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Photovoltaic technology plays an important role in the sustainable development of clean energy, and arid areas are particularly ideal locations to build large-scale solar farms, all over the world. Modifications to the energy balance and water availability through the installation of large-scale solar farms, however, fundamentally affect the energy budget, water, and biogeochemical cycles. In-situ field observations, though, fail to draw definitive conclusions on how photovoltaic panels (PVs) affect the ambient environment, or how microclimates and soil moisture evolve under the long-term, continuous, cumulative influence of PVs. Here, we designed a synthetic model, integrating processes of energy budget and water cycle, to quantify the ecohydrological effects of PVs on soil microclimate and moisture regimes at different locations (zones) near individual PVs. Simulations run with a stochastically generated 100-year climate time series were examined to capture the evolutionary trends of soil microclimate and soil moisture. The results indicate that soil moisture content was increased by 59.8% to 113.6% in the Middle and Front zones, and soil temperature was decreased by 1.47 to 1.66 °C in all the sheltered zones, mainly because there was 5– 7 times more available water and ~27% less available radiation there, compared with the control zone. On the other hand, if the ground clearance of the PVs is too low, turbulence beneath hot PVs will have a significant influence on not only soil temperature but also soil moisture content. The innovative contribution of this study lies in reinforcing existing theoretical patterns for the development of soil microclimate and moisture dynamics influenced by PVs, and can be used to provide reliable insights into the hydrological and biogeochemical processes on Earth and the sustainable management of large-scale solar farms in arid ecosystems.

To achieve efficient simulation for surface shallow-water flows in large-scale basin irrigation, a semi-Lagrangian numerical solution for two-dimensional shallow-water equations in unstruct...

The QQ social media platform is very popular among Chinese adolescents. As with other social media platforms (e.g., Facebook, Instagram, YouTube, etc.), there have been increasing reports that the use of QQ can be potentially problematic to a minority of users. However, unlike these other social media platforms, there is currently no scale to assess the risk of problematic QQ use. The present study developed the Problematic QQ Use Scale (PQQUS) among Chinese adolescents based on six core criteria of behavioral addiction (salience, tolerance, mood modification, loss of control, withdrawal, and conflict) that have been used in the development of other social media addiction scales. The scale was administered to a sample of 1008 Chinese school children to assess its psychometric properties, utilizing both classical test theory and item response theory. The analysis demonstrated that the PQQUS had good item discrimination indices relating to both CTT and IRT. The CFA results and Loevinger’s H-coefficient suggested the PQQUS had a unidimensional factor structure. The PQQUS had good internal reliability, good composite reliability, and good concurrent validity (based on correlations with measures of anxiety, depression, self-esteem, and life satisfaction). The invariance testing between boys and girls suggested this scale is a valid assessment tool for both groups. Overall, the PQQUS is a psychometrically robust tool for assessing problematic QQ use and will have a key role in further research on problematic QQ use among Chinese adolescents.

The automatic detection and identification of fish from underwater videos is of great significance for fishery resource assessment and ecological environment monitoring. However, due to the poor quality of underwater images and unconstrained fish movement, traditional hand-designed feature extraction methods or convolutional neural network (CNN)-based object detection algorithms cannot meet the detection requirements in real underwater scenes. Therefore, to realize fish recognition and localization in a complex underwater environment, this paper proposes a novel composite fish detection framework based on a composite backbone and an enhanced path aggregation network called Composited FishNet. By improving the residual network (ResNet), a new composite backbone network (CBresnet) is designed to learn the scene change information (source domain style), which is caused by the differences in the image brightness, fish orientation, seabed structure, aquatic plant movement, fish species shape and texture differences. Thus, the interference of underwater environmental information on the object characteristics is reduced, and the output of the main network to the object information is strengthened. In addition, to better integrate the high and low feature information output from CBresnet, the enhanced path aggregation network (EPANet) is also designed to solve the insufficient utilization of semantic information caused by linear upsampling. The experimental results show that the average precision (AP)0.5:0.95, AP50 and average recall (AR)max=10 of the proposed Composited FishNet are 75.2%, 92.8% and 81.1%, respectively. The composite backbone network enhances the characteristic information output of the detected object and improves the utilization of characteristic information. This method can be used for fish detection and identification in complex underwater environments such as oceans and aquaculture.

