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Key message: Based on transport inhibition and genome-wide analysis, 123 ABC transporters of Euphorbia lathyris were identified, and it was found that the PDR family members ElABCG39 mediated ingenol efflux. Identification of ingenol biosynthetic enzymes and transporters in plant is fundamental to realize its biosynthesis in chassis cells. At present, several key enzymes of the ingenol biosynthesis pathway have been identified, while the mechanisms governing the accumulation or transport of ingenol to distinct plant tissue compartments remain elusive. In this study, transport inhibition analyses were performed, along with genome-wide identification of 123 genes encoding ABC proteins in Euphorbia lathyris L., eventually discovering that a PDR transporter ElABCG39 mediates ingenol transmembrane transport and is localized on the plasma membrane. Expression of this protein in yeast AD1–8 promoted the transmembrane efflux of ingenol with strong substrate specificity. Furthermore, in ElABCG39 RNAi transgenic hairy roots, ingenol transmembrane efflux was significantly reduced and hairy root growth was inhibited. The discovery of the first Euphorbia macrocyclic diterpene transporter ElABCG39 has not only further improved the ingenane diterpenoid biosynthesis regulatory network, but also provided a new key element for ingenol production in chassis cells. [ABSTRACT FROM AUTHOR]

Cold rolling is one of the feasible and effective methods for regulating the microstructure and enhancing the mechanical properties of metallic materials. However, the cold rolling of particulate-reinforced aluminum matrix composites has been rarely studied comprehensively and systematically due to their limited plasticity. In this study, in-situ TiB2/2219Al matrix composites with a comparable ductility to 2219Al matrix were prepared and subjected to T3 treatment, which includes solution treatment, cold rolling, and natural ageing, with varying degrees of rolling reduction. The effects of cold rolling on the dislocation multiplication, grain and texture evolution, precipitation behavior, and mechanical properties were comprehensively investigated and discussed. The results reveal that both total dislocation density and geometrically necessary dislocation density increase with increasing rolling reduction. The average grain size progressively decreases under the joint influence of gradual growth of large grains and increase of small grains. Besides, rolling deformation changes the ageing behavior of composites, resulting in a decrease in precipitation temperature for both θ″ and θ′ phases. Under a large deformation, these phases precipitate at room temperature. Moreover, the types and proportions of textures undergoes a distinct evolution during deformation, with S, Copper and Brass textures being predominantly observed in the composite subjected to a 60% rolling reduction. Additionally, the increase in deformation results in an enhanced hardness and strength at both room temperature and 373 K. However, the strength initially increases but subsequently decreases at 573 K, and the composite with a 20% rolling reduction exhibits the highest strength at 573 K. [ABSTRACT FROM AUTHOR]

Introduction: Recent data have shown elevated infection rates in several subpopulations at risk of SARS-CoV-2 infection and COVID-19, including immunocompromised (IC) individuals. Previous research suggests that IC persons have reduced risks of hospitalization and medically attended COVID-19 with two doses of mRNA-1273 (SpikeVax; Moderna) compared to two doses of BNT162b2 (Comirnaty; Pfizer/BioNTech). The main objective of this retrospective cohort study was to compare real-world effectiveness of third doses of mRNA-1273 versus BNT162b2 at multiple time points on occurrence of COVID-19 hospitalization and medically attended COVID-19 among IC adults in the United States (US). Methods: This retrospective, observational comparative effectiveness study identified patients from the US HealthVerity database from December 11, 2020, through August 31, 2022. Medically attended SARS-CoV-2 infections and hospitalizations were assessed following a three-dose mRNA-1273 versus BNT162b2 regimen. Inverse probability weighting was applied to balance baseline confounders between vaccine groups. Relative risk (RR) and risk difference were calculated for subgroup and sensitivity analyses using a non-parametric method. Results: In propensity score-adjusted analyses, receiving mRNA-1273 vs. BNT162b2 as third dose was associated with 32.4% (relative risk 0.676; 95% confidence interval 0.506–0.887), 29.3% (0.707; 0.573–0.858), and 23.4% (0.766; 0.626–0.927) lower risk of COVID-19 hospitalization after 90, 180, and 270 days, respectively. Corresponding reductions in medically attended COVID-19 were 8.4% (0.916; 0.860–0.976), 6.4% (0.936; 0.895–0.978), and 2.4% (0.976; 0.935–1.017), respectively. Conclusions: Our findings suggest a third dose of mRNA-1273 is more effective than a third dose of BNT162b2 in preventing COVID-19 hospitalization and breakthrough medically attended COVID-19 among IC adults in the US. [ABSTRACT FROM AUTHOR]

High-quality identification schemes are essential for controller design of nonlinear systems in the field of automatic control. In control communities, the prescribed performance technology has received wide attention as a promising methodology because of its quantitative description of the steady-state and transient performance of system control over the past several years. The improved transient performance of the parameter estimation is widely known to enable simplified controller design, reduce system regulation time, and prevent system divergence. However, in system identification communities, few studies on the transient performance of parameter identification have been published because of the difficulties in designing an error variable that reflects the transient performance of parameter identification. To address this problem, this study provides a solution by integrating the prescribed performance technique into the estimator design. In this study, we introduced an adaptively prescribed performance parameter identification for nonlinear sandwich systems subjected to quantitative observations. First, a low-pass filter and forcing variables are developed to construct an identification error expression. Subsequently, an improved prescribed performance function that characterises the error bound of parameter estimation is introduced. Second, the error transformation concept is used to obtain a new system by transforming the raw system such that constraint conditions are avoided. A novel adaptive law is proposed to guarantee original parameter identification using the prescribed performance. Finally, simulation and process examples are presented to illustrate finding results. [ABSTRACT FROM AUTHOR]

