental platform, combined with an ESP32 microcontroller (Espressif Systems, Shanghai, China) and the RoboMaster SDK (version 3.0). On the Python (version 3.12.7) platform, a GUI was implemented using Tkinter (version 8.6), allowing users to input addresses or landmarks, which were then automatically converted into geographic coordinates and imported into Google Maps for route planning. The generated flight commands were transmitted to the UAV via a UDP socket, enabling remote autonomous flight. For gesture recognition, a Raspberry Pi integrated with the MediaPipe Hands module was used to capture 16 types of air-written flight commands in real time through a camera. The training samples were categorized into one-dimensional coordinates and two-dimensional images. In the one-dimensional case, X/Y axis coordinates were concatenated after data augmentation, interpolation, and normalization. In the two-dimensional case, three types of images were generated, namely font trajectory plots (T-plots), coordinate-axis plots (XY-plots), and composite plots combining the two (XYT-plots). To evaluate classification performance, several machine learning and deep learning architectures were employed, including a multi-layer perceptron (MLP), support vector machine (SVM), one-dimensional convolutional neural network (1D-CNN), and two-dimensional convolutional neural network (2D-CNN). The results demonstrated effective recognition accuracy across different models and sample formats, verifying the feasibility of the proposed air-writing trajectory framework for non-contact gesture-based UAV control. Furthermore, by combining gesture recognition with a GUI-based map planning interface, the system enhances the intuitiveness and convenience of UAV operation. Future extensions, such as incorporating aerial image object recognition, could extend the framework’s applications to scenarios including forest disaster management, vehicle license plate recognition, and air pollution monitoring. Full article

Waveguide bends are critical components for compact routing in integrated photonic circuits, yet their design in air-clad polymer waveguides fabricated by two-photon polymerization direct laser writing (2PP-DLW) is challenging due to multimode behavior. We address this by systematically modeling Bézier-shaped 90° bends and S-bends using a variational FDTD solver, exploring bend span, curvature, and waveguide dimensions. Our results show that smaller waveguides (widths 2–4 µm) and lower Bézier parameters (B = 0–0.2) consistently yield superior performance, enabling sharper bends with minimal loss. For 90° bends, spans as small as 20–30 µm achieve near-unity transmission, while for S-bends, aspect ratios below 1 are feasible, allowing highly compact layouts. Although all configurations transmit energy to the fundamental mode, wider waveguides exhibit stronger higher-order mode excitation and greater sensitivity to fabrication imperfections. Smaller waveguides reduce these effects but approach the resolution limits of 2PP-DLW. Thus, a 2 µm wide waveguide represents an optimal compromise between fabrication feasibility and optical performance. Experimental demonstrations confirm the practicality of these design rules, illustrating trends predicted by simulations. These findings establish clear guidelines for designing low-loss, space-efficient 3D photonic circuits and highlight the critical role of simulation-driven optimization in fully exploiting 2PP-DLW technology, while providing deeper insight for future device architectures. Full article

WO₃-based electrochemical transistors (ECTs) are recognized as candidates for three-terminal memristors due to their high on–off ratio, long retention time, and rapid switching speed. However, their patterned fabrication often relies on complex vacuum systems or extreme processing conditions, hindering cost-effective scalability. Here, we developed a novel wet etching technique integrated with sol–gel-derived WO₃ channels, enabling ambient-air fabrication of Nafion-WO₃ ECTs. The wet-etched devices achieve an on–off ratio of ~10⁵, surpassing unetched and dry-etched counterparts by orders of magnitude. Furthermore, they exhibit exceptional paired-pulse facilitation and long-term stability, maintaining 12 distinct conductance states for 10³ s, and an on–off ratio of ~10² over 25 read–write cycles. XPS result shows higher W⁵⁺ content and M-O-H bond proportion for wet-etched devices, revealing an optimized interface, with enhanced H⁺ injection efficiency. The simulated artificial neural network using this wet-etched ECT shows ~97% recognition accuracy for handwritten numerals. This approach offers a novel patterning strategy for developing cost-effective, high-performance neuromorphic devices. Full article