Human resource is the most important resource of an enterprise, and good talents can lead the enterprise to make continuous breakthroughs. So far, human resource has become the key to the competition of enterprises in the market. The reasonable distribution of human resource can enhance the competitiveness of enterprises. In addition, giving full play to the role of talents can promote the innovation and development of enterprises. Therefore, we should give full play to the role of talents in the development of enterprises. Through the construction of the model, we can see that human resources have a positive role in promoting the development of enterprises. The efficient use of human resources can make the development of enterprises more stable. Enterprises are composed of people, and talents are the main driving force for sustainable development of enterprises. The dynamic ability and technological innovation ability of talents are the key to enhance the innovation ability and market competitiveness of enterprises. This paper mainly studies the influence coefficient of talent's dynamic ability and technological innovation ability. We can judge the influence degree of human resource on enterprise according to the different influence coefficient.

Multimodal perception is not only an important ability of human intelligence, but also one of the essential differences between human intelligence and artificial intelligence. With the rapid development of sensor technology, artificial intelligence technology and the Internet, various modalities of sensor data are emerging rapidly, for example, vision sensors and voice sensors are widely used in target detection and speech interaction. Integrating multiple-modality sensor data could obtain more comprehensive and accurate information, and also enhance the reliability and fault tolerance of the system. Clarifying the principles and mechanisms of how human brain integrates multi-sensory information can provide a theoretical basis for the scientific development of artificial intelligence. The introduction of multi-modality integration modules in artificial intelligence can simulate human perception largely, thus artificial intelligence will be infinitely similar to human intelligence.

Equipped with complex terrain structure, physical models provide an alternative way in understanding and modeling how critical zone shapes hydrologic processes in headwaters for research and education in hydrology. However, this type of physical models is limited by frustrating rain-erosion or gully-erosion. Herein, in order to replace the real-world backfilling soil, we drew on the experience of normal concrete workmanship and adjusted the raw material’s proportion for three times. And it is found that saturated hydraulic conductivity (SHC) and field moisture capacity (FMC) are both well correlated with bulk density (BD) for the developed materials in three cases. Thereby, based on the strongest correlation (R2=0.75) between SHC and BD, two-layer alternative soil has been designed through altering BD in the physical model with complex terrain. The SHC values of alternative soil are close to that of the natural soil while the FMC values are far lower. Additionally, the non-uniform scaling of bedrock terrain was applied for the convenience of teaching and construction by zooming out a steep 0.31-ha zero-order basin 130 times horizontally and 30 times vertically. And multiple observation items, including free water level, temperature and humidity of soil, as well as outflow could provide potential opportunity to explore the role of single or combined critical zone’s element in modulating streamflow. We’d like to share this effective tool to facilitate the development of critical zone science and enrich experimental teaching methods.

The soil thickness is the key controlling factor of local hydrology and geomorphologic characteristics. The accuracy, reliability and coverage of soil thickness map are required for reliable application. Though with quite distinct structures, models for simulating soil thickness take modern topographic data (normally digital elevation model, DEM) as one of the most important inputs. Understanding the effect of grid resolution on soil thickness prediction and selecting an appropriate resolution is crucial for the macro-scale modeling. In this study, we further explored the relationship between topographic resolution and simulation accuracy of soil thickness, and propose a new method to determine the optimal simulation resolution. A series of abstract hillslopes with different terrain noise and terrain complexity were construct and different resolutions of DEM were generated. We used a simple geomorphic based model to calculate topographic index (slope, aspect and curvature) and soil thickness. The results show that the truncation error and noise of DEM will propagate during the simulation process. Furtherly, the correlation curve between DEM resolution and the simulation error of soil thickness is a hook curve. The shape of the curve is mainly controlled by two factors, terrain noise and terrain complexity. By fitting the correlation curve of all hillslopes, the curve can be predicted by them, and the resolution corresponding to the error minimum be found out, which can be called the optimal simulation resolution of the soil thickness prediction model.

