Search Results (5,396)

Biomolecule-driven smart materials represent a paradigm shift in pharmacology, transitioning drug delivery from a passive process to an active, programmable, and highly specific intervention. These systems, constructed from or functionalized with biological macromolecules such as nucleic acids, peptides, proteins, and polysaccharides, are engineered to sense and respond to specific pathophysiological cues or external triggers. This review provides a comprehensive analysis of this rapidly evolving field. We first delineate the fundamental principles of stimuli-responsive actuation, categorizing systems based on their response to endogenous (pH, redox, enzymes, ROS) and exogenous (temperature, light, magnetic fields) triggers. We then conduct an in-depth survey of the primary biomolecular architectures, examining the unique design space offered by DNA nanotechnology, the functional versatility of peptides and proteins, and the biocompatibility of polysaccharides. Key therapeutic applications in oncology, inflammatory diseases, and gene therapy are discussed, highlighting how these intelligent systems are being designed to overcome critical biological barriers and enhance therapeutic efficacy. Finally, we address the formidable challenges—spanning biocompatibility, manufacturing scalability, and regulatory navigation—that constitute the “bench-to-bedside” chasm. We conclude by exploring future perspectives, including the development of multi-stimuli responsive, logic-gated systems and the transformative potential of artificial intelligence in designing the next generation of personalized nanomedicines. Full article

This study addresses the problem of anomaly detection in water treatment systems by proposing a hybrid VAE–LSTM model with a combined loss function that integrates reconstruction and prediction errors. Following the signal flow of wastewater treatment systems, data acquisition, transmission, and cyberattack scenarios were simulated, and a dual-dimensional learning framework of “feature space—temporal space” was designed: the VAE learns latent data distributions and computes reconstruction errors, while the LSTM models temporal dependencies and computes prediction errors. Anomaly decisions are made through feature extraction and weighted scoring. Experimental comparisons show that the proposed fusion model achieves an accuracy of approximately 0.99 and an F1-Score of about 0.75, significantly outperforming single models such as Isolation Forest and One-Class SVM. It can accurately identify attack anomalies in devices such as the LIT101 sensor and MV101 actuator, e.g., water tank overflow and state transitions, with reconstruction errors primarily beneath 0.08 ensuring detection reliability. In terms of time efficiency, Isolation Forest is suitable for real-time preliminary screening, while VAE-LSTM adapts to high-precision detection scenarios with an “offline training (423 s) + online detection (1.39 s)” mode. This model provides a practical solution for intelligent monitoring of industrial water treatment systems. Future research will focus on model lightweighting, enhanced data generalization, and integration with edge computing to improve system applicability and robustness. The proposed approach breaks through the limitations of traditional single models, demonstrating superior performance in detection accuracy and scenario adaptability. It offers technical support for improving the operational efficiency and security of water treatment systems and serves as a paradigm reference for anomaly detection in similar industrial systems. Full article

The Internet of Things (IoT) has enabled a vast network of devices to communicate over the Internet. However, the fragmentation of IoT systems continues to hinder seamless data sharing and coordinated management across platforms.However, there is currently no actual search engine for IoT data. Existing IoT search engines are considered device discovery tools, providing only metadata about devices rather than enabling access to IoT application data. While efforts such as IoTCrawler have striven to support IoT application data, they have largely failed due to the fragmentation of IoT systems and the heterogeneity of IoT data.To address this, we recently introduced SensorsConnect—a unified framework designed to facilitate interoperable content and sensor data sharing among collaborative IoT systems, inspired by how the World Wide Web (WWW) enabled shared and accessible information spaces for humans. This paper presents the IoT Agentic Search Engine (IoT-ASE), a real-time semantic search engine tailored specifically for IoT environments. IoT-ASE leverages LLMs and Retrieval-Augmented Generation (RAG) techniques to address the challenges of navigating and searching vast, heterogeneous streams of real-time IoT data. This approach enables the system to process complex natural language queries and return accurate, contextually relevant results in real time. To evaluate its effectiveness, we implemented a hypothetical deployment in the Toronto region, simulating a realistic urban environment using a dataset composed of 500 services and over 37,000 IoT-like data entries. Our evaluation shows that IoT-ASE achieved 92% accuracy in retrieving intent-aligned services and consistently generated concise, relevant, and preference-aware responses, outperforming generalized outputs produced by systems such as Gemini. These results underscore the potential of IoT-ASE to make real-time IoT data both accessible and actionable, supporting intelligent decision-making across diverse application domains. Full article

