Search Results (10,930)

The rapid deployment of electric vehicles (EVs) has introduced new challenges to distribution networks, which are mainly related to power quality and grid reliability. Electric vehicle chargers behave as nonlinear loads because they are based on power electronic converters, which generate harmonic currents, cause voltage distortion, increase stress on network components, and might impact the overall power quality of distribution networks. In this study, power quality (PQ) measurements and harmonic characteristics were investigated for five electric vehicle models, namely the BYD Song Plus, Volkswagen ID6, Neta U, Nissan LEAF 2016, and Tesla Model 3. Measurements were carried out for different power levels—slow AC, low-power and fast AC, high-power charging modes—to evaluate the PQ characteristics and harmonic behavior of EVs. Fast charging power levels for most vehicles ranged between 5 and 11 kW, while slow charging ranged between 2.7 and 3.6 kW. It is found that harmonic characteristics, total harmonic current distortion (THD_I), and harmonic distribution depend on the EV type and the charging mode. This study found that THD_I varies between 1.5% and 10.72% for the tested EVs. Comparison with IEC power quality standards indicates that the impact of electric vehicle charging on voltage quality is limited, while current harmonic distortion varies significantly among vehicle models. Harmonic analysis reveals that the third and fifth orders dominate across most of the tested EVs, while the transition from slow to fast charging power level generally reduces low-order harmonics in most models, with vehicle-specific redistribution patterns that reflect converter topology and control strategy. The results also show that some EV chargers draw reactive power and operate with a lagging power factor, whereas other vehicles inject reactive power and operate under leading power factor conditions. Full article

As network environments become increasingly interconnected, ensuring robust cyber-security has become critical, particularly with the growing sophistication of modern cyber threats. Intrusion detection systems (IDSs) play a vital role in identifying and mitigating unauthorized or malicious activities; however, conventional machine learning-based IDSs often rely on handcrafted features and are limited in their ability to detect diverse attack types across disparate network domains. To address these limitations, this paper introduces a novel unified intrusion detection framework that implements “Structural Dualism” to integrate three heterogeneous benchmark datasets (CSE-CIC-IDS2018, NF-BoT-IoT-v2, and IoT-23) into a harmonized, protocol-agnostic representation. The framework employs a shared autoencoder architecture with dataset-specific projection layers to learn a unified latent manifold. This 15-dimensional space captures the underlying semantics of attack patterns (e.g., volumetric vs. signaling) across multiple domains, while dataset-specific decoders preserve reconstruction fidelity through alternating multi-domain training. To identify complex micro-signatures within this manifold, the framework utilizes a synergistic hybrid convolutional neural network–deep neural network (CNN–DNN) classifier, where the CNN extracts spatial latent patterns and the DNN performs global classification across twenty-five distinct classes. Class imbalance is addressed through resampling strategies such as adaptive synthetic sampling (ADASYN) and edited nearest neighbors (ENN). Experimental results demonstrate remarkable performance, achieving 99.76% accuracy for binary classification and 99.54% accuracy for multi-class classification on the merged dataset, with strong generalization confirmed on individual datasets. These findings indicate that the shared autoencoder-based CNN–DNN framework, through its unique feature alignment and spatial extraction capabilities, significantly strengthens intrusion detection across diverse and heterogeneous environments. Full article

