Search Results (4,925)

Underground mining robots are increasingly modeled for planning, operator training, and digital-twin workflows, where reliable actuator-level kinematics is needed to reduce hazardous in situ trials. Unlike typical open-chain industrial manipulators, representative mining machines are often linear-actuator-driven closed-chain mechanisms with planar four-bar linkages, making reusable kinematic modeling and real-time FK/IK solving challenging. We present MineRobot, an actuator-centered framework for modeling and solving the kinematics of this representative mechanism class. MineRobot introduces the Mining Robot Description Format (MRDF), a domain-specific representation that parameterizes mining-robot kinematics with native semantics for actuators and loop closures. It then contracts planar four-bar substructures into generalized joints and extracts, for each actuator, an Independent Topologically Equivalent Path (ITEP) classified into four canonical types. Based on this decomposition, per-type solvers are composed into a sequential forward-kinematics (FK) pipeline, while inverse kinematics (IK) is formulated as a bound-constrained actuator-length optimization solved by a Gauss–Seidel-style update scheme. By converting coupled closed-chain kinematics into small topology-aware solves, MineRobot reduces robot-specific hand derivations and supports efficient repeated FK/IK computation without treating each query as a full coupled constraint-solving problem. Experiments on representative underground mining robots demonstrate real-time FK performance and robust IK convergence within the tested operating ranges, supporting the use of MineRobot as an actuator-centered kinematic layer for planning, training, and digital-twin workflows. Full article

The safe and uninterrupted operation of the ship’s main engine is critical for maritime transportation. The shutdown mechanism, part of the main engine protection systems, prevents serious damage by automatically stopping the engine in critical situations such as low lubrication oil pressure, overspeed, high bearing temperature, and cooling system failures. However, identifying the faults that trigger the shutdown system and evaluating their risk levels is crucial for improving system reliability. In this study, shutdown events that may occur in a two-stroke low-speed marine diesel main engine were investigated using Fuzzy Fault Tree Analysis (FFTA). The shutdown event was defined as the peak event, and a total of 34 baseline events were modelled under five main branches: low lubrication oil pressure, overspeed, high thrust bearing temperature, abnormal jacket coolant inlet condition, and crankcase/cylinder oil mist formation. Fuzzy assessments based on expert opinions were defuzzified and converted into probability values and used in fault tree calculations. The results showed that the shutdown risk is largely affected by failures originating from the jacket coolant system and the lubrication oil system. Specifically, lubrication oil filter clogging and contamination/blockage in the coolant line were identified as the most critical risk factors. The findings significantly contribute to prioritizing maintenance and condition-monitoring activities aimed at improving the ship’s main engine reliability through a risk-based approach. Full article

Grid-connected photovoltaic–battery energy storage–electric vehicle (PV-BESS-EV) charging stations require supervisory energy management that can coordinate tariff response, carbon-intensity signals, peak constraints, storage utilization, and converter-level operability within a transparent evidential framework. This study develops a bounded-reference rule-based supervisory energy management system (RB-SEMS) that preserves lower-level local converter controllers while generating operating modes and saturated reference commands for BESS power, grid exchange, and EV charging limits. A dual-time-scale evaluation framework is established by combining short-time switching/control simulations for dynamic traceability and SOC-sensitive protection with 24 h, 15 min EMS-level energy-balance simulations for cost, carbon, peak, PV utilization, EV service, and storage throughput assessment. Selected daily reference-injection cases are retained as copied-model diagnostic checks rather than as full-day switching-level validation. Under the D4-LSOC condition, RB-SEMS reduces the reported post-startup DC-bus deviation from 46.13 V to 40.60 V and the filtered BESS peak from 269.18 kW to 84.42 kW. In the E1-TOU scenario, E1-TOU-cost reduces daily total cost from 623.57 CNY to 564.05 CNY, lowers peak-period grid import from 183.75 kWh to 126.75 kWh, and increases local PV utilization from 71.13% to 78.71%; E1-PC66 further reduces the maximum 15 min grid import from 77.88 kW to 66.00 kW. Under the prescribed E2-PCC scenario, E2-CP reduces the calculated grid-related CO₂ emissions from 550.29 kg to 500.42 kg, whereas the price-only diagnostic increases them to 572.29 kg. Same-metric PV-SC and MILP comparisons, tested-range sensitivity analysis, and a throughput-based degradation proxy clarify that RB-SEMS is an interpretable supervisory baseline for cost–carbon–peak–cycling trade-off analysis rather than a cost-optimal controller or regionally validated proof of carbon reduction. Full article

