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Remote Enantioselective Redox ε‐Alkylation of Copper Allylic Allenylidenes with Enals
Abstract The development of asymmetric functionalization at positions distant from the catalytic center—achieving high complexity, diversity, and stereocontrol—poses significant challenges. Here, we introduce an N ‐heterocyclic carbene (NHC)/copper cooperative catalytic strategy for the regioselective remote ε‐alkylation of yne‐allylic esters and yne‐heteroarenic esters with enals, producing a diverse array of oxindoles with outstanding stereoselectivity (up to >95:5 dr, 99% ee). Remarkably, copper allylic allenylidenes are proven to be compatible with NHC‐bound intermediates, facilitating efficient, regioselective, and stereoselective intermolecular C─C bond formation at distant sites.
Engineering dielectric properties and charge transport in PANI/CuO nanocomposites via microstructural control
Abstract This study systematically investigates the structure-property relationships in polyaniline/copper oxide (PANI/CuO) nanocomposites, with a specific focus on how controlled CuO incorporation (0.5 to 1.25 mol%) tunes their microstructural, dielectric, and charge transport characteristics. The key innovation of this work lies in establishing a direct correlation between CuO-induced lattice expansion and the evolution of charge transport mechanisms, revealing a tunable microstructural-dielectric coupling. X-ray diffraction confirmed successful composite formation, revealing a significant lattice expansion and an optimized microstructure with increased crystallite size and reduced micro-strain. Dielectric spectroscopy demonstrated a remarkable enhancement in the dielectric constant and revealed a distinct interfacial polarization peak. The analysis of AC conductivity identified Overlapping Large-Polaron Tunneling as the dominant charge transport mechanism, a finding further supported by the calculated trends in hopping distance. Complex impedance analysis confirmed non-Debye relaxation behavior and visualized the critical role of interfacial effects, which transition from blocking to conductive with increasing temperature. The PANI/CuO-1 mol composite emerged as the optimal candidate, achieving an ideal balance between high charge storage and efficient transport. This work not only advances the fundamental understanding of charge dynamics in hybrid systems but also underscores the potential of these tailored nanocomposites for high-performance capacitive and optoelectronic applications.
A‐Site Cation‐Regulated <i>Operando</i> Restructuring of Cu‐Based Perovskite Oxides for Selective Carbon Monoxide Electroreduction
Abstract Understanding the correlation between surface catalytic motifs and electrochemical reaction pathways is crucial for the rational design of high‐performance electrocatalysts, yet remains hindered by the dynamic reconfiguration of active sites under operating conditions. In this study, we establish a tunable platform based on a series of Cu‐based perovskite oxides with systematically varied A‐site cations to investigate how A‐site chemistry regulates the structural dynamics of Cu and its interplay with the carbon monoxide reduction (COR) pathway. Operando spectroscopic analyses reveal that those perovskites with alkaline‐earth A‐site cations promote Cu clustering into metallic states, favoring multicarbon product formation. In contrast, rare‐earth A‐site perovskites stabilize surface Cu + species through strong Cu–O interactions, thereby enhancing the selectivity of methane. Complementary theoretical calculations further demonstrate that the Cu─O bond strength—modulated by A‐site composition—dictates the electrochemical stability of Cu active sites. These findings underscore the pivotal role of local coordination environments in steering catalyst reconstruction and product distribution, and provide guiding principles for A‐site engineering in perovskite‐based COR catalysts.
