ABSTRACT Recent remarkable advancements in meta‐photonics are shaping the future of innovation, enhancing capabilities across various fields, and promoting sustainability through energy‐efficient solutions. In particular, bound states in the continuum (BICs) have attracted significant attention as a highly versatile and powerful platform for advancing photonic technologies in fundamental and practical applications. BICs are non‐radiative states that enable precise confinement and control of light properties, including polarization, amplitude, and phase. This review paper offers a comprehensive understanding of photonic BICs, from fundamental principles to engineering and implementation across various optical regimes for diverse applications. Based on the implementation and promising potential to revolutionize a wide range of optical applications, the BIC systems are categorized and discussed across different optical regimes, from ultraviolet to visible, infrared, and terahertz. Moreover, a section discussed the crucial role of asymmetry in generating and controlling BICs, leading to practically implementable quasi‐BICs with finite yet high Q‐factors. Furthermore, dynamic BIC devices, including phase change materials (PCMs) are discussed as advanced photonic concepts to achieve real‐time tunable and adaptable light confinement in modern optical technologies. Additionally, integrating artificial intelligence in BIC‐related technologies has also been discussed to expedite the development and optimization of advanced BIC designs with enhanced light‐matter interactions and high‐Q factors. In addition, implementing BIC devices is addressed within the context of passive and active photonic systems. Finally, the potential future developments of BIC‐based devices are highlighted, underscoring their critical role in next‐generation photonic technologies.

An innovative gas-cooled fast reactor concept being investigated in the United States is the General Atomics Fast Modular Reactor (FMR). The FMR includes a reactor vessel cooling system (RVCS) that is designed to remove decay heat from the reactor pressure vessel via natural circulation in the event that primary cooling is unavailable. Because of its potential role in maintaining the reactor within design limit temperatures, a series of complementary safety assessments were performed to elicit potential failure modes of the system; these included a component failure modes and effects analysis (FMEA), a functional FMEA (FFMEA), and development of a master logic diagram (MLD). The assessments were performed on an analog of the RVCS with design insights derived from the reactor cavity cooling system of the steam cycle–high temperature gas-cooled reactor concept. A model-based systems engineering approach was used to conduct the safety assessments on the analog RVCS via development of a SysML model that captured design features, interfaces, and primary system functions to inform the results of the assessments. Using the SysML model, potential component-level failures and functional failure modes were identified from the component FMEA and FFMEA, respectively. The SysML-facilitated MLD provided complementary results to the FFMEA. The results of the assessments indicate that the RVCS performance is dependent on system parameters that influence natural driving heads. The risk-significance of individual failure modes on RVCS performance can be further evaluated by probabilistic approaches in the future.

Exceptional points (EPs) in non-Hermitian systems offer a remarkably strong response to weak perturbations, but the nonorthogonal nature of the corresponding eigenvectors causes noise to diverge, hindering EPs practical application. Here, we report a twelve-fold enhancement of signal-to-noise ratio (SNR) in magnetic field sensing enabled by a third-order EP of coherent perfect absorption (CPA EP3) in a passive cavity magnonic system. This non-Hermitian magnonic platform comprises two identical yttrium iron garnet (YIG) spheres coherently coupled to a cavity mode, in which the CPA EP3 is realized by engineering the three-mode loss to form a pseudo-Hermitian absorption Hamiltonian. By independently tailoring the absorption EP apart from the resonance EP, the system circumvents the noise divergence caused by eigenbasis collapse. Notably, we harness the sensitivity of the minimum output intensity near CPA to perturbations, yielding a seventy-fold SNR improvement and a 400-fold increase in responsivity compared with non-CPA system. A comprehensive noise analysis over one hundred repeated measurements confirms the suppression of frequency noise near the CPA EP3. This demonstrates that our scheme not only avoids the noise divergence plaguing conventional higher-order EP sensors but also provides a general strategy to exploit both CPA and EP for SNR enhancement in passive non-Hermitian systems.

Machine learning-enabled mapping of techno-economic and environmental performance for passive envelope systems towards low-energy medium office buildings in China

Cell membrane-camouflaged chemotactic nanomotors for enhanced cancer chemotherapy.

