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Conductive nanofiltration (CNF) membranes hold great promise for removing small organic pollutants from water through enhanced Donnan exclusion and electrocatalytic degradation. However, current CNF membranes face limitations in conductivity, structural stability, and nanochannel control strategies. This work addresses these challenges by introducing aniline-functionalized carbon nanotubes (NH2-CNTs) as an interlayer. NH2-CNTs enhance the dispersibility and adhesion of pristine carbon nanotubes, leading to a more conductive and stable composite nanofiltration membrane. The redesigned NH2-CNTs interlayered conductive nanofiltration (NICNF) membrane exhibits a 10-fold increase in conductivity and a high response degree (80%) with excellent cyclic stability, surpassing existing CNF membranes. The synergistic effects of enhanced Donnan exclusion, voltage switching, and electrocatalysis enable the NICNF membrane to achieve selective recovery of mixed dyes, 98.97% removal of residual wastewater toxicity, and a 5.2-fold increase in permeance compared to the commercial NF270 membrane. This research paves the way for next-generation multifunctional membranes capable of the efficient recovery and degradation of toxic organic pollutants in wastewater.

Background and Objectives: Smoothened (SMO), a key component of the hedgehog signaling pathway, represents a therapeutic target for triple negative breast cancer (TNBC), yet the chemotherapy response rate in TNBC patients is only 40–50%, underscoring the urgent need for the development of novel drugs to effectively treat this condition. The novel compound TPB15, an SMO inhibitor derived from [1,2,4] triazolo [4,3-α] pyridines, demonstrated superior anti-TNBC activity and lower toxicity compared to the first SMO inhibitor vismodegib in both in vitro and in vivo. However, the compound's pharmacokinetic properties remain unclear. The present work aims to develop a simple HPLC-MS/MS method to profile the pharmacokinetics and bioavailability of TPB15 in rats as a ground work for further clinical research. Methods: Separation was performed on an Agilent ZORBAX StableBond C18 column by gradient elution using acetonitrile and 0.1% formic acid as mobile phase at a flow rate of 0.3 mL/min. Multiple reaction monitoring(MRM) in positive mode with the transitions of m/z454.2 → 100.0, 248.1 → 121.1 was employed to determine TPB15 and internal standard tinidazole, respectively. The specificity, intra- and inter- day precision and accuracy, extraction recovery, stability, matrix effect, dilution integrity and carryover of the method was validated. The pharmacokinetics and bioavailability  study of TPB15 were carried out on rats through intravenous injection at the dose of 5 mg/kg and oral gavage at the dose of 25 mg/kg, and the pharmacokinetics parameters were calculated by the non-compartment analysis using the pharmacokinetics software DAS 2.1.1. Results: The values of specificity, intra- and inter- day precision and accuracy, extraction recovery, stability, matrix effect, dilution integrity and carryover satisfied the acceptable limits. The lower limit of quantification of this method was 10 ng/mL with a linear range of 10–2000 ng/mL. The validated method was then applied to pharmacokinetics and bioavailability studies in rat by dosing with gavage (25 mg/kg) and intravenous injection(5 mg/kg), and the oral bioavailability of TBP15 in rat was calculated as 16.4 ± 3.5%. The pharmacokinetic parameters were calculated as following: maximum of plasma concentration (Cmax) (PO: 2787.17 ± 279.45 µg/L), Time to maximum plasma concentration (Tmax) (PO: 4.20 ± 0.90 h), the area under the concentration-time curve 0 to time (AUC0–t) (PO: 17,373.03 ± 2585.18 ng/mL·h, IV: 21,129.79 ± 3360.84 ng/mL·h), the area under the concentration-time curve 0 to infinity (AUC0–∞) (PO: 17,443.85 ± 2597.63 ng/mL·h, IV: 17,443.85 ± 2597.63 ng/mL·h), terminal elimination half-life (t1/2) (PO: 7.26 ± 2.16 h, IV: 4.78 ± 1.09 h). Conclusions: TPB15, a promising candidate for treating TNBC, has demonstrated outstanding efficacy and safety in vitro and in vivo. This study established a simple, sensitive, and rapid HPLC-MS/MS bioanalytical method, developed and validated in accordance with FDA and EMA guidelines, for conducting pharmacokinetic and bioavailability studies of TPB15. The results revealed a favorable pharmacokinetic profile owing to its long t1/2. Nevertheless, the next phase of research should include formulation screening to enhance bioavailability, as well as clinical trials, metabolism pathway analysis, and assessment of potential drug-drug interactions.

Platinum(II) drugs as a first-line anticancer reagent are limited by side effects and drug resistance. Stimuli-responsive nanosystems hold promise for precise spatiotemporal manipulation of drug delivery, with the aim to promote bioavailability and minimize side effects. Herein, a multitargeting octahedral platinum(IV) prodrug with octadecyl aliphatic chain and histone deacetylase inhibitor (phenylbutyric acid, PHB) at axial positions to improve the therapeutic effect of cisplatin was loaded on the upconversion nanoparticles (UCNPs) through hydrophobic interaction. Followed attachment of DSPE-PEG2000and arginine-glycine-aspartic (RGD) peptide endowed the nanovehicles with high biocompatibility and tumor specificity. The fabricated nanoparticles (UCNP/Pt(IV)-RGD) can be triggered by upconversion luminescence (UCL) irradiation and glutathione (GSH) reduction to controllably release Pt(II) species and PHB, inducing profound cytotoxicity. Both in vitro and in vivo experiments demonstrated that UCNP/Pt(IV)-RGD exhibited remarkable antitumor efficiency, high tumor-targeting specificity, and real-time UCL imaging capacity, presenting an intelligent platinum(IV) prodrug-loaded nanovehicle for UCL-guided dual-stimuli-responsive combination therapy.

