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Intracellular Dynamic Supramolecular Polymerization to Elicit Tumor Pyroptosis
AC measurements and magnetic properties of magnesium ferrite and its composites with reduced graphene oxide (rGO) and polypyrrole (PPy)
Photodriven Sm-Catalyzed Asymmetric Ketyl-Olefin Coupling
Correction: Ergonomic assessment of a multi-joint actuated lower extremity exoskeleton to assist dynamic lifting and carrying tasks
Cleavage Alkylation Coupling with Versatile Amide-Based Eutectic Catalytic Systems
A new good point set stepwise shrinkage optimization in machine learning model for fog node performance prediction
Enhanced Green Hydrogen Generation via Photocatalytic Water Splitting Using V-Doped Ti-Squarate MOFs
Biodegradable composites from organic waste as a circular solution for improving soil fertility, water retention, and plant productivity
Abstract Growing environmental problems and challenges related to plant production require the use of innovative soil additives that reduce water deficits and soil fertility decline while caring for the environment. This study presents a sustainable approach to improving soil properties and plant growth conditions through the use of innovative biodegradable soil additives made from organic waste with the addition of biochar and Trichoderma. A two-year field experiment conducted in difficult habitats included an assessment of the impact biodegradable composites on soil and plants properties, water availability. The use of composites resulted in intensive plant growth, increasing biomass gains by up to 190%. A significant improvement in soil parameters was noted, as evidenced by increases of up to 119%, 177%, and 145% in the N, P, K content of the soil. The amendments also enhanced plant water status, as evidenced by a 20% increase in leaf relative water content, and the beneficial effects persisted into the second year of the study. The results obtained indicate that the combination of biodegradable fibers with biochar has significant potential in the creation of circular environmental technologies. The research provides new insights into the dynamics of natural fiber biodegradation and the functional role of biochar in improving soil quality.
Kinetic Self-Assembly of Hierarchical V-Notch Spherulites via Asynchronous Polymerization-Crystallization for Multiscale Anticounterfeiting
Tumor-suppressing multi-enterobacteria enhance the anti-PD-1/PD-L1 efficacy in microsatellite stable colorectal cancer
Single-Feature Identification of α2–8 Linked Sialoglycans Using Engineered Aerolysin Nanopores: A Paradigm for Glycan Linkage Analysis
Anti-inflammatory treatment confirms rsfMRI and TSPO PET as biomarkers of functional connectivity and neuroinflammation in rat contusion spinal cord injuries
Decoupling Product Selectivity in Electrocatalytic CO <sub>2</sub> Reduction by Steering the Interfacial Water Structure
Multiplexed optical barcoding and sequencing for spatial omics
Abstract Spatial omics has brought a fundamental change in the way that we study cell and tissue biology in health and disease. Among various spatial omics methods, genome-scale imaging allows transcriptomic, 3D-genomic, and epigenomic profiling of individual cells with high spatial (subcellular) resolution but typically requires a preselection of targeted genes or genomic loci. On the other hand, spatially dependent barcoding of molecules followed by sequencing provides untargeted, genome-wide profiling but has a lower spatial resolution than imaging-based methods. Here, we report a spatial omics method that could potentially combine the power of the two approaches using optically controlled spatial barcoding followed by sequencing. Specifically, we utilize patterned light to encode the locations of molecules in tissues using oligonucleotide-based barcodes and then identify the barcoded molecular content, such as mRNAs, by sequencing. This optical barcoding method is designed with multiplexing and error-correction capability and achieved by a light-directed ligation chemistry that attaches distinct nucleic-acid sequences to the reverse transcribed cDNA products at different locations. As a proof of principle for this method, we demonstrated high-efficiency in situ light-directed ligation, spatially dependent barcoding with multiplexed light-controlled ligations at the single-cell level, and high-accuracy detection of spatially barcoded mRNAs in cells.
Optimizing sonication-assisted hydrodistillation of Cinnamomum tamala essential oil using response surface methodology and artificial neural network modeling
Abstract This study optimized the sonication-assisted hydrodistillation (SAHD) process for extracting essential oil (EO) from Cinnamomum tamala leaves, aiming to maximize yield and antioxidant activity. Both response surface methodology (RSM) and artificial neural network (ANN) models were used to predict extraction performance. The interpretability of the ANN model was enhanced using a neural interpretation diagram (NID), Olden’s algorithm, and sensitivity analysis, and it demonstrated higher accuracy and generalization than RSM. Under optimized conditions, the EO yield reached 1.67 ± 0.13%, with strong antioxidant activity indicated by a total phenolic content (TPC) of 79.24 ± 0.82 mg GAE/g and 81.54 ± 0.88% inhibition of the 2,2-diphenyl-1-picrylhydrazyl radical (DPPH). Residual analysis showed that both models satisfied key regression assumptions, including normality, independence, homoscedasticity, and lack of bias. Gas chromatography–mass spectrometry (GC–MS) analysis identified linalool (47.37%), eugenol (18.34%), and cinnamaldehyde (16.45%) as key constituents. Physicochemical characterization verified EO quality and stability. The integrated modeling approach provides a robust framework for enhancing EO extraction efficiency.
Long-Acting Fractionated Sonodynamic Therapy Enabled by Fused-Trianthracene Nanoparticles with Ultra-Bright Ultrasound-Induced Afterglow Luminescence
Dynamic behavior of a stochastic epidemic model for skin sores: theoretical and computational perspectives
Inter-area minimisation of reactive power flow for voltage improvement in large electric grids
Abstract Traditionally, Electric grids are designed to transport the bulk power generated at conventional power plants to load centres. Electricity regulators are tightening the grid codes to improve the performance and efficiency of electric grids. The coordinated planning of reactive power management for voltage profile regulation is an essential aspect of the seamless operation and control of electric grids. The adverse effects of seasonal variation in load profiles and the de-commitment of generating units based on their viability magnify the voltage regulation challenge in the large electric grid. These operational scenarios create low-voltage pockets in the distribution network, and there is a high draw of reactive power from the upstream transmission system. The power transfer capabilities of inter-regional tie lines decrease, and subsequently, this leads to overloading of power equipment and increases active loss in the utility grid. In this research article, reactive power management is formulated as a nonlinear optimisation problem. The objective function is minimised as the sum of reactive power flow over inter-intra-regional tie lines in a large electric grid. The optimisation problem is solved with a set of constraints imposed by placing the local reactive power support devices at critical locations. Selection of critical locations is identified through a new hybrid voltage-grid strength sensitivity index. The proposed index utilises the grid strength in addition to the voltage sensitivity of bus selection of buses for the installation of reactive power support devices. The performance of the proposed algorithm has been tested on real data from the Northern region of the Indian grid, which includes seven power transmission utilities with over 9000 buses. The simulation results show that the proposed reactive power optimisation, based on the hybrid voltage-grid strength sensitivity index, reduces reactive power import from 1592 to 383 MVAr by injecting 9421.8 MVAr at 33 kV at only 14.1% of the highly sensitive buses identified through this index. It is observed that injecting compensation devices at 33 kV buses improves the average bus voltage to nearly 0.98. The reactive power in the inter-intra tie lines decreases by 76%, and active power losses are reduced by 7.99%. In conclusion, the proposed algorithm can serve as a guiding tool for planning reactive power management in large-scale grid utilities, aiding voltage improvement with the optimal installation of compensating devices at a minimal number of 33 kV buses.