Accurate fault location is essential for rapid service restoration in distribution networks. However, modern active distribution networks (ADNs) with high penetration of distributed energy resources (DERs) challenge conventional methods through multi-source fault contributions, bidirectional power flows, and converter-limited fault currents. This paper presents a time-domain fault location method for both passive distribution networks (PDNs) and ADNs, based on a three-sample apparent inductance estimator that uses local voltage and current measurements. The estimator exploits the strong correlation between line inductance and fault distance, with reduced sensitivity to fault resistance compared with classical impedance approaches. Its performance was evaluated on a 22 kV, 20 km distribution feeder, covering three fault types, four fault resistance levels (5–500 Ω), four fault locations, EN 50160 standard-compliant harmonic distortion, and DER penetration levels from 0 to 80%. Under ideal sinusoidal conditions, relative location errors remained below 2% for low-resistance faults. In ADNs, the method achieved errors below 5% for low-resistance faults across all fault types, with accuracy decreasing for high-resistance faults at high DER penetration. A sensitivity analysis confirmed robustness across the tested simulation conditions, covering the SNR, load current, THD, and DER penetration. Full article

Controller comparisons for grid-forming battery inverters are often confounded by simultaneous changes in the plant model, saturation law, measurement filtering, and disturbance envelope. This paper addresses that problem through a reproducible weak-grid benchmark and a switching-averaged EMT validation layer for a battery-backed PV microgrid. Droop, virtual synchronous machine (VSM), and power-synchronization control (PSC) are compared under identical plant data, load disturbance, grid-strength reduction, voltage sag, current limit, and metric-extraction rules. The benchmark reveals a consistent trade-off: VSM provides the best frequency moderation, droop provides the fastest post-fault restoration and the lowest implementation burden, and PSC provides the most balanced compromise across recovery, stability, EMT, and implementation metrics. The averaged EMT layer preserves the low-order restoration ordering and sharpens the waveform trade-off during the fault window. Additional analyses quantify the converter-angle excursions during the sag, clarify the reduced lag tolerance of VSM as the grid becomes weaker, and test the local robustness of the reported ranking against representative tuning perturbations. The resulting message is benchmark-specific but operationally useful: controller selection should follow the dominant project objective—frequency quality, restorative efficiency, or balanced performance—before controller-specific switching EMT, hardware-in-the-loop, and plant-level studies are launched. Full article

Background: Vitamin D has traditionally been recognized for its role in calcium homeostasis and skeletal health, but vitamin D receptor expression and vitamin D-metabolizing enzymes have also been identified in extra-skeletal tissues, including components of the male reproductive tract. Observational evidence has suggested associations between vitamin D status and androgen-related markers; however, whether vitamin D supplementation has a measurable effect on androgen bioavailability remains uncertain. Objective: This systematic review and meta-analysis evaluated the effects of vitamin D supplementation on total testosterone (TT) and androgen bioavailability markers in adult men, including sex hormone-binding globulin (SHBG), free androgen index (FAI), calculated free testosterone (calculated FT), and bioactive testosterone (BAT) where methodologically compatible. Methods: The review was registered in PROSPERO (CRD420261365005) and conducted according to PRISMA 2020 and Cochrane methodological guidance. Searches were conducted from database inception to April 2026 in PubMed, Web of Science, Scopus, ClinicalTrials.gov, and the WHO ICTRP. Embase was initially planned but was not searched because institutional access was unavailable; this amendment was made before screening, extraction, risk-of-bias assessment, and synthesis. Records were deduplicated in Zotero, screened in a structured matrix, and converted from report-level records into independent comparison-level datasets where appropriate. Meta-analyses used random-effects REML models with Hartung–Knapp adjustment. Results: The official search set comprised 2854 records, of which 703 duplicates were removed, leaving 2151 records for title and abstract screening. The full-text screening file was reconciled to 162 PRISMA-countable reports/records: 135 reports were assessed, 27 reports could not be assessed because the full text was unavailable or had not been obtained for review, and 27 reports/studies were retained for qualitative synthesis. Eighteen reports were considered candidate sources for quantitative synthesis and were operationalized into 21 comparison-level records. The primary TT model included 11 comparisons and showed no clear effect of vitamin D supplementation on final TT (MD 0.47 nmol/L, 95% CI −0.50 to 1.44; I² = 24.1%). No clear effects were observed for SHBG (MD 0.27 nmol/L, 95% CI −2.14 to 2.68), FAI (MD −0.37, 95% CI −4.28 to 3.55), calculated FT sensitivity evidence (MD −0.0096 nmol/L, 95% CI −0.0525 to 0.0332), or BAT exploratory evidence (MD −0.47 nmol/L, 95% CI −1.77 to 0.83). GRADE certainty was low for TT, SHBG, and FAI, and very low for calculated FT and BAT. Conclusions: Current randomized evidence does not demonstrate a statistically clear or reproducible effect of vitamin D supplementation on total testosterone or androgen bioavailability markers in adult men. GRADE certainty was low for total testosterone, SHBG, and FAI, and very low for calculated free testosterone and bioactive testosterone. Because directly measured and calculated free testosterone are not analytically equivalent, free testosterone was not pooled as a primary outcome; method-compatible calculated FT was handled as sensitivity evidence and BAT as exploratory evidence. Full article

