Browse Articles

N-Sulfated Heparan Sulfate Promotes Reelin Signaling as a Co-receptor

Comparison of multi-miRNA models from donor-matched plasma and cerebrospinal fluid as candidate biomarkers for Alzheimer’s disease prediction

Quantifying Phase Contributions to Ion Transport in Organic–Inorganic Composite Electrolytes

Author Correction: Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms

Copper-Catalyzed Asymmetric Alkynylation of <i>sp</i> ² Allenic C–H Bonds for the Synthesis of Skipped Diynes

Sidelobe suppression for cosine-sum window functions via chaotic particle swarm optimization

Photo-Induced Intermolecular N–N Cross-Coupling via Nitrene Transfer Reaction

Merge-based syntax is mediated by distinct neurocognitive mechanisms in 84,000 individuals with language deficits across nine languages

Efficacy of early goal-directed therapy for hemodynamics stability in off-pump coronary artery bypass surgery

Application of deep learning for transformation of Chinese traditional cultural narrative patterns and enhancement of cultural identity empowered by AIGC

Multiplexed Analysis of Multicomponent Biomolecular Condensates without Any Tag

Zone-inspired hydrogel constructs promote spatially controlled chondrogenesis for osteochondral regeneration

Bifurcation analysis and analytical traveling wave solutions of a sasa-satsuma equation involving beta, M-truncated and conformable derivatives using the EGREM method

Structural High-Entropy FePt Alloy Nanoparticles Enabled Fast Magnetization Dynamics

Non-linear model predictive control for variable speed hydropower

Abstract Inverter Based Resources (IBR) are gaining more popularity in modern power systems, leading to decrease in grid inertia. Hydropower Plants with rotating synchronous machines have been excellent source of inertia in existing grids. Adding a frequency converter between the generator and the grid in these hydropower plant would enable to run the hydropower in variable speed leading to enhanced efficiency and more flexibility in operation. These Variable Speed Hydropower Plant (VSHP), having the capability of anciliary services for grid support could be a potential solution for providing synthetic inertia to low-inertia power grids. However, there is a little research done on control of VSHP for grid support. This paper aims at implementing Non-Linear Model Predictive Controller (NLMPC) algorithm for optimal control of VSHPs, and the results are compared with classical PID control method. Explicit comparison under realistic operating condition and analysis of constraint handling capabilities and robustness of MPC have been performed. Advanced model based NLMPC successfully coordinated the hydraulic and electric systems having different time constants by implementing multi-objective optimization and upstream constraints satisfaction. Furthermore, the NLMPC has shown relatively better performance than the classical controllers even during the occurrence of an unanticipated grid-side disturbance. This paper is claimed to be an important work in control domain since it develops the control system for VSHPs using time-domain models which can offer better insights over the nonlinearities that exist within hydropower systems. Apart from the computational complexity, NLMPC is found to be viable for the control of VSHP since it ensured stable operation, as can be seen from the analysis of different operational cases studied implemented in this paper. The key takeaway from this paper is the potential of utilizing advanced model based optimal control strategy for coordination among complex dynamic systems of VSHP for different loading patters and disturbances. Also, the MPC has a scope of providing more robust grid support by addressing overloads and uncertainties during operation.

Ice-Confinement Overcomes the Diffusion-Reaction Limitation in Surface Assays

High-resolution climate reconstruction from historical Chinese weather records using optimized natural language processing

Spatial and temporal assessment of soil degradation risk in Europe

Abstract Soil degradation threatens agricultural productivity and ecosystem resilience across Europe, yet spatially consistent assessments of its intensity and drivers remain limited. In this study, we used Soil Degradation Proxy (SDP), that integrates four key indicators of soil degradation, including erosion rate, soil pH, electrical conductivity, and organic carbon content, to quantify soil degradation risk. Using over 38,000 LUCAS topsoil observations and a machine learning model trained on climate, land cover, topographic, soil parent material properties, and spectral variables, we map annual SDP values between years 2000 to 2022 across Europe. Results show soil degradation risk is highest in southern Europe, especially in intensively managed and sparsely vegetated landscapes. Over the past two decades, approximately 7.1% of land area across the EU and the UK has experienced increasing degradation risk (most notably across Eastern Europe), with rainfed croplands emerging as the most affected land cover type. Land cover is the most influential driver, modulating effects of climatic variables such as precipitation and temperature on SDP. This data-driven framework provides a consistent and scalable approach for monitoring soil degradation risk and offers actionable insights to support targeted conservation and EU-wide policy implementation.

Effect of moisture content variation on dielectric properties of seeds of multipurpose species in 20 MHz-3 GHz frequency range

Abstract The study presents measurements and analysis of complex dielectric permittivity spectra of seeds of multipurpose crop species such as mustard, buckwheat, phacelia, and crimson clover. These species due to their ecosystem service properties such as the improvement of soil health, carbon sequestration and pollinator support, can be part of sustainable food production.Seeds with different moisture content were measured in a coaxial cell system covering 20 MHz to 3 GHz frequency range. The results indicate that dielectric parameters such as the square root of dielectric permittivity, loss tangent, penetration depth, and effective electrical conductivity are influenced by factors including volumetric water content and measurement frequency. Additionally, significant variations in dielectric properties are observed among different seed types and species. Dielectric permittivity, in particular, shows potential as a reliable indicator of seed water content, making it a valuable tool for assessing seed quality and monitoring changes during storage under various conditions. These findings highlight the importance of dielectric measurements in seed quality assessment and storage management as well provide valuable information for modelling and designing efficient dielectric heating and microwave-assisted conditions.

Total Synthesis of Aconicarmisulfonine A, a Sulfonated Diterpene Alkaloid