Search Results (149)

Electric vehicle (EV) charging has a large, spatially clustered, schedulable load whose vehicle-to-grid flexibility can be sold back to the power system. That flexibility has grid value only when the committed quantity can be reliably delivered under uncertainty. Open forecasting benchmarks operators rely on report-only point predictions. The dispatch models that turn forecasts into firm commitments assume a constant round-trip efficiency, so the committed flexibility is systematically over-scheduled. This study contributes two complementary modules, validated separately on public data. The first is a calibrated probabilistic charging forecaster that provides, to our knowledge, the first prediction intervals with reported empirical coverage on the UrbanEV benchmark. It is a gradient-boosted quantile-regression model that combines each zone’s own-history lags with adjacency-weighted neighbor-mean features and exogenous price and calendar inputs. It is calibrated by conformalized quantile regression and scored over thirty zones across a 120-day hourly window. The second is a deliverable-flexibility envelope whose returnable-energy bounds are set by measured, state-of-charge- and rate-dependent vehicle-to-grid (V2G) discharge efficiency rather than a constant round-trip number. These bounds are fit to the measured discharge traces of three V2G-capable vehicles in the Esser bidirectional-charging dataset. Chosen as a lightweight, reproducible baseline, the forecaster keeps its prediction intervals within a five-percentage-point coverage tolerance at both the 80% and 90% nominal levels. Measured coverage is 0.823 and 0.911. It also improves on the continuous ranked probability score of its conformalized-point counterpart at matched point accuracy. This calibration holds across the hyperparameter neighborhood and under data deficiency. On the delivery side, a leave-one-vehicle oracle shows the efficiency-aware envelope short-delivers less than the constant-average-efficiency aggregator on held-out vehicles. Its residual shortfall is 1.21% against the aggregator’s 2.03% at the conservative operating point. The margin widens as commitments grow more aggressive and discharges reach the lowest states of charge. Each of these two measured properties, calibrated demand-side uncertainty and state-dependent discharge physics, imposes a material, separately validated constraint on how much contracted EV flexibility can be delivered, a constraint the point-forecasting frontier leaves unaddressed. Full article

Wearable vibrotactile devices are increasingly used in virtual reality, teleoperation and neurorehabilitation, but objective EEG evaluation of glove-mediated touch remains limited. We compared EEG recorded during natural object interaction with EEG recorded when tactile feedback was reproduced through a vibrotactile smart glove. Data were collected with an eight-channel wireless headset while participants interacted with three object types (bottle, cube, and sphere) in natural-touch and glove-mediated conditions. An exploratory model trained on natural-touch data and tested on glove-mediated trials yielded rounded cross-condition accuracies of 83%, 78%, and 68% for bottle vs. rest, cube vs. rest, and sphere vs. rest, respectively. These findings suggest that some object-related EEG patterns may carry across conditions, but they should not be interpreted as evidence of physiological equivalence. Supplementary analyses using repeated-run evaluation, band-power and ERD/ERS summaries, temporal-window inspection, and channel ablation were included as cautious interpretability checks. The results underscore the need for larger subject-independent studies, stronger artifact-control pipelines, formal statistical testing, and richer haptic conditions before asserting equivalence to natural touch. Full article

