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How are the merits of innovative ideas communicated in science? Here, we conduct semantic analyses of grant application success with a focus on scientific promotional language, which may help to convey an innovative idea's originality and significance. Our analysis attempts to surmount the limitations of prior grant studies by examining the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies: the NIH, the NSF, and the Novo Nordisk Foundation, one of the world's largest private science funding foundations. We find a robust association between promotional language and the support and adoption of innovative ideas by funders and other scientists. First, a grant proposal's percentage of promotional language is associated with up to a doubling of the grant's probability of being funded. Second, a grant's promotional language reflects its intrinsic innovativeness. Third, the percentage of promotional language is predictive of the expected citation and productivity impact of publications that are supported by funded grants. Finally, a computer-assisted experiment that manipulates the promotional language in our data demonstrates how promotional language can communicate the merit of ideas through cognitive activation. With the incidence of promotional language in science steeply rising, and the pivotal role of grants in converting promising and aspirational ideas into solutions, our analysis provides empirical evidence that promotional language is associated with effectively communicating the merits of innovative scientific ideas. [ABSTRACT FROM AUTHOR]

In order to obtain accurate information from low illumination images, we propose a low-light image enhancement method based on guided filter and Gamma correction according to the Retinex model. First, the image is converted into the Lab color space. After that, the guided filter is used to extract the scene's illumination and the parameter of local square window radius is updated by the size of source image. Then, a novel adaptive Gamma correction, based on heat transfer law, is applied to achieve precise illumination intensity. Finally, the illumination component with color information is to obtain the reconstructed enhancement image. The ablation analysis indicates the effectiveness of main part in the proposed method. Through numerous experiments, the proposed method enhances the overall brightness, corrects the color distortion, preserves details, and demonstrates favorable visual results for diverse low-light images. The proposed method also shows certain superiority and comparability in objective and subjective evaluations compared to state-of-the-art methods, and meanwhile remains highly efficient. [ABSTRACT FROM AUTHOR]

[Display omitted] Flexible films with thermal management capability and efficient electromagnetic interference (EMI) shielding performance are highly needed for electronic devices. Moreover, it remains difficult to integrate fire safety performance into the multifunctional film. Thus, a facile multi-interfacial engineering strategy was proposed to prepare a fire resistant MXene-based flexible film with excellent Joule heating and EMI Shielding performance. Specifically, the neighboring and interlayer MXene sheets were respectively bridged by graphene oxide and carbon nanotube via multiple physical and chemical interactions, thus formed a optimized hierarchical microstructure. The resultant film possessesd outstanding Joule heating performance including wide electrical-to-thermal temperature and sensitive conversion ability. Simultaneously, the film exhibited high EMI shielding efficiency (99.97%). Most significantly, after being burned up to 60 min, the film still maintained its flexibility and multifunctional perfprmance benefiting from a large expanded protective layer. The excellent fire resistance and multi-functions endowed the film wide application prospects in advanced electronics. [ABSTRACT FROM AUTHOR]

Extended hybrid continuous mode expands the design bandwidth of the power amplifier (PA) by sacrificing drain efficiency. To balance the performance of drain efficiency and bandwidth, this letter limits the range of relevant parameters of its impedance space through theoretical analysis. An improved high‐efficiency load impedance space is proposed. Through the improved high‐efficiency impedance space, a PA operating at 0.8–2.2 GHz is designed, with a drain efficiency of more than 55% and an output power of more than 38.2 dBm, which verifies the design goals of broadband and high efficiency. [ABSTRACT FROM AUTHOR]

Objectives: This study was aimed to quantitatively assess hyperperfusion using arterial spin labeling (ASL) to predict hemorrhagic transformation (HT) in acute ischemic stroke (AIS) patients. Methods: This study enrolled 98 AIS patients with anterior circulation large vessel occlusion within 24 h of symptom onset. ASL was performed before mechanical endovascular therapy. On pre-treatment ASL maps, a region with relative cerebral blood flow (CBF) ≥ 1.4 was defined as an area of hyperperfusion. The maximum CBF (CBFmax) of hyperperfusion was calculated for each patient. A non-contrast CT scan was performed during the subacute phase for the evaluation of HT. Good clinical outcome was defined as a 90-day modified Rankin scale score of 0–2. Results: The CBFmax of hyperperfusion (odds ratio, 1.023; 95% confidence interval [CI], 1.005–1.042; p = 0.012) was an independent risk factor for the status of HT. The CBFmax of hyperperfusion for HT showed an area under the curve of 0.735 (95% CI, 0.588–0.882) with optimal cutoff value, sensitivity, and specificity being 146.5 mL/100 g/min, 76.9%, and 69.6%, respectively. There was a statistically significant relationship between HT grades (from no HT to PH2) and CBFmax of hyperperfusion with a Spearman rank correlation of 0.446 (p = 0.001). In addition, low CBFmax of hyperperfusion were associated with good functional outcome (95% CI, 17.130–73.910; p = 0.002). Conclusions: High CBFmax of hyperperfusion was independently associated with subsequent HT and low CBFmax of hyperperfusion linked to good functional outcome. There was a positive correlation between HT grade and CBFmax. Clinical relevance statement: Arterial spin labeling is a noninvasive and contrast agent–independent technique, which is sensitive in detecting hyperperfusion. This study shows that the cerebral blood flow of hyperperfusion is associated with clinical prognosis, which will benefit more patients. Key Points: • Quantitative assessment of hyperperfusion using pre-treatment arterial spin labeling to predict hemorrhagic transformation and prognosis in acute ischemic stroke patients. • The maximum cerebral blood flow of hyperperfusion was associated with hemorrhagic transformation and clinical prognosis and higher maximum cerebral blood flow of hyperperfusion was associated with higher grade hemorrhagic transformation. • The maximum cerebral blood flow of hyperperfusion can predict hemorrhagic transformation which enables timely intervention to prevent parenchymal hematoma. [ABSTRACT FROM AUTHOR]

We study the conformation of an amphiphilic comb-like copolymer in a selective solvent by using Brownian dynamics simulations. Our results demonstrate that, there is an optimal total degree of polymerization to form spherical micelles. Only when the total degree of polymerization is less than the optimal total degree of polymerization, a unimolecular spherical micelle can be formed, otherwise, the spherical micelle will be transformed into a cylindrical micelle. When the total degree of polymerization is less than the optimal total degree of polymerization, the radius of gyration and the stretching factor meet an exponential relationship, where the power exponent decreases with the increase of the length of hydrophilic side chains. The fundamental principles uncovered here afford insights for the optimization of molecular design of amphiphilic comb-like copolymers in various applications. [ABSTRACT FROM AUTHOR]

