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As the brightest gamma-ray burst ever observed, GRB 221009A provided a precious opportunity to explore spectral line features. In this article, we performed a comprehensive spectroscopy analysis of GRB 221009A jointly with GECAM-C and Fermi/GBM data to search for emission and absorption lines. For the first time we investigated the line feature throughout this GRB including the most bright part where many instruments suffered problems, and identified prominent emission lines in multiple time intervals. The central energy of the Gaussian emission line evolves from about 37 to 6 MeV, with a nearly constant ratio (about 10%) between the line width and central energy. Particularly, we find that both the central energy and the energy flux of the emission line evolve with time as a power law decay with power law index of −1 and −2, respectively. We suggest that the observed emission lines most likely origin from the blue-shifted electron positron pair annihilation 511 keV line. We find that a standard high latitude emission scenario cannot fully interpret the observation, thus we propose that the emission line comes from some dense clumps with electron positron pairs traveling together with the jet. In this scenario, we can use the emission line to directly, for the first time, measure the bulk Lorentz factor of the jet (Γ) and reveal its time evolution (i.e., Γ ∼ t−1) during the prompt emission. Interestingly, we find that the flux of the annihilation line in the co-moving frame keeps constant. These discoveries of the spectral line features shed new and important lights on the physics of GRB and relativistic jet. [ABSTRACT FROM AUTHOR]

Purpose of Review: Pregnancy-induced preeclampsia is a severe pregnancy complication and preeclampsia has been associated with an increased risk of chronic hypertension for offspring. However, the magnitude of the overall effect of exposure to preeclampsia in pregnancy on blood pressure (BP) in offspring is unknown. This systematic review and meta-analysis was sought to systematically assess the effects of preeclampsia on the BP of the offspring. Recent Findings: Of 2550 publications identified, 23 studies were included. The meta-analysis indicated that preeclampsia increases the potential risk of hypertension in offspring. Systolic blood pressure (SBP) was 2.0 mm Hg (95% CI: 1.2, 2.8) and diastolic blood pressure (DBP) was 1.4 mm Hg (95% CI: 0.9, 1.9) higher in offspring exposed to pre-eclampsia in utero, compared to those born to normotensive mothers. The correlations were similar in stratified analyses of children and adolescents by sex, geographic area, ages, and gestational age. Summary: During childhood and young adulthood, the offspring of pregnant women with preeclampsia are at an increased risk of high BP. It is crucial to monitor their BP. [ABSTRACT FROM AUTHOR]

This study was aimed at investigating the purification and identification of serine protease inhibitors, F. tataricum trypsin inhibitor (FtTI) from tartary buckwheat (Fagopyrum tataricum) seeds. The FtTI was isolated by anion exchange chromatography, affinity chromatography, and centrifugal ultrafiltration. Under reducing and nonreducing conditions, an SDS-PAGE analysis showed that the isolated protein consists of a single polypeptide chain with a molecular mass of approximately 14 kDa. The two isoforms of FtTI were confirmed by the mass spectrometric profile where the two peaks corresponded to 11.487 and 13.838 kDa. The complete amino acid sequence of FtTI has been established by automatic Edman degradation and mass spectrometry. The molecule of FtTI consists of 86 amino acid residues containing two disulfide bonds which connect Cys8 to Cys65 and Cys49 to Cys58. The active site of FtTI contains an Asp66–Arg67 bond. The Ki value was calculated using the equation for slow tight binding inhibition which was 1.6 nM for trypsin. FtTI retained its inhibitory activity over a wide range of pH (3–10) and temperature (20–80 °C). FtTI can be rapidly inactivated by the combination of high temperature and high pressure. An analysis of the amino acid sequence suggests that FtTI is a member of the protease inhibitor Ι family. Furthermore, FtTI exhibited a strong inhibitory activity against phytopathogenic fungi. [ABSTRACT FROM AUTHOR]

Motif-based graph local clustering (MGLC) is a popular method for graph mining tasks due to its various applications. However, the traditional two-phase approach of precomputing motif weights before performing local clustering loses locality and is impractical for large graphs. While some attempts have been made to address the efficiency bottleneck, there is still no applicable algorithm for large scale graphs with billions of edges. In this paper, we propose a purely local and index-free method called Index-free Triangle-based Graph Local Clustering (TGLC*) to solve the MGLC problem w.r.t. a triangle. TGLC* directly estimates the Personalized PageRank (PPR) vector using random walks with the desired triangle-weighted distribution and proposes the clustering result using a standard sweep procedure. We demonstrate TGLC*’s scalability through theoretical analysis and its practical benefits through a novel visualization layout. TGLC* is the first algorithm to solve the MGLC problem without precomputing the motif weight. Extensive experiments on seven real-world large-scale datasets show that TGLC* is applicable and scalable for large graphs. [ABSTRACT FROM AUTHOR]

In this paper, we construct the multi-state Dirac stars (MSDSs) consisting of two pairs of Dirac fields. The two pairs of Dirac fields are in the ground state and the first excited state, respectively, with opposite spins to ensure that the system possesses spherical symmetry. We discuss the solutions of the MSDSs under synchronized and nonsynchronized frequencies. By varying the ratio of masses between the two sets of Dirac fields, different branches of solutions can be obtained. Furthermore, we analyze the characteristics of the various MSDSs solutions and analyze the relationship between the ADM mass M of the MSDSs and the synchronized and nonsynchronized frequencies. Subsequently, we calculate the binding energy E B of the MSDSs and discuss the stability of the solutions. Then, we investigated the solutions of the MSDSs under the single particle condition. Finally, we discuss the feasibility of simulating the dark matter halos using MSDSs. [ABSTRACT FROM AUTHOR]

