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Isocorydine is an aporphine alkaloid that is mainly produced via chemical synthesis and extracted from plants. Its hydrochloride has been authorized to be a prescription drug for clinical use. This study aims to discover potential alkaloidal metabolites from endophytic fungi associated with the plant. Endophytic fungi were subjected to solid-state fermentation (SSF) to investigate the production of isocorydine. An aporphine alkaloid was obtained from the metabolite of SSF with Aspergillus sydowii G12. Its chemical structure was deduced to be isocorydine according to the spectroscopic data of ESI-MS, 1H and 13C NMR spectroscopy. The fermentation conditions including substrate, fermentation temperature, and time were optimized. As a result, SSF with A. sydowii G12 using potato as substrate at 20 °C for 15 d could produce isocorydine with a high yield of 2.51 ± 0.09 mg/g. This paper is the first to report an approach to producing isocorydine from microorganisms instead of plants. [Display omitted] • Isocorydine (1) was obtained from the metabolite of SSF using A. sydowii G12. • Achieved SSF condition with A. sydowii G12 using potato substrate at 20°C for 15 d. • A high yield of 2.51 ± 0.09 mg/g can be obtained for the production of isocorydine. • This is the first report of an approach to produce isocorydine from microorganisms. [ABSTRACT FROM AUTHOR]

Thiolate‐protected Cu clusters with well‐defined structures and stable low‐coordinated Cu+ species exhibit remarkable potential for the CO2RR and are ideal model catalysts for establishing structure‐electrocatalytic property relationships at the atomic level. However, extant Cu clusters employed in the CO2RR predominantly yield 2e− products. Herein, two model Cu4(MMI)4 and Cu8(MMI)4(tBuS)4 clusters (MMI=2‐mercapto‐1‐methylimidazole) are prepared to investigate the synergistic effect of Cu+ and adjacent S sites on the CO2RR. Cu4(MMI)4 can reduce CO2 to deep‐reduced products with a 91.0 % Faradaic efficiency (including 53.7 % for CH4) while maintaining remarkable stability. Conversely, Cu8(MMI)4(tBuS)4 shows a remarkable preference for C2+ products, achieving a maximum FE of 58.5 % with a C2+ current density of 152.1 mA⋅cm−2. In situ XAS and ex situ XPS spectra reveal the preservation of Cu+ species in Cu clusters during CO2RR, extensively enhancing the adsorption capacity of *CO intermediate. Moreover, kinetic analysis and theoretical calculations confirm that S sites facilitate H2O dissociation into *H species, which directly participate in the protonation process on adjacent Cu sites for the protonation of *CO to *CHO. This study highlights the important role of Cu−S dual sites in Cu clusters and provides mechanistic insights into the CO2RR pathway at the atomic level. [ABSTRACT FROM AUTHOR]

Thiolate‐protected Cu clusters with well‐defined structures and stable low‐coordinated Cu+ species exhibit remarkable potential for the CO2RR and are ideal model catalysts for establishing structure‐electrocatalytic property relationships at the atomic level. However, extant Cu clusters employed in the CO2RR predominantly yield 2e− products. Herein, two model Cu4(MMI)4 and Cu8(MMI)4(tBuS)4 clusters (MMI=2‐mercapto‐1‐methylimidazole) are prepared to investigate the synergistic effect of Cu+ and adjacent S sites on the CO2RR. Cu4(MMI)4 can reduce CO2 to deep‐reduced products with a 91.0 % Faradaic efficiency (including 53.7 % for CH4) while maintaining remarkable stability. Conversely, Cu8(MMI)4(tBuS)4 shows a remarkable preference for C2+ products, achieving a maximum FE of 58.5 % with a C2+ current density of 152.1 mA⋅cm−2. In situ XAS and ex situ XPS spectra reveal the preservation of Cu+ species in Cu clusters during CO2RR, extensively enhancing the adsorption capacity of *CO intermediate. Moreover, kinetic analysis and theoretical calculations confirm that S sites facilitate H2O dissociation into *H species, which directly participate in the protonation process on adjacent Cu sites for the protonation of *CO to *CHO. This study highlights the important role of Cu−S dual sites in Cu clusters and provides mechanistic insights into the CO2RR pathway at the atomic level. [ABSTRACT FROM AUTHOR]

Though several anti-PD-1/PD-L1 antibodies approved for monotherapy in microsatellite instability-high or mismatch repair-deficient unresectable/metastatic solid tumors, novel immunotherapy with better anti-tumor activity is needed in clinic. In this single-arm, multicenter, pivotal, phase II study, patients received iparomlimab (a novel humanized anti-PD-1 mAb, 200 mg or 3 mg/kg for patients with body weight < 40 kg, IV, Q3W) until disease progression, intolerable toxicities, withdrawal of consent, death, or up to 2 years. The primary endpoint was objective response rate (ORR) assessed by independent radiological review committee (IRRC). Totally, 120 patients were enrolled, of whom 60 patients failed from prior standard therapy, were enrolled in the full analysis set (FAS). As of Jan 20, 2024, the confirmed ORR per IRRC in FAS were 50.0% (30/60; 95% CI 36.8–63.2%) patients, including 4 (6.7%) complete response (CR) and 26 (43.3%) partial response (PR). In colorectal cancer (CRC) patients in FAS, the ORR reached 57.9% (22/38; 95% CI 40.8–73.7%) per IRRC, with 3 (7.9%) CR and 19 (50.0%) PR. Furtherly, the ORRs in liver metastatic or non-liver metastatic CRC patients were 52.9% (9/17, 95% CI 27.8–77.0%) vs 61.9% (13/21, 95% CI 38.4%–81.9%). The incidence of TRAE was 90.8% (any grade) and 20.8% (grade ≥ 3). Immune-related adverse events occurred in 33.3% (any grade) and 5.0% (grade ≥ 3) of patients. No iparomlimab-related death occurred. Iparomlimab presented encouraging antitumor activity with durable response and tolerable safety profile. Trial registration ClinicalTrials.gov Identifier: NCT04326829. [ABSTRACT FROM AUTHOR]

The automatic extraction of bottom sediment annotations in large-scale raster nautical charts has limitations, including an imprecise semantic information description and low efficiency. To overcome them, we propose a convolutional neural network (CNN)-based method for the automatic extraction of bottom sediment annotations in raster nautical charts, using image processing techniques to improve it. First, an adaptive chart partitioning model that considers element completeness is constructed. Second, a principle for the unique identification of elements based on spatial conflicts is designed. Finally, a model for accurately extracting semantic information for bottom sediment annotations is established. To evaluate the effectiveness of the proposed method, we implemented a model based on the PyTorch framework and used the PIL library to analyze the results. We also conducted comparative experiments on multiple CNN models to recommend the selection of such models in the proposed method by comparing their classification and recognition performance. The experimental results indicate that (1) the proposed model can achieve high-precision extraction of bottom sediment annotations in raster nautical charts. (2) Furthermore, the proposed model generally has high recognition accuracy and semantic completeness, with better recognition precision than traditional pattern recognition methods. [ABSTRACT FROM AUTHOR]

An innovative polyphosphide route is developed to synthesize a series of P-doped PdAu ternary alloys. The alloying of P and Au optimizes the electronic structure and reduces the back-donation of d electrons to CO. Meanwhile, the generation of CO is largely inhibited by the highly selective direct pathway arising from the synergistic electron/ligand effect of Au and P, leading to a remarkable anti-poisoning capability for formic acid oxidation. [ABSTRACT FROM AUTHOR]

In this paper, we characterize the boundedness and compactness of the block dual Toeplitz operators acting on the orthogonal complement of the Fock spaces, and the compactness of the finite sum of two dual Toeplitz operators products. The commutator and semi-commutator induced by the block dual Toeplitz operators are considered. [ABSTRACT FROM AUTHOR]

