Search Results (69,914)

Reliable short-term hydropower forecasting is essential for dispatch planning and early electricity procurement in snowmelt-influenced power systems. This study develops a leak-free operational forecasting framework using quality-controlled hourly generation and hydro-meteorological records from eight hydropower plants in Kazakhstan. Two tasks are addressed: deterministic multi-step forecasting for D+1–D+7 and uncertainty-aware envelope forecasting for D+8–D+14 using MIN and Q90 targets. The benchmark uses Persistence as the primary baseline, against which RIDGE, SARIMAX, Random Forest, HistGradientBoosting, MLP, and LSTM are compared using Nash–Sutcliffe efficiency (NSE), root mean squared error (RMSE), and mean absolute error (MAE). For D+1–D+7, the results reveal strong cross-station heterogeneity and the expected decline in skill with increasing lead time. In the aggregated comparison, SARIMAX achieves the highest mean NSE at D+1 (0.903), while RIDGE becomes strongest by D+7 (0.625), both outperforming Persistence (0.534 at D+7). At the station level, SARIMAX performs best for Kapch, Kask, Moin, Bukh, and Ustk, RIDGE is best for Shar and Lenin, and LSTM is best for Shulb. The strongest stations, Kapch and Kask, reach mean NSE values of 0.941 and 0.933, respectively, whereas Ustk and Bukh remain the most difficult cases. A central methodological contribution is a flood-sensitive switched hybrid strategy for Ust-Kamenogorsk based on an observed-generation high-flow window selected by a regime-score procedure. This strategy improves robustness at medium lead times: for SARIMAX, NSE increases from 0.587 to 0.739 at D+2 and from 0.161 to 0.559 at D+7, while for RIDGE, NSE increases from 0.549 to 0.701 at D+2 and from 0.109 to 0.435 at D+7, together with substantial RMSE and MAE reductions. For D+8–D+14, envelope forecasting remains informative, but model ranking becomes target-dependent: SARIMAX and RIDGE provide the strongest mean performance for MIN (0.664 and 0.658), whereas LSTM and RIDGE are strongest for Q90 (0.746 and 0.743). Overall, the results show that hydropower forecasting in Kazakhstan is best approached as a station-wise, regime-aware, and horizon-specific problem. Full article

Allelopathy means that one plant produces chemical substances to affect the growth of other plants. Crop rotation is considered as a potential strategy to alleviate the allelopathic inhibition. So, it is important to identify rotation crops with wide availability and low inhibitory effects. In this study, the allelopathic potential of soil extracts was investigated on the germination, seedling growth, biomass, and biochemical parameters (malondialdehyde, photosynthetic pigments, and antioxidant enzyme activities) of five crops, by a series of laboratory experiments. Firstly, both soil water extracts (SWE) and soil ethanol extracts (SEE) exhibited allelopathic inhibition on the seed germination and the root length of all seedlings in a dose-dependent relationship. The SWE significantly promoted the shoot length of bok choy and Chinese lettuce, while the SEE had no significant effect in bok choy. The application of SEE resulted in a significant increase in the dry weight of bok choy and rocket. In contrast, SWE had a negligible effect on bok choy and lettuce. Both of them caused decrease in the dry weight of the other seedlings. Then, the allelopathic synthetic effect index of water/ethanol extracts was chemo-inhibitory, and the inhibitory effect increased with increasing extract concentration. The SWE had the strongest inhibition on rocket and the SEE on lettuce. Both of them had the weakest effect on bok choy. The extracts significantly inhibited the photosynthetic capacity in five crops, manifested as decrease in photosynthetic pigments and dose-dependent effects. The malondialdehyde (MDA) content in all crops increased in a dose-dependent manner, confirming that the extracts caused lipid peroxidation. However, the defense strategies of different crops vary significantly. There is crop with active defense, such as bok choy treated with SWE. It delayed oxidative damage by continuously upregulating the activities of superoxide dismutase (SOD) and catalase (CAT). This is the key physiological mechanism for tolerance. There is also the oxidative stress failure type, as follows: CAT activity of rocket and cabbage increased, but the SOD activity did not increase by SEE. This reveals the physiological essence of their sensitivity—the lack of persistent scavenging ability for reactive oxygen species. Based on the inhibition of peroxidase (POD) and ascorbic acid peroxidase (APX), it is speculated that the extracts may inhibit the hydrogen peroxide scavenging pathway, which centered on the ascorbate–glutathione cycle. It is the fundamental reason why the continuous accumulation of MDA though SOD/CAT is up. This study confirmed the allelopathic effects of the water and ethanol extracts on five vegetable crops, and found that bok choy was less affected by them. The soil extracts affected the growth and development of seedlings by regulating their oxidative metabolism and photosynthetic capacity. These results support recommending pak choi as a rotation crop. This provides crops for subsequent field experiments and a new direction for next-step research on continuous cropping obstacles. Full article