Electrocardiography (ECG)-only workload-state classification offers a lower-burden physiological sensing route than denser multimodal, multi-sensor physiological, or neuroimaging setups for controlled laparoscopic training research. This study evaluated whether ECG-only representations can classify condition-derived cognitive workload states during a controlled laparoscopic peg transfer task performed under Control and auditory N-back conditions (N0, N1, and N2). Twenty surgical trainees from an advanced surgical-skills course completed the task protocol, and 17 participants entered ECG modelling after ECG quality-control exclusions. The retained ECG modelling dataset comprised 268 task blocks (Control/N0/N1/N2: 68/68/68/64), evaluated as held-out task-block predictions in a known-participant four-fold leave-one-round-out (LOTO) evaluation. Branch-specific raw ECG windows, recurrence-plot sequences, and heart-rate/time-domain heart-rate-variability inputs are detailed in the Methods, and model metrics were computed after reduction to task-block predictions. The primary endpoint was Surgery Task Load Index (SURG-TLX)-aligned low/high workload, defined as Control plus N0 versus N1 plus N2. Four-class and three-level endpoints were retained as secondary views. Raw ECG, recurrence-plot (RP)-derived, hybrid score-level fusion, and conventional heart-rate/time-domain heart-rate-variability Random Forest (HRV-RF) models were compared using a locked evaluation protocol, leakage-aware train-fold-only preprocessing, participant-clustered confidence intervals, and planned paired tests for the primary endpoint. On the primary low/high endpoint, raw ECG achieved the highest macro-F1/balanced accuracy (0.865/0.865), followed by the hybrid branch (0.847/0.847) and HRV-RF (0.648/0.649). Raw ECG and hybrid were supported over RP-derived and HRV-RF under the planned paired tests. On selected secondary endpoints, hybrid achieved higher macro-F1 values than raw ECG, consistent with possible endpoint-dependent RP-derived complementarity rather than a general hybrid advantage. These findings support ECG-only block-level workload-state classification in this controlled training setting. The evidence is retrospective and based on held-out rounds from known participants rather than subject-independent or deployment validation. Full article

Reliable wearable activity recognition requires not only a class label but also an auditable indication of whether that label is supported by historical sensor evidence. We present CC-NSIEA, a label-preserving neural-plus-rule-based class-contrast evidence audit for cross-subject wearable activity recognition. A Temporal Residual Perception Network supplies the sole activity label, posterior probabilities, and a normalized temporal embedding. A read-only Training-Subject Evidence Memory retrieves global, predicted-class, and competing-class records. A rule-based Evidence Consistency Audit combines data validity, dynamic/static motion coherence, retrieval support, and class separation. When first-round evidence is insufficient, Class-Contrast Evidence Refinement performs one deterministic contrast between the predicted class and the strongest posterior competitor; the audit cannot change the neural label. The term neuro-symbolic is used only in this restricted architectural sense: a neural predictor is coupled to explicitly represent deterministic predicates and a finite rule-based controller; the method does not perform symbolic inference, theorem proving, or knowledge-graph reasoning. On five subject-disjoint outer folds of the UCI HAR official training partition, the shared perception model achieved 90.13% accuracy and 90.55% macro-F1 across 7352 out-of-fold windows from 21 subjects. Relative to a matched dynamic deterministic controller, CC-NSIEA increased Error AUPRC from 0.423802 to 0.433057 and reduced AURC from 0.035941 to 0.035913. The 10,000-resample subject-cluster bootstrap interval for the AUPRC difference was [0.001595, 0.019547]. CC-NSIEA provides an evidence-centered complement to confidence-based reliability estimation. Full article

Energy-efficient renovation of existing buildings is one of the important approaches to achieving sustainable development. This study takes a naturally ventilated sports hall (without heating or air conditioning systems) at a university in Weifang, Shandong Province, as the research object, where indoor thermal comfort levels remain low throughout most of the year. Adopting passive optimization as the core approach, the study aims to improve natural daylighting and winter thermal environment by adjusting window-to-wall ratio (WWR), window-to-floor ratio (WFR), skylight height, and glass thermal–optical parameters. The research methodology consists of two main stages: field measurement and multi-scenario simulation. On-site measurements were first conducted to ascertain the building’s actual usage patterns, existing daylighting conditions, and temperature distribution characteristics. Subsequently, six scenarios—including the original design, the current condition, and four differentiated optimization schemes (Schemes A, B, C, and D)—were quantitatively evaluated for indoor daylighting and thermal performance using Ecotect Analysis 2011 and eQUEST 3.65. The simulation models were calibrated against field measurement data to ensure result reliability. Key findings are as follows. In terms of daylighting, daylight factor and indoor average illuminance increase significantly with higher WFR, with this growth trend noticeably plateauing around a WFR of 0.7. Illuminance uniformity should be comprehensively assessed using both of its calculation methods; skylights provide more balanced daylighting than side windows, and combined side-window and skylight schemes yield far superior illuminance uniformity compared to single-type window arrangements. Regarding thermal performance, in schemes incorporating skylights, indoor temperature rises with increasing glazing area when WFR is below 0.7; however, when WFR exceeds 0.7, building heat dissipation surpasses solar heat gain, causing indoor temperature to decrease. Considering annual thermal comfort performance, Scheme C achieves the longest cumulative comfort hours and the most balanced year-round thermal performance, making it suitable for renovation projects pursuing stable indoor environments. Scheme A demonstrates significant winter warming effects but suffers from overheating defects during summer and transition seasons, thus requiring enhanced ventilation measures. After implementing increased ventilation (5 air changes per hour), Schemes A and C achieve 36.7% and 37.2% more comfortable hours during the building’s 10-month usage period, respectively, compared to the current condition. In conclusion, for large-space buildings such as sports halls, relying solely on increasing WFR and WWR for passive winter warming yields limited effects, and coordinated optimization of glass thermal–optical properties and ventilation strategies should be adopted. Full article