The aim of this study was to experimentally investigate the process of chloride binding and its sulfate-induced release in cementitious materials. The cementitious materials were replaced with hardened cement paste particles (HCPs) with water-to-cement ratios (w/c) of 0.35 and 0.45. A long-term immersion experiment of HCPs in 0.1 M sodium chloride solution was performed to investigate its chloride-binding capacity, and then it was immersed in sodium sulfate solutions with concentrations of 0.1 and 0.5 M to explore the release of chloride binding induced by sulfates. Silver nitrate titration and quantitative X-ray diffraction (QXRD) were used to measure the concentration of free chlorides in the solutions and the content of bound chlorides in HCPs, respectively. The results show that there is a higher chloride-binding capacity in HCPs with a w/c ratio of 0.45 compared to 0.35, and the content of chemically bound chlorides is associated with the formation and decomposition of Friedel's and Kuzel's salts in HCPs. The presence of sulfates can easily result in the release of bound chlorides in Friedel's salt, but it cannot cause a complete release of bound chlorides in Kuzel's salt. Physically bound chlorides are more easily released by sulfates than chemically bound chlorides, and a high w/c ratio or sulfate concentration can increase the release rate of bound chlorides in HCPs. [ABSTRACT FROM AUTHOR]

Background: Non-alcoholic fatty liver disease (NAFLD) is a multifaceted metabolic disorder, whose global prevalence is rapidly increasing. Acetyl CoA carboxylases 1 (ACACA) is the key enzyme that controls the rate of fatty acid synthesis. Hence, it is crucial to investigate the function of ACACA in regulating lipid metabolism during the progress of NAFLD. Methods: Firstly, a fatty liver mouse model was established by high-fat diet at 2nd, 12th, and 20th week, respectively. Then, transcriptome analysis was performed on liver samples to investigate the underlying mechanisms and identify the target gene of the occurrence and development of NAFLD. Afterwards, lipid accumulation cell model was induced by palmitic acid and oleic acid (PA ∶ OA molar ratio = 1∶2). Next, we silenced the target gene ACACA using small interfering RNAs (siRNAs) or the CMS-121 inhibitor. Subsequently, experiments were performed comprehensively the effects of inhibiting ACACA on mitochondrial function and lipid metabolism, as well as on AMPK- PPARα- CPT1A pathway. Results: This data indicated that the pathways significantly affected by high-fat diet include lipid metabolism and mitochondrial function. Then, we focus on the target gene ACACA. In addition, the in vitro results suggested that inhibiting of ACACA in vitro reduces intracellular lipid accumulation, specifically the content of TG and TC. Furthermore, ACACA ameliorated mitochondrial dysfunction and alleviate oxidative stress, including MMP complete, ATP and ROS production, as well as the expression of mitochondria respiratory chain complex (MRC) and AMPK proteins. Meanwhile, ACACA inhibition enhances lipid metabolism through activation of PPARα/CPT1A, leading to a decrease in intracellular lipid accumulation. Conclusion: Targeting ACACA can reduce lipid accumulation by mediating the AMPK- PPARα- CPT1A pathway, which regulates lipid metabolism and alleviates mitochondrial dysfunction. [ABSTRACT FROM AUTHOR]

In this paper, we consider the numerical solution of a large complex linear system with a saddle-point form obtained by the discretization of the time-harmonic eddy-current optimal control problem. A new Schur complement is proposed for this algebraic system, extending it to both the block-triangular preconditioner and the structured preconditioner. A theoretical analysis proves that the eigenvalues of block-triangular and structured preconditioned matrices are located in the interval [1/2, 1]. Numerical simulations show that two new preconditioners coupled with a Krylov subspace acceleration have good feasibility and effectiveness and are superior to some existing efficient algorithms. [ABSTRACT FROM AUTHOR]

The reliable and secure operation of power grids can be efficiently supported by the charging load prediction of electric vehicles (EVs). To address the problem of insufficient accuracy of existing charging load prediction models, a technique for predicting charging load for EVs using the sparrow search algorithm-support vector regression (SSA-SVR) is proposed. First, the daily travel patterns of space and time of EV users are analyzed. Therefore, EV charging load data is obtained by Monte Carlo simulation. Finally, a support vector regression (SVR)-based model for predicting EV charging load is established and the sparrow search algorithm (SSA) is further used to find the optimal kernel function factor and penalty factor of SVR to achieve the optimized prediction effect. The simulation experiments show that, compared with the backpropagation (BP) neural network, SVR methods and PSO-SVR methods, the proposed prediction model can enhance the prediction accuracy of the charging load of EVs. [ABSTRACT FROM AUTHOR]

Atomically precise Cu clusters are highly desirable as catalysts for CO2 reduction reaction (CO2RR), and they provide an appropriate model platform for elaborating their structure–activity relationship. However, an efficient overall photocatalytic CO2RR with H2O using assembled Cu‐cluster aggregates as single component photocatalyst has not been reported. Herein, we report a stable crystalline Cu−S−N cluster photocatalyst with local protonated N−H groups (denoted as Cu6−NH). The catalyst exhibits suitable photocatalytic redox potentials, high structural stability, active catalytic species, and a narrow band gap, which account for its outstanding photocatalytic CO2RR performance under visible light, with ≈100 % selectivity for CO evolution. Remarkably, systematic isostructural Cu‐cluster control experiments, in situ infrared spectroscopy, and density functional theory calculations revealed that the protonated pyrimidine N atoms in the Cu6−NH cluster act as a proton relay station, providing a local proton during the photocatalytic CO2RR. This efficiently lowers the energy barrier for the formation of the *COOH intermediate, which is the rate‐limiting step, efficiently enhancing the photocatalytic performance. This work lays the foundation for the development of atomically precise metal‐cluster‐based photocatalysts. [ABSTRACT FROM AUTHOR]

Atomically precise Cu clusters are highly desirable as catalysts for CO2 reduction reaction (CO2RR), and they provide an appropriate model platform for elaborating their structure–activity relationship. However, an efficient overall photocatalytic CO2RR with H2O using assembled Cu‐cluster aggregates as single component photocatalyst has not been reported. Herein, we report a stable crystalline Cu−S−N cluster photocatalyst with local protonated N−H groups (denoted as Cu6−NH). The catalyst exhibits suitable photocatalytic redox potentials, high structural stability, active catalytic species, and a narrow band gap, which account for its outstanding photocatalytic CO2RR performance under visible light, with ≈100 % selectivity for CO evolution. Remarkably, systematic isostructural Cu‐cluster control experiments, in situ infrared spectroscopy, and density functional theory calculations revealed that the protonated pyrimidine N atoms in the Cu6−NH cluster act as a proton relay station, providing a local proton during the photocatalytic CO2RR. This efficiently lowers the energy barrier for the formation of the *COOH intermediate, which is the rate‐limiting step, efficiently enhancing the photocatalytic performance. This work lays the foundation for the development of atomically precise metal‐cluster‐based photocatalysts. [ABSTRACT FROM AUTHOR]

This paper aims to propose positivity-preserving nonstaggered central difference schemes solving the two-layer shallow water equations with a nonflat bottom topography and geometric channels. One key step is to discretize the bed slope source term and the nonconservative product term due to the exchange of the momentum based on defining auxiliary variables. The second-order accuracy in space can be obtained by constructing non-oscillatory piecewise linear polynomials. In order to guarantee the strong-stability-preserving (SSP) property and second-order accuracy in time, we use a SSP Nonstaggered Runge-Kutta method. We prove that the designed nonstaggered central difference schemes can obtain a well-balanced property for the steady-state stationary solution. In particular, the positivity of layer heights is guaranteed by providing an appropriate CFL condition with the aid of a "draining" time-step technique. Finally, we conduct several classical problems of the two-layer open channel flows. Numerical results confirm that the current nonstaggered central difference scheme is efficient, accurate, and robust. [ABSTRACT FROM AUTHOR]