Biological surfaces with physical discontinuity or chemical heterogeneity possess special wettability in the form of anisotropic wetting behavior. However, there are several challenges in designing and manufacturing samples with anisotropic wettability. This study investigates the fabrication of PTFE/PDMS grid membranes using Direct Ink Writing (DIW) 3D printing for oil–water separation applications. The ink’s rheological properties were optimized, revealing that a 60% PTFE/PDMS composite exhibited the ideal shear-thinning behavior for 3D printing. Our research investigated the interplay between various printing parameters like the extrusion air pressure, layer thickness, feed rate, and printing speed, which were found to influence the filament dimensions, pore sizes, and hydrophobic properties of the grid membrane. Two distinct grid structures were analyzed for their wettability and anisotropic hydrophobic characteristics. The grid membranes achieved up to 100% oil–water separation efficiency in specific configurations. Separation efficiency was shown to be dependent on factors like intrusion pressure, grid architecture, and the number of layers. This study underscores the potential of DIW 3D printing in creating specialized surfaces with controlled wettability, particularly superhydrophobicity and anisotropy, paving the way for advanced environmental applications such as efficient oil–water separation. Full article

In this work, we propose a fiber Bragg grating (FBG)-based sensor for curvature measurements. Two gratings are inscribed through the protective coating in a specialty optical fiber using focused femtosecond laser pulses and point-by-point direct writing technology. One grating is inscribed on the central core adjacent to an air channel, while the other is inscribed on the eccentric core. The bending characteristics of the two-core fiber strongly depend on the bending direction due to the asymmetry of the fiber cores. A bending sensitivity of 58 $\mathrm{p}\mathrm{m}/{\mathrm{m}}^{-1}$ is achieved by the FBG in the eccentric fiber core over the curvature range of 0–50 ${\mathrm{m}}^{-1}$. Temperature and humidity cross-sensitivity could be significantly reduced by analyzing the differences in peak shifts between the two gratings. The sensor features a large sensing range and good robustness due to the presence of its protective buffer coating, which makes it a good candidate for curvature sensing in engineering fields. Full article

Learning to write the Arabic alphabet is crucial for Arab children’s cognitive development, enhancing their memory and retention skills. However, the lack of Arabic language educational applications may hamper the effectiveness of their learning experience. To bridge this gap, SamAbjd was developed, an interactive web application that leverages deep learning techniques, including air-writing recognition, to teach Arabic letters. SamAbjd was tailored to user needs through extensive surveys conducted with mothers and teachers, and a comprehensive literature review was performed to identify effective teaching methods and models. The development process involved gathering data from three publicly available datasets, culminating in a collection of 31,349 annotated images of handwritten Arabic letters. To enhance the dataset’s quality, data preprocessing techniques were applied, such as image denoising, grayscale conversion, and data augmentation. Two models were experimented with using a convolution neural network (CNN) and Visual Geometry Group (VGG16) to evaluate their effectiveness in recognizing air-written Arabic characters. Among the CNN models tested, the standout performer was a seven-layer model without dropout, which achieved a high testing accuracy of 96.40%. This model also demonstrated impressive precision and F1-score, both around 96.44% and 96.43%, respectively, indicating successful fitting without overfitting. The web application, built using Flask and PyCharm, offers a robust and user-friendly interface. By incorporating deep learning techniques and user feedback, the web application meets educational needs effectively. Full article

The aim of the entry was to write a substantial contribution that analyses and compares the biological pollution of indoor air, the possibilities of its assessment and the control methods. In addition, the aim of our entry was to review journals covering both commercial and residential buildings. By analysing the above topics from the existing articles, one can have the impression that air pollution is one of the most important problems that need to be solved in the modern world. Adequate air quality is important for maintaining human health, affects the health of ecosystems, including animals, and determines crop production. With the development of civilisation, the quality of air in the atmosphere and indoors is constantly deteriorating. Indoor air pollution can be divided into physical (e.g., noise, inadequate lighting, ionising radiation), chemical (e.g., tobacco smoke, household products) and microbiological (bacteria, viruses, fungi and products of their metabolism) factors. Each of these factors can have a negative impact on a person’s health or cause premature death. The entry deals with indoor air pollution, focussing on biological pollutants. It compares different methods available and describes the method of sampling to analyse indoor air pollution and ways to reduce it. Full article