Slope units have great potential for hydrological and geomorphological studies, especially for landslide susceptibility modelling. Digital Elevation Models are widely used to delineate slope units by connecting drainage and divide lines. However, it is difficult to estimate reasonable scale thresholds for drainage and divide lines, which limits the application of slope units. Most existing methods for slope unit delineation determine the scales manually. Recently, several automatic methods have been proposed, but these methods encounter the problem of low computing efficiency for large-scale region. In this study, a new efficient method is presented for automatic slope unit delineation. Similar to an existing method, our method divides the region into several sub-basins and delineate slope units for every sub-basin independently. Within a sub-basin, grid cells are classified into massive units, and neighboring units are merged according to several strategies when aspect homogeneity can be satisfied. The new method is tested in Yarlung Tsangpo Basin, southeastern Tibetan Plateau. This basin has a large area of nearly 250 000 km2, and can be divided into nearly 340 000 slope units within 3 hours using a general personal computers. The rationality of our method is proved by both visual and quantitative assessments.

In the mountainous basins with less anthropogenic influence, the hydrological function is mainly affected by climate and landscape, which makes it possible to measure hydrological similarity indirectly by geographical features. Due to the mechanisms of runoff generation can vary geographically, in this study, a simple stepwise clustering scheme was proposed to explore the role of geographical features at different spatial hierarchy in indicating hydrological response. Research methods mainly include (1) Stepwise regression was used to quantitatively show the correlation between 35 geographical features and 35 flow features and identify the important explanatory variables for hydrological response; (2) 64 basins were divided by stepwise clustering scheme, and the overall ability of the scheme to capture hydrological similarity was tested by comparing the optimal parameters; (3) The hydrological similarity of basin groups was measured by the leave-one cross validation of hydrological model parameters. The results showed that: (1) Rainfall features, elevation, slope and soil bulk density are the main explanatory variables. (2) The NSE of basin groups based on stepwise clustering is 0.64, reaches 80% of the optimal parameter sets (NSE=0.80). The NSE of 90% basins is greater than 0.5, 80% is greater than 0.6, and 49% is greater than 0.7. (3) In humid areas, the hydrological responses of the basins with more uniform monthly rainfall and more abundant summer rainfall are more similar, e.g., the NSE of Class 4 is 0.77. Under similar rainfall patterns, the hydrological responses of the basins with higher average altitude, greater slope, more convergent of shape and richer vegetation are more similar, e.g., the NSE of Class 3-2 is 0.72 and that of Class 1-2 is 0.70. In the case of similar rainfall patterns and landforms, the hydrological responses of the basins with smaller soil bulk density are more similar, e.g., the NSE of Class 3-2-2 is 0.80. In conclusion, the stepwise clustering enhances the interpretability of basin classification, and the effect of different geographical features on hydrological response can show the applicability of hydrological simulation in ungauged basins.

Highly intermittent rivers are widespread on the Tibetan Plateau and deeply impact the ecological stability and social development downstream. Due to the highly intermittent rivers are small, seasonal variated and heavy cloud covered on the Tibetan Plateau, their distribution location is still unknown at catchment scale currently. To address these challenges, a new method is proposed for extracting the cumulative distribution location of highly intermittent river from Sentinel-1 time series in an alpine catchment on the Tibetan Plateau. The proposed method first determines the proper time scale of extracting highly intermittent river, based on which the statistical features are calculated to amplify the difference between land covers. Subsequently, the synoptic cumulative distribution location is extracted through Random Forest model using the statistical features above as explanatory variables. And the precise result is generated by combining the synoptic result with critical flow accumulation area. The highly intermittent river segments are derived and assessed in an alpine catchment of Lhasa River Basin. The results show that the the intra-annual time scale is sufficient for highly intermittent river extraction. And the proposed method can extract highly intermittent river cumulative distribution locations with total precision of 0.62, distance error median of 64.03 m, outperforming other existing river extraction method.

Preferential flow (PF)-dominated soil structure is often considered a unique system consisting of micropores and macropores and thus supposed to provide dual-pore filtering effects on hydrological signals, through which smoothing effects are likely to be stronger for matrix flow and weaker for PF via macropores. By using time series of hydrological signals (precipitation, canopy interception, throughfall, soil moisture, evapotranspiration, water storage in soil and groundwater, and catchment discharge) propagating through the Shale Hills Catchments and representative soil series, the filtering effects of the catchment and soil profiles were tested through the wavelet analysis. The hypothesized dual-pore-style filtering effects of the soil profile were also confirmed through the coherence spectra and phase differences, rendering them applicable for possible use as “fingerprints” of PF to infer subsurface flow features. We found that PF dominates the catchment’s discharge response at the scales from three to twelve days, which contributes to the catchment discharge mainly as subsurface lateral flow at upper or middle soil horizons. Through subsurface PF pathways, even the hilltop is likely hydrologically connected to the valley floor, building connections with or making contributions to the catchment discharge. This work highlights the potential of wavelet analysis for retrieving and characterizing subsurface flow processes based on the revealed dual-pore filtering effects of the soil system.