Conventional frequency selective surface (FSS) absorbers design is time-consuming, involving multiple electromagnetic (EM) simulations for parameter scanning. A novel reverse design method is proposed utilizing evolutionary deep learning (EDL) based on an improved bacterial foraging optimization (IBFO) algorithm and a deep belief network. It establishes the relationship between the geometric structure and EM response. The combination of IBFO and EDL facilitates an efficient optimization for structural parameters, mitigating the 'one-to-many' problem and accelerating the design process. An optically transparent FSS absorber with an ultra-bandwidth of 8–18 GHz is designed to verify the proposed method's capability. The simulation and experimental results demonstrate that the absorber displays exceptional characteristics such as polarization insensitivity and robustness under a 45° oblique incidence angle, making it a suitable candidate for radar stealth and photovoltaic solar energy applications. The proposed method can be applied to the design and optimization of various absorbers and complex EM devices. [ABSTRACT FROM AUTHOR]

Recently, an increasing number of studies have shown that long noncoding RNAs (lncRNAs) are involved in host metabolism after infection with pseudorabies virus (PRV). In our study, via RNA sequencing analysis, a total of 418 mRNAs, 137 annotated lncRNAs, and 312 new lncRNAs were found to be differentially expressed. These lncRNAs were closely associated with metabolic regulation and immunity-related signalling pathways, including the T-cell receptor signalling pathway, chemokine signalling pathway, mitogen-activated protein kinase (MAPK) signalling pathway, TNF signalling pathway, Ras signalling pathway, calcium signalling pathway, and phosphatidylinositol signalling system. Real-time PCR indicated that several mRNAs and lncRNAs involved in the regulation of the immune effector process, T-cell receptor signalling pathway, TNF signalling pathway, MAPK signalling pathway, and chemokine signalling pathways were significantly expressed. These mRNAs and lncRNAs might play a role in PRV infection. [ABSTRACT FROM AUTHOR]

Background Left ventricular thrombus (LVT) is a common complication of dilated cardiomyopathy (DCM), causing morbidity and mortality. Methods This study retrospectively analyzed patients with DCM from January 2002 to August 2020 in Beijing Anzhen Hospital. Clinical characteristics were compared between the LVT group and the age and sex 1:4 matched with the LVT absent group. The receiver operator characteristic (ROC) curve was plotted to evaluate the diagnostic value of D-dimer predicting LVT occurrence in DCM. Results A total of 3,134 patients were screened, and LVT was detected in 72 (2.3%) patients on echocardiography. The patients with LVT had higher D-dimer, fibrinogen, and lower systolic blood pressure than those without LVT. The ejection fraction (EF) was lower and left ventricular end-systolic diameter was larger in the LVT group. Severe mitral regurgitation (MR) was more common in the LVT absent groups. The prevalence of atrial fibrillation was lower in the LVT group. The ROC curve analysis yielded an optimal cut-off value of 444 ng/mL DDU (D-dimer units) for D-dimer to predict the presence of LVT. Multivariable binary logistic regression analysis revealed that EF (OR = 0.90, 95% CI = 0.86–0.95), severe MR (OR = 0.19, 95% CI = 0.08–0.48), and D-dimer level (OR = 15.4, 95% CI = 7.58–31.4) were independently associated with LVT formation. Conclusion This study suggested that elevated D-dimer levels (>444 ng/mL DDU) and reduced EF were independently associated with increased risk of LVT formation. Severe MR could decrease the incidence of LVT. [ABSTRACT FROM AUTHOR]

The most prevalent type of intestinal polyposis, colorectal adenomatous polyposis (CAP), is regarded as a precancerous lesion of colorectal cancer with obvious genetic characteristics. Early screening and intervention can significantly improve patients' survival and prognosis. The adenomatous polyposis coli (APC) mutation is believed to be the primary cause of CAP. There is, however, a subset of CAP with undetectable pathogenic mutations in APC, known as APC (-)/CAP. The genetic predisposition to APC (-)/CAP has largely been associated with germline mutations in some susceptible genes, including the human mutY homologue (MUTYH) gene and the Nth-like DNA glycosylase 1 (NTHL1) gene, and DNA mismatch repair (MMR) can cause autosomal recessive APC (-)/CAP. Furthermore, autosomal dominant APC (-)/CAP could occur as a result of DNA polymerase epsilon (POLE)/DNA polymerase delta 1 (POLD1), axis inhibition protein 2 (AXIN2), and dual oxidase 2 (DUOX2) mutations. The clinical phenotypes of these pathogenic mutations vary greatly depending on their genetic characteristics. Therefore, in this study, we present a comprehensive review of the association between autosomal recessive and dominant APC (-)/CAP genotypes and clinical phenotypes and conclude that APC (-)/CAP is a disease caused by multiple genes with different phenotypes and interaction exists in the pathogenic genes. [ABSTRACT FROM AUTHOR]

With the increasing demand for high-precision and difficult-to-obtain geospatial point cloud data copyright protection in military, scientific research, and other fields, research on lossless watermarking is receiving more and more attention. However, most of the current geospatial point cloud data watermarking algorithms embed copyright information by modifying vertex coordinate values, which not only damages the data accuracy and quality but may also cause incalculable losses to data users. To maintain data fidelity and protect its copyright, in this paper, we propose a lossless embedded watermarking algorithm based on vertical stability. First, the watermark information is generated based on the binary encoding of the copyright information and the code of the traceability information. Second, the watermark index is calculated based on the length of the watermark information after compression and the vertical distribution characteristics of the data. Finally, watermark embedding is completed by modifying the relative storage order of the corresponding data according to the index and watermark value. The experimental results show that the proposed algorithm has good invisibility without damaging the data accuracy. In addition, compared with existing algorithms, this method has a higher robustness under operations such as projection transformation, precision perturbation, and vertex deletion of geospatial point cloud data. [ABSTRACT FROM AUTHOR]

Contribution [[2]] introduces chaotic mapping into the PPE algorithm to propose a new algorithm, the Chaotic-based Phasmatodea Population Evolution (CPPE) algorithm, and apply CPPE to stock prediction. Swarm intelligence algorithms represent a rapidly growing research domain and have recently attracted a great deal of attention. The research and application of these algorithms provide an efficient and flexible approach to tackling real-world problems, while also driving the development of optimization algorithms and advancing theoretical investigations. Contribution [[5]] proposes a new convex combination based on grey wolf optimization and LMS algorithms, to save area and achieve high convergence speed by maximally exploiting the best features of each algorithm, presenting a customized time-multiplexing control scheme to dynamically vary the number of search agents. [Extracted from the article]

In this paper, we investigate a well‐balanced and positive‐preserving nonstaggered central scheme, which has second‐order accuracy on both time and spatial scales, for open‐channel flows with the variable channel width and the nonflat bottom. We perform piecewise linear reconstructions of the conserved variables and energy as well as discretize the source term using the property that the energy remains constant, so that the complex source term and the flux can be precisely balanced so as to maintain the steady state. The scheme also ensures that the cross‐sectional wet area is positive by introducing a draining time‐step technique. Numerical experiments demonstrate that the scheme is capable of accurately maintaining both the still steady‐state solutions and the moving steady‐state solutions, simultaneously. Moreover, the scheme has the ability to accurately capture small perturbations of the moving steady‐state solution and avoids generating spurious oscillations. It is also capable of showing that the scheme is positive‐preserving and robust in solving the dam‐break problem. [ABSTRACT FROM AUTHOR]

