Search Results (317)

The modern power grid is considered a Smart Grid (SG) when it relies extensively on technologies that integrate traditional power infrastructure with Information and Communication Technologies (ICTs). The dependence on Internet of Things (IoT)-based communication systems to operate physical power devices transforms the grid into a complex system of systems (SoS), introducing cybersecurity vulnerabilities across various SG layers. Several surveys have addressed SG cybersecurity, but none have correlated recent developments with the NIST seven-domain framework, a comprehensive model covering all major SG domains and crucial for domain-level trend analysis. To bridge this gap, we systematically review and classify studies by impacted NIST domain, threat type, and methodology (including tools/platforms used). We note that the scope of applicability of this study is 60 studies (2011–2024) selected exclusively from IEEE Xplore. Unlike prior reviews, this work maps contributions to the NIST domain architecture, examines temporal trends in research, and synthesizes cybersecurity defenses and their limitations. The analysis reveals that research is unevenly distributed: the Operations domain accounts for ~35% of all studies, followed by Generation ~25% and Distribution ~14%, while domains like Transmission (~9%) and Service Provider (5%) are comparatively under-studied. We find a heavy reliance on simulation-based tools (~46% of studies) such as MATLAB/Simulink, and False Data Injection (FDI) attacks are predominantly studied, comprising approximately 36% of analyzed attacks. The broader objective of this work is to guide researchers and SG stakeholders (e.g., utilities, policy-makers) toward understanding and coordinating strategies for improving system-level cyber-resilience, which is crucial for future SGs, while avoiding any overstatement of findings beyond the reviewed evidence. Full article

This essay examines how Shakespeare’s King Lear and Tarkovsky’s Nostalghia employ fool figures to articulate truths inaccessible through rational discourse. The Fool in King Lear speaks through riddles, songs, and prophecies, revealing uncomfortable realities about power and identity that direct statement cannot safely convey. His performed madness contrasts with Lear’s genuine descent into insanity, yet both states access knowledge unavailable to those maintaining social position and sanity. Tarkovsky’s Domenico embodies the Russian Orthodox tradition of yurodstvo (holy foolishness), performing sacred madness through impossible rituals and apocalyptic prophecy. His mathematical impossibility—“1 + 1 = 1”—expresses spiritual unity that logic cannot grasp. Both figures draw on Plato’s distinction in the Phaedrus between divine madness and human pathology, where four forms of god-sent mania provide superior insight into rational thought. Through Erasmus’s humanist satire and Foucault’s analysis of reason’s violent separation from unreason, the essay traces how Western culture moved from integrating fool-wisdom to confining it as pathology. The protective mechanisms enabling fool-speech—performance frames, liminal positioning, sacred authorization—reveal society’s ambivalent need for dangerous truths. As contemporary culture increasingly medicalizes cognitive deviation, these masterworks preserve essential epistemological functions, demonstrating why certain truths require the fool’s disruptive voice. Full article

Pneumatic Artificial Muscles (PAMs) are soft actuators that mimic the contractile behavior of biological muscles through fluid-driven deformation. Originating from McKibben’s 1950s braided design, PAMs have evolved into a diverse class of actuators, offering high power-to-weight ratios, compliance, and safe human interaction, with applications spanning rehabilitation, assistive robotics, aerospace, and adaptive structures. This review surveys recent developments in actuation mechanisms and applications of PAMs. Traditional designs, including braided, pleated, netted, and embedded types, remain widely used but face challenges such as hysteresis, limited contraction, and nonlinear control. To address these limitations, researchers have introduced non-traditional mechanisms such as vacuum-powered, inverse, foldable, origami-based, reconfigurable, and hybrid PAMs. These innovations improve the contraction range, efficiency, control precision, and integration into compact or untethered systems. This review also highlights applications beyond conventional biomechanics and automation, including embodied computation, deployable aerospace systems, and adaptive architecture. Collectively, these advances demonstrate PAMs’ expanding role as versatile soft actuators. Ongoing research is expected to refine material durability, control strategies, and multifunctionality, enabling the next generation of wearable devices, soft robots, and energy-efficient adaptive systems. Full article

