System Design Considerations Research Articles

Analytical Fragility Surfaces and Global Sensitivity Analysis of Buried Operating Steel Pipeline Under Seismic Loading

The structural integrity of buried pipelines is threatened by the effects of Permanent Ground Deformation (PGD), resulting from seismic-induced landslides and lateral spreading due to liquefaction, requiring accurate analysis of the system performance. Analytical fragility functions allow us to estimate the likelihood of seismic damage along the pipeline, supporting design engineers and network operators in prioritizing resource allocation for mitigative or remedial measures in spatially distributed lifeline systems. To efficiently and accurately evaluate the seismic fragility of a buried operating steel pipeline under longitudinal PGD, this study develops a new analytical model, accounting for the asymmetric pipeline behavior in tension and compression under varying operational loads. This validated model is further implemented within a fragility function calculation framework based on the Monte Carlo Simulation (MCS), allowing us to efficiently assess the probability of the pipeline exceeding the performance limit states, conditioned to the PGD demand. The evaluated fragility surfaces showed that the probability of the pipeline exceeding the performance criteria increases for larger soil displacements and lengths, as well as cover depths, because of the greater mobilized soil reaction counteracting the pipeline deformation. The performed Global Sensitivity Analysis (GSA) highlighted the influence of the PGD and soil–pipeline interaction parameters, as well as the effect of the service loads on structural performance, requiring proper consideration in pipeline system modeling and design. Overall, the proposed analytical fragility function calculation framework provides a useful methodology for effectively assessing the performance of operating pipelines under longitudinal PGD, quantifying the effect of the uncertain parameters impacting system response.

Enhancing Prehospital Decision-Making: Exploring User Needs and Design Considerations for Clinical Decision Support Systems.

In prehospital emergency care, providers face significant challenges in making informed decisions due to factors such as limited cognitive support, high-stress environments, and lack of experience with certain patient conditions. Effective Clinical Decision Support Systems (CDSS) have great potential to alleviate these challenges. However, such systems have not yet been widely adopted in real-world practice and have found to cause workflow disruptions and usability issues. Therefore, it is critical to investigate how to design CDSS that meet the needs of prehospital providers while accounting for the unique characteristics of prehospital workflows. We conducted semi-structured interviews with 20 prehospital providers recruited from four emergency medical services (EMS) agencies in an urban area in the northeastern U.S. The interviews focused on the decision-making challenges faced by prehospital providers, their technological needs for decision support, and key considerations for the design and implementation of a CDSS that can seamlessly integrate into prehospital care workflows. The data were analyzed using content analysis to identify common themes. Our qualitative study identified several challenges in prehospital decision-making, including limited access to diagnostic tools, insufficient experience with certain critical patient conditions, and a lack of cognitive support. Participants highlighted several desired features to make CDSS more effective in the dynamic, hands-busy, and cognitively demanding prehospital context, such as automatic prompts for possible patient conditions and treatment options, alerts for critical patient safety events, AI-powered medication identification, and easy retrieval of protocols and guidelines using voice commands. Key considerations for successful CDSS adoption included prioritizing alerts to reduce alert fatigue and workflow disruptions, facilitating real-time data collection and documentation to enable decision generation, and ensuring trust and accountability while preventing over-reliance when using CDSS. This study provides empirical insights into the challenges prehospital providers face and offers design recommendations for developing CDSS solutions that align with prehospital workflows.

Natural fiber reinforced polymer composites for ballistic protection: Design, performance, and challenges

The increasing demand for sustainable and lightweight materials in defense and security applications has driven the development of natural fiber-reinforced polymer composites (NFRPCs) for ballistic protection. This paper explores the potential of NFRPCs in ballistic armor, focusing on material design, performance evaluation, and the challenges encountered in their application. Natural fibers, such as jute, flax, and hemp, offer significant environmental and weight advantages over traditional synthetic fibers while providing acceptable impact resistance when embedded in polymer matrices. The design considerations for NFRPCs-based ballistic protection systems are examined, highlighting the interplay between fiber type, matrix selection, and composite architecture. The ballistic impact behavior of these composites is assessed through various testing methodologies, emphasizing their energy absorption, deformation mechanisms, and multi-hit performance under different threat levels. Furthermore, this study presents an analysis of the key challenges—ranging from fiber variability and moisture absorption to the optimization of mechanical properties—that hinder widespread adoption in high-performance armor applications. The results underline the potential of NFRPCs as a cost-effective, eco-friendly alternative for protective armor while emphasizing the need for further research to overcome performance limitations. Ultimately, this work aims to provide a foundation for advancing sustainable ballistic protection materials through innovative design and testing strategies.