The Vehicle Routing Problem with Time Windows (VRPTW) takes on a structurally distinct form when the goods being routed undergo first-order quality decay during transport. In this setting, distance minimisation alone underestimates the true economic cost. A per-customer minimum-quality acceptance constraint further introduces a non-linear feasibility condition that does not appear in the classical formulation. This paper addresses such a setting in the context of loose-skin citrus fruit (e.g., mandarins) distribution, where stock has already undergone several days of cold storage at the origin warehouse, and remaining shelf life makes retail time windows binding rather than decorative. We formulate a Maturity-Aware Multi-Echelon Dynamic Reallocation Vehicle Routing Problem with Time Windows (MA-MEDR-VRPTW) on a three-echelon network (origin warehouse → distribution centres → stores) over a seven-day rolling horizon. A first contribution shows that the minimum-quality acceptance constraint admits an analytic transformation into a time-window tightening, which removes per-extension exponential evaluations from the subproblem solver. The algorithmic contribution is a proximal alternating direction method of multipliers (ADMM) with NG-route relaxation (padmm-ma) whose quality-loss weight is updated by a residual-balancing rule and is decoupled from the outer reallocation linear program (LP) through approximate dynamic-programming-style marginal costs. On twelve Solomon-derived mandarin instances (72 feasible algorithm–instance combinations), padmm-ma returns a mean seven-day cost of 12,638 CNY against 11,753 CNY for a subgradient baseline ($+7.5\%$) at statistically indistinguishable arrival quality (paired Wilcoxon $p=0.077$ for ${\overline{q}}_{\mathrm{arr}}$), while cutting mean wall-clock time from 350 to 23 s (about $15\times$). The method, therefore, reads as a fast operational heuristic for daily re-planning. An ablation, an exact-MIP benchmark on tractable subproblems, and a scale extension to $n=100$ customers round out the validation. Full article

Sustainable EV charging infrastructure is fragmented by proprietary applications, vendor lock-in, and weakly time-differentiated pricing, blunting its contribution to urban-mobility decarbonisation. This paper asks whether an open-protocol, super-app-mediated photovoltaic–storage charging architecture can jointly resolve these three fragmentations under deployed field conditions and what its sustainability profile then looks like. We report a campus photovoltaic–storage microgrid integrating heterogeneous EV chargers under an open, vendor-neutral charging-control protocol with super-app authentication and payment replacing dedicated charging applications and a time-differentiated tariff aligned at the meter-interval level with the underlying utility wholesale rate; the deployment is exercised through a researcher-scheduled commissioning campaign of 13 sessions designed to establish functional correctness across the operating envelope rather than to measure user behaviour. Three results emerge across cross-vendor compatibility, onboarding friction, and grid alignment. First, basic message-level OCPP compatibility is sustained across two charger vendors under a single cloud management system—in sequential single-vendor sessions—including the full charging profile up to near-rated DC peak power. Second, the super-app-mediated workflow, which requires no charging-specific application installation and no new charger-operator account, structurally eliminates the dedicated application installation and the email/SMS/credit-card verification round-trips of conventional onboarding, compressing measured first-use end-to-end interaction to 31 s; relative to reconstructed commercial-operator baselines, this is, to the best of the authors’ knowledge, an order-of-magnitude reduction rather than a controlled benchmark. Third, mid-day energy delivery aligns incidentally with the utility off-peak window, not user-driven demand shifting, while PV-displacement and BESS-discharge contributions to charging are bracketed by scenario rather than being separately metered. The paper’s contribution is therefore a replicable, policy-embedded sustainable charging architecture validated at field scale within the New Taipei Net-Zero Carbon Demonstration Site Programme, with no claim of global novelty; the same architecture is structurally positioned to convert the observed incidental grid-friendliness into a deliberate, user-facing benefit via a hardware-free mid-day-discount redesign. Full article