The integration of artificial intelligence (AI) into the Internet of Things (IoT) has revolutionized industries, enabling smarter decision-making through real-time data analysis. However, the inherent complexity and opacity of many AI models pose significant challenges to trust, accountability, and safety in critical applications such as healthcare, industrial automation, and cybersecurity. Explainable AI (XAI) addresses these challenges by making AI-driven decisions transparent and interpretable, empowering users to understand, validate, and act on algorithmic outputs. This paper examines the pivotal role of XAI in IoT development, synthesizing advancements, challenges, and opportunities across domains. Key issues include the computational demands of XAI methods on resource-constrained IoT devices, the diversity of data types requiring adaptable explanation frameworks, and vulnerabilities to adversarial attacks that exploit transparency. By looking at healthcare IoT, predictive maintenance, and smart homes, we can see how XAI bridges the gap between complex algorithms and human-centric usability—for instance, clarifying medical diagnoses or justifying equipment failure alerts. We discuss multiple XAI implementations with IOT, such as lightweight XAI for edge devices and hybrid models combining rule-based logic with deep learning. This paper advocates for XAI as a cornerstone of trustworthy IoT ecosystems, ensuring transparency without compromising efficiency. As IoT continues to shape industries and daily life, XAI will remain essential to fostering accountability, safety, and public confidence in automated systems. Full article

Carbon programs often assume that uniform cash transfers are sufficient to change land use, yet the design of benefits may be the controlling factor. We test payment complementarity—the coordinated use of cash and community benefits—in the International Small Group and Tree Planting Program across Kenya, Tanzania, Uganda, and India. Using administrative and survey data from 8432 participants, we classify realized mechanisms into cash-only, alternative-only, and mixed categories, and examine their associations with conservation adoption and land-use intensity. Mixed arrangements are associated with 73% higher conservation farming adoption (68.4% vs. 36.6% under cash-only) and greater tree density (281 vs. 215 and 115 trees/ha for cash-only and alternative-only, respectively). Formal tests reject simple averaging, consistent with super-additive effects. Adoption of mixed mechanisms clusters in districts that exceed an organizational participation threshold (approximately 38.9%), suggesting peer exposure and social learning. Gender-disaggregated patterns indicate that women receiving alternatives (predominantly in mixed regimes) manage nearly three times as many trees as their cash-only peers and are the only subgroup surpassing the USD 2/day poverty threshold. Each alternative arrangement benefits an average of 167 community members; accounting for spillovers implies an approximate 191-times village-level multiplier. Mixed designs require greater administrative effort but deliver larger community returns. We report associations, not causal effects, and employ controls, fixed effects, matching, and stability checks to probe our selection. Policy implications are immediately clear: outcome-based standards that permit mixed payments, credit spillovers, and paired flexibility with safeguards (transparent negotiation, verified delivery, documented consent) can multiply the land-use impact of climate finance. The results are associative rather than causal and generalize primarily to contexts with similar institutional prerequisites, including established organizational capacity and program rules permitting benefit negotiation. Full article

Autonomy is enabled by the close connection of traditional mechanical systems with information technology. Historically, both communities have built norms for validation and verification (V&V), but with very different properties for safety and associated legal liability. Thus, combining the two in the context of autonomy has exposed unresolved challenges for V&V, and without a clear V&V structure, demonstrating safety is very difficult. Today, both traditional mechanical safety and information technology rely heavily on process-oriented mechanisms to demonstrate safety. In contrast, a third community, the semiconductor industry, has achieved remarkable success by inserting design artifacts which enable formally defined mathematical abstractions. These abstractions combined with associated software tooling (Electronics Design Automation) provide critical properties for scaling the V&V task, and effectively make an inductive argument for system correctness from well-defined component compositions. This article reviews the current methods in the mechanical and IT spaces, the current limitations of cyber-physical V&V, identifies open research questions, and proposes three directions for progress inspired by semiconductors: (i) guardian-based safety architectures, (ii) functional decompositions that preserve physical constraints, and (iii) abstraction mechanisms that enable scalable virtual testing. These perspectives highlight how principles from semiconductor V&V can inform a more rigorous and scalable safety framework for autonomous systems. Full article

