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Measuring the Coefficient of Friction Between Snowboard Bases and Terrain-Park Rails Under Dry, Water-Lubricated, and Wax-Lubricated Conditions
This study investigated the friction between a snowboard and a metal park rail under different surface conditions. While snowboard–snow friction has been widely studied, friction between snowboards and rails has received little attention. The mechanism of friction reduction likely to happen is waterlubrication. Waxing can also help by reducing the plowing effect. The experiment is conducted on static dry snow and consists of a snowboarder performing repeated rail slides on a dry rail, a rail sprayed with water, and a rail coated with wax. Motion was recorded on video, and acceleration along the rail was calculated to determine the coefficient of friction. The dry rail had the highest friction, the water-sprayed rail had lower friction, and the waxed rail had the lowest friction. The specific values are provided but are subject to the same number of systematic errors, so they are not emphasized. These results suggest that adding water or wax reduces friction between the snowboard and the rail, with wax having the greatest effect under the tested conditions.
Copyright (c) 2026 Minghuan Zhao, LaNell Williams https://creativecommons.org/licenses/by/4.0
Auditing Operating-Condition Normalization in C-MAPSS Remaining Useful Life Evaluation
NASA C-MAPSS is a canonical benchmark for turbofan remaining useful life (RUL) prediction, yet conclusions can depend on preprocessing and evaluation protocol in addition to model architecture. We present a protocol and reproducibility audit using compact MLP, temporal CNN, and LSTM baselines as controlled probes. A leakage-safe factorial grid varies the C-MAPSS subset, RUL cap, window length, normalization policy, architecture, and random seed, while enforcing and recording a fixed train/validation/final preprocessing fit policy. All 1080 planned canonical-grid runs completed, with no engine-split overlap or non-finite metrics. On single-regime FD001/FD003, global and per-condition normalization are intentionally equivalent in the harness and are used only as an implementation unit test; on multi-regime FD002/FD004, per-condition normalization lowers RMSE in every matched cell, with mean signed RMSE deltas of -4.39 and -7.40, respectively. A focused 720-run FD002/FD004 ablation further shows that jointly refitting the final model and normalizer on train+validation engines changes reported RMSE by -1.119 to -0.206 on average relative to train-only final fitting, depending on subset and normalization. Across the full grid, subset identity explains 60.8% of cell-mean RMSE variation; within multi-regime subsets, RUL cap and normalization are descriptively large among the evaluated protocol factors, with a seed-balanced sensitivity giving the same qualitative conclusion. These results extend prior PHM studies of operating-condition-specific standardization by quantifying matched protocol effects under a frozen audit contract and by making split unit, fit scope, regime assignment, score convention, and reproducibility records explicit.
Copyright (c) 2026 Aaditya Gupta https://creativecommons.org/licenses/by/4.0
Predicting Stacked-Filament Color from Independently Measured Filament Properties
Consumer multi-material fused deposition modeling (FDM) printers reproduce color images by stacking translucent filament layers; stack color must be predicted before printing. Existing workflows predict with a scalar transmission distance (TD) plus manual tuning, or with dense lookup tables (LUTs) per palette. We ask whether per-filament measurements alone predict arbitrary stack combinations. We present a forward model that composes nominal RGB, per-channel TD, an effective attenuation coefficient per filament, a shared monochromatic scattering prefactor, and stack geometry into stack color through a loss-allocation stacking rule; when only a scalar TD is available, the remaining coefficients are estimated on one printed plate, a LUT-free calibration of the same analytic model. Staircase-measured per-channel TDs predict 256-cell clear-filament permutation plates with no parameters fitted on the plates: 18.6 versus 47.2 CIEDE2000 color difference (ΔE00) at best, 42-60% reduction on all six plate/backing combinations. Eight scalars fitted on a plate of five arbitrary non-CMYWK filaments, RGB and per-channel TDs measured off-plate, explain 780 cells at 6.9 ΔE00 (white 5.3, black 8.5); a RAW replication reaches 5.5. A staircase, dual-backing plate, and phone camera supply these properties; a single-point optical filament sensor implies a 75x absorption scale across CMYW filaments and saturates on transparent ones, so it cannot deliver them. On ColorChecker targets across three prints, the model reaches 16.69 versus 30.92 ΔE00 for the community TD-table formula; coefficients are process-conditioned effective values in the sRGB-encoded domain, within which one shared model predicts arbitrary stacks from one measurement per filament.