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates chair, and stepladder. The limitations of the multifunctional rollator walker were identified from the user feedback of a foundational work and were then addressed by identifying the engineering and physical contradictions and problem modeling using Su-field analysis. Through TRIZ Inventive Principles, the proposed design eliminates common trade-offs between portability, stability, and usability. The conceptual enhancement incorporates features such as deployable steps, the utilization of high strength–to–weight ratio material, foldability, a passive mechanical brake-locking system, retractable armrests, the incorporation of spring-assist hinges, and the use of large tires with vibration-dampening hubs. This study contributes a novel, user-focused, and space-saving mobility solution that aligns with the evolving demands of assistive technology, laying the groundwork for future iterations involving smart control, power assist, and modular enhancements. Full article

This paper presents the final implemented design and performance evaluation of the ground-based C-band Cheia radar system, developed to enhance Romania’s contribution to the EU Space Surveillance and Tracking (EU SST) network. All data used for performance analysis are real-time, real-life measurements of true spatial test objects orbiting Earth. The radar is based on two decommissioned 32 m satellite communication antennas already present at the Cheia Satellite Communication Center, that were retrofitted for radar operation in a quasi-monostatic architecture. A Linear Frequency Modulated Continuous Wave (LFMCW) Radar design was implemented, using low transmitted power (2.5 kW) and advanced software-defined signal processing for detection and tracking of Low Earth Orbit (LEO) targets. System validation involved dry-run acceptance tests and calibration campaigns with known reference satellites. The radar demonstrated accurate measurements of range, Doppler velocity, and angular coordinates, with the capability to detect objects with radar cross-sections as low as 0.03 m² at slant ranges up to 1200 km. Tracking of medium and large Radar Cross Section (RCS) targets remained robust under both fair and adverse weather conditions. This work highlights the feasibility of re-purposing legacy satellite infrastructure for SST applications. The Cheia radar provides a cost-effective, EUSST-compliant performance solution using primarily commercial off-the-shelf components. The system strengthens the EU SST network while demonstrating the advantages of LFMCW radar architectures in electromagnetically congested environments. Full article

During the suspension flight of high-altitude scientific balloons in near-space, they are highly vulnerable to time-varying wind field disturbances, which tend to excite multiple distinctive torsional modes of the balloons themselves, thereby interfering with the observations of balloon-borne equipment. Focusing on the azimuth control of the balloon-borne gondola, this paper designs a simplified decoupling mechanism and a reaction wheel as actuators. Specifically, the reaction wheel achieves azimuth tracking through angular momentum exchange, while the simplified decoupling mechanism performs the functions of decoupling and unloading. To fully utilize the control performance of the actuating structure, this paper further proposes a control algorithm based on a nonlinear differential tracker and neural network PID. Simulation results demonstrate that under typical wind disturbances and sensor noise conditions, the proposed system exhibits excellent smoothness and high-precision and stable control performance. This research provides a significant basis for stable observation platforms in precise near-space observation missions. Full article

Free-space optical (FSO) communication systems face significant challenges from atmospheric turbulence, which induces time-correlated fading and burst errors that critically affect link reliability. This paper presents a comprehensive end-to-end CCSDS O3K simulation platform with detailed atmospheric channel and pointing error modeling, enabling realistic performance evaluation. The atmospheric channel model follows ITU-R P.1622-1 recommendations and incorporates amplitude scintillation with temporal correlation using Ornstein–Uhlenbeck processes, while the pointing error model captures beam misalignment effects inherent in satellite optical links. Through extensive Monte Carlo simulations, we investigate the impact of coherence time, and interleaving depth on system performance. Results show that deeper interleaving significantly improves reliability under realistic channel conditions, providing valuable design guidance for CCSDS-compliant optical communication systems. This study does not propose new algorithms or protocols; rather, it delivers the first end-to-end CCSDS-compliant simulation framework under realistically modeled turbulence and pointing errors. Accordingly, the results offer meaningful reference value and practical benchmarks for inter-satellite optical communication research and system design. Full article

