Browse Articles

Effect of pore-throat structure on movable fluid and gas–water seepage in tight sandstone from the southeastern Ordos Basin, China

Statistical learning re-shapes the center-surround inhibition of the visuo-spatial attentional focus

Interplay between Jahn–Teller Distortions and Structural Phase Transitions in Ruddlesden–Poppers

Dual-directional epi-genotoxicity assay for assessing chemically induced epigenetic effects utilizing the housekeeping TK gene

Tailoring Lewis Acidity of Metal Oxides on Nickel to Boost Electrocatalytic Hydrogen Evolution in Neutral Electrolyte

Cannulated intravaginal injection technique (CIVIT) A Novel Vaginal Injection Technique 

Fluorogenic Platform for Real-Time Imaging of Subcellular Payload Release in Antibody–Drug Conjugates

Steady-state data-driven dynamic stability assessment in the Korean power system

Abstract The extensive research on dynamic security assessment stability prediction has focused on data preprocessing techniques to improve accuracy because it was assumed that high-resolution postfault data exist. For practical users, the acquisition and application of high-resolution measurement data present significant challenges. Installing phasor measurement units on all power system nodes is deemed impractical due to high costs. In this work, we aimed to develop a rotor angle stability prediction model using steady-state data that can be easily generated from the current energy management system. Note that the steady-state measurement data refer to a pre-contingency operation condition characterized by real and reactive loads, generation levels, flows, as well as voltages and angles. The proposed framework comprises three stages: it finds physical meaning from the extended equal-area criterion to move away from the black-box approach, proposes a feature data extraction strategy to reduce the dimensionality of the input space in the support vector machine, and partition time-series power flow data by month to consider system topology changes. By utilizing 5-min-interval power flow data, unstable cases are determined, and two main feature data are extracted to train the support vector machine. The obtained results showed the effectiveness of the proposed framework in responding to a critical line fault event in real time.

Engineering Helical Chirality in Metal-Coordinated Cyclodextrin Nanochannels

Determining the optimal harvest time for pomegranate variety wonderful in semi-arid climate

Abstract Due to limited local knowledge regarding the optimal harvest time for this non-native variety, a two-year study (2021–2022) was conducted using a randomized complete block design with four blocks. This study aimed to determine the ideal harvest time based on quantitative and qualitative fruit characteristics in saveh, which has a semi-arid climate. Twelve similarly sized trees were selected for each orchard, and fruits were harvested at three-time intervals: 155 days after flowering (DAF) (September 27), 170 DAF (October 12), and 185 DAF (October 27). Ten fruits from four sides of the tree canopy were collected and analyzed for physical and biochemical properties. The results showed that harvest time significantly affected fruit weight, aril weight, and juice percentage positively, while it negatively impacted rind percentage. The first harvest date yielded the lowest quantitative and qualitative traits, with incomplete skin and aril coloration. By the third harvest, pomegranate fruits exhibited the highest total soluble solids (17.76 °Brix), pH (3.41), and anthocyanin content (32.56 mg/L), along with the lowest total phenols (17.28 mg GAE/L), antioxidant capacity (79.78%), and titratable acidity (1.11%), resulting in the highest flavor or ripening index (16.31). In addition, cracking rates increased substantially, reaching 30.25% by the third harvest, compared to negligible levels of 20.72% by the second harvest. Juice percentage and aril weight improved significantly with delayed harvest, peaking on October 27. These findings suggest that October 12–27 is the optimal harvest window for superior fruit quality while considering the risk of fruit cracking. This study provides practical insights into harvest timing for maximizing the marketability and nutritional value of ‘Wonderful’ pomegranates in semi-arid climates.

C₁-Based Route for Vinyl Chloride Synthesis with Environmental and Economic Benefits

Field based analysis of vegetation and climate impacts on the hydrological properties of urban vegetated slope

Modeling, analysis and control of an inertial wave energy converter and hydraulic power take-off unit

Functionalized Violet-Emitting Cd, Pb-Free Quantum Dots with Thermally Activated Delayed Photoluminescence for Efficient Photochemical Reactions

Electrical grid linked to PV/wind system based fuzzy controller and PID controller tuned by PSO for improving LVRT

Abstract This paper presents the use of a static synchronous compensators (STATCOM) device to improve the low voltage ride through (LVRT) ability of an electrical network consisting of wind farms that produce 9 MW and 1 MW PV stations during grid faults. A hybrid energy model is connected with 100 MVAR STATCOM at the point of common coupling (PCC) through line to line fault occurs on the grid. STATCOM control is used to detect the voltage at the PCC bus through occurring line to line (LL) faults by compensating reactive energy. A method of particle swarm optimization (PSO) is utilized for adjusting the optimum value of proportional—integral—derivative (PID) STATCOM control. STATCOM is controlled by (PID) and is compared with STATCOM controlled by fuzzy logic control (FLC). The proposed system has been performed utilizing Matlab/Simulink. Results of the simulation clear effectiveness and the ability of STATCOM with FLC in improving LVRT, power quality, and mitigation voltage dip, during grid faults like line to line (LL) faults as compared with STATCOM with PID control.

Estimation of actual evapotranspiration and water requirements of strategic crops under different stresses

Abstract According to the importance of water conservation in water scarcity regions, estimating the exact amount of required water for crops under different stress conditions in irrigation networks is vital. One of the challenges in water management is estimating these stresses with crop models. AquaCrop is a robust model that can simulate the actual evapotranspiration and the water needs under different biophysical and management conditions. In this study, the actual evapotranspiration (Eta) and the irrigation requirement of wheat, barley, and maize are estimated by the AquaCrop model in the Qazvin province, and then compared with the results of the CropWat model. According to the results, the irrigation requirement for all three crops was significantly less than the CropWat estimation that were 184, 55.9, and 38.6 mm less water volume is needed for wheat, barley, and maize, respectively, showing using this model, the water efficiency will increase and the less amount of water can bring us the same amount of production. After that, for better comparison and assessment of the AquaCrop model, results were compared to the amount estimated by the Moghan plain and represented a higher amount of the actual evapotranspiration and the irrigation requirement because of different climate situations. These differences are mostly due to the AquaCrop model that is able to adjust itself under different stress conditions.

Identification of candidate nsSNPs of the human FNDC5 gene and their structural and functional consequences using in silico analysis

Enantioselective Total Synthesis of (−)-Rubriflordilactone B by a Bioinspired Skeletal Reorganization Approach

Long term gait postural characteristics of children with general foot pain using smartphone connected wearable sensors

Embodied design for enhanced flipper-based locomotion in complex terrains