Copyright (c) 2026 Garnet Liu https://creativecommons.org/licenses/by/4.0
Objective generalized covariant derivative with respect to time in time-varying curvilinear coordinates
This paper develops an objective generalized covariant derivative with respect to time from the perspective of space-time duality. It is formulated in arbitrary time-varying curvilinear coordinate systems and serves as a temporal counterpart of the spatial covariant derivative. Reference bases generated by the Eulerian-Lagrangian tensor are used to construct the temporal covariant derivative. The resulting unified component form contains temporal connection terms determined by the Eulerian-Lagrangian tensor, whereas the spatial connection terms involving Christoffel symbols cancel systematically in the corresponding tensor-entity expansion. Hence, this covariant temporal derivative can be expressed without spatial Christoffel symbols even in time-varying curvilinear coordinates. Classical objective rates, including the Oldroyd, Cotter-Rivlin, Green-Naghdi, and Jaumann rates, are unified and interpreted within this framework. In particular, the Green-Naghdi rate shows that such a Christoffel-free component structure is not restricted to Lie-type objective rates, but can also be obtained for a non-Lie-type rate. The formulation clarifies the common covariant structure of Lie-type and non-Lie-type objective rates, and extends the construction from ordinary tensor components to generalized components.
objective covariant derivative with respect to time
Copyright (c) 2026 Tianyi Zhou, Yajun Yin, Zhimo Jian https://creativecommons.org/licenses/by/4.0
A Decentralized Epidemic LoRa Mesh V2X Architecture for Fleet-Wide Situational Awareness and Opportunistic Coast Guard Alerting in Artisanal Maritime CPS
Artisanal fishing fleets in the Bay of Bengal operate with little or no continuous cellular or satellite coverage, and Automatic Identification System (AIS) or VSAT-class equipment is not economically viable for 10-to-15-meter wooden vessels. We propose a decentralized, edge-intelligent maritime cyber-physical system (CPS) in which every vessel senses and locally classifies its own position, kinematic (oceanic) distress state, mechanical (in-boat) anomaly state, and nearby-intruder status using unsupervised edge machine learning. Rather than routing telemetry to a fixed gateway, vessels exchange and replicate a shared fleet-wide telemetry table over a decentralized vessel-to-vessel (V2X) LoRa mesh using an epidemic (gossip) protocol, so that every vessel eventually holds a synchronized copy of the fleet's last-known state. Because vessels routinely transit toward and away from shore, any vessel that comes within cellular or fixed-gateway range opportunistically uploads its cached fleet-wide table to a coast guard backend, giving near-continuous composite situational awareness without requiring any single vessel to hold a persistent connection. We validate the onboard unsupervised anomaly detectors and the near-field radar physics governing intruder detection on low radar-cross-section wooden hulls through synthetic, physics-grounded simulation, and evaluate the proposed epidemic mesh against a fixed-gateway multi-hop baseline under one shared, corrected two-ray/shadow-fading link-budget model over a realistic 5--60~km offshore fishing area. Over a 6-hour mobility window, the proposed mesh achieves a 0.989--0.999 eventual delivery ratio across 20--100 vessel densities, markedly higher than the fixed-gateway baseline's instantaneous multi-hop packet delivery ratio (PDR) of 0.451--0.999 over the same range, while delivering a median distress-to-shore alert in 33.8--48.5~s.
Copyright (c) 2026 Sunnymoon Rafi https://creativecommons.org/licenses/by/4.0
Propagation Mode Analysis of Undersea Insulated Single-Wire Transmission Line with Open Lossy Boundary
Insulated single wires have been employed for undersea wireless power and data transfer systems. The inner conductor, insulating material and seawater form a structure superficially analogous to a coaxial cable, enabling electromagnetic waves to propagate along the single wire over long distances. Underwater units can wirelessly acquire energy or data via couplers placed near the single wire. However, the semi-infinite open boundary of seawater fundamentally alters the electromagnetic propagation regime. Previous works have largely employed quasi-static approximations in the low-frequency limit or antenna-based models at higher frequencies, both assuming a TEM (or quasi-TEM) mode within the dielectric insulation. The TEM assumption underlying both approaches breaks down at electrically significant scales. Starting from Maxwell's equations under the semi-infinite open boundary of seawater, this paper derives the propagation modes of the single-wire transmission line. The analysis reveals that the structure does not support a standard TEM mode, but exclusively the TM0 mode. The theoretical predictions are validated by full-wave simulations in CST, using a 1 m long insulated wire model with an inner conductor radius of 2.5 mm and a 2 mm thick dielectric insulation layer, in the 1 MHz to 100 MHz range, and are further confirmed by a water tank experiment, in which the measured response contains a single propagating mode whose attenuation agrees with theory. These results provide theoretical support for high-speed underwater wireless communication via single-wire structures.