General aviation (GA), comprised mainly of piston engine airplanes, has an inferior safety history compared with air carriers in the United States. Most studies addressing this safety disparity has focused on pilot deficiencies. Herein, we determined the rates/causes of equipment failure-related GA fatal accidents for type-certificated and experimental-amateur-built airplanes. Aviation accidents/injury severity were per the NTSB Access^R database. Statistical tests employed proportion/binomial tests/a Poisson distribution. The rate of fatal accidents (1990–2019) due to equipment failure was unchanged (p > 0.026), whereas the fatal mishap rate related to other causes declined (p < 0.001). A disproportionate (2× higher) count (p < 0.001) of equipment-related fatal accidents was evident for experimental-amateur-built aircraft with type-certificated references. Propulsion system (67%) and airframe (36%) failures were the most frequent causes of fatal accidents for type-certificated and experimental-amateur-built aircraft, respectively. The components “fatigue/corrosion” and “manufacturer–builder error” resulted in 60% and 55% of powerplant and airframe failures, respectively. Most (>90%) type-certificated aircraft propulsion system failures were within the manufacturer-prescribed engine time-between-overhaul (TBO) and involved components inaccessible for examination during an annual inspection. There is little evidence for a decline in equipment failure-related fatal accident rate over three decades. Considering the fact that powerplant failures mostly occur within the TBO and involve fatigue/corrosion of one or more components inaccessible for examination, GA pilots should avoid operations where a safe off-field landing within glide-range is not assured. Full article

In this paper we present a brief review of extended general relativity in four dimensions and solve versions of the extended equations for the case of static spherical symmetry in various contexts, for a previously studied Lagrangian. The exterior vacuum yields a Schwarzschild solution with an additional scalar field potential that falls off logarithmically, the latter essentially an inverse square force. That is probably not adequate as a dark matter force, but might contribute. When a constant density field of ions holds sway in the exterior, a solution identical to the cosmological constant extension of Schwarzschild occurs, together with a scalar field potential declining as $r^{-3/2}$, however it is not asymptotically flat. An inverse square declining distribution of ionic material, according to perturbation theory, results in an additional linear gravity potential that would provide further attraction in the gravity term. A limited exact solution in the same case yields a cubic equation with a Schwarzschild solution, corresponding to $A=0$, and two MOND-like possible potentials, one vanishing at infinity, but a better solution must be found. The approximate solution is complex (one of many) and the system requires further study. Ionic matter is ubiquitous in the universe and provides a source for the scalar field, which suggests that the extended Einstein equations could be of utility in the dark matter problem, provided such an electromagnetic scalar force could be found and differentiated from the usual, far stronger electromagnetic forces. Further, it’s possible that the strong photon flux outside stars might have an influence, and is under current investigation. These calculations show that extending the concept of curvature and working in four dimensions with larger operators may bring new tools to the study of physics and unified field theories. Full article