Modeling, simulation, and optimization behavior of pharmaceutical compound removal from water in SR-AOPs technique for wastewater treatment
Four Cytochrome P450 Enzymes Mediate Oxidation Cascades in the Biosynthesis of Cephalotane‐Type Diterpenoids
Abstract Cephalotane‐type diterpenoids, a class of natural products exclusively found in Cephalotaxus plants, are well known for their attractive structures and potent biological activities. However, their low natural abundance and intricate cage‐like structures hinder their accessibility. Recently, the identification of a cephalotene synthase ( Cs CTS) has addressed the first committed step in the biosynthesis. However, the enzymes involved in the complex post‐modification of the cephalotene core into structurally diverse cephalotane‐type diterpenoids remain obscure. In this study, we functionally characterised four novel cytochrome P450 enzymes from C. sinensis . These enzymes demonstrate multiple oxidative functions and cooperatively catalyse a cascade of oxidation reactions, including the formation of signature 13,17‐lactone, 5,19‐lactone, and tropone. We further co‐expressed the characterised CYP450 enzymes in combination with Cs CTS to produce a variety of cephalotane‐type diterpenoids, including hainanolidol ( 2 ), mannolide C ( 3 ), mannolide A ( 4 ), and cephinoid H ( 5 ), in Nicotiana benthamiana . Subsequently, harringtonolide ( 1 ) was chemically converted from hainanolidol (3.9 µmol with 10 equiv of Pb(OAc) 4 ) in 87.5% yield. In this study, the biosynthetic pathways of representative cephalotane‐type diterpenoids were elucidated and reconstructed, thereby establishing a foundation for their sustainable production through biosynthesis and/or chemo‐biosynthesis, highlighting the remarkable efficiency of merely five Cephalotaxus ‐specific enzymes in assembling such structurally complex natural products.
Deep learning based thyroid prediction with opposition learning based red panda optimization feature selection
Explainable machine learning model and gene expression programming for predicting reinforced concrete beams moment capacity exposed to fire
Abstract In this study, a new formulation for the moment capacity ( M r ) of Reinforced Concrete (RC) beams under fire conditions is estimated using Gene Expression Programming (GEP). In addition, the use of Machine Learning (ML) methods such as XGBoost, AdaBoost, and LightGBM is investigated for estimating the M r of RC beams in fire. The database for predicting the M r of RC beams includes 280 samples. In this paper, the cross-section width b w , cross-section depth d , distance from the beam edge to the center of steel reinforcement d eff , area of steel reinforcement A st , time duration of fire t , compressive strength of concrete f c , and moment capacity of the beam under fire M r are considered as the parameters of ML models. Several statistical metrics were employed to assess the performance of the models, including the mean absolute error ( MAE ), mean square error ( MSE ), root mean square error ( RMSE ), coefficient of determination ( R 2 ), and gradients of regression lines ( k and k ′). In this study, Shapley Additive exPlanations (SHAP) analysis was used to interpret the predictions of the XGBoost model, which was selected for its high accuracy with the best R 2 and the lowest error rate. The results indicate that the methods used demonstrate high accuracy in estimating the M r of RC beams.
Mechanical Constraints Promote Noncanonical Base‐Pairing Interactions
Abstract Mechanical perturbations profoundly influence nucleobase interactions in cells, serving as key modulators of fundamental cellular processes such as transcriptional regulation. However, their precise roles remain elusive due to methodological limitations. Here, we have developed a DNA origami‐based nanobender system that probes base–base interactions under mechanical constraints. This system imposes tunable geometric and mechanical constraints on single‐stranded DNA/RNA by pulling its two ends together while adjusting its contour length, and enables the assessment of weak interactions between bases through the detection of DNA origami dimerization. Combining experiments and molecular dynamics simulations, we speculate that mechanical constraints promote stacking‐driven noncanonical base‐pairing via entropy compensation and favorable nucleobase orientation (hydrophobic exposure), advancing our understanding of base recognition diversity. Customizable nanobender parameters allow investigation of the effects of geometric and mechanical constraints on hybridization thermodynamics across DNA‐DNA, RNA‐RNA, DNA‐RNA, and epigenetically modified nucleotides. Notably, we suggest that entropy modulation mediated by mechanical constraints enables fine‐tuning of binding free energy, thereby expanding material assembly applications while conferring environmental sensitivity.