Despite the high prevalence, stroke remains incurable due to the limited regeneration capacity in the central nervous system. Neuronal replacement strategies are highly diverse biomedical fields that attempt to replace lost neurons by utilizing exogenous stem cell transplants, biomaterials, and direct neuronal reprogramming. Although these approaches have achieved encouraging outcomes mostly in the rodent stroke model, further preclinical validation in non-human primates (NHP) is still needed prior to clinical trials. In this paper, we briefly review the recent progress of promising neuronal replacement therapy in NHP stroke studies. Moreover, we summarize the key characteristics of the NHP as highly valuable translational tools and discuss (1) NHP species and their advantages in terms of genetics, physiology, neuroanatomy, immunology, and behavior; (2) various methods for establishing NHP focal ischemic models to study the regenerative and plastic changes associated with motor functional recovery; and (3) a comprehensive analysis of experimentally and clinically accessible outcomes and a potential adaptive mechanism. Our review specifically aims to facilitate the selection of the appropriate NHP cortical ischemic models and efficient prognostic evaluation methods in preclinical stroke research design of neuronal replacement strategies. [ABSTRACT FROM AUTHOR]

Background: 17β-estradiol (E2) residues exhibit harmful effects both for human and animals and have got global attention of the scientific community. Microbial enzymes are considered as one of the effective strategies having great potential for removal E2 residues from the environment. However, limited literature is available on the removal of E2 from wastewater using short-chain dehydrogenase. Results: In this study, 17β-estradiol degrading enzyme (17β-HSD-0095) was expressed and purified from Microbacterium sp. MZT7. The optimal pH and temperature for reaction was 7 and 40 °C, respectively. Molecular docking studies have shown that the ARG215 residue form a hydrogen bond with oxygen atom of the substrate E2. Likewise, the point mutation results have revealed that the ARG215 residue play an important role in the E2 degradation by 17β-HSD-0095. In addition, 17β-HSD-0095 could remediate E2 contamination in synthetic livestock wastewater. Conclusions: These findings offer some fresh perspectives on the molecular process of E2 degradation and the creation of enzyme preparations that can degrade E2. [ABSTRACT FROM AUTHOR]

The T T ¯ deformation is a solvable irrelevant deformation whose properties depend on the sign of the deformation parameter μ. In particular, T T ¯ -deformed CFTs with μ < 0 have been proposed to be holographically dual to Einstein gravity where the metric satisfies Dirichlet boundary conditions at a finite cutoff surface. In this paper, we put forward a holographic proposal for T T ¯ -deformed CFTs with μ > 0, in which case the bulk geometry is constructed by gluing a patch of AdS3 to the original spacetime. As evidence, we show that the T T ¯ trace flow equation, the spectrum on the cylinder, and the partition function on the torus and the sphere, among other results, can all be reproduced from bulk calculations in glue-on AdS3. [ABSTRACT FROM AUTHOR]

Adding a small amount of surfactant to a gas–liquid two-phase flow can markedly change the dynamic behavior of its bubbles. In this study, the lateral motion of a single bubble (deq = 1.99–3.33 mm, Reb = 200–420) contaminated by surfactant and rising in a linear shear flow is experimentally studied. Sodium dodecyl sulfate (SDS) is chosen as the surfactant with concentrations ranging from 10 to 50 ppm. A curved screen is used to generate a stable linear shear flow, and particle image velocimetry is used to measure the quality of the flow field. Bubble motion parameters, including trajectory, aspect ratio, instantaneous velocity, and terminal velocity, are captured using the shadow method with charge-coupled device cameras. The lift coefficient C L is obtained by a quasi-steady-state analysis. The results show that the presence of surfactant inhibits the lateral migration of bubbles rising in a shear flow and that increasing the SDS concentration and bubble equivalent diameter strengthens this inhibition effect. That is, the C L and the net lateral migration distance decreased with SDS concentration and bubble equivalent diameter. In addition, the variation trends of the quasi-steady drag coefficient, bubble terminal velocity, and bubble oscillation frequency with bubble equivalent diameter and SDS concentration also were analyzed. [ABSTRACT FROM AUTHOR]

Sea surface temperature is an important physical parameter in marine research. Accurate prediction of sea surface temperature is important for coping with climate change, marine ecological protection, and marine economic development. In this study, the SST prediction performance of ConvLSTM and ST-ConvLSTM with different input lengths, prediction lengths, and hidden sizes is investigated. The experimental results show that: (1) The input length has an impact on the prediction results of SST, but it does not mean that the longer the input length, the better the prediction performance. ConvLSTM and ST-ConvLSTM have the best prediction performance when the input length is set to 1, and the prediction performance gradually decreases as the input length increases. (2) Prediction length affects SST prediction. As the prediction length increases, the prediction performance gradually decreases. When other parameters are kept constant and only the prediction length is changed, the ConvLSTM gets the best result when the prediction length is set to 2, and the ST-ConvLSTM gets the best result when the prediction length is set to 1. (3) The setting of the hidden size has a great influence on the prediction ability of the sea surface temperature, but the hidden size cannot be set blindly. For ST-ConvLSTM, although the prediction performance of SST is better when the hidden size is set to 128 than when it is set to 64, the consequent computational cost increases by about 50%, and the performance only improves by about 10%. [ABSTRACT FROM AUTHOR]

In surrogate-based optimization (SBO), the recognized issues associated with the high-dimensional surrogate models focus on the prohibitive computational costs and the low model accuracy. However, there is a lack of effective solutions in the face of the ‘curse of dimensionality’. In this paper, we propose a novel Kriging metamodel to remedy this deficiency. The Kriging model based on projection correlation (KPC) introduces the projection correlation into the Kriging modeling process as prior information, taking into account the nature of hyperparameters. The effectiveness and accuracy of the KPC are illustrated through 10–70-dimensional numerical examples. Furthermore, a parallel computing strategy that combines the multi-peak characteristics of expected improvement and minimizing prediction (MEI&MP) is proposed to further improve high-dimensional optimization efficiency and potential. The global performance and optimization efficiency of our method are validated via typical test functions and structural optimization problems. [ABSTRACT FROM AUTHOR]

Grid-stiffened structures are widely used in industrial equipment, where the layout of stiffener unit cells is critical in the structural performance. However, owing to the lack of design techniques, existing stiffener unit cell designs are often achieved only by comparative selection among several common cell configurations. In this study, a deep learning-based intelligent optimization framework for the stiffener unit cell of grid-stiffened panels was proposed. First, a database containing nearly 10,000 stiffener unit cells was generated by traversal while considering the manufacturability. Feature extraction was then performed on the generated database using a variational autoencoder and mapped to a 16-dimensional continuous latent design space according to geometric features. Subsequently, in this latent space, a Gaussian process model was established, and the maximum expected improvement criterion was utilized to drive the model update and optimization search, thus realizing data-driven optimization for the stiffener unit cell of grid-stiffened panels. In three typical numerical examples, compared with the best of the traditional stiffener unit cells, the obtained optimal designs were improved by 25.61%, 25.88%, and 10.66%, respectively, demonstrating the effectiveness of this method as an alternative stiffener unit cell design method. Furthermore, this study also indicates the significant potential of geometric feature extraction and further structural layout optimization via deep learning. [ABSTRACT FROM AUTHOR]