Copyright (c) 2026 Yuejiu Zhu https://creativecommons.org/licenses/by/4.0
Automated 3-D Piping Routing Synthesis Considering Seismic Resilience: Part II—Algorithmic Characterization, Statistical Assessment, and Proof-of-Concept Validation
Stochastic optimization algorithms, such as the Multi-Objective Genetic Algorithm (MOGA) integrated into the MOGA-A* framework established in Part I, enable automated 3-D pathfinding in plant engineering. However, their inherent stochasticity introduces trial-to-trial geometric variability, raising reliability concerns for safety-critical applications. To evaluate the operational capabilities and limitations of this lightweight surrogate-driven solver, this paper (Part II) presents a three-part empirical assessment. First, to quantify search-space reproducibility, a computational sweep of 1,000,000 candidate layouts across distinct spatial topologies was conducted. Maximum Likelihood Estimation confirmed that compliant total evaluation indices follow predictable log-normal or gamma distributions, parameterized by a topological Designable Space Ratio metric incorporating space occupancy and obstacle clustering. Second, to assess whether the response-spectrum modal surrogate captures relative physical dynamic trends rather than absolute stress magnitudes, frequency-sweep shaking-table experiments were performed on 1:50 scaled models. The experiments reproduced the predicted downward shift in the dominant modal frequency and confirmed a lower peak dynamic response for the synthesized flexible-detour layout, which exhibited a 45.7% reduction in the experimentally derived response metric (11.98 MPa) relative to the unoptimized baseline (22.08 MPa). Third, to assess real-world decision-support utility, an algorithmically synthesized layout was benchmarked against a baseline manually drafted by an experienced engineer under identical spatial constraints from the Onagawa Nuclear Power Plant. Although the human designer achieved a lower peak dynamic stress (18.63 MPa vs. 145.46 MPa) by incorporating higher intermediate support density, the automated solver generated a code-compliant, collision-free candidate in 46 minutes. These results demonstrate that while support allocation heuristics benefit from post-processing refinement, the MOGA-A* framework functions as an effective decision-support engine that automates initial spatial pathfinding and reduces manual trial and error in early-stage plant design.
Multi-Objective Genetic Algorithm (MOGA)
Copyright (c) 2026 Shunta Mogi, Naoya Takamura, Akane Uemichi https://creativecommons.org/licenses/by/4.0
We consider spatial observations encoded so that nearby coordinates produce similar keys, regardless of access order. A query at the current coordinate can then combine information stored at that address with evidence from similar historical keys. Standard Delta memory corrects only one address per event. We introduce Block-Coherent Delta (BC-Delta), a fixed-capacity fast-weight rule that forms a two-key update block from the current and preceding keys, with the latter serving as causal context without implying spatial adjacency. A 2 x 2 Gram pseudoinverse separates their shared key component, while squared cosine coherence attenuates residual transport at low similarity. BC-Delta retains Delta’s single learning rate and adds no learned gate, window length, or decay parameter. Its rank-two affine update admits associative prefix evaluation. Under equal-budget tuning, both methods select eta = 0.025. Across six route–field conditions and three horizons from 16K to 262K events, BC-Delta lowers blind historical-recall MSE by 4.43% (95% confidence interval 4.11–4.82) and wins 90/90 primary comparisons. Tuned controls, coherence strata, and a signed key–value diagnostic distinguish residual transport from Gram preconditioning and expose the boundary of the spatial-continuity assumption. Code, frozen seeds, and evaluation records support reproducibility.
Copyright (c) 2026 Dian Yu https://creativecommons.org/licenses/by/4.0
RACE-Nav: Refinable Occupancy Contracts and Prefix-Wide Runtime Assurance for Dynamic Mobile-Robot Navigation
Modular navigation stacks permit predictors and controllers to be exchanged, but their uncertainty, timing, and braking assumptions rarely form one executable assurance argument. RACE-Nav introduces typed, refinable occupancy contracts whose guaranteed class, hazard scope, frame, horizon, risk allowance, and expiry are checked before command release. A model-conditional radial provider supplies the closed-loop conditional premise used by the risk ledger; marginal split conformal prediction is retained only as a diagnostic. Concrete trajectories are certified by finite sampled tests with Hausdorff-Lipschitz inter-sample margins and a prefix-wide recoverable-stop condition. A horizon-aware lease and downstream watchdog preserve the trusted-gate invariant under cancellation and provider substitution. We prove provider refinement, continuous-time separation, swept-stop safety, finite/anytime risk composition, stale-command exclusion, non-Zeno switching, and conditional release liveness. In a held-out paired-seed benchmark spanning eight dynamic interactions and six controllers (1,920 episodes), RACE-Nav produced 0/320 collisions (95% Wilson interval 0.00%-1.19%) and 97.5% goal success versus 12.2% collisions for the predictive time-to-collision/model predictive control comparator. The decision kernel recorded 0 and modelled 300-ms deadline misses. Stress and ablation results separate guaranteed behaviour from violations of the declared model and actuator bounds.