Plastic crystals as barocaloric materials exhibit the large entropy change rivalling freon, however, the limited pressure-sensitivity and large hysteresis of phase transition hinder the colossal barocaloric effect accomplished reversibly at low pressure. Here we report reversible colossal barocaloric effect at low pressure in two-dimensional van-der-Waals alkylammonium halides. Via introducing long carbon chains in ammonium halide plastic crystals, two-dimensional structure forms in (CH3–(CH2)n-1)2NH2X (X: halogen element) with weak interlayer van-der-Waals force, which dictates interlayer expansion as large as 13% and consequently volume change as much as 12% during phase transition. Such anisotropic expansion provides sufficient space for carbon chains to undergo dramatic conformation disordering, which induces colossal entropy change with large pressure-sensitivity and small hysteresis. The record reversible colossal barocaloric effect with entropy change ΔSr ~ 400 J kg−1 K−1 at 0.08 GPa and adiabatic temperature change ΔTr ~ 11 K at 0.1 GPa highlights the design of novel barocaloric materials by engineering the dimensionality of plastic crystals.The authors report the colossal barocaloric effect driven reversibly by low pressure in two dimensional van-der-Waals alkylammonium halides, underlyingly from the disordering of the organic alkyl chains within the two-dimensional structure. [ABSTRACT FROM AUTHOR]

Analyzing scientific advances and networks in NPs research can provide valuable insights into the evolving trends, research gaps, and priorities for future research efforts, highlighting the importance of scientific research in pollution control and risk management of uncontrolled and unknown nanoplastics (NPs) that pose a potential global threat, and have raised concerns in the scientific community and media. A total of 2055 nanoplastics (NPs) studies published from 1995 onwards were retrieved from the Web of Science Core Collection database. Bibliometric methods were applied to assess evolving scientific advances and networks. The general term, "nanoplastics," was first introduced in 1995 as "intelligent" materials. Before 2009, defined as the ambiguous stage, NPs were produced and applied in many different manufacturing areas and processes. The first research referring to nano-scale plastic particles/debris as potential hazardous contaminants appeared in 2010. Thereafter, the number of annual publications on NPs has increased rapidly, particularly from 2018 onwards. Results showed China published 822 scientific papers, overtaking the United States' 229 papers, whereas European researches, i.e., the Netherlands, Portugal, German, and the United Kingdom, led in quality and citation with extensive international collaborations. Furthermore, we concluded three main research themes from keyword cluster analysis: environmental monitoring (identification, quantification, fresh-water, marine-environment); environmental behaviors (fate, adsorption, aggregation, transport); and toxicology (toxicity, exposure, ingestion, oxidative stress). Toxicology and environmental behaviors of NPs were the leading themes. An overview of the current understanding of NPs in the above three major themes provides perspectives to identify future research directions based on knowledge gaps, e.g., advancing analytical methods, and exploring the mobility and fate of NPs in different ecosystems. Scientific research on NPs is a key fundamental requirement for their pollution control and risk management. To bridge the gap between research and reality, future efforts are required to promote the dissemination of scientific research findings and encourage actions in engineering, policy, education, etc., to support a sustainable society. [ABSTRACT FROM AUTHOR]

Search results from the search engine may be not enough to satisfy users’ search intent when the issued query is broad or ambiguous. In such cases, presenting to the user query facets, which include common query reformulations, may help disambiguate the current query, save the effort of query reformulation, and improve the user’s search experience. Existing approaches for mining query facets are mainly based on rule-based statistical features, but ignore the deep semantic information which can measure the relationship between items in facets more precisely and find more potential facet items. In this paper, we introduce a deep learning model with contrastive learning for query facets mining—DeepQFM. We first extract items from search result documents, form lists containing items having a parallel structure, and weight these lists based on their importance. Then, we cluster the weighted lists based on their semantic distance. Finally, we train an item encoder with contrastive sampling and rank the facets and the facet items based on their semantic representation. Experimental results show that our deep query facets mining model outperforms the state-of-the-art approach QDMiner in almost all evaluation metrics, especially for the recall and rp-nDCG, suggesting that DeepQFM can effectively mine more facet items from search result documents. [ABSTRACT FROM AUTHOR]

Understanding the distribution of di(2-ethylhexyl) phthalate (DEHP) is necessary for future risk evaluation of DEHP in agricultural soils. This study used 14C-labeled DEHP to examine its volatilization, mineralization, extractable residues, and non-extractable residues (NERs) incubated in Chinese typical red and black soil with/without Brassica chinensis L. Results showed that after incubated for 60 days, 46.3% and 95.4% of DEHP were mineralized or transformed into NERs in red and black soil, respectively. The distribution of DEHP in humic substances as NER descended in order: humin > fulvic acids > humic acids. DEHP in black soil was more bioavailable, with 6.8% of initial applied radioactivity left as extractable residues at the end of incubation when compared with red soil (54.5%). Planting restrained the mineralization of DEHP by 18.5% and promoted the extractable residues of DEHP by 1.5% for black soil, but no such restrain was observed in red soil. These findings provide valuable information for understanding the distribution of DEHP in different soils and develop the understanding for the risk assessments of PAEs in typical soils. [ABSTRACT FROM AUTHOR]

