Antidepressant abuse has become a growing concern due to their bioaccumulation and potential drug resistance in the environment. Developing smart sensing platforms for antidepressant drug identification could monitor ...
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Antidepressant abuse has become a growing concern due to their bioaccumulation and potential drug resistance in the environment. Developing smart sensing platforms for antidepressant drug identification could monitor their contamination situation in time. Here, a novel boron-doped g-C3N4-glycolchitosan composite (BCNP-GC) was synthesized with high fluorescence emission and ultralong water stability. The electron-deficient boron atom greatly improves the fluorescence response of the composite, while the encapsulation of glycol-chitosan (GC) further enhances its water stability. The designed BCNP-GC could serve as a highly efficient fluorescent probe for the rapid and sensitive detection of nortriptyline (NOT), a typical antidepressant drug in the environment, via internal filtration effect and dynamic quenching effect. It is expected that this strategy can be extended to the fabrication of a variety of nitrogenous carbon-based tricyclic antidepressant monitoring systems with more customized functionalities.
Background: MIL-101(Fe), an eco-friendly catalyst in sulfate radical based advanced oxidation processes (SRAOPs) for treating textile wastewater, faces limitations in peroxymonosulfate (PMS) activation due to its full...
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Background: MIL-101(Fe), an eco-friendly catalyst in sulfate radical based advanced oxidation processes (SRAOPs) for treating textile wastewater, faces limitations in peroxymonosulfate (PMS) activation due to its fully coordinatively saturated state and the slow conversion of Fe III to FeII. Methods: Three co-modified MIL-101(Fe) catalysts of CUS-FeII-MIL-101(Fe), CUS-CuII-MIL-101(Fe) and CUS-CoII- MIL-101(Fe) were successfully synthesized by combining metal-doping (Fe2+, Cu2+ and Co2+) and thermal activation (300 degrees C). The physiochemical properties of as-synthesized catalysts were characterized by powder Xray diffraction (PXRD), field emission electron microscope coupled with energy dispersive spectroscopy (FESEMEDS), Brunauer-Emmett-Teller (BET) and Fourier transform infrared spectroscopy (FTIR). The effects of catalyst dosage and type, PMS concentration, solution pH and co-existing anions on methylene blue (MB) degradation in SR-AOPs systems were analyzed, and the degradation mechanisms was discussed by quenching tests with scavengers of Methanol (MeOH), tertbutyl alcohol (TBA), p-benzoquinone (BQ) and L-histidine (L-his). Significant findings: Compared to the MB degradation efficiency of original MIL-101(Fe) (92.5 %), three co- modified catalysts shown higher MB degradation efficiencies of 97.5 %, 98.1 % and an outstanding 100 %, respectively. Free radicals quenching tests indicated that SO 4 center dot- and center dot OH played key roles in MB degradation mechanism. Promisingly, the three catalysts also demonstrated high degradation efficiencies above 94.0 % for four additional dyes.
Graph neural networks (GNNs) have shown great promise in few-shot learning, where they typically represent the entire feature of a sample as a node. However, this approach can overlook finer details within the sample,...
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Graph neural networks (GNNs) have shown great promise in few-shot learning, where they typically represent the entire feature of a sample as a node. However, this approach can overlook finer details within the sample, as GNNs usually measure the distance between nodes to determine overall differences, making them prone to background noise interference. To alleviate this limitation, we propose a novel framework based on a hybrid graph neural network for few-shot image classification, incorporating deep local features clustering (Cluster-HGNN). This framework comprises two types of GNNs: a global feature GNN and a local feature GNN. The former applies traditional label propagation to classify query nodes, while the latter treats feature embeddings as multiple deep local features, aggregating these by analyzing the categories of each query node's K nearest neighbours to infer the sample's category. The proposed design incorporates local features to rectify the final classification outcome, even in scenarios where the global features may inaccurately assess the current sample. Furthermore, the framework integrates multi-scale techniques and clustering to expand the feature space and reduce the influence of background noise on classification performance. As a result, Cluster-HGNN achieves state-of-the-art results on standard few-shot image classification benchmarks.
Global digital elevation models (GDEMs) are critical in the measurement and analysis of Earth's surface, and should be evaluated prior to use. However, existing GDEM evaluations mainly use global statistical metri...