Copyright (c) 2026 Hari Sunmukeswar Baskaran, Salem Ameen https://creativecommons.org/licenses/by/4.0
Secure Passive Attachment and Docking Equipment
As NASA continues to refine extravehicular activity (EVA) systems for the International Space Station (ISS) and future exploration missions, reliable and efficient tool storage remains critical for astronaut safety and mission success. S.P.A.D.E. (Secure Passive Attachment and Docking Equipment) is a dual-button mechanical docking system that enables astronauts to securely store and retrieve EVA tools with one hand. The design incorporates a spring-loaded locking mechanism that enables single-fault tolerance while maintaining intuitive operation in microgravity. By guiding the tool’s buckle into a spring-assisted locking interface, the system allows tools to be quickly secured and released in varying orientations. S.P.A.D.E. aims to improve EVA task efficiency, reduce the risk of tool loss, and enhance the safety and ergonomics of astronaut maintenance operations. Experimental testing conducted post production verified reliable blind docking and release under 20 lbs of force with only 2.9 lbf of activation force. Future work will optimize lid geometry and fatigue life, enhance debris-resistance, and integrate space-qualified alloys and polymers for operational flight testing.
Copyright (c) 2026 Aarya Gupta, Natalie Chapman, Alena Arnold, Vamsi Sri Sai Guttikonda, Logan Pepin, Adam Younis, Spencer Matijak https://creativecommons.org/licenses/by/4.0
Some Alternative Forms of Nonviscous Damping
This paper develops a general framework for nonviscous damping in dynamic systems by introducing additive energy-dissipating forces governed by first-order differential equations. Several choices of the driving field are examined, including displacement-, velocity-, and acceleration-dependent forms associated with stiffness and mass contributions. For each formulation, the frequency-domain response is derived to identify the corresponding storage and loss stiffnesses, admissible complex conjugate parameter pairs, stability and dissipation requirements, and asymptotic behaviour. The analysis shows that some direct formulations must be augmented by algebraic correction terms to recover the correct static stiffness, while reciprocal formulations can be converted into each other through transformed damping parameters. A trapezoidal update of the damping history variables is then embedded into a standard direct integration workflow, yielding a modified residual and a consistent tangent effective stiffness without increasing the size of the original system. Numerical examples involving single-degree-of-freedom oscillators, broadband damping approximations, and a large finite element model verify the equivalence of selected formulations, demonstrate second-order convergence, and illustrate the computational advantages and practical limitations of the proposed alternatives.
Copyright (c) 2026 Theodore Chang, Chin-Long Lee https://creativecommons.org/licenses/by/4.0
Carbon Efficiency Comparison of FRP and Steel Bars for Reducing the Embodied Carbon of Concrete Structural Elements
In recent years, FRP (Fibre-Reinforced Polymer) bars have been considered to be a promising alternative to conventional steel bars for reducing the CO2 emissions of concrete structural elements, whilst their environmental performance compared to traditional steel bars requires quantitative assessment. This paper introduces a multi-level comparative framework to evaluate the carbon efficiency of FRP bars compared to steel bars, from the material level to the section level and structural element levels, leading to quantitative comparative outcomes useful for decision-making when selecting the most carbon-efficient rebar type for achieving the lowest embodied carbon (cradle-to-gate) of structural elements. Each comparison level has its applicability depending on the specific context of construction projects. Because relative environmental performance can vary significantly in function of material and environmental data, the developed comparative framework aims to provide the rigorous methodology to follow, which can be adapted to any construction project by updating material and environmental datasets, rather than declaring a universally superior rebar type. Steel and BFRP (basalt FRP) bars are compared, based on the assumed material and environmental data, as an example to demonstrate how to apply the proposed comparative formwork. Results indicate that the optimal solution depends mainly on the structural parameters (such as span and slab thickness) as well as the assumed carbon data. For prismatic elements, the optimal choice between steel and BFRP bar is strongly influenced by the selection of slab thickness. For non-prismatic elements, it is found that non-prismatic BFRP-reinforced slabs have 4.8%–14.4% lower CO2 than non-prismatic steel-reinforced slabs and can save up to 63% of CO2 compared to the traditional solution (prismatic steel-reinforced slabs) in the presented examples.