The main objective of this study was to conduct initial evaluations of the performance of a classifier utilizing the EVA-02 model, which was designed to identify tool wear states by analyzing scanned images of machined, melamine-faced MDF workpieces produced under varying tool degradation levels. Tool wear was quantified using the flank wear indicator VB and grouped into four wear classes (Class I: VB = 0–0.1 mm, Class II: VB = 0.1–0.2 mm, Class III: VB = 0.2–0.3 mm, Class IV: VB = 0.3–0.4 mm). The classifier automatically analyzed the delamination level observed on the edges of the workpieces to predict the corresponding tool wear class. To increase the number of training samples and capture local manifestations of edge damage, each edge image was divided into 28 overlapping image windows of size 250 × 250 pixels. A few different data aggregation strategies were investigated. The most accurately recognized tool wear class was Class IV (Precision 89%; Recall 93% and F1-score 91%—rounded to whole numbers). However, the classification metrics for the remaining classes were considerably lower. For instance, the F1-score for each of them fell well below 80%. Most notably, the recall for class III was particularly poor, reaching a mere 65%. The overall accuracy, averaged across all four classes, was 79%. This result is comparable to previous research reports and can be considered promising, but it does not represent a major breakthrough. Full article

Capacitated vehicle routing with time windows (CVRPTW) is a natural target for coherent Ising machines (CIMs), but a direct multi-vehicle arc encoding scales as $O\left(m{N}^2\right)$ and exceeds the variable budget of current CIM-compatible systems. We argue the bottleneck is encoding density, not expressiveness, and present LSQ, a hardware-aware sparse Quadratic Unconstrained Binary Optimization (QUBO) framework that decouples CVRPTW into a compact customer-to-route assignment QUBO and a classical intra-route ordering step under a soft no-wait service convention. LKH candidate edges compress the per-route edge space from $O\left(N^2\right)$ to $O\left(KN\right)$, and a per-route dynamic-penalty subroutine encodes time-window sensitivities as binary variables in a round-wise outer loop. On a six-vehicle, 51-node reference instance curated from long-term operational data, LSQ shrinks the maximum single-submission QUBO from 15,300 arc variables to 342 logicalQUBOvariables (∼45× compression), cuts travel time by 22.9% (74 vs. 96), and cuts route duration by 11.2% (174 vs. 196) against an OR-Tools soft-window baseline at the same fleet size. OR-Tools retains an advantage on raw time-window penalty (1600 vs. 3540) and runtime; under the scalar operational cost ${\sum }_{k}T\left({\pi }_k\right)+{\sum }_i{\ell }_i\left({\tau }_i\right)$, OR-Tools is therefore the better single-objective solver, and the comparison is a multi-objective trade-off rather than a scalar dominance claim. Ablations confirm that the LKH prior recovers Held–Karp on a 15-customer TSP at 53 vs. 120 variables and that the dynamic-penalty encoding reduces compressed time-window loss by 15.25% at constant travel. All hardware claims refer to QUBO sizing on a Kaiwu/CIM-compatible backend, not physical CIM execution. Full article