Infrared (IR) stealth plays a vital role in the modern military field. With the continuous development of detection technology, multi-band (such as near-IR laser and middle-IR) compatible IR stealth is required. Combining rigorous coupled wave analysis (RCWA) with Deep Learning (DL), we design a Ge/Ag/Ge multilayer circular-hole metasurface capable of multi-band IR stealth. It achieves low average emissivity of 0.12 and 0.17 in the two atmospheric windows (3~5 μm and 8~14 μm), while it achieves a relatively high average emissivity of 0.61 between the two atmospheric windows (5~8 μm) for the purpose of radiative thermal management. Additionally, the metasurface has a narrow-band high absorptivity of 0.88 at the near-infrared wavelength (1.54 μm) for laser guidance. For the optimized structure, we also analyze the potential physical mechanisms. The structure we optimized is geometrically simple, which may find practical applications aided with advanced nano-fabrication techniques. Also, our work is instructive for the implementation of DL in the design and optimization of multifunctional IR stealth materials. [ABSTRACT FROM AUTHOR]

Background: As a complex vascular malformation, fibro-adipose vascular anomaly was first proposed in 2014. Its overlap with other vascular malformations regarding imaging and clinical features often leads to misdiagnosis and improper management. Objective: To construct a radiomics-based machine learning model to help radiologists differentiate fibro-adipose vascular anomaly from common venous malformations. Materials and methods: We retrospectively analyzed 178 children, adolescents and young adults with vascular malformations (41 fibro-adipose vascular anomaly and 137 common vascular malformation cases) who underwent MRI before surgery between May 2012 to January 2021. We extracted radiomics features from T1-weighted images and fat-saturated (FS) T2-weighted images and further selected features through least absolute shrinkage and selection operator (LASSO) and Boruta methods. We established eight weighted logistic regression classification models based on various combinations of feature-selection strategies (LASSO or Boruta) and sequence types (single- or multi-sequence). Finally, we evaluated the performance of each model by the mean area under the receiver operating characteristics curve (ROC-AUC), sensitivity and specificity in 10 runs of repeated k-fold (k = 10) cross-validation. Results: Two multi-sequence models based on axial FS T2-W, coronal FS T2-W and axial T1-W images showed promising performance. The LASSO-based multi-sequence model achieved an AUC of 97%±3.8, a sensitivity of 94%±12.4 and a specificity of 89%±9.0. The Boruta-based multi-sequence model achieved an AUC of 97%±3.7, a sensitivity of 95%±10.5 and a specificity of 87%±9.0. Conclusion: The radiomics-based machine learning model can provide a promising tool to help distinguish fibro-adipose vascular anomaly from common venous malformations. [ABSTRACT FROM AUTHOR]

Background: Uterus transplantation is the only treatment for absolute uterine factor infertility. Complex vascular anatomy, long operation time, and intraoperative injuries are the main factors that limit progress in uterus transplantation. Moreover, robot-assisted uterus transplantation is not popular at present due to technical difficulties, with only a few countries reporting success. Methods: In this paper, we present the key technical points of robot-assisted uterine transplantation by analyzing and summarizing our surgical experience and other successful cases of robot-assisted uterine transplantation. This study provides an evidence-based reference for clinicians planning robot-assisted uterine transplantation procedures. Conclusion: Minimally invasive technologies can shorten the operation time, reduce injuries, and contribute to analyzing the anatomy of complex blood vessels. Therefore, robot-assisted uterine transplantation is an important direction for the future of uterine transplantation, and the findings and procedures reported herein contribute to the standardization and promotion of robot-assisted uterine transplantation operations. [ABSTRACT FROM AUTHOR]

A frequency-selective surface (FSS) optimization method combining a curve-fitting technique and an improved bacterial foraging optimization (IBFO) algorithm is proposed. In the method, novel Koch curve-like FSS and Minkowski fractal islands FSS were designed with a desired resonance center frequency and bandwidth. The bacteria foraging optimization (BFO) algorithm is improved to enhance the performance of the FSS. A curve-fitting technique is provided to allow an intuitive and numerical analysis of the correspondence between the FSS structural parameters and the frequency response. The curve-fitting results are used to evaluate the fitness function of the IBFO algorithm, replacing multiple repeated calls to the electromagnetic simulation software with the curve-fitting equation and thus speeding up the design process. IBFO is compared with the classical BFO algorithm, the hybrid BFO-particle swarm optimization algorithm (BSO), and the artificial bee colony algorithm (ABC) to demonstrate its superior performance. The designed fractal FSS is fabricated and tested to verify the experimental results. The simulation and measurement results show that the proposed FSS has a fractional bandwidth of 91.7 % in the frequency range of 3.41–9.19 GHz (S, C, and X-bands). In addition, the structure is very thin, with only 0.025 λ and 0.067 λ at the lowest and highest frequencies, respectively. The proposed fractal FSS has shown stable performance for both TE and TM polarizations at oblique incidence angles up to 45°. according to simulations and measurements. [ABSTRACT FROM AUTHOR]

• Two congestion mitigation strategies are formulated for port operations. • Consider customers' joint price-sensitive and delay-sensitive behavior. • ESG (Environment, Social and Governance) performances are evaluated. • Smart port construction may not reduce congestion but incurs investment dilemma. In practice, ports compete on both service volume and service quality. The latter can be measured by the port congestion situation so the mitigation of congestion helps improve customers' experience. We observe that smart ports are widely built and many local governments are promoting port integration to ease competition and reduce congestion. One immediate question is: Are the two strategies really effective that further enable the improvement of ESG (Environment, Social and Governance) performance? In this study, by taking the do-nothing strategy as the benchmark, we examine how smart port and port integration strategies work in port congestion reduction and ESG improvement. We reveal that the smart port strategy brings the Matthew effect that the large port obtains a larger market share and the smaller port worries about the win-lose situation. We also reveal that smart port can make each port and the entire port system more congested, resulting in the investment dilemma. Differently, the port integration strategy can effectively reduce congestion but hurt social welfare. We further discuss a mixed strategy where both strategies are implemented. Interestingly, under the mixed strategy, the risk of falling into the investment dilemma can be reduced and social welfare can be increased. We compare the ESG performances under three strategies and highlight that the mixed strategy achieves the highest system profit, the smart port strategy yields the highest social welfare, and the port integration strategy may outperform the other strategies in terms of environmental sustainability. [ABSTRACT FROM AUTHOR]

Recently, duality principles in g-frame theory were studied. This paper addresses a relaxation of g-R-duals. We introduce the notion of weak g-R-dual in g-frame theory setting, and present the link between frame properties of a bounded operator sequence and its weak g-R-duals. Using weak g-R-duals, we characterize g-frames and (unitary) equivalence between g-frames. And using pseudo-inverse operators, we represent the canonical duals of weak g-R-duals. Some examples are also provided. [ABSTRACT FROM AUTHOR]