Poplar (Populus) trees are indispensable to various industries and environmental sustainability efforts. They are widely utilized for paper production, timber, and windbreaks, while also playing a significant role in carbon sequestration. Given their economic and ecological importance, the effective management of diseases is crucial. Convolutional Neural Networks (CNNs), renowned for their ability to process visual data, are pivotal in accurately detecting and classifying plant diseases. This study presents a domain-specific dataset of manually collected images of diseased poplar leaves from Uzbekistan and South Korea, ensuring geographic diversity and broader applicability. The dataset includes four disease classes, i.e., “Parsha (Scab),” “Brown spotting,” “White-Gray spotting,” and “Rust,” which represent common afflictions in these regions. To advance research efforts, this dataset will be made publicly accessible, providing a valuable resource for the scientific community. Leveraging the cutting-edge YOLOv9c model, a state-of-the-art CNN architecture, we applied the Histogram Equalization technique as a preprocessing step to enhance the image quality to increase the accuracy of disease detection. This method not only improves the diagnostic performance of the model but also provides a scalable solution for monitoring and managing poplar diseases. By ensuring the health of poplar trees, this approach supports the sustainability of these critical resources. To our knowledge, this is the first publicly available dataset specifically focused on diseased poplar leaves, making it a significant contribution to global research efforts. It offers an invaluable resource for researchers and practitioners, enabling further advancements in early disease detection and sustainable forestry management. Full article

Aesthetic medicine is shifting from symptomatic correction to biological structural restoration. Regenerative aesthetics represents a frontier in dermatology, focusing on the restoration of the skin microenvironment to enhance cellular vitality and tissue resilience. Central to this approach is the concept of “skin bed preparation”, a strategic priming phase designed to optimize the physiological terrain before the delivery of advanced aesthetic interventions. This review explores the molecular and cellular mechanisms by which skin bed preparation modulates the extracellular matrix (ECM) and the dermal niche to maximize the efficacy of subsequent treatments and promote long-term skin longevity. Evidence suggests that biostimulatory priming utilizing senolytics, senomorphics, mitochondrial, and/or epigenetic rejuvenators rehabilitates the fibroblast–collagen interactome. By reducing oxidative stress and chronic low-grade inflammation, these preparatory steps transition the skin from a catabolic to an anabolic state. This metabolic reset ensures that subsequent procedures, such as laser therapy, injectable fillers, encounter a responsive cellular environment, resulting in superior collagen induction and prolonged clinical outcomes. Optimizing the skin microenvironment via regenerative aesthetics is not merely an adjunctive step but a fundamental requirement for therapeutic success. Integrating skin bed preparation into clinical protocols provides a synergistic framework that enhances immediate procedural results while addressing the underlying hallmarks of skin aging, ultimately redefining the trajectory of skin health and longevity. Full article

Distributed economic dispatch in AC distribution systems relies heavily on communication networks and is therefore vulnerable to denial-of-service (DoS) attacks. To address this issue, this paper proposes a resilient event-triggered distributed economic dispatch control strategy. Two typical DoS attack scenarios, namely communication-link blocking and node isolation, are first modeled, and an event-triggered distributed economic dispatch controller is then developed to maintain incremental cost consensus and system power balance while reducing communication overhead. Based on Lyapunov stability theory and a linear matrix inequality approach, sufficient conditions for the asymptotic stability of the closed-loop system are derived, tolerable bounds on the frequency and duration of DoS attacks are established, and the absence of Zeno behavior is proved. Simulations on the IEEE 33-bus AC distribution system show that, under load disturbances, dispatch-command variations, and DoS attacks, the proposed strategy can maintain stable system operation, restore dispatch performance after attacks, and reduce communication overhead by 91.86% compared with a fixed-step periodic updating baseline. These results demonstrate the effectiveness and resilience of the proposed method for distributed economic dispatch in AC distribution systems under DoS attacks. Full article