The aviation industry requires a series of actions that will transform its current status, aiming for sustainable operations. Aviation’s end-of-life stream is a pivotal lever for circularity, yet current dismantling and recycling practices leave significant value unrealized. Circular Economy could be considered as a transformational approach to the aviation industry and address its environmental and economic challenges, meeting sustainability principles. This study conducts a PRISMA-guided qualitative systematic review across academic and industry sources to synthesize regulations, technologies, and economics of aircraft decommissioning. It aims to quantify material recovery potential and environmental gains at the aircraft level and assess technology readiness and cost drivers for metals, polymers, and composites. Findings indicate that optimized decommissioning enables high-value part reuse and substantial material recovery (notably aluminum), with associated lifecycle greenhouse-gas avoidance at the aircraft scale. However, high costs, weak regulations, and limited recycling technologies hinder adoption. Results show that optimized dismantling and certified part-reuse pathways can recover up to 85–90% of total aircraft mass, with potential CO₂-emission avoidance of 25–35 t per narrow-body aircraft compared with landfill disposal. Metal recycling technologies (TRL 8–9) already achieve high yields, whereas polymer and composite recycling remain limited (TRL 5–6) by purity and certification barriers. A comparative assessment of EU, US, and Asia–Pacific regulations identifies enforcement and infrastructure gaps hindering implementation. The study introduces an integrated CE roadmap for aviation comprising (i) standards-aligned design-for-disassembly and digital traceability, (ii) accredited MRO-to-reuse networks, and (iii) performance-based policy incentives. Full article

This study examined the impact of a shift schedule change on firefighter sleep and health outcomes (n = 24). Firefighters from a U.S. department transitioned from a 24 h on, 48 h off (24/48) schedule to a 48 h on, 96 h off (48/96) schedule. Wrist actigraphy and self-reported health outcomes were assessed at three time points: baseline (24/48), 3 months post-transition, and 6 months post-transition. Objective sleep measures included total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO). Self-reported health outcomes included the Insomnia Severity Index (ISI), Beck Depression Inventory–II (BDI-II), Beck Anxiety Inventory (BAI), Multidimensional Assessment of Fatigue (MAF), and the Alcohol Use Disorders Identification Test (AUDIT). Linear mixed-effects models (LMMs) with random intercepts were used to evaluate changes over time, adjusting for age, years of service, and individual night-time call volume. Results showed significant improvements in TST, SE, SOL, and WASO at the 3-month follow-up, which were sustained but did not further increase at 6 months. ISI and BDI-II scores also improved, while BAI, MAF, and AUDIT remained stable. These findings suggest that the 48/96 schedule may provide short-term improvements in sleep and psychological health for firefighters in low call-volume settings. Additional research is needed in higher-volume departments and over longer timeframes. Full article

As technology advances, small unmanned aerial vehicles (UAVs) are being engineered for increasingly versatile missions. The Multiple Environment Deployable Aerial Item Delivery (MEDAID) team, composed of 16 senior undergraduate aerospace engineering students, developed the XM-24 Orca as part of a capstone design project. This single-use UAV is designed to deliver medical supplies to soldiers in contested or remote environments. Capable of being ground or air-launched, the Orca incorporates spring-loaded swinging wings to meet a compact 610 mm stowed width requirement, a defining challenge in this project, allowing integration with existing drone platforms. The design effort was driven by key requirements: the ability to carry two 2.3 kg medical aid canisters, achieve a range of at least 370 km, sustain endurance for at least 4 h, and execute a dash speed of 51.4 m/s. This unique combination of mission requirements including airborne launch and wing deployment, extended range, and payload delivery necessitated an innovative design previously undocumented in the literature. The design was developed through rigorous computational analysis, refined through wind tunnel testing, and validated through a series of ground-based and flight tests. This paper documents unique design challenges and innovative solutions that offer guidance for future development efforts. Full article

The geometric content of chaos in nonlinear systems with multiple stabilities of high order is a challenge to computation. We introduce a single algorithmic framework to overcome this difficulty in the present study, where a parametrically forced oscillator with cubic–quintic nonlinearities is considered as an example. The framework starts with the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm, which is a self-learned algorithm that extracts an interpretable and correct model by simply analyzing time-series data. The resulting parsimonious model is well-validated, and besides being highly predictive, it also offers a solid base on which one can conduct further investigations. Based on this tested paradigm, we propose a unified diagnostic pathway that includes bifurcation analysis, computation of the Lyapunov exponent, power spectral analysis, and recurrence mapping to formally describe the dynamical features of the system. The main characteristic of the framework is an effective algorithm of computational basin analysis, which is able to display attractor basins and expose the fine scale riddled structures and fractal structures that are the indicators of extreme sensitivity to initial conditions. The primary contribution of this work is a comprehensive dynamical analysis of the DM-CQDO, revealing the intricate structure of its stability landscape and multi-stability. This integrated workflow identifies the period-doubling cascade as the primary route to chaos and quantifies the stabilizing effects of key system parameters. This study demonstrates a systematic methodology for applying a combination of data-driven discovery and classical analysis to investigate the complex dynamics of parametrically forced, high-order nonlinear systems. Full article

