Search Results (1,325)

Phenotypic plasticity is a key mechanism by which crops adjust to fluctuating environmental conditions, yet its genetic basis under drought remains poorly characterized in barley (Hordeum vulgare). We hypothesized that phenotypic plasticity under drought is controlled by a distinct, trait-specific genetic architecture that can be detected using complementary plasticity metrics and genome-wide association studies (GWAS). Here, we examined data from 1277 spring barley genotypes grown under well-watered and water-limited conditions to quantify plastic responses across two developmental traits (i.e., heading time, and maturity) and seven productivity-related traits (i.e., total dry matter, plant grain yield, grain number, grain weight, harvest index, vegetative dry weight, and grain-filling period). The experimental design, based on contrasting water regimes across a large diversity panel, allowed robust assessment of genotype-by-environment interactions. We combined five complementary plasticity estimators with four independent GWAS approaches to resolve the genomic architecture underlying trait-specific plasticity. Environmental effects dominated variation in yield-related traits, whereas developmental traits remained more genetically determined. The different plasticity metrics captured distinct but partially overlapping response dimensions, and their integration greatly increased the robustness of association signals. A total of 239 high-confidence SNPs obtained for top traits, those associated across metrics and methods, were enriched in coding regions and mapped to genes involved in osmoregulation, carbohydrate metabolism, hormonal pathways, and ion transport. A total of 27 high-confidence SNPs were located in coding regions, showing genotype-specific differences in the magnitude and even direction of phenotypic plasticity. These loci exhibited opposite allelic effects across water regimes, consistent with context-dependent antagonistic pleiotropy. The fact that candidate alleles for the plastic response modulate environmental sensitivity differently highlights that drought resilience arises from environment-contingent genetic architectures. Overall, these results provide a comprehensive framework for dissecting plasticity and identify concrete genomic targets for indirect selection targeting crop resilience with improved performance under increasingly variable water availability. Full article

Background: Tuberculosis (TB) is a significant global health issue, particularly in resource-limited regions where radiological expertise is constrained. This project aims to develop a scalable deep learning system that safeguards privacy and achieves high accuracy in the early identification of tuberculosis using chest X-ray images. The objective is to implement federated learning with an adaptive-weighted ensemble optimised by a Genetic Algorithm (GA) to address the challenges of centralised training and single-model approaches. Method: We developed an ensemble learning method that combines multiple locally trained models to improve diagnostic consistency and reduce individual-model bias. An optimisation system that autonomously selected the optimal ensemble weights determined each model’s contribution to the final decision. A controlled augmentation process was employed to enhance the model’s robustness and reduce the likelihood of overfitting by introducing realistic alterations to appearance, geometry, and acquisition conditions. Federated learning facilitated collaboration among universities for training while ensuring data privacy was maintained during the establishment of the optimal ensemble at each location. In this system, just model parameters were transmitted, excluding patient photographs. This enabled the secure amalgamation of global data without revealing sensitive clinical information. Standard diagnostic metrics, including accuracy, sensitivity, precision, F1 score, AUC, and confusion matrices, were employed to evaluate the model’s performance. Results: The proposed federated, GA-optimized ensemble demonstrated superior performance compared with individual models and fixed-weight ensembles. The system achieved 98% accuracy, 97% F1 score, and 0.999 AUC, indicating highly reliable discrimination between TB-positive and typical cases. Federated learning preserved model robustness across heterogeneous data sources, while ensuring complete patient privacy. Conclusions: The proposed federated, GA-optimized ensemble achieves highly accurate and robust early tuberculosis detection while preserving patient privacy across distributed clinical sites. This scalable framework demonstrates strong potential for reliable AI-assisted TB screening in resource-limited healthcare settings. Full article