Spaceborne SAR System Design Considerations: Minimizing Satellite Size and Mass, System Parameter Trade-Offs, and Optimization

The goal of this research is to assess and guide the development of next-generation synthetic aperture radar (SAR) satellites, optimize their performance, and present the requirements related to the design parameters. In the current era, characterized by the rapid advancement of SAR technologies, the challenge of designing compact and efficient satellites is more relevant than ever. The present research provides a comprehensive analysis of design parameters for microsatellite applications, including altitude, incidence angle, operating frequency, antenna sizing, and transmitting power. The complex relationships between these parameters and their combined impact on SAR system performance and satellite dimensions are demonstrated through various scenarios. Special attention is given to balancing the SAR antenna area and the transmitting power needs, which are primary constraints in SAR microsatellite design. A detailed comparative study is presented, highlighting how each design decision affects the overall functionality and performance. Modern SAR satellites with masses under 150 kg can operate with approximately 1 kW of transmitting power and a 10 m2 SAR antenna area. The present results analyze and validate the key parameters related to these satellites, coping with the challenging trade-offs through optimization. Furthermore, this study aims to guide future innovative spaceborne SAR system design, highlighting the potential of optimization techniques in advancing spaceborne SAR technology.

A Review of the Application of the Laser-Light Backscattering Imaging Technique to Agricultural Products

Growing concerns about food safety and waste have increased consumer demand for high-quality agricultural products, particularly at the postharvest stage. This demand has prompted the development of non-destructive methods to assess or inspect the internal quality of fruits and vegetables. The backscattering imaging technique, also known as diffuse reflectance imaging, is considered a highly promising approach. Numerous studies have focused on practical applications, using laser light at selected wavelengths to develop quick multispectral methods. Due to the rapid interaction of photons with biological tissue, together with the highly computational performance of machine vision, backscattering imaging can offer a valuable alternative to traditional methods. Its primary benefits include quick measurements without chemical sample preparation, easy integration with high-throughput automatic quality control, and reduced waste, since this non-destructive technique does not damage samples. This review presents a comprehensive overview of backscattering imaging, including the measurement geometry, data analysis, and design considerations for vision systems. Additionally, it explores this technique’s advantages, challenges, and accuracy, as demonstrated using various case studies.

Design requirements for human UHF magnets from the perspective of MRI scientists

Abstract The highest magnetic field strength for human-sized magnetic resonance imaging (MRI) currently lies at 11.7 tesla. Given the opportunities for enhanced sensitivity and improved data quality at higher static magnetic fields, several initiatives around the world are pursuing the implementation of further human MRI systems at or above 11.7 tesla. In general, members of the MR research community are not experts on magnet technology. However, the magnet is the technological heart of any MR system, and the MRI community is challenging the magnet research and design community to fulfill the current engineering gap in implementing large-bore, highly homogeneous and stabile magnets at field strengths that go beyond the performance capability of niobium-titanium. In this article, we present an overview of magnet design for such systems from the perspective of MR scientists. The underlying motivation and need for higher magnetic fields are briefly introduced, and system design considerations for the magnet as well as for the MRI subsystems such as the gradients, the shimming arrangement, and the radiofrequency hardware are presented. Finally, important limitations to higher magnetic fields from physiological considerations are described, operating under the assumption that any engineering or economic barriers to realizing such systems will be overcome.

Electrical Fire Safety Considerations in the Fire Protection System Design of High-rise Buildings

High-rise buildings, as significant symbols of urban development, demand critical attention to the electrical fire safety design of their fire protection systems. This paper aims to explore the electrical fire safety design in the fire protection systems of high-rise buildings to enhance fire safety. By comprehensively analyzing the principles and methods of electrical fire safety design, the feasibility and effectiveness of such systems in high-rise buildings are examined. This study also considers modern technologies and innovations to improve the performance of electrical fire safety systems. Finally, several recommendations are proposed to strengthen the practical application of electrical fire safety design in high-rise buildings.