Pine wilt disease control often depends on reducing adult beetle activity, but how aerial spraying performs under operational forest management conditions remains poorly understood. We evaluated a 2022 operational aerial spray program in Pinus thunbergii stands in Shandong, China, by combining droplet deposition measurements, branch-feeding bioassays to assess acute and residual toxicity with Monochamus alternatus, and seasonal trap monitoring of both M. alternatus and Arhopalus rusticus, a relevant co-occurring cerambycid species. Spray cards showed that insecticide reached the stand in both spray rounds, although vertical differences between upper and lower strata were stronger during the second application. Branches collected immediately after spraying caused rapid mortality of M. alternatus, and both strata reached complete mortality within 72 h of exposure. In contrast, branches collected one month later caused little additional mortality beyond control levels, indicating that biologically effective exposure declined quickly and provided an insufficient window of protection relative to the full period of adult beetle activity. Trap data matched this pattern. After the first spray, M. alternatus captures dropped sharply during the immediate post-spray period but rebounded before the second spray. A. rusticus showed a similar short-term response, but its seasonal activity pattern differed from that of M. alternatus. Overall, the main limitation of the spray program was not weak initial toxicity, but the short duration of effective control relative to beetle activity in the field. This study shows that better aerial control of pine wilt vectors will depend on matching spray timing and residual persistence with local beetle phenology to improve the design and timing of aerial control programs in pine wilt management. Full article

We study a topological problem in discrete extreme value theory. Let $\mathcal{P}\left(\mathbb{N}\right)$ denote the space of probability laws on $\mathbb{N}$, endowed with the total variation metric $d_{\mathrm{TV}}$. Fix a rounding map r, either the ceiling map or the nearest-integer map. We consider the rounded discrete max-domain-of-attraction class ${\mathcal{D}}_r\subset \mathcal{P}\left(\mathbb{N}\right)$, consisting of all laws of the form $\mathrm{law}\left(r\right(Y\left)\right)$, where the parent law of Y belongs to a classical max domain of attraction $\mathrm{MDA}\left(G_{\xi }\right)$ for some generalized extreme value shape $\xi$. The main result of this note is that, for the ceiling and midpoint rounding schemes, each class ${\mathcal{D}}_r$ is meager in $\mathcal{P}\left(\mathbb{N}\right)$, while remaining dense; this mirrors the continuous picture of Leonetti and Khorrami Chokami. The proof is based on the Baire category theorem: we construct a comeager subset of $\mathcal{P}\left(\mathbb{N}\right)$ by forcing infinitely many incompatible dyadic tail ratios on disjoint far-out windows; such behavior cannot occur for any rounded law arising from a single classical max domain of attraction. We also record the corresponding Banach–Mazur game interpretation and explain why the argument applies to the rounded schemes (Types B and C) rather than to the sampled-density discretization (Type A). Full article

Background: Early-life exposure to dichlorodiphenyltrichloroethane (DDT) may increase adult cancer risk, but evidence from Asian populations remains limited. Taiwan’s nationwide indoor residual spraying (IRS) program during the 1950s provides a unique setting to examine long-term reproductive cancer risk associated with early-life DDT exposure. Methods: We conducted an ecological study using township-level DDT IRS frequency (0–5 times) as the exposure indicator. Individuals born between 1952 and 1958 were followed from 1979 to 2022 for incident reproductive cancers based on data from the Taiwan Cancer Registry. Poisson regression models were applied to estimate relative risks associated with each additional IRS exposure. Results: A total of 109,244 reproductive cancer cases were identified. Each additional DDT spraying round was associated with increased risks of breast, ovarian, corpus uteri, prostate, testicular, and cervical cancers (RRs = 1.01–1.16). Elevated risks were observed for testicular cancer (RR = 1.16, 95% CI: 1.01–1.23) and cervical cancer (RR = 1.01, 95% CI: 1.002–1.02), for which Asian epidemiological evidence remains limited. Higher exposure levels were also associated with differences in stage at diagnosis for breast cancer among women aged ≥55 years and for corpus uteri cancer. Conclusions: Early-life DDT exposure was associated with increased risks of several reproductive cancers. These findings support the Developmental Origins of Health and Disease framework and suggest that environmental exposures during critical developmental windows may influence long-term cancer risk. However, the findings should be interpreted cautiously given the ecological study design and potential residual confounding. Full article