While often framed as historical or ‘post’colonial, the pervasive legacies of anti-Black racism, rooted in the afterlives of slavery and the dehumanization of African, Caribbean, and Black (ACB) voices, continues to shape the health experiences of young ACB women in Ontario, Canada. Using an intersectional framework, this qualitative study utilized focus groups (n = 24) to understand factors influencing access to sexual and reproductive health services for young ACB women in southern Ontario. The findings reveal that fostering ACB youth engagement in the design and facilitation of healthcare programs will be vital for creating more responsive spaces to fully express sexual health concerns. It also demonstrates that Eurocentric biomedical frameworks continue to obscure young ACB women’s needs, emphasizing the necessity for culturally relevant care. Lastly, the findings indicate that internalized colonial narratives around health practices perpetuate intergenerationally, further complicating young ACB women’s access to adequate sexual and reproductive healthcare. This examination illuminates the need to address the colonial legacies within healthcare systems that continue to pathologize and hypersexualize young ACB women’s bodies. The study concludes by advocating for intersectional, youth-centered, and culturally competent approaches to dismantling the barriers young ACB women face in accessing sexual and reproductive health services. Full article

Resource efficiency is essential in today’s approach to horticulture. The global problems of water scarcity, soil pollution, biodiversity loss, and rapid growth of the global population require increased food production with fewer resources. Resource efficiency is an indicator that allows defining how much biomass an agri-food system can produce per unit of the resource used. Closed hydroponic systems, such as vertical hydroponic towers (VHTs), exhibit high resource efficiency. In these systems, the water use efficiency (WUE) and the nutrient use efficiency (NUE) can be calculated in terms of the water loss through transpiration and the ion concentration in the nutrient solution. The research aimed to determine the WUE and NUE for chard crops in VHT under greenhouse conditions and to evaluate its feasibility as an urban and peri-urban system for leafy vegetable production. Trials were carried out with chard in the fall 2024 in a tunnel-type greenhouse at the facilities of the Autonomous University of San Luis Potosi. The VHTs were built with a 20 L square lower deposit on which a cylindrical pipeline of 11.5 cm in diameter and 1.6 m in height was vertically placed. Each pipe had 45 growing containers distributed on 15 levels of three containers spaced vertically 9 cm and a density of 25 plants·m⁻². The experimental design was completely randomized with three treatments (75, 100, and 125% of Steiner’s nutrient solution) and three replications. The transpiration (Tr) of the crop (recording weight loss in the deposit) and the shoot fresh weight (SFW) of the plants were measured daily using a scale. An ANOVA and Tukey’s test for mean differentiation were performed with p < 0.05. Significant differences were found between treatments for SFW, WUE and NUE obtaining the best results at 75% of Steiner’s nutrient solution. Results show that WUE increased between 3 and 6 times, and NUE between 3 and 12 times compared to chard grown in soil. These results were equal and even higher than horizontal hydroponic systems or vertical farms. Vertical hydroponic closed towers installed in greenhouses are an optimal horticultural production system with high resources use efficiency. The implementation of VHT is feasible in areas where there is water scarcity or have a high population density. Full article

In response to the IMO’s decarbonisation strategy, hydrogen—especially green hydrogen—becomes a promising alternative fuel in shipping. This article provides a comparative analysis of two hydrogen propulsion technologies suitable for a service vessel (SOV) operating in offshore wind farms: hydrogen fuel cells and hydrogen-powered internal combustion engines. This study focuses on the use of liquid hydrogen (LH₂) stored in cryogenic tanks and fuel cells as an alternative to the previously considered solution based on compressed hydrogen (CH₂) stored in high-pressure cylinders (700 bar) and internal combustion engines. The research aims to examine the feasibility of a fully hydrogen-powered SOV energy system. The analyses showed that the use of liquefied hydrogen in SOVs leads to the threefold reduction in tank volume (1001 m³ LH₂ vs. 3198 m³ CH₂) and the weight of the storage system (243 t vs. 647 t). Despite this, neither of the technologies provides the expected 2-week autonomy of SOVs. LH₂ storage allows for a maximum of 10 days of operation, which is still an improvement over the CH₂ gas variant (3 days). The main reason for this is that hydrogen tanks can only be located on the open deck. Although hydrogen fuel cells take up on average 13.7% more space than internal combustion engines, they are lower (by an average of 24.3%) and weigh less (by an average of 50.6%), and their modular design facilitates optimal arrangement in the engine room. In addition, the elimination of the exhaust system and lubrication simplifies the engine room layout, reducing its weight and space requirements. Most importantly, however, the use of fuel cells eliminates exhaust gas emissions into the atmosphere. Full article