The three key design criteria for nearly zero-energy buildings (nZEBs) and climate-neutral buildings are minimizing energy use, ensuring high occupant comfort, and reducing environmental impact. Thermal comfort is one of the main components of indoor environmental quality (IEQ), strongly affecting occupants’ health, well-being, and productivity. As energy-efficiency requirements become more demanding, the appropriate selection of heating systems, their automated control, and the management of solar heat gains are becoming increasingly important. This study investigates the influence of two low-temperature radiant heating systems—underfloor and wall-mounted—and the use of Venetian blinds on perceived thermal comfort in a highly glazed public nZEB building located in a densely built urban area within a temperate climate zone. The assessment was based on the PMV (Predicted Mean Vote) index, commonly used in IEQ research. The results show that both heating systems maintained indoor conditions corresponding to comfort or slight thermal stress under steady state operation. However, during periods of strong solar exposure in the room without blinds, PMV values exceeded 2.0, indicating substantial heat stress. In contrast, external Venetian blinds significantly stabilized the indoor microclimate—reducing PMV peaks by an average of 50.2% and lowering the number of discomfort hours by 94.9%—demonstrating the crucial role of solar protection in highly glazed spaces. No significant whole-body PMV differences were found between underfloor and wall heating. Overall, the findings provide practical insights into the control of thermal conditions in radiant-heated spaces and highlight the importance of solar shading in mitigating heat stress. These results may support the optimization of HVAC design, control, and operation in both residential and non-residential nZEB buildings, contributing to improved occupant comfort and enhanced energy efficiency. Full article

Energy efficiency in hospitals—where continuous operation with high internal gains and strict comfort needs—demands facade strategies tailored to climate. This study quantifies how the window-to-wall ratio (WWR) distribution and city-specific envelope properties affect the annual heating and cooling loads of a four-story, 3000 m² hospital in Turkey. Energy simulations were conducted using DesignBuilder (2021) with EnergyPlus under a controlled modeling framework, following ASHRAE healthcare guidelines for internal loads and TS 825:2024 for envelope compliance. Three locations were selected to span national variability: Bursa (Marmara—temperate/transition), Mersin (Mediterranean—hot–humid), and Kars (humid continental—cold). Scenario 1 (S1) assigned a graduated WWR on the south facade by floor—20%, 30%, 40%, and 50% from ground to top—while the north, east, and west facades were held at 20%, 30%, and 20%. Scenario 2 (S2) preserved the same geometry and WWR values but applied the graduated WWR to the north facade instead, keeping the south at 20%, east at 30%, and west at 20%. Within each city, opaque and glazing properties were kept constant across scenarios to isolate WWR–orientation effects. For every city–scenario combination, annual space-heating and space-cooling loads were computed, and window heat gains and losses were analyzed on the facade with variable WWR to support interpretation of performance mechanisms. The results indicate that S2 outperforms S1 in Mersin, S1 outperforms S2 in Kars, and S2 offers a moderate advantage in Bursa. Full article

Given the deteriorating situation of ambient ozone (O₃) pollution in some areas of China, understanding the mechanisms driving O₃ formation is essential for formulating effective control measures. This study examines O₃ formation mechanisms and RO_x (OH, HO_2, and RO₂) radical cycling driven by photochemical processes in Bozhou, located at the junction of Jiangsu–Anhui–Shandong–Henan (JASH), a region heavily affected by O₃ pollution, by applying a zero-dimensional box model (Framework for 0-Dimensional Atmospheric Modeling, F0AM) coupled with the Master Chemical Mechanism (MCM v3.3.1) and Positive Matrix Factorization (PMF 5.0) to characterize O₃ pollution, identify volatile organic compound (VOC) sources, and quantify radical budgets during pollution episodes. The results show that O₃ episodes in Bozhou mainly occurred in June under conditions of high temperature and low wind speed. Oxygenated volatile organic compounds (OVOCs), alkanes, and halocarbons were the dominant VOCs groups. The CH₃O₂ + NO reaction accounted for 24.3% of O₃ production, while photolysis contributed 68.7% of its removal. Elevated VOCs concentrations in Bozhou were largely maintained by anthropogenic sources such as vehicle exhaust, solvent utilization, and gasoline evaporation, which collectively enhanced O₃ production. The findings indicate that O₃ formation in the region is primarily regulated by NO_x availability. Therefore, emission reductions targeting NO_x, along with selective control of OVOCs and alkenes, would be the most effective strategies for lowering O₃ levels. Model simulations further highlight Bozhou’s strong atmospheric oxidation capacity, with OVOC photolysis identified as the dominant contributor to RO_x generation, accounting for 33% of the total. Diurnal patterns were evident: NO_x-related reactions dominated radical sinks in the morning, while HO₂ + RO₂ reactions accounted for 28.5% in the afternoon. By clarifying the mechanisms of O₃ formation in Bozhou, this study provides a scientific basis for designing ozone control strategies across the JASH junction region. In addition, ethanol was not directly measured in this study; given its potential to generate acetaldehyde and affect local O₃ formation, its possible contribution introduces additional uncertainty that warrants further investigation. Full article