Copyright (c) 2026 Shizhe Hong, John Orr, Arnaud Delaplace https://creativecommons.org/licenses/by/4.0
Modeling and Variability Assessment of Global Solar Radiation in Gwagwalada, North-Central Nigeria: A Comparison of the Hargreaves-Samani and Angstrom-Prescott Models
Reliable estimates of global solar radiation are essential for the design, sizing, and performance evaluation of solar energy systems, particularly in regions where ground-based radiometric data are sparse. This study assessed the variability of global solar radiation and solar irradiance in Gwagwalada, a town in Nigeria's Federal Capital Territory (8.95°N, 7.08°E), using the Hargreaves-Samani and Angstrom-Prescott models. Monthly average maximum and minimum temperature, daylight hours, and measured global solar radiation and irradiance data spanning January 2020 to December 2022 were obtained from the Nigerian Meteorological Agency (NIMET). Model outputs were validated against measured radiation using mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and the coefficient of determination (R²). The Hargreaves-Samani model showed a stronger association with measured radiation (R² = 0.981, RMSE = 1.100 MJ/m²/day, MBE = 0.999 MJ/m²/day) than the Angstrom-Prescott model (R² = 0.902, RMSE = 2.031 MJ/m²/day, MBE = 1.734 MJ/m²/day), indicating that a temperature-based estimation approach is more reliable than a sunshine-duration-based approach at this location. Global solar radiation was consistently higher during the dry season (November to March) and lower during the wet season (April to October), consistent with reduced cloud cover and lower atmospheric moisture in the dry months, with the annual peak occurring in February. Daily global solar radiation ranged from approximately 11.4 to 19.9 MJ/m²/day in the wet season and 17.4 to 21.8 MJ/m²/day in the dry season. These findings provide a quantitative basis for solar energy system planning in Gwagwalada and add to the limited body of location-specific solar radiation data available for North-Central Nigeria.
Copyright (c) 2026 Praise Okwuchukwu Ezego, Ogorchukwu Emmanuel Ochem https://creativecommons.org/licenses/by/4.0
Coupling-Aware Planner Exploration for Shared-Workspace Multi-Manipulator Motion Planning
Shared-workspace multi-manipulator planning repeatedly faces a representation decision: exploit efficient decoupled/hybrid planning or escalate to coupled composite-space search. We cast this as coupling-aware exploration over planning representations: the system probes interaction structure before deciding whether to exploit cheap decoupled/hybrid planning or explore a more expensive coupled composite-space representation. Our framework logs interpretable interaction descriptors, routes tasks among decoupled, hybrid, and joint-space modes, and evaluates these policies on 4,000 PyBullet tasks and 32,000 planner runs. Coupling-aware routing improves paired solve outcomes over random and pure joint-space routing, while matching the best fixed-mode solve rate in the selection ablation. The main contribution is a regime-level account of escalation under interaction uncertainty: coupling descriptors indicate when hybrid exploitation is sufficient, when deeper coupled search is warranted, and where selector overhead remains.
Copyright (c) 2026 Rahul Vimalkanth https://creativecommons.org/licenses/by/4.0
Numerical Investigation of Supersonic and Hypersonic Flows over a Flat Plate using a Thermally Perfect Gas Model
High-speed external flows with free-stream Mach numbers exceeding 4-5 (M∞ > 4-5) exhibit strong shock waves, steep temperature gradients, and molecular vibrational effects, leading to the breakdown of the calorically perfect gas assumption. This work investigates supersonic and hypersonic flow over a flat plate geometry to isolate and understand the physics under such conditions. An in-house Computational Fluid Dynamics (CFD) solver, implemented in Python and based on the MacCormack explicit finite-difference scheme, was developed for this purpose. The solver models a thermally perfect gas, incorporating temperature-dependent specific heats using two widely referenced formulations from the literature, namely, a polynomial functional form and an exponential functional form that is based on quantum theory. Comparative simulations using a calorically perfect gas model are performed to quantify the effect of incorporating a thermally perfect gas model. Viscosity is evaluated using Sutherland’s law, while thermal conductivity is obtained from a constant molecular Prandtl number assumption. Near-wall resolution is achieved through y+ based meshing strategies, ensuring accurate boundary-layer characterization, and a mesh sensitivity study was performed to confirm grid independence of the results. Analysis of predicted pressure, temperature, density, and Mach number distribution is done across both the calorically perfect gas and thermally perfect gas models. The influence of specific heat formulations on boundary-layer development and thermal gradients is systematically evaluated. The results demonstrate the necessity of temperature-dependent thermodynamic modelling to accurately predict the thermal and aerodynamic characteristics of high-speed flows. The insights obtained are directly applicable to the preliminary design of hypersonic vehicles, including missiles and high-speed aircraft. Possible extensions to this work can include the incorporation of automated mesh generation and the adaptation of the solver to handle blunt bodies, wedges, and lifting surfaces under high-speed flow conditions.