Lighting systems in sports venues have a significant impact on both the user experience and quality of events. However, owing to the large number of luminaires, high individual lamp power, and strict lighting standards, the lighting energy consumption of sports venues is high, accounting for approximately 30% of the total energy use. Therefore, introducing natural light through appropriate means during non-event periods and ensuring adequate lighting via collaborative control between natural light and artificial-lighting systems are crucial for reducing the lighting energy consumption of sports venues. Light pipe systems are a novel form of natural lighting and can effectively supplement artificial lighting. However, no clear methodology for selecting light pipes or designing light pipe systems in high spaces such as sports venues currently exists. Furthermore, developing a method for collaborative control between artificial-lighting systems and light pipe systems under various natural light conditions is an urgent issue in the optimization of the design of sports venue lighting. Therefore, we considered a conventional sports venue as a case study. By conducting HOLIGILM simulation experiments, we first investigated the factors affecting the transmission efficiency of light pipe systems and proposed optimization parameters for system design in terms of the pipe diameter, length, and configuration. Subsequently, using the Chinese Standard for Daylighting Design of Buildings (GB50033-2013) and the construction cost as optimization objectives, we optimized the pipe diameter, length, and placement of the light pipe system by applying non-dominated sorting genetic algorithm II. The simulation results showed that the optimized design of the light pipe system in the sports venue achieved a daylight factor of 1%, which met the standard requirements while reducing the construction cost by approximately 27%. Finally, to meet the indoor Class I (non-tournament) lighting standards stipulated in the Standard for Lighting Design and Test of Sports Venues (JGJ153-2016) and taking energy conservation as the optimization goal, we proposed a strategy for achieving collaborative control between the light pipe system and artificial-lighting system based on a greedy algorithm. The results indicated that under various weather conditions, the collaborative control strategy enabled the lighting of the field of play to meet Class I illuminance standards while reducing the annual lighting energy consumption by 35%. Thus, this study provides a methodological reference for optimizing the design of light pipe systems and achieving collaborative control with artificial-lighting systems in large-scale venues. Although these results were obtained based on meteorological data from Xi’an, China, the research method presented in this study can also be applied to other regions. The study provides a methodological reference for the design and optimization of light pipe systems and associated control systems to operate light pipes alongside artificial lighting systems in sports venues and other large multistory buildings. Full article

Anomaly detection of catenary support components (CSCs) is an important component in railway condition monitoring systems. However, because the abnormal features of CSCs loosening are not obvious, and the current CNN models and visual Transformer models have problems such as limited remote modeling capabilities and secondary computational complexity, it is difficult for existing deep learning anomaly detection methods to effectively exert their performance. The state space model (SSM) represented by Mamba is not only good at long-range modeling, but also maintains linear computational complexity. In this paper, using the state space model (SSM), we proposed a new visual state space reconstruction network (VSM-UNet) for the detection of CSC loosening anomalies. First, based on the structure of UNet, a visual state space block (VSS block) is introduced to capture extensive contextual information and multi-scale features, and an asymmetric encoder–decoder structure is constructed through patch merging operations and patch expanding operations. Secondly, the CBAM attention mechanism is introduced between the encoder–decoder structure to enhance the model’s ability to focus on key abnormal features. Finally, a stable abnormality score calculation module is designed using MLP to evaluate the degree of abnormality of components. The experiment shows that the VSM-UNet model, learning strategy and anomaly score calculation method proposed in this article are effective and reasonable, and have certain advantages. Specifically, the proposed method framework can achieve an AUROC of 0.986 and an FPS of 26.56 in the anomaly detection task of looseness on positioning clamp nuts, U-shaped hoop nuts, and cotton pins. Therefore, the method proposed in this article can be effectively applied to the detection of CSCs abnormalities. Full article