Tubular thin-walled structure has attracted more and more attention because of its light weight and energy absorption characteristic, and has been widely applied to the fields of aerospace and automotive engineering. For millions of years, effective strategies in the biological tissues of nature creatures had evolved to synthesize structures that possess excellent mechanical properties. One impressive example is found in the internal morphology of horsetail plants. In this study, five kinds of the finite element model of multi-cellular thin-walled structures were established inspired by horsetails, and the energy absorption characteristics and crushing force efficiency of the above structures under axial impact loading were investigated by finite element method. Combined with the above bio-mimetic structures with good performance, a novel bio-mimetic multi-cellular thin-walled structure was proposed. The parameter study, including wall thickness, column diameter and impact angle were completed by numerical simulation method. The results show that the specific energy absorption and crushing force efficiency of the new proposed structure are 49.9 kJ/kg and 88.9% respectively, which are significantly higher than those of the conventional structure. The above bio-mimetic thin-walled structure inspired by horsetails can be applied in developing lightweight energy absorbing structure in the field of automotive or aircraft design. [ABSTRACT FROM AUTHOR]

In this work, we continue our work on two dimensional Galilean conformal field theory (GCFT2). Our previous work (2011.11092) focused on the ξ ≠ 0 sector, here we investigate the more subtle ξ = 0 sector to complete the discussion. The case ξ = 0 is degenerate since there emerge interesting null states in a general ξ = 0 boost multiplet. We specify these null states and work out the resulting selection rules. Then, we compute the ξ = 0 global GCA blocks and find that they can be written as a linear combination of several building blocks, each of which can be obtained from a sl(2, ℝ) Casimir equation. These building blocks allow us to give an Euclidean inversion formula as well. As a consistency check, we study 4-point functions of certain vertex operators in the BMS free scalar theory. In this case, the ξ = 0 sector is the only allowable sector in the propagating channel. We find that the direct expansion of the 4-point function reproduces the global GCA block and is consistent with the inversion formula. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to guide an Earth observation satellite equipped with maneuverable sensors for remote sensing using the measurement of the total column ozone (TCO) as the application. The resulting task planning can interpret the measurements in real time and balance the exploration and exploitation of the area of interest intelligently. A Bayesian optimization (BO)-based method is developed to achieve this goal. For comparison, by the nadir-pointing strategy, the satellite always points to and measures the nadir points; whereas by the offset-pointing strategy, the satellite is guided by the BO-based tasking method to measure the location with either larger TCO values or higher model uncertainties. As demonstrated by the simulation results, the proposed tasking method leads to both better prediction accuracy and better precision of the TCO distribution. This reveals that the proposed observation strategy can enhance the efficiency and accuracy of the remote sensing satellite. A comparison with a deterministic offset-pointing method is also presented to demonstrate that the BO-based tasking method is indeed superior. [ABSTRACT FROM AUTHOR]

Graph Neural Networks (GNNs) have been widely used for the representation learning of various structured graph data, typically through message passing among nodes by aggregating their neighborhood information via different operations. While promising, most existing GNNs oversimplify the complexity and diversity of the edges in the graph and thus are inefficient to cope with ubiquitous heterogeneous graphs, which are typically in the form of multi-relational graph representations. In this article, we propose RioGNN, a novel Reinforced, recursive, and flexible neighborhood selection guided multi-relational Graph Neural Network architecture, to navigate complexity of neural network structures whilst maintaining relation-dependent representations. We first construct a multi-relational graph, according to the practical task, to reflect the heterogeneity of nodes, edges, attributes, and labels. To avoid the embedding over-assimilation among different types of nodes, we employ a label-aware neural similarity measure to ascertain the most similar neighbors based on node attributes. A reinforced relation-aware neighbor selection mechanism is developed to choose the most similar neighbors of a targeting node within a relation before aggregating all neighborhood information from different relations to obtain the eventual node embedding. Particularly, to improve the efficiency of neighbor selecting, we propose a new recursive and scalable reinforcement learning framework with estimable depth and width for different scales of multi-relational graphs. RioGNN can learn more discriminative node embedding with enhanced explainability due to the recognition of individual importance of each relation via the filtering threshold mechanism. Comprehensive experiments on real-world graph data and practical tasks demonstrate the advancements of effectiveness, efficiency, and the model explainability, as opposed to other comparative GNN models. [ABSTRACT FROM AUTHOR]

Estrogen contamination is widespread and microbial degradation is a promising removal method; however, unfavorable environments can hinder microbial function. In this study, a natural estrogen 17β-estradiol (E2) was introduced as a degradation target, and a new combination of bacterial carrier was investigated. We found the best combination of polyvinyl alcohol (PVA) and sodium alginate (SA) was 4% total concentration, PVA:SA = 5:5, with nano-Fe3O4 at 2%, and maltose and glycine added to promote degradation, for which the optimal concentrations were 5 g·L−1 and 10 g·L−1, respectively. Based on the above exploration, the bacterial carrier was made, and the degradation efficiency of the immobilized bacteria reached 92.3% in 5 days. The immobilized bacteria were reused for three cycles, and the degradation efficiency of each round could exceed 94%. Immobilization showed advantages at pH 5, pH 11, 10 °C, 40 °C, and 40 g·L−1 NaCl, and the degradation efficiency of the immobilized bacteria was higher than 90%. In the wastewater, the immobilized bacteria could degrade E2 to about 1 mg·L−1 on the 5th day. This study constructed a bacterial immobilization carrier using a new combination, explored the application potential of the carrier, and provided a new choice of bacterial immobilization carrier. [ABSTRACT FROM AUTHOR]

Doxorubicin (Dox) is the standard treatment approach for osteosarcoma (OS), while acquired drug resistance seriously attenuates its treatment efficiency. The present study aimed to investigate the potential roles of metabolic reprogramming and the related regulatory mechanism in Dox-resistant OS cells. The results showed that the ATP levels, lactate generation, glucose consumption and oxygen consumption rate were significantly increased in Dox-resistant OS cells compared with parental cells. Furthermore, the results revealed that the increased expression of estrogen-related receptor alpha (ERRα) was involved in metabolic reprogramming in chemotherapy resistant OS cells, since targeted inhibition of ERRα restored the shifting of metabolic profiles. Mechanistic analysis indicated that the mRNA stability, rather than ERRα transcription was markedly increased in chemoresistant OS cells. Therefore, it was hypothesized that the 3'-untranslated region of ERRα mRNA was methylated by N6-methyladenine, which could further recruit insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) to suppress mRNA decay and increase mRNA stability. IGF2BP1 knockdown downregulated ERRα and reversed the metabolic alteration of resistant OS cells. Additionally, the oncogenic effect of the IGF2BP1/ERRα axis on Dox-resistant OS cells was verified by in vitro and in vivo experiments. Clinical analysis also revealed that the expression levels of IGF2BP1 and ERRα were associated with the clinical progression of OS. Collectively, the current study suggested that the IGF2BP1/ERRα axis could regulate metabolic reprogramming to contribute to the chemoresistance of OS cells. [ABSTRACT FROM AUTHOR]