This text discusses the synthesis of copper nanoparticles via a liquid phase reduction method, using ascorbic acid as a reducing agent and CuSO₄·5H₂O as the copper source. The synthesized copper nanoparticles are small in size, uniformly distributed, are mostly between 100–200 nm with clear boundaries between particles, and exhibit excellent dispersibility, making them suitable for metal conductive inks. 1. The copper nanoparticles are analyzed for good antioxidation properties, because their surface is coated with PVP and ascorbic acid. This organic layer somewhat isolates the particle surface from contact with air, preventing oxidation, and accounts for about 9% of the total weight. 2. When the prepared copper nanoparticles are spread on a polyimide substrate and sintered at 250 °C for 120 min, the resistivity can be as low as 23.5 μΩ·cm, and at 350 °C for 30 min, the resistivity is only three times that of bulk copper. 3. The prepared conductive ink, printed on a polyimide substrate using a direct writing tool, shows good flexibility before and after sintering. After sintering at 300 °C for 30 min and connecting the pattern to a circuit with a diode lamp, the diode lamp is successfully lit. 4. This method produces copper nanoparticles with small size, good dispersion, and antioxidation capabilities, and the conductive ink prepared from them demonstrates good conductivity after sintering. Full article

The rising Greenhouse Gas (GHG) emissions stemming from the extensive use of automobiles across the globe represent a critical environmental challenge, contributing significantly to phenomena such as global warming and the deterioration of air quality. To address these challenges, there is a critical need for research and development in electric vehicles (EVs) and their associated charging infrastructure, including off-board and on-board chargers (OBCs). This paper aims to bridge the gaps in existing review literature by offering a comprehensive review of both integrated and non-integrated OBCs for EVs, based on the authors’ knowledge at the time of writing. The paper begins by outlining trends in the EV market, including voltage levels, power ratings, and relevant standards. It then provides a detailed analysis of two-level and multi-level power converter topologies, covering AC-DC power factor correction (PFC) and isolated DC-DC topologies. Subsequently, it discusses single-stage and two-stage non-integrated OBC solutions. Additionally, various categories of integrated OBCs (iOBCs) are explored, accompanied by relevant examples. The paper also includes comparison tables containing technical specifications and key characteristics for reference and analysis. Full article

Health Improvement Through Employee Control (HITEC) is a 16-year program directed toward the health of corrections personnel and developed through the application of the principles of Participatory Action Research (PAR) and participatory ergonomics. Its impetus has always been the adverse health status of the corrections workforce: early mortality, depression, obesity, and hypertension. The HITEC program trained small “Design Teams” (DTs) of front-line personnel in participatory methods for intervention design for health improvement and organizational change in line with the Total Worker Health^® principles. Periodic surveys and physical testing were introduced for longitudinal assessments. Comparative interventions at comparable sites included DTs without a priori assignation, problem-focused kaizen effectiveness teams (KETs), and bargaining unit-centered DTs. DT resilience and the replacement of members who transferred facilities or retired was aided by novel cooperative administrative structures. DT-generated interventions included stress lounges, changes in critical event report writing, a joint program with trained inmates to improve air quality, and training in staff mental health and sleep behavior. A specialized peer-to-peer Health Mentoring Program (HMP) paired new officers with trained peers. Many interventions and program features were institutionalized, thus improving prospects for self-supporting program longevity. Participatory interventions designed and supported by the corrections workforce were found to be both feasible and exceptionally effective. Full article