Over the past half-century, plastic consumption has grown rapidly due to its versatility, low cost, and unrivaled functional properties. Among the different implemented strategies for recycling waste plastics, pyrolysis is deemed the most economical option. Currently, the wax obtained from the pyrolysis of waste plastics is mainly used as a feedstock to manufacture chemicals and fuels or added to asphalt for pavement construction, with no other applications of wax being reported. Herein, the thermal pyrolysis of three common waste polyolefin plastics: high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP), was conducted at 450 °C. The waste plastics-derived waxes were characterized and studied for a potential new application: phase change materials (PCMs) for thermal energy storage (TES). Gas chromatography–mass spectrometry analysis showed that paraffin makes up most of the composition of HDPE and LDPE waxes, whereas PP wax contains a mixture of naphthene, isoparaffin, olefin, and paraffin. Differential scanning calorimetry (DSC) analysis indicated that HDPE and LDPE waxes have a peak melting temperature of 33.8 °C and 40.3 °C, with a relatively high latent heat of 103.2 J/g and 88.3 J/g, respectively, whereas the PP wax was found to have almost negligible latent heat. Fourier transform infrared spectroscopy and DSC results revealed good chemical and thermal stability of HDPE and LDPE waxes after 100 cycles of thermal cycling. Performance evaluation of the waxes was also conducted using a thermal storage pad to understand their thermoregulation characteristics for TES applications. [ABSTRACT FROM AUTHOR]

Fine-grained classification with few labeled samples has urgent needs in practice since fine-grained samples are more difficult and expensive to collect and annotate. Standard few-shot learning (FSL) focuses on generalising across seen and unseen classes, where the classes are at the same level of granularity. Therefore, when applying existing FSL methods to tackle this problem, large amounts of labeled samples for some fine-grained classes are required. Since samples of coarse-grained classes are much cheaper and easier to obtain, it is desired to learn knowledge from coarse-grained categories that can be transferred to fine-grained classes with a few samples. In this paper, we propose a novel learning problem called cross-granularity few-shot learning (CG-FSL), where sufficient samples of coarse-grained classes are available for training, but in the test stage, the goal is to classify the fine-grained subclasses. This learning paradigm follows the laws of cognitive neurology. We first give an analysis of CG-FSL through the Structural Causal Model (SCM) and figure out that the standard FSL model learned at the coarse-grained level is actually a confounder. We thus perform backdoor adjustment to decouple the interferences and consequently derive a causal CG-FSL model called Meta Attention-Generation Network (MAGN), which is trained in a bilevel optimization manner. We construct benchmarks from several fine-grained image datasets for the CG-FSL problem and empirically show that our model significantly outperforms standard FSL methods and baseline CG-FSL methods. [ABSTRACT FROM AUTHOR]

In natural free surface flows, sediment particles in the surface layer of a sediment bed are moved and entrained by the fluctuating hydrodynamic forces, such as lift and drag, exerted by the overlying flow. Accurate prediction of near-bed hydrodynamic forces in rapidly varied flows is vital for coastal sediment transport and morphodynamics. Directly measured hydrodynamic forces within the rapidly varied flows over rough bed layer have been limited by previous spatial averaging shear force studies. Therefore, the direct measurements were designed and adapted to estimate tidal bore forces, including longitudinal (drag) and vertical (lift) force on near-bed sediment particle. Specially designed experiments were conducted to measure the instantaneous forces using a highly sensitive force sensor assembled with a target sphere. A novel 1D-CNN model (i.e. SedimentNet) has been developed for the prediction of hydrodynamic forces and compared with existing machine learning models (i.e. Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Regressor (SVR), XGBoost, k -Nearest Neighbour (k -NN)). The parameters affecting near-bed hydrodynamic forces are also analysed. In the context of machine learning, both conventional dataset split and fivefold cross-validation approaches were implemented. The results indicated that the proposed SedimentNet was able to achieve marginally better cross-validation performance (i.e. R 2 score of 0.77 for drag force, R 2 score of 0.96 for lift force) for the prediction of drag and lift forces. RF and XGBoost were the second best models with R 2 score of 0.73 and 0.95 for drag and lift force prediction, respectively. Results also showed the potential of machine learning models for the efficient prediction of complex hydrodynamic forces in a coastal environment. A use-case edge computing solution for the reported machine learning-based prediction of hydrodynamic forces has also been proposed and discussed to demonstrate the practical implementability of the presented research. [ABSTRACT FROM AUTHOR]

In this paper, we construct Dirac-boson stars (DBSs) model composed of a scalar field and two Dirac fields. The scalar field and both Dirac fields are in the ground state. We consider the solution families of the DBSs for the synchronized frequency ω ~ and the nonsynchronized frequency ω ~ D cases, respectively. We find several different solutions when the Dirac field mass μ ~ D and scalar field frequency ω ~ s are taken in some particular ranges. In contrast, no similar case has been found in previous studies of multistate boson stars. Moreover, we discuss the characteristics of each type of solution family of the DBSs and present the relationship between the ADM mass M of the DBSs and the synchronized frequency ω ~ or the nonsynchronized frequency ω ~ D . Finally, we calculate the binding energy EB of the DBSs and investigate the relationship of EB with the synchronized frequency ω ~ or the nonsynchronized frequency ω ~ D . [ABSTRACT FROM AUTHOR]

We used 14 C-radiolabelling to study the non-extractable residues (NERs) formation of tetrabromobisphenol A (TBBPA) in a humic acid (HA) suspension under catalysis of laccase in the presence of copper. When entering the suspension after TBBPA adsorbing to HA supramolecular associates, Cu2+ at low concentrations (even without toxicity to laccase) significantly reduced the amount and first-order kinetic constant of the NER formation, while Cu2+ had no significant effect on the formation after it was complexed with HA. The inhibition effect of Cu2+ on the NER formation is explained to be attributed to the prevention of laccase-induced oxidation of TBBPA in the voids of HA associates by complexation of Cu2+ with periphery molecules of the associates. The results provide insights into varying effects of heavy metals on the environmental fate of organic contaminants and suggest that co-existing heavy metals could increase their environmental risk by reducing their NER formation. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks. To achieve this goal, we propose to pre-train our foundation model by self-supervised learning with weak semantic correlation data crawled from the Internet and show that promising results can be obtained on a wide range of downstream tasks. Particularly, with the developed model-interpretability tools, we demonstrate that strong imagination ability is now possessed by our foundation model. We believe that our work makes a transformative stride towards AGI, from our common practice of "weak or narrow AI" to that of "strong or generalized AI". Artificial intelligence approaches inspired by human cognitive function have usually single learned ability. The authors propose a multimodal foundation model that demonstrates the cross-domain learning and adaptation for broad range of downstream cognitive tasks. [ABSTRACT FROM AUTHOR]