Background: Both denosumab and bisphosphonates have been demonstrated effective for glucocorticoid-induced osteoporosis. However, evidence-based medicine is still lacking to prove the clinical results between denosumab and bisphosphonates. This meta-analysis aims to compare the efficacy and safety between denosumab and oral bisphosphonates for the treatment of glucocorticoid-induced osteoporosis through evidence-based medicine.Methods: MEDLINE, EMBASE, and the Cochrane library databases were searched up to June 2022 for randomized controlled trials that compared denosumab and oral bisphosphonates in the treatment of glucocorticoid-induced osteoporosis. The following outcomes were extracted for comparison: percentage change in bone mineral density from baseline at the lumbar spine, total hip, femoral neck, and ultra-distal radius; percentage change from baseline in serum concentration of bone turnover markers; and incidence of treatment-emergent adverse events.Results: Four randomized controlled trials involving 714 patients were included. The pooled results showed that denosumab was superior to bisphosphonates in improving bone mineral density in lumbar spine (mean difference (MD) 1.70; 95% confidence interval (CI) 1.11-2.30; P < 0.001) and ultra-distal radius (MD 0.87; 95% CI 0.29-1.45; P = 0.003), and in suppressing C-terminal telopeptide of type 1 collagen (MD -34.83; 95% CI -67.37--2.28; P = 0.04) and procollagen type 1 N-terminal propeptide (MD -14.29; 95% CI -23.65- -4.94; P = 0.003) at 12 months. No significant differences were found in percentage change in total hip or femoral neck bone mineral density at 12 months, or in the incidence of treatment-emergent adverse events or osteoporosis-related fracture.Conclusions: Compared with bisphosphonates, denosumab is superior in improving bone mineral density in lumbar spine and ultra-distal radius for glucocorticoid-induced osteoporosis. Further studies are needed to prove the efficacy of denosumab. [ABSTRACT FROM AUTHOR]

A well-balanced and positivity-preserving adaptive unstaggered central scheme for two-dimensional shallow water equations with nonflat bottom topography on irregular quadrangles is presented. The irregular quadrilateral mesh adds to the difficulty of designing unstaggered central schemes. In particular, the integral of the source term needs to subtly be dealt with. A new method of discretizing the source term for the well-balanced property is proposed, which is one of the main contributions of this work. The spacial second-order accuracy is obtained by constructing piecewise bilinear functions. Another novelty is that we introduce a strong-stability-preserving Unstaggered-Runge–Kutta method to improve the accuracy in time integration. Adaptive moving mesh strategies are introduced to couple with the current unstaggered central scheme. The well-balanced property is still valid. The positivity-preserving property can be proved when the cells shrink. We prove that the current adaptive unstaggered central scheme can obtain the stationary solution ("lake at rest" steady solutions) and guarantee the water depth to be nonnegative. Several classical problems of shallow water equations are shown to demonstrate the properties of the current numerical scheme. [ABSTRACT FROM AUTHOR]

In this paper, a fast reverse design method of multi-layer frequency selective surface (FSS) based on the equivalent circuit (EC)-assisted multi-objective particle swarm optimization (MOPSO) algorithm is proposed. Converting the desired frequency response requirements into an EC and then determining structural parameters via building blocks' EC and MOPSO simplifies the inverse design process of the FSS. The layer-by-layer building blocks of EC are used instead when dealing with the problem of complicated EC computation associated with multi-layer FSS. By converting factors that are difficult to calculate, such as interlayer coupling, into an MOPSO seeking process, the computational complexity is reduced while the design accuracy can be improved. To begin with, it is necessary to determine the distribution of zeros and poles according to the design goals in order to calculate the appropriate EC. Then, the preliminary design of the FSS has been completed in accordance with the EC and the associated building block structure. Finally, the objective function of the optimization algorithm is determined according to the desired frequency response, and the FSS structure parameters are optimized. Taking dual band-stop FSS and triple band-pass FSS structures as examples, the transmission coefficient results obtained by the proposed reverse design method are consistent with the transmission coefficient results based on the ECs, which verifies the effectiveness of the proposed method. The optimized triple band-pass FSS demonstrates strong stability even at oblique incident angles of up to 45° in both TE and TM polarizations. [ABSTRACT FROM AUTHOR]

Deformation is an intuitive reflection of the safety status of a dam. The construction of a dam deformation prediction model can predict the deformation and interpret the effects of environmental loads. The current research mainly focuses on the predictive ability of the model and rarely involves the interpretation of the load impact on deformation. Meanwhile, the selection of the model factors, such as water pressure factors and temperature factors, mostly relies on prior knowledge. In addition, the complex structure of multiple arch dams makes it difficult to capture the relationship between deformation and environmental loads. Consequently, the performance of conventional models based only on time domain information may be insufficient. In this paper, a deformation prediction model is established by integrating time frequency domain information. First, the deformation and load monitoring data are decomposed and regrouped according to the frequency characteristic of signals via kurtosis index‐based VMD. Second, the sequence relationship between the dam deformation and loads under different frequency characteristics is automatically captured based on the temporal convolution network (TCN). Finally, a quantitative method of the load impact is proposed based on the network parameters. The case results show that the proposed modeling paradigm has significantly improved the prediction accuracy. The quantification result of the load impact on the horizontal displacement change of the dam conforms to the actual state of the project during the analysis period. The work effectively supplements the research on the prediction of ML‐based models and interpretation of the load impact on deformation. [ABSTRACT FROM AUTHOR]

The deregulation of Brain-Derived Neurotrophic Factor (BDNF) was reported to be responsible for the development of post-stroke depression (PSD), while the stimulation of the fastigial nucleus (FN) can be used to treat PDS by down-regulating the expression of miR-182 and miR-382. Therefore, we aim to test the hypothesis that the therapeutic effect of FN stimulation obtained in the treatment of PSD is mediated by the miR-382&miR-182/BDNF mRNA signaling pathways. Rat models of PSD were established and divided into sham, stroke, PSD and PSD + FNS groups to receive different treatments. Post-stroke depression-like behaviors were observed after the initiation of the treatments. TUNEL assay, Western Blot, IHC assay, real-time PCR, bioinformatics tools and luciferase assays were performed to examine the effect of FN stimulation on the expression of miR-182, miR-382 and BDNF mRNA/protein, as well as to further clarify the role of miR-382&miR-182/BDNF mRNA signaling pathways in FN stimulation. Post-stroke depression-like behaviors were significantly reduced in PSD rats. In contrary, the treatment by FN stimulation alleviated the symptoms of PSD and reduced the apoptosis index in the PSD group. Furthermore, in the PSD group, BDNF mRNA/protein levels were suppressed while the miR-382/miR-182 levels were both significantly up-regulated. After the treatment of FN stimulation, BDNF mRNA/protein levels were partly recovered, while miR-382/miR-182 levels was decreased. Furthermore, BDNF was identified as a virtual target of miR-382 and miR-182. In conclusion, FN stimulation increases the expression of BDNF via down-regulating the expression of miR-382/miR-182, thus exhibiting a positive effect in the management of PSD. • FN stimulation could alleviate depression-like behaviors in PSD rats. • FN stimulation inhibited cell apoptosis. • FN stimulation affected the activity of the miR-283&miR-182/BDNF mRNA signaling pathways. • BDNF mRNA was targeted by miR-382 and miR-182. • miR-382 and miR-182 negatively regulated the mRNA/protein expression of BDNF. [ABSTRACT FROM AUTHOR]

