Search Results (227)

In radio frequency identification (RFID), differences in spectrum policies and tag misreading in different countries are the two main issues that limit its application. To solve these problems, this article proposes a composite right/left-handed transmission line (CRLH-TL)-based reconfigurable antenna for ultra-high frequency near-field and far-field RFID reader applications. The CRLH-TL is achieved using a periodically capacitive gap-loaded parallel plate line. By deploying the CRLH-TL operating at zeroth-order resonance, a loop antenna with in-phase radiating current is obtained, which contributes to a strong and uniform H-field and a horizontally polarized omnidirectional radiation pattern. By introducing additional tunable components, frequency and reading range reconfigurabilities are enabled. The frequency tuning range is from 833 MHz to 979 MHz, which covers the worldwide UHF RFID band. Moreover, each operation mode has a narrow frequency band, which means it can operate without violating different countries’ radio frequency policy and reduce the design difficulty of designing multiple versions of a reader. Both the near-field interrogation zone and maximum far-field reading distance of the antenna are adjustable. The near-field interrogation zone is 400 mm × 400 mm × 50 mm and can be further confined. The tuning range for far-field reading distance is from 2.71 m to 0.35 m. Full article

Convolutional neural networks (CNNs) are increasingly recognized as an important and potent artificial intelligence approach, widely employed in many computer vision applications, such as facial recognition. Their importance resides in their capacity to acquire hierarchical features, which is essential for recognizing complex patterns. Nevertheless, the intricate architectural design of CNNs leads to significant computing requirements. To tackle these issues, it is essential to construct a system based on field-programmable gate arrays (FPGAs) to speed up CNNs. FPGAs provide fast development capabilities, energy efficiency, decreased latency, and advanced reconfigurability. A facial recognition solution by leveraging deep learning and subsequently deploying it on an FPGA platform is suggested. The system detects whether a person has the necessary authorization to enter/access a place. The FPGA is responsible for processing this system with utmost security and without any internet connectivity. Various facial recognition networks are accomplished, including AlexNet, ResNet, and VGG-16 networks. The findings of the proposed method prove that the GoogLeNet network is the best fit due to its lower computational resource requirements, speed, and accuracy. The system was deployed on three hardware kits to appraise the performance of different programming approaches in terms of accuracy, latency, cost, and power consumption. The software programming on the Raspberry Pi-3B kit had a recognition accuracy of around 70–75% and relied on a stable internet connection for processing. This dependency on internet connectivity increases bandwidth consumption and fails to meet the required security criteria, contrary to ZYBO-Z7 board hardware programming. Nevertheless, the hardware/software co-design on the PYNQ-Z2 board achieved an accuracy rate of 85% to 87%. It operates independently of an internet connection, making it a standalone system and saving costs. Full article

The COVID-19 pandemic has significantly impacted globalization by disrupting the course of international economic integration, reducing interpersonal interaction and communication, and lessening the significance of global governance and political interactions. This unprecedented event has altered global supply chains, MNEs’ operations and FDI, and trade patterns, and it has favored protectionist and border policies. Meanwhile, travel restrictions and social-distancing measures reduced human mobility and hindered intercultural exchanges. This study explores the short-term and long-term effects of the COVID-19 pandemic on economic globalization while also reflecting on its implications for social and political globalization. The analysis underlines that the COVID-19 pandemic has encouraged many governments to assess their strategies vis-à-vis globalization by seeking a certain equilibrium between global engagement, regional retreat, and national seclusion. Despite the adverse implications, some positive outcomes have emerged via the COVID-19-induced digital transformation and the reconfiguration of the global supply chains to improve resilience against future exogenous shocks. This pandemic exposed the shortcomings of the current global system and emphasized the necessity for a post-COVID-19 “re-designed” globalization to mitigate anti-globalization sentiments and expand benefits across countries/geo-economic regions and different segments of society. Full article