Redox-mediated Cr(VI) removal in anaerobic passive columns using waste Fe-sludge containing indigenous Fe-reducing bacteria.

Adaptive Channel Allocation in Multistatic Passive Radar System for Multiple Maneuvering Targets Tracking With Missed Detection

Characterizing both the CO2 distribution and wind dynamics in the Martian mesosphere and lower thermosphere is vital for planetary atmospheric science and mission planning. In this work, we propose a novel dual-channel passive limb-viewing imaging system designed to simultaneously observe partial CO2 column density and line-of-sight (LOS) wind speed from ultraviolet and visible airglow emissions under dayside and terminator illumination conditions. A dichroic beam splitter separates the ultraviolet and visible channels, ensuring high optical throughput and independent optimization of both subsystems. The ultraviolet channel targets O(1S) 297.2 nm emission, a well-established Martian limb emission driven by CO2 photodissociation under solar Lyman-α flux. By applying narrow-band imaging and brightness inversion, this channel provides quantitative constraints on CO2 column density with a stable and well-defined response function. In the visible channel, we introduce a lens array-based compact static Michelson interferometer optimized for the O(1S) 557.7 nm green line emission, which has been observed in the Martian dayside limb, providing Doppler wind measurements in the 60–180 km altitude range. Radiative transfer simulations using Mars Climate Database indicate retrieval precisions of ±6~8% for CO2 column density and better than ±5 m/s for wind speed within the primary emission layer (approximately 60–160 km) under representative dayside limb conditions. This dual-parameter remote sensing concept simultaneously constrains the composition and dynamics of the Martian mesosphere and lower thermosphere region, addressing a long-standing observational gap. The compact and modular design of the system makes it well suited for future Mars orbiter payloads under nominal dayside and terminator observation geometries, providing critical data for validating global circulation models and supporting future entry, descent, and landing system design.

Movement monitoring with wearable technologies is becoming increasingly popular in different fields of application (clinical, sports, entertainment). Particularly, textile-based wearables for movement monitoring are attractive as they follow the body movement, are comfortable to use, and can provide continuous tracking capabilities. Ideally, these wearable devices should be flexible (as opposed to current technologies with rigid electronics on the garments) and transmit data wirelessly to avoid hindering the natural movement with connections. Although fully textile wireless and passive wearable systems — whereby the textile sensing part does not have any rigid components and the data is wirelessly transmitted to an external reader — have been developed, the capability of these technologies is currently limited to a single sensor. In this work, we present a system based on a resonating inductor-capacitor (LC) circuits that can measure multiple sensors to broaden the range of use by tracking more than a single joint. Importantly, the presented system employs multiple capacitive strain sensors but retains the use of a single inductor for data transmission, limiting the complexity of realization and the number of connections. After characterization on the bench for careful design of the circuit components, we demonstrated the capability of the system to be used for human movement monitoring and activity classification by integrating two sensors in sport leggings and performing different static and dynamic activities. The tests with sensorized leggings were performed by a single participant. Among a set of chosen classification algorithms, the best performance (F1-score) was 0.98 for the static activities and 0.96 for dynamic activities. When including three independent sessions (donning and doffing the sensorised leggings) accuracy and F1-score dropped to 0.86 and 0.87 respectively. Overall, the presented system has the potential to be adopted as unobtrusive and comfortable smart clothing for real time movement monitoring.

Superelastic (SE) response of shape memory alloys (SMAs) offers significant potential for base isolation (BI) systems by reducing superstructure deformations and improving structural safety. This study presents a novel isolation device integrating steel sliding bearings with SE NiTi spring attenuators, designed to provide self-centering capacity and energy dissipation through reversible phase transformations. The attenuator configuration was optimized using a custom-developed algorithm to balance isolation efficiency with displacement control. To evaluate performance, an array of SMA springs was incorporated into a three-story steel frame prototype with three degrees of freedom, tested experimentally on a shake table. For comparison, a conventional elastic spring was also employed, and both systems were subjected to recorded earthquake ground motions. Results for the SE isolation device (SEID) showed that substituting steel with SMA springs reduced structural stiffness by 69%. Calibration confirmed consistent behavior across spring pairs, with maximum deviations of 17.3% due to material nonlinearity. Adoption of shorter springs with fewer coils improved efficiency, reducing oscillating mass by 42%. Modal testing further demonstrated amplitude reductions of 80% under seismic excitations and 91% under forced vibration, validating the SEID as an effective solution for diverse dynamic loading conditions.