This study examines the impact of chilled water supply parameters on the energy efficiency of an office building’s HVAC system located in a temperate European climate. Two cooling system variants were analyzed: (1) a traditional low-temperature system using fan-coil units and (2) a high-temperature system with chilled beams for sensible cooling. In the latter, moisture removal is performed entirely by the air handling unit, where outdoor air is dehumidified before being supplied to the space. Hourly simulations were carried out for the summer period using typical meteorological year data. Detailed heat gain calculations included transmission, occupancy, equipment, lighting, and solar radiation. Based on the cooling loads, chilled water production and distribution systems were selected, and their electricity consumption was assessed. The total energy use of chillers, ventilation units, circulation pumps, and auxiliary equipment was compared for both systems. The findings highlight the energy-saving potential of high-temperature chilled water systems, especially when integrated with centralized ventilation capable of latent load control. Additionally, results show that increasing the chilled water supply temperature significantly enhances the Energy Efficiency Ratio (EER) of chillers. Full article

The use of solar control foils (SCFs) is a minimally invasive method that enables energy savings while preserving the original character of historic building facades. This study analysed the energy reduction potential of four types of window films applied to single-pane glazing. A typical office space at the University of Bologna, located in a historic building, served as a case study. Building performance simulations using DesignBuilder and Berkeley Lab Optics software were applied as research tools. The potential reduction in cooling energy consumption by using SCFs can be up to about 35% in humid subtropical (Bologna) and Mediterranean (Seville) climates. A decrease of about 53% can be achieved in a temperate oceanic climate (Paris). Due to the reduction in heat gains from solar radiation, there is an increase in energy consumption for heating by 6% to even 50% and up to a maximum of about 15% for artificial lighting. Financial indicators such as LCC, NPV, and IRR were used to select the optimal option. The recommended solution was an SCF installed on the inside of the window with SHGC of 0.452, a visible transmittance of 0.361, and an inside reflectance of 0.195. Additionally, this study proposes a method for correcting heating and cooling energy demand results calculated based on data for a typical meteorological year and weather parameters measured over the past 19 years. This allows for the validity of energy simulation results by taking into account current climate changes. Full article

Wireless charging for drones is significant for solving problems such as the frequent manual plugging and unplugging of cables. A large number of densely packed transmitting coils and fully independent on-off control can precisely track the receiver with random access location. To balance the excitation area of the transmitter, additional hardware cost, and receiving voltage fluctuation, the wireless charging system of drones based on a D3-type transmitter is proposed in this article. The circuit model considering states of multiple switches is developed for three excitation modes. The dual-coil excitation mode is selected after comparative analysis. The transmitter reconfiguration method with low hardware cost and high receiving-excitation area ratio is proposed based on one detection sensor of DC current and one relay furtherly. Finally, an experimental prototype is built to verify the theoretical analysis and proposed method. When the output voltage fluctuation is limited to ±10%, the ratios of the maximum misalignment value in the x-axis and y-axis directions to the side length of the receiver reach 66.7% and 46.7%, respectively. The receiving-excitation area ratio of 37.5% is achieved, significantly reducing the excitation area not covered by the receiver. The maximum receiving power is 289.44 W, while the DC-DC efficiency exceeds 87.05%. Full article