Virtual reality (VR) has emerged as a promising tool for transforming science, technology, engineering, and mathematics (STEM) education, yet its adoption in K–12 classrooms remains uneven and often limited to short-term pilots. While prior studies highlight VR’s potential to increase engagement and support conceptual understanding, questions persist about scalability, sustainability, and equity in implementation. This paper addresses these gaps by synthesizing recent scholarship and proposing a structured framework of best practices for integrating VR into K–12 STEM education. Drawing on academic literature, U.S. policy reports, and case studies, we identify persistent challenges that include high costs, lack of teacher preparation, infrastructure disparities, and overlooked accessibility concerns. We use these findings to inform a phased implementation roadmap. Our framework emphasizes assessment and planning, technical integration, teacher preparation, student implementation, and iterative evaluation, providing actionable strategies for schools and districts. Results of this synthesis indicate that successful VR adoption requires coordinated attention to pedagogy, funding, professional development, and equity. We conclude that moving VR from isolated novelty projects to sustainable and equitable tools in STEM classrooms depends on aligning technology with curricular goals, investing in teacher pipelines, and embedding VR within long-term evaluation and improvement cycles. Full article

The escalating frequency and complexity of cyber threats have made cybersecurity education a national priority, yet a practical gap persists between theoretical instruction and workforce readiness. This study presents a comprehensive, modular framework for designing and implementing cybersecurity laboratories in academic institutions, environments that foster hands-on learning, skill mastery, and curricular innovation. Using a mixed-methods, multi-stage case study approach, the research combined qualitative analysis of institutional practices and instructional methods with quantitative evaluation of learning outcomes to comprehensively examine technical and pedagogical considerations impacting lab development. Data sources included literature analysis, direct observation, document review, and semi-structured interviews. The study synthesized best practices across these domains into a scalable lab design model grounded in experiential learning theory. Results demonstrate that the framework supports enhanced student performance, instructional adaptability, and simulation fidelity. Case study data revealed measurable gains in participant competency, with all participants achieving at least a 20% improvement in post-training test scores, high engagement levels demonstrated through consistent session attendance and active participation in hands-on exercises, and successful adaptation to logistical and technological barriers, including facility relocations and system downtime incidents. The lab’s modularity enabled curricular alignment, resource efficiency, and expansion to serve workforce training initiatives beyond the classroom. By integrating pedagogical (structured, teacher-guided instructional approaches) and andragogical (adult learning) design with technological scalability, this research contributes an actionable roadmap for institutions seeking to modernize cybersecurity education and respond effectively to evolving digital threats. The findings offer broad implications for future curriculum development, facilitator training, and sustainable program implementation. Full article

We propose a novel numerical test to evaluate the reliability of numerical propagations, leveraging the fiber bundle structure of phase space typically induced by Lie symmetries, though not exclusively. This geometric test simultaneously verifies two properties: (i) preservation of conservation principles, and (ii) faithfulness to the symmetry-induced fiber bundle structure. To generalize the approach to systems lacking inherent symmetries, we construct an associated collective system endowed with an artificial G-symmetry. The original system then emerges as the G-reduced version of this collective system. By integrating the collective system and monitoring G-fiber bundle conservation, our test quantifies numerical precision loss and detects geometric structure violations more effectively than classical integral-based checks. Numerical experiments demonstrate the superior performance of this method, particularly in long-term simulations of rigid body dynamics and perturbed Keplerian systems. Full article