A physical model demonstrating critical zone structure and flow processes in headwatersXuhui Shen1,2, Jintao Liu1,2*, Wanjie Wang2, Xiaole Han1,3, Jie Zhang2, Guofang Li2, Xiaopeng Li4, and Yue Shi2___________________1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China2 College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China3 School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China4 Institute of Soil Science, Chinese Academy of Sciences, Nanjing, Jiangsu 210008, China___________________*Corresponding author: Jintao Liu. Tel.: +86-025-83787803; Fax: +86-025-83786606.Running head: A physical model demonstrating critical zone structure in headwaterKeywords: Physical model; Hydrologic processes; Critical zone structures; Artificial soil

The drilling process is an important step in petrochemical industries, but the drilling process is risky and costly. In order to improve the safety and cost the impact of faults in the drilling process, this paper proposes intelligent moving window based sparse principal component analysis (MWSPCA) integrating case-based reasoning (CBR) (MWSPCA-CBR) in the fault diagnosis of the drilling process in the petrochemical industry. Through introducing sparsity into the PCA model, the Lasso constraint function of the MWSPCA method is used to optimize the sparse principals. The corresponding T2 and Q statistics calculated by the selected sparse principals decide whether the faults have occurred, and the occurrence time of the anomaly is quickly located based on the MWSPCA method. Then the CBR method is used to analyze the anomaly data to identify the possible fault types, and provide the relational handling methods for real-time monitoring experts. Finally, the MWSPCA method is verified based on the intelligent diagnosis of the Tennessee Eastman (TE) process, reducing false negatives and false positives and improving the accuracy rate and the diagnosis speed. Furthermore, the proposed method is applied to analyze the data of the drilling process. The experimental results demonstrate that the proposed method can effectively diagnosis faults in the drilling process and reduce risks and costs in the petrochemical industry.

To solve the problem of autonomous collaboration of unmanned cluster in military operations, an approach to coordinated control of structured unmanned swarm based on evolutionary game is proposed. It starts with the requirement analysis of task collaboration in unmanned cluster; and the collaboration model based on evolutionary game theory is established; Then the evolutionary dynamics and equilibrium is constructed by theoretical derivation, furthermore, the formation conditions of autonomous collaboration is obtained; Finally the strategy evolution process of swarm on regular lattice and general topology is simulated via case study, which proves the rationality and feasibility of the proposed model and method. The conclusion of this paper provides a preliminary and meaningful exploration for the transformation from theories to practical applications.

Background Microsatellite stable (MSS) or mismatch repair proficient (pMMR) metastatic colorectal cancer (mCRC) is resistant to immune checkpoint inhibitors. However, a recent Japanese trial showed that regorafenib plus nivolumab had encouraging anti-cancer activity in MSS or pMMR mCRCs. Materials and methods We retrospectively reviewed the efficacy and safety data of combination therapy with regorafenib plus anti-PD-1 antibody in patients with refractory MSS or pMMR mCRC in the medical centers of Shandong Province in China. Results Twenty-three patients with MSS or pMMR mCRC received regorafenib plus anti-PD-1 antibody. Eighteen (78.3%) patients experienced stable disease as best response, five (21.7%) patients had progressive disease, and no partial response was observed. The disease control rate (DCR) was 78.3% (18/23), and the median progression-free survival (PFS) was 3.1 months (95% CI, 2.32-3.89). Four of five (80.0%) patients with progressive disease had baseline liver metastasis, while nine of 18 (50.0%) patients with stable disease displayed no liver metastasis. One patient receiving radiofrequency ablation treatment for liver and abdominal wall metastases prior to combination treatment experienced a remarkably prolonged PFS of 9.2 months with SD. Neither liver metastasis status nor previous exposure to regorafenib was associated with treatment outcome. Treatment-related grade 3 toxicities were observed in 5/23 (21.7%) patients. Conclusion No objective response was observed with the combination of regorafenib plus anti-PD-1 antibody, suggesting its little clinical activity in unselected Chinese patients with pMMR/MSS mCRC. Meanwhile, it exhibited some potential benefit in this cohort in terms of DCR and PFS. Adverse events were generally tolerable and manageable. Prospective studies with large sample sizes are needed to verify the findings. This combination strategy plus local ablative therapy might be worthy of further exploration.