This article proposes a multiscale convolutional residual neural network algorithm with attention mechanisms for early interturn short circuit (ITSC) fault diagnosis of five-phase permanent magnet synchronous motors (FPPMSMs). First, a multiscale convolutional neural network with channel attention is used to highlight the fault features. Second, a spatial attention residual module is developed to improve feature learning performance, which can alleviate the problem of disappearing gradients and further enhance the fault features in the feature map. Finally, a self-attention structure is adopted to reduce reliance on manually set parameters, capture the internal correlation of features, and improve the interpretability of the network model. Experiments on ITSC faults of FPPMSM are carried out. The experimental results and the comparison with the other four methods highlight the superiority of the proposed method.

Noise can have a negative impact on the performance of dc–dc converters with continuous control set model predictive control (CCS-MPC). This issue is commonly encountered, making it difficult to effectively apply CCS-MPC in dc–dc converters. In this letter, we present a noise tolerance method for dc–dc converters with CCS-MPC that utilizes a virtual capacitor. This method offers a simple and effective solution to address the aforementioned problem while enhancing system robustness. To illustrate, we examine the noise generation mechanism and establish a predictive model using a dual-active-bridge converter as an example. Subsequently, we delve into the influence of noise on MPC and propose a noise tolerance method centered around the virtual capacitor. Importantly, this method does not incur additional costs, computational burden, or voltage/current ripples in the system, while preserving the inherent dynamic performance of MPC. Finally, we validate the effectiveness of the proposed method through experimental results using the TMS320F28377D as the core controller.

Alloy material corrosion is a comprehensive problem affected by multi-dimensional factors, including the time, environment, and material element. Its corrosion prediction has been facing the challenges of complex mechanism and small sample size. However, parametric methods are limited in terms of modeling accuracy and generalization performance for high-dimensional feature problems. Non-parametric machine learning algorithms, while having excellent modeling capabilities, need to be optimized in conjunction with the structure of the corrosion problem. Therefore, we develop a two-stage hybrid intelligent machine learning model for improving alloy corrosion prediction accuracy. The model takes the time, environment, and material information of the alloy corrosion process as inputs and the corrosion rate as output. The first stage of the model utilizes tree ensemble learning (TEL) models for initial prediction modeling and feature importance knowledge mining. In the second stage, the neural network (NN) is used to enhance the fusion of the multi-model prediction outputs, and it is optimized using feature importance modification (FIM). The proposed TEL-FIMNN model shows considerable performance improvement over the TEL and ANN models on real low-alloy steel corrosion dataset. Compared to other advanced multi-model fusion methods such as linear regression (LR), support vector regression (SVR), random forest (RF), and Bayesian model averaging (BMA), the proposed model also shows superior results. The TEL-FIMNN model provide a new structure from the perspectives of knowledge mining and fusion enhancement, which has good potential for multi-dimensional corrosion prediction.

This study builds upon the success achieved from commercial self-assembled monolayers (SAMs), such as Me-4PACz, by replacing its flexible butyl linker with a conjugated phenylene ring to form a SAM molecule, Me-PhpPACz, for inverted perovskite solar cells (PSCs). The Me-PhpPACz-derived PSCs exhibited an unprecedented power conversion efficiency of 26.17% with an extremely high fill factor of 86.79% and exceptional long-term stability. The result from ultrafast spectroscopy shows that phenylene-linked SAMs not only modulate the work function of indium tin oxide electrode but also facilitate charge carrier extraction and transport. Our detailed study helps deepen our understanding of the delicate relationship between SAM molecular design and PSC performance, paving the way for further enhancing the efficiency and stability of PSCs.

Study design: Cross-sectional study. Objectives: To study the relationship between the structural changes in the cervical spinal cord (C2/3 level) and the sensorimotor function of children with traumatic thoracolumbar spinal cord injury (TLSCI) and to discover objective imaging biomarkers to evaluate its functional status. Setting: Xuanwu Hospital, Capital Medical University, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, China. Methods: 30 children (age range 5–13 years) with TLSCI and 11 typically developing (TD) children (age range 6–12 years) were recruited in this study. Based on whether there is preserved motor function below the neurological level of injury (NLI), the children with TLSCI are divided into the AIS A/B group (motor complete) and the AIS C/D group (motor incomplete). A Siemens Verio 3.0 T MR scanner was used to acquire 3D high-resolution anatomic scans covering the head and upper cervical spinal cord. Morphologic parameters of the spinal cord at the C2/3 level, including cross-sectional area (CSA), anterior-posterior width (APW), and left-right width (LRW) were obtained using the spinal cord toolbox (SCT; https://www.nitrc.org/projects/sct). Correlation analyses were performed to compare the morphologic spinal cord parameters and clinical scores determined by the International Standard for Neurological Classification of Spinal Cord Injuries (ISNCSCI) examination. Results: CSA and LRW in the AIS A/B group were significantly lower than those in the TD group and the AIS C/D group. LRW was the most sensitive imaging biomarker to differentiate the AIS A/B group from the AIS C/D group. Both CSA and APW were positively correlated with ISNCSCI sensory scores. Conclusions: Quantitative measurement of the morphologic spinal cord parameters of the cervical spinal cord can be used as an objective imaging biomarker to evaluate the neurological function of children with TLSCI. Cervical spinal cord atrophy in children after TLSCI was correlated with clinical grading; CSA and APW can reflect sensory function. Meanwhile, LRW has the potential to be an objective imaging biomarker for evaluating motor function preservation.