We present a novel photoreconfigurable metasurface designed for independent and efficient control of electromagnetic waves with identical incident polarization and frequency across the entire spatial domain. The proposed metasurface features a three-layer architecture: a top layer incorporating a gold circular split ring resonator (CSRR) filled with perovskite material and dual C-shaped perovskite resonators; a middle layer of polyimide dielectric; and a bottom layer comprising a perovskite substrate with an oppositely oriented circular split ring resonator filled with gold. By modulating the intensity of a laser beam, we achieve autonomous manipulation of incident circularly polarized terahertz waves in both transmission and reflection modes. Simulation results demonstrate that the metasurface achieves a cross-polarized transmission coefficient of 0.82 without laser illumination and a co-polarization reflection coefficient of 0.8 under laser illumination. Leveraging the geometric phase principle, adjustments to the rotational orientation of the reverse split ring and dual C-shaped perovskite structures enable independent control of transmission and reflection phases. Furthermore, the proposed metasurface induces a +1 order orbital angular momentum in transmission and +2 order in reflection, facilitating beam deflection through metasurface convolution principles. Imaging using metasurface digital imaging technology showcases patterns “NUIST” in reflection and “LOONG” in transmission, illustrating the metasurface design principles via the proposed metasurface. The proposed metasurface’s capability for full-space control and reconfigurability presents promising applications in advanced imaging systems, dynamic beam steering, and tunable terahertz devices, highlighting its potential for future technological advancements. Full article

Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. Consequently, there remains significant potential for further exploration into improving the efficiency, latency, and power consumption of neural network accelerators across diverse computational scenarios. This paper investigates three key techniques for hardware acceleration of sparse neural networks. The main contributions are as follows: (1) Most neural network inference tasks are typically executed on general-purpose computing devices, which often fail to deliver high energy efficiency and are not well-suited for accelerating sparse convolutional models. In this work, we propose a specialized computational circuit for the convolutional operations of sparse neural networks. This circuit is designed to detect and eliminate the computational effort associated with zero values in the sparse convolutional kernels, thereby enhancing energy efficiency. (2) The data access patterns in convolutional neural networks introduce significant pressure on the high-latency off-chip memory access process. Due to issues such as data discontinuity, the data reading unit often fails to fully exploit the available bandwidth during off-chip read and write operations. In this paper, we analyze bandwidth utilization in the context of convolutional accelerator data handling and propose a strategy to improve off-chip access efficiency. Specifically, we leverage a compiler optimization plugin developed for Vitis HLS, which automatically identifies and optimizes on-chip bandwidth utilization. (3) In coefficient-based accelerators, the synchronous operation of individual computational units can significantly hinder efficiency. Previous approaches have achieved asynchronous convolution by designing separate memory units for each computational unit; however, this method consumes a substantial amount of on-chip memory resources. To address this issue, we propose a shared feature map cache design for asynchronous convolution in the accelerators presented in this paper. This design resolves address access conflicts when multiple computational units concurrently access a set of caches by utilizing a hash-based address indexing algorithm. Moreover, the shared cache architecture reduces data redundancy and conserves on-chip resources. Using the optimized accelerator, we successfully executed ResNet50 inference on an Intel Arria 10 1150GX FPGA, achieving a throughput of 497 GOPS, or an equivalent computational power of 1579 GOPS, with a power consumption of only 22 watts. Full article

This study explores the intricate relationship between Baroque religious architecture and the transformation of the territory in Paredes de Coura, Portugal. Between the second half of the 17th century and the first half of the 19th century, Paredes de Coura, located in northern Portugal, gradually transformed its religious spaces and buildings. Parish communities and private initiatives, driven by a deep religious motivation and favourable conjuncture factors, rebuilt, enlarged, and built dozens of chapels and churches from scratch, mostly in Baroque configuration but with differentiating characteristics. This process gradually gave the rural landscape a unique singularity, i.e., a transformation of significant cultural and historical importance. Numerous artisans constructed these buildings and filled their interior spaces with works of sacred art, mainly carved altars, originating primarily from Paredes de Coura and Alto-Minho municipalities. This systematic study, based on the analysis of contemporary documentation of religious buildings and extensive fieldwork, ensures the thoroughness and reliability of our research and aims to disseminate the data related to this process, presenting an overall reading of religious architecture and seeking to understand the reasons which were at the base of the construction of such a large number of temples in the municipality of Paredes de Coura during this period that changed the territory. This also highlights how Baroque religious architecture was a product of artistic and spiritual ambitions and a powerful agent of territorial reconfiguration, affecting settlement patterns, infrastructure, and social hierarchy. The legacy of these transformations continues to influence the region’s cultural landscape today. Full article

