Explore the vast range of titles available.

Aquatic animals have a close relationship with water, but differences in their symbiotic bacteria and the bacterial composition in water remains unclear. Wild or domestic Chinese mitten crabs (Eriocheir sinensis) and the water in which they live were collected from four sampling sites in Jiangsu and Shanghai, China. Bacterial composition in water, gills or guts of E. sinensis, were compared by high-throughput sequencing using 16S rRNA genes. Analysis of >660,000 sequences indicated that bacterial diversity was higher in water than in gills or guts. Tenericutes and Proteobacteria were dominant phyla in guts, while Actinobacteria, Proteobacteria and Bacteroidetes were dominant in gills and water. Non-metric multidimensional scaling analysis indicated that microbiota from gills, guts or water clearly separated into three groups, suggesting that crabs harbor a more specific microbial community than the water in which they live. The dominant OTUs in crab gut were related to Mycoplasmataceae, which were low in abundance in gills, showing that, like mammals, crabs have body-site specific microbiota. OTUs related to Ilumatobacter and Albimonas, which are commonly present in sediment and seawater, were dominant in gills but almost absent from the sampled water. Considering E. sinensis are bottom-dwelling crustacean and they mate in saline water or seawater, behavior and life cycle of crabs may play an important role in shaping the symbiotic bacterial pattern. This study revealed the relationship between the symbiotic bacteria of Chinese mitten crab and their habitat, affording information on the assembly factors of commensal bacteria in aquatic animals.

Thermal energy storage (TES) system plays an essential role in the utilization and exploitation of renewable energy sources. Over the last two decades, single-tank thermocline technology has received much attention due to its high cost-effectiveness compared to the conventional two-tank storage systems. The present paper focuses on clarifying the performance indicators and the effects of different influencing factors for the thermocline TES systems. We collect the various performance indicators used in the existing literature, and classify them into three categories: (1) ones directly reflecting the quantity or quality of the stored thermal energy; (2) ones describing the thermal stratification level of the hot and cold regions; (3) ones characterizing the thermo-hydrodynamic features within the thermocline tanks. The detailed analyses on these three categories of indicators are conducted. Moreover, the relevant influencing factors, including injecting flow rate of heat transfer fluid, working temperature, flow distributor, and inlet/outlet location, are discussed systematically. The comprehensive summary, detailed analyses and comparison provided by this work will be an important reference for the future study of thermocline TES systems.

Adversarial examples have aroused great attention during the past years owing to their threat to the deep neural networks (DNNs). Recently, they have been successfully extended to video models. Compared with image cases, the sparse adversarial perturbations in the videos can not only reduce the computation complexity, but also guarantee the crypticity of adversarial examples. In this paper, we propose an efficient attack to generate adversarial video perturbations with large sparsity in both the temporal (inter-frames) and spatial (intra-frames) domains. Specifically, we select the key frames and key pixels according to the gradient feedback of the target models by computing the forward derivative, and then add the perturbations on them. To overcome the problem of dimensional explosion in the video, we introduce super-pixels to decrease the number of pixels that need to compute gradients. The proposed method is finally verified under both the white-box and black-box settings. We estimate the gradients using natural evolution strategy (NES) in the black-box attacks. The experiments are conducted on two widely used datasets: UCF101 and HMDB51 versus two mainstream models: C3D and LRCN. Results show that compared with the state-of-the-art method, our method can achieve the similar attacking performance, but it pollutes only <1% pixels and costs less time to finish the attacks.

Most regional seismic damage assessment (RSDA) methods are based on the rigid-base assumption to ensure evaluating efficiency, while these practices introduce factual errors due to neglecting the soil–structure interaction (SSI). Predicting the influence of the SSI on seismic responses of regionwide structure portfolios remains a challenging undertaking, as it requires developing numerous high-fidelity, integrated models to capture the dynamic interplay and uncertainties in structures, foundations, and supporting soils. This study develops a one-dimensional convolutional neural network (1D-CNN) model to efficiently predict to what degree considering the SSI would change the inter-story drifts and base shear forces of RC frame buildings. An experimentally validated finite element model is developed to simulate the nonlinear seismic behavior of the building-foundation–soil system. Subsequently, a database comprising input data (i.e., structural and soil parameters, ground motions) and output predictors (i.e., changes in story drift and base shear) is constructed by simulating 1380 pairs of fixed-base versus soil-supported structures under earthquake loading. This large-scale dataset is used to train, test, and identify the optimal hyperparameters for the 1D-CNN model to quantify the demand differences in inter-story drifts and base shears due to the SSI. Results indicate the 1D-CNN model has a superior performance, and the absolute prediction errors of the SSI influence coefficients for the maximum base shear and inter-story drift are within 9.3% and 11.7% for 80% of cases in the testing set. The deep learning model can be conveniently applied to enhance the accuracy of the RSDA of RC buildings by updating their seismic responses where no SSI is considered.