Removal of organic micropollutants from water through advanced oxidation processes (AOPs) is hampered by the excessive input of energy and/or chemicals as well as the large amounts of residuals resulting from incomplete mineralization. Herein, we report a new water purification paradigm, the direct oxidative transfer process (DOTP), which enables complete, highly efficient decontamination at very low dosage of oxidants. DOTP differs fundamentally from AOPs and adsorption in its pollutant removal behavior and mechanisms. In DOTP, the nanocatalyst can interact with persulfate to activate the pollutants by lowering their reductive potential energy, which triggers a non-decomposing oxidative transfer of pollutants from the bulk solution to the nanocatalyst surface. By leveraging the activation, stabilization, and accumulation functions of the heterogeneous catalyst, the DOTP can occur spontaneously on the nanocatalyst surface to enable complete removal of pollutants. The process is found to occur for diverse pollutants, oxidants, and nanocatalysts, including various low-cost catalysts. Significantly, DOTP requires no external energy input, has low oxidant consumption, produces no residual byproducts, and performs robustly in real environmental matrices. These favorable features render DOTP an extremely promising nanotechnology platform for water purification. Removal of organic micropollutants from water through advanced oxidation processes is hampered by the excessive input of energy and/or chemicals as well as the large amounts of residuals resulting from incomplete mineralization. Here the authors present a new alternative water purification technology to adsorption and advanced oxidation. [ABSTRACT FROM AUTHOR]

Key Smart City applications such as traffic management and public security rely heavily on the intelligent processing of video and image data, often in the form of visual retrieval tasks, such as person Re-IDentification (ReID) and vehicle re-identification. For these tasks, Deep Neural Networks (DNNs) have been the dominant solution for the past decade, for their remarkable ability in learning discriminative features from images to boost retrieval performance. However, it is been discovered that DNNs are broadly vulnerable to maliciously constructed adversarial examples. By adding small perturbations to a query image, the returned retrieval results will be completely dissimilar from the query image. This poses serious challenges to vital systems in Smart City applications that depend on the DNN-based visual retrieval technology, as in the physical world, simple camouflage can be added on the subject (a few patches on the body or car), and turn the subject completely untrackable by person or vehicle Re-ID systems. To demonstrate the potential of such threats, this paper proposes a novel adversarial patch generative adversarial network (AP-GAN) to generate adversarial patches instead of modifying the entire image, which also causes the DNNs-based image retrieval models to return incorrect results. AP-GAN is trained in an unsupervised way that requires only a small amount of unlabeled data for training. Once trained, it produces query-specific perturbations for query images to form adversarial queries. Extensive experiments show that the AP-GAN achieves excellent attacking performance with various application scenarios that are based on deep features, including image retrieval, person ReID and vehicle ReID. The results of this study provide a warning that when deploying a DNNs-based image retrieval system, its security and robustness needs to be thoroughly considered. [ABSTRACT FROM AUTHOR]

Background: Due to their widespread use, sulfonamide antibiotics (SAs) have become ubiquitous environmental contaminants and thus a cause of public concern. However, a complete understanding of the behavior of these pollutants in complex environmental systems has been hampered by the unavailability and high cost of isotopically labeled SAs. Results: Using commercially available uniformly [14C]- and [13C]-labeled aniline as starting materials, we synthesized [phenyl-ring-14C]- and [phenyl-ring-13C]-labeled sulfamethoxazole (SMX), sulfamonomethoxine (SMM), and sulfadiazine (SDZ) in four-step (via the condensation of labeled N-acetylsulfanilyl chloride and aminoheterocycles) or five-step (via the condensation of labeled N-acetylsulfonamide and chloroheterocycles) reactions, with good yields (5.0–22.5% and 28.1–54.1% for [14C]- and [13C]-labeled SAs, respectively) and high purities (> 98.0%). Conclusion: The synthesis of [14C]-labeled SAs in milligram amounts enables the preparation of labeled SAs with high specific radioactivity. The efficient and feasible methods described herein can be applied to the production of a variety of [14C]- or [13C]-labeled SAs for studies on their environmental behavior, including the fate, transformation, and bioaccumulation of these antibiotics in soils and aqueous systems. [ABSTRACT FROM AUTHOR]

Background: Previous reports stated that DNA polymerase ζ is highly expressed in lung cancer tissues. The present study aimed to investigate the roles and underlying mechanism of DNA polymerase ζ in lung cancer cell radioresistance. Methods: The A549 and HCC827 cells were used to evaluate the effects of different doses of radiation on the mRNA and protein expressions of DNA polymerase ζ. Multiple assays, including PCR, western blot, flow cytometry, and EdU have been used to investigate the roles of DNA polymerase ζ on the cellular behaviors of A549 and HCC827 cells. Results: The mRNA and protein expression of REV7L in A549 and HCC827 cells were significantly increased after 6 Gy irradiation compared to the control group. In A549 and HCC827 cells, over-expression of polymerase ζ decreased the radiosensitivity, inhibited cell apoptosis as well as reduced oxidative stress; while the knockdown of polymerase ζ showed the opposite effects. Knockdown of Polymerase ζ in xenograft animal models significantly decreased tumor size and induced oxidative stress of tumor tissues after irradiation. Discussion: Our results provided a theoretical basis for targeting DNA polymerase ζ to improve the radiosensitivity of the lung cancer cells to radiotherapy. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the functions and molecular mechanism of miR-196a in esophageal cancer (EC). miR-196a as well as UHRF2 and TET2 mRNA and protein levels in EC tissues and cells were detected using quantitative real-time PCR or western blot, respectively. Cell proliferation was evaluated via MTT assay. Transwell assays were used to detect cell migration. In addition, the targeted relationship between miR-196a and UHRF2 was assessed through a dual luciferase reporter assay. Enzyme-linked immunosorbent assay was performed to detect the levels of the cytosine intermediates 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). We found increased miR-196a expression in EC tissues and cells but decreased UHRF2 and TET2 expression. Next, functional experiments showed that knockdown of miR-196a or UHRF2 overexpression suppress EC cell proliferation and migration. miR-196a negatively regulates TET2 expression by directly targeting UHRF2. UHRF2 overexpression decreased 5mC levels but increased 5hmC levels. Furthermore, TET2 downregulation reversed the functions of miR-196a inhibition on EC cell proliferation and migration. Collectively, our study suggested that miR-196a was closely related to the progression of EC possibly by regulating the UHRF2/TET2 axis. Thus, miR-196a represents a potential new EC therapeutic target. [ABSTRACT FROM AUTHOR]