The prevalence of radio frequency signals in indoor environments has in recent years given rise to new technologies across many domains such as robotics, healthcare, and surveillance. Radio frequency signals propagate in the wireless medium through multiple paths and carry useful environment-dependent information. Capturing and analyzing these signal patterns can offer new solutions for a number of applications relevant to ranging, tracking, perception and recognition. In this work we propose a novel architecture, separating physical, back-bone networks, and inference layers, towards fully ubiquitous passive recognition systems that scale with the number of environments and applications. We propose a back-bone architecture that utilizes a novel Cross Dual-Path Attention (CDPA) block to capture spatial and temporal correlations from Channel State Information (CSI) for device-free, multi-task applications. Subsequently, a distill and transfer algorithm is proposed to generalize the inference capabilities of CDPA over multiple target environments for scalable training and reduced computational costs. By sharing knowledge between models across a shared network, experimentation shows that edge devices can be deployed with improved performance while simultaneously meeting strict computation and memory requirements. Our distributed learning paradigm demonstrates that CDPA-based models are capable of using passive signals in a non-intrusive and privacy-protecting manner, in order to achieve ubiquitous recognition at scale in smart environments.

Diabetic foot ulcers (DFUs), prone to infection and deterioration without timely intervention, significantly increase risks of amputation and mortality. Elevated local temperature in DFUs further impedes the healing process. Although microneedles (MNs) represent a promising strategy for DFUs treatment, conventional passive drug release systems suffer from slow release kinetics and low utilization efficiency. To address these limitations, we developed a dual-thermo-responsive microneedle patch (DTMN) that actively controls drug delivery through temperature-induced structural transitions. The inner layer consists of sodium alginate-poly (N-isopropylacrylamide) (SA-PNIPAM) loaded with sucrose octasulfate sodium salt (SOS), utilizing the volume phase transition of PNIPAM to accelerate drug expulsion in response to temperature change. The outer layer comprises a polyethylene glycol/polylactic acid-glycolic acid copolymer (PEG-PLGA) loaded with urea, which undergoes gel-sol transition to facilitate controlled urea release and wound cooling. An upper electrospun nanofiber membrane made of poly (ε-caprolactone)/chitosan (PCL/CS) incorporated with tetracycline hydrochloride (TH) and SOS provides enhanced antibacterial efficacy and increased drug loading capacity. The resulting DTMN exhibits efficient drug release (85.23% SOS and 35.44% urea-derived ammonia at 24h), remarkable antioxidant activities, potent antibacterial performance, excellent biocompatibility, and significantly enhanced wound healing. This multifunctional system offers a novel and effective strategy for the management of DFUs.

This study presents a review of passive linear gravity compensation (GC) mechanisms. Linear GC is defined as the realization of a displacement-independent constant upward force along a vertical axis to balance the gravitational load over the entire stroke. This paper focuses on passive systems that counteract gravity solely through mechanical or magnetic energy storage elements, without relying on external power sources. The main energy sources in passive systems—springs, permanent magnets, counterweights, and fluid pressure—are surveyed with emphasis on their ability to generate a constant force. Representative spring-based constant-force mechanisms, cam–spring linkages, and quasi-zero-stiffness magnetic gravity compensators are summarized, together with their applications in vibration isolation systems. Finally, reported performance data are compiled to outline the practical operating envelope of passive linear GC in terms of force level, stroke, and equivalent stiffness. This review reveals that permanent-magnet-based approaches are advantageous for short-stroke, high-precision applications, whereas spring-based mechanisms offer superior suitability for long-stroke requirements due to their greater design flexibility. Consequently, this review provides a strategic selection guideline based on the inherent trade-offs of energy-storage elements to meet specific application requirements.