Copyright (c) 2026 Neerav Krishna, Biswadip Shome https://creativecommons.org/licenses/by/4.0
Algebraic Codification and Discrete Isomorphic State Propagation for Exact Synthesis of NCV Quantum Circuits
Exact synthesis of quantum circuits seeks depth-optimal gate layouts but is fundamentally bottlenecked by the continuous-variable scaling of unitary matrices or complex amplitudes. In this paper, we propose a mathematically novel approach for the exact synthesis of NCV (NOT, CNOT, Controlled-V , Controlled-V †) quantum circuits. We demonstrate that the quantum state evolution of basis vectors under NCV logic does not require continuous variable tracking; instead, it is strictly isomorphic to a discrete 4-valued cyclic group. By codifying quantum amplitudes and relative phases into a single scalar integer S ∈ {0, 1, 2, 3}, we bypass fractional and imaginary components entirely. We further give a binary algebraic decomposition of this scalar, reducing quantum gate interactions to exact bitwise XOR continuous relaxations. This formulation maps the exact synthesis problem into a highly constrained, pure Mixed-Integer Linear Programming (MILP) model. We mathematically prove the validity of this discrete encoding by demonstrating that it flawlessly preserves the NCV group structure, achieving computational efficiency by eliminating traditional large-M relaxations and dual-variable tracking
Copyright (c) 2026 George Papakonstantinou https://creativecommons.org/licenses/by/4.0
Industrial Internet of Things-Enabled Fault Detection and Diagnosis in Measurement and Control Systems: A Bibliometric Analysis and Systematic Mapping Review
Industrial Internet of Things (IIoT) architectures are shifting fault detection and diagnosis (FDD) from centralized supervisory computers toward smart instruments, edge controllers and distributed cyber-physical systems, yet evidence remains fragmented across metrology, networking, embedded computing and machine learning. This bibliometric analysis and systematic mapping review maps the field's structure and examines the measurement-to-action chain. A PRISMA-ScR informed protocol retrieved 447 OpenAlex records published in 2010-2025. After normalized-title deduplication, deterministic engineering-relevance screening, retraction checks, Crossref DOI verification and direct source/year auditing against the July 2026 official Scopus source list, 192 journal articles and reviews formed the frozen analytic corpus. The source list was used for source/year parity, not document-level Scopus coverage. All 192 DOI-title pairs matched Crossref. Output rose from five papers in 2018 to 55 in 2025 (40.9% compound annual growth). The corpus spans 97 sources, 742 disambiguated author identifiers and 54 countries. Bradford zones showed a compact core but not a strict geometric source sequence; a discrete Lotka model yielded an exponent of 4.16 with a bootstrap goodness-of-fit p value of 0.306. A three-community co-citation network had moderate modularity (Q = 0.267). Explicit edge-cloud architecture occurred in 86.3% of 2023-2025 title/abstract records, whereas explicit decision or closed-loop control language occurred in 8.5%. Because 34 records lacked abstracts, reporting frequencies are lower-bound indicators rather than study-quality estimates. The review concludes that progress depends on traceable measurement uncertainty, grouped cross-machine validation, calibrated abstention, bounded end-to-end latency, semantic interoperability and safely governed supervisory action.
Copyright (c) 2026 Bui Thanh Lam https://creativecommons.org/licenses/by/4.0
OpenNUMA: A Custom Shared System-Memory Allocator for Heterogeneous Neural-Network Computing Across CPU and Integrated GPU
Neural network and machine-learning workloads commonly rely on dedicated GPUs with tensor cores, While existing systems with integrated GPUs (iGPUs) may have unused computing power. This study investigates whether a custom memory allocator can enable existing or older systems to utilize integrated GPUs for such workloads without requiring hardware-level modification. The proposed method does not require unified virtual memory mappings. OpenNUMA (Open Source Neural Unified Memory Allocator) is a custom allocator developed for these tasks. Although OpenNUMA proposed to platform-independent, in this study it relies on PyTorch XPU backend, Intel oneAPI SYCL and Shared Unified Shared Memory (USM), and Microsoft Windows. OpenNUMA provides a memory-management layer that allows CPU and iGPU workloads to access shared system-memory allocations through the parent application interface. This prototype implements memory pooling, allocation tracking, deallocation tracking, and thread safety using mutex locking. Feasibility testing successfully shows OpenNUMA initialization, iGPU tensor allocation, tensor operations, and tensor aliasing through PyTorch. CPUto-iGPU transfer testing achieved a 34.076% reduction in transfer time, while iGPU-to-CPU transfer time increased by 5.258%. General workload testing showed minimal performance differences for iGPU and neural-network workloads compared to default allocator. The performance of OpenNUMA is nearly identical and for some cases improved compared to default allocator. Although the results can vary due to different systems, OpenNUMA shows such allocator can exist and perform effectively. However, CPU-iGPU shared tensor access could not be verified through the current PyTorch allocator interface. Future work will investigate memory-release mechanisms, improved synchronization, and queue tracking.