Extracellular vesicles released by probiotics have been demonstrated to effectively alleviate intestinal inflammation, yet the precise underlying mechanisms remain unclear. In this research, for the first time, Lactobacillus plantarumUJS001 (LP-UJS) was isolated from fermented sauerkraut in Zhenjiang, China. Thereafter, the therapeutic effect of LP-UJS-derived extracellular vesicles (LP-UJS-EVs) on dextran sulfate sodium-induced ulcerative colitis (UC) in mice was analyzed to elucidate the immune mechanisms. According to our findings, LP-UJS-EVs played a pivotal role in restoring the intestinal barrier and alleviating intestinal inflammation. Notably, LP-UJS-EVs induced M2 polarization of macrophages, promoted the release of IL-10 and TGF-β, inhibited the release of histamine, IL-6, and TNF-α, and exerted regulatory effects on intestinal microflora, as evidenced by the reduced abundances of Coprococcus, Parabacteroides, Staphylococcus, and Allobaculum, alongside the enhanced abundance of Prevotella. Furthermore, both LP-UJS and LP-UJS-EVs affected the lysine degradation pathway and significantly increased the abundance of related metabolites, especially oxoadipic acid. In summary, our results underscore the substantial therapeutic potential of LP-UJS and its secreted EVs in the treatment of UC.

Selective electrodialysis (SED) has surfaced as a highly promising membrane separation technique in the realm of acid recovery owing to its ability to effectively separate monovalent ions through the utilization of a potential difference. However, the current SED process is limited by conventional commercial monovalent cation permselective membranes (MCPMs). This study systematically investigates the use of an independently developed MCPM in the SED process for acid recovery. Various factors such as current density, volume ratio, initial ion concentration, and waste acid systems are considered. The independently developed MCPM offers several advantages over the commercial monovalent selective cation-exchange membrane (CIMS), including higher recovered acid concentration, better ion flux ratio, improved acid recovery efficiency, increased recovered acid purity, and higher current efficiency. The SED process with the MCPM achieves a recovered acid of 95.9% and a concentration of 2.3 mol·L–1in the HCl/FeCl2system, when a current density of 20 mA·cm−2and a volume ratio of 1:2 are applied. Similarly, in the H2SO4/FeSO4system, a purity of over 99% and a concentration of 2.1 mol·L–1can be achieved in the recovered acid. This study thoroughly examines the impact of operation conditions on acid recovery performance in the SED process. The independently developed MCPM demonstrates outstanding acid recovery performance, highlighting its potential for future commercial utilization.

This article proposes a new method, simultaneously considering inter-turn short-circuit (ITSC) fault diagnosis and fault-tolerant control of a five-phase permanent magnet synchronous motor (FPMSM), to realize an online diagnosis and fault-tolerant operation. This article is focused on linking the signals required for fault-tolerant control with diagnostic algorithms. The method uses a disturbance observer to obtain the disturbance signal from the ITSC and directly utilizes the fault characteristics in the disturbance signal for fault-tolerant control. No additional fault parameters (short-circuit current and short-circuit turn ratio) and no additional hardware equipment are required in this process while reducing the complexity of the fault-tolerant control method of FPMSM. In addition, since fault-tolerant reference current and injected current are both ac signals, the deadbeat current prediction control is constructed for fault conditions to track the signals accurately. The effectiveness and feasibility of the method are verified by simulation and experiment.

Cells employing PPTU binder exhibit exceptional rate performance and excellent cycling stability. Through various techniques including XPS and SXCT, we attribute these improvements to the binder's remarkable conductivity and effective absorption of LiPSs, thereby suppressing the detrimental shuttle effect.

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This article proposes an auxiliary notch design method for the interior permanent magnet (IPM) machines for suppressing torque ripple. The key principle of this design method is to identify the main source of torque ripple, then guides the modification of reluctance variation along the rotor surface. First, the theoretical analysis of the torque ripple in IPM machines are investigated to guide the auxiliary notches design. Based on this, a spoke-type IPM machine with permanent magnet torque as the main component and a U-type IPM machine dominated by reluctance torque are analyzed, respectively. Additionally, the relationship between the shifted angle of the auxiliary notch and the order of torque ripple is revealed. Furthermore, the electromagnetic performances are investigated by the finite-element method. After using auxiliary notch design, the torque ripple is significantly reduced and the torque amplitude is almost not sacrificed. Finally, a spoke-type IPM machine prototype is manufactured for experiments to evaluate the effectiveness of the theoretical analysis.

Hydrogen sulfide (H2S) is an important endogenous gas transmitter that plays a critical role in various physiological and pathological processes and can also cause a negative impact on foodstuffs. In this study, we designed and synthesized a simple, easily available, high-yield, and low-cost near-infrared (λem= 710 nm) fluorescent probe, DEM-H2S, with a substantial Stokes shift (205 nm) for the detection of H2S. DEM-H2Sfeatures high selectivity and sensitivity (LOD = 80 nM) toward H2S, accompanied by a noticeable color change. Upon interaction with H2S, DEM-H2Sexhibits a restored ICT (Intramolecular Charge Transfer) process, thereby manifesting near-infrared fluorescence. DEM-H2Shas been successfully utilized to detect H2S in actual water samples and to monitor the spoilage of food items, such as pork, shrimp, and eggs. Furthermore, DEM-H2Senables the imaging of endogenous and exogenous H2S in living MCF-7 cells and zebrafish. Hence, DEM-H2Sprovides an attractive method for the detection of H2S in environmental, food, and biological systems, holding potential value in physiological and pathological research.

We explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

•ECP constitutes a promising therapeutic approach for GVHD after CAR T-cell infusion.•ECP reduces alloreactivity without compromising the functionality of CAR-T cells.

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

The fringe field effect in liquid crystal (LC) devices can cause pixel crosstalk issues. Therefore, LC devices with multiple electrode structures require multiple calibrations to achieve an approximate distribution of the target phase modulation. At the same time, optical inverse design based on data‐driven algorithms is also a highly popular topic. This article introduces a deep‐learning approach to realize inverse phase modulation in LC devices. By adopting the deep learning method for inverse phase modulation in LC devices, can effectively alleviate the problems caused by fringe field effects and achieve more precise and accurate phase modulation distribution.

Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6–8 weeks postpartum. Residential PM2.5and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction= 0.003). In the quantile-based g-computation model, NO3–consistently contributed to the combined effect of PM2.5components on gestational and postpartum FPG. This study was the first to suggest that PM2.5components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5components are essential to improving maternal glucose metabolism.

Identifying next-generation batteries with multivalent ions, such as Ca2+is an active area of research to meet the increasing demand for large-scale, renewable energy storage solutions. Despite the promise of higher energy densities with multivalent batteries, one of their main challenges is addressing the sluggish kinetics in cathodes that arise from stronger electrostatic interactions between the multivalent ion and host lattice. In this paper, zircons are theoretically and experimentally evaluated as Ca cathodes. A migration barrier as low as 113 meV is computationally found in YVO4, which is the lowest Ca2+barrier reported to date. Low barriers are confirmed across 18 zircon compositions, which are related to the low coordination change and reduced interstitial site preference of Ca2+along the diffusion pathway. Among the four materials (BiVO4, YVO4, EuCrO4, and YCrO4) that were synthesized, characterized, and electrochemically cycled, the highest initial capacity of 81 mA h/g and the most reversible capacity of 65 mA h/g were achieved in YVO4and BiVO4, respectively. Despite the facile migration of multivalent ions in zircons, density functional theory predictions of the unstable, discharged structures at higher Ca2+concentrations (Cax>0.25ABO4), the low dimensionality of the migration pathway, and the defect analysis of the B site atom can rationalize the limited intercalation observed upon electrochemical cycling.

Objectives: To evaluate the cost-effectiveness of three permanent vascular accesses for maintenance hemodialysis patients from a hospital perspective throughout 5 years, which is the average life expectancy of patients with end-stage kidney disease.Subjects and methods: We conducted a EuroQol(EQ-5D) questionnaire survey between January 2021 and March 2021 with 250 patients to estimate the health utility of various states in patients under different hemodialysis vascular access. We designed a Markov model and conducted a cost-effectiveness analysis to compare the cost-effectiveness of three hemodialysis vascular access in Guangzhou throughout 5 years.Results: The mean costs were US$44,481 with tunneled-cuffed catheter (TCC), and US$68,952 and US$59,247 with arteriovenous graft (AVG) and autogenous arteriovenous fistula (AVF), respectively. The mean quality-adjusted life-years (QALYs) was 1.41 with TCC, and 2.37 and 2.73 with AVG and AVF, respectively. AVG had an incremental cost-effectiveness ratio (ICER) of US$25,491 per QALY over TCC; AVF had an ICER of -US$26,958 per QALY over AVG. At a willingness to pay below US$10,633.8 per QALY, TCC is likely the most cost-effective vascular access. At any willingness to pay between US$10,633.8 and US$30,901.4 per QALY, AVF is likely the most cost-effective vascular access.Conclusion: These findings illustrate the value of AVF given its relative cost-effectiveness to other hemodialysis modalities. Although AVG costs much more than TCC for slightly higher QALYs than TCC, AVG still has a greater advantage over TCC for patients with longer life expectancy due to its lower probability of death.

Coactivator-associated arginine methyltransferase 1 (CARM1), an important member of type I protein arginine methyltransferases (PRMTs), has emerged as a promising therapeutic target for various cancer types. In our previous study, we have identified a series of type I PRMT inhibitors, among which ZL-28-6 (6) exhibited increased activity against CARM1 while displaying decreased potency against other type I PRMTs. In this work, we conducted chemical modifications on compound 6, resulting in a series of (2-(benzyloxy)phenyl)methanamine derivatives as potent inhibitors of CARM1. Among them, compound 17edisplayed remarkable potency and selectivity for CARM1 (IC50= 2 ± 1 nM), along with notable antiproliferative effects against melanoma cell lines. Cellular thermal shift assay and western blot experiments confirmed that compound 6effectively targets CARM1 within cells. Furthermore, compound 17edisplayed good antitumor efficacy in a melanoma xenograft model, indicating that this compound warrants further investigation as a potential anticancer agent.

Covalent organic polymers (COPs) have emerged as a promising class of materials for memory devices due to their unique electronic properties and potential for tunability. This review highlights recent advances in the field of COPs‐based thin films for memory applications, with a focus on the synthesis and characterization of COP thin films, their electronic properties, and their performance as memory devices. The potential of COPs‐based thin films as flexible memory devices is also discussed. Overall, the recent progress in COPs‐based thin films for memory applications suggests that these materials may have a significant impact on the development of next‐generation memory technologies. This review highlights recent advances in the field of COPs‐based thin films for memory applications, with a focus on the synthesis and characterization of COP thin films, their electronic properties, and their performance as memory devices.