Maintaining a constant frequency is vital for grid stability and reliability, especially during dynamic changes in load and generation, which are caused by the increasing incorporation of renewable intermittent energy sources such as solar and wind power. These energy sources decrease the system’s inertia, which compromises the primary frequency regulation, a process historically sustained by the speed regulators of conventional synchronous generators. In this study, to mitigate this issue, we investigate a battery energy storage system (BESS) operating with virtual synchronous machine (VSM) control to provide ancillary services of primary frequency control. A multilevel cascade H-bridge static converter with eleven levels is controlled to emulate the dynamic behavior of a conventional synchronous machine, allowing primary frequency control support. The case studies are evaluated using Matlab/Simulink R2024a software and tested under contingency scenarios involving load rejection and step-load insertion within an isolated power grid comprising other synchronous machines, alongside an analysis of the BESS-controlled power dispatch. Our simulation results demonstrate that the energy storage system, operating under a virtual synchronous machine (VSM) strategy, effectively emulates the dynamic behavior of a conventional synchronous generator, enabling controlled active and reactive power dispatch. Furthermore, the proposed control strategy provides virtual inertia support, mitigating the Rate of Change of Frequency (RoCoF) following disturbances, improves the damping of frequency oscillations, and ensures a smoother frequency recovery after load variations. These findings indicate that the proposed BESS can provide effective primary frequency control support in power systems characterized by a high penetration of converter-interfaced renewable energy sources. Nonetheless, further investigations into the influence of VSM parameters on the system’s dynamic response are needed to further optimize the performance of the proposed solution. Full article

Glaucoma is a leading cause of irreversible vision loss, and its early diagnosis remains critically important yet challenging. Traditional assessment based on the cup-to-disc ratio is often insufficient at early stages, whereas the retinal vascular network can provide additional quantitative biomarkers. This study develops and validates a binary classification method for distinguishing healthy from glaucomatous fundus images by combining deep-learning-based vessel segmentation, fractal and multifractal analysis, and textural features. The public ORIGA dataset is utilized. Images are converted to grayscale using three alternative approaches, followed by Gray-Level Co-occurrence Matrix texture analysis and fractal analysis based on the differential box-counting method. Vessel segmentation is implemented via a U-Net neural network trained on a combination of public datasets, after which multifractal analysis is performed on the resulting binary masks. The extracted features are used to train and compare several machine learning models with hyperparameter optimization. The best-performing model among ONH-based features (Random Forest) achieves 75.00%; however, a logistic regression model using multifractal parameters and CDR reaches 86.17%, substantially outperforming the CDR-only baseline (66.15%). Notably, while classical fractal dimension shows only marginal differences (1–2% relative change) between groups, multifractal parameters reveal distinct changes: the multifractal spectrum width $\Delta \alpha$ increases markedly and the minimum singularity exponent ${\alpha }_{\min }$ decreases in glaucomatous eyes, indicating increased heterogeneity of the vascular network. These findings suggest that multifractal characteristics of the vascular network can serve as reliable and sensitive biomarkers for automated glaucoma screening, offering clear advantages over classical fractal analysis. Full article