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Global digital elevation models (GDEMs) are critical in the measurement and analysis of Earth's surface, and should be evaluated prior to use. However, existing GDEM evaluations mainly use global statistical metrics to evaluate vertical elevation (VE) differences with reference data, ignoring the relationship between a centre pixel and its neighbouring pixels, which is defined as the GDEM's neighbouring structure (NS). Along track ATL03 points allow evaluation of the along track NS (ATNS). This study comprehensively accesses the VE and ATNS accuracy of 1 arc-second GDEMs, including Copernicus, NASA, AW3D30 and ASTER DEM, using for the first time ICESat-2 ATL03 along track points throughout the Tibetan Plateau, where the rugged terrains and various features make it difficult to maintain its NS's accuracy. This study first introduces continuous and discrete ATNS metrics, then evaluates their effectiveness by analysing their relationships with errors in GDEM terrain derivatives. Finally, the better-performing metric is used for evaluations across various terrain parameters, landforms and land covers. The proposed framework achieved DEM evaluations from pixel-by-pixel statistical analysis of elevation differences to local ATNS assessment. Evaluation results demonstrate that the ATNS errors of the GDEMs are linearly correlated with the RMSE of the vertical errors. Overall, the errors of the VE RMSE and ATNS are ranked as Copernicus< AW3D30 < NASA< ASTER. However, evaluations conducted in the Andes and Alps reveal regional variations in these rankings. This study endeavours to introduce a new framework for large-scale GDEM evaluations, and the conclusions are beneficial for GDEM selection in further applications.
Heavy metal pollution is a global issue of concern. Most heavy metals are non-biodegradable which as a result accumulate in the environment and affect the soil ecosystem adversely. Thus, remediation of heavy metal pol...
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Heavy metal pollution is a global issue of concern. Most heavy metals are non-biodegradable which as a result accumulate in the environment and affect the soil ecosystem adversely. Thus, remediation of heavy metal pollution is decisive for a cleaner environment. Various traditional and emerging remediation techniques are being adopted to overcome this pollution. Conventional remediation techniques have several limitations like high cost, intensive labor, alteration of soil properties as well as disturbance of soil microbes. In recent years, phytoremediation has taken over traditional soil washing and soil burning processes due to its cost-effectiveness, sustainability, and environmental safety. Ligands have a progressive role in enhancing the phytoremediation of heavy metals. This review explores the type of ligands and their role in enhancing metal availability, decreasing metal toxicity, metal transport, and the sequestration of metals into the vacuole. Some contradictory effects of ligands are also discussed systematically, such as the mobilization and immobilization of metals under the influence of ligands. Moreover, this review article widely discusses the background, concepts, and future trends in the phytoremediation of heavy metals under the influence of ligands.
The equivalent circuit models of permanent magnet synchronous motors (PMSM) are crucial for investigating electromagnetic compatibility (EMC). In this paper, a new model with fourteen circuit components per phase is p...
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The equivalent circuit models of permanent magnet synchronous motors (PMSM) are crucial for investigating electromagnetic compatibility (EMC). In this paper, a new model with fourteen circuit components per phase is proposed, aimed at predicting common-mode (CM) currents in a wide frequency range, from 10 kHz to 30 MHz, during motor operation. Initially, based on experimental measurements of CM and differential-mode (DM) impedance characteristic curves, the component parameters of resonant circuits in the model are identified. Then, an improved differential evolution (I-DE) algorithm, which incorporates a novel mutation strategy, is adopted to optimize and fit the model, selecting optimal individuals within the population to enhance the search efficiency and convergence speed. When compared to standard differential evolution (S-DE) algorithms and genetic algorithms (GAs), the I-DE algorithm shows superior performance in both fitting precision and computation time. Experimental results demonstrate that the established model can accurately predict CM currents, laying a solid foundation for further research on suppressing electromagnetic interference (EMI) in PMSMs.
Beyond directed evolution, ancestral sequence reconstruction (ASR) has emerged as a powerful strategy for engineering proteins with superior functional properties. Herein, we harnessed ASR to uncover robust PET hydrol...