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During the 2008-09 financial crisis, the U.S. government arranged bailouts of major banks to prevent a suspension of bank deposits, where banks cease paying checks and refuse depositors' requests to withdraw funds. Although these bailouts likely helped firms and households continue to make payments, they have been debated due to potential moral hazard concerns as well as the high cost to taxpayers. Assessing the costs and benefits of preventing deposit suspensions is difficult, as nationwide bank suspensions have not occurred since the Great Depression. To circumvent this challenge, Qian Chen, Christoffer Koch, Gary Richardson, and Padma Sharma study the effects of more recent deposit suspensions at the state level (Nebraska in 1983, Ohio and Maryland in 1985, and Rhode Island in 1991). They find that the suspension in Rhode Island, which occurred during a recession, lowered employment, gross state product, and per capital personal income. Their results suggest that interventions that prevent large deposit suspensions during recessions, such as those undertaken after 2008, are likely worth the costs. Effective interventions not only help avoid economic losses during recessions, but also prevent losses to output and employment several years into the future., During the 2008-09 financial crisis, the U.S. government acted quickly to prevent the commercial banking system from shutting down. Policymakers arranged bailouts of major banks to prevent a suspension of [...]

In the field of oxide thermoelectrics, perovskite CaMnO3ceramics have drawn plenty of attention due to their chemical stability, low cost, and environmental friendliness. By employing Ruddlesden–Poppe phase Ca3Mn2O7as a precursor, the plate-like CaMnO3microcrystals were successfully synthesized by the molten salt method combined with topochemical microcrystal conversion (TMC). The plate-like morphology of CaMnO3was coordinately optimized by modulating the crystal structure of MnO2and the molten salt environment. Plate-like microcrystals with an average size of ~14.55 µm and a thickness of ~2.89 µm were obtained by TMC reaction, demonstrating an obvious anisotropy. When ß-MnO2was used as the raw material, a length–thickness ratio of 4.77 was obtained, which was attributed to the fact that CaMnO3inherited the plate-like morphology of the Ca3Mn2O7precursor during the TMC. The results confirm that the plate-like CaMnO3microcrystals with obvious anisotropy can provide excellent template seeds for high-quality CaMnO3-based textured ceramics.

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. We hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

A practical synthesis of valuable N-acyl anthranilic acids has been achieved via a silver-catalyzed imino-ketene generation from readily available anthranils and carboxylic acids. A wide range of carboxylic acids including sterically demanding aliphatic carboxylic acids, aromatic carboxylic acids, acrylic acids, and amino acids are compatible in this reaction. Moreover, this method can be used to modify drug molecules and natural products, such as ibuprofen, probenecid, and acetylglycine.

Lipid metabolism disorders commonly occur during menopause. Estrogen deficiency has been shown to lead to excessive energy intake and abnormal lipid metabolism in ovariectomized rats, resulting in obesity. Probiotics exhibit anti-obesity properties, and their underlying mechanism has been widely reported. In this study, we demonstrated the metabolic benefits of Lactobacillus plantarumCCFM1180 in suppressing appetite, controlling body weight, correcting obesity-induced abnormalities, enhancing liver lipid metabolism, and protecting liver function in estrogen-deficient rats. The mechanisms associated with the anti-obesity and anti-dyslipidemia effects of CCFM1180 on estrogen-deficient rats were clarified. The results showed that CCFM1180 dramatically reduced food intake by activating the expression of estrogen receptor alpha (ERα) and increasing the level of leptin in abdominal adipose tissue. These changes, combined with the increased butyrate concentration and recovered bile acid structure, helped enhance lipid metabolism. Additionally, CCFM1180 treatment was found to be safer than exogenous estrogen supplementation. Thus, L. plantarumCCFM1180 could be considered a new therapeutic strategy for preventing and alleviating menopausal lipid abnormalities.

Im Zuge der Digitalisierung werden neue digitale Ansätze für die Fabrikplanung und den Fabrikbetrieb entwickelt. Die Übergänge zwischen diesen beiden Lebenszyklusphasen und den jeweils verwendeten digitalen Modellen gehen mit Informationsbrüchen einher. In dieser Veröffentlichung wird eine mögliche Konvergenz des Building Information Models und des Digitalen Zwillings aufgezeigt. Anhand eines Anwendungsbeispiels wird demonstriert, wie eine Durchgängigkeit der Informationen erreicht werden kann.

In this study, a high-isolation and high-gain multiple-input multiple-output (MIMO) antenna array operating at 77 GHz is proposed. It consists of two columns of transmitting (TX) sawtooth linear antenna arrays and two rows of receiving (RX) sawtooth linear antenna arrays with a rectangle ring layout. Each TX and RX linear antenna array contains 12 and 24 antenna units, respectively. The TX and RX antenna units adopt the same topology of a metal cavity fed by a substrate-integrated waveguide (SIW) slot. We introduce several $3\times $ 3 metal pin arrays to increase the gain and isolation of the TX and RX antennas. The metal pin arrays surround the four edges of the metal cavity on the top surface, and adjacent metal cavities share two metal pin arrays. Simulated results reveal that the antenna units exhibit a broad bandwidth of 75.3–81 GHz with S 11 less than −15 dB. The boresight gains of the TX and RX antenna units surpass 12 dBi, and the isolation is around 42 dB at 75–81 GHz. To verify the antenna’s performance, four WR 12 waveguide ports are used to excite two adjacent TX and two adjacent RX antenna units. The measured voltage standing wave ratios (VSWRs) of the TX and RX antenna units are less than 2 at 75–81 GHz, and the measured isolation between adjacent antenna units is more than 37 dB. Moreover, the measured boresight gains and radiation efficiencies of the TX and RX antenna units are 10–11 dBi and 60%–70%, respectively. This high-gain and high-isolation MIMO antenna array can be used for millimeter-wave (MMW) automotive radar.