Accurate methods to estimate the aboveground biomass (AGB) of mangroves are required to monitor the subtle changes over time and assess their carbon sequestration. The AGB of forests is a function of canopy-related information (canopy density, vegetation status), structures, and tree heights. However, few studies have attended to integrating these factors to build models of the AGB of mangrove plantations. The objective of this study was to develop an accurate and robust biomass estimation of mangrove plantations using Chinese satellite optical, SAR, and Unmanned Aerial Vehicle (UAV) data based digital surface models (DSM). This paper chose Qi’ao Island, which forms the largest contiguous area of mangrove plantation in China, as the study area. Several field visits collected 127 AGB samples. The models for AGB estimation were developed using the random forest algorithm and integrating images from multiple sources: optical images from Gaofen-2 (GF-2), synthetic aperture radar (SAR) images from Gaofen-3 (GF-3), and UAV-based digital surface model (DSM) data. The performance of the models was assessed using the root-mean-square error (RMSE) and relative RMSE (RMSEr), based on five-fold cross-validation and stratified random sampling approach. The results showed that images from the GF-2 optical (RMSE = 33.49 t/ha, RMSEr = 21.55%) or GF-3 SAR (RMSE = 35.32 t/ha, RMSEr = 22.72%) can be used appropriately to monitor the AGB of the mangrove plantation. The AGB models derived from a combination of the GF-2 and GF-3 datasets yielded a higher accuracy (RMSE = 29.89 t/ha, RMSEr = 19.23%) than models that used only one of them. The model that used both datasets showed a reduction of 2.32% and 3.49% in RMSEr over the GF-2 and GF-3 models, respectively. On the DSM dataset, the proposed model yielded the highest accuracy of AGB (RMSE = 25.69 t/ha, RMSEr = 16.53%). The DSM data were identified as the most important variable, due to mitigating the saturation effect observed in the optical and SAR images for a dense AGB estimation of the mangroves. The resulting map, derived from the most accurate model, was consistent with the results of field investigations and the mangrove plantation sequences. Our results indicated that the AGB can be accurately measured by integrating images from the optical, SAR, and DSM datasets to adequately represent canopy-related information, forest structures, and tree heights.

To determine the research status of phosphogypsum‐based materials in Chinese road engineering, this article introduces the physicochemical properties of phosphogypsum materials, analyzes its strength formation mechanism, and evaluates its road performance. Moreover, the pretreatment methods and environmental impact of phosphogypsum application in Chinese road engineering were summarized. It can be clearly stated that the phosphogypsum is a low‐strength material that has poor water stability; however, when compounded with cement or other materials, stabilized phosphogypsum exhibits significantly improved water stability, strength, and overall road performance. On the one hand, ettringite (AFt) and calcium silicate hydrate (C–S–H) were formed via cement hydration to provide strength. On the other hand, phosphogypsum reacts chemically with cement hydration products to generate AFt, which can further enhance the strength of the stabilized materials. In addition, research on phosphogypsum materials is mostly focused on experimental roads and has not yet been widely applied to road engineering on a large scale. The performance of most experimental roads showed that the bearing capacity and compaction of the base course or subgrade constructed by the phosphogypsum‐based modified materials can meet the Chinese standards; therefore, it can be applied for road engineering from the perspective of road performance. However, most studies only utilized phosphogypsum in small quantities, whereas the application of phosphogypsum at high contents in road engineering remains to be further investigated. Moreover, phosphogypsum‐based materials tend to agglomerate into clumps, which can easily clog mechanical mixing equipment. Therefore, it is urgent to develop dedicated mixing equipment for such materials in road engineering. Additionally, common pretreatment methods for phosphogypsum, such as washing, lime neutralization, and flotation, can be used to remove impurities like phosphorus and fluorine. Furthermore, various curing agents have been developed for stabilizing the harmful substances.