Background/Objectives: This study evaluated the effects of at-home bleaching on color stability (ΔE) and surface roughness (Ra) of a single-shade nanohybrid composite, an ORMOCER-based composite, and a conventional nanohybrid resin composite, acknowledging that bleaching represents only one of several clinical ageing challenges. Methods: One hundred and five extracted, non-carious human molars received standardized Class I restorations and were randomly allocated to five groups (n = 21): an ORMOCER-based composite (Admira Fusion), a single-shade composite (Omnichroma), Omnichroma bonded with an alternative universal adhesive, and two conventional nanohybrid composites (Filtek Supreme Ultra and Harmonize). Baseline and experimental color (CIELAB, ΔE) were measured with a spectrophotometer, and surface roughness (Ra) was measured using a 3D optical profilometer. Specimens underwent five bleaching cycles using 22% carbamide peroxide, with each cycle consisting of 8 h of bleaching followed by 16 h of storage in artificial saliva at 37 °C. Measurements were taken at baseline and after each cycle. The data were analyzed using a repeated-measures ANOVA, with bleaching cycle as the within-subject factor, the effect sizes reported as partial eta-squared (ηp²), and the statistical significance set at α = 0.05. Results: All restorative materials exhibited progressive color change with repeated bleaching, and ΔE values exceeded established clinical acceptability thresholds across materials. The extent of color change varied among materials. None of the evaluated materials maintained clinically acceptable color stability following repeated bleaching cycles. The single-shade composite (Omnichroma) demonstrated the greatest magnitude of color change, particularly when bonded with Scotchbond Universal Bond. Admira Fusion and Filtek Supreme Ultra had lower ΔE values but still exceeded acceptability thresholds. Surface roughness generally decreased following bleaching, with statistically significant reductions in Ra observed for multiple materials. Admira Fusion and Omnichroma bonded with Tokuyama Universal Bond showed minimal surface alteration. Conclusions: All restorative materials demonstrated clinically unacceptable color changes following bleaching, indicating limited esthetic stability under bleaching conditions. ORMOCER-based composites showed comparatively greater resistance to surface roughness alterations. Full article

Mangrove ecosystems are recognized as highly efficient blue-carbon reservoirs, yet their monitoring requires scalable, transparent methods suitable for climate-finance and greenhouse-gas accounting applications. This study quantifies interannual carbon-stock dynamics and derives a carbon-market valuation indicator for Ecuador’s Churute Mangrove Ecological Reserve (2015–2021) using publicly available remote-sensing land-cover products. Annual activity data were derived from Copernicus Global Land Service LC100 (100 m, 2015–2019) and ESA WorldCover (10 m, 2020–2021), harmonized to a common reporting scheme, and combined with IPCC Tier 1 default coefficients for biomass and soil organic carbon in tropical wetlands. Total carbon stocks averaged 1.67 million t C across the period, remaining stable within the internally consistent LC100 phase (2015–2019), with trend statistics treated as descriptive given the short annual series, while a pronounced drop in 2020 primarily reflected methodological discontinuities between products rather than ecological change. Converted to CO₂e equivalents (mean 6.1 million t CO₂e), illustrative market values fluctuated between USD 18 and 123 million annually, driven predominantly by carbon-price variability. This remote-sensing-based, MRV-aligned approach provides a conservative baseline for protected-area blue-carbon accounting, highlighting the need for homogeneous high-resolution time series to distinguish real dynamics from classification artifacts in future assessments. Full article

Background: Microplastics (MPs) and nanoplastics (NPs) are now common in land and water ecosystems. Their spread is an increasing issue from a One Health perspective. These particles end up in soils, water, air, and farm inputs. This poses direct risks to animal health and indirect risks to people who eat animal-derived food. There are also risks from plastic additives and pesticides migrating with these particles in animal-based food. Scope and Approach: This review summarizes how MPs and NPs move in agroecosystems and livestock production. It covers their main sources, such as agricultural plastics, sludge-amended soils, plastic-lined storage, and environmental fallout. It explains how farm animals are exposed, including through feed, water, soil contact, and inhalation. Evidence is condensed for occurrence in manure, tissues, and animal products. The review also highlights key analysis challenges, especially those limiting the assessment of nanoplastic exposure. Key Findings: Field surveys show very different contamination levels in the environment. Agricultural soils range from 0.36 to 42,960 particles/kg. Livestock indicators, like contaminated feed and manure, range from 10² to 10⁵ particles/kg. In free-roaming systems, chicken feces have very high loads, showing trophic transfer in land food chains. A pilot study found plastic particles in pig and cow blood, suggesting some particles cross the gut into the blood. Experimental models link MPs/NPs to oxidative stress, inflammation, mitochondrial dysfunction, metabolic disturbance, and potential reproductive toxicity in livestock and poultry. Conclusions and outlook: Animal-based foods provide a major source of human exposure. MPs and NPs have been observed in milk and poultry products, such as packaged meat and eggs (mean 11.67 ± 3.98 particles/egg). There is still a research gap on raw milk taken directly from the teat and on raw eggs that have not been handled or packaged. This gap makes it hard to identify real contamination sources and control strategies. The review stresses the need for harmonized detection methods (especially for NPs), monitoring from farm to fork, and practical ways to reduce plastic use on farms and minimize contamination during processing, feed handling, and packaging. Full article