Microwave spectroscopy is crucial to chemical sensing, deep-space molecule hunting, as well as quantum mechanical studies. In order to make broadband measurement of rotational transitions convenient and affordable for most laboratories, a proof-of-concept miniaturized microwave spectrometer was designed and developed based on a common field-programmable gate array (FPGA) platform to mainly integrate a fast phase-locked microwave synthesizer board for local oscillator (LO) hopping, a direct digital synthesizing board for chirp pulsing and a homodyne quadrature-detection system for sideband identification, thus fulfilling the broadband and image rejection functions. Rotational spectra of three molecules, cyanoacetylene (HCCCN), dibenzofuran, and tert-butyl iodide, were measured during the instrumentation of this system-on-chip (SOC) design. The resulting prototype exhibited a single scan of its full bandwidth between 1.7 and 4.7 GHz by five local oscillator hops under one gas jet, with measurement accuracy of about 30 kHz and linewidth of about 250 kHz, comparable to many modern broadband designs but with much simpler and more compact apparatus structure. Although the operating range of the current version can only cover the ${S}$ -band, this FPGA-based integration idea can be readily extended to much higher frequency and might lead to a trend-setting perspective for both instrumentation and related scientific research.

This paper presents a novel distributed predefined-time optimization scheme consisting of the distributed optimization estimator and the local controller for the networked marine surface vehicles. Concretely, the distributed optimization estimator is developed to estimate the optimal solution on to the set constraints. In the local control layer, a sliding mode scheme is built to guarantee that the sailing states of networked marine surface vehicles can track the optimal signals obtained by the distributed optimization estimator. Besides, the regulating time of both the estimation and the local tracking process is independent of the initial system states and can be artificially determined by directly adjusting the sum of serval control parameters. Later, a singularity avoidance scheme is further designed to avoid the possible singularity problems of the local control layer. Finally, a simulation example is given to show the efficacy of the proposed distributed predefined-time optimization algorithm.

An absorptive frequency-selective reflector (AFSR) with a switchable reflection band is proposed to achieve a switch between absorption-reflection-absorption (A-R-A) mode and wideband absorption (WA) mode. The AFSR is composed of triangular hybrid resonators loaded with lumped resistors at the top layer, hexagonal patches loaded with PIN diodes at the bottom layer and a backed metal layer. The AFSR can be readily deployed as an antennas’ ground plane or reflector for RCS reduction, which is verified by a bow-tie antenna. Simulation and measured results show that the AFSR increases the antenna gain by 1.43 dB at 6 GHz compared to a perfect electric conductor ground. Besides, the AFSR significantly reduces the out-of-band RCS in two absorption bands when it operates at A-R-A mode. Both in-band and out-of-band RCS are reduced if it works at WA mode as the reflection band is switched off.

An aerobic oxidative cleavage of 1,3-diketones under visible light irradiation using an organic dye as a photocatalyst is disclosed. The newly developed reaction provides practical access to 1,2-diketones and (Z)-1,4-enediones in moderate to good yields with absolute regio- and stereoselectivity. Mechanistic studies of the reaction suggest that tetraketone intermediates might undergo a photocatalytic energy transfer from the excited photocatalyst to form biradical-like (n,π*) states of ketones.

Methicillin-resistant Staphylococcus aureus(MRSA) exhibits multiresistance to a plethora of antibiotics, therefore, accurate detection methods must be employed for timely identification to facilitate effective infection control measures. Herein, we construct a high-efficiency ratiometric electrochemiluminescent (ECL) biosensor that integrates multiple exonuclease (Exo) III-assisted cyclic amplification units for rapid detection of trace amounts of MRSA. The target bacteria selectively bind to the aptamer, triggering the release of two single-stranded DNAs. One released DNA strand initiates the opening of a hairpin probe, inducing exonuclease cleavage to generate a single strand that can form a T-shaped structure with the double strand connecting the oxidation–reduction (O–R) emitter of N-(4-aminobutyl)-N-ethylisoluminol gold (ABEI-Au). Consequently, ABEI-Au is released upon Exo III cleavage. The other strand unwinds the hairpin DNA structure on the surface of the reduction–oxidation (R–O) emitter ZIF-8@CdS, facilitating the subsequent release of a specific single strand through Exo III cleavage. This process effectively anchors the cathode-emitting material to the electrode. The Fe(III) metal-organogel (Fe-MOG) is selected as a substrate, in which the catalytic reduction of hydrogen peroxide by Fe(III) active centers accelerates the generation of reactive oxygen species and enhances signals from both ABEI-Au and ZIF-8@CdS. In this way, the two emitters cooperate to achieve bacterial detection at the single-cell level, and a good linear range is obtained in the range of 100–107CFU/mL. Moreover, the sensor exhibited excellent performance in detecting MRSA across various authentic samples and accurately quantifying MRSA levels in serum samples, demonstrating its immense potential in addressing clinical bacterial detection challenges.

