Search Results (77)

Accurate power prediction is essential for assessing wind turbine performance under real-world operating conditions and for supporting condition monitoring and maintenance planning using SCADA data. Most existing approaches rely directly on raw SCADA signals, which may limit their ability to capture complex spatiotemporal dependencies among operational variables. To address this limitation, this paper proposes a novel SCADA-driven power prediction framework that transforms selected SCADA variables into multi-channel grayscale images and leverages an optimized LeNet-5–LSTM hybrid neural network for active and reactive power prediction. First, the SCADA dataset is analyzed to identify the most influential variables affecting power output. Six key variables are then selected, segmented, and encoded as 2D grayscale images, enabling the model to learn richer feature representations compared to conventional raw SCADA data-based methods. The proposed network combines convolutional layers for spatial feature extraction from SCADA data-based grayscale images with LSTM layers to capture temporal dependencies. Model training incorporates a customized loss function that integrates both data-driven supervision and physics-based constraints. The model is trained using 70% of the image-based dataset, with five independent runs to ensure robustness and reproducibility, while the remaining 30% is used for testing. The proposed approach is validated using SCADA data from three real-world cases: (i) a 2 MW Siemens wind turbine in Poland, (ii) a Vestas V52 wind turbine in Ireland, and (iii) the La Haute Borne wind farm in France, consisting of four wind turbines. The results demonstrate that the SCADA-based image representation enables the proposed LeNet-5–LSTM model to effectively learn discriminative feature patterns and achieve accurate active and reactive power predictions across different turbine types and operating conditions. Full article

In this study, we investigated the optimization of a wind farm layout on complex mountainous terrain in Yeongdeok, South Korea, with varying hub heights. Specifically, the energy performance of mixing two commonly used commercial models with different heights, i.e., Vestas V82 and V162, was evaluated. The impact of site scale in terms of farm area (ranging from 1 to 9 km²) on power generation and wake effects was also determined. The results obtained using WindPRO and the Wind Atlas Analysis and Application Program demonstrated that, with increased wind farm area, the annual energy production increased while wake losses decreased. Compared with the case employing hubs with a uniform height, the mixed-height case showed a decrease in wake losses of up to 1.7% while maintaining comparable AEP. The findings of this study demonstrate that combining turbines of different hub heights provides more energy-efficient layouts, even in complex mountainous terrains. Insights from these findings can be further utilized to expand wind power in complex terrain in other countries. Full article

Southern Patagonia in Argentina possesses a world-class wind resource; however, its remote location challenges long-term monitoring. This study presents the first long-term Doppler LiDAR-based wind characterization in the region, analyzing six months of high-resolution data at a 100 m hub height. Power for the LiDAR is provided by a hybrid system combining photovoltaic (PV) and grid sources, with remote monitoring. The results reveal two distinct seasonal regimes identified through a multi-model statistical framework (Weibull, Lognormal, and non-parametric Kernel Density Estimation: a high-energy summer with concentrated westerly flows and pronounced diurnal cycles (Weibull scale parameter A ≈ 11.9 m/s), and a more stable autumn with a broad wind direction spectrum (shape parameter k ≈ 2.86). Energy output, simulated using Windographer v5.3.12 (Academic License) for a Vestas V117-3.3 MW turbine, shows close alignment (~15% difference) with the operational Bicentenario I & II wind farm (Jaramillo, AR), validating the site’s wind energy potential. This study confirms the viability of utility-scale wind power generation in Southern Patagonia and establishes Doppler LiDAR as a reliable tool for high-resolution wind resource assessment in remote, high-wind environments. Full article

Background/Objectives: Non-muscle invasive bladder cancer (NMIBC) management is increasingly complex due to conflicting guideline-based risk classifications, ongoing Bacillus Calmette–Guérin (BCG) shortages, and emerging alternative therapies. Computational Histology Artificial Intelligence (CHAI) tests are clinically available, providing insights from tumor specimens including predicting BCG responsiveness and individualized recurrence and progression risks, which may support precision medicine. This technology features biomarkers purpose-built for clinically unmet needs and has practical advantages including a fast turnaround time and no need for consumption of tissue or other specimens. We assessed the impact of such tests on physicians’ decision-making in routine, real-world NMIBC management. Methods: Physicians at six centers ordered CHAI tests (Vesta Bladder) at their discretion during routine NMIBC care. Tumor specimens were processed by a CLIA/CAP-accredited laboratory (Valar Labs, Houston, TX, USA) where H&E-stained slides were analyzed with the CHAI assay to extract histomorphic features of the tumor and microenvironment, which were algorithmically assessed to generate biomarker test results. For each case from 24 June 2024 to 18 July 2025, ordering physicians were surveyed to assess pre- and post-test management plans and post-test result usefulness. Results: Among 105 high-grade NMIBC cases with complete survey results available, primary management changed in 67% (70/105). Changes included modality shifts (n = 7; three to radical cystectomy with high prognostic risk scores; four avoiding cystectomy with low scores) and intravesical agent change (n = 63). Surveillance was intensified in 7%, predominantly among those with ≥90th percentile risk scores. The therapeutic agent changed in 80% (40/50) of predictive biomarker-present (indicative of poor response to BCG) tumors vs. 48% (23/48) of biomarker-absent tumors. Conclusions: In two thirds of cases, CHAI biomarker results influenced clinical decision-making during routine care. BCG predictive biomarker results frequently guided intravesical agent selection. These results have implications for optimizing clinical outcomes, especially in the setting of ongoing BCG shortages. Prognostic risk stratification results guided treatment escalation vs. de-escalation, including surveillance intensification and surgical vs. bladder-sparing decisions. CHAI biomarkers are currently utilized in routine clinical care and informing precision NMIBC management. Full article