The gamma band observed in human electroencephalography (EEG) has been extensively studied. However, recent research has begun distinguishing the potential roles assigned to phase and non-phase modulation within this band. The primary aim of this study is to analyze the potential role of non-phase gamma modulation in a widely used visual task in human subjects. For this purpose, using a 58-channel EEG recording, gamma activity was evaluated during an oddball task. Responses from 21 healthy subjects were recorded at two separate time points, with an average interval of 49.5 ± 48.9 days. Latency, amplitude, and topographic correlation values were calculated to assess the replicability. Furthermore, potential influence of alpha band harmonics on gamma was analyzed. Topographic analyses revealed a strong negative correlation between gamma phase-locked (synchronous) and non-phase-locked (asynchronous) activity, with correlation coefficients of r < −0.9 for both measures. The results observed between the two time points were robust. The harmonic analysis did not show any potential contribution of the alpha band. The separate analysis of phase and non-phase activity has enabled us to identify distinct roles for each. Establishing non-phase activity as a perceptual “anti-binding” mechanism opens new avenues for exploring a previously unaddressed aspect of gamma activity. Full article

Text-to-music generation aims to automatically produce audio content with semantic consistency and coherent musical structure based on natural language descriptions. However, existing methods still face challenges in terms of style diversity, rhythmic consistency, and long-term structural modeling. To address these issues, we propose a novel text-to-music generation model, termed MusicDiffusionNet (MDN), which integrates diffusion models with the WaveNet architecture to jointly model musical semantics and temporal structure in a continuous latent space. By decoupling high-level semantic conditioning from low-level audio generation, MDN enhances its ability to model long-range musical structure while improving semantic alignment between text and generated music with stable generation behavior. Building upon this framework, we further design two complementary mixing strategies to improve generation quality and structural coherence. Adaptive Style Mixing (ASM) performs weighted interpolation among stylistically similar music samples in the style embedding space, incorporating key and harmonic compatibility constraints to expand the style distribution while avoiding dissonance. Multi-scale Temporal Mixing (MTM) adopts beat-aware temporal decomposition, mixing, and reorganization across multiple time scales, thereby enhancing the modeling of both local and global temporal variations while preserving rhythmic periodicity and musical groove. Both strategies are integrated into the diffusion process as conditional augmentation mechanisms, contributing to improved learning stability and representational capacity under limited data conditions. Experimental results on the Audiostock dataset demonstrate that MDN and its mixing strategies achieve consistent improvements across multiple objective metrics, including generation quality, style diversity, and rhythmic coherence, validating the effectiveness of the proposed approach for text-to-music generation. Full article