Sparrow Search Algorithm (SSA) has recently received more attention in the intelligent optimization group. However, the high randomness and local optimal problems of the algorithm limit the application of the algorithm. In this paper, a novel sparrow search algorithm (NSSA) combined with spawning technology is proposed, which effectively improves the problem of the algorithm falling into local optimization. First of all, it is proposed to replace the traditional stochastic method with the good point set theory to find the initial individual, so that the initial population is more evenly distributed in the search space and improve the quality of the initial solution. Secondly, the spawning strategy of the cuckoo algorithm is integrated into the discoverer stage, which improves the search method of the discoverer and enhances the global search ability, which makes the algorithm avoids the sudden decline of population diversity and premature convergence. Finally, Levy flight and Brownian motion are used to disturb the position of the sparrow dimension by dimension to improve the ability of the algorithm to jump out of the local optimal value in subsequent iterations. By comparing and analyzing NSSA and SSA, DE, ALO, GOA, DOA, HSSA and XSSA algorithms in 12 common evaluation functions and CEC-2017 test functions, and apply NSSA to the TSP problem. The simulation results show the effectiveness and superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

Temporal variability in the macro-mechanics and microstructure induced by periodic water fluctuations during reservoir operation is widespread but adverse for slip zone soils. Herein, taking the slip zone soils of Huangtupo No. 1 landslide in the Three Gorges Reservoir area as a research case, the consolidation undrained (CU) triaxial tests coupled with wetting–drying cycles are organized to address macroscopic temporal variability of shear strength parameters. Then, quantitative microscopic characterizations are performed based on X-ray diffraction (XRD) and scanning electron microscopy (SEM) combined with mercury compression test (MIT). Eventually, the macro and micro connections are identified via gray rational analysis (GRA) and dynamic time warping (DTW) to be thus mathematized. Moreover, the weakened constitutive model is constructed. The test results show that the temporal variability of macroscopic shear strength parameters can be quantified as negative exponential decay. The wetting–drying cycles prominently contribute to the generation of intra-agglomerate pores (0.9–35 μm). Besides, the inter-granular pores (0.007–0.9 μm) and porosity are the connections to bridge microstructural parameters and macroscopic shear strength parameters. Furthermore, empirical equations for macro and micro connections are tentatively derived; the temporal variability of slip zone soils is invited to appropriately model the weakening laws of stress–strain. This study is expected to provide ingenious perspectives and promising references in stability evaluation and even disaster prevention of reservoir landslides. [ABSTRACT FROM AUTHOR]

The tracking framework based on the memory network has gained significant attention due to its enhanced adaptability to variations in target appearance. However, the performance of the framework is limited by the negative effects of distractors in the background. Hence, this paper proposes a method for tracking using Credit Allocation Network to join target and distractor memory. Specifically, we design a Credit Allocation Network (CAN) that is updated online via Guided Focus Loss. The CAN produces credit scores for tracking results by learning features of the target object, ensuring the update of reliable samples for storage in the memory pool. Furthermore, we construct a multi-domain memory model that simultaneously captures target and background information from multiple historical intervals, which can build a more compatible object appearance model while increasing the diversity of the memory sample. Moreover, a novel target–distractor joint localization strategy is presented, which read target and distractor information from memory frames based on cross-attention, so as to cancel out wrong responses in the target response map by using the distractor response map. The experimental results on OTB-2015, GOT-10k, UAV123, LaSOT, and VOT-2018 datasets show the competitiveness and effectiveness of the proposed method compared to other trackers. [ABSTRACT FROM AUTHOR]

Submarine groundwater discharge (SGD) is an important part in the land-sea interactions, which mainly contains three components: submarine fresh groundwater discharge (SFGD), tidal flat recirculated saline groundwater discharge (tidal flat RSGD) and subtidal recirculated saline groundwater discharge (subtidal RSGD). In order to make a more accurate assessment of the impact of SGD on coastal ecological environment, it is necessary to distinguish the main components of SGD. In this study, the Maowei Sea, located in the northern part of the Beibu Gulf, was selected as the study area. Based on the radium (Ra) tracing method, we present a new analytical method for distinguishing the three main components of SGD in this area combined with field data. The average daily flow along the coastline of the Maowei Sea of tidal flat RSGD was slightly higher than that of SFGD, and both two were on the magnitude of 1×105 m3/d. The average daily flow for the subtidal RSGD of the entire subtidal zone of the Maowei Sea reached to the magnitude of 1×106−1×107 m3/d. The long-term variation trend of terrestrial SGD is a valuable information for the study of the influence of terrigenous material on the coastal ecological environment. Based on the results of four sampling periods, it is found that the fluxes of SFGD and tidal flat RSGD in the Maowei Sea had good linear correlation with the net precipitation. As an example, January 2015 to August 2022 were selected as the study periods, and the variation trends of SFGD and tidal flat RSGD were calculated by linear function with net precipitation as the independent variable. The results showed that the flux of tidal flat RSGD was slightly higher than that of SFGD, and the difference between the two is larger in flood season while smaller in dry season. In general, in the coastal range of China, the total SGD flux in the Maowei Sea area is at a high level, and the SFGD flux is at a medium level. [ABSTRACT FROM AUTHOR]

As one of the most destructive geological disasters, a myriad of landslides has revived and developed in the Three Gorges Reservoir area under the combined action of various detrimental factors. Therefore, the pertinently regional landslide susceptibility mapping (LSM) is of great significance for disaster prevention and mitigation. In this study, LSM is prepared by using a boosting-C5.0 decision tree model. Under the landslide verification of on-site investigations, the study area is divided into accumulation and rock areas, and a total of 12 impact factors are selected. TOL and VIF are employed to determine the multicollinearity among the impact factors. The independent training (80%) and validation (20%) datasets are constructed by random sampling for LSM. ANN, C5.0, and SVM are selected for comparative analysis. The results show that there is no rigorous multicollinearity among the impact factors proposed in this paper. The landslide susceptibility in the study area is divided into low, moderate, high, and very high. The highest susceptibility area distributes along the riverside where the landslide ratio is 37.05% in boosting-C5.0 model. Then the ROCs are expropriated to infer the accuracy of each model. The boosting-C5.0 performs the best with the largest area under the curve in both accumulation and rock areas, reaching at 0.991 and 0.990 in the validation sets, respectively. Finally, the composite modification of the 5 validation sets shows that the uncertainty of boosting-C5.0 is concentrated in the intermediate probability areas of susceptibility. This study reveals the feasibility of machine learning in landslide susceptibility assessment, which could provide a basis for the risk management and control of geological disasters. [ABSTRACT FROM AUTHOR]