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Beyond directed evolution, ancestral sequence reconstruction (ASR) has emerged as a powerful strategy for engineering proteins with superior functional properties. Herein, we harnessed ASR to uncover robust PET hydrolase variants, expanding the repertoire of PET-degrading enzymes and providing deeper insights into the underlying mechanisms of PET hydrolysis. As a result, ASR1-PETase, featuring a unique cysteine catalytic site, was discovered. Despite having only 19.3 % sequence identity with IsPETase, ASR1-PETase demonstrated improved PET degradation efficiency, with a finely-tuned substrate-binding cleft. Comprehensive experimental validation, including mutagenesis studies and comparisons with six state-of-the-art PET hydrolases, combined with microsecond-scale molecular dynamics (MD) simulations and QM-cluster calculations, revealed that ASR1-PETase's C161 catalytic residue assisted with the wobbled H242 can simultaneously cleave both ester bonds of BHET - a feature not commonly observed in other PET hydrolases. This mechanism may serve as the primary driving force for accelerating PET hydrolysis while minimizing the accumulation of the intermediate MHET, thereby enhancing the efficiency of TPA production.
For any prime p and any positive integer n, let nu p(n)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usep...
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For any prime p and any positive integer n, let nu p(n)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nu _p(n)$$\end{document} be the largest integer alpha\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document} such that p alpha divided by n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<^>\alpha \mid n$$\end{document}. Let phi\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varphi $$\end{document} be Euler's totient function. In this paper, we prove that nu p(phi(n))<=& LeftFloor;logpn & RightFloor;\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nu _p(\varphi (n))\le \lfloor \log _pn\rfloor $$\end{document} for all primes p and all positive integers n, where & LeftFloor;x & RightFloor;\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lfloor x\rfloor $$\end{document} denotes the largest integer not greater than x, and give the sufficient and necessary conditions for equality.
For any positive integer n, let sigma(n) be the sum of all positive divisors of n. For any prime p and any positive integer m, let nu(p)(m) be the largest integer alpha such that p(alpha) divided by m. Recently, Amdeb...
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For any positive integer n, let sigma(n) be the sum of all positive divisors of n. For any prime p and any positive integer m, let nu(p)(m) be the largest integer alpha such that p(alpha) divided by m. Recently, Amdeberhan, Moll, Sharma and Villamizar proved that for any odd prime p and any integer n >= 2, nu(p)(sigma(n)) <= [log(p) n] if n satisfies some conditions, where [x] denotes the least integer not less than x. In this paper, for any odd prime p, we prove that nu(p)(sigma(n)) <= [log(p) n] for all positive integers n unconditionally. Moreover, we prove that if 3 <= p < 10(5) is a prime and p not equal 31, then there are only finitely many positive integers n such that nu(p)(sigma(n)) = [log(p) n]. For p = 31 and n >= 2, nu(p)(sigma(n)) = [log(p) n] if and only if n = 2(4), 5(2), 2(4)5(2) and 2(4)5(2)(2 31(s) - 1), where s is a positive integer and 2 31(s) - 1 is a prime
Searching for long-lived particles (LLPs) beyond the Standard Model (SM) is a promising direction in collider experiments. The Georgi-Machacek (GM) model extends the scalar sector in the SM by introducing various new ...
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Searching for long-lived particles (LLPs) beyond the Standard Model (SM) is a promising direction in collider experiments. The Georgi-Machacek (GM) model extends the scalar sector in the SM by introducing various new scalar bosons. In this study, we focus on the parameter space that allows the light doubly charged scalar to become long-lived. This light doubly charged scalar is fermophobic and predominantly decays into a pair of on-shell or off-shell same-sign W bosons. We investigate three types of signal signatures at the LHC: displaced vertices in the inner tracking detector, displaced showers in the muon system, and heavy stable charged particles. Additionally, we analyze the potential for detecting such doubly charged scalars in far detectors, including ANUBIS, MATHUSLA, FACET, FASER, CODEX-b, MoEDAL-MAPP and AL3X. By combining the LLP searches at the LHC and in far detectors, we project that the limits on the mixing angle, theta H, (between the doublet and triplets) can cover most of the parameter space with sin theta H less than or similar to 10-3 for the mass of doubly charged scalar starting from 50 GeV to 1050 GeV, assuming the full integrated luminosity at the LHC and HL-LHC which is complementary with the usual measurements at the LHC.
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