Melissa officinalis L. (lemon balm) is a Lamiaceae species widely used in traditional and contemporary herbal practice, yet its reported bioactivities are strongly preparation-dependent, reflecting variability between polyphenol-rich extracts and volatile essential-oil fractions. This integrative review links phytochemistry with recent preclinical findings and available clinical evidence. Across model systems, lemon balm most consistently shows antioxidant and anti-inflammatory signatures, with additional domain-specific signals reported in neurobehavioral, cardiometabolic, gastrointestinal, and dermatological models; however, comparability is limited by heterogeneous plant parts, extraction procedures, and chemical standardization. Preclinical findings were organized by biological domain, whereas clinically, the most consistent signals are observed for symptom-oriented endpoints, particularly anxiety/stress and sleep-related outcomes reported in controlled trials, including aromatherapy studies, while evidence for other indications remains mixed or insufficiently confirmed. Overall, the evidence supports continued development of chemically characterized, standardized preparations and mechanism-informed trials with harmonized outcomes and robust safety reporting to improve translational interpretability. Full article

Current national-scale building stock models mainly focus on structural materials, overlooking the significant resource potential of Mechanical, Electrical, and Plumbing (MEP) systems. These systems are resource-intensive and contain standardized components with high-value materials such as copper and steel, yet their potential remains largely untapped due to fragmented data. This study introduces the novel systematic framework to estimate MEP components at high granularity and national scale. It integrates harmonized public data, machine-learning imputation (>90% accuracy under sparse conditions), and parametric rules reflecting building type, energy system, and construction decade. A Swiss case study yields scalable material stock estimates and lifespan-based turnover projections, showing strong consistency with existing GHG benchmarks. The framework highlights contrasting patterns across regions and building types, indicating where policy and industry can upscale reuse and recovery. Its modular design enables transferability and integration with circular economy planning and material-efficiency targets. Full article

This work analyzes the non-Newtonian electromagnetohydrodynamic (EMHD) flow in an irregular circular porous microchannel while incorporating the consequences of surface charge-dependent slip boundary conditions. The Jeffrey fluid is employed to examine the non-Newtonian behavior, such as elasticity. The boundary walls of the channel are considered in the form of periodic sinusoidal wave function. The mathematical formulation is developed using the momentum equation, modified Darcy’s law, the continuity equation, and Ohm’s law. The perturbation method is used to derive the solutions up to second-order approximation. The analytical expression for the velocity field and volumetric flow rate are explicitly presented. At the zeroth-order, a nonhomogeneous partial differential equation is solved, and the solutions are presented in terms of Bessel functions. The first-order problem defined by a homogeneous partial differential equation is solved using the method of separation of variables. At the second-order, a homogeneous partial differential equation is obtained, and the solution form is prescribed by the boundary conditions, consisting of a radially varying mean component and a second-harmonic angular contribution. Two- and three-dimensional plots are used to analyze and discuss the impacts of key parameters, namely the Reynolds, Darcy, and Hartmann numbers, channel corrugation amplitude and wave number, surface charge density, and the relaxation and retardation times on the velocity field and flow rate. It is found that elastic memory causes a proportional growth between the flow rate and the relaxation time, emphasizing the consequences of surface charge application in conjunction with corrugations. Conversely, maintaining a short retardation time mitigates changes in wave amplitude and surface charge. While prolonging it lessens the flow rate and diminishes corrugations and surface charge effects. The Darcy number dampens the velocity and the flow rate, while its enhancement reduces the impact of surface charge density and corrugations amplitude. For high Reynolds number, a ring phenomenon emerges which is attenuated by increased Darcy number, preventing the formation of trapped boluses close to the border. Ignoring surface charge amplifies the flow rate while its consideration diminishes the latter with reinforced impacts of surface charge and wall corrugations at higher Reynolds number. Full article