A core dielectric cylindrical rod wrapped in a dielectric circular pipe whose outer surface is enclosed by a helical conducting strip grating that is skewed along the axial direction is herein analyzed using the asymptotic strip boundary conditions along with classical vector potential analysis. Targeted for use as a cylindrical holographic antenna, the resultant field solutions facilitate the aperture integration of the equivalent cylindrical surface currents to obtain the radiated far fields. As each rod section of a certain skew angle exhibits a distinct modal attribute; this topology allows for the distribution of the cylindrical surface impedance via the effective refractive index to be modulated, as in gradient-index (GRIN) materials. Beam steering can also be achieved by altering the skew angle via mechanical sliding motion while leaving the cylindrical structure itself unchanged, as opposed to impractically reconfiguring the geometrical and material parameters of the latter to attain each new beam direction. The results computed by the program code based on the proposed technique in terms of the modal dispersion and radiation patterns are compared with simulations by a software solver. Manufactured prototypes are measured, and experimentally acquired dispersion diagrams and radiation patterns are favorably compared with theoretical predictions. Full article

In order to implement multiple electromagnetic (EM) wave front control, a reconfigurable multifunctional metasurface (RMM) has been investigated in this paper. It can meet the requirements for 6G communication systems. Considering the full-space working modes simultaneously, both reflection and transmission modes, the flexible transmission-reflection-integrated RMM with p-i-n diodes and anisotropic structures is proposed. By introducing a 45°-inclined H-shaped AS and grating-like micro-structure, the polarization conversion of linear to circular polarization (LP-to-CP) is achieved with good angular stability, in the transmission mode from top to bottom. Meanwhile, reflection beam patterns can be tuned by switching four p-i-n diodes to achieve a 1-bit reflection phase, which are embedded in the bottom of unit cells. To demonstrate the multiple reconfigurable abilities of RMMs to regulate EM waves, the RMMs working in polarization conversion mode, transmitted mode, reflected mode, and transmission-reflection-integrated mode are designed and simulated. Furthermore, by encoding two proper reflection sequences with $13\times 13$ elements, reflection beam patterns with two beams and four beams can be achieved, respectively. The simulation results are consistent with the theoretical method. The suggested metasurface is helpful for radar and wireless communications because of its compact size, simple construction, angular stability, and multi-functionality. Full article

The multifunctionality model is receiving more and more attention from policymakers as a result of recent initiatives to build more resilient and sustainable food systems as well as the potential for increased farm revenue. This paper explores the role of multifunctional farming in the Italian agriculture viewed through the lens of an entrepreneurial strategy grounded on-farm diversification. Farm diversification strategies, which broaden the farm’s traditional boundaries to include additional activities at the farm level, help the evolution towards multifunctionality. A policy-driven transition towards multifunctional farming has been noticed in Italy during the past few decades, which has prompted a strategic reconfiguration of the farm’s business models. Drawing on the identified activity of portfolio diversification, this study provides an overview of the analyzed 49,429 Italian farms, by articulating diversification strategies into four entrepreneurial activities, which are related to on/off-farm/farm-related or farm-diverse diversification strategies. This article has attempted to verify the presence of farm types that responded to portfolio diversification management strategies through the use of a cluster analysis on data from the general census of Italian agriculture. Supporting new patterns in the adoption of business models focused on multifunctionality should be considered in European rural development policies. Full article