[Display omitted] • Zn 2 In 2 S 5 shell effectively inhibits oxidation of oxygen vacancies on MoO 3-x. • Zn 2 In 2 S 5 can effectively regulate oxygen defect concentration of MoO 3-x. • MoO 3-x /Zn 2 In 2 S 5 heterojunction exhibits superior CIP removal and ABR inactivation. • The correlation between pollutant active sites and degradation path was revealed. Water pollution caused by organic pollutants and water-borne pathogens has posed a serious threat to human health. Herein, a fully encapsulated core–shell MoO 3-x @Zn 2 In 2 S 5 S-scheme heterojunction was constructed for efficient removal of ciprofloxacin (CIP) and disinfection of antibiotic-resistant bacteria (TC- E. coli). The excellent catalytic performance is attributed to the synergistic advantages of optimized oxygen defect concentration, the protection of oxygen vacancy and enhanced photogenerated carrier separation efficiency. The MO@ZIS-15 with optimum defect density can remove 92.6 % of CIP in 120 min and inactivate 7.7 log TC- E. coli in 75 min. Furthermore, the developed MO@ZIS-15 system has excellent anti-anion and organic matter interference ability, and also exhibit good utilization potentiality in practical water. Combining theoretical calculations and liquid chromatography-mass spectrometry (LC-MS), the structure–function correlation between different CIP active sites and degradation pathway are revealed. Toxicity prediction and cytotoxicity experiments demonstrated that photocatalytic treatment can effectively reduce the ecotoxicity of degradation products. This work provideds a novel vision to design high-efficiency plasma-based photocatalysts for the removal of organic contaminants and disinfection of antibiotic-resistant bacteria. [ABSTRACT FROM AUTHOR]

This study addresses the control problem of simultaneous tracking control and stabilization for underactuated unmanned surface vessels (USVs) with only two available inputs in the surge and yaw directions. Firstly, two velocity modifications are introduced to transform the error dynamics into two decoupled subsystems. Then, a novel error transforming scheme is presented to reduce the complexity of controller expressions and overcome the difficulties caused by underactuated dynamics. Based on the above transforming scheme and the event-triggered control (ETC) mechanism, a unified control method is designed to guarantee that the error states converge to a bounded neighborhood of the origin while excluding the Zeno behavior of the controllers. In addition, two radial basis function neural networks (RBFNNs) are applied to approximate the unknown dynamics and additional control errors caused by the ETC mechanism. Finally, comparative simulation experiments are performed to validate the effectiveness of the proposed controller. • A novel error transforming scheme is presented to simplify the designing procedure. • An ETC based simultaneous tracking and stabilization control strategy is designed. • Some complementary variables are involved to deal with the input saturation constraints. [ABSTRACT FROM AUTHOR]

Red tide is a marine phenomenon caused by the excessive growth of microscopic algae in the ocean. This study aims to analyze the development trends of red tides in the past 20 years and the dynamic external causes that induce red tides based on existing satellite remote sensing and numerical simulation data. And the changes in dominant species of red tides in different seasons are analyzed. The results show significant temperature fluctuations within the week before the red tide occurs, with an average increase of 1.42 °C. In contrast, the change in salinity is relatively small. Meanwhile, ocean fronts are areas in the ocean where different water masses meet and form boundaries. The average strength of ocean fronts increased by 3.7%, indicating enhanced ocean mixing over a short period of time. Under the combined influence of these factors, the probability of a red tide outbreak in the East China Sea increases rapidly. Therefore, this study has important reference value for further research on the causes of red tides and their response to ocean dynamic changes. • Study analyzes 20-year trend of red tides and their dynamic causes. • Before a red tide, average temperature rises by 1.42 °C; salinity changes little. • Increased ocean front strength by 3.7% boosts East China Sea red tide risk. [ABSTRACT FROM AUTHOR]

• For the complex variable-stiffness features of curvilinear paths, non-uniform layouts and variable thicknesses, a unified image characterization method is proposed for the curvilinearly stiffened structures. • A combination strategy of intelligent and gradient optimization has been proposed as an approach to efficiently obtain different types of excellent load-bearing structural forms. • For the curvilinearly stiffened panel, the typical buckling experiments and corresponding FEA have been carried out, exploring the excellent load-bearing mechanism. Curvilinearly stiffened variable-stiffness structures offer excellent load-bearing capacities and design flexibility, particularly for thin-walled structures with cutouts. Nevertheless, the complex combination of numerous variables, buckling failure modes, and unclear load-carrying mechanisms present significant challenges to structural analysis and optimization. Hence, a unified characterization method for nonuniform layouts and variable thicknesses is proposed and an intelligent optimization framework based on structural image learning is established. Buckling experiments on two stiffened panels and a corresponding numerical analysis are performed to verify the effectiveness of the method under axial compressive loading. Results show that the curvilinearly stiffened panel exhibits a superior load-bearing capacity of 28.8% compared with an orthogonally stiffened panel. Specifically, the curvilinearly stiffened panel efficiently transfers axial loads to a broader region and avoids interruptions in the force transmission path by cutouts, thereby resulting in material and buckling failures simultaneously. [ABSTRACT FROM AUTHOR]

Retracted papers often circulate widely on social media, digital news, and other websites before their official retraction. The spread of potentially inaccurate or misleading results from retracted papers can harm the scientific community and the public. Here, we quantify the amount and type of attention 3,851 retracted papers received over time in different online platforms. Comparingwith a set of nonretracted control papers fromthe same journals with similar publication year, number of coauthors, and author impact, we show that retracted papers receive more attention after publication not only on social media but also, on heavily curated platforms, such as news outlets and knowledge repositories, amplifying the negative impact on the public. At the same time, we find that posts on Twitter tend to express more criticism about retracted than about control papers, suggesting that criticism-expressing tweets could contain factual information about problematic papers. Most importantly, around the time they are retracted, papers generate discussions that are primarily about the retraction incident rather than about research findings, showing that by this point, papers have exhausted attention to their results and highlighting the limited effect of retractions. Our findings reveal the extent to which retracted papers are discussed on different online platforms and identify at scale audience criticism toward them. In this context, we show that retraction is not an effective tool to reduce online attention to problematic papers. [ABSTRACT FROM AUTHOR]

Arabidopsis thaliana activating factor 2 (ATAF2) plays extensive regulatory roles in pathogenesis, seedling development, and stress responses. Here, we performed transcriptome analysis on ATAF2 loss- and gain-of-function mutants to identify differentially expressed genes (DEGs). Gene ontology analyses on DEGs reveal that ATAF2 enhances seedling responses to multiple hormone and stress signals. In particular, our transcriptome analysis suggests that ATAF2 promotes ethylene biosynthesis and responses via activating relevant genes. This novel role of ATAF2 was further demonstrated by using multiple ATAF2-null and overexpression lines for reverse transcription quantitative PCR verification, ethylene production measurements, and assays of seedlings growth responses to the ethylene immediate biosynthetic precursor 1-aminocyclopropane-1-carboxylic acid (ACC). ACC suppresses ATAF2 expression to form a negative feedback regulation loop. [ABSTRACT FROM AUTHOR]