Some properties of landslide soils are generally recognized as inherently spatially variable because of the heterogeneity of natural geological deposits. Fluctuations in water levels of the Three Gorges Reservoir cause the depth of the groundwater table at landslide toes to change, resulting in fluctuations in the soil water content and significant soil degradation. The spatial variability and temporal weakening of soil properties should be incorporated into the landslide stability analysis. More importantly, rational deformation prediction and stability analysis of landslide numerical models require an advanced soil constitutive model. Herein, taking the Tangjiao landslide as a case study, the statistical characteristics of shear strength parameters were studied based on valuable soil test data. Then, the spatial variability of these parameters was modeled as a random field for the sliding mass. A hypoplastic constitutive model for clay was used to simulate the landslide deformation over 6 years caused by precipitation and changes in the reservoir water level. In addition, soil degradation induced by the fluctuating groundwater level was accounted for in key model parameters on the basis of experimental results. Eventually, the non-intrusive random finite element method was used to compute the landslide deformation and stability for the random field model. Landslide simulation of the deterministic model ignoring the spatial variation of soil parameters was also performed. Simulation results indicate that the difference in the landslide safety factor between the deterministic and random field models is up to 0.14 for the leading edge and up to 0.12 for the trailing edge. Random field models predict greater deformation and less stability than the deterministic model, suggesting that they are more conservative in this specific case. This research can serve as a useful reference for probabilistic stability analyses of riverside landslides considering soil spatial and temporal variability, which may be quantified more precisely in future research based on multi-source data inversion. [ABSTRACT FROM AUTHOR]

Surface rivers play an essential role in carbon cycle processes in karst regions. However, the CO2 diffusion flux from karst rivers under the influence of urbanization has been scarcely examined in the literature. Along these lines, in this work, the CO2 partial pressure (pCO2) and its degassing in a typical karst river (Nanming River and its tributaries) were thoroughly investigated, which are significantly affected by urbanization in Southwest China. From the acquired results, it was demonstrated that the average values of pCO2 in the main stream of the Nanming River in the wet season, dry season, and flat season were 1975.77 ± 714.45 μatm, 1116.08 ± 454.24 μatm, and 976.89 ± 746.37 μatm, respectively. On the other hand, the tributary showed mean pCO2 values of 1770.46 ± 1120.79 μatm, 1638.13 ± 1121.82 μatm, and 1107.74 ± 824.03 μatm in the three different hydrographic periods. Overall, the pCO2 of the Nanming River basin decreased in the following order: wet season > dry season > flat season, while the mainstream of the Nanming River was slightly higher than that of the tributaries in the wet season. However, it was lower than that of the tributaries in the dry and flat seasons. Additionally, more than 90% of the samples displayed a supersaturated state of CO2, which acted as an important source of CO2 in the atmosphere. From a spatial point of view, pCO2 tended to be higher in the western region than in the eastern region, higher in the middle than in the immediate vicinity, and higher in the south during the three seasons. The higher urban areas showed also relatively higher pCO2 than the lower urban areas. The urban land along with the Nanming River's mainstream exhibited a weaker correlation with pCO2 than the urban land along with the main tributaries due to the mainstream's regular management in recent years. Moreover, the pCO2 was mainly influenced by the carbonate rocks dissolution, aquatic organism metabolic processes, and human activities. In the Nanming River basin, the average CO2 diffusion fluxes in the wet season, dry season, and flat season were 147.02 ± 100.3 mmol·m−2·d−1, 76.02 ± 67.45 mmol·m−2·d−1, and 119.28 ± 168.22 mmol·m−2·d−1, respectively, which indicates high potential CO2 emissions. In addition, it was found that urban construction could increase the pCO2 of karst rivers and cause an increase in the CO2 release flux during the regional urban expansion. In view of the increasing intensive and extensive urbanization in karst regions, our findings are helpful to elucidate the characteristics of carbon dioxide emissions from karst rivers under the disturbance of human activities and further deepen the understanding of the carbon balance in karst river basins. [ABSTRACT FROM AUTHOR]

Purpose: Medical image segmentation is the most widely used technique in diagnostic and clinical research. However, accurate segmentation of target organs from blurred border regions and low-contrast adjacent organs in Computed tomography (CT) imaging is crucial for clinical diagnosis and treatment. Methods: In this article, we propose a Multi-Scale Feature Pyramid Fusion Network (MS-Net) based on the codec structure formed by the combination of Multi-Scale Attention Module (MSAM) and Stacked Feature Pyramid Module (SFPM). Among them, MSAM is used to skip connections, which aims to extract different levels of context details by dynamically adjusting the receptive fields under different network depths; the SFPM including multi-scale strategies and multi-layer Feature Perception Module (FPM) is nested in the network at the deepest point, which aims to better focus the network's attention on the target organ by adaptively increasing the weight of the features of interest. Results: Experiments demonstrate that the proposed MS-Net significantly improved the Dice score from 91.74% to 94.54% on CHAOS, from 97.59% to 98.59% on Lung, and from 82.55% to 86.06% on ISIC 2018, compared with U-Net. Additionally, comparisons with other six state-of-the-art codec structures also show the presented network has great advantages on evaluation indicators such as Miou, Dice, ACC and AUC. Conclusion: The experimental results show that both the MSAM and SFPM techniques proposed in this paper can assist the network to improve the segmentation effect, so that the proposed MS-Net method achieves better results in the CHAOS, Lung and ISIC 2018 segmentation tasks. [ABSTRACT FROM AUTHOR]