This communication introduces a versatile, multi-service, shared-aperture antenna system for multiple vehicle applications. The design comprises three antenna elements: a rotatable microstrip antenna for global positioning system (GPS) communication, a cross-dipole circularly polarized antenna for satellite communication in the S-band, and a pattern reconfigurable antenna for V2V (vehicle-to-vehicle) communication. These antennas collectively support GPS, satellite communication (Satcom), and V2V communication in a single, shared-aperture design. This shared-aperture antenna system offers cost savings and occupies less space compared to using separate antennas for each service. The microstrip antenna covers the 1575 MHz frequency band used for GPS communication. The cross-dipole circularly polarized antenna provides continuous wideband coverage for S-band satellite communication. The pattern reconfigurable antenna, tailored for the specific application scenario, covers the 5.9 GHz V2V working frequency band (5.855–5.925 GHz). Practical testing and simulation results confirm the effectiveness of this antenna system for the intended applications. In summary, the microstrip antenna has a bandwidth of 1.565–1.578 GHz and a realized gain of 7 dBi with radiation efficiency of 81%, the cross-dipole antenna has a bandwidth of 2.2–3.8 GHz (53.3%) and a realized gain of 8.3 dBi with radiation efficiency of 90%, and the pattern reconfigurable antenna has a 5.8–6 GHz bandwidth and a realized gain of 3.7 dBi with radiation efficiency of 85%, and the isolation between antennas with different frequencies is 25 dB, 20 dB, and 30 dB in three frequency bands. Full article

The proliferation of Internet of Things (IoT) devices, such as trackers and sensors, necessitates a delicate balance between device miniaturization and performance. This extends to the antenna system, which must be both efficient and multiband operational while fitting within space-constrained electronic enclosures. Traditional antennas, however, struggle to meet these miniaturization demands. Reconfigurable antennas have emerged as a promising solution for adapting their frequency, radiation pattern, or polarization in response to changing requirements, making them ideal for IoT applications. Among various reconfiguration techniques (electrical, mechanical, optical, and material-based), electrical reconfiguration reigns supreme for IoT applications. Its suitability for compact devices, cost-effectiveness, and relative simplicity make it the preferred choice. This paper reviews various approaches to realizing IoT reconfigurable antennas, with a focus on electrical reconfiguration techniques. It categorizes these techniques based on their implementation, including PIN diodes, digital tunable capacitors (DTCs), varactor diodes, and RF switches. It also explores the challenges associated with the development and characterization of IoT reconfigurable antennas, evaluates the strengths and limitations of existing methods, and identifies open challenges for future research. Importantly, the growing trend towards smaller IoT devices has led to the development of antenna boosters. These components, combined with advanced reconfiguration techniques, offer new opportunities for enhancing antenna performance while maintaining a compact footprint. Full article

Neurons are central to lifelong learning and memory, but ageing disrupts their morphology and function, leading to cognitive decline. Although epigenetic mechanisms are known to play crucial roles in learning and memory, neuron-specific genome-wide epigenetic maps into old age remain scarce, often being limited to whole-brain homogenates and confounded by glial cells. Here, we mapped H3K4me3, H3K27ac, and H3K27me3 in mouse neurons across their lifespan. This revealed stable H3K4me3 and global losses of H3K27ac and H3K27me3 into old age. We observed patterns of synaptic function gene deactivation, regulated through the loss of the active mark H3K27ac, but not H3K4me3. Alongside this, embryonic development loci lost repressive H3K27me3 in old age. This suggests a loss of a highly refined neuronal cellular identity linked to global chromatin reconfiguration. Collectively, these findings indicate a key role for epigenetic regulation in neurons that is inextricably linked with ageing. Full article