Background As substitutes for antibiotics, probiotic bacteria protect against digestive infections caused by pathogenic bacteria. Ligilactobacillus salivarius is a species of native lactobacillus found in both humans and animals. Herein, a swine-derived Ligilactobacillus salivarius was isolated and shown to colonize the ileal mucous membrane, thereby promoting nutritional digestion, absorption, and immunity. To evaluate its probiotic role, the entire genome was sequenced, the genetic information was annotated, and the metabolic information was analyzed. Results The phylogenetic relationship indicated that the bacteria was closer to L. salivarius MT573555.1 and MT585431.1. Functional genes included transporters, membrane proteins, enzymes, heavy metal resistance proteins, and putative proteins; metabolism-related genes were the most abundant. The six types of metabolic pathways secreted by L. salivarius were mainly composed of secretory transmembrane proteins and peptides. The secretory proteins of L. salivarius were digestive enzymes, functional proteins that regulate apoptosis, antibodies, and hormones. Non-targeted metabolomic analysis of L. salivarius metabolites suggested that ceramide, pyrrolidone- 5- carboxylic acid, N2-acetyl-L-ornithine, 2-ethyl-2-hydroxybutyric acid, N-lactoyl-phenylalanine, and 12 others were involved in antioxidation, repair of the cellular membrane, anticonvulsant, hypnosis, and appetite inhibition. Metabolites of clavaminic acid, antibiotic X14889C, and five other types of bacteriocins were identified, namely phenyllactic acid, janthitrem G, 13-demethyl tacrolimus, medinoside E, and tertonasin. The adherence and antioxidation of L. salivarius were also predicted. No virulence genes were found. Conclusion The main probiotic properties of L. salivarius were identified using genomic, metabonomic, and biochemical assays, which are beneficial for porcine feeding. Our results provided deeper insights into the probiotic effects of L. salivarius .

Finding solid and practical quantum advantages via noisy quantum devices without error correction is a critical but challenging problem. Conversely, comprehending the fundamental limitations of the state-of-the-art is equally crucial. In this work, we consider the class of strictly contractive unital noise and derive its analytical representation by decomposition. Under such noise, we observe the polynomial-time indistinguishability of n -qubit devices from random coins when circuit depths exceed Ω ( log ( n ) ) . Even with classical processing, we demonstrate the absence of computational advantage in polynomial-time algorithms with super-logarithmic noisy circuit depths. These results impact variational quantum algorithms, error mitigation, and quantum simulation with polynomial depth. Furthermore, we consider noisy quantum devices with a restricted gate topology. For one-dimensional noisy qubit circuits, we rule out super-polynomial quantum advantages in all-depth regimes. We also establish upper limits on entanglement generation: O ( log ( n ) ) for one-dimensional circuits and O ( n log ( n ) ) for two-dimensional circuits. Our findings underscore the computational capacity and entanglement scalability constraints in noisy quantum devices.

Drought is one of the most brutal environmental factors limiting the productivity of fruit trees. The search for new and efficient microorganisms from unexplored environments that can be used to mitigate the negative effects of water stress is an interesting alternative to alleviate the drought stress experienced by plants. This study aimed to determine the effects of PGPR inoculation on the growth and physioecological characteristics of walnut (Juglans regia) seedlings under drought stress. A pot experiment was conducted using J. regia seedlings with controlled water supplies at different levels (light, moderate, and severe drought stress and control) and with or without inoculation with Bacillus cereus L90, a type of PGPR that produces high levels of cytokinins and indoleacetic acid (IAA). Under well-watered conditions, there was no obvious effect of PGPR inoculation on the antioxidant enzyme activities, osmotic adjustment levels, and photosynthetic characteristics of J. regia. As the stress intensity increased, B. cereus inoculation increased the antioxidant enzyme activities in walnut seedlings and changed their photosynthetic characteristics. However, levels of osmotic adjustment substances were decreased as a result of PGPR inoculation. Regardless of water status, B. cereus inoculation induced a significant increase in IAA, gibberellins, and zeatin contents in J. regia. Under well-watered and light stress conditions, the abscisic acid content of walnut was significantly increased by B. cereus inoculation. Additionally, B. cereus inoculation significantly promoted the growth of plants in terms of ground diameter and plant height. As a result, PGPR inoculation could improve the drought resistance of J. regia and improve its photosynthetic characteristics and growth, suggesting that it is a useful supplementary measure for use in afforestation in arid and semiarid environments.

To improve the reliability and fault tolerance of electric helicopter propulsion systems, this paper presents a master–slave fault-tolerant control method based on an extended state observer (ESO) for dual-redundant electric propulsion systems that addresses dynamic coupling disturbances. First, the control architecture puts the master motor in speed loop mode and puts the slave motor in torque loop mode with an ESO to estimate disturbances and compensate for mechanical coupling torque through feedforward control based on Lyapunov stability theory. Second, a least squares parameter identification method establishes a current-torque mapping model to ensure consistent dual-motor output. Then, fault-tolerant switching is implemented, transitioning from normal torque mode coordination to independent speed mode with adaptive PI adjustment during faults. Experimental validation shows that the total torque stabilizes at 240 N·m, and the synchronization error remains within ±0.5 N·m during normal operation. Under single-motor fault scenarios, the ESO detects disturbances within 15 ms with >95% accuracy. The system speed decreases to a minimum of 2280 rpm (5% deviation) and recovers within 3.5 s. Compared to traditional PI control, this method improves torque synchronization by 65.4%, speed stability by 62.6%, and dynamic response by 51.2%. Finally, the results validate that the method effectively suppresses coupling interference and meets aviation safety standards, providing reliable, fault-tolerant solutions for electric helicopter propulsion.