A real-time on-site precision nutrient monitoring system for hydroponic cultivation utilizing LIBS

Indoor hydroponic farming is an advanced cultivation technique with diverse sustainability benefits, such as facilitating local produce, minimizing transportation costs and emissions, and enabling year-round crop cultivation. To optimize crop growth for enhanced yield, improved crop quality, and reduced environmental footprint, precise monitoring and replenishment of essential nutrients within hydroponic systems is crucial. Current methods employed in most commercial farms for online nutrient supply monitoring is limited to pH and conductivity measurements. These techniques can only offer an indication of the overall change in the complex nutrient mixture and lack the capability to precisely identify the specific nutrient or quantify the nutrient content. Most of the existing techniques for measuring individual nutrient levels are expensive and invasive, necessitating sample preparation, frequent recalibration, and skilled personnel for operation. In this context, we propose and demonstrate a real-time, on-site monitoring system for the precise analysis of hydroponic nutrient supply based on laser-induced breakdown spectroscopy (LIBS). We also discuss the system design considerations, parametric optimizations, limit of detection (LOD), and limit of quantitation (LOQ) of key nutrient components such as potassium (K), sodium (Na), calcium (Ca), and magnesium (Mg), using the proposed approach. The detection range of the developed LIBS-based monitoring system can encompass the typical concentration range observed in hydroponic nutrient solutions used at agricultural farms. This technique offers rapid online monitoring of individual nutrient components, providing precise, real-time analysis and the potential to enable comprehensive automation capabilities for current and future hydroponic farms.Graphical abstract

A capacitive power transfer system with LCL primary compensation for very‐low‐power portable devices

AbstractThis paper investigates and technically demonstrates a capacitive power transfer (CPT) system applicable to the charging of emerging very‐low‐power portable devices. The constant‐current operation of the primary LCL compensation in CPT is implemented and analysed to simplify the system design process and minimize the configuration on the receiving side. Additionally, the system design considerations for the capacitive coupler and the diode rectifier are presented based on the battery charging specifications. All the design concepts and considerations are validated through experimentation with a 13.56 MHz CPT system, which achieves load‐independent constant‐current output from full‐load to light‐load (one‐tenth of the full load) charging operations.

Free Space Optical Communication and its Implementation Using Diffractive Optical Elements Using Artificial Intelligence (AI)

Background: Free Space Optics (FSO) is a wireless data transmission method for infrastructure that uses laser beam energy to transmit information waves through the atmosphere. Furthermore, due to its high bandwidth potential and simple deployment, FSO has garnered considerable interest. However, atmospheric turbulence and misalignment present obstacles to establishing dependable and effective FSO links. Objective: For systems varying from space invariant to totally space variant, the optimal design of free-space optical connectivity systems using diffractive optics is found from an engineering perspective. Parameters such as the light's wavelength, the system's total number of optical sources and detectors, their sizes, and their spacing are used to determine the system's volume. Another important parameter is the diffractive lens's f-number. Diffraction Optical Elements (DOEs) have emerged as a promising means of addressing these difficulties. Also, the patent related to automated honey beehive box gives the insight of its monitoring system. Methods:: This paper provides an overview of the implementation and advancements of FSO systems utilizing DOEs, including the fundamental principles, design considerations, and performance improvements. The study discusses the basics of diffraction and the role of DOEs in FSO systems. It explores the diffraction grating equation and the Huygens-Fresnel principle to understand wave propagation and interference phenomena. Design considerations for FSO systems equipped with DOEs are discussed, including the selection of appropriate DOEs and evaluation of performance benefits. The study also investigates the application of AI methods, such as machine learning and deep learning, in optimizing FSO systems with DOEs. Results: A thorough overview of Free Space Optics (FSO) systems utilizing Diffraction Optical Elements (DOEs) is given in this review study. It examines diffraction theory and DOE use in FSO, emphasizing their potential for beam forming, beam steering, and adaptive optics. The study examines FSO with DOE design concerns, performance improvements, applications, and future approaches. FSO systems may overcome problems with air turbulence, misalignment, and fading by using the characteristics of DOEs, opening the door for dependable and effective wireless communication. Conclusion: In conclusion, the effect of DOEs on BER efficiency is also modified by the obscuration ratio. Transmission power is increased when more DOEs are used by an amount defined by their obscuration ratios. Additionally, because of the increased power complement in these systems, the effect of DOEs is more pronounced. The integration of AI further enhances FSO capabilities by providing adaptive optimization, fault detection, predictive maintenance, and improved security. Future research directions may include exploring advanced AI techniques and conducting practical implementations of FSO systems with DOEs for various applications, particularly in Internet of Things (IoT) scenarios.

Exploring design considerations for multimodal learning analytics systems: an interview study

Exploring design considerations for multimodal learning analytics systems: an interview study

Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.

Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size. The Bureau of Communicable Disease's systems have quickly detected outbreaks of salmonellosis, legionellosis, shigellosis, and COVID-19. This tutorial details system design considerations, including geographic and temporal data aggregation, study period length, inclusion criteria, whether to account for population size, network location file setup to account for natural boundaries, probability model (eg, space-time permutation), day-of-week effects, minimum and maximum spatial and temporal cluster sizes, secondary cluster reporting criteria, signaling criteria, and distinguishing new clusters versus ongoing clusters with additional events. We illustrate how to support health equity by minimizing analytic exclusions of patients with reportable diseases (eg, persons experiencing homelessness who are unsheltered) and accounting for purely spatial patterns, such as adjusting nonparametrically for areas with lower access to care and testing for reportable diseases. We describe how to fine-tune the system when the detected clusters are too large to be of interest or when signals of clusters are delayed, missed, too numerous, or false. We demonstrate low-code techniques for automating analyses and interpreting results through built-in features on the user interface (eg, patient line lists, temporal graphs, and dynamic maps), which became newly available with the July 2022 release of SaTScan version 10.1. This tutorial is the first comprehensive resource for health department staff to design and maintain a reportable communicable disease outbreak detection system using SaTScan to catalyze field investigations as well as develop intuition for interpreting results and fine-tuning the system. While our practical experience is limited to monitoring certain reportable diseases in a dense, urban area, we believe that most recommendations are generalizable to other jurisdictions in the United States and internationally. Additional analytic technical support for detecting outbreaks would benefit state, tribal, local, and territorial public health departments and the populations they serve.

Effective Motion Self-Learning Genre Using 360° Virtual Reality Content on Mobile Device: A Study Based on Taichi Training Platform.

Online fitness training, with its affordability and flexibility, offers a convenient way for individuals to engage in regular workouts that promote physical and mental health. Yet, learning fitness motions in this way presents various challenges and may not always be as effective as in-person training. To address the practical demands of motion learning, we conducted a systematic survey and accordingly proposed a four-stage self-learning genre that integrates immersive virtual reality (VR) environments with motion skill learning theories, strategies, and expert experience. Herein, we merged progressive structures and multi-level visual cues to enhance instruction, and proposed a fine-grained motion analysis method to provide adaptive correction feedback during training. Utilizing a Taichi training platform with the genre embedded, we systematically validated the effectiveness of the genre, and examined the potential impact of VR content presentation form on motion learning among different age groups, as well as their preferences and focus on VR fitness training genre design. Results from the quantitative analysis, qualitative evaluation, and case study showed that the 360° video-based VR content brought more positive motion learning performance and user experiences than the fully-simulated VR used in many previous studies. The proposed genre demonstrated outstandingly performance, experience, and usability, with each stage and design playing an effective role. Moreover, we offer several design considerations for VR fitness systems targeting diverse age groups, providing beneficial insights for VR development in the sports and health-related fields.

Laboratory Demonstration of Grating Embedded Mirrors for Single-Shot Heliostat Optical Metrology

Abstract Concentrated solar power (CSP) plants need to monitor the surface slope error of thousands of heliostats with sub-milliradian accuracy. Large numbers of heliostats installed in harsh environments mean that measurement speed and durability are key design considerations for metrology systems. We present a compact, accurate, and high-speed heliostat slope error metrology system that is robust to the harsh environmental conditions at CSP plants. The system is composed of (1) grating embedded mirrors (GEMs), which have multiple different phase diffraction gratings written within a glass mirror substrate, and (2) a compact optical system, the diffractive auto-stigmatic Hartmann camera (DASHCam). Using focused ultrafast laser pulses, we write phase gratings within second-surface float glass mirror without damaging the reflective coating on the backside. The gratings direct a small fraction of incident light to non-specular directions, which the DASHCam senses from a virtual center of curvature to measure the mirror slopes at each grating patch. In a CSP plant, each heliostat mirror would be a GEM, and the DASHCam would rapidly measure slope and canting errors during heliostat manufacturing, installation, or operation. We fabricated 0.1 meter-diameter GEMs with 24 grating patches, built a prototype DASHCam system, and tested the system repeatability and accuracy by comparing against a Fizeau interferometer. Our results show, in a laboratory environment, 24μrad root mean square (RMS) measurement repeatability and 47μrad RMS accuracy, with single-shot image capture. The combination of GEMs and DASHCam is a promising metrology approach that could lead to improved optical accuracy of heliostats throughout their life cycle. This work serves as a proof of principle for this system.