Heavy metal in cosmetics and its risk to future generation in remote area of Azad Jammu and Kashmir Trarkhel District Sudhnoti
Machine Learning‐Driven Automated Synthesis of Polysubstituted Gentisaldehydes
Abstract Gentisaldehyde is a fundamental motif with broad applications in pharmaceuticals. However, the construction of such molecules is time‐ and cost‐intensive with low step efficiency. The development of a disruptive retrosynthetic method is therefore highly necessary to enhance ring‐formation capability and reduce redundancy in synthetic strategies. Herein, guided by cutting‐edge computer‐aided synthesis planning (CASP) algorithms, synthetic routes were systematically deduced toward polysubstituted gentisaldehydes (PGAs). An automated flow system was subsequently developed to implement the streamlined synthesis via selective 6‐endo cyclization of cyclobutenedione derivatives and propargyl diacetal moieties. DFT computational studies further revealed the involvement of diradical intermediates, rather than the conventional zwitterionic mechanism, and identified the 1,5‐hydrogen atom transfer process as the key driving force. The rapid and collective construction of a gram‐scale library of PGAs highlights the industrial potential for scalability and application. This work demonstrates the synergistic interplay among computational retrosynthetic analysis, mechanistic elucidation, and flow processing, establishing an innovative model for universally integrated molecule library construction.
Enhanced DEWMA-type control chart for process mean monitoring utilizing auxiliary information
Abstract Statistical Process Control (SPC) improves product quality by monitoring process performance, with control charts being the primary tool to detect and manage variability. The effectiveness of a control chart can be enhanced by incorporating additional pertinent information regarding the study variable. This study revisits the DEWMA chart, which is designed to monitor variations in the process mean under the assumption that the underlying process follows a normal distribution. We propose a Regression-based DEWMA (M R DEWMA) control chart that utilizes an auxiliary variable through a regression estimation method to determine the process mean. The control limits for the proposed chart are established based on both time-varying and asymptotic conditions. The features of run length (RL), including Average Run Length (ARL), Standard Deviation of Run Length (SDRL), and Median Run Length (MRL), are evaluated using Monte Carlo simulations. A comparative analysis reveals that the proposed M R DEWMA chart outperforms the traditional DEWMA chart in detecting small to moderate shifts in the process mean. The efficacy of the proposed approach is demonstrated using both Monte Carlo simulated data and a real-life industrial case study.
Self‐Adaptive Interface Reconstruction over Black Phosphorus Complex for Wide‐Temperature and Fast‐Charging Potassium Ion Storage
Abstract Black phosphorus (BP), exhibiting a large spatial layer and high theoretical capacity, has been heralded as a promising candidate for K + storage. Nevertheless, the unpredictability of the structural/interfacial reconstruction guides the arduous kinetics and poor stability, especially conferring to high current density and wide‐temperature operation. To address these challenges, self‐adaptive interface reconstruction with a multiple secondary bonds mediation (IRSM) strategy is adopted for amphipathic BP complex to improve kinetics and stability, wherein BP nanospheres encapsulated into a sacciform B‐doped carbon matrix (BC) are further grafted with polybromoisobutyryloxy benzenesulfonic (PBBS), which undergoes in situ polymerization and is transformed into metal‐organic bromoisobutyrylox supramolecular (PBS). Consequently, combining the flexibility/rigidity advantage of organic moiety and the stability advantage of inorganic moiety, BC@BP@PBS manifests excellent fast charging behaviors, a wide‐temperature operation from −70 °C to 80 °C, and an extended cycle life of up to 1300 cycles. This work builds an ingenious protocol for leveraging the trade‐off between fast charging, wide‐temperature operation, and long life span for high‐performance cell devices.