Polymer patching on inorganic nanoparticles (NPs) enables multifunctionality and directed self-assembly into nonclosely packed optical and mechanical metamaterials. However, experimental demonstration of such assemblies has been scant due to challenges in leveraging patch-induced NP–NP attractions and understanding NP self-assembly dynamics. Here we use low-dose liquid-phase transmission electron microscopy to visualize the dynamic behaviors of tip-patched triangular nanoprisms upon patch-clasping, where polymer patches interpenetrate to form cohesive bonds that connect NPs. Notably, these bonds are longitudinally robust but rotationally flexible. Patch-clasping is found to allow highly selective tip–tip assembly, interconversion between dimeric bowtie and sawtooth configurations, and collective structural relaxation of NP networks. The integration of single particle tracking, polymer physics theory, and molecular dynamics simulation reveals the macromolecular origin of patch-clasping-induced NP dynamics. Our experiment–computation integration can aid the design of stimuli-responsive nanomaterials, such as topological metamaterials for chiral sensors, waveguides, and nanoantennas.

Purpose: The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system. Design/methodology/approach: The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis. Findings: This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems. Originality/value: By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

BackgroundThe relationships between various obesity measures and hypertensive disorders of pregnancy (HDP) remain inadequately explored, and their causal links are not well understood. This study aims to clarify these associations and investigate the mediating role of triglycerides.MethodsWe conducted a comprehensive meta-analysis of observational studies alongside Mendelian randomisation (MR) analysis to assess the impact of 10 obesity measures on HDP risk. Additionally, we evaluated the mediating effect of triglycerides.ResultsOur meta-analysis revealed significant associations between maternal prepregnancy overweight/obesity and increased risks of gestational hypertension (GH) (overweight: OR=1.98, 95% CI 1.83 to 2.15; obesity: OR=3.77, 95% CI 3.45 to 4.13) and pre-eclampsia (overweight: OR=1.78, 95% CI 1.67 to 1.90; obesity: OR=3.46, 95% CI 3.16 to 3.79). Higher maternal waist circumference (WC) was also linked to increased pre-eclampsia risk (OR=1.45, 95% CI 1.14 to 1.83). MR analyses indicated that each 1-SD increase in genetically predicted obesity measures (whole body fat mass, body fat percentage, trunk fat mass, trunk fat percentage, body mass index, WC, hip circumference) was associated with higher risks of GH and pre-eclampsia. Triglycerides mediated 4.3%–14.1% of the total genetic effect of these obesity measures on GH and pre-eclampsia risks.ConclusionsThis study demonstrates that various obesity measures are causally linked to increased HDP risk and highlights the mediating role of triglycerides. These findings could inform clinical practices and public health strategies aimed at reducing HDP through targeted obesity and triglyceride management.

Colorectal cancer represents the over-expression of TMEM16A and COX-2, offering a promising therapeutic strategy. Two Pt(iv) conjugates derived from Pt(ii) drug (cisplatin or oxaliplatin) and niflumic acid, complexes 1and 2, were designed and prepared to exert the positive impact of multiple biological targets of DNA/TMEM16A/COX-2 against colorectal cancer. Complex 2afforded higher cytotoxicity than 1and the combination of an intermediate of oxidized oxaliplatin and NFA against cancer cells A549, HeLa, MCF-7, and HCT116. Especially for colorectal cancer cells HCT116, 2was significantly more toxic (22-fold) and selective to cancer cells against normal HUVEC cells (4-fold) than first-line oxaliplatin. The outstanding anticancer activity of 2is partly attributed to its dramatic increase in cellular uptake, DNA damage, and apoptosis. Mechanistic studies indicated that 2inhibited HCT116 cell metastasis by triggering TMEM16A, COX-2, and their downstream signaling pathways, including EGFR, STAT3, E-cadherin and N-cadherin.

Peeling strength can comprehensively reflect slider track safety and is crucial in car seat safety assessments. Current methods for determining slider peeling strength are primarily physical testing and numerical simulation. However, these methods encounter the potential challenges of high costs and overlong time consumption which have not been adequately addressed. Therefore, the efficient and low-cost surrogate model emerges as a promising solution. Nevertheless, currently used surrogate models suffer from inefficiencies and complexity in data sampling, lack of robustness in local model predictions, and isolation between data sampling and model prediction. To overcome these challenges, this paper aims to set up a systematic framework for slider track peeling strength prediction, including sensitivity analysis, dataset sampling, and model prediction. Specifically, the interpretable linear regression is performed to identify the sensitivity of various geometric variables to peeling strength. Based on the variable sensitivity, a distance metric is constructed to measure the disparity of different variable groups. Then, the sparsity-targeted sampling (STS) is proposed to formulate a representative dataset. Finally, the sequentially selected local weighted linear regression (SLWLR) is designed to achieve accurate track peeling strength prediction. Additionally, a quantitative cost assessment of the supplementary dataset is proposed by utilizing the minimum adjacent sample distance as a mediator. Experimental results validate the efficacy of sequential selection and the weighting mechanism in enhancing localization robustness. Furthermore, the proposed SLWLR method surpasses similar approaches and other common surrogate methods in terms of prediction performance and data quantity requirements, achieving an average absolute error of 3.3 kN in the simulated test dataset.