Digital Twin-Enabled Response Function Analysis: A Synthetic Approach to Ship's Propulsion System Assessment

Analyzing the behavior of vessels in actual sea conditions is crucial for conceptual system design, safety and energy efficiency considerations. However, the essential seakeeping problem is reduced to the analysis of wave-hull interactions often neglecting consideration of the propulsion. But in the meantime, the synthetic consideration of wave–propulsion interactions is a key for safety and energy efficiency. Furthermore, safety evaluation of a ship's design with reduced propulsion power in adverse seas is vital for risk management. Response functions are commonly used to estimate propulsion system responses in incoming seaways. This paper proposes a synthetic approach using digital twin technology for rapid response function estimation. It introduces a companion linearized state-space model linked with the digital twin, enabling immediate retrieval of coefficients for response function analysis at the desired operating point. This integrated methodology provides a comprehensive representation of ship propulsion behavior in wave environments, offering a comprehensive framework for system performance assessment.

Comparing Pr3+ and Nd3+ for deactivating the Er3+: 4I13/2 level in lanthanum titanate glass

Erbium lanthanum titanate glasses were prepared by levitation melting for the spectroscopic study of ways to promote the mid-infrared fluorescence. Two series of heavily erbium doped glasses (15 wt%) were prepared with the addition of either Pr3+ or Nd3+ in amounts relative to Er3+ of 0.05, 0.1, and 0.2. Both ions quench the lower Er3+ laser level with the Pr3+ doing so more rapidly. Although high co-dopant concentrations result in higher energy transfer, as clearly evidenced in upconversion and downconversion fluorescence measurements, the mid-infrared lifetime also suffers a reduction and, therefore, a balance must be struck in the co-dopant concentration. Lifetime and spectral measurements indicate that, at a fixed relative co-dopant amount, Pr3+ is more effective than Nd3+ at removing the bottleneck of the Er3+ 4I13/2 level. Moreover, consideration of the lifetimes alongside the absorption data of the individual ions indicates that despite the large absorption cross-section of Nd3+ at 808 nm, the concentration needed to yield more absorbed power than utilizing direct 976 nm excitation of Er3+ results in unfavorable lifetimes of the mid-infrared transition. In the end, Pr3+ prevails as the superior co-dopant in terms of the effects on fluorescence lifetimes as well as potential laser system design considerations. In a unique self-doping approach, a reducing melt atmosphere of Ar instead of O2 creates a small fraction of Ti3+. In 5Er2O3-12La2O3-83TiO2 glass, the presence of Ti3+ quenches the 4I13/2 emission about 2.6 times more than the 4I11/2 when lifetimes are compared to an O2 melt environment. As an additional means of increasing the mid-infrared emission, the effect of temperature on the mid- and near- infrared lifetimes of a lightly doped lanthanum titanate composition is investigated between 77-300 K. The mid-infrared lifetime increases by ∼30% while the near-infrared lifetime increases by ∼10%, which suggests in addition to co-doping, active cooling of the gain media will further enhance performance.

Optimizing GANs for Cryptography: The Role and Impact of Activation Functions in Neural Layers Assessing the Cryptographic Strength

Generative Adversarial Networks (GANs) have surfaced as a transformative approach in the domain of cryptography, introducing a novel paradigm where two neural networks, the generator (akin to Alice) and the discriminator (akin to Bob), are pitted against each other in a cryptographic setting. A third network, representing Eve, attempts to decipher the encrypted information. The efficacy of this encryption–decryption process is deeply intertwined with the choice of activation functions employed within these networks. This study conducted a comparative analysis of four widely used activation functions within a standardized GAN framework. Our recent explorations underscore the superior performance achieved when utilizing the Rectified Linear Unit (ReLU) in the hidden layers combined with the Sigmoid activation function in the output layer. The non-linear nature introduced by the ReLU provides a sophisticated encryption pattern, rendering the deciphering process for Eve intricate. Simultaneously, the Sigmoid function in the output layer guarantees that the encrypted and decrypted messages are confined within a consistent range, facilitating a straightforward comparison with original messages. The amalgamation of these activation functions not only bolsters the encryption strength but also ensures the fidelity of the decrypted messages. These findings not only shed light on the optimal design considerations for GAN-based cryptographic systems but also underscore the potential of investigating hybrid activation functions for enhanced system optimization. In our exploration of cryptographic strength and training efficiency using various activation functions, we discovered that the “ReLU and Sigmoid” combination significantly outperforms the others, demonstrating superior security and a markedly efficient mean training time of 16.51 s per 2000 steps. This highlights the enduring effectiveness of established methodologies in cryptographic applications. This paper elucidates the implications of these choices, advocating for their adoption in GAN-based cryptographic models, given the superior results they yield in ensuring security and accuracy.