In this study, phenol adsorption from aqueous solutions was investigated using a carbonized adsorbent derived from a 1:1:1 mixture of banana, carrot, and potato peels, representing a major fraction of municipal bio-waste in Serbia. The material (CARB_BCP) was characterized by pH_pzc, SEM, FTIR, and BET analyses. The results indicated a highly porous structure with developed micro- and mesoporosity and a high specific surface area (S_BET = 483 m²/g). FTIR confirmed the formation of a stable aromatic carbon structure, while the high pH_pzc value (10.55) suggested a limited role of electrostatic interactions. Adsorption experiments performed at an initial phenol concentration of 1858 mg/L, room temperature, and an adsorbent dose of 0.1 g achieved a removal efficiency of 20.5%. The Langmuir model provided the best fit, indicating monolayer adsorption, with good agreement between theoretical (≈187 mg/g) and experimental (≈190 mg/g) capacities. Kinetic analysis followed the pseudo-second-order model, suggesting chemisorption as the rate-controlling step. The adsorption mechanism was mainly governed by π–π interactions, hydrophobic effects, and hydrogen bonding. These results demonstrate that CARB_BCP, derived from biodegradable waste, is a promising low-cost adsorbent for wastewater treatment. Full article

Transfer accuracy is widely used to evaluate orthodontic indirect bonding workflows, particularly in the context of digital CAD/CAM planning and three-dimensional bracket positioning. However, substantial heterogeneity in its definition, measurement, and reporting may limit comparability and clinical interpretability across systematic reviews. This methodological umbrella review examined how transfer accuracy is operationalized as an outcome construct, with specific focus on conceptual definitions, dimensional frameworks, reference systems, measurement pipelines, and interpretative strategies rather than pooled quantitative deviation estimates. A systematic search of major biomedical databases was conducted to identify systematic reviews evaluating transfer accuracy in orthodontic indirect bonding. Data extraction was performed independently by two reviewers using a predefined methodological mapping framework, and methodological quality was assessed with AMSTAR-2. Four systematic reviews met the inclusion criteria. Across reviews, transfer accuracy was operationalized through heterogeneous linear and angular geometric deviation metrics derived from planned–achieved bracket position comparisons, without use of a standardized composite accuracy indicator. Nevertheless, substantial heterogeneity was found in outcome definitions, dimensional architectures, reference system selection, and analytical workflows, resulting in structurally non-equivalent representations of transfer accuracy and limiting cross-review comparability. Within the included systematic reviews, transfer accuracy functioned primarily as a workflow-dependent geometric measurement construct rather than as an outcome systematically operationalized within clinically validated frameworks. We recommend standardized construct definitions, mandatory reporting of reference systems and registration algorithms, routine uncertainty quantification, and harmonized dimensional frameworks as essential steps toward valid evidence synthesis, reproducible digital orthodontic workflows, and clinically interpretable transfer accuracy measurement. Full article

We provide a simple algorithm for calculating all generators of power integral bases in pure quintic fields. This procedure involves the usual standard elements like Baker’s method and LLL reduction. The main purpose of this paper is to introduce a new idea to considerably diminish the number of small exponents to be considered after the reduction step. This new idea allows us to test all remaining small exponents within a few minutes, using an appropriate sieve method, which turns out to be surprisingly fast. This idea will be applicable in many similar cases. Full article