The scarcity of explicit feedback data is a major challenge in the design of recommender systems. Although such data are of a high quality due to users’ voluntary provision of numerical ratings, collecting a sufficient amount in real-world service environments is typically infeasible. As an alternative, implicit feedback data are extensively used. However, because implicit feedback represents observable user actions rather than direct preference statements, it inherently suffers from ambiguity as a signal of true user preference. To address this issue, this study reinterprets the ambiguity of implicit feedback signals as a problem of epistemic uncertainty regarding user preferences and proposes a latent factor model that incorporates this uncertainty within a Bayesian framework. Specifically, the behavioral vector of a user, which is learned from implicit feedback, is restructured within the embedding space using attention mechanisms applied to the user’s interaction history, forming an implicit preference representation. Similarly, item feature vectors are reinterpreted in the context of the target user’s history, resulting in personalized item representations. This study replaces the deterministic attention scores with stochastic attention weights treated as random variables whose distributions are modeled using a Bayesian approach. Through this design, the proposed model effectively captures the uncertainty stemming from implicit feedback within the vector representations of users and items. The experimental results demonstrate that the proposed model not only effectively mitigates the ambiguity of preference signals inherent in implicit feedback data but also achieves better performance improvements than baseline models, particularly on datasets characterized by high user–item interaction sparsity. The proposed model, when integrated with an attention module, generally outperformed other MLP-based models in terms of NDCG@10. Moreover, incorporating the Bayesian attention mechanism yielded an additional performance gain of up to 0.0531 compared to the model using a standard attention module. Full article

This study presents a novel strategy for designing photocurable resins tailored for the additive manufacturing of smart thermoset materials. A quaternary formulation was developed by integrating bis(2-methacryloyl)oxyethyl disulfide (DADS) with an epoxy/thiol-ene system (ETES) composed of diglycidyl ether of bisphenol A (EP), pentaerythritol tetrakis(3-mercaptopropionate) (PTMP), and 4,4′-methylenebis(N,N-diallylaniline) (ACA4). This unique combination enables the simultaneous activation of four polymerization mechanisms: radical photopolymerization, thiol-ene coupling, thiol-Michael addition, and anionic ring-opening, within a single resin matrix. A key innovation lies in the exothermic nature of DADS photopolymerization, which initiates and sustains ETES curing at room temperature, enabling 3D printing without thermal assistance. This represents a significant advancement over conventional systems that require elevated temperatures or post-curing steps. The resulting hybrid poly(acrylate–co-ether–co-thioether) network exhibits enhanced mechanical integrity, shape memory behavior, and intrinsic self-healing capabilities. Dynamic Mechanical Analysis revealed a shape fixity and recovery of 93%, while self-healing tests demonstrated a 94% recovery of viscoelastic properties, as evidenced by near-overlapping storage modulus curves compared to a reference sample. This integrated approach broadens the design space for multifunctional photopolymers and establishes a versatile platform for advanced applications in soft robotics, biomedical devices, and sustainable manufacturing. Full article

This paper presents an intelligent design framework for a high-performance 26 GHz MIMO antenna array tailored to 5G applications, built upon a compact single-element patch. The 11.5 mm × 11.5 mm × 1.6 mm microstrip patch on FR4 exhibits near-unity electrical length, an ultra-deep return loss (S11 < −40 dB at 26 GHz), and a wide operational bandwidth from 24.4 to 31.2 GHz (6.8 GHz, ~26.2%). A two-element array, spaced at λ/2, is first augmented with a inspired metamaterial (MTM) unit cell whose dimensions are optimized via a Multi-Layer Perceptron (MLP) model to maximize gain (+2 dB) while preserving S11. In the second phase, a closed-square parasitic ring is introduced between the elements; its side length, thickness, and position are predicted by a Random Forest (RF) model with Bayesian optimization to minimize mutual coupling (S12) from −25 dB to −58 dB at 26 GHz without significantly degrading S11 (remains below −25 dB). Full-wave simulations and anechoic chamber measurements confirm the ML predictions. The close agreement among predicted, simulated, and measured S-parameters validates the efficacy of the proposed AI-assisted optimization methodology, offering a rapid and reliable route to next-generation millimeter-wave MIMO antenna systems. Full article