Textbook outcomes after splenectomy in patients with portal hypertension
Hyperbranched Oxime‐Ester Covalent Adaptive Network for Recyclable Ultralow‐Dielectric Epoxy
Abstract Epoxy thermosets are indispensable in high‐frequency (5G/6G) electronics, but their permanent crosslinks hinder recyclability and worsen e‐waste. Although covalent adaptable networks (CANs) offer recyclability, their polar dynamic bonds exacerbate dielectric losses at gigahertz (GHz) bands due to dipolar relaxation. Here, we develop generation‐tunable dendritic dynamic crosslinkers that yield recyclable epoxy‐based printed circuit board (PCB) with ultralow dielectric performance. O ‐acylation reaction of a vanillin‐derived tetrahedral aldoxime with phthalic anhydride affords precise control over generations, branching degree, and nanomorphology of the crosslinkers. This controlled synthesis yields porous coral‐like architecture, which in turn produces graded‐branched epoxy CANs with enhanced free volume and steric confinement. Within the rigid constrained topology, the network containing spherically distributed oxime‐ester motifs exhibits restricted dipolar relaxation and achieves low dielectric loss in GHz bands, while remaining acid‐cleavable for closed‐loop recycling at 80 °C. The resulting PCB exhibits a record‐low dielectric constant/loss (2.02/0.005@10 GHz), 71.53% improved X‐band impedance matching, a tensile strength of 256 MPa, and V‐0 flame retardancy, alongside a 98.9% reduction in ecotoxicity after recycling. This work demonstrates how precision dendrimer synthesis and topology regulation can reconcile the tradeoff between circularity and high‐frequency performance in sustainable electronics.
Effect of process parameters on surface integrity in laser powder bed fusion of Ti-6Al-4V alloy
Proteome-wide mendelian randomization reveals circulating proteins causally associated with childhood body mass index
Abstract Childhood obesity is a major public health problem, affecting one in 5 youths. We aimed to characterize biomarkers for pediatric obesity among circulating proteins using Mendelian randomization (MR). We utilized genome-wide significant cis-protein quantitative trait loci (pQTL) from three large adult proteomic GWAS (N total>58,000) and a small childhood proteomic GWAS (N=2,147) as genetic instruments for circulating protein levels. Using two-sample Mendelian randomization, we estimated causal effects of the circulating proteins on childhood body mass index (BMI) in a European GWAS of 39,620 children. MR Wald ratios were calculated to estimate the causal effect of each protein on childhood BMI. Sensitivity analyses testing the MR assumptions included colocalization and phenome-wide association studies (PheWAS). Replication was conducted using independent GWAS datasets, complemented by reverse MR and tissue enrichment analyses. Among 535 tested proteins, three colocalized and demonstrated decreasing effects on BMI per standard deviation increase in their level: endoglin (ENG; MR beta: -0.07, 95% CI [-0.10, -0.04], P=4.4×10⁻ 5 ), fatty acid binding protein 4 (FABP4; MR beta: -0.33, 95% CI [-0.50, -0.16], P=1.3×10⁻ 4 ), and cell adhesion molecule 1 (CADMI1; MR beta: -0.26, 95% CI [-0.37, -0.15], P=5.45×10⁻ 5 ). All three proteins showed evidence of colocalization (posterior probability >75%) and were identified using adult proteomic GWAS, given a limited statistical power using the pediatric proteomic GWAS data. Reverse causation was identified for FABP4, suggesting a compensatory mechanism. In conclusion, we identified three circulating proteins as potential blood biomarkers or drug targets for pediatric obesity, warranting further functional validation to elucidate biological mechanisms and assess therapeutic potential.
Functionalization of Polyolefins via Catalytic Nitrene Addition
Abstract The post‐polymerization functionalization of polyolefins has emerged as a key tool for obtaining new materials with enhanced properties. With an array of approaches being already reported, the incorporation of N‐containing fragments en route to the generation of amino groups in yet scarce and not disclosed for the metal‐catalyzed nitrene transfer strategy. Here we introduce such tactics employing silver‐based catalysts for the incorporation of nitrene NTs (Ts = p ‐toluenesulfonyl) groups to commercially available polybutadienes. The process occurs at room temperature without appreciable chain scission or cross‐linking processes and enables precise control of the degree of functionalization. Thermal analyses demonstrate a correlation between such degree and the T g values of the functionalized polymers.