The metal-insulator transition makes vanadium dioxide an attractive material for developing reconfigurable optoelectronic components. Here we report on dynamically tunable broadband absorbers consisting of planar multilayered thin films. By thermally triggering the phase transition of vanadium dioxide, the effective impedance of multilayered structures is tuned in or out of the condition of impedance matching to free-space, leading to switchable broadband absorptions. Two types of absorbers are designed and demonstrated by using either the insulating or metallic state of vanadium dioxide at the impedance matched condition. The planar multilayered absorbers exhibit tunable absorption bands over the wavelength ranges of 5–9.3 μm and 3.9–8.2 μm, respectively. A large modulation depth up to 88% is measured. The demonstrated broadband absorbance tunability is of potential interest for reconfigurable bolometric sensing, camouflaging, and modulation of mid-infrared lights. [ABSTRACT FROM AUTHOR]

Text classification is the most fundamental and essential task in natural language processing. The last decade has seen a surge of research in this area due to the unprecedented success of deep learning. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, raising the need for a comprehensive and updated survey. This paper fills the gap by reviewing the state-of-the-art approaches from 1961 to 2021, focusing on models from traditional models to deep learning. We create a taxonomy for text classification according to the text involved and the models used for feature extraction and classification. We then discuss each of these categories in detail, dealing with both the technical developments and benchmark datasets that support tests of predictions. A comprehensive comparison between different techniques, as well as identifying the pros and cons of various evaluation metrics are also provided in this survey. Finally, we conclude by summarizing key implications, future research directions, and the challenges facing the research area. [ABSTRACT FROM AUTHOR]

Magnetic field noise is an important factor causing quantum decoherence in quantum systems. In order to suppress the decoherence effect, magnetic field noise needs to be properly measured and controlled. Magnetic field noise power spectrum measurement using a single trapped ion based quantum spectrum analyzer is a very effective way. In this paper, the magnetic field noise measurement based on dynamic decoupling technique is analyzed theoretically. Furthermore, we use magnetically insensitive transition to measure the magnetic field noise, which has the potential to measure stronger magnetic field noise and speed up the measurement process. In our experiment, we suppress the magnetic field noise by using active feedback control and passive compensation, where the required passive compensation amplitude is obtained by measuring the magnetic field noise spectrum of a single 25Mg+ ion. With the magnetic field noise suppressed, the expected contribution of the magnetic field noise to the stability of the 25Mg+â€"27Al+ ion optical clock can be decreased from 2.8 Ă— 1 0 âˆ' 15 / Ď„ to 7.2 Ă— 1 0 âˆ' 16 / Ď„ . [ABSTRACT FROM AUTHOR]

Pulmonary arteriovenous malformations (PAVMs) are a rare pulmonary arteriovenous direct traffic vascular malformation, which directly connect the pulmonary artery to the pulmonary vein without pulmonary capillary bed. Currently, surgical resection and percutaneous transcatheter embolization are the main mode of treatment. Embolization is gradually becoming the preferred treatment for people with PAVMs, because it is less invasive and easy to repeat. We describe a case of PAVMs with hemoptysis that relapsed again after three times of embolization and then only presented new symptoms of transient ischemic attack. Finally, the patient was treated by Da Vinci robotic-assisted thoracoscopic surgery, and there were no obvious post-operative complications and recurrence. It is the first report of multiple recurrent complex PAVMs and we present our experience with the treatment of recurrent PAVMs. [ABSTRACT FROM AUTHOR]

• We propose and demonstrate a novel FOG configuration to eliminate this 6 dB optical loss by replacing the two directional couplers with two polarization beamsplitters (PBS), which is called PBS-FOG and is advantageous for applications requiring low power assumption. • Implemented a orthogonal demodulation algorithm (ODA) to operate the PBS-FOG in open-loop, which requires only 12 sampling points per modulation cycle to accurately extract the Sagnac phase and hence the rotation rate, without suffering a dynamic range limitation imposed by the length of the sensing fiber coil, similar to that of close-loop I-FOGs. • With a 1-km polarization maintaining coil, we achieved a bias instability and angle random walk of 0.0655°/h and 0.0059°/ h , respectively, with an extended measurement range of more than ± 500°/s, limited by our rotation table. We propose and demonstrate a novel fiber-optic gyroscope (FOG) in which a pair of polarization beam splitters (PBS) is used to route light to and from a Sagnac loop that senses rotation with significantly reduced optical loss. In addition, an orthogonal demodulation algorithm (ODA) is implemented using low-cost digital circuitry in an open-loop configuration to accurately extract the Sagnac phase shift with an extended dynamic range. With a 1-km polarization maintaining coil, we achieved a bias instability and angle random walk of 0.0655°/h and 0.0059°/ h , respectively, with an extended measurement range of more than ± 500°/s and a scale factor nonlinearity of 743 ppm. [ABSTRACT FROM AUTHOR]

Grid-stiffened structures have excellent performance, such as high specific stiffness and strength, and are widely used as critical load-bearing structures in aerospace equipment, including launch vehicles and spacecraft. It is now a well-established fact that curvilinearly stiffened panels with curved stiffener paths and varying stiffness distributions significantly improve load-bearing efficiency. However, existing methods are usually designed based on two clusters of approximately orthogonal stiffeners, which may limit the design flexibility and load-carrying potential of such structures. In the proposed design method, various complex variations of curved stiffener layouts can be characterized with a simple set of variables by establishing a database of stiffener unit cells and feature dimension reduction, as well as using coordinate transformation and monotonicity preserving interpolation methods for geometric dimension reduction, respectively, which allows simultaneous selection of basic stiffener unit cells and adjustment of stiffener paths. Based on the structure characterization with high design flexibility, the hyperparameter dimension reduction of the Kriging model is introduced, thereby forming an optimization framework through multi-level dimension reduction, while ensuring the efficiency of the optimization process. Moreover, an accurate geometric modeling based on NURBS is proposed to meet the needs of designing stiffened structures on various types of complex surfaces. In two typical aerospace cases, the developed structural concept and design method can improve structural performance by over 80 % compared to initial design schemes with straight stiffeners and constant stiffness. The results demonstrate that both the developed structural concept and design methodology effectively enhance the upper performance design limit of stiffened structures. These findings are practically significant for the application of advanced lightweight thin-walled structures in aerospace equipment. [ABSTRACT FROM AUTHOR]