Urban planning increasingly depends on methods capable of capturing citizen perspectives in forms that are both inclusive and analytically useful for decision-making. Conventional participation mechanisms, such as public meetings, paper questionnaires, and online platforms, often suffer from low reach, strong self-selection effects, and weak suitability for structured comparative analysis. This paper presents XRCity, a decision support system that combines extended reality, conversational artificial intelligence, and a planner-side backend to support participatory urban planning in public spaces. The system is centered on Olivia, a life-sized virtual assistant deployed on outdoor interactive screens, and on a backend environment that enables planners to prepare knowledge resources, configure interaction scripts, validate conversational behavior, process transcripts, and analyze elicited opinions. The contribution of the paper is not just the presentation of an XR interface, but the description and validation of a complete decision-support pipeline that connects campaign design, citizen interaction, opinion structuring, and planner-side analytics. The system was validated through real-world deployment in Torres Vedras, Portugal. Across more than 250 interactions and over 740 min of conversation, 191 usable sessions were analyzed, showing an average of 6.7 messages per user and 2.8 min per interaction. Of these sessions, 14.7% produced at least one structured response to an urban planning question, exceeding the project target of 10%. These results indicate the operational feasibility of using public-space conversational XR to elicit analyzable planning input, while a formal validation of the opinion-matching step remains future work. Full article

The expansion of accessible, fine-grained city data has significantly increased opportunities for evidence-based and informed policy-making. Despite this evolution, extracting actionable insights from heterogeneous data sources and effectively communicating findings remain persistent challenges. Most existing visualisation approaches and research prioritise technical implementation by focusing on how to visualise, often neglecting the importance of policy-driven visualisation questions and data contexts. This led to flawed analyses, particularly in complex domains such as smart cities and urban policy-making using digital twins. This article presents a novel, practical, step-by-step policy visualisation methodology grounded in empirical smart city research, shifting the emphasis toward policy-element-based questions informed by data-informed evidence. The methodology was successfully applied, tested, and adapted, resulting in an implementable, structured, and integrative approach that aligns with policymakers’ established policy design, implementation, and evaluation cycles. Through this approach, 20 user-driven smart city policy visualisations were operationalised and implemented in strategic policy decision-making contexts across smart city domains, including mobility, spatial planning, and environment. The results demonstrate how dashboards, algorithmic simulations, and digital twins visualisations can be systematically deployed to support evidence-informed decision-making. Full article

The radial structure and azimuthal asymmetry of tropical cyclone (TC) eyewall winds are critical for intensity change and wind-related hazards, yet they remain difficult to characterize using conventional observations. Using multi-platform C-band synthetic aperture radar (SAR) wind fields and collocated Stepped Frequency Microwave Radiometer (SFMR) wind speed and rain-rate observations, this study examined TC inner-core structure, eyewall asymmetry, and rainfall-dependent wind retrieval uncertainty for 51 TCs and 130 SAR scenes. The TC inner-core structure was characterized using a best-track-constrained center refinement and quality control procedure, in which the storm center was refined from the minimum of a Gaussian-smoothed SAR wind field and scenes were screened by eye/annulus sampling, eye–eyewall contrast, and annular wind organization. Of the 130 SAR scenes, 53 were retained for refined-center evaluation, and the 32 QC-passed scenes were used for the primary storm-centered structural analysis. The RMW showed a weak tendency to decrease with an increasing SAR-derived maximum azimuthal-mean wind speed, and the normalized wavenumber-1 asymmetry at the RMW decreased in stronger storms. Under strict temporal collocation ($\left|\Delta t\right|\le 30$ min), the SAR–SFMR comparison achieved an RMSE of 4.22 m s⁻¹, a bias of −1.61 m s⁻¹, $R^2$ = 0.82, and a regression slope of 0.90. Rainfall-related SAR–SFMR mismatch was most evident around the eyewall and adjacent outer-eyewall region, indicating the need to consider center uncertainty, scene suitability, temporal collocation, and rain-sensitive retrieval effects when interpreting SAR-derived TC inner-core structure. Full article