Key agreement in open networks must not only resist quantum computing threats but also establish keys and authenticate counterparties without explicitly revealing identities. Existing solutions often rely on additional certificates or explicit signature-based authentication or require multiple rounds of interaction and complex state management, thereby imposing burdens on deployment and scalability. To address this, we propose a key agreement protocol based on a post-quantum identity-matching scheme, which unifies identity binding, implicit authentication, and session key establishment into a single key agreement process. Specifically, the initiator generates a ciphertext based on the peer’s identity and embeds session-related information within it, enabling the recipient to verify the peer’s identity and confirm the consistency of the key while decrypting and recovering the shared material. Additionally, bidirectional confirmation messages are used to eliminate negotiation deviations such as the sharing of unknown keys. Furthermore, a version control mechanism is introduced as a synchronization tag for key evolution, allowing the session key to be naturally updated within a predetermined time window. Concurrently, a revocation list maintained by a blockchain is established, enabling distributed verification and auditing of revocation status. This supports key update and revocation management without increasing the number of negotiation rounds. Performance evaluations and security analyses indicate that the protocol incurs a single-end computational overhead of less than 100 μs and a communication overhead of approximately 17.1 KB, trading moderate performance overhead for strong security semantics. Full article

To overcome low bioavailability and high trauma in inner ear therapies, targeted delivery across the round window membrane (RWM) via hollow microneedles (HMNs) offers a promising solution. However, the fabrication of high-aspect-ratio, small-size HMNs remains challenging. This study demonstrates the successful fabrication of small-outer-diameter HMNs using a 10 μm resolution digital light processing (DLP) system. Finite element analysis (FEA) identified a double tangent-arc transition as the optimal structural design for minimizing stress concentration. To manage the heightened parameter sensitivity at sub-feature-scale fabrication, a corrected curing index (CCI) model was established via a physics-informed regression approach incorporating polymerization kinetics and nonlinear spatial intensity distribution, achieving high fitting accuracy (R² > 0.96). Under optimized parameters, the fabricated HMNs possessed mean dimensions of 805.13 μm in height, 37.54 μm in inner diameter, and 79.36 μm in outer diameter. Compressive tests exhibited a robust structural strength of up to 141 mN per needle following post-curing. Combined in silico and in vitro experiments demonstrated excellent penetration performance. Furthermore, the HMNs achieved stable, pressure-dependent delivery with volumetric flow rates rising from 0.14 mL∙min⁻¹ to 0.39 mL∙min⁻¹ as driving pressure escalated from 50 kPa to 300 kPa, validating their functional capacity for controlled drug administration. Full article

Climate change poses an increasing threat to the functionality of forest transportation infrastructure, particularly in northern regions where seasonal access and ground conditions are critical for wood mobilization. The objective of this study was to assess how projected changes in temperature and precipitation may compromise accessibility to forest resources. In addition, it aimed to develop targeted adaptation recommendations to support resilient transportation systems. These actions are essential to ensure the continuity of wood supply under future climatic conditions. Climate projections were extracted from the climatedata.ca platform based on the CMIP6 (CanDCS-M6) model under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Using a GIS-based workflow, projected temperature and precipitation data were spatially matched to the selected Forest Management Units (FMUs) in Quebec, Canada, and the study area was divided into three latitudinal subregions to capture spatial temperature variation. Classified road network maps were then overlaid with projected climate data for 2020, 2040, 2060, and 2080 to evaluate winter road usability, precipitation-related exposure of road classes, and changes in effective winter road density. Results showed a consistent shortening of the winter road operational period under all scenarios, with the most severe reductions under SSP5-8.5. In highly affected areas, the winter road usability window may decrease from 90 days in 2020 to only 21 days by 2080. Increased precipitation is also expected to affect numerous road segments, raising risks of erosion, sedimentation, and loss of accessibility. A reduction of approximately 7% in effective winter road density is projected across the study area under the high-emission scenario (SSP5-8.5), reflecting the most severe impact of future temperature increases. Based on these findings, targeted road upgrades, climate-informed infrastructure design, and alternative access planning are proposed to help sustain wood flow and support year-round forest operations under future climatic conditions. Full article