To address head-end three-phase current unbalance and terminal power-quality deterioration caused by uneven three-phase load allocation in a low-voltage transformer area (LVTA), this paper proposes a DC-link-voltage-control-based phase-wise unbalanced power compensation strategy for a head-to-tail flexible interconnection structure embedded in the LVTA. The proposed structure consists of two three-phase four-leg converters sharing a common DC bus and connected to the head end and tail end of the LVTA, respectively. Different from conventional phase-wise compensation methods in which the DC side mainly acts as a power-transfer channel, the proposed strategy uses the DC-link voltage control of the head-end converter as the core of compensation power generation. Specifically, the outer DC-link voltage loop generates the total active compensation power, which is then allocated among the three phases according to the measured phase-power unbalance of the LVTA, thereby yielding the phase-wise compensation current references. Combined with phase-wise quasi-proportional-resonant current control, the compensation currents of different phase legs can be regulated without explicit positive-, negative-, and zero-sequence decomposition. Meanwhile, the tail-end converter adopts PQ control to support terminal power regulation and improve the terminal voltage quality of the LVTA. To provide a theoretical basis for the proposed method, a switching-cycle averaged model of the three-phase four-leg converter is established, and the leg-level phase-wise control characteristics are analyzed under the assumptions of a stiff DC link and symmetrical converter parameters. A control-oriented equivalent LVTA model is developed in MATLAB/Simulink. The proposed strategy is validated under steady-state unbalanced, RL load, load-disturbance, and equivalent feeder-impedance conditions. In addition, a conventional positive-, negative-, and zero-sequence compensation method is introduced as a benchmark for quantitative comparison. The simulation results demonstrate that the proposed method can effectively suppress the head-end three-phase current unbalance, maintain the DC-link voltage around its reference value, and improve the terminal voltage quality of the LVTA. Compared with the conventional sequence-component-based compensation method, the proposed strategy achieves effective unbalance mitigation while avoiding explicit sequence extraction and reducing the complexity of the compensation-current generation process. This study provides a feasible control framework for three-phase unbalance mitigation in flexible low-voltage transformer areas. Full article

Renewable energy communities (RECs) are legally recognised instruments of decentralised energy transition, but their scaling remains limited by a separation between governance design, economic appraisal, and multi-criteria decision analysis (MCDM/A). This systematic review applies a conservative explicit-reporting coupling diagnostic to 322 REC studies from a 2014–2026 corpus. The diagnostic identifies 267 unilateral studies (82.9%), 55 bilateral studies (17.1%), and no study satisfying the strict trilateral criterion at the title/abstract/metadata reporting threshold. A loosened-keyword sensitivity test identified two weak trilateral candidates, but the manual construct-validity audit did not support reclassifying them as strong trilateral studies. The result is therefore interpreted as a conditional and conservative signal of limited visible integration, not as proof that no body-text-level integration exists. The paper argues that the observed separation is not only methodological but also institutional. It therefore proposes second-level renewable energy cooperatives as federated decision-support entities that pool data stewardship, distributional economic appraisal, stakeholder-weighted MCDM/A, and auditable cooperative voting packages while preserving local REC control. The model converts the explicit-reporting gap into a testable governance architecture for REC scaling. Full article

Background/Objectives: Evidence on spinal versus general anesthesia in unilateral total knee arthroplasty (TKA) may not extend to one-week-staged bilateral surgery, where older patients receive two anesthetics in a short interval and intra-operative spinal-to-general conversion is common but rarely reported transparently. We compared peri-operative acute kidney injury (AKI) and transfusion between strategies in this setting. Methods: We retrospectively analyzed 207 patients (414 surgeries) undergoing one-week-staged bilateral primary TKA at one center. Co-primary endpoints were creatinine-based AKI (patient level) and packed-red-blood-cell transfusion (surgery level). Because 42 general-anesthesia-classified surgeries had an attempted spinal injection, the primary analysis used the initial anesthetic plan (an intention-to-treat analogue), reclassifying these as spinal, with as-treated classification as a sensitivity analysis; AKI was modeled at the patient level (any general anesthesia versus spinal–spinal) and transfusion per surgery. Results: Median age was 75 years and 82.6% were female; AKI affected 74 of 207 patients (35.7%) and transfusion 185 of 414 surgeries (44.7%). The adjusted any-general-anesthesia versus spinal–spinal estimate was not statistically significant and opposite the spinal-protective hypothesis (adjusted odds ratio 0.49, 95% confidence interval 0.23–1.01, p = 0.054), and no pre-specified sensitivity scenario survived Benjamini–Hochberg correction. Transfusion did not differ between strategies; among secondary endpoints, length of stay, hemoglobin drop, peak C-reactive protein, and intra-operative hypotension likewise showed no significant difference after multiplicity correction. Conclusions: These hypothesis-generating findings do not support changing anesthetic practice; the choice should remain individualized. Approximately 12% of attempted spinal anesthetics converted intra-operatively to general anesthesia—a record-based observation, not a validated failure rate. Full article

