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Research on the aerodynamic characteristics of eVTOL aircraft ducted rotor tip embedded inside the ducted body
Intelligent recognition of counterfeit goods text based on BERT and multimodal feature fusion
Neuroectoderm-derived iris muscle characterization at the single-cell resolution in native human iris and a pluripotent stem cell eye model
Diagnostic and prognostic value of combined cerebrospinal fluid parameters for post-neurosurgical intracranial infection in brain tumor patients
Evaluation of aesthetic parameters and changes in alveolar bone level in patients undergoing maxillary expansion with invisalign technique
Bedrock uplift reduces Antarctic sea-level contribution over next centuries
Synergistic CNT-SnS nanocomposites for enhanced photocatalytic dye degradation and supercapacitor applications
Role of particle size and element characteristics on shear response at sandy soil-textured surface interfaces
Abstract A fundamental understanding of shear behavior at the interface between foundation elements with innovative surfaces that include bio-inspired or structured element designs is critical in the design of many geotechnical structures. Some geotechnical applications could benefit from the use of surfaces with structured roughness form that mobilize larger shear resistances than conventional interfaces with random roughness form. However, several parameters such as soil properties, particle size, surface roughness, geometry of surface elements may influence the shear behavior at the interface between soil and surfaces with structured roughness which requires further research. To study the possible effects of these parameters on shear resistance, a series of interface direct shear tests were performed for 7 sands with varying particle sizes and four aluminum surfaces (three textured with trapezoidal-like elements and a smooth surface). When the 7 sands sheared against the same textured surface, the shear resistance decreases with increasing element height to mean particle diameter ratio ( h / D 50 ) and increases with increasing element-to-element spacing to height ratio ( S / h ). A parametric study on the geometrical characteristics of surface elements and soil particle size revealed that the h / D 50 and S / h ratios could quantitatively capture the interface load-transfer mechanisms between sand and textured surfaces. Based on the results obtained, it was found that the effect of particle size of test sand on shear resistance diminishes as h / D 50 and S / h decreases (i.e., surfaces with closely spaced elements). It was also found that, for identical surface characteristics, particle size affects the mobilized resistance: higher shear strengths are achieved when the sand’s mean particle diameter ( D 50 ) closely matches the asperity (element) height of the textured surface.
Applying fairness in subnational carbon budget allocations
Analytical and numerical solutions of MABC fractional advection dispersion models by utilizing the modified physics informed neural networks with impacts of fractional derivative
RNA modifications, alternative splicing and circular RNA landscape in the mouse brain: inosine and beyond
A scalable reinforcement learning approach for screening large peptide libraries for bioactive peptide discovery
Abstract Bioactive peptides such as anticancer peptides (ACPs) offer a promising therapeutic alternative to small molecules due to their efficiency and selectivity against tumors and minimal toxicity towards healthy human cells. However, their rational discovery requires navigating a vast chemical space using computationally demanding in silico tools. Herein, we present a computational method enabling cost-efficient exploration of large peptide libraries using reinforcement learning and posterior sampling. Practical application of the developed approach results in identification of membranolytic peptides with therapeutic potential. The developed computational method reduces the search space by over 90% compared to exhaustive library screening and enables effective balancing between dataset’s exploration and exploitation. We demonstrate the scalability of this method by screening a focused library of 36 million structurally resolved helical peptides curated from the Protein Data Bank. When screened in in vitro assays, 15 of the top 100 selected candidates exhibit cytotoxic activity against breast cancer cells including drug resistant triple-negative breast cancer, with the three lead compounds further characterizing as non-toxic towards healthy human cells. This study highlights the potential of using deep reinforcement learning to expedite bioactive peptide discovery, offering a promising path for developing new peptide-based cancer therapies.
Enhancing maize growth and drought resilience by synergistic application of plant growth promoting rhizobacteria
Abstract The agriculture system in India is mostly rainfed, water is a major limiting factor in the country. Limited access to available water creates a drought-like condition which severely affects the crop production. Maize was selected as the target crop due to its importance as third major crop after wheat and rice and its huge water demand. The present study was conducted to observe the effect of bacterial inoculants on drought stress tolerance of Zea mays L. The maize seeds (DH line and composite) were treated with 2 bacterial inoculants (LZn-4 and S34) which were characterized as plant growth-promoting microorganisms and were able to tolerate water potential of − 1.5 MPa. The experiment was conducted in two conditions Vis-à-vis stress and without stress. As per the observation plant height, relative water content, antioxidants level, and soil enzymes were found to be maximum in the case of LZn-4 in drought conditions. Principal component analysis also highlighted the positive correlation of some of the treatments (T2 and T8) with microbial inoculants towards different stress related factors. The present investigation needs to be taken to the field level to understand the relationship between microbial inoculants and drought stress in real-time situations.
RETRACTED ARTICLE: Sustainable pretreatment and adsorption of chemical oxygen demand from car wash wastewater using Noug sawdust activated carbon
Essential oil-derived decomposable polymers via cycloaddition polymerization of silyl ether-linked phenylpropanoids
Abstract Owing to increasing concerns regarding climate change, research concerning the use of plant biomass as a renewable carbon resource has become increasingly active. Phenylpropanoids, which are aromatic compounds derived from plants, offer renewable sources owing to their availabilities and structural diversity. This study presents an approach for use in producing decomposable polymers with high biomass contents via [2 + 2] cycloaddition polymerization. Bifunctional monomers with silyl ether-linked phenylpropanoids were synthesized, and their polymerizations were investigated using chemical and electro- and photochemical methods. The resulting polymers contained aromatic and cyclobutane rings and silyl ether bonds in their backbones, which enhanced their thermal properties. Notably, these polymers could be decomposed via Diels-Alder reactions at the cyclobutane rings or Si–O bond cleavage, facilitating chemical re- and upcycling. Here, we show a sustainable method of producing high-biomass decomposable polymers, potentially contributing in reducing plastic waste and promoting a circular economy.
Spatial gene expression profiling reveals the distinct microenvironment of tuberous sclerosis complex-associated angiomyolipoma
Comparative genomics of aflatoxigenic A. flavus reveals mycotoxin diversity and postharvest adaptation in cashew nuts from coastal Kenya
An antagonistic epigenetic mechanism regulating gene expression in pollen revealed through single-nucleus multiomics
Abstract Arabidopsis MBD5, MBD6, and MBD7 are CG-specific methyl-readers with opposite functions: MBD5 and MBD6 (MBD5/6) repress methylated loci in pollen vegetative nuclei (VN), while MBD7 prevents transgene silencing, possibly by promoting DNA demethylation. Here we show that loss of MBD7 rescues transcriptional defects at a large subset of MBD5/6-bound loci. Using simultaneous profiling of DNA methylation and transcription in single pollen nuclei, we found that MBD5/6-bound loci that are actively demethylated in immature VN lose additional methylation in mbd5/6 , prior to transcriptional derepression. A subset of these loci is also bound by MBD7, correlating with demethylation and transcriptional derepression in mbd5/6 that are both reversed by loss of MBD7 . Conversely, ectopically recruiting the MBD7 complex to MBD5/6 targets causes partial demethylation and upregulation. We propose that MBD5/6 maintain silencing in VN in part by preventing the MBD7 complex from enhancing the active demethylation that occurs during VN maturation.