Thin-walled structures are commonly utilized in aerospace and aircraft structures, which are prone to buckling under axial compression and extremely sensitive to geometric imperfections. After decades of efforts, it still remains a challenging issue to accurately predict the lower-bound buckling load due to the impact of geometric imperfections. Up to now, the lower-bound curve in NASA SP-8007 is still widely used as the design criterion of aerospace thin-walled structures, and this series of knockdown factors (KDF) has been proven to be overly conservative with the significant promotion of the manufacturing process. In recent years, several new numerical and experimental methods for determining KDF have been established, which are systematically reviewed in this paper. The Worst Multiple Perturbation Load Approach (WMPLA) is one of the most representative methods to reduce the conservatism of traditional methods in a rational manner. Based on an extensive collection of test data from 1990 to 2020, a new lower-bound curve is approximated to produce a series of improved KDFs. It is evident that these new KDFs have an overall improvement of 0.1–0.3 compared with NASA SP-8007, and the KDF predicted by the WMPLA is very close to the front of the new curve. This may provide some insight into future design guidelines of axially compressed cylindrical shells, which is promising for the lightweight design of large-diameter aerospace structures. [ABSTRACT FROM AUTHOR]

The huge computational cost is a main barrier of structural reliability assessment for complex engineering. Surrogate models can release the CPU burden of reliability assessment, however, it is very challenging to guarantee the prediction accuracy of failure probability. In this study, we propose an Adversarial Learning-Based Kriging model (ALBK), where two models learn from and compete with each other to achieve an improved model accuracy. First, the initial models are established, and fitting accuracy is evaluated by each other with the proposed criterion. Then, the modeling parameters are optimized according to the evaluation results. The data-driven criteria and adversarial relationship promote the evolution of modeling parameters. Moreover, a triple-indicator method is provided to choose the final model and avoid oscillation. The ALBK adjusts modeling parameters with alternative evolution, while the predicted values are more accurate than those of Kriging. Finally, an adaptive ALBK method is provided with new samples added to improve the accuracy of reliability assessment. Through several numerical examples, it can be seen that the ALBK always provides the best results with the fewest assessment calls, and the robustness is also good. [ABSTRACT FROM AUTHOR]

The spatial-temporal modeling on long sequences is of great importance in many real-world applications. Recent studies have shown the potential of applying the self-attention mechanism to improve capturing the complex spatial-temporal dependencies. However, the lack of underlying structure information weakens its general performance on long sequence spatial-temporal problem. To overcome this limitation, we proposed a novel method, named the Proximity-aware Long Sequence Learning framework, and apply it to the spatial-temporal forecasting task. The model substitutes the canonical self-attention by leveraging the proximity-aware attention, which enhances local structure clues in building long-range dependencies with a linear approximation of attention scores. The relief adjacency matrix technique can utilize the historical global graph information for consistent proximity learning. Meanwhile, the reduced decoder allows for fast inference in a non-autoregressive manner. Extensive experiments are conducted on five large-scale datasets, which demonstrate that our method achieves state-of-the-art performance and validates the effectiveness brought by local structure information. [ABSTRACT FROM AUTHOR]

This paper proposes a novel machine learning (ML) gyro calibration method that can achieve higher-accuracy gyro calibration and attitude estimation than the classical extended Kalman filter (EKF) approach when high-accuracy measurements are unavailable. The gyro calibration process is modeled as a time-series problem based on the standard EKF output. Then, a designed ML model is trained by the collected time-series data so that it can conduct gyro calibration by generating an ML correction to the gyro measurement. The proposed ML calibration method does not make assumptions in the form of gyro measurement errors, but directly learns it from data when high-accuracy information is available. Therefore, it is possible to outperform the EKF bias calibration when there is only low-accuracy information. To validate the method, a torque-free CubeSat is simulated using sun sensors and magnetometers to generate higher- and lower-accuracy attitude measurements, respectively. The simulation results show that the ML gyro calibration achieves smaller residual errors compared with the standard EKF. Meanwhile, the EKF attitude estimation accuracy is also improved, as the attitude integration is more accurate using the ML-calibrated gyro measurement. Four ML models based on different principles are examined, including multilayer perceptron, convolutional neural network, recurrent neural network, and Gaussian processes. It is found that, usually, a more sophisticated ML model can capture more gyro error information, but all four models can achieve similar performance with well-tuned parameters. [ABSTRACT FROM AUTHOR]

Traditional high-speed precision motion stage (HSPMS) design pursues high-stiffness structure to achieve fast response. However, such structure leads to high-frequency disturbance near dead zone of friction, which causes poor performance in controlling HSPMS. To this end, this paper proposes the active disturbance rejection control (ADRC)-based mechanical design to reduce the bandwidth of friction disturbance and improve the control performance of HSPMS. It is proved that the low-frequency disturbance can be more effectively tackled by the extended state observer (ESO) in the frame of ADRC. In particular, rigid-flexible coupling (RFC) positioning stage is presented for converting the high-frequency friction disturbance into the low-frequency elastic deformation disturbance by flexure hinges. The experimental tests are carried out for both traditional stage and RFC stage. It is clearly shown that compared with traditional design, the control performance of RFC stage is remarkably promoted. [ABSTRACT FROM AUTHOR]

In this paper, important functional parameters of solid oxide fuel cells are identified by introducing a novel high-speed optimization method, namely adaptive chaotic grey wolf optimization algorithm. The suggested optimization method is obtained by combining the adaptive grey wolf optimization and chaotic grey wolf optimization algorithms. The chaotic algorithm is applied to the basic grey wolf optimization to achieve higher convergence speed, keep the population's diversity, and provide an initial population with uniform distribution. Besides, a nonlinear convergence factor is defined for balancing the global and local exploration abilities. Employing the improved convergence factor resulted in a new version of the grey wolf optimization algorithm, namely adaptive grey wolf optimization algorithm. Adaptive chaotic grey wolf optimization algorithm adopts the advantages of both chaotic grey wolf optimization and adaptive grey wolf optimization methods simultaneously. The adaptive grey wolf optimization algorithm is applied to a 5 kW dynamic tubular stack. The results of the simulation report the lowest values of mean squared error, higher accuracy, higher robustness, and high convergence speed for the adaptive grey wolf optimization algorithm compared to some well-known optimization methods. Besides, the proposed method shows a good agreement with experimental results with lower computational difficulty. [Display omitted] • An adaptive chaotic grey wolf optimization for parameter identification of solid oxide fuel cells is developed. • The proposed ACGWO algorithm is applied on a 5 kW tubular SOFC stack. • Various evaluation criteria and other parameter estimation techniques are discussed. • A comprehensive comparison analysis of different identification approaches is presented. • ACGWO is a competitive method in terms of accuracy, robustness, convergence and statistics. [ABSTRACT FROM AUTHOR]

From the perspective of both fundamental and applied science, it is extremely advisable to develop a facile and feasible strategy for fabricating gels with defined structures. Herein, the authors report the rapid synthesis of patterned gels by conducting frontal polymerization (FP) at millimeter‐scale (2 mm), where a series of microchannels, including linear‐, parallel‐, divergent‐, snakelike‐, circular‐ and concentric circular channels, were used. They have investigated the effect of various factors (monomer mass ratio, channel size, initiator concentration, and solvent content) on FP at millimeter‐scale, along with the propagating rule of the front during FP in these microchannels. In addition, we developed a new microfluidic‐assisted FP (MFP) strategy by combining the FP and microfluidic technique. Interestingly, the MFP can realize the production of hollow‐structured gel in a rapid and continuous fashion, which have never been reported. Our work not only offers an effective pathway towards patterned gels by the microchannel‐conformal FP, but also gives new insight into the continuous production of hollow‐structured materials. Such a method will be beneficial for fabricating vessel and scaffold materials in a flexible, easy‐to‐perform, time and energy saving way. [ABSTRACT FROM AUTHOR]