Microplastics have received more and more attention worldwide as an emerging persistent pollutant. Soil microplastic pollution can cause serious environmental problems and potentially endanger the soil ecosystems and human health. Currently, most available studies of microplastics have been performed in aquatic environments. However, soil environments have been less studied, and our understanding of microplastic pollution in soil is still lacking. Therefore, based on the existing knowledge, this review firstly focuses on the current situation of microplastic pollution in soil, basically including sources, distribution characteristics, degradation, and migration. Furthermore, analytical methods are briefly discussed, and ecological effects of microplastics in soil are summarized. Soil is a reservoir of microplastics. Microplastics have a wide distribution and high abundance in environmental media, and their distribution in soil exhibits spatial heterogeneity. Microplastics affect soil physicochemical properties, soil microorganisms, soil fauna, and plants through several mechanisms, leading to different ecological effects. Finally, future research directions of soil microplastic pollution are proposed to provide novel ideas for follow-up research. [ABSTRACT FROM AUTHOR]

SimRank is a popular measurement for evaluating the node-to-node similarities based on the graph topology. In recent years, single-source and top-k SimRank queries have received increasing attention due to their applications in web mining, social network analysis, and spam detection. However, a fundamental obstacle in studying SimRank has been the lack of ground truths. The only exact algorithm, Power Method, is computationally infeasible on graphs with more than 10 6 nodes. Consequently, no existing work has evaluated the actual accuracy of various single-source and top-k SimRank algorithms on large real-world graphs. In this paper, we present ExactSim, the first algorithm that computes the exact single-source and top-k SimRank results on large graphs. This algorithm produces ground truths with precision up to 7 decimal places with high probability. With the ground truths computed by ExactSim, we present the first experimental study of the accuracy/cost trade-offs of existing approximate SimRank algorithms on large real-world graphs and synthetic graphs. Finally, we use the ground truths to exploit various properties of SimRank distributions on large graphs. [ABSTRACT FROM AUTHOR]

Tire crumb rubber (TCR) has been widely used in artificial turf fields, however, the potential environmental risk of TCR and the effect of sunlight exposure are scarcely studied. Here, we evaluated leachability of Zn and polycyclic aromatic hydrocarbons (PAHs) in four types of TCRs and acute toxicity of leachates to Daphnia magna. The results showed that all types of TCRs tested released Zn (0.20−1.3 μg/g) and PAHs (9.4−17 μg/g) but only two were lethal to D. magna (mortality 73%). Notably, ultraviolet (UV) irradiation induced TCR to generate acidic leachate (pH ~ 4.8), which contained 24- and 1.2-fold higher concentrations of Zn and PAHs and therefore was more toxic to D. magna than that in the absence of UV treatment. These findings demonstrate source-dependent toxicity of TCR and highlight the need to consider the effect of photoaging when evaluating the environmental risks of TCR. [ABSTRACT FROM AUTHOR]

In this study, we explored the aging processes of a commercial polyethylene (PE) mulch film under UV irradiation and compared the laboratory aged films with films aged in nature. Overall, the aged films obtained from laboratory conditions were similar with that from natural conditions. Among the investigated factors, UV irradiation was crucial in the aging of the films, producing cracks and oxygen-containing functional groups on the films surface, constantly with natural aging. The formation of cracks induced a decrease of mechanical strength as well as the formation of MPs on the surface. The chemical oxidations detected by Fourier-transform infrared spectroscopy (FTIR) usually happened after the observed physical changes during aging. Moreover, a protocol was developed for laboratory preparation of MPs with characteristics similar with that from environmental aging and PE MPs with sizes of 2–400 μm could be produced in large amounts at relatively short period of time. [ABSTRACT FROM AUTHOR]

Background: Vitamin E is the most abundant lipid-soluble antioxidants present in plasma; however, the relationship between serum vitamin E and change in body mass index (BMI)-for-age Z scores in adolescents has not been well described. Methods: This study is a cross-sectional study. Data were analyzed from 4014 adolescents who participated in the National Health and Nutrition Examination Survey. The nutritional status was calculated by BMI Z scores and was classified into normal weight, overweight, and obese. Multivariable-adjusted logistic regression was used to examine the association between serum vitamin E levels with overweight/obesity. Besides, the interaction effects between potential confounders and vitamin E on obesity were further evaluated. Results: After adjusting potential confounders, serum vitamin E levels were negatively associated with overweight/obesity in girls but not in boys. Per standard deviation increment in vitamin E concentrations was associated with a 92% decreased risk of obesity in females. Besides, lower quartiles of serum vitamin E were associated with a higher risk of overweight/obesity in girls. Moreover, the inverse association between serum vitamin E levels and obesity was also found in most subgroups through subgroup analysis. Conclusions: Our study supports the negative association between serum vitamin E levels and overweight/obesity in adolescents. A higher serum vitamin E level may be associated with a reduced probability of obesity in girls, but not in boys. [ABSTRACT FROM AUTHOR]