In this article, we consider the case of a multinational company realizing profits in a country other than its base country. The currencies used in the base and foreign countries are referred to as the domestic and foreign currencies respectively. For its quarterly and yearly financial statements, the company transfers its profits from a foreign bank account to a domestic bank account. Thus, the foreign currency liquidation task consists formally in exchanging over a period T a volume V of cash in the foreign currency f for a maximum volume of cash in the domestic currency d. The foreign exchange (FX) rate that prevails at time t is denoted Xd/f(t) and is defined as the worth of one unit of currency d in the currency f. We assume in this article that the natural logarithm of the FX rate x t = log X d / f (t) follows a discrete generalized Ornstein-Uhlenbeck (OU) process, a process which generalizes the Brownian motion and mean-reverting processes. We also assume minimum and maximum volume constraints on each transaction. Foreign currency liquidation exposes the multinational company to financial risks and can have a significant impact on its final revenues, since FX rates are hard to predict and often quite volatile. We introduce a Reinforcement Learning (RL) framework for finding the liquidation strategy that maximizes the expected total revenue in the domestic currency. Despite the huge success of Deep Reinforcement Learning (DRL) in various domains in the recent past, existing DRL algorithms perform sub-optimally in this task and the Stochastic Dynamic Programming (SDP) algorithm – which yields the optimal strategy in the case of discrete state and action spaces – is rather slow. Thus, we propose here a novel algorithm that addresses both issues. Using SDP, we first determine numerically the optimal solution in the case where the state and decision variables are discrete. We analyse the structure of the computed solution and derive an analytical formula for the optimal trading strategy in the general continuous case. Quasi-optimal parameters of the analytical formula can then be obtained via grid search. This method, simply referred to as "Estimated Optimal Liquidation Strategy" (EOLS) is validated experimentally using the Euro as domestic currency and 3 foreign currencies, namely USD (US Dollar), CNY(Chinese Yuan) and GBP(Great British Pound). We introduce a liquidation optimality measure based on the gap between the average transaction rate captured by a strategy and the minimum rate over the liquidation period. The metric is used to compare the performance of EOLS to the Time Weighted Average Price (TWAP), SDP and the DRL algorithms Deep Q-Network (DQN) and Proximal Policy Optimization (PPO). The results show that EOLS outperforms TWAP by 54%, and DQN and PPO by 15 − 27%. EOLS runs in average 20 times faster than DQN and PPO. It has a performance on par with SDP but runs 44 times faster. EOLS is the first algorithm that utilizes a closed-form solution of the SDP strategy to achieve quasi-optimal decisions in a liquidation task. Compared with state-of-the-art DRL algorithms, it exhibits a simpler structure, superior performance and significantly reduced compute time, making EOLS better suited in practice. [ABSTRACT FROM AUTHOR]

As the largest Phanerozoic accretionary orogenic belt in the world, the Central Asian Orogenic Belt (CAOB) experienced multiple episodes of tectonic and magmatic activities in association with extensive gold mineralization during the early Paleozoic. The newly discovered Baiyinha'er gold deposit in the southwestern CAOB exemplifies a typical structure-controlled gold mineralization due tectonic compression related to oceanic–continental subduction during the closure of the Paleo-Asian Ocean. A sequence of gold-bearing quartz veins and diorite porphyry dykes are emplaced along faults and fractures in a deformed quartz diorite batholith and its host rocks. Gold mineralization is closely associated with the emplacement of quartz veins that were formed in the same stress as the diorite porphyry dykes. They are the results of continued N–S compression. Zircon U–Pb dating yielded identical ages of 433–432 Ma for the diorite porphyry dykes and their host quartz diorite batholith. Furthermore, geochemical analysis reveals that the dioritic rocks (both the batholith and the dykes) belong to a magmatic arc related to the closure of the Paleo-Asian Ocean. The tectonic–magmatic–mineralization processes in the Baiyinha'er and contiguous areas are ascribed to the prolonged oceanic-continental subduction during the closure of the Paleo-Asian Ocean in the early Silurian. Oceanic subduction beneath the Bainaimiao arc led to generation of arc magmatism, forming the quartz diorite pluton in the Baiyinha'er and contiguous areas. Subduction-related tectonic compression resulted in faulting and fracturing of the solidified diorite intrusion and subsequent emplacement of the dioritic magmas along the faults and fractures. Continued and co-axial N–S compression induced new faults and fractures that host the gold-bearing quartz veins. [ABSTRACT FROM AUTHOR]

210Po, 210Pb, and 234Th were determined in water columns of the East China Sea (ECS) to investigate their biogeochemical behaviors during a severe red tide event. Dissolved 210Po, 210Pb, and 234Th accounted for large fractions of the total phases. The abnormally high concentrations of dissolved 210Pb were observed. Partition behaviors of these radionuclides were influenced by particle content effect and particle composition based on distribution coefficient (Kd) vs. total suspended matter (TSM) content and Kd vs. ratios of particulate organic carbon and total suspended matter contents (POC/TSM content ratios). The peaks of mass specific activities of 210Po, 210Pb, and 234Th indicated that degraded particles could have an intensified enrichment ability for radionuclides compared with the surficial suspended matters. Fractionation factor of 210Po and 210Pb (FPo/Pb) (>1) and fractionation factor of 210Po and 234Th (FPo/Th) (>1) were much higher at algal blooming regions than that at non-blooming stations, indicating that algal blooms promoted the fractionation of 210Po against 210Pb and 234Th, and proving that 210Po exhibited a stronger affinity for biogenic particles than 210Pb and 234Th when POC content increased in the sea. POC/210Po, POC/210Pb and POC/234Th ratios (content/activity ratios) sharply decreased with depth in both algal bloom and non-bloom stations. The outbreak of algal bloom promoted the complexity of suspended particles and increased the variability of POC/tracer ratios (content/activity ratios) in the different depth of the shallow seas. More considerations should be taken to the difficulty of the selection of export interface and the suitable tracers when algal blooming occurs. [ABSTRACT FROM AUTHOR]

Background: In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery. Aim of review: Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms. Key scientific concepts of review: This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms. [ABSTRACT FROM AUTHOR]

RGO/Fe3O4/FeCO3-based composite was prepared by a one-step hydrothermal method. The microscopic morphology and structure were studied using analytical techniques including scanning electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The electromagnetic parameters and the wave absorption properties of the composite/paraffin mixture were analyzed by the vector network analyzer. It is divulged that the FeCO3 spheres, Fe3O4 spheres, and the RGO sheets form a fluffy structure rich in microscopic cavities, as well as a good conductive network through the sphere–sheet and sphere–sphere interlap mechanisms, which significantly improves the absorbing performance of the composite. The composite can achieve a maximum reflection loss of − 37.9 dB at a frequency value of 13.9 GHz with a matching thickness of only 6.8 mm. The matching thickness can be adjusted in the range of 5.2–10.0 mm in order to attain a flexible adjustment of the effective microwave absorption band of 9.9–18.0 GHz. Combined with the first-principles calculations, compositing reduces the electron migration energy barrier and thus improves the charge transferring capability. Meanwhile, the interaction of the different components leads to the formation of a special charge transferring channel and the increase of carrier concentration, which enhances the charge transport, as well as the absorbing capacity of the absorbing material. [ABSTRACT FROM AUTHOR]