Copyright (c) 2026 Md. Muminul Islam https://creativecommons.org/licenses/by/4.0
Enforcement Triage as Constrained MPC: From FIFO to Foresight
In a trust-and-safety review backlog, harm accrues while genuine cases wait to be actioned, cases carry consumer-protection deadlines, review capacity is scarce and below the mean arrival rate, and the magnitude of harm caused by a case is observable only through a noisy classifier score until it is eventually reviewed by a human. Production systems prioritize this backlog in a myopic fashion, using a first-in-first-out approach or by choosing those cases with the highest estimated harm based on a machine-learning classifier. These approaches ignore the forecastable quantities of future load and the rate at which pending harm accrues. The problem can be posed as a constrained model predictive control (MPC) over a marked-arrival backlog. A seeded, config-driven simulator anchored to public data provides the simulated environment to test MPC's efficacy. Evaluating against a series of baseline approaches (the c-mu rule, a Whittle-inspired index, a full-information greedy benchmark, and a PPO reinforcement-learning agent), a fluid linear-program MPC controller is designed and tested on paired seeds. Three findings emerge and form the primary contribution of this work: Firstly, the cost of partial observability is large and dominant under a realistic signal. A factorial attribution assigns roughly 20% of it to unobserved harm magnitude, which improving a label-only classifier cannot address under our score-magnitude independence assumption but which can be learned online, and 80% to label uncertainty. Secondly, the forecast-aware controller beats the strong myopic rules only conditionally, namely when the deadline constraint carries weight and load is near-critical, and can be significantly worse than the c-mu rule when its internal model is misleading. Finally, both failure modes share one cause and can be addressed by applying a dual-mode controller which executes the myopic rule when the plan's anticipatory value is found to be negligible. It reveals no statistically significant disadvantage against the better of the pure c-mu and MPC policies in any of the tested regimes. In fact, it is significantly better than both pure rules in several regimes, and it retains MPC's advantages where foresight is particularly valuable.
Copyright (c) 2026 Chinmay Koimuttum, Rohan Shekhar https://creativecommons.org/licenses/by/4.0
Automated 3D Piping Routing Synthesis Considering Seismic Resilience: Part I— Mathematical Formulation and Layout Optimization Framework
Automated piping routing methods face dual challenges in high-dimensional space planning and structural safety verification. Traditional workflows treat seismic qualification as a retrospective step, leading to inefficient design loops and costly backtracking. This study (Part I) presents a hybrid optimization framework that integrates deterministic A* pathfinding with a Multi-Objective Genetic Algorithm (MOGA) to automate seismic-aware 3D piping routing synthesis. To bypass the prohibitive computational cost of full-scale Finite Element Method (FEM) simulations during iterative optimization, a lightweight linear-response spectrum modal analysis is used as a surrogate physical indicator to rank candidate layouts. A stochastic midway point strategy is introduced during initial population generation to ensure topological diversity and bypass local minima. The framework was validated using a 32 x 60 x 20 m congested design space derived from the Onagawa Nuclear Power Plant blueprints with carbon-steel piping (STPT410). The optimization loop evaluated 10,000 unique candidates and converged in 46 minutes and 19 seconds, reducing the aggregate evaluation index by 93.2%. The results successfully characterized the non-linear trade-offs between material length, bend frequency, and dynamic seismic stress. Notably, the framework systematically identified configurations in which expanding pipe length and adding bends to lower structural stiffness successfully shifted the system's natural frequencies away from the resonance peak, thereby reducing peak seismic stress by up to 86.1%. This framework substantiates a transition from reactive verification to proactive, physics-informed layout synthesis.
Copyright (c) 2026 Shunta Mogi, Akane Uemichi https://creativecommons.org/licenses/by/4.0
AQUA_MEM: Multi-Dimensional Aqueous State Vector Encoding for Digital Information Storage in Water Droplets
We present AQUA_MEM, a framework for encoding digital information into the measurable physicochemical properties of aqueous solutions. Each water droplet serves as a multi-dimensional state vector whose independent physical channels (pH, ionic conductivity, and optical chromaticity) encode discrete bit values. We demonstrate a proof-of-concept system encoding 8 bits per 50 μL droplet across three channels with 8, 8, and 4 discrete levels, achieving 100% decode accuracy over multiple trials with persistence exceeding 14 days in sealed glass containers. The full system uses commodity sensors totaling under €50 and an ESP32 microcontroller. We analyze the scaling path toward picoliter droplet volumes: with five encoding channels, information densities on the order of 25 MB/L become reachable using existing microfluidic infrastructure. This work constitutes the first systematic framework for intentional multi-channel digital encoding in aqueous solutions.