Background: B-cell maturation antigen (BCMA) directed therapies have transformed the treatment landscape for relapsed or refractory multiple myeloma (RRMM). Soluble BCMA (sBCMA), a circulating product of the membrane-bound BCMA shedding, has emerged as a potential biomarker reflecting tumor burden and disease biology. This systematic review and meta-analysis aimed to evaluate the prognostic value of baseline circulating sBCMA in patients with multiple myeloma receiving BCMA-directed therapies, with progression-free survival (PFS) as the primary endpoint. Methods: A systematic literature search of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases was conducted in accordance with PRISMA guidelines. Studies enrolling patients with multiple myeloma treated with BCMA-directed therapies and reporting baseline circulating sBCMA measured in serum or plasma in relation to survival outcomes were included. Hazard ratios (HRs) for PFS and overall survival (OS) were pooled using random-effects models. Risk of bias was assessed using the QUIPS tool. Results: Four independent RRMM cohorts fulfilled the eligibility criteria and were included in the quantitative PFS meta-analysis. Elevated baseline circulating sBCMA was significantly associated with inferior PFS (pooled HR = 2.64, p < 0.05), with a consistent adverse prognostic direction across all studies. Moderate to substantial heterogeneity was observed (I² = 63.2%), potentially reflecting differences in BCMA-directed therapy modalities across cohorts and methodological variability, including study-specific sBCMA cut-off definitions, assay procedures and sampling timepoints. Exploratory subgroup analysis suggested that the prognostic impact of baseline sBCMA on PFS may differ according to BCMA-directed therapy class. Overall risk of bias was judged as low to moderate. Conclusions: Elevated baseline circulating sBCMA is associated with inferior progression-free survival in patients with multiple myeloma treated with BCMA-directed therapies. These findings support the prognostic relevance of sBCMA as a risk stratification marker, although harmonization of assays and cut-offs and prospective validation are required before clinical implementation. Full article

Environmental degradation in Iraq is a critical issue that requires strong monitoring. One indication of land degradation is a decrease in or loss of vegetation cover. This study examines changes in vegetation and productivity in the Thi-Qar region from 2001 to 2022, using the normalized difference vegetation index (NDVI) and net primary production (NPP), and their response to climatic and hydrological factors. To address the gap in assessments that simultaneously quantify the influence of streamflow, rainfall, and temperature across distinct land cover classes in arid and semi-arid regions, we developed a replicable multi-source geospatial framework. We used MODIS data within the Google Earth Engine platform to perform spatiotemporal analysis. We applied models to detect NDVI trends on a pixel-by-pixel basis. This study provides the first integrated, data-driven assessment of vegetation sensitivity to streamflow versus climate in the Thi-Qar Governorate using a harmonized multi-source dataset. This combines the FAO WaPOR NPP dataset with hydrological (streamflow) and climatic (CHIRPS rainfall, MODIS LST) variables within an analytical workflow to extract anthropogenic water management from climatic drivers. The results showed variations in the NDVI and productivity in the southern and southwestern regions, indicating areas of both degradation and improvement. The analysis found that 12% of the study area showed improvement, while 56.5% of the area showed degradation. Additionally, we classified the study area as either vegetation (cropland) or non-vegetation (fallow arable land, bare areas, and sand dunes). A multiple regression model was then applied to these categories to examine the relationships between streamflow, precipitation, land surface temperature (LST), and the NDVI. The multiple regression for the entire region showed that these factors explained 45.1% of NDVI variation, with streamflow being the most significant positive driver (p < 0.001). The result showed that the NDVI in cropland and arable land was strongly positively correlated with both precipitation and streamflow (R = 0.78, R = 0.75). In contrast, bare land and dunes showed weaker relationships (R = 0.26 and 0.51, respectively). Of these factors, streamflow had the most significant influence in explaining vegetation change (partial correlation p = 0.53), indicating the importance of human management in addition to climate. Full article