This study presents the first comprehensive techno-economic assessment of wind-based green hydrogen production across Senegal, a country highly dependent on fossil fuel imports. Using a novel integrated approach combining 30 years of ERA5 reanalysis data (1993–2023), turbine performance modeling and electrolyzer comparison, it fills an important gap for renewable hydrogen development in West Africa. Wind resources were analyzed at multiple altitudes, revealing strong potential in both coastal and northeastern regions, particularly during the dry season, with higher wind speeds at higher turbine heights. Four turbines (Vestas_150, Goldwind_155, Vestas_126 and Nordex_N100) and two electrolyzer types (alkaline and PEM) were evaluated. The alkaline system performed best. Vestas_150 and Goldwind_155 achieved the highest hydrogen yields of 241 and 183 tons/year and CO₂ reductions of 2951 and 2241 tons/year, generating carbon credits of 0.118 M$ and 0.089 M$, respectively. Their levelized cost of electricity remained low (0.042 and 0.039 $/kWh), while smaller turbines showed higher costs. Vestas_150 also had the shortest payback period of 2.16 years, making it the most competitive option. Sensitivity analyses showed that longer system lifespans and high-performance turbines significantly reduce the levelized cost of hydrogen. Priority investment zones include Saint-Louis, Matam, Louga and Tambacounda, with levelized cost of hydrogen values as low as 3.4 $/kg. Full article

This paper presents a comprehensive techno-economic and environmental assessment of offshore wind-powered green hydrogen production systems in Egypt and Oman, two strategically located countries within the MENA region with substantial renewable energy potential. A 120 MW offshore wind farm configuration, employing Vestas 8 MW turbines, was simulated for each country and coupled with an electrolyzer system to evaluate electricity generation, hydrogen yield, system efficiency, and cost-effectiveness. The analysis shows that both Egypt and Oman achieve high annual capacity factors (51% and 49.7%, respectively), resulting in annual green hydrogen production of 11.5 million kg and 11.2 million kg. Despite Egypt’s more stable year-round wind profile and slightly lower Levelized Cost of Hydrogen (LCOH: $3.09/kg vs. $3.17/kg), Oman’s seasonal monsoon (Khareef) offers exceptional summer productivity, with peak capacity factors exceeding 74%. A dual-framework environmental assessment was conducted to quantify CO₂ emissions mitigation. In the first scenario, based on grid substitution, the systems could avoid up to 240,000 and 256,000 tonnes of CO₂ annually in Egypt and Oman, respectively. The second scenario evaluates emissions avoided by replacing conventional gray hydrogen, yielding reductions of 126,500 tCO₂/year and 123,200 tCO₂/year, respectively. These results highlight the flexibility of offshore hydrogen systems in addressing both electricity-sector and hydrogen-market decarbonization goals. Additionally, sensitivity analysis shows that increasing turbine hub height yields only marginal wind speed and cost improvements, suggesting limited economic justification under current site conditions. Overall, the study positions Egypt as a stable, year-round hydrogen producer and Oman as a high-output seasonal exporter, supporting a complementary regional strategy for green hydrogen leadership. Full article