Copyright (c) 2026 Sofiane Boumeddane https://creativecommons.org/licenses/by/4.0
Robustness of Episodic Acoustic Leak Detection Across Noise Levels
Acoustic leak detection is critical for pipeline integrity, yet it faces challenges from environmental noise and limited labeled data. To our knowledge, no prior work has systematically quantified noise robustness in episodic acoustic leak detection. We tested a Conformer-based prototypical network on the GPLA-12 dataset over an SNR 0-20dB range with five different random seeds. The results for clean, 10dB, and 0dB conditions were 65.88% ±1.36%, 68.04% ±0.66%, and 63.07% ±1.30%, respectively. The addition of 10dB SNR enhanced performance by 2.16% (p < 0.05), which was linked to a regularization effect observed in the training-validation curves, while 0dB SNR reduced accuracy by 2.81% (p < 0.05). While fully-supervised methods achieve higher absolute accuracy, our 5-shot episodic result of 65.88% provides the first baseline for few-shot leak detection on this dataset, demonstrating feasibility under extreme data scarcity.
Copyright (c) 2026 Abdulrahman Kalli Mustapha https://creativecommons.org/licenses/by/4.0
Fraction-valued Equilibrium for Fraction-valued Bi-matrix Games
Using the well-known result about existence of equilibrium for bi-matrix games, we prove that a fraction-valued bi-matrix game has a fraction-valued equilibrium. Our proof is direct, and simpler than the one using the Lemke-Howson algorithm.
Copyright (c) 2026 Somdeb Lahiri, Anirban Ghatak https://creativecommons.org/licenses/by/4.0
Bang-Bang Temperature Control in Espresso Machines
Consumer-grade espresso machines and bean-to-cup machines primarily regulate their brew temperature using on-off control, known in technical jargon as "bang-bang." Commercial and prosumer devices, on the other hand, are increasingly relying on PID control. From a product development perspective, this article explains how on-off control works in the key heating architectures—boiler, thermoblock, classic tube-type flow heater, and thick-film heater—why this results in the characteristic sawtooth curve with hysteresis, overshoot, and measurement dead time, and how PID-controlled temperature regulation differs under load. A patent- and manufacturer-supported case study on BSH's sensoFlow principle demonstrates how a lack of thermal mass is compensated for by sensors at the inlet and outlet, pulsed heating power, and flow rate measurement. It also highlights the new dependencies that arise in this process: the thermal saturation gap and scaling as a disturbance in the control loop. The analysis is based on published literature and patent sources, not on proprietary measurement data. The discussion covers the implications for extraction consistency, reproducibility, and long-term stability, as well as the underlying cost-benefit considerations. The core thesis is: the choice of control and heating architecture is a rational product decision that is, however, invisible to end consumers—and only its disclosure enables informed purchasing decisions.
Copyright (c) 2026 Joerg Michael Schudrowitz https://creativecommons.org/licenses/by/4.0
Connected Autonomous Mobility in the United States: A Narrative Review of Transportation, Urban, Economic, Environmental, and Governance Implications
Connected autonomous vehicles are often evaluated as individual driving systems, yet their larger transportation effects depend on how automation interacts with connectivity, service models, freight operations, infrastructure, and governance. This narrative, trend-oriented review synthesizes U.S.-focused literature on passenger and freight automation, traffic operations, urban form, mobility, economics, energy, cybersecurity, and regulation. The reviewed evidence does not support a single expected outcome. Cooperative control can improve traffic stability and capacity under sufficient participation; shared mobility can reduce parking demand yet generate empty travel; freight automation can improve logistics efficiency while shifting infrastructure and workforce requirements; and energy benefits can be offset by induced travel. Four scenarios distinguish development paths by ownership, application, and degree of network coordination rather than by assumed adoption rates. The central conclusion is that the long-term significance of autonomous vehicles may depend less on removing the human driver than on whether passenger vehicles, freight fleets, public transit, and infrastructure become interoperable components of a coordinated mobility network. The resulting benefits and risks are therefore system-level and policy-dependent.
Copyright (c) 2026 Hung-Yu Lin, Xingran Huang, Qiming Guo, Jinwen Tang https://creativecommons.org/licenses/by/4.0