Plant-growth-promoting bacteria (PGPB) have beneficial effects on plants. They can promote growth and enhance plant defense against abiotic stress and disease, and these effects are associated with changes in the plant metabolite profile. The research problem addressed in this study was the impact of inoculation with PGPB on the metabolite profile of Salicornia europaea L. across controlled and field conditions. Salicornia europaea seeds, inoculated with Brevibacterium casei EB3 and Pseudomonas oryzihabitans RL18, were grown in controlled laboratory experiments and in a natural field setting. The metabolite composition of the aboveground tissues was analyzed using GC–MS and UHPLC–MS. PGPB inoculation promoted a reconfiguration in plant metabolism in both environments. Under controlled laboratory conditions, inoculation contributed to increased biomass production and the reinforcement of immune responses by significantly increasing the levels of unsaturated fatty acids, sugars, citric acid, acetic acid, chlorogenic acids, and quercetin. In field conditions, the inoculated plants exhibited a distinct phytochemical profile, with increased glucose, fructose, and phenolic compounds, especially hydroxybenzoic acid, quercetin, and apigenin, alongside decreased unsaturated fatty acids, suggesting higher stress levels. The metabolic response shifted from growth enhancement to stress resistance in the latter context. As a common pattern to both laboratory and field conditions, biopriming induced metabolic reprogramming towards the expression of apigenin, quercetin, formononetin, caffeic acid, and caffeoylquinic acid, metabolites that enhance the plant’s tolerance to abiotic and biotic stress. This study unveils the intricate metabolic adaptations of Salicornia europaea under controlled and field conditions, highlighting PGPB’s potential to redesign the metabolite profile of the plant. Elevated-stress-related metabolites may fortify plant defense mechanisms, laying the groundwork for stress-resistant crop development through PGPB-based inoculants, especially in saline agriculture. Full article

Regular exercise plays a crucial role in promoting overall well-being in today’s lifestyle. However, individuals often find it challenging to properly execute exercises, including maintaining correct postures and appropriate movement speeds. Robotic companions have emerged as potential solutions to assist and motivate users during exercise sessions. This research paper proposes a novel robot companion designed for exercise scenarios using a reconfigurable robot. In contrast to existing non-reconfigurable robotic companions, the use of a reconfigurable robot provides added flexibility in generating emotions. The system incorporates a module that utilizes fuzzy logic to evaluate the correctness of exercise performance based on posture variations and movement speeds. The robot generates emotions and provides feedback to users based on the exercise correctness score. The robot expresses emotions through reconfigurations, motion patterns, and variations in robot speed. This emotion-based feedback could be helpful for creating engaging and interactive exercise experiences. Apart from emotion generation, the robot utilizes vocal cues as feedback. Experimental results validate the effectiveness of the proposed system in evaluating exercise correctness and demonstrating meaningful emotion transitions. The findings of this work contribute to the development of innovative robotic companions for improving exercise adherence and overall well-being. Full article

Field-programmable gate arrays (FPGAs) offer the inherent ability to reconfigure at runtime, making them ideal for applications such as data centers, cloud computing, and edge computing. This reconfiguration, often achieved through remote access, enables efficient resource utilization but also introduces critical security vulnerabilities. An adversary could exploit this access to insert a dormant hardware trojan (HT) into the configuration bitstream, bypassing conventional security and verification measures. To address this security threat, we propose a supervised learning approach using deep recurrent neural networks (RNNs) for HT detection within FPGA configuration bitstreams. We explore two RNN architectures: basic RNN and long short-term memory (LSTM) networks. Our proposed method analyzes bitstream patterns, to identify anomalies indicative of malicious modifications. We evaluated the effectiveness on ISCAS 85 benchmark circuits of varying sizes and topologies, implemented on a Xilinx Artix-7 FPGA. The experimental results revealed that the basic RNN model showed lower accuracy in identifying HT-compromised bitstreams for most circuits. In contrast, the LSTM model achieved a significantly higher average accuracy of 93.5%. These results demonstrate that the LSTM model is more successful for HT detection in FPGA bitstreams. This research paves the way for using RNN architectures for HT detection in FPGAs, eliminating the need for time-consuming and resource-intensive reverse engineering or performance-degrading bitstream conversions. Full article