Background. Circulating tumor cells (CTCs) have been regarded as an independent prognostic marker for metastatic castration-resistant prostate cancer (mCRPC). Its prognostic value, however, in nonmetastatic prostate cancer (NMPC) is still unclear. Purpose. To elucidate whether CTCs can predict the biochemical recurrence (BCR) in NMPC patients following radical prostatectomy (RP) or radiotherapy (RT). Methods. PubMed, Cochrane Database, and Embase and the references in relevant studies were systematically searched. Studies that investigated the correlation of CTCs and BCR in NMPC patients after RP or RT were identified and reviewed. Overall odds ratio (OR) of BCR in such patients with/without CTCs was pooled. We also calculated and pooled overall prevalence of BCR in such CTC-positive patients. Results. In total, 12 studies comprising 1917 participants were eligible for the meta-analysis and showed that the presence of secondary circulating tumor cells (SCTCs) is associated with a higher BCR rate of 59% (95% CI: 22%-88%) in patients with NMPC after RP or RT (OR = 6.12 ; 95% CI: 2.22-16.85; P < 0.001). However, regardless of the presence of primary circulating tumor cells (PCTCs), it has not been shown to be associated with higher BCR. Conclusions. Our research demonstrated that SCTC-positive patients are associated with higher BCR compared to SCTC-negative patients in NMPC. Therefore, it is recommended that NMPC patients undergo CTC surveillance intensively after RP or RT. [ABSTRACT FROM AUTHOR]

In this work, we develop conformal bootstrap for Galilean conformal field theory (GCFT). In a GCFT, the Hilbert space could be decomposed into quasiprimary states and its global descendants. Different from the usual conformal field theory, the quasiprimary states in a GCFT constitute multiplets, which are block-diagonized under the Galilean boost operator. More importantly the multiplets include the states of negative norms, indicating the theory is not unitary. We compute global blocks of the multiplets, and discuss the expansion of four-point functions in terms of the global blocks of the multiplets. Furthermore we do the harmonic analysis for the Galilean conformal symmetry and obtain an inversion formula. As the first step to apply the Galilean conformal bootstrap, we construct generalized Galilean free theory (GGFT) explicitly. We read the data of GGFT by using Taylor series expansion of four-point function and the inversion formula independently, and find exact agreement. We discuss some novel features in the Galilean conformal bootstrap, due to the non-semisimpleness of the Galilean conformal algebra and the non-unitarity of the GCFTs. [ABSTRACT FROM AUTHOR]

Black phosphorus (BP) is a novel two-dimensional nanostructure with wide potential applications in such areas as nanoresonators and nanosensors. In this study, we concentrate on the role of the bending stiffness of the BP monolayer in its mechanical performances, including tension, compression, buckling and bending. Firstly, the stress–strain curve and Young's modulus of the single layer black phosphorus (SLBP) nanoribbon with different chiral structures are obtained in the tension process via the molecular dynamics (MD) simulation. Next, the loading behavior of the SLBP nanoribbon during compression is simulated via MD. It was found that the bending stiffness of the nanoribbon has an essential effect on its postbuckling behaviors, and an empirical formula is proposed which can accurately depict the postbuckling process. Eventually, the bending properties of chiral SLBP nanoribbons are explored via the MD simulation, and the modified expression of the bending stiffness can better predict its large deflection. These findings are beneficial for us to fully understand mechanical responses of BP, which hold implications in engineering new materials and devices at nanoscale. [ABSTRACT FROM AUTHOR]

Aphids are infected by a series of bacteria that can help them survive on specific host plants. However, the associations between aphids and these bacteria are not clear, and the bacterial communities in many aphid species are poorly characterized. Here, we investigated the bacterial communities of cotton aphids (Aphis gossypii) on 2 representative winter host plants and transferred to 3 summer host plants by 16S rDNA sequencing using the Illumina MiSeq platform. Our results revealed that the bacterial communities varied among cotton aphids on hibiscus, cotton aphids on pomegranate, cotton aphids on cotton transferred from hibiscus, cotton aphids on muskmelon transferred from hibiscus, cotton aphids on cucumber transferred from hibiscus,. The diversity and richness of the bacterial communities were significantly higher in aphids on muskmelon and aphids on cucumber than in the other treatments. There were two main factors influencing the distribution of internal bacterial OTUs revealed by principal component analysis, including the differences among Punicaceae, Malvaceae and Cucurbitaceae. There were 28 bacterial communities with significant differences between two arbitrary treatments, which could be grouped into 6 main clusters depending on relative abundance. Moreover, our results indicated that in addition to the obligate endosymbiont Buchnera, with a dominant position (> 52%), A. gossypii also harbored 3 facultative endosymbiotic bacteria (Serratia, Arsenophonus, and Wolbachia) and 3 possibly symbiotic bacteria (Acinetobacter, Pantoea, and Flavobacterium). There were several correspondences between the symbiotic bacteria in cotton aphids and the specific host plants of the aphids. This study provides a better understanding of the interactions among symbiotic bacteria, aphids and host plants, suggesting that the selection pressure on aphid bacterial communities is likely to be exerted by the species of host plants. [ABSTRACT FROM AUTHOR]

BACKGROUND Multiple lasers have been used for the treatment of café au lait macules (CALMs) with various results. Objective tools to predict therapeutic efficacy of CALMs treatment is lacking. OBJECTIVE To determine whether reflectance confocal microscopy (RCM) characteristics correlate with CALMs response to laser treatment. MATERIALS AND METHODS All CAMLs underwent RCM examination of length and density of dermal papillae followed by 3 sessions of Q-switched alexandrite laser (QSAL). A visual analog scale was used to assess clinical treatment efficacy. RESULTS Forty-three patients were included, 22 had CALMs with irregular borders and 21 with smooth borders. Café au lait macules with irregular border had shorter rete pegs and less papillae (p < .05) on RCM compared with smooth border CAMLs and responded better to QSAL treatment (2.32 vs 1.10). CONCLUSION Reflectance confocal microscopy measurement of length and density of papillae were inversely correlated with treatment response. Reflectance confocal microscopy may be a useful tool to predict CALMs response to laser treatment. [ABSTRACT FROM AUTHOR]