The EAT-Lancet Commission has proposed a reference diet aiming to promote human health and environmental sustainability. Socioeconomic disadvantage and poor diet are well-known risk factors for dementia; however, whether the effect of this reference diet on dementia varies by socioeconomic status has not been investigated. The dietary habits of 190,893 participants from UK-Biobank were assessed; the association of EAT-Lancet diet with incident dementia across socioeconomic status was determined by Cox models. One thousand seven hundred twenty-eight dementia cases were identified during a median of 12.24 years follow-up. An inverse association between adherence to EAT-Lancet diet and all-cause dementia (high vs. low; hazard ratio [HR], 95% confidence interval [CI]: 0.82, 0.72–0.94) or late-onset dementia (high vs. low; HR, 95% CI: 0.78, 0.68–0.91) was observed only in individuals with high socioeconomic status. On the contrary, no protective effects of EAT-Lancet diet on early-onset dementia were observed, regardless of the socioeconomic status. Our findings indicated that adherence to an environment-friendly diet helps attenuate risk of dementia only in individuals with high socioeconomic level.

The majority of vehicle accidents are attributable to driver error, such as substance use, distractions, fatigue, speeding, and driving experience. Many of these driver errors are also associated with delay discounting, where individuals that excessively devalue a reward are more likely to use substances such as alcohol, cigarettes, and cocaine, and text-while-driving. The current study sought to examine a more direct association between delay discounting and driver error by providing 50 participants with a series of simulated driving tasks, along with measuring their delay discounting rates. A median-split for delay discounting rates showed that participants with high-delay discounting rates made significantly more total errors for simple driving tasks (e.g., braking and one-lane change) early during the simulation, relative to participants with low-delay discounting rates. On the other hand, high-delay discounting participants continued to make more total errors for a more complicated two-lane change driving task after multiple trials, relative to low-delay discounting participants. These results support the idea that delay discounting is a transdisease process that can significantly negatively affect a large range of health-related behaviors, including driver errors. Treatment implications for reducing driver errors are discussed.

Affective computing, representing the forefront of human–machine interaction, is confronted with the pressing challenges of the execution speed and power consumption brought by the transmission of massive data. Herein, we introduce a bionic organic memristor inspired by the ligand-gated ion channels (LGICs) to facilitate near-sensor affective computing based on electroencephalography (EEG). It is constructed from a coordination polymer comprising Co ions and benzothiadiazole (Co–BTA), featuring multiple switching sites for redox reactions. Through advanced characterizations and theoretical calculations, we demonstrate that when subjected to a bias voltage, only the site where Co ions bind with N atoms from four BTA molecules becomes activated, while others remain inert. This remarkable phenomenon resembles the selective in situactivation of LGICs on the postsynaptic membrane for neural signal regulation. Consequently, the bionic organic memristor network exhibits outstanding reliability (200 000 cycles), exceptional integration level (210pixels), ultra-low energy consumption (4.05 pJ), and fast switching speed (94 ns). Moreover, the built near-sensor system based on it achieves emotion recognition with an accuracy exceeding 95%. This research substantively adds to the ambition of realizing empathetic interaction and presents an appealing bionic approach for the development of novel electronic devices.

Molecular electronic devices require precise control over the flow of current in single molecules. However, the electron transport properties of single molecules critically depend on dynamic molecular conformations in nanoscale junctions. Here we report a unique strategy for controlling molecular conductance using shape-persistent molecules. Chemically diverse, charged ladder molecules, synthesized via a one-pot multicomponent ladderization strategy, show a molecular conductance (d[log(G/G0)]/dx≈ −0.1 nm−1) that is nearly independent of junction displacement, in stark contrast to the nanogap-dependent conductance (d[log(G/G0)]/dx≈ −7 nm−1) observed for non-ladder analogues. Ladder molecules show an unusually narrow distribution of molecular conductance during dynamic junction displacement, which is attributed to the shape-persistent backbone and restricted rotation of terminal anchor groups. These principles are further extended to a butterfly-like molecule, thereby demonstrating the strategy’s generality for achieving gap-independent conductance. Overall, our work provides important avenues for controlling molecular conductance using shape-persistent molecules.

Large Language Models (LLMs) have proven successful across a spectrum of speech-related tasks, such as speech recognition, text-to-speech, and spoken language understanding. Recently, the use of discretized speech features has gained attention as an efficient and compatible alternative to continuous features for LLMs. This is mainly due to their reduced storage requirements and better alignment of these features with LLM's input space. However, the typical practice of freezing the speech encoder during training poses challenges in bridging the modality gap between speech and text. To address this, we propose to use a mixed-scale re-tokenization layer, integrating multiple granularities in discretized speech features directly within the LLM's input module. Our experimental results demonstrated that the proposed method can effectively enhance the performance of ASR in the setting of continuous learning of an LLM, highlighting the importance of a meticulously designed input module for the integration of discretized speech features with an LLM.

Millimeter-wave (mmW) phase-locked loops (PLLs) prefer large loop bandwidth for suppressing more voltage-controlled oscillator (VCO) phase noise, which, in turn, degrades the level of rejection to reference spur. This article proposes a complementary mixing phase detector (CMPD) to relax the above tradeoff through the spur compensation technique. Distinct from traditional RC filtering, the CMPD realizes spur reduction by mutual harmonic rejection whose effectiveness is enhanced by a foreground calibration. It also neutralizes charge injection and clock feedthrough without consuming extra power, while enabling frequency detection and lock detection. Fabricated in a 28-nm CMOS technology, the PLL achieves a frequency tuning range (FTR) of 28.8-to-43.2 GHz, −78.5-dBc reference spur, and an rms jitter of 79.8 fsrms (from 10 kHz to 100 MHz), with a jitter-power figure-of-merit (FoM) of −250.0 dB.