Chronic limb threat ischemia is associated with cardiovascular events, resulting in high amputation, morbidity and mortality rates. This study aims to accomplish a comprehensive summary of randomized controlled trials and single-center trials related to drug-coated balloons (DCBs) in the treatment of below-the-knee (BTK) artery disease, and to provide a recommendation for the application of DCBs in BTK artery disease. Five electronic databases were used to retrieve relevant articles on the safety and effectiveness of DCBs in the treatment of BTK artery disease. A random-effects model was applied to calculate the standard mean deviation, odds ratio (OR) and their 95% of confidence interval (CI). As of April 8, 2021, a total of 241 articles were retrieved, but only 13 articles were finally included for meta-analysis. The 12 mo follow-up study found that major adverse events , all-cause mortality, major amputation ,and target lesion revascularization had no statistically significant difference between the DCBs group and the control group (target lesion revascularization: OR = 0.68, 95% CI: 0.36, 1.31; all-cause mortality: OR = 1.30, 95% CI: 0.69, 2.46; major amputation: OR = 1.34, 95% CI: 0.64, 2.79; target lesion revascularization: OR = 0.72, 95% CI: 0.35, 1.45). The meta-analysis results of randomized controlled trials focusing on comparing DCBs and other treatments suggest that DCBs do not have significant advantages in the treatment of BTK artery disease when compare with percutaneous transluminal angioplasty (PTA), but better than control intervention except PTA in both safety and efficacy end points. However, the results of meta-analysis of single-arm trial reported DCBs in treating BTK artery lesions are significantly improved compared with the meta-analysis concentrating on PTA. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) and stable coronary artery disease (SCAD) frequently coexist. This study aimed to assess the long‐term outcome of catheter ablation in patients with paroxysmal AF and SCAD. Methods: In total, 12,104 patients with paroxysmal AF underwent catheter ablation in the Chinese Atrial Fibrillation Registry between 2011 and 2019 were screened. A total of 441 patients with SCAD were matched with patients without SCAD in a 1:4 ratio. The primary endpoint was AF recurrence after single ablation. The composite secondary endpoints were thromboembolism, coronary events, major bleeding, all‐cause death. Results: Over a mean follow‐up of 46.0 ± 18.9 months, the recurrence rate in patients with SCAD was significantly higher after a single ablation (49.0% vs. 41.9%, p =.03). The very late recurrence rate of AF in the SCAD group was also significantly higher than that in the control group (38.9% vs. 31.2%;p =.04). In multivariate analysis, adjusted with the female, smoking, duration of AF, previous thromboembolism, COPD, and statins, SCAD was independently associated with AF recurrence (adjusted HR, 1.19 [1.02–1.40], p =.03). The composite secondary endpoints were significantly higher in the SCAD group (12.70% vs. 8.54%, p =.02), mainly due to thromboembolism events (8.16% vs. 4.41%, p <.01). Conclusions: SCAD significantly increased the risk of recurrence after catheter ablation of paroxysmal AF. The incidence of thromboembolic events after catheter ablation of paroxysmal AF in the patients with SCAD was significantly higher than that in those without SCAD. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid optimization algorithm named GPOFWA, which integrates political optimizer (PO) with fireworks algorithm (FWA) to solve numerical and engineering optimization problems. The original PO uses subgroup optimal solutions such as party leaders and constituency winners to guide the movement of the search agent. However, the number of such subgroup optimal solutions is limited, which leads to insufficient global exploration capabilities of PO. In addition, the recent past-based position updating strategy (RPPUS) of PO lacks effective verification of the updated candidate solutions, which reduces the convergence speed of the algorithm. The proposed hybrid algorithm uses the spark explosion mechanism in FWA to perform explosion spark and Gauss explosion spark operations on the subgroup optimal solutions (party leader and constituency winner) respectively based on the greedy strategy, which optimizes the subgroup optimal solution and enhances the exploitative ability of the algorithm. Moreover, Gaussian explosion sparks are also used to correct the candidate solutions after RPPUS, which makes up for the shortcomings of the original PO. In addition, a new subgroup optimal solution called the Converged Mobile Center (CMC) based on two-way consideration is designed to guide the movement of search agents and maintain the population diversity. We test the presented hybrid algorithm on 30 well-known benchmark functions, CEC2019 benchmark functions and three engineering optimization problems. The experimental results show that GPOFWA is superior to many statE−of-thE−art methods in terms of the quality of the resulting solution. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the clinical outcome and quality of life in elderly patients in poor conditions with unilateral symptomatic degenerative lumbar spinal stenosis (DLSS) who were treated with percutaneous endoscopic lumbar discectomy (PELD) assisted by double tubes. Methods: This study was designed retrospectively. From June 2017 to June 2018, 31 consecutive elderly patients who were presented with unilateral symptomatic DLSS, underwent PELD assisted by double tubes under local anesthesia. American Society of Anesthesiology score (ASA) was used to evaluate the patients' conditions. The operative time, intraoperative blood loss, hospital stay, and complications were evaluated. Clinical outcomes were assessed by the visual analog scale (VAS), Oswestry disability index (ODI), and modified Macnab criteria. Short Form 36 (SF‐36) was used to evaluate the life quality. The CT or MRI was used to evaluate the spinal area. Results: Thirty‐one patients were enrolled and 25 cases achieved at least a 24‐month follow‐up. Three patients were lost to follow‐up and three patients died from other diseases. A total of 76% (19/25) of the patients presented an ASA score of more than 3. The mean operative time was 67.80 min, the mean blood loss was 18.2 ml, and the hospital stay was 6.92 days. The postoperative 12‐month follow‐up VAS score significantly decreased compared with that before the operation (1.12 ± 0.73 vs. 5.12 ± 1.81, p < 0.01). Although the VAS score decreased at the final follow‐up, there was no significant difference compared with that at the 12‐month follow‐up (0.92 ± 0.64 vs. 1.12 ± 0.73, p = 0.549). So did the ODI. Also, there was no difference in the ODI scores between the 12‐month follow‐up and the final follow‐up (12.52 ± 5.58 vs. 9.44 ± 6.32, p = 0.172). The overall excellent rate was 92% (23/25) at the final follow‐up. The scores of the physical function, mental function, and social function of SF‐36 after the operation improved significantly compared with those before operation (p < 0.05). But there was no difference in the physical function score (84.00 ± 6.29 vs 84.40 ± 6.18, p = 0.871), mental function score (81.76 ± 8.01 vs 81.68 ± 6.67, p = 0.974), or social function score (115.50 ± 13.64 vs 118.50 ± 12.03, p = 0.437) between the 12‐month follow‐up and the final follow‐up. There were no differences in the VAS, ODI, and SF‐36 between the L4/5 and L5S1 groups before operation or at the final follow‐up (p > 0.05). The postoperative radiology indicated the lateral recess is opened and the area of the dural sac is expanded. Two cases (8.0%, 2/25) experienced recurrence and a secondary PELD was performed. Conclusions: PELD assisted by double tubes is effective for unilateral symptomatic DLSS in elderly patients with comorbidities and could improve life quality. [ABSTRACT FROM AUTHOR]

Metasurface-based multi-band camouflage holds significant value in both military and civilian applications due to its superior performance and structural simplicity. Combining a physics-driven neural network (PNN) and genetic algorithm (GA), we designed the AZO-Ge disk metasurface capable of achieving 1.06 μm laser stealth, mid-infrared thermal camouflage and efficient thermal management. In contrast to conventional spectra prediction neural networks, the PNN adopts a data dimensionality reduction prediction paradigm, resulting in enhanced accuracy and accelerated convergence. The combination of PNN and GA in the inverse design effectively addresses the prevalent "one-to-many" and single-solution challenges encountered in tandem neural networks. Such data-driven approach makes metasurface design faster and more efficient. Finally, four groups of metasurface geometric parameters were designed by the PNN-GA framework. The designed metasurfaces exhibit low average emissivities (<0.3 and < 0.2, respectively) in the two atmospheric windows (3∼5 μm and 8∼14 μm), high average emissivity (>0.75) in the non-atmospheric window (5∼8 μm) and high absorptivity (>0.8) at 1.06 μm. We also demonstrate that these spectral properties are insensitive to the incident angles and polarizations. In addition, the electric field intensity distribution plots of the cross sections reveal that surface plasmon polariton (SPP) predominantly contributes to the high emission in the non-atmospheric window band, while the high absorptivity at 1.06 μm is attributed to the resonance and the intrinsic absorption of the Ge material. The designed metasurface with its simple structure suggests the potential for low-cost and large-scale fabrication in the future. Meanwhile, the combination of machine learning and evolutionary algorithms is a pioneering work in metasurface design and we believe our work will provide guidelines for the multi-solution design of complex metasurfaces. • A framework that combine machine learning and genetic algorithm is adopted to design metasurface. • A neural network with physics-based data dimensionality reduction prediction. • An inverse design framework with multi-solution capability. • The generated solutions achieve laser stealth, thermal camouflage, and efficient thermal management. [ABSTRACT FROM AUTHOR]