As network services become more open and convenient, Internet services based on web server are gradually in the leading position in network services. Developing ecosystem is an important way to improve ecological environment and realize economic and social benefits. This paper introduces the importance and potential of developing ecosystem in plain area. With the rapid development of China's economy and society and the continuous improvement of people's living standards, people's requirements for the living environment continue to improve, and air pollution detection and other issues have increasingly attracted people's attention. The form of air pollution is so serious that it has become an urgent practical problem in China. At the same time, basketball is a sport with a broad mass base. Playing basketball has become an important part of many people's lives, and basketball training is also an important part of China's physical education system. The state attaches great importance to the implementation of basketball training and education and the cultivation of basketball talents. In recent years, there are many problems in China's basketball training. It is difficult to achieve good results in basketball training. Sports departments need innovation in basketball education. Knowledge graph visualization can visualize many abstract knowledge and data, which is very useful for stakeholder research. Basketball coaches can use knowledge map visualization to investigate the deficiencies in basketball training and find the innovation in basketball training, so as to improve the level of basketball education in China. Through the research of web server, this paper applies it to air pollution detection and basketball training visualization in plain areas, so as to promote the improvement of air quality and the development of basketball training. [ABSTRACT FROM AUTHOR]

Based on field visits and literature research, the situations of several typical wastewater treatment plants (WWTPs) in the Rhine basin and the Yangtze basin were investigated, to compare the technology and concept of wastewater treatment in these two areas. Our results showed that WWTPs in the Rhine performed well in pollutant removal, and have shifted their focus to energy production and nutrient recovery; While in the Yangtze basin, most WWTPs still operate on the sole concept of pollution treatment. Though China's WWTPs attach importance to water reclamation, the related technologies are still under development. In years to come, the construction of New Concept WWTPs is expected by Chinese famous experts, to integrate sustainable wastewater treatment and energy/nutrient recovery. To better plan its future avenue in wastewater treatment, China is suggested to learn from the successful practice of energy production and nutrient recovery of WWTPs in the Rhine. [ABSTRACT FROM AUTHOR]

Purpose: The survival benefits and which patients with advanced hepatocellular carcinoma (HCC) would benefit from sorafenib plus transarterial chemoembolization (TACE) therapy remain controversial. We aimed to develop a prognostic score model for predicting different prognoses of patients with HCC and portal vein invasion who received sorafenib plus TACE. Methods: This observational study included 167 patients with HCC and portal vein invasion undergoing sorafenib combined with TACE from January 2013 to June 2018 at two hospitals. Multivariate Cox regression analysis was performed using a training cohort (n = 83) to identify critical factors associated with survival. Then, a prognostic score model was established to classify different outcomes and confirmed using a validation cohort (n = 84). Results: Three factors were determined to critically impact survival in the training cohort: portal vein invasion extent, sorafenib-related dermatologic response, and initial radiological response. Using the β-coefficients of these factors, a prognostic score was calculated, and the survival time decreased as the score increased. Based on the prognostic score model, three different prognoses of patients with 0 points, 2–3 points, and > 3 points were stratified with a median survival of 38.0 months, 20.0 months, and 7.0 months, respectively (P < 0.001). Time to progression was also significantly different using the same prognostic index. The prognostic score model was confirmed by the validation cohort. Conclusion: Sorafenib plus TACE is a potential therapy for selected HCC patients with portal vein invasion. This prognostic score model can predict the survival benefits for these patients. [ABSTRACT FROM AUTHOR]

The pollution control of the Rhine is a successful management mode for comprehensive cooperation in environmental governance, which could provide an important reference for the Yangtze River governance. This study explored river basin management and various pollution problems faced by these two rivers at different times, and also includes governance and management effects. The changes in water quality and aquatic life before and after policy implementation had also been compared. The results showed that the International Commission for the Protection of the Rhine (ICPR) made outstanding contributions to the water-quality improvement, demonstrating its management mode was efficient and effective. Cooperative communication and targeted policies are effective ways to improve the water quality of large river basins. Clear division of labor system and phased cooperation-governance objectives are also significant for the inter-provincial cooperative governance of Yangtze River pollution. [ABSTRACT FROM AUTHOR]

Monitoring water environmental quality of large rivers is the basis of river evaluation and local environmental protection worldwide. This study compared the water quality of the Rhine and the Yangtze River, two of the world's most important arteries, based on monitoring data collected from their monitor stations from 2007 to 2018. Dissolved oxygen (DO), pH, chemical oxygen demand (COD)/dissolved organic carbon (DOC) and ammonia-nitrogen (NH3-N) were used to evaluate their water quality. The changing trend, the temporal and special patterns were also analyzed. It was found that the overall water quality of the Rhine in the last decade (p = 0.95) was better than the Yangtze (p = 1.01). Notably, CODMn and NH3-N were identified as main pollution factors of the Rhine and the Yangtze, respectively. This study provided information for water quality modelling, therefore might be helpful for the water quality management of China. [ABSTRACT FROM AUTHOR]