Alfalfa (Medicago sativa) is a globally important forage crop; however, improvements in its biomass yield have stagnated due to its complex genetic architecture and the costly, labor-intensive phenotyping. This study evaluated the potential of the normalized difference vegetation index (NDVI) to predict biomass yield and enhance selection efficiency in alfalfa breeding programs. Specifically, nineteen alfalfa experimental populations (AEXP 1–19) and one control cultivar (OS 66) were evaluated over two growing seasons in Croatia. NDVI was measured at four development stages using a GreenSeeker sensor and compared with forage yield, dry matter yield, and plant height. NDVI values varied significantly among genotypes, years, and growth stages, ranging from 0.23 to 0.87, and increased consistently from early to late vegetative phases. Strong positive correlations were observed between NDVI and forage yield (r = 0.543–0.843) and plant height (r = 0.537–0.738) at early vegetative, late vegetative, and early bud stages. Conversely, NDVI at the mid-vegetative stage correlated negatively with yield and height (r = –0.622 to –0.794). High-performing populations (AEXP 2, AEXP 15, AEXP 18) also exhibited the highest NDVI values. NDVI is a reliable, non-destructive indicator for early selection of high-yielding alfalfa genotypes, although multi-location validation is advised to confirm its broader applicability. Full article

Surface Plasmon Resonance imaging (SPRi) is a powerful label-free technique for high-throughput biochemical analysis. Wavelength modulation is particularly suitable for SPRi due to its wide dynamic range and robustness to fabrication tolerances. However, conventional systems relying on tunable filters (e.g., AOTF, LCTF) suffer from high cost, complexity, and limited temporal resolution. To overcome these drawbacks, we developed a rapid wavelength-modulation SPRi system using a multi-LED source and an adaptive second-order fitting (ASF) algorithm. The system covers the 730–805 nm spectrum with five LEDs. The ASF algorithm first performs a coarse full-spectrum scan to locate the resonance wavelength, then dynamically selects an optimal three-LED subset for fast second-order fitting, enabling accurate reconstruction of resonance wavelength without mechanical scanning. This approach significantly reduces cost and complexity while achieving a scanning cycle of 105 ms, RI resolution of 5.54 × 10⁻⁶ RIU, dynamic range of 0.0241 RIU, and excellent multi-channel consistency. The system has been successfully applied to monitor multi-channel antibody–antigen interactions in real time. Furthermore, it was used to detect cartilage oligomeric matrix protein (COMP) in synovial fluid, where an elevated concentration in an osteoarthritis sample versus a control aligned with its role as a cartilage catabolism marker. This work validates a practical and reliable platform for early diagnosis of osteoarthritis. Full article

Gel treatments have been widely applied to control water production in oil and gas reservoirs. However, for water shutoff in dense gas reservoirs, most gel-based treatments focus on individual wells rather than the entire reservoir, exhibiting limited treatment depth, poor durability, and inadequate repeatability Notably, formation damage is a primary consideration in treatment design—most dense gas reservoirs have a permeability of less than 1 mD, making them highly susceptible to damage by formation water, let alone viscous polymer gels. Constrained by well completion methods, gelant can only be bullheaded into deep gas wells in most scenarios. Due to the poor gas/water selective plugging capability of conventional gels, the injected gelant tends to enter both gas and water zones, simultaneously plugging fluid flow in both. Although several techniques have been developed to re-establish gas flow paths post-treatment, treating gas-producing zones remains risky when no effective barrier exists between water and gas strata. Additionally, most water/gas selective plugging materials lack sufficient thermal stability under high-temperature and high-salinity (HTHS) gas reservoir conditions, and their injectivity and field feasibility still require further optimization. To address these challenges, treatment design should be optimized using non-selective gel materials, shifting the focus from directly preventing formation water invasion into individual wells to mitigating or slowing water invasion across the entire gas reservoir. This approach can be achieved by placing large-volume gels along major water flow paths via fully watered-out wells located at structurally lower positions. Furthermore, the drainage capacity of these wells can be preserved by displacing the gel slug to the far-wellbore region, thereby dissipating water-driven energy. This study evaluates the viability of placing gels in fully watered-out wells at structurally lower positions in an edge-water drive gas reservoir to slow water invasion into structurally higher production wells interconnected via numerous microfractures and high-permeability streaks. The gel system primarily comprises polyethyleneimine (PEI), a terpolymer, and nanofibers. Key properties of the gel system are as follows: Static gelation time: 6 h; Elastic modulus of fully crosslinked gel: 8.6 Pa; Thermal stability: Stable in formation water at 130 °C for over 3 months; Injectivity: Easily placed in a 219 mD rock matrix with an injection pressure gradient of 0.8 MPa/m at an injection rate of 1 mL/min; and Plugging performance: Excellent sealing effect on microfractures, with a water breakthrough pressure gradient of 2.25 MPa/m in 0.1 mm fractures. During field implementation, cyclic gelant injections combined with over-displacement techniques were employed to push the gel slug deep into the reservoir while maintaining well drainage capacity. The total volumes of injected fluid and gelant were 2865 m³ and 1400 m³, respectively. Production data and tracer test results from adjacent wells confirmed that the water invasion rate was successfully reduced from 59 m/d to 35 m/d. The pilot test results validate that placing gels in fully watered-out wells at structurally lower positions is a viable strategy to protect the production of gas wells at structurally higher positions. Full article