Background: Diffusion-prepared pseudo-continuous arterial spin labelling (DP-pCASL) can quantify the cerebral blood flow (CBF) and the water exchange rate (kw) across the blood–brain barrier (BBB). Little is known about the BBB water exchange in major depressive disorder (MDD). Objective: We aimed to explore the associations between kw, CBF, peripheral inflammation, and MDD. Methods: Using DP-pCASL, we measured the global and selected regional kw and CBF together with blood plasma levels of lipopolysaccharide (LPS) and inflammatory cytokines in 85 patients with MDD and 51 controls. Results: The global CBF was significantly lower in MDD patients compared with controls (means of 51 and 57 mL/100 g/min, respectively; p = 0.006), with similar reductions found in the dorsolateral and ventromedial prefrontal, anterior, and posterior cingulate regions, while no differences were found in the amygdala and the isthmic cingulate. There were no differences in the kw between groups globally (means of 128 min⁻¹; p = 0.958) and in the studied regions. Among MDD patients, the kw was weakly correlated with the MADRS scores (r = 0.231, p = 0.034). There were no associations between kw, CBF, and inflammatory markers (LPS, IL-6, IL-10, TNF-α, IFN-γ). Logistic regression showed that a combination of the regional CBF < 59.22 mL/100 g/min together with LPS > 143.58 pg/mL and/or IL-10 > 0 pg/mL distinguished MDD patients from controls with a moderate accuracy of 83.1% (sensitivity = 94.1%, specificity = 64.7%, AUC = 0.876). Conclusions: DP-pCASL imaging confirmed previous findings of reduced CBF in MDD, which together with LPS and IL-10 concentrations were independent significant predictors of MDD. However, no changes in the BBB water exchange were found, suggesting that it may not be as significant as CBF in MDD pathophysiology. Full article

The application of alizarin dye for the marking of fish is a widely adopted practice in post-stocking monitoring programmes. Nevertheless, concerns regarding the welfare implications of alizarin staining persist. The present study conclusively demonstrated that ARS dye exerts instantaneous and protracted deleterious effects on the physiological parameters (gill ventilation frequency, homeostasis in the gut microbiota, total number of erythrocytes and leukocytes) and body fitness (total length, weight and Fulton’s condition factor) of S. trutta fry. The validity of the dye-marked fish stocking effectiveness studies is called into question by these findings. Full article

In this present study, the efficiency of ultrasound-assisted extraction (UAE) in increasing the yields of extraction of starch and polyphenols from Canna indica L. (Canna) rhizomes were analyzed, along with its influence on the physiochemical properties of the extracted compounds. Extraction parameters (temperature, time, and solid-to-liquid ratio) were optimized through Box–Behnken response surface design (BBD). The physiochemical and functional properties of starch and polyphenols were investigated through scanning electron microscopy (SEM), the swelling and solubility index, oil and water absorption index, total polyphenol yield, and antioxidant activity assays (DPPH and ORAC). The starch yield obtained from Canna at the optimum extraction conditions (temperature 40 °C, time 10 min, and solid-to-liquid ratio 1:30 g/mL) was 19.81%. The obtained starch yield was found to be significantly higher than the yield attained through the conventional extraction method without adverse changes in the physicochemical and functional properties. The total polyphenol extraction yield from the Canna rhizome, through UAE, was significantly higher (1061.72 mg GAE/100 g) than that of the conventional method. The antioxidant activity of bioactive compounds was proportional to the attained polyphenol yield. Our results suggest that UAE optimized conditions efficiently and improved Canna starch and polyphenol extraction yields while preserving their functional properties. Full article

This study introduces a hybrid siting approach for Offshore Wind Farms by combining bottom-fixed and floating wind turbines to address seabed variability in the Mediterranean region. Using Heraklion Bay, Crete, as a case study, a multi-step methodology was adopted, integrating GIS tools, micro-siting analysis, and WAsP simulations to estimate the energy output of three layout scenarios. A comprehensive energy and economic assessment was performed, including key metrics such as Net Present Value, Internal Rate of Return, Payback Period and Levelised Cost of Energy. Scenario 2, which featured a mixed deployment of Vestas and Siemens Gamesa turbines, proved to be the most financially attractive option, yielding the highest Net Present Value (€167 million) and shortest Payback Period. Sensitivity analysis under a 20% reduction in wind resources confirmed the robustness of this scenario. Results demonstrate that hybrid configurations offer a flexible and scalable solution, particularly in island regions with varied bathymetry and seasonal energy demands. The findings highlight the potential of hybrid offshore systems to accelerate energy transitions, optimise spatial utilisation, and improve cost-effectiveness in medium-depth seas. Full article

Krenitsyn Peak is one of the two active volcanoes on Onekotan Island (Greater Kuril Ridge). The inaccessibility of the island, along with the volcano being situated within a sizeable (7 km in diameter) and cold (3.7 °C) caldera lake, has led to minimal research on the area. We present the first detailed characterization of the rocks from the only historical eruption of Krenitsyn Peak (November 1952) and a brief description of the ancient lava and pyroclastic density current (PDC) deposits that make up the building of the volcano. The 1952 eruptive products are represented by two-pyroxene andesites (59.2–63.3 wt.% SiO₂), and the older lava and pyroclastic flow rocks consist of two-pyroxene andesites and dacites (62–67.6 wt.% SiO₂). Almost all samples belong to the calc-alkaline, medium-K, and medium-Fe series, and the pumiceous lapilli from the 1952 eruption fall into the low-Fe series. The minerals exhibit signs of magma mingling, including relic high-Ca (up to An₉₂) plagioclase cores with signs of dissolution and recrystallization, and oscillatory-zoned pyroxene. Full article