Drug delivery systems with high content of drug can minimize excipients administration, reduce side effects, improve therapeutic efficacy and/or promote patient compliance. However, engineering such systems is extremely challenging, as their loading capacity is inherently limited by the compatibility between drug molecules and carrier materials. To mitigate the drug-carrier compatibility limitation towards therapeutics encapsulation, we developed a sequential solidification strategy. In this strategy, the precisely controlled diffusion of solvents from droplets ensures the fast in-droplet precipitation of drug molecules prior to the solidification of polymer materials. After polymer solidification, a mass of drug nanoparticles is embedded in the polymer matrix, forming a nano-in-micro structured microsphere. All the obtained microspheres exhibit long-term storage stability, controlled release of drug molecules, and most importantly, high mass fraction of therapeutics (21.8–63.1 wt%). Benefiting from their high drug loading degree, the nano-in-micro structured acetalated dextran microspheres deliver a high dose of methylprednisolone (400 μg) within the limited administration volume (10 μL) by one single intrathecal injection. The amount of acetalated dextran used was 1/433 of that of low drug-loaded microspheres. Moreover, the controlled release of methylprednisolone from high drug-loaded microspheres contributes to improved therapeutic efficacy and reduced side effects than low drug-loaded microspheres and free drug in spinal cord injury therapy. High drug loading improves therapeutic efficacy and reduces side effects in drug delivery. Here, the authors use controlled diffusion of solvents to precipitate drug nanoparticles in polymer particles while the polymer is solidifying and demonstrate the particles for drug delivery in a spinal cord injury model. [ABSTRACT FROM AUTHOR]

In certain regions, submarine groundwater discharge (SGD) into the ocean plays a significant role in coastal material fluxes and their biogeochemical cycle; therefore, the impact of SGD on the ecosystem cannot be ignored. In this study, SGD was estimated using naturally occurring radium isotopes (223Ra and 224Ra) in a subtropical estuary along the Beibu Gulf, China. The results showed that the Ra activities of submarine groundwater were approximately 10 times higher than those of surface water. By assuming a steady state and using an Ra mass balance model, the SGD flux in May 2018 was estimated to be 5.98×106 m3/d and 3.60×106 m3/d based on 224Ra and 223Ra, respectively. At the same time, the activities of Ra isotopes fluctuated within a tidal cycle; that is, a lower activity was observed at high tide and a higher activity was seen at low tide. Based on these variations, the average tidal pumping fluxes of SGD were 1.15×106 m3/d and 2.44×106 m3/d with 224Ra and 223Ra, respectively. Tidal-driven SGD accounts for 24%–51% of the total SGD. Therefore, tidal pumping is an important driving force of the SGD in the Dafengjiang River (DFJR) Estuary. Furthermore, the SGD of the DFJR Estuary in the coastal zone contributes significantly to the seawater composition of the Beibu Gulf and the material exchange between land and sea. [ABSTRACT FROM AUTHOR]

Constructing an accurate and dependable displacement forecasting model is a prerequisite for realizing effective early warning systems of landslide disasters. To overcome the drawbacks of previous displacement prediction models for landslides with step-like deformation characteristics, such as the low prediction accuracy of the mutational displacements and the unclear reliability of the prediction results, we propose a novel hybrid interval forecasting model. This model consists of four parts. First, clustering by fast search and find of density peaks is implemented to distinguish the deformation states of the landslide. Second, the ensemble classifier based on the random forest algorithm is established to identify the deformation states. Third, based on the wild bootstrap, kernel extreme learning machine, and back propagation neural network approaches, the ensemble regressors under different deformation states are built. Finally, by combining the ensemble classifier and ensemble regressors, an interval prediction framework is constructed to realize the dynamic interval prediction of landslide displacement. Taking the Baishuihe landslide as an example, the datasets of three monitoring sites from June 2006 to December 2016 are used to verify the accuracy and reliability of the proposed model. The results show that the proposed model can effectively improve the prediction accuracy of mutational displacements, with the root mean square errors of 28.19 mm, 14.21 mm, and 34.44 mm and the R-squares of 0.9827, 0.9955, and 0.9903, respectively. Moreover, the reliability of the prediction results obtained using this model can be expressed in the flexible prediction intervals (PIs) under different deformation states. The coverage width-based criteria of PIs at 90% nominal confidence are 140.38 mm, 86.61 mm, and 173.68 mm, respectively. In conclusion, the proposed model provides a good basis for developing early warning systems for landslides with step-like deformation characteristics. [ABSTRACT FROM AUTHOR]

The impoundment of the Three Gorges Reservoir in China inevitably caused the reservoir landslides to develop toward instability, which has attracted widespread attention. Taking the Huangtupo Riverside Slump 1# with the structural characteristics of double sliding zones as a case, this study focuses on the sliding zone soils in the hydro-fluctuation belt affected by the periodic fluctuations of reservoir water level. The wetting-drying cycles test is carried out to simulate the cyclic impact of the fluctuations on the sliding zone soils. Hence the weakening law of the strength parameters is illustrated and well characterized by an exponential function model. Considering the different number of wetting-drying cycles, the long-term reliability of the shallow and deep sliding surfaces is quantified via the imbalance thrust force method and reliability theory. The results indicate that the local failure probability of both sliding surfaces gradually rises as the number of wetting-drying cycles increases. In particular, the shallow sliding surface presents a greater local failure probability than that of the deep one since more slices are in the hydro-fluctuation belt. Besides, the sensitivity of the landslide response to the strength parameters is different, and the internal friction angle is much greater than the cohesion. The area of the hydro-fluctuation belt plays a significant role on the long-term reliability of the landslide, which should be closely monitored to guide the reservoir operation. [ABSTRACT FROM AUTHOR]