We aim to introduce a new variant of hydrostatic reconstruction scheme, which is physical-structure-preserving and semi-discrete entropy-preserving for shallow water equations with a discontinuous bottom topography, based on novel surface reconstructions (NSR). The NSR is used to define approximate Riemann states with respect to the water depth and the velocity to compute consistent numerical fluxes across the cell interface and the upwind interface source term. This work is motivated by path-conservative surface reconstructions (Dong (2023) [19]), in which the conditions to satisfy the entropy inequality are complicated. We propose the NSR scheme to satisfy the entropy inequality without the corresponding complicated conditions. A key advantage of the NSR scheme is to preserve the physical structure of the water surface in the sense that when the water surface is continuous, then the defined approximate Riemann state should inherit this property. The physical-structure-preserving property is indispensable for obtaining a more accurate discretized source term and avoiding artificial "waterfall" effects. We prove that the NSR scheme satisfies a semi-discrete entropy condition and can guarantee the water depth to be nonnegative, and maintain the stationary state. We show several computed results to compare the NSR scheme with the hydrostatic reconstruction scheme based on subcell reconstructions and the path-conservative surface reconstruction scheme. We also extend the NSR scheme for pollutant transport in shallow water based on adaptive moving triangular meshes. Finally, several numerical results obtained by the adaptive NSR scheme for pollutant transport in shallow water are shown. • We propose a physical-structure-preserving and semi-discrete entropy-preserving novel surface reconstructions. • The novel surface reconstruction scheme out performs standard hydrostatic reconstruction schemes. • We extend the NSR scheme for the pollutant transport in shallow water moving triangles. [ABSTRACT FROM AUTHOR]

With the increasing capacity of wind power generators (WTGs), the volatility of wind power could significantly challenge the stability and economy of electric and heating networks. To tackle this challenge, this paper proposes an optimal dispatch framework based on controllable load (including controllable electric load and controllable thermostatically load) to reduce wind power curtailment. A forecasting model is developed for the controllable load, which comprehensively considers autocorrelation, weather factor, and consumers' behavior characteristics. With adjusting controllable load, an optimal dispatch model of power system is then established and resolved by Sequential Least Squares Programming (SLSQP) method. Our method is verified through numerous simulations. The results show that, compared with the state-of-the-art techniques of support vector machine and recurrent neural networks, the root mean square error with the proposed long short-term memory can be reduced by 0.069 and 0.044, respectively. Compared with conventional method, the peak wind power curtailment with dispatching controllable load is reduced by nearly 10% and 5% in two cases, respectively. [ABSTRACT FROM AUTHOR]

Left ventricular mechanical dyssynchrony (LVMD) is one of the manifestations of abnormal left ventricular motion. And the measured indexes related to LVMD are the indexes derived from left ventricular strain, which can predict the response to cardiac resynchronization therapy and the prognosis of the patients with acute myocardial infarction. The premise of LVMD diagnosis is to measure segmental strains of left ventricle accurately. As an emerging cardiac imaging technology, cardiac magnetic resonance (CMR) can accurately measure the strain of each left ventricle segment, which makes it valuable in both clinic and scientific research. In this article, the mechanism of LVMD, the measurement by CMR and its clinical application to heart diseases are reviewed. [ABSTRACT FROM AUTHOR]

Ultrafast High-temperature Sintering (UHS) allows consolidation of ceramics in just a few tens of seconds. The green body is placed within a carbon felt heated by the Joule effect at temperatures up to 3000 °C. Here, we propose a combined experimental and numerical analysis to enable the fabrication of fully dense and fine-grain α-Al 2 O 3 samples using a multistep computer-controlled current profile. Reference samples processed using a single step current formed cracks at the onset of shrinkage due to their uneven temperature distribution. Fully coupled simulations accounting for electric current, voltage, power, temperature and shrinkage allowed us to improve the experimental setup and to define the current profiles required to UHS highly dense (i.e., relative density > 99 %) 3 mm thick samples with an average grain size of 0.77 μm. [ABSTRACT FROM AUTHOR]

We demonstrate nonreciprocal far-field thermal emission and nonreciprocal near-field radiative heat transfer of Weyl semimetal nanoparticles when the circular thermal emission of the particles directionally couples with the spin of the surface modes supported by a reciprocal substrate. Our work can be applied to the development of nonreciprocal and directional thermal emitters and to the nanoscale routing of a radiative heat flux. [ABSTRACT FROM AUTHOR]

Software defect prediction, which can identify the defect‐prone modules, is an effective technology to ensure the quality of software products. Due to the importance in software maintenance, many learning‐based software defect prediction models are presented in recent years. Actually, the defects usually occupy a very small proportions in software source codes; thus, the imbalanced distributions between defect‐prone modules and non‐defect‐prone modules increase the learning difficulty of the classification task. To address this issue, we present a random over‐sampling mechanism used to generate minority‐class samples from high‐dimensional sampling space to deal with the imbalanced distributions in software defect prediction, in which two constraints are applied to provide a robust way to generate new synthetic samples, that is, scaling the random over‐sampling scope to a reasonable area and distinguishing the majority‐class samples in a critical region. Based on nine open datasets of software projects, we experimentally verify that our presented method is effective on predict the defect‐prone modules, and the effect is superior to the traditional imbalanced processing methods. [ABSTRACT FROM AUTHOR]

• Proposed the UEHAR/ANO 2 /O 2 system for treating coking wastewater. • The COD non-compliance rate reduced by 86.49 %. • The effluent VPs concentration decreased by 90.74 ± 3.69 %. • The BTEX removal efficiency improved by 10.63 ± 2.44 %. • DHA and ATP were increased by 67.23 ± 26.31 % and 40.62 ± 14.22 %, respectively. In this study, the performance of a novel up-flow electrocatalytic hydrolytic acidification reactor (UEHAR) and anoxic/oxic (ANO 2 /O 2) combined system (S 2) was compared with that of a traditional anaerobic/anoxic/oxic (ANA/ANO 1 /O 1) system (S 1) for treating coking wastewater at different hydraulic retention time (HRT). The effluent non-compliance rates of chemical oxygen demand (COD) of S 2 were 45 %, 35 %, 25 % and 55 % lower than S 1 with HRT of 94, 76, 65 and 54 h. The removal efficiency of benzene, toluene, ethylbenzene and xylene (BTEX) in S 2 was 10.6 ± 2.4 % higher than that in S 1. The effluent concentration of volatile phenolic compounds (VPs) in S 2 was lower than 0.3 mg/L. The dehydrogenase activity (DHA) and adenosine triphosphate (ATP) of O 2 were enhanced by 67.2 ± 26.3 % and 40.6 ± 14.2 % compared with O 1 , respectively. Moreover, COD was used to reflect the mineralization index of organic matter, and the positive correlation between COD removal rate and microbial activity, VPs, and BTEX was determined. These results indicated that S 2 had extraordinary microbial activity, stable pollutant removal ability, and transcendental effluent compliance rate. [Display omitted] [ABSTRACT FROM AUTHOR]