An innovative design for a dual-piezoelectric-layer MEMS hydrophone based on a composite film of scandium-doped aluminum nitride (Sc0.2Al0.8N) is presented. By designing the dual piezoelectric layer, the frequency response range has been expanded and the sensitivity of the device has been significantly enhanced. Meanwhile, doping with scandium can significantly increase the piezoelectric coefficient, enhancing the sensitivity. According to the standard underwater acoustic calibration test, the device exhibits an average sound pressure sensitivity of -162 dB (re: 1 V/μPa) across the 20 Hz-50 KHz frequency band and equivalent noise density of 47 dB (re: 1 μPa/√Hz) with a linearity of 99%. The experimental results show that the comprehensive performance of the dual-piezoelectric-layer hydrophone provides a new solution for underwater sensing and detection, and opens up a new path for the performance optimization of passive sonar systems.

Considering the increasing demand for environmentally friendly and economically viable transportation options, this in-depth analysis of fault-tolerant control (FTC) in the context of electric vehicles (EVs) covers all the latest developments and applications in the field. Maintaining vehicle stability and handling component failures with minimal or acceptable loss of performance are the primary goals of FTC systems in EVs. Thus, the FTC's crucial role in improving EV dependability is examined in this study. An explanation of the control strategies employed in EVs is followed by a description of the several types of FTC, including active, passive, and hybrid systems. The study aims to objectively evaluate advancements in tracking accuracy and robust performance by thoroughly reviewing FTC systems for modern EVs. This discusses various strategies as well as the challenges of integrating them into EV subsystems. Real-time deployment, validation against coupled failures, and the incorporation of learning-based FTC into safety-critical EV systems are some suggestions for future research. This study will help identify research gaps and topics that require additional investigation in order to advance the discipline.

Passive control systems that provide both stiffness and energy dissipation, such as viscoelastic dampers (VEs), offer a promising strategy for seismic retrofit of existing reinforced concrete (RC) buildings, especially critical facilities that must remain operational during construction. Unlike conventional retrofit methods that require concrete casting and occupant evacuation, VE-based systems can be installed with shorter construction periods and reduced environmental disturbance. This study experimentally investigates the dynamic behavior of VE material subjected to large shear strain amplitudes of 300% and 400%, the latter exceeding typical design limits, to clarify its performance under severe seismic demands. The test results are used to calibrate a numerical model that represents the stiffness and energy-dissipation characteristics of the VE over this strain range. The calibrated model is then implemented in the seismic retrofit design of a six-story RC hospital building and evaluated through nonlinear structural analyses. The results indicate that the proposed VE retrofit scheme can achieve the targeted performance objectives and demonstrate the feasibility of applying high-strain VE dampers in practical seismic retrofit projects.

Smart suspensions have significantly improved passenger comfort and vehicle stability compared to their passive counterparts. This manuscript explores the integration of artificial intelligence (AI) into hybrid suspension control systems to enhance vehicle stability and ride comfort under conditions where suspended mass changes. A one-quarter-vehicle model is employed to simulate and evaluate the performance of a hybrid control strategy, which combines skyhook and groundhook methods using a dynamic weighting factor (α). This investigation considers an everyday situation where the sprung mass of a vehicle changes considerably when passengers enter or exit the automobile, impacting the suspension performance. Reinforcement learning techniques are utilized to optimize α, achieving an acceptable balance between passenger comfort and vehicle stability. Simulation results show significant improvements in the dynamic response of the sprung mass compared to traditional passive systems, while keeping vehicle stability. Although improvements in road holding are incremental, simulation effort validates the AI-based hybrid system’s potential for refinement and practical application. Validation in MATLAB-Simulink demonstrates the system’s adaptability to varying road conditions and load distributions. The findings highlight the transformative role of AI in suspension control, paving the way for real-time implementation, advanced algorithms, and integration into full-vehicle models. This study contributes to the ongoing development of intelligent suspension systems toward vehicle performance advancement by improving passenger comfort and road holding.