Carbon dots (CDs) are photoluminescent nanomaterials with wide-ranging applications. Despite their photoactivity, it remains unknown whether CDs degrade under illumination and whether such photodegradation poses any cytotoxic effects. Here, we show laboratory-synthesized CDs irradiated with light degrade into molecules that are toxic to both normal (HEK-293) and cancerous (HeLa and HepG2) human cells. Eight days of irradiation photolyzes 28.6-59.8% of the CDs to <3 kilo Dalton molecules, 1431 of which are detected by high-throughput, non-target high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Molecular network and community analysis further reveal 499 cytotoxicity-related molecules, 212 of which contain polyethylene glycol, glucose, or benzene-related structures. Photo-induced production of hydroxyl and alkyl radicals play important roles in CD degradation as affected by temperature, pH, light intensity and wavelength. Commercial CDs show similar photodegraded products and cytotoxicity profiles, demonstrating that photodegradation-induced cytotoxicity is likely common to CDs regardless of their chemical composition. Our results highlight the importance of light in cytocompatibility studies of CDs. Carbon dots have attracted much attention for biomedical applications but potential degradation and associated toxicity are still poorly understood. Here, the authors report on a study into the photo-degradation of carbon dots, the products produced and associated cytotoxicity. [ABSTRACT FROM AUTHOR]

Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to unseen ones so that the latter can be recognised without any training samples. This is made possible by learning a projection function between a feature space and a semantic space (e.g. attribute space). Considering the seen and unseen classes as two domains, a big domain gap often exists which challenges ZSL. In this work, we propose a novel inductive ZSL model that leverages superclasses as the bridge between seen and unseen classes to narrow the domain gap. Specifically, we first build a class hierarchy of multiple superclass layers and a single class layer, where the superclasses are automatically generated by data-driven clustering over the semantic representations of all seen and unseen class names. We then exploit the superclasses from the class hierarchy to tackle the domain gap challenge in two aspects: deep feature learning and projection function learning. First, to narrow the domain gap in the feature space, we define a recurrent neural network over superclasses and then plug it into a convolutional neural network for enforcing the superclass hierarchy. Second, to further learn a transferrable projection function for ZSL, a novel projection function learning method is proposed by exploiting the superclasses to align the two domains. Importantly, our transferrable feature and projection learning methods can be easily extended to a closely related task—few-shot learning (FSL). Extensive experiments show that the proposed model outperforms the state-of-the-art alternatives in both ZSL and FSL tasks. [ABSTRACT FROM AUTHOR]

The accumulation and transformation of 2,2',4,4'-tetrabrominated diphenyl ether (BDE47), one congener of the flame retardants polybrominated diphenyl ethers (PBDEs), in soil-feeding fauna are still unknown. Using radioactivity tracer, we incubated 14C-labelled BDE47 in soil for 21 days in the presence and absence of the geophagous earthworm Metaphire vulgaris. BDE47 accumulated in the earthworm predominantly via oral ingestion of soil, giving a biota-soil accumulation factor (BSAF) value of 1.3 for radioactivity at the end of incubation, and was mostly located in intestine, followed by clitellum (organs region) and skin of earthworms. Accumulation was accompanied by significant decrease of BDE47 concentration in soil porewater and BDE47 mineralization in soil. BDE47 was transformed in the earthworm gut into two metabolites with higher polarities than BDE47. The results provide for the first time insights into accumulation and transformation of lower-brominated congeners of PBDEs in geophagous earthworms, being helpful for environmental risk assessment of PBDEs. [ABSTRACT FROM AUTHOR]

Fate of 2,4,6-tribromophenol (TBP) in environmental matrices is obscure. We used 14C-tracer to investigated mineralization, transformation, and non-extractable residue (NER)-formation of TBP in a soil under continuously oxic, continuously anoxic, and anoxic–oxic alteration conditions. In all cases, TBP rapidly dissipated, mineralized to CO2, and formed NERs in the soil. Considerable amounts of transformation products (2–12%) were detected during the incubation. Marked mineralization (13–26%) indicated that soil microorganisms used TBP as their energy source. About 62–70% of the initial radioactivity was transformed into NERs, being mainly attributed to binding to humic and fulvic acid fractions. TBP transformation was significantly faster under oxic conditions than under anoxic conditions, and was boosted when the soil redox changed from anoxic to oxic state. The results provide new insights into fate of TBP in soil and suggest the importance to evaluate the stability of NERs for risk assessment of TBP in soil. [ABSTRACT FROM AUTHOR]

In this paper, the proposed algorithm provides a fluent and efficient method for repairing very-low quality depth maps of considerable manifold defects for low-cost stereoscopic 3D (S3D) photographing that such a depth map can be easily yielded by 1st-generation Kinect (Kinect-v1). The corresponding framework cascades two repairing portions named discriminative non-segmentation hole filling and edge rectification-by-deforming. The former can discriminatively fill a variety of depth-invalid holes with no need of practically making attribute-discrimination and target segmentation for depth holes. The main portions of the latter contain edge-shifting-rectification and texture-edge guided dual processing for tailoring possible twisted depth edges. Since the ingredients of proposed algorithm are compactly concatenated according to intimate context, most troublesome defects in Kinect-v1 depths can be tackled. Particularly, the proposed algorithm can obtain the restoring coherency for successive depth maps. A series of experimental results under various photographing scenarios can demonstrate that a single Kinect-v1 device can fast tell on the development of very low-cost S3D imaging tool by the proposed algorithm. [ABSTRACT FROM AUTHOR]

Online shopping has become more and more popular in recent years, which leads to a prosperity on online platforms. Generally, the identical products are provided by many sellers on multiple platforms. Thus the comparison between products on multiple platforms becomes a basic demand for both consumers and sellers. However, identifying identical products on multiple platforms is difficult because the description for a certain product can be various. In this work, we propose a novel neural matching model to solve this problem. Two kinds of descriptions (i.e. product titles and attributes), which are widely provided on online platforms, are considered in our method. We conduct experiments on a real-world data set which contains thousands of products on two online e-commerce platforms. The experimental results show that our method can take use of the product information contained in both titles and attributes and significantly outperform the state-of-the-art matching models. [ABSTRACT FROM AUTHOR]