This study designed a series of low-cost AlxCrFe2Ni2 high-entropy alloys with different Al contents (x = 0.1-1.0 at.) and investigated their microstructure and mechanical properties. The XRD analysis revealed that, with an increase in the Al content, their crystalline structures changed from the initial single face-centered cubic (FCC) one to FCC plus body-centered cubic (BCC) and ordered BCC (B2) structures. The tensile strength and hardness first increased and then dropped with increasing Al content related to the volume fraction of the FCC/BCC phase. At x = 0.9, the as-cast alloy containing 49.1 pct BCC phase exhibited the highest ultimate tensile strength of 1278 MPa with a 12.6 pct ductility. With an increase in the Al content, the alloy fracture mechanism changed from ductile fracture to brittle. [ABSTRACT FROM AUTHOR]

The analysis of landslide monitoring data is important to the study and prediction of landslide deformation but is very challenging. In this research, a data mining method combining two-step clustering, Apriori algorithm and decision tree C5.0 model are proposed, and the Baishuihe Landslide in the Three Gorges Reservoir area is taken as the study case. 6 hydrologic factors related to rainfall and reservoir water level are chosen to carry out the data mining analysis. First, 6 hydrologic triggering factors and the deformation rate of the landslide are clustered by the two-step clustering. Then, the Apriori algorithm is used to mine the association rules between triggering factors and deformation rate. A total of 173 association rules are generated based on the data mining, and 20 rules are selected to be analyzed. At last, the decision tree C5.0 model is built to carry out threshold analysis of hydrologic triggering factors. The results show that monthly cumulative rainfall plays an important role in controlling landslide deformation, and 73.9 mm can be regarded as its threshold. Monthly average water level is the second factor to control landslide deformation. While the monthly maximum daily rainfall has no direct control over the acceleration stage of landslide deformation. The data mining method proposed in this paper has a high accuracy in the study of Baishuihe landslide, which could provide a significant basis for the data analysis and prediction of the accumulative landslide in the Three Gorges Reservoir area. [ABSTRACT FROM AUTHOR]

The paper presents an adaptive identification algorithm via data filtering and improved prescribed performance function for Sandwich systems with hysteresis nonlinearity. By developing a filter in which the filter is simple and easy to realize online and several variables, the estimation error vector can be derived. To improve the transient performance of estimator, a modified prescribed performance function is proposed to constrain the estimation error data through the usage of the predefined domain. For the constrained estimation error condition, the error transformation technique is utilized to simplify the design of the estimator thanks to that the restricted condition is transformed into unconstrained condition. To achieve the convergence of the parameter estimation and assure the predetermined property, a fresh adaptive law is developed. Moreover, the theoretical analysis indicates that the error can converge to a small region based on martingale difference theorem. According to the numerical verification and experimental results, the advantage and practicability of the invented estimator are inspected by comparing the estimators with unconstrained condition. [ABSTRACT FROM AUTHOR]

This study aimed to understand the expression of solute carrier family 12 member 8 (SLC12A8) in breast carcinoma and its biological functions, as well as its effect on the Toll-like receptor /NOD-like receptor (TLR/NLR) signaling pathway. The expression of SLC12A8 was analyzed using the public RNA sequencing dataset from TCGA database and the two datasets from Oncomine database. The former dataset was also used to evaluate the prognostic value of SLC12A8 in breast carcinoma. Real-time qPCR and western blot were applied to measure relative expression of SLC12A8. Functionally, the effect of SLC12A8 on the cells proliferation and motion was studied using cell counting kit 8 and Transwell assays respectively. Mechanistic studies were conducted using Gene Set Enrichment Analysis (GSEA) and confirmed by western blot. As a result, SLC12A8 was upregulated in breast carcinoma, and high levels of SLC12A8 led to a poorer prognosis and can be regarded as an independent prognosticator for patients with breast carcinoma. Functional experiments demonstrated that SLC12A8-knockdown suppressed while SLC12A8-overexpression elevated the viability, invasiveness and motility of breast carcinoma cells. Furthermore, GSEA indicated that high SLC12A8 was positively correlated with TLR/NLR signaling pathway. Silencing SLC12A8 significantly reduced the protein expression of TLR/NLR-related markers, whereas overexpression of SLC12A8 caused an elevation on the protein expression of these markers. All these data suggested that SLC12A8 plays a promoting effect on the cells viability, invasiveness and motility in breast carcinoma by activating TLR/NLR signaling pathway. [ABSTRACT FROM AUTHOR]

The impoundment of the Three Gorges Reservoir has a significant impact on the storage area, where the frequent occurrence of reservoir landslides with great harm has attracted much attention. Taking the Majiagou landslide as a case, this study focuses on the hydro-fluctuation belt affected by the reservoir operation. Under the scheduling of reservoir water level, the landslide displacement associated with the hydro-fluctuation belt presents a step-like deformation and the movement behaves as a retrogressive type. The wetting-drying cycles test has been performed to simulate the effects of reservoir water level on the hydro-fluctuation belt. Then, the weakening of soil strength parameters is well characterized by an exponential function model. Considering the continuous weakening of the hydro-fluctuation belt, the time-varying reliability, consistent with the actual landslide zoning, is analyzed under the reservoir operation for 10 years. The results indicate that the migration of seepage field in the landslide is closely related to the scheduling of reservoir water level and lags behind the scheduling. Similarly, the factor of safety varies with the reservoir water level, and the minimum value is obtained when the water drops to the lowest level. With the repeated interaction of reservoir water level on the hydro-fluctuation belt, the most dangerous failure probability of the landslide gradually increases. As a result, the stability of the Majiagou landslide declines from the initial basic stable to the less stable state. [ABSTRACT FROM AUTHOR]

This paper is concerned with the identification of turntable servo system through the usage of a reframed multi-innovation least-squares scheme. A Wiener–Hammerstein model is employed in this paper to depict the dynamic characteristics of the turntable system. In the test bed, the stabilized platform can be considered as a linear dynamic subsystem. The motor is also a linear dynamic subsystem. And the major nonlinearity characteristic between motor and platform is captured by a continuously differentiable friction model. A new reframed multi-innovation least-squares approach (RMILS) is proposed to identify the Wiener–Hammerstein model. By introducing the intermediary step updating, the innovation updating is decomposed into sub-innovations updating, which can solve the inverse of covariance matrix and improve the identification performance. Then, the consistency nature of the RMILS method is discussed by using the theoretical analysis. Finally, the simulation and experiment results explain that the developed approach produces an outstanding performance in convergence speed and identification precision comparing to the conventional multi-innovation least-squares approach. [ABSTRACT FROM AUTHOR]