In grain storage and transportation, biological activity, including respiration and metabolism, generates heat, creating temperature gradients that can induce moisture migration and form high-humidity areas. This accelerates fungal and insect activity, leading to quality degradation. Long-term, distributed temperature monitoring inside grain piles is essential for ensuring safe storage and early risk warning. Radio Frequency Identification (RFID) technology has become widely adopted in storage temperature monitoring due to its low cost, maintenance-free operation, and high security. However, traditional RFID systems have limited communication ranges, and the large size of storage facilities necessitates the deployment of multiple readers, which increases costs. Additionally, the high density and fluctuating moisture content of bulk grain lead to significant RF signal absorption and scattering, weakening the accessibility of purely wireless systems to deeper parts of the grain pile. To address these issues, a passive distributed temperature monitoring system based on RFID technology is proposed. The system utilizes RFID readers to harvest RF energy for passive power supply, with an external antenna ensuring stable energy harvesting and data transmission. Single-bus multi-point temperature sensor modules are integrated into the system, enabling distributed temperature measurements across grain piles or warehouses. Experimental results show that the system achieves a temperature collection success rate of 98%, with an accuracy of ±1 °C and a polling cycle of less than 30 s, providing a low-cost, battery-free, and scalable solution for grain storage monitoring, significantly improving storage quality.

The development of advanced integrated small reactors is a significant trend in modern nuclear engineering. Designed by the Institute of Nuclear and New Energy Technology at Tsinghua University, NHR200-II is a nuclear heating reactor that incorporates a range of advanced passive and inherent safety features. Different from general pressurized water reactors, the safety injection system is excluded from the NHR200-II design to enhance system safety and simplicity. Therefore, the potential occurrence of a loss-of-coolant accident (LOCA) will be a key concern in the NHR200-II reactor design. The main objective of this study is to develop a Reactor Excursion and Leak Analysis Program 5 (RELAP5) model suitable for small-break loss-of-coolant accident (SB-LOCA) analysis and to explore the dynamic characteristics of system thermal-hydraulic parameters during the accident, as well as to assess the safety of NHR200-II. In this paper, a detailed thermal-hydraulic analysis of two typical SB-LOCA scenarios is presented: (1) pipe rupture of the hydraulic control rod driving system with isolation failure and (2) rupture of a small-diameter pipe on the head of the reactor pressure vessel (RPV). Several key safety characteristics, including total coolant loss from the RPV, liquid level remaining in the RPV, and maximum temperature of fuel rods, are examined to assess the safety performance of NHR200-II. The results indicate that in both accident scenarios, the remaining coolant in the primary loop is adequate to cover the reactor core and effectively remove decay heat via the passive residual heat removal system, which prevents the reactor core from overheating damage and ensures the reactor remains in a safely controllable state. Thus, the safety characteristics of the NHR200-II reactor in LOCAs are demonstrated.

Adolescents and young adults often engage in risk behaviors in close proximity to peers. Detecting peer presence could identify high-risk contexts, but typically relies on self-report, which is prone to bias. This study evaluated the feasibility, acceptability, functionality, and validity of a smartphone-based passive detection system using Bluetooth beacons to identify real-world peer proximity. Twenty-one young adult participants (38% women) and their peers (N = 55; 40% women) completed a 3-week protocol, during which peers carried a small Bluetooth beacon that was detected by participant smartphones. Participants indicated the presence of peers on beacon signal-contingent ecological momentary assessment reports and three daily random reports. Feasibility of participant recruitment was low, primarily due to Android OS updates requiring app revisions that interrupted recruitment. However, feasibility of peer enrollment was high, occurring rapidly but at a lower-than-expected number. Response latencies to signal-contingent and random reports were similar, indicating good feasibility of the ecological momentary assessment report procedures. Acceptability, reflected in high retention for participants and peers, participant self-report ratings, and good ecological momentary assessment report response rates (76%-79%), was high. Functionality was moderate; problems with the app were reported by almost half of participants, and functionality ratings were lower than for acceptability. For validity, the beacon detection technology identified 61% of participant-reported encounters (true positives), with 5.6% false positives. False negatives (39%) were likely due to peer noncompliance or misreporting. Results support the initial utility of Bluetooth-based passive detection for identifying peer presence in real time, offering potential for use in just-in-time interventions targeting health-risk behaviors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).