Permeability, thermal conductivity, and porosity distribution are key factors to control groundwater flow and heat transport in porous media. The parameter estimation procedure is widely used to understand flow and transport behavior in geothermal systems. As recognized in most studies, this parameter estimation relies on the quality and quantity of spatiotemporal measurements. With the typically limited resources for conducting field investigations, understanding suitable sampling strategies is crucial before applying a model to site-specific conditions. This study aims to quantify uncertainties in hydro-thermal properties using Monte Carlo Simulation (MCS) and Ensemble Kalman Filter (EnKF). A synthetic two-dimensional aquifer profile is used to evaluate the accuracy of the estimated hydrothermal properties in accounting for variations in groundwater temperature resulting from cross-hole pumping and injection events. Based on the calculations of the mean absolute and squared errors for estimated hydrothermal properties, EnKF generally leads to more accurate estimates of hydrothermal properties than MCS. Furthermore, EnKF strikes a balance between accuracy and efficiency, making it the most effective method. This study highlights the strengths and limitations of each method, providing valuable insights for selecting appropriate inversion techniques to quantify uncertainties in geothermal systems. Additionally, well spacing and open screen locations are recommended to obtain optimal thermal energy in the geothermal system Full article

Background: Colorectal cancer is a major public health burden in Hungary, with one of the highest incidence and mortality rates in Europe. Long non-coding RNAs (lncRNAs) have emerged as key regulators in tumorigenesis, but population-specific genetic associations remain understudied. This study aimed to investigate whether single-nucleotide polymorphisms (SNPs) in lncRNA genes are associated with colorectal cancer susceptibility, with attention to tumor site- and sex-specific effects. Methods: We conducted an exploratory case–control study involving 91 Hungarian participants (38 patients with colorectal lesions and 53 controls). Genotyping of six SNPs located in HOTAIR, PTCSC3, H19, CCAT1, and CCAT2 was performed using TaqMan-based qPCR. Associations were tested using allele frequency analysis, different genotype models (dominant, recessive, additive), and binary logistic regression, including stratified analyses by tumor subtype and sex. Results: While no significant associations were found in the unadjusted overall case–control comparisons, logistic regression including sex revealed that HOTAIR rs12826786 and rs7958904 were significantly associated with a reduced risk of colorectal lesions, particularly in females (p = 0.022 and p = 0.043). Analyses by tumor localization revealed that H19 rs2839698 and PTCSC3 rs944289 were more frequent in colon than in rectal tumors (p = 0.017 and p = 0.035) and were associated with a reduced risk of rectal tumors (OR = 0.18 and OR = 0.20), suggesting that these variants may influence tumor site rather than overall susceptibility. None of the results remained significant after Bonferroni correction. Conclusions: Our findings suggest that these selected lncRNA-related SNPs may contribute to colorectal cancer risk in a sex- and site-specific manner. These preliminary results warrant further validation in larger, independent cohorts and functional studies. Full article