Safety analysis is an essential way to ensure the safe operation of high-speed railway train control systems. It is of significance to design special modeling language and modeling method for safety analysis of high-speed railway train control systems. This will contribute to improving the accuracy of safety analysis. According to the composition of safety analysis model of high-speed train control system, the characteristic elements of the safety analysis model are extracted. On the base of the characteristic elements, the UML extension mechanism is used to realize the stereotype design of UML classes and UML messages. As a result, an extended UML for safety modelling of high-speed railway train control systems is formed. The proposed modelling language is applied to a typical scenario of Chinese high-speed railway. The results show the effectiveness of the proposed method.

Relying on the gradual deepening of computer technology research and the widespread application of Internet technology, virtual reality, or VR for short, has also gradually emerged. Applying virtual reality to many traditional industries can bring new directions for the development of traditional industries. Among them, immersive virtual reality is more favored by people because of its good sense of bringing in experience. In terms of metal wire rendering method research, it is combined with virtual reality technology to continuously meet people's requirements. This paper proposes a 3D cloud modeling method with strong artistic controllability. Artists use modeling tools to generate 3D cloud external contours. The contours are preprocessed by spatial subdivision to obtain the 3D cloud spatial distribution represented by a 3D grid. In terms of 3D cloud rendering, the 3D cloud model represented by the grid is converted into a particle space representation, and the improved forward multi-directional scattering illumination method is used to calculate the illumination and coloring of the cloud, which realizes the dynamic real-time illumination of the 3D cloud based on particles. The controllability of the three-dimensional cloud shape and the dynamic lighting based on physics effectively solve the problem of combining wire rendering and virtual reality technology.

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Background Probiotics seems to play a beneficial role in stressed populations; thus, a systematic review and meta‐analysis to assess the effects of probiotics on stress in healthy subjects were conducted. Methods Randomized controlled trials on the effects of probiotics on stress in healthy subjects were retrieved from five databases. The effects of probiotics on subjective stress level, stress‐related subthreshold anxiety/depression level, cortisol level, and adverse reactions were analyzed. Separate subgroup analyses were conducted on single‐strain probiotics versus multi‐strain probiotics, and short‐term administration versus long‐term administration. Results Seven studies were included, involving a total of 1,146 subjects. All the studies were rated as low or moderate risk of bias. Our research found that probiotic administration can generally reduce the subjective stress level of healthy volunteers and may improve their stress‐related subthreshold anxiety/depression level, but no significant effect was observed in the subgroup analysis. The effect of probiotics on cortisol level was not significant. Adverse reactions were reported in only one of seven studies, but left undescribed. Conclusion Current evidence suggests that probiotics can reduce subjective stress level in healthy volunteers and may alleviate stress‐related subthreshold anxiety/depression level, without significant effect on cortisol level, and there is not enough support to draw conclusions about adverse effects; thus, more reliable evidence from clinical trials is needed., This is a systematic review and meta‐analysis based on randomized controlled trials to assess the effects of probiotics on stress in healthy volunteers.

The extension-induced rift systems on the Tibetan Plateau (TP) may convey large amount of groundwater to rivers, but sources and flow paths of such groundwater are unknown. The Yarlungzangbo River (YR) is the only large river that traverses the southern Tibetan plateau from west to east, following one major suture zone that is cut by extensional normal faults. The faults could influence the flow paths of groundwater discharging to the river. In this study, O and H isotopes, major ions and 222Rn concentrations are analyzed along the YR, and interpreted in relation to structural geology and tectonics. The YR exhibits an abrupt change of isotopic and chemical compositions along with a large increase in flow where the middle reach intersects NE-SW-trending rifts. Low values of δD and δ18O and high concentrations of major ions and 222Rn in the middle reach show that waters are modified isotopically and chemically by a variety of possible water origins, such as recharge of high-altitude glacier melt and discharge from groundwater. Groundwater contributes 27 to 40% of the river flow in the middle reach. Isotopically-light meltwater from high-altitude glacier melt cannot account for the isotope composition of the present outflow of groundwater. The O and H isotope data in the YR and discharging groundwater can be well explained by the groundwater originated as paleo-precipitation during a cooler time, such as the late Pleistocene to early Holocene. The paleo-groundwater discharge can account for about 36 × 108 m3 water budget unbalance in the middle reach. The study provides the first clear isotope evidence for the source of groundwater discharge into a large river through favorable conduits in large-scale active tensile fault zones and confirms the regional scale of groundwater flow on the Tibetan Plateau. Understanding the characteristics and changes of streamflow and surface-groundwater circulation on the Tibetan Plateau will help to manage water resources under a changing environment.