Handwriting abnormalities in children with attention deficit hyperactivity disorder (ADHD) have sometimes been reported both (i) at the product level (i.e., quality/legibility of the written trace and speed of writing) and (ii) at the process level (i.e., dynamic and kinematic features, such as on-paper and in-air durations, pen pressure and velocity peaks, etc.). Conversely, other works have failed to reveal any differences between ADHD and typically developing children. The question of the presence and nature of handwriting deficits in ADHD remains open and merits an in-depth examination. The aim of this systematic review was, therefore, to identify studies that have investigated the product and/or process of handwriting in children with ADHD compared to typically developing individuals. This review was conducted and reported in accordance with the PRISMA statement. A literature search was carried out using three electronic databases. The methodological quality of the studies was systematically assessed using the Critical Appraisal Skills Program (CASP) criteria. Twenty-one articles were identified. Of these, 17 described handwriting quality/legibility, 12 focused on speed and 14 analyzed the handwriting process. All the studies (100%) with satisfactory methodology procedures reported an impaired product (for quality/legibility) and 91.7% reported abnormalities in process, while only 25% evidenced a difference in the speed of production. Most importantly, the studies differed widely in their methodological approaches. Substantial gaps remain, particularly with regard to ascertaining comorbidities, ADHD subtypes and the medical status of the included children. The lack of overall homogeneity in the samples calls for higher quality studies. We conclude with recommendations for further studies. Full article

The features or actuation behaviors of nature’s creatures provide concepts for the development of biomimetic soft bioactuators/robots with stimuli-responsive capabilities, design convenience, and environmental adaptivity in various fields. Mimosa pudica is a mechanically responsive plant that can convert pressure to the motion of leaves. When the leaves receive pressure, the occurrence of asymmetric turgor in the extensor and flexor sides of the pulvinus from redistributing the water in the pulvinus causes the bending of the pulvinus. Inspired by the actuation of Mimosa pudica, designing soft bioactuators can convert external stimulations to driving forces for the actuation of constructs which has been receiving increased attention and has potential applications in many fields. 4D printing technology has emerged as a new strategy for creating versatile soft bioactuators/robots by integrating printing technologies with stimuli-responsive materials. In this study, we developed a hybrid ink by combining gelatin methacryloyl (GelMA) polymers with iron oxide nanoparticles (IONs). This hybrid ION-GelMA ink exhibits tunable rheology, controllable mechanical properties, magnetic-responsive behaviors, and printability by integrating the internal metal ion-polymeric chain interactions and photo-crosslinking chemistries. This design offers the inks a dual crosslink mechanism combining the advantages of photocrosslinking and ionic crosslinking to rapidly form the construct within 60 s of UV exposure time. In addition, the magnetic-responsive actuation of ION-GelMA constructs can be regulated by different ION concentrations (0–10%). Furthermore, we used the ION-GelMA inks to fabricate a Mimosa pudica-like soft bioactuator through a mold casting method and a direct-ink-writing (DIW) printing technology. Obviously, the pinnule leaf structure of printed constructs presents a continuous reversible shape transformation in an air phase without any liquid as a medium, which can mimic the motion characteristics of natural creatures. At the same time, compared to the model casting process, the DIW printed bioactuators show a more refined and biomimetic transformation shape that closely resembles the movement of the pinnule leaf of Mimosa pudica in response to stimulation. Overall, this study indicates the proof of concept and the potential prospect of magnetic-responsive ION-GelMA inks for the rapid prototyping of biomimetic soft bioactuators/robots with untethered non-contact magneto-actuations. Full article

Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain the best model parameters and outcomes. Several machine learning methods (e.g., neural networks (NNs), random forest (RF), K-nearest neighbours (KNN), and support vector machine (SVM)) are applied to deep features extracted from deep convolutional neural networks (CNNs), such as VGG16, VGG19, and SqueezeNet. Our study uses the AHAWP dataset, which consists of diverse writing styles and hand sign variations, to train and evaluate the models. Prepossessing schemes are applied to improve data quality by reducing bias. Furthermore, OCR character (OCR) methods are integrated into our model to isolate individual letters from continuous air-written gestures and improve recognition results. The results of this study showed that the proposed model achieved the best accuracy of 88.8% using NN with VGG16. Full article