The carbon emission allowance (CEA) market is a complex socio-technical and environmental-management system in which regulatory design, trading activity, liquidity conditions, and price volatility interact dynamically. Accurate systems-level tail-risk forecasting and early warning remain challenging because carbon-market losses are affected by nonlinear dependence, episodic liquidity stress, and time-varying volatility. This study proposes an Interpretable Quantile Temporal Network (IQTN) as a systems-oriented risk-monitoring framework for China’s national CEA market. By integrating a feature-gating mechanism, a causal temporal convolutional encoder, and a non-crossing quantile output layer, IQTN directly models the conditional tail distribution of future carbon-market losses. The framework produces multi-horizon Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) forecasts for 1-day, 5-day, and 10-day horizons and converts predicted tail risk into operational early-warning signals. Compared with historical simulation, EWMA, GARCH-type models, machine-learning quantile models, and deep temporal benchmarks, IQTN achieved the lowest 95% VaR pinball loss across all horizons, with values of 0.1765, 0.3958, and 0.5732. VaR backtesting showed empirical exceedance rates of 5.23%, 6.04%, and 6.94%, closest to the nominal 5% level. Interpretability analysis identified rolling volatility, maximum loss, intraday range, trading value, and illiquidity as key risk drivers. The temporal importance results also show that recent observations dominated the risk forecasts, suggesting that the risk state of the CEA market is highly sensitive to short-term market information. This supports the use of a short-horizon temporal network as a systems-oriented tool for carbon-market tail-risk monitoring and early warning. Full article

Software quality assessment in agile projects remains fragmented. Technical, process-related, and team-related indicators are often evaluated through separate models, tools, and reports. This fragmentation limits cross-project comparability and weakens evidence-based decisions for software quality improvement. To address this problem, this study proposes the Overall Software Quality Index (OSQI), a multidimensional decision-support framework for software quality assessment in agile projects. OSQI integrates code quality, process quality, and team quality into a single project-level assessment model. The framework was initially grounded in ISO/IEC 25010:2011 and is discussed in relation to the ISO/IEC 25010:2023 revision, particularly its explicit inclusion of Safety as a product quality characteristic. Since the industrial datasets used in this study were not collected from safety-critical systems, Safety was not modeled as a separate OSQI dimension in the current version; instead, it is addressed as a scope limitation and future extension. The measurement structure was defined using the Goal–Question–Metric (GQM) approach. An initial set of 49 candidate metrics was reduced to 15 core indicators. This reduction was performed using dimension-specific strategies: Random Forest-based feature importance for code quality, Delphi and Analytic Hierarchy Process (AHP) for process quality, and thematic consolidation for team quality. The selected indicators were normalized and integrated through entropy-based weighting. This process generates an interpretable composite quality score. The main contribution of OSQI is not the isolated use of these methods, but their integration into a reproducible and tool-supported framework. The framework converts heterogeneous software engineering signals into a unified decision-support index. OSQI was evaluated using industrial agile project data. The data included static code analysis outputs, issue-tracking records, team assessment results, and product outcome indicators. In an exploratory validation across five industrial projects, OSQI showed a strong positive association with Net Promoter Score ($r=0.97, p=0.0076$) and a strong negative association with churn rate ($r=-0.97, p=0.0061$). A supporting software tool was also developed to automate data integration, score calculation, visualization, and project-level comparison. The findings suggest that OSQI can support quality monitoring, project benchmarking, and evidence-based improvement decisions in agile software engineering contexts. Full article