Tin-based compounds have received much attention as anode materials for lithium/sodium ion batteries owing to their high theoretical capacity. However, the huge volume change usually leads to the pulverization of electrode, giving rise to a poor cycle performance, which have severely hampered their practical application. Herein, highly durable yolk-shell SnSe

Characterizing soil volumetric water content (VWC) dynamics at different soil depth plays a key role in hydrological modeling and is essential for effective catchment management. However, our understanding of how critical zone structure (topography and soil) and rainfall affect VWC dynamics is limited. Therefore, the objective of this study was to investigate the effects of the hillslope structure and rainfall on VWC dynamics in a steep forested, zero-order catchment. VWC was measured from soil surface to soil-bedrock interface at five soil layers (0-8, 8-40, 40-70, 70-110, and 110-160 cm) for a complete water year, and covering various landscapes such as an ephemeral stream, riparian, and different hillslope positions. A total of 13 environmental indices, including eight DEM-derived terrain attributes and five soil attributes, were used to investigate the relationships between soil-terrain attributes and VWC. An all-possible-subsets regression model was adopted to construct the soil water content prediction model (SWPM). A geophysical method (ground penetrating radar, GPR) was used to investigate the soil depth to assist in the establishment of SWPM. The results demonstrate that the all-possible-subsets regression model performed well for predicting VWC. Additionally, the strength of the relationships between soil-terrain attributes and VWC could be different through time. For instance, the relationships between the topographic wetness index (TWI) and VWC were all significant (P

An accurate assessment of soil water balance components (SWBCs) is necessary for improving irrigation strategies in any water-limited environment. However, quantitative information of SWBCs is usually challenging to obtain, because none of the components (i.e., irrigation, drainage, and evapotranspiration) can be easily measured under actual conditions. Soil moisture is a variable that integrates the water balance components of land surface hydrology, and the evolution of soil moisture is assumed to contain the memory of antecedent hydrologic fluxes, and thus can be used to determine SWBCs from a hydrologic balance. A database of soil moisture measurements from six experimental plots with different treatments in the middle Heihe River Basin of China was used to test the potential of a soil moisture database in estimating the SWBCs. We first compared the hydrophysical properties of the soils in these plots, such as vertical saturated hydraulic conductivity (Ks) and soil water retention features, for supporting the SWBC estimations. Then we determined evapotranspiration and other SWBCs through a method that combined the soil water balance method and the inverse Richards equation (a model of unsaturated soil water flow based on the Richards equation). To test the accuracy of our estimation, we used both indirect methods (such as power consumption of the pumping irrigation well, and published SWBCs values at nearby sites), and the water balance equation technique to verify the estimated SWBCs values, all of which showed a good reliability of our estimation method. Finally, the uncertainties of the proposed methods were analyzed to evaluate the systematic error of the SWBC estimation and any restrictions on its application. The results showed significant variances among the film-mulched plots in both the cumulative irrigation volumes (652.1~ 867.3 mm) and deep drainages (170.7~364.7 mm). Moreover, the unmulched plot had remarkably higher values in both cumulative irrigation volumes (1186.5 mm) and deep drainages (651.8 mm) compared with the mulched plots. Obvious correlation existed between the volume of irrigation and that of drained water. However, the ET demands for all the plots behaved pretty much the same, with the cumulative ET values ranging between 489.1 and 561.9 mm for the different treatments in 2016, suggesting that the superfluous irrigation amounts had limited influence on the accumulated ET throughout the growing season because of the poor water-holding capacity of the sandy soil. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived by using soil moisture measurements; the proposed methods provided a reliable solution over the entire growing season and showed a great potential for identifying appropriate irrigation amounts and frequencies, and thus a move toward sustainable water resources management, even under traditional surface irrigation conditions.