We characterized long-term, objectively measured physical activity trajectories surrounding total knee arthroplasty (TKA) and total hip arthroplasty (THA) and examined factors associated with wearable-derived physical activity recovery. In this observational study within the All of Us Research Program, linked electronic health records and Fitbit step count data spanning the two years before and the two years after surgery were analyzed using piecewise linear mixed-effects models to characterize preoperative and postoperative trajectories. Recovery of physical activity was defined relative to two preoperative baselines—activity measured immediately before surgery and a more remote baseline approximating longer-term habitual activity—and associated factors were examined using Cox proportional hazards models. Among 238 participants (147 TKA, 91 THA; mean age 64.9 [SD 8.3] years), both procedures showed progressive preoperative decline, with accelerated decline beginning earlier in TKA than in THA. Postoperative recovery followed a staged pattern, with rapid early improvement, slower intermediate gains, and later stabilization. Recovery to the immediate preoperative baseline occurred earlier than recovery to the remote baseline. Higher activity during the 4 weeks before surgery was associated with a greater likelihood of recovery to the remote baseline. These findings support long-term wearable monitoring as a complementary measure of physical activity recovery after arthroplasty. Full article

Phase-modulated continuous wave (PMCW) has emerged as a promising waveform candidate for next-generation integrated sensing and communication systems due to its favorable sensing performance and multiplexing capability. In multiple-input and multiple-output (MIMO) PMCW systems, fast-time code-division multiplexing enables simultaneous transmission from multiple transmitters but causes inter-transmitter code interference due to non-ideal cross-correlation properties. The interference is observed to manifest as a low-rank component in the range–Doppler domain while target echoes appear as sparse components. This structural distinction motivates the use of robust principal component analysis (RPCA) for interference mitigation. In practice, conventional RPCA incurs high computational complexity due to the singular value decomposition (SVD) required at every iteration. To address this limitation, we propose an unfolded RPCA network in which each iterative step is mapped to a network stage and SVD is replaced by a factorized low-rank approximation. The proposed network also incorporates stage-wise learnable parameters for adaptive interference mitigation in MIMO PMCW systems. Simulation results demonstrate that the proposed method achieves interference mitigation performance comparable to conventional RPCA with 21.2 times lower inference latency. These results confirm the effectiveness and computational efficiency of the proposed method for real-time mitigation of inter-transmitter code interference in MIMO PMCW systems. Full article

This paper presents a model-based control strategy for a power factor correction system that employs a high conversion-ratio DC–DC converter. The proposed system consists of two stages. In the first stage, a full-bridge diode rectifier is connected to the grid through a passive filter to improve the quality of the injected current. Two passive AC input filters, namely L and $LCL$ configurations, are evaluated to analyze their impact on grid current quality and overall system performance. The second stage is a high-step-up DC–DC converter based on the switched-inductor technique, which provides a high voltage conversion ratio. A model-based approach is employed to derive the control design from the averaged system model. The resulting control structure consists of a current tracking loop and a voltage regulation loop. A proportional-resonant controller is used to ensure current tracking and achieve a near-unity power factor, while a proportional-integral controller regulates the output voltage. Experimental validation is carried out using a low-power laboratory-scale prototype to assess the effectiveness of the proposed approach. The results demonstrate adequate current tracking and satisfactory dynamic performance within the tested operating conditions. Full article

The modal behaviour of the wooden bridge over the Rhine described by Julius Cæsar in the De Bello Gallico is analysed by a simple analytical model, i.e., a Kirchhoff–Love (KL) plate. The overall structure is indeed modelled as a thin plate, representing the walking surface, resting on elastic supports that approximate the compliance of the underlying structure. Firstly, these elastic constraints are represented by linear springs; in a refined step, beam elements with equivalent stiffness and mass are adopted. The system complexity arises from the consequent non-trivial boundary conditions and is tackled by selecting suitable auxiliary functions to operate with discretised equations of motion, in a Galërkin-like approach. MATLAB helped to develop in-house scripts capable of reconstructing the flexural behaviour as the governing parameters vary, without repeated experimental tests. The analytical results are compared with theoretical predictions and between the two assumed elastic supports, allowing verification of model consistency and explanation of differences in the bridge behaviour. The ease of implementation of these codes also enables the evaluation of the structural potential of historical constructions, the investigation of modular characteristics and connections between subcomponents, and the assessment of the effects of external loads. The study of historical structure dynamics is thus relevant not only for reconstruction, but also for modern mechanical design, with potential applications in civil, mechanical, materials, and naval engineering. Full article