This article proposes a parallel current-summing LCC multilevel inverter (MLI) to suppress harmonic distortion of radiated EMI for wireless power transfer. Traditionally, ZVS has been an issue for staircase voltage output multilevel inverters because a shared current output became faster than some of the voltage transitions in staircase voltage output. The other common problem was capacitor voltage imbalance and resultant output voltage distortion if a sophisticated voltage balancing function is not used. The proposed LCC MLI ensures ZVS by separating each voltage transition into multiple bridge legs. Each bridge leg outputs different phases of currents for each voltage transition. The individual output currents are summed at the matching network of wireless power transfer, generating a near-sinusoid output current to suppress harmonic distortions. In this way, each leg achieves ZVS even though the summed output current at the LCC network is faster than some of the voltage transitions. To avoid the capacitor voltage imbalance issue, the proposed MLI eliminated the flying capacitor. Instead, the four parallel legs are supplied by a shared DC input link. Therefore, the four legs can output identical voltages without using a typical DC flying capacitor. The necessity of multiple input voltage sources is, therefore, also eliminated. Measurement demonstrates that the proposed method effectively reduces radiated harmonic EMI by up to 14 dB. Full article

Mitochondria govern energy transfer, redox balance, and cell fate. Tryptophan catabolism generates kynurenines (KYNs) that can tune mitochondrial function, with growing evidence that G protein-coupled receptor 35 (GPR35), aryl hydrocarbon receptor (AhR), and N-methyl-D-aspartate receptors (NMDA receptors) link extracellular cues to adenosine 5 prime triphosphate (ATP) maintenance, calcium (Ca²⁺) handling, mitophagy, and inflammasome control. In parallel, quinolinic acid (QA)-driven de novo nicotinamide adenine dinucleotide (NAD⁺) synthesis connects KYN flux to tricarboxylic acid (TCA) cycle activity and sirtuin programs across tissues. Key gaps remain: receptor pharmacology is rarely integrated with NAD⁺ economics and respiration, and clinical workflows still lack single-run assays that quantify both kynurenine and TCA nodes. We therefore integrate receptor proximal signaling, QA-driven NAD⁺ supply, and unified liquid chromatography–mass spectrometry (LC-MS) measurement into one translational framework spanning kynurenic acid (KYNA), KYN, 3-hydroxykynurenine (3-HK), and QA, using mitochondrial endpoints as the common readout. We synthesize evidence for mitochondrial GPR35 signaling that preserves ATP, AhR programs that tune oxidative defenses and mitophagy, and NMDA receptor antagonism that limits excitotoxic stress. These mechanisms are linked to QA-dependent NAD⁺ biogenesis and alpha ketoglutarate control points, then aligned with chromatography and ionization choices suited to routine LC-MS workflows. This receptor to organelle framework couples KYN flux to respiratory control and provides a practical roadmap for standardized single-run LC-MS panels. It can strengthen target validation in ischemia, neurodegeneration, psychiatry, and oncology while improving biomarker qualification through harmonized analytics and decision-grade readouts. Full article

This study investigates whether the moderate geomagnetic storm of 14 November 2012 was associated with measurable variability in selected power-quality parameters of the Polish National Power System, utilising anonymised, standardised hourly transmission data alongside solar-wind and geomagnetic drivers. Cross-correlation analysis reveals location-dependent, time-lagged couplings, with the strongest correlation, r = 0.74, between a current-harmonic component and the Dst index at a lag of −8 h. The most pronounced anticorrelation, with r = −0.66, occurs between current harmonics and the Ap index at lags of −9 to −11 h during a storm interval that reached $Ds{t}_{min}=-108$ nT. Principal Component Analysis and Hierarchical Agglomerative Clustering distinguish internally driven grid variability from externally driven storm-time signatures, demonstrating that seven principal components capture $89.54\%$ and $86.47\%$ of the variance at the two most responsive locations. These findings indicate that moderate storms can coincide with detectable changes in power-transfer and harmonic-related parameters at specific substations, supporting the need for multi-event studies and physics-based geoelectric or geomagnetically induced current (GIC) modelling to assess operational significance. Overall, this analysis demonstrates that space weather may contribute to observable variability in the Polish power grid. However, further research incorporating additional geomagnetic events, seasonal variability, and geophysical modelling is necessary to fully assess operational impacts and inform potential mitigation strategies. The findings highlight the importance of continued monitoring and interdisciplinary analysis to support long-term resilience planning. Full article