Tourism development potential and observed development performance do not necessarily evolve synchronously, particularly in old industrial and restructuring regions where attraction supply, market linkage, and visitor experience may be spatially uneven. This study develops a multi-source diagnostic framework for identifying tourism potential–performance mismatch across the 14 prefecture-level cities of Liaoning Province, China. Drawing on Ctrip review texts, rating scores, timestamps, platform-displayed reviewer-origin labels, A-level scenic-spot point data, and annual official city-level tourism statistics, the study constructs three dimension-specific sub-indices—the Scenic Experience Index (ESI), the Market Linkage Index (MLI), and the Attraction Foundation Index (AFI)—and synthesizes them into a Comprehensive Potential Index (CPI). The CPI is then compared with an Observed Performance Index (OPI) constructed from domestic tourist arrivals and domestic tourism revenue for 2016–2022. The results show that attraction foundation contributes most strongly to composite tourism potential, while market linkage and scenic experience condition how this structural basis is associated with observed outcomes. The CPI–OPI comparison identifies three relationship types: matched, potential-leading, and performance-leading cities. Dalian and Shenyang are high-level matched cities, Benxi and Jinzhou are high-potential but under-converted cities, and Anshan and Dandong are performance-leading cities. These findings demonstrate that favorable structural tourism conditions are not automatically transformed into realized market performance. The study contributes a multidimensional, gap-analysis-based diagnostic architecture that can support tourism-related spatial planning and territorial governance in transitional regions. Full article

The safety profile for bio-derived phenols post-oxidation and their related antioxidant/redox potential remain largely under-explored. Oxidation by fungi, in terms of environmental impacts via fungal oxidation by enzymes, remains an attractive strategy under milder conditions, since it is one route by which many naturally occurring lignocellulosic phenols are modified; thus, an immediate need still exists for characterizing the effects that these modified phenolic compounds may have. Methodology: We examined four different biomass-derived phenolics—vanillin, ferulic acid, syringaldehyde and guaiacol—that were oxidized with fungal laccase and characterized their effects on normal human lung fibroblasts and levels of cellular oxidative stress. Laccase activity was evaluated via the ABTS method and through simple observation and UV-Vis spectroscopic scanning of the phenolics in question, and compared with the untreated version of each phenolic. In addition to assessing the cytotoxic effect and oxidative stress generated by the phenols alone, an ELISA-based measurement assay was used to investigate the relative abundance of malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and reduced glutathione (GSH) in the human normal lung fibroblast cell line under varying treatment regimes, complemented by phase-contrast microscopy. Scores integrating the biomarkers were analyzed via clustering, PCA, radar and Pearson correlation analyses, to discern distinct trends in antioxidant potential after laccase conversion. Observations: Each of the four tested phenolics demonstrated the presence of laccase activity, leading to substantial differences in visible appearance compared with the control and characteristic absorbance shifts at differing wavelengths from the original molecule. Cell viability dropped dramatically as phenol concentration was increased and the untreated phenolics resulted in diminished confluence and induced greater levels of oxidative damage, from guaiacol and syringaldehyde. Laccase treatment resulted in higher MTT reduction activity and improved cellular morphology compared with the corresponding untreated phenolic compounds. Untreated phenols induced the highest levels of MDA, while decreasing SOD, CAT, GPx and GSH levels. Post-oxidation with laccase, there were lower amounts of lipid peroxidation, along with improved levels of antioxidant activity compared with the control phenol. Multi-technique analyses show clear distinctness between the untreated and laccase-converted phenolic groups. Clustering with multivariate techniques separated all cell groups in line with control samples, grouping the laccase-converted treatments towards the middle and displaying an inverse relationship between MDA and the antioxidant markers. Conclusions: Laccase conversion markedly decreases the adverse effects that bio-derived phenols have on normal cell viability and induces fewer detrimental effects on the cellular redox balance. This is a critical discovery in terms of finding greener methods by which to upgrade bio-derived substances as we research these lignocellulosic phenols. By employing ELISA-based measurements along with multiple analysis techniques, we present a suitable paradigm for studying biological effects in all bio-based goods intended for pharmaceuticals, packaging materials, nutraceuticals or a host of different applications. Full article