Improving the Prediction Performance (PP) of crack pipeline Failure Assessment Model (FAM) is of great significance for the safety of pipeline structure and engineering. However, conventional optimizations for PP always focus on either safety or accuracy, failing to balance the overall requirements of structural applications. Therefore, this paper proposes an optimization procedure for comprehensively improving FAM’s PP. The establishment of the procedure can be divided into three parts: 1. setting a rational and robust optimization target, where the Improved Guo-Ni Model (IGNM) is raised to provide an absolute score s for fully quantifying FAM’s PP in terms of the multi-dimensional performances, including stability and Distributional Location Characterizations (DLCs) of FAM’s prediction results; 2. determining the candidate solutions which are selected as the Critical Safety Factor (CSF) values related to FAM’s prediction confidence level (R₁) in this paper; 3. constructing the optimization framework based on the Particle Swarm Optimization algorithm to search for the optimal CSF (OCSF) that can maximize s. Finally, empirical verification results show that the procedure enhances the overall s values of BS 7910:2019 and CorLAS models by 3.32% and 6.09%, respectively, through balancing DLCs, which increases the applicability of FAM across different projects and provides a new approach for the optimization control of FAM’s overall performance. Full article

Background: Adamantinoma is a very rare primary malignant bone tumor. A histopathological grading is still lacking, and as a result, metastatic risk stratification at diagnosis is challenging. Due to this, imaging could play a role in prognosis prediction and treatment strategy assessment. We aimed to evaluate baseline imaging features and their correlation with the development of metastatic disease. Methods: We retrospectively collected clinical (metastatic disease) and radiological data at baseline (Conventional Radiography, CT, MRI) of all consecutive patients with a histopathological diagnosis of adamantinoma at our sarcoma center between 2006 and 2022. Tumor location, dimensions, main radiological pattern (lytic, sclerotic, mixed), Lodwick–Madewell grading, periosteal reaction, multifocality, soft-tissue extraskeletal component, peritumoral edema, peritumoral enhancement, and vascular invasion were analyzed. Associations between the above-mentioned radiological features and metastatic disease at diagnosis or during follow-up were assessed. Results: Twenty-two patients were included (15 [68.2%] women, median age 27 years old, range 7–58 years old). Six out of twenty-two patients (27.3%) developed distant metastases (only two of them were dedifferentiated adamantinoma): two patients (9%) presented with metastatic disease at diagnosis, while four patients developed metastases during follow-up (18.2%). The following radiological features represent a significant risk for metastatic disease (p = 0.01): (i) presence of an extra-skeletal component (Odds Ratio [OR] = 75.40; 95% CI = 3.15–1802.71), (ii) vascular invasion (OR = 121.00; 95% CI = 4.28–3424.73), (iii) diffuse peritumoral edema (OR = 75.40; 95% CI = 3.15–1802.71), (iv) peritumoral enhancement (OR = 84.33; 95% CI = 2.93–2423.26). All other features analyzed were not significantly associated with the onset of distant metastases. Based on these above-mentioned MRI features, we built two risk models for metastatic disease (excluding peritumoral enhancement, which was not available in five patients, to be applicable on unenhanced MRIs): Model (A) = simultaneous presence of two of those three features (2/3) with a sensitivity of 100% (54.07–100%) and a specificity of 93.75% (69.67–99.84%). Model (B) = simultaneous presence of all three features (3/3) with a sensitivity of 83.33% (35.88–99.58%) and a specificity of 100% (74.1–100%). Conclusions: An accurate evaluation of baseline imaging studies (particularly MRI) in patients affected by adamantinoma may significantly aid in prognosis prediction and the selection of high-metastatic-risk patients. For these patients, strict follow-up controls and more aggressive treatments should be suggested after multidisciplinary discussions in sarcoma centers. Full article