Human–computer conversation is an active research topic in natural language processing. One of the representative methods to build conversation systems uses the sequence-to-sequence (Seq2seq) model through neural networks. However, with limited input information, the Seq2seq model tends to generate meaningless and trivial responses. It can be greatly enhanced if more supplementary information is provided in the generation process. In this work, we propose to utilize retrieved responses to boost the Seq2seq model for generating more informative replies. Our method, called ReBoost, incorporates retrieved results in the Seq2seq model by a hierarchical structure. The input message and retrieved results can influence the generation process jointly. Experiments on two benchmark datasets demonstrate that our model is able to generate more informative responses in both automatic and human evaluations and outperforms the state-of-the-art response generation models. [ABSTRACT FROM AUTHOR]

Search result diversification aims at covering different user intents by returning a diversified document list. Most existing diversity measures require a predefined set of intents for a given query, where it is assumed that there is no relationship across these intents. However, studies have shown that modeling a hierarchy of intents has some benefits over the standard measure of using a flat list of intents. Intuitively, having more layers in the intent hierarchy seems to imply that we can consider more intricate relationships between intents and thereby identify subtle differences between documents that cover different intents. On the other hand, manually building a rich intent hierarchy imposes extra cost and is probably not very practical. In light of these considerations, we first propose a measure to build a hierarchy of intents from a given set of flat intents by clustering per-intent relevant documents and thereby identifying subintents. Furthermore, in our second measure, we consider a variant of our first measure that clusters per-topic relevance documents rather than per-intent ones, which is also intent-free. In addition, we propose our third measure, a simple, completely intent-free measure to search result diversity evaluation, which leverages document similarities. Our experiments based on TREC Web Track 2009–2013 test collections show that our proposed measures have advantages over existing diversity measures despite their low annotation costs. [ABSTRACT FROM AUTHOR]

KRAS is the most frequently mutated oncogene in cancer and encodes a key signalling protein in tumours1,2. The KRAS(G12C) mutant has a cysteine residue that has been exploited to design covalent inhibitors that have promising preclinical activity3–5. Here we optimized a series of inhibitors, using novel binding interactions to markedly enhance their potency and selectivity. Our efforts have led to the discovery of AMG 510, which is, to our knowledge, the first KRAS(G12C) inhibitor in clinical development. In preclinical analyses, treatment with AMG 510 led to the regression of KRASG12C tumours and improved the anti-tumour efficacy of chemotherapy and targeted agents. In immune-competent mice, treatment with AMG 510 resulted in a pro-inflammatory tumour microenvironment and produced durable cures alone as well as in combination with immune-checkpoint inhibitors. Cured mice rejected the growth of isogenic KRASG12D tumours, which suggests adaptive immunity against shared antigens. Furthermore, in clinical trials, AMG 510 demonstrated anti-tumour activity in the first dosing cohorts and represents a potentially transformative therapy for patients for whom effective treatments are lacking. Treatment of KRASG12C-mutant cancer cells with the KRAS(G12C) inhibitor AMG 510 leads to durable response in mice, and anti-tumour activity in patients suggests that AMG 510 could be effective in patients for whom treatments are currently lacking. [ABSTRACT FROM AUTHOR]

The widespread use of bisphenol S (BPS) as a bisphenol A substitute increases its potential of release into the aquatic environments. However, the degradation of BPS in aquatic systems is largely unknown, which will dictate its fate and toxicity. In this study, a bacterial consortium was enriched from river sediments and the dynamic changes of community structure during bacterial acclimation were studied. BPS degrading bacterial strains isolated from the consortium were identified by 16S rRNA analysis. The efficiency of the consortium and strains for BPS degradation were further evaluated. After 28 days of acclimation, the microbial diversity decreased significantly and four bacterial genera Hyphomicrobium, Pandoraea, Rhodococcus, and Cupriavidus with relative abundances of 5.1%–52.8% became dominant in the consortium. Total of two pure strains including Terrimonas pekingensis and Pseudomonas sp. were isolated from the consortium, using BPS as the sole carbon source. The consortium was highly efficient to degrade BPS, and 99% of BPS with an initial concentration of 50 mg/L was removed within 10 days at pH 7 and 30°C. In comparison with the consortium, a single strain cultures had lower BPS degradation efficiency. These findings indicate that BPS will degrade rapidly under aerobic conditions in river sediments and have implication for BPS-contaminated site remediation using the enriched consortium. [ABSTRACT FROM AUTHOR]

High-performance phase change materials (PCMs) are regarded as a promising strategy in thermal energy storage applications. However, pure PCMs exhibit some inherent disadvantages such as leakage, low thermal conductivity and poor thermal cycling stability. Herein, this work presents novel microencapsulated PCMs with nano-Al2O3-enhanced shell materials due to the high thermal conductivity and mechanical properties of nano-Al2O3. And nano-Al2O3 was contributed uniformly to the shell materials through self-assembly of functional materials, forming a connected thermal conductive network for the microencapsulated PCMs and resulting in an enhancement on the thermal conductivity of the microencapsulated PCMs. Results show that thermal conductivity of the obtained microencapsulated PCMs with 8 mass% nano-Al2O3 is improved up to 0.5977 W m−1 k−1 which is about 287.4% compared with that of the pure PCMs. Moreover, the obtained microcapsules enhanced by nano-Al2O3 possess good phase change behavior and excellent thermal cycling stability, whose melting enthalpy can achieve 170.5 J g−1 and almost has no change after 12 times of thermal cycles. [ABSTRACT FROM AUTHOR]

This special issue contains 14 research articles that present solid and novel fundamental research studies in the area of geo-social data and geo-spatial data analytics for autonomous vehicle applications. Experiments compared against eight state-of-the-art image defogging methods on both synthetic and real-world images demonstrate that SH-CycleGAN outperforms state-of-the-art methods and obtains more pleasing visually defogging results. They cannot fully represent the information in high spatial resolution images and tend to yield unsatisfactory segmentation accuracy. [Extracted from the article]