Slip zone soils play a crucial role in the evolution of landslides. In this paper, slip zone soils of the Huangtupo Landslide in the Three Gorges Reservoir area, which is an ancient landslide affected by water level fluctuation, are taken as an example to research the influence of wetting–drying cycles on soil properties. The mercury intrusion porosimetry test is used to study the soil's microstructure, while the triaxial test is used to measure the mechanical parameters. The experimental results indicate that the wetting–drying cycles can change the micropore structures and macro-mechanical properties of the soils. Meanwhile, it is demonstrated that there is a certain relationship between the macro- and micro-properties. From the microcosmic perspective, the fractal structure unit formed in the long-term geological environment is the key factor affecting the mechanical properties of the slip zone soils. Then, based on fractal theory, a weakening model of slip zone soils during wetting–drying cycles is proposed. The correctness and reliability of the model are verified by the mechanical parameters from triaxial tests. Finally, it is indicated that the weakening model can be used to forecast the weakening coefficient of slip zone soils under wetting–drying action, which results from the periodic fluctuations of the reservoir level. [ABSTRACT FROM AUTHOR]

Landslide displacement prediction is an important aspect of landslide hazard research. In this paper we assess the characteristics of landslide deformation in the Three Gorges Reservoir Area of China and propose and apply a step-like displacement prediction model based on a kernel extreme learning machine with grey wolf optimization (GWO-KELM) to the Baishuihe landslide. In this model, the cumulative displacement is first decomposed into trend displacement and periodic displacement by time series. The trend displacement is then predicted by a cubic polynomial model, and the periodic displacement is predicted by the proposed model after the displacement data have been statistically analyzed. A hybrid model is then established for the prediction of landslide displacement. We then compare the performance of this hybrid model with that of the extreme learning machine with GWO (GWO-ELM), support vector machine with GWO (GWO-SVM) and extreme learning machine (ELM) models. The results show that the proposed hybrid model outperforms the other models and that the GWO-KELM model achieves excellent performance in predicting landslide displacement with a step-like behavior. [ABSTRACT FROM AUTHOR]

Conventional landslide analyses, based on deterministic methods or simple random variable methods, cannot consider the spatial variability and the depth-dependent nature of saturated hydraulic conductivity (Ks) in accumulative landslides. However, studies show that these conditions exist objectively and have a large impact on the seepage and deformation of landslides. Thus, the non-stationary characteristics of Ks need to be properly accounted for. In this paper, the Baishuihe landslide is taken as a case study. First, based on surface nuclear magnetic resonance (surface-NMR) technology, spatial variability and the depth-dependent nature of the Ks are obtained. Then, a non-stationary random field model is established to model the trend and fluctuating components of the Ks individually, and a deterministic model is established to model the trend of the Ks with depth. Finally, numerical simulations of the stochastic model and deterministic model under reservoir water fluctuation conditions are carried out by the non-intrusive stochastic finite element method, and the seepage-deformation and stability characteristics of the landslide are analyzed. The results show that compared with that in the deterministic model, the change in pore pressure in the stochastic model obviously lags, during reservoir water drawdown, the displacement of the trailing edge in the stochastic model is larger than that in the deterministic model, with increasing reservoir water deceleration, the hysteresis of the pore pressure in the stochastic model is more notable, and the deformation is larger and the stability is worse in the stochastic model. It is demonstrated that ignoring the spatial variability of the Ks will overestimate the stability of the landslide. [ABSTRACT FROM AUTHOR]

Using a bottom simulating reflector (BSR) on a seismic profile to identify marine gas hydrate is a traditional seismic exploration method. However, owing to the abundance differences between the gas hydrate and free gas in different regions, the BSR may be unremarkable on the seismic profile and invisible in certain cases. With the improvement of exploration precision, difficulty arises in meeting the requirements of distinguishing the abundance differences in the gas hydrate based on BSR. Hence, we studied other sensitive attributes to ascertain the existence of gas hydrate and its abundance variations, eventually improving the success rate of drilling and productivity. In this paper, we analyzed the contradiction between the seismic profile data and drilling sampling data from the Blake Ridge. We extracted different attributes and performed multi-parameter constraint analysis based on the prestack elastic wave impedance inversion. Then, we compared the analysis results with the drilling sampling data. Eventually, we determined five sensitive attributes that can better indicate the existence of gas hydrate and its abundance variations. This method overcomes the limitations of recognizing the gas hydrate methods based on BSR or single inversion attribute. Moreover, the conclusions can notably improve the identification accuracy of marine gas hydrate and provide excellent reference significance for the recognition of marine gas hydrate. Notably, the different geological features of reservoirs feature different sensitivities to the prestacking attributes when using the prestack elastic inversion in different areas. [ABSTRACT FROM AUTHOR]

Ocean-Bottom Node (OBN) acquisitions provide both non-converted and converted reflection energy. There is a clear advantage to independently imaging both P- and S-waves, as they provide more information collectively than either does alone. In many conventional converted-wave pre-stack migration algorithms, density is treated as a constant, which is not the real-life case on earth. S-wave velocity and density information is crucial for hydrocarbon detection because it helps in the identification of pore-filling fluids. In this paper, we focused on the effect of density on imaging, and developed a method of reverse-time migration (RTM) on converted s-waves of varying densities (VD-RTMCS). Phase correction was required prior to pre-stack migration to avoid constructive interference between data from adjacent sources. Synthetic data examples showed that when density variations were included, image profiles showed advantages in signal-to-noise ratio, vertical resolution and imaging of complex structures. [ABSTRACT FROM AUTHOR]