This paper presents a broadband linearizer based on equivalent power‐dependent impedance function (PDIF) of diode and load match network (LMN). A method to measure the PDIF is proposed, then the broadband LMN can be synthesized by using the PDIF and the transfer characteristic of the amplifier to realize a broadband linearizer. To verify the proposed method, a linearizer for a 100 W traveling wave tube amplifier (TWTA) is designed and measured from 29 to 31 GHz. By using the linearizer, the output 1‐dB compression point (OP1dB) has increased by more than 1.2 dB, and phase error has reduced by more than 16.9°. Then a two‐tone signal with 100 MHz spacing is used for test, the results show that 12.2 to 14.6 dB suppression of third‐order intermodulation distortion (IMD3) is achieved over the working frequency range without bias tuning. [ABSTRACT FROM AUTHOR]

In order to improve the search performance of rich text content, a cloud search engine system based on rich text content is designed. On the basis of traditional search engine hardware system, several hardware devices such as Solr index server, collector, Chinese word segmentation device and searcher are installed, and the data interface is adjusted. On the basis of hardware equipment and database support, this paper uses the open source Apache Tika framework to obtain the metadata of rich text documents, implements word segmentation according to the rich text content and semantics, and calculates the weight of each keyword. Input search keywords, establish a text index, use BM25 algorithm to calculate the similarity between keywords and text, and output the search results of rich text according to the similarity calculation results. The experimental results show that the design system has high recall rate, high throughput, and the construction time of each data item index in different files is short, which improves the search efficiency and search accuracy. [ABSTRACT FROM AUTHOR]

Atherosclerotic cardiovascular disease (ASCAD) is recognized as a chronic subclinical systemic inflammatory condition. The platelet-albumin ratio (PAR) has shown promise in prognosticating various inflammation-related disorders. Our study aimed to assess the connection between PAR and major adverse cardiovascular events (MACE) in percutaneous coronary intervention (PCI)-treated patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS). PAR, derived from platelet and albumin counts, categorized participants into four quartiles. The primary outcome was composite MACE, encompassing all-cause mortality, non-fatal myocardial infarction (MI), and ischemia-driven revascularization. Secondary outcomes comprised individual MACE components. Multivariate Cox regression evaluated PAR's independent impact on adverse events. The non-linear relationship between the PAR value and MACE was explored using a restricted cubic spline (RCS). Receiver operating characteristic (ROC) analysis was conducted and the area under the curve (AUC) was calculated. Subgroup analysis was used to determine the effect of PAR on MACE in different subgroups. Enrolling 1391 NSTE-ACS patients, high PAR quartiles were correlated with elevated MACE rates (quartile 4 vs. quartile 1: 33.5% vs. 10.2%, p < 0.001). PAR was revealed to be independently related to an increased risk of MACE (quartile 4 vs. quartile 1: HR, 2.04 [95% CI, 1.34–3.08], p = 0.001). RCS indicated a positive PAR-MACE relationship. The AUC of PAR for the 3-year MACE was 0.659 (95% CI: 0.626–0.677, P<0.001). Subgroup analysis showed no significant interactions across subsets. PAR independently predicted MACE risk in PCI-treated NSTE-ACS patients. • PAR Predicts Prognosis: PAR (Platelet-albumin ratio) predicts outcomes in NSTE-ACS (non-ST-segment elevation acute coronary syndrome) patients post-PCI (percutaneous coronary intervention), revealing its potential as a novel prognostic marker. • Higher PAR, Increased MACE Risk: Elevated PAR quartiles link to higher risk of major adverse cardiovascular events (MACE), encompassing mortality, MI (myocardial infarction), and revascularization. • PAR Informs Risk Assessment: PAR's independent association with heightened MACE risk offers a practical tool for risk assessment in NSTE-ACS patients undergoing PCI, aiding tailored interventions. [ABSTRACT FROM AUTHOR]

Steroidal estrogens residues in the environment can be a serious hazard to humans and animals and has been listed as group 1 carcinogens by World Health Organization (WHO). Microbial degradation is one of the effective strategies for the removal of such contaminants. In this study, a low-temperature degrading bacterial strain (Rhodococcus sp. RCBS9) was isolated from the soil of a dairy farm for 17β-estradiol (E2) degradation. The strain RCBS9 exhibited an efficient degradation potential at low temperatures. To lean how different factors influence E2 degradation, we have found a major role of intracellular enzymes in E2 degradation. Genomic and metabolomic analyses have suggested potential degradation genes and four metabolic pathways. These findings provide valuable strain resources for the low temperature bioremediation of E2 contamination and insights into E2 biodegradation mechanism. [Display omitted] • A low-temperature E2-degrading bacterium was isolated from the farm soil. • The E2 degradation efficiency by strain RCBS9 was 71.61% at 10 °C. • Intracellular enzymes were the main contributors to E2 biodegradation. • Four possible biodegradation pathways for E2 were proposed. • Potential degradation genes were predicted by genome sequencing. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fe 3 O 4 modified with saturated long-chain fatty acid was successful for MPs removal. • Ingredients in beverages can affect the removal efficiency of MPs. • The developed adsorption kinetic equation can predict the value of adsorption of MPs. • Electrostatic interaction, and van der Waals force were main forces. Microplastics (MPs) stemming from plastic products have attracted wide attention around the world due to their stealth, persistence and potential threat to humans. It is essential to remove MPs by using eco-friendly and effective methods. In this study, to remove MPs, we proposed to prepare Fe 3 O 4 superhydrophobic magnetic adsorbents (Fe 3 O 4 @C n , n = 12, 14, 16, 18) modified by different saturated fatty acids (C 12 , C 14 , C 16 , C 18) by liquid phase deposition method. Transmission electron microscope, atomic force microscopy, Fourier transform infrared spectroscopy, powder X-ray diffraction, X-ray photoelectron spectroscopy, vibrating sample magnetometry and nitrogen adsorption measurements were applied to characterize the morphology, functional groups, crystalline structures of Fe 3 O 4 @C n as well as its magnetic properties and pore size distribution. It was shown that Fe 3 O 4 @C n exhibited the characteristics of magnetic materials with superhydrophobic properties and thus possessed the ability to separate oil and water. During the removal of MPs in five liquid food systems, Fe 3 O 4 @C 12 exhibited 92.89 % adsorption efficiency, which was ascribed to the electrostatic and chemical bonding interactions between MPs and Fe 3 O 4 @C n , as suggested by density functional theory (DFT) calculations. In addition, the presence of organic matter in water can decrease the removal efficiency of Fe 3 O 4 @C n due to the competitive adsorption effect. Simulation by Langmuir isotherm model suggested that Fe 3 O 4 @C 12 displayed the greatest adsorption efficiency for Polystyrene (PS) (809.29 mg/g), which is higher than that of Fe 3 O 4 @C 14 , Fe 3 O 4 @C 16 , and Fe 3 O 4 @C 18. In addition, Langmuir adsorption isotherm and Gaussian calculations suggested that PS was removed by Fe 3 O 4 @C 12 through an exothermic reaction controlled by chemisorption. Overall, these results indicated that superhydrophobic magnetic materials prepared in this study show high potential for removing MPs in aqueous systems due to their low costs, good environmental friendliness, and high removal performance. [ABSTRACT FROM AUTHOR]