Excessive oxidative stress and NLRP3 inflammasome activation are considered the main drivers of inflammatory bowel disease (IBD), and inhibition of inflammasomes ameliorates clinical symptoms and morphological manifestations of IBD. Herein, we examined the roles of NLRP3 activation in IBD and modulation of NLRP3 by sulforaphane (SFN), a compound with multiple pharmacological activities that is extracted from cruciferous plants. To simulate human IBD, we established a mouse colitis model by administering dextran sodium sulfate in the drinking water. SFN (25, 50 mg·kg−1·d−1, ig) or the positive control sulfasalazine (500 mg/kg, ig) was administered to colitis-affected mice for 7 days. Model mice displayed pathological alterations in colon tissue as well as classic symptoms of colitis beyond substantial tissue inflammation. Expression of NLRP3, ASC, and caspase-1 was significantly elevated in the colonic epithelium. The expression of NLRP3 inflammasomes led to activation of downstream proteins and increases in the cytokines IL-18 and IL-1β. SFN administration either fully or partially reversed these changes, thus restoring IL-18 and IL-1β, substantially inhibiting NLRP3 activation, and decreasing inflammation. SFN alleviated the inflammation induced by LPS and NLRP3 agonists in RAW264.7 cells by decreasing the levels of reactive oxygen species. In summary, our results revealed the pathological roles of oxidative stress and NLRP3 in colitis, and indicated that SFN might serve as a natural NLRP3 inhibitor, thereby providing a new strategy for alternative colitis treatment. [Display omitted] ● Sulforaphane ameliorates mice ulcerative colitis. ● Sulforaphane inhibits NLRP3 inflammasome in ulcerative colitis. ● Sulforaphane can reduce ROS content to inhibit NLRP3 inflammasome activation. [ABSTRACT FROM AUTHOR]

Magnesium is one of the essential nutrients for plant growth, and plays a pivotal role in plant development and metabolism. Soil magnesium deficiency is evident in citrus production, which ultimately leads to failure of normal plant growth and development, as well as decreased productivity. Citrus is mainly propagated by grafting, so it is necessary to fully understand the different regulatory mechanisms of rootstock and scion response to magnesium deficiency. Here, we characterized the differences in morphological alterations, physiological metabolism and differential gene expression between trifoliate orange rootstocks and lemon scions under normal and magnesium-deficient conditions, revealing the different responses of rootstocks and scions to magnesium deficiency. The transcriptomic data showed that differentially expressed genes were enriched in 14 and 4 metabolic pathways in leaves and roots, respectively, after magnesium deficiency treatment. And the magnesium transport-related genes MHX and MRS2 may respond to magnesium deficiency stress. In addition, magnesium deficiency may affect plant growth by affecting POD, SOD, and CAT enzyme activity, as well as altering the levels of hormones such as IAA, ABA, GA 3 , JA, and SA, and the expression of related responsive genes. In conclusion, our research suggests that the leaves of lemon grafted onto trifoliate orange were more significantly affected than the roots under magnesium-deficient conditions, further indicating that the metabolic imbalance of scion lemon leaves was more severe. • Magnesium-deficient conditions can inhibit the growth of lemon plants and alter their external morphology. • Magnesium deficiency can affect plant physiological metabolism, and the response degree of scion and rootstock of grafted plants to magnesium deficiency is different. • Magnesium transport-related genes MHX and MRS2 may respond to magnesium deficiency stress. [ABSTRACT FROM AUTHOR]

Purpose: To provides the clinical and genetic characteristics of a series of Chinese patients with X‐linked juvenile retinoschisis (XLRS) through multimodal imaging and next‐generation sequencing. Methods: Thirty patients (60 eyes) from 29 unrelated families of Chinese origin with XLRS were screened using multigene panel testing, and underwent a complete clinical evaluation. All variants identified in this study and reported in the Human Gene Mutation Database were analysed. Results: Twenty‐five distinct variants in the retinoschisin gene were identified, of which eight were novel, and one was de novo. Missense mutations were the most prevalent type, and mutation hot spot was localized in the discoidin domain. The mean Snellen best‐corrected visual acuity was 0.28 ± 0.17. Of all eyes presenting with schisis, 92.86% had lamellar schisis and 62.5% had peripheral schisis. Schisis changes mostly involved inner and outer nuclear layers. X‐linked juvenile retinoschisis (XLRS) patients had a high incidence of complications, and peripheral schisis was a risk factor for it. No obvious genotype–phenotype association was observed. Conclusion: This study provides comprehensive analyses of the genetic and clinical characteristics of XLRS in a cohort of Chinese patients. The fourth de novo mutation in RS1 was identified. And we show that XLRS has a wide spectrum of clinical characteristics; hence, molecular diagnosis is crucial for its diagnosis, differential diagnosis and genetic counselling. Peripheral schisis is a risk factor for the high incidence of complications, and no clear genotype–phenotype correlations were found. [ABSTRACT FROM AUTHOR]

Since the introduction of R-duals by Casazza, Kutyniok and Lammers with the motivation to obtain a general version of duality principle in Gabor analysis, various R-duals and some relaxations of the R-dual setup have been introduced and studied by some mathematicians. They provide a powerful tool in the analysis of duality relations in general frame theory, and are far beyond the duality principle in Gabor analysis. In this paper, we introduce the concept of generalized weak R-dual based on a pair of frames which is a relaxation of the R-dual setup. Using generalized weak R-duals, we characterize the frame properties of a sequence and the equivalence between two frames, prove that the generalized weak R-duals of frames (Riesz bases) are frame sequences (frames), and present a coefficient expression corresponding to the canonical duals of generalized weak R-duals. Some examples are provided to illustrate the generality of the theory. [ABSTRACT FROM AUTHOR]

This paper addresses duality relations in HS‐frame theory. By introducing the notion of HS‐R‐dual sequence, some duality relations and related results are obtained. We prove that a sequence is an HS‐frame (HS‐frame sequence, HS‐Riesz basis) if and only if its HS‐R‐dual sequence is an HS‐Riesz sequence (HS‐frame sequence, HS‐Riesz basis) and characterize the (unitary) equivalence between two HS‐frames in terms of their HS‐R‐duals and transition matrices, respectively. We characterize HS‐R‐duals and prove that, given an HS‐frame, among all its dual HS‐frames, only the canonical dual admits minimal‐norm HS‐R‐dual. And using HS‐R‐duals, we also characterize dual HS‐frame pairs. [ABSTRACT FROM AUTHOR]

Summary: This paper reports a feasible approach to offer LiNi0.8Co0.1Mn0.1O2 (NCM811) layered cathode materials with enhanced lattice ordering and improved electrochemical performance through a nano grinding assisted solid‐state reaction. Different from the commercial precursor method, oxide raw materials, NiO, CoO and MnO2, rather than the hydroxides, was employed as the starting raw material which was milled into submicron size, pressed into pellets and crushed into granular powder. After calcination under oxygen atmosphere under different temperature, such a simple approach provides layered cathode materials with controllable Li/Ni disordering. Powder XRD results show that when sintered at 800°C, a largest I(003)/I (104) ratio is observed, indicating that the cationic disordering is the lowest, as been confirmed by the XRD refinement data, showing that only 1.08% Ni is misplaced at 3b site. For the electrochemical test, the pNCM800 sample presented an initial specific discharge capacity of 203 mAh/g at 0.1C, together with a capacity retention of 91.77% after 100 cycles at 0.5C. Compared to the value of the sample obtained at normal routine (163.8 mAh/g and 74.85%), the improvement in electrochemical behavior is obvious. Furthermore, the rate performance is also improved, with a specific capacity of 144.1 mAh/g even at 5C rate. The reason for such enhancement could be ascribed to the better kinetic process with low interfacial resistance and fast Li diffusion contributed from the promoted lattice ordering. The results obtained in the experiments greatly indicate the significance of the approach in controlling the Li/Ni disordering, and thus offer an alternative routine for the mass production of layered cathode materials besides the so‐called precursor method. [ABSTRACT FROM AUTHOR]