In early 2008, southern China experienced a severe freezing snow event, causing many geological disasters (such as landslides). Based on combining the infinite slope model and the snowmelt effect, an effective snowmelt model (ESM) is proposed to calculate the stability of landslides. The geological mechanics model of snowmelt-induced landslides is established with the Enshi area as a case study. The landslide susceptibility in the Enshi area is evaluated based on the set pair analysis and analytical hierarchy process. Then, the hazard grade of snowmelt-induced landslides is predicted and classified by the calculation results of ESM. And the warning grade of Enshi is determined based on the landslide susceptibility and the hazard grade. The results indicate the following: (1) High-susceptibility areas in Enshi are mainly concentrated in the regions of Badong County and Lichuan County. (2) The snowmelt hazard in the rock group with a high susceptibility is considered a medium-level hazard and the other areas are low-level hazards. (3) A total of 94.73% of the study region is a no-warning area, and the levels 3 and 4 warning zones account for 1.04% and 4.23%, respectively. (4) The increases in the slope gradient α and the slip zone depth Z lead to a decreasing initial stability and decreased influence of snowmelt water infiltration. (5) The snowmelt threshold can be calculated by the ESM model, and different snowmelt risk levels can be classified according to the relationship between the snowmelt threshold and the slope gradient. [ABSTRACT FROM AUTHOR]

Radiation is a form of energy derived from a source that is propagated through material in space. It consists of ionizing radiation or nonionizing radiation. Ionizing radiation is a feature of the environment and an important tool in medical treatment, but it can cause serious damage to organisms. A number of protective measures and standards of protection have been proposed to protect against radiation. There is also a need for biomarkers to rapidly assess individual doses of radiation, which can not only estimate the dose of radiation but also determine its effects on health. Proteomics, genomics, metabolomics, and lipidomics have been widely used in the search for such biomarkers. These topics are discussed in depth in this review. [ABSTRACT FROM AUTHOR]

Ocean bottom seismograph (OBS) is widely used in investigating deep crustal structure, which is characterized by a large amount of data information and abundant frequency components because of its multi-component acquisition. OBS is seldom used in deepwater oil and gas exploration and basin research due to the high cost. The complicated seismic wave field is caused by the complex seabed topography, basin and oil and gas structure in deepwater area, which increases the difficulty of image processing. In addition to reflection imaging, we utilize the multiple of OBS data to make accurate imaging and have achieved desirable results in a deep sea area in South China Sea in this paper. Firstly, the original P and Z components of OBS data are processed by wave field separation to obtain the upgoing wave filed and downgoing wave filed. Secondly, its image velocity filed is constructed. Finally, downgoing wave data is used to image (called mirror migration). Compared with conventional migration, the mirror migration can clearly image the seabed and provide better illumination for shallow layer below the seafloor in the case of sparse nodes, which is proved by the migration results of theoretical and real data in this paper. [ABSTRACT FROM AUTHOR]

Comparative studies of next-generation sequencing (NGS) and clone sequencing in diet analysis have not been conducted. This study compares the performance of NGS and clone sequencing to analyze the diet of Asian great bustard (Otis tarda dybowskii). Identification of known taxa using NGS method was significantly greater than by clone method (t = 8.12, df = 14, p < 0.01), which has highlighted the higher sensitivity of the NGS approach. The proportion of occurrence for NGS method and clone method was significantly correlated (r = 0.63, p = 0.01), suggesting the prey taxa present at low frequency could not be identified by clone method. The cost and time of NGS method was also low compared with the clone method. We recommend the NGS opens up for new possibilities in the diet study, and has wide applicability to other species whose faeces can be collected easily and non-invasively in the field. [ABSTRACT FROM AUTHOR]

Differentially expressed proteins in liver tissues of C57BL/6J mice receiving low-dose Cs radiation were examined by proteomics analysis. Compared with the control group, 80 proteins were differentially expressed in the irradiated group. Among the 40 randomly selected proteins used for peptide mass fingerprinting analysis and bioinformatics, 24 were meaningful. These proteins were related to antioxidant defense, amino acid metabolism, detoxification, anti-tumor development, amino acid transport, anti-peroxidation, and composition of respiratory chain. Western blot analysis showed that catalase (CAT), glycine N-methyltransferase (GNMT), and glutathione S-transferase P1 (GSTP1) were up-regulated in the irradiated group; these results were in agreement with qPCR results. These results show that CAT, GNMT, and GSTP1 may be related to stress response induced by low-dose irradiation in mice liver. The underlying mechanism however requires further investigation. [ABSTRACT FROM AUTHOR]

A lattice Boltzmann model combined with curvilinear coordinate is proposed for lid-driven cavity three-dimensional (3D) flows. For particle velocity distribution, the particle collision process is performed in physical domain, and the particle streaming process is carried out in the corresponding computational domain, which is transferred from the physical domain using interpolation method. For the interpolation calculation, a second-order upwind interpolation method is adopted on internal lattice nodes in flow fields while a second-order central interpolation algorithm is employed at neighbor-boundary lattice nodes. Then the above-mentioned model and algorithms are used to numerically simulate the 3D flows in the lid-driven cavity at Reynolds numbers of 100, 400 and 1000 on non-uniform meshes. Various vortices on the x- y, y- z and x- z symmetrical planes are successfully predicted, and their changes in position with the Reynolds number increasing are obtained. The velocity profiles of u component along the vertical centerline and w component along the horizontal centerline are both in good agreement with the data in literature and the calculated results on uniform meshes. Besides, the velocity vector distributions on various cross sections in lid-driven cavity predicted on non-uniform meshes are compared with those simulated on uniform meshes and those in the literature. All the comparisons and validations show that the 3D lattice Boltzmann model and all the numerical algorithms on non-uniform meshes are accurate and reliable to predict effectively flow fields. [ABSTRACT FROM AUTHOR]

Enthalpies of dilution of N,N′-hexamethylenebisacetamide in water and aqueous alkali halide solutions at the concentration of 0.150 mol⋅kg (approximately the concentration of physiological saline) have been determined by isothermal titration microcalorimetry at 298.15 K. The enthalpic interaction coefficients in the solutions have been calculated according to the excess enthalpy concept based on the calorimetric data. The values of enthalpic pair-wise interaction coefficients ( h) of the solute in aqueous solutions of different salts were discussed in terms of the different alkali salt ions and weak interactions of the diluted component with coexistent species as well as the change in solvent structure caused by ions. [ABSTRACT FROM AUTHOR]