Marine diatoms construct their hierarchically ordered, three-dimensional (3D) external structures called frustules through precise biomineralization processes. Recapitulating the remarkable architectures and functions of diatom frustules in artificial materials is a major challenge that has important technological implications for hierarchically ordered composites. Here, we report the construction of highly ordered, mineralized composites based on fabrication of complex self-supporting porous structures—made of genetically engineered amyloid fusion proteins and the natural polysaccharide chitin—and performing in situ multiscale protein-mediated mineralization with diverse inorganic materials, including SiO2, TiO2 and Ga2O3. Subsequently, using sugar cubes as templates, we demonstrate that 3D fabricated porous structures can become colonized by engineered bacteria and can be functionalized with highly photoreactive minerals, thereby enabling co-localization of the photocatalytic units with a bacteria-based hydrogenase reaction for a successful semi-solid artificial photosynthesis system for hydrogen evolution. Our study thus highlights the power of coupling genetically engineered proteins and polysaccharides with biofabrication techniques to generate hierarchically organized mineralized porous structures inspired by nature., Inspired by the exquisite diatom frustule, genetically engineered amyloid proteins bearing mineralization-promoting domains are combined with chitin to fabricate and then mineralize a variety of hierarchically ordered porous structures.

Propofol, a commonly used anesthetic, is convenient to use, induces quick effect, enables rapid recovery, and is widely accessible given its stable supply. However, its adverse effects are a concern. Reportedly, propofol exhibits a significant inhibitory effect on the respiratory and circulatory systems. Furthermore, intravenous administration of this drug results in hypotension, rapid heart rate, and respiratory failure. Because many pregnant women are administered propofol during childbirth, it may have a significant negative effect on the development of infants. Propofol can cause considerable developmental neurotoxicity and has known activity on the heart. However, the underling mechanisms of these toxicities remain unclear. In the present study, zebrafish embryos were exposed to propofol at different concentrations (0.05, 0.1, 0.5, 1, 5, 10, and 20 μg/ml) to determine its developmental and cardiac toxicities. Propofol exposure decreased the survival rate and hatchability of zebrafish embryos. Additionally, the embryo malformation rate increased in a concentration-dependent manner. Different types of malformations were observed following propofol administration. The proportion of pericardial cysts increased, whereas the heart rate and size decreased with an increase in propofol concentration. The quantitative reverse-transcription polymerase chain reaction revealed that propofol significantly altered the expression of genes related to cardiac development and functions in zebrafish. Collectively, our findings indicate that propofol exposure induces significant developmental and cardiac toxicities in zebrafish.

Simple Summary In aquaculture, the number of fish population can provide valuable input for the development of an intelligent production management system. Therefore, by using machine vision and a new hybrid deep neural network model, this paper proposes an automated fish population counting method to estimate the number of farmed Atlantic salmon. The experiment showed that the estimation accuracy can reach 95.06%, which can provide an essential reference for feeding and other breeding operations. Abstract In intensive aquaculture, the number of fish in a shoal can provide valuable input for the development of intelligent production management systems. However, the traditional artificial sampling method is not only time consuming and laborious, but also may put pressure on the fish. To solve the above problems, this paper proposes an automatic fish counting method based on a hybrid neural network model to realize the real-time, accurate, objective, and lossless counting of fish population in far offshore salmon mariculture. A multi-column convolution neural network (MCNN) is used as the front end to capture the feature information of different receptive fields. Convolution kernels of different sizes are used to adapt to the changes in angle, shape, and size caused by the motion of fish. Simultaneously, a wider and deeper dilated convolution neural network (DCNN) is used as the back end to reduce the loss of spatial structure information during network transmission. Finally, a hybrid neural network model is constructed. The experimental results show that the counting accuracy of the proposed hybrid neural network model is up to 95.06%, and the Pearson correlation coefficient between the estimation and the ground truth is 0.99. Compared with CNN- and MCNN-based methods, the accuracy and other evaluation indices are also improved. Therefore, the proposed method can provide an essential reference for feeding and other breeding operations.

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Propellant management devices (PMDs) are a key component used to manage liquid propellant in a propellant tank under zero gravity conditions. A microgravity drop tower test system was established to investigate the performance of a PMD. A single module was used for the experiments, and the microgravity level was less than 3 × 10 − 3 g . Anhydrous ethanol was used as the simulate liquid. Different volume fractions of liquid were used to study the influence of the PMD on performance management. Experiments were conducted with the position of the container oriented in different directions. Changes