The role of algae-based wastewater treatment systems: A comprehensive review

Algae-based wastewater treatment systems have gained significant attention as sustainable and efficient solutions for nutrient removal, organic pollutant degradation, and biomass production. This comprehensive review explores the role of algae-based systems in wastewater treatment, covering key aspects such as nutrient uptake mechanisms, cultivation techniques, system design considerations, and environmental sustainability implications. Algae offer unique advantages for wastewater treatment, including high nutrient removal rates, CO2 sequestration, and the production of valuable biomass for biofuel production and nutrient recycling. Various cultivation methods, including open ponds, raceways, photobioreactors, and wastewater treatment wetlands, are evaluated for their suitability in different wastewater treatment scenarios. The integration of algae-based systems with conventional wastewater treatment processes, such as activated sludge and membrane bioreactors, is discussed to enhance treatment efficiency and resource recovery. Furthermore, the environmental sustainability of algae-based systems, including carbon footprint, water footprint, and ecosystem impacts, is assessed to identify opportunities for mitigating environmental impacts and promoting ecosystem resilience. Future research directions in algae-based wastewater treatment systems, such as optimization of cultivation conditions, development of novel algal strains, and techno-economic analysis of large-scale implementation, are proposed to address remaining challenges and accelerate the adoption of algae-based technologies in wastewater treatment practices. Overall, this review provides valuable insights into the role of algae-based systems as sustainable and versatile tools for wastewater treatment, highlighting their potential to address the growing challenges of nutrient pollution and water scarcity in the 21st century.

Advancing traffic safety through the safe system approach: A systematic review

The Safe System Approach (SSA) has emerged as a comprehensive framework for enhancing traffic safety through system-wide interventions. This systematic review, conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzes 82 relevant studies categorized based on the SSA pillars: safe road users, safe vehicles, safe speeds, safe roads, and post-crash care. The review provides insights into SSA's effectiveness in reducing road traffic fatalities and injuries, exploring implementation challenges and opportunities, including policy initiatives, institutional frameworks, and stakeholder collaborations. The findings highlight the potential for SSA to create a more forgiving and resilient transportation system, offering valuable guidance for policy decisions, future research, and interventions aimed at promoting safer road environments. SSA's comprehensive strategy for Safe Road Users encompasses considerations of road system design, behavior modification, and tailored measures for vulnerable users, showcasing its versatility in addressing diverse challenges. In the realm of Safe Vehicles, SSA actively involves manufacturers in a cycle of continuous improvement, rigorous testing, and collaborative efforts to establish new safety regulations. The emphasis on managing Safe Speeds, aligning with human parameters, and involving communities reflects SSA's adaptable nature and provides insights for establishing context-specific speed limits. SSA contributes significantly to Safe Roads through its implementation of innovative countermeasures, forgiving road designs, and the integration of emerging disciplines, resulting in a notable reduction in fatalities and injuries. In the domain of Post-Crash Care, SSA's integrated perspective fosters collaboration among emergency services, medical professionals, and the justice system. It addresses challenges through standardized approaches and information sharing, ensuring a comprehensive and unified approach to road safety. This review contributes to the ongoing efforts to prioritize safety and transform the transportation landscape on a global scale.

Waveguide Eavesdropping Threat for Terahertz Wireless Communications

As wireless communications move to higher frequency band for 5G networks and beyond, resiliency against eavesdropping and other security threats is still one of the key system-design considerations. Compared to data transmissions by lower frequencies, terahertz links are inherently more robust against eavesdropping attacks due to their propagation characteristics (such as high free-space path loss) and aligned link path by high-gain antennas. However, it does not indicate that eavesdropping is always impossible. Line-of-sight terahertz links have proven to be vulnerable to active/passive eavesdroppers by placing scatters in the path of data transmission, or by collecting side-lobe leakages. Here, we demonstrate a waveguide-based approach for signal eavesdropping which can be operated much more feasibly with several advantages, such as lower propagation loss and reliable data interception. Our method relies on a 3D printed rectangular dielectric waveguide and can overcome spatial limitations caused by directional modulation or near-field modulation. We demonstrate successful eavesdropping attacks for a 16 quadrature amplitude modulated (16-QAM) data link at rates up to 5 gigabits per second. Our work highlights the importance of system designs in resisting waveguide-based eavesdropping strategies and identifies aspects where