The specialty background of intensive physicians managing severely injured patients varies internationally, with trauma ICUs often led by either trauma surgeons or anesthesiologists, both of whom receive additional intensive care training. Whether physician specialty affects outcomes remains uncertain. We conducted a retrospective single-center cohort study of patients aged ≥ 16 years with an Injury Severity Score (ISS) ≥ 16 admitted to a level I trauma center between January 2005 and December 2022. Patients were treated either in a trauma surgery ICU (T-ICU) or an anesthesiology ICU (A-ICU). Briefly, 1:1 matching was conducted based on demographic and injury-related variables, with the primary outcome being in-hospital mortality and secondary outcomes including transfusion requirements, duration of mechanical ventilation, ICU and hospital length of stay, and Glasgow Outcome Scale (GOS) at discharge. Among the 1015 eligible patients (T-ICU: n = 920; A-ICU: n = 95), 52 patients (26 per group) were successfully matched with comparable baseline characteristics. No significant differences were observed in mortality, GOS, transfusion requirements, ventilation duration, or ICU/hospital length of stay. These findings suggest that, when both are led by certified intensive care specialists, trauma surgery- and anesthesiology-based ICUs achieve comparable outcomes, supporting multidisciplinary models while highlighting the need for larger multicenter studies. Full article

Fermenting fruit and vegetable juices with probiotic bacteria is becoming a popular way to create functional drinks, offering an alternative to traditional dairy-based probiotic products. These plant-based juices are naturally rich in nutrients that help support the growth and activity of various probiotic strains. They also meet the rising demand for lactose-free, vegan, and clean-label options. This review looks at the key microbiological, nutritional, and sensory aspects of probiotic fermentation in juice. Common probiotic groups like Lactobacillus, Bifidobacterium, Lactococcus, Bacillus, and Streptococcus show different abilities to adapt to juice environments, affecting properties such as antioxidant levels, shelf life, and taste. The review also explores how factors like pH, sugar levels, heating, and storage can influence fermentation results. New non-thermal processing methods that help maintain probiotic survival are also discussed. Since fermented juices can sometimes develop off-flavors, this paper looks at ways to improve their taste and overall consumer appeal. Finally, future directions are suggested, including personalized nutrition, synbiotic products, and advanced encapsulation technologies. Overall, probiotic fermentation of fruit and vegetable juices shows strong potential for developing a new generation of healthy and appealing functional foods. Full article

Passive Microwave Imagers (PMWIs) aboard meteorological satellites have been instrumental in advancing the understanding of Earth’s atmospheric and surface processes, providing invaluable data for weather forecasting, climate monitoring, and environmental research. This review examines the relevance, applications, and benefits of PMWI data, focusing on their practical use and benefits to society rather than the specific techniques or algorithms involved in data processing. Specifically, it assesses the impact of PMWI data on Tropical Cyclone (TC) intensity and structure, global precipitation and extreme events, flood prediction, the effectiveness of tropical storm and hurricane watches, fire severity and carbon emissions, weather forecasting, and drought mitigation. Additionally, it highlights the importance of PMWIs in hydrometeorological and real-time applications, emphasizing their current usage and potential for improvement. Key recommendations from users include expanding satellite networks for more frequent global coverage, reducing data latency, and enhancing resolution to improve forecasting accuracy. Despite the notable benefits, challenges remain, such as a lack of direct research linking PMWI data to broader societal outcomes, the time-intensive process of correlating PMWI use with measurable societal impacts, and the indirect links between PMWI and improved weather forecasting and disaster management. This study provides insights into the effectiveness and limitations of PMWI data, stressing the importance of continued research and development to maximize their contribution to disaster preparedness, climate resilience, and global weather forecasting. Full article

Flexible wearable electronic devices have found widespread applications in health monitoring and human–machine interaction. Piezoelectric sensors, capable of converting mechanical stress into electrical signals, serve as critical components in these systems. In this study, we enhanced the piezoelectric performance of PVDF-based composite materials through MoS₂ incorporation. Experimental results demonstrated that MoS₂ addition effectively increased the β-phase content in PVDF, achieving a maximum value of 70.0% at an optimal MoS₂ concentration of 0.75 wt%. Density functional theory (DFT) calculations revealed that while β-phase PVDF possesses slightly higher energy than other phases, it exhibits stronger adsorption interactions and enhanced charge transfer with MoS₂, thereby promoting β-phase formation. The fabricated MoS₂/PVDF composite nanofiber film maintained stable voltage output under repeated mechanical stress through 2000 operational cycles. When implemented as a body-mounted sensor, the composite material demonstrated exceptional responsiveness to human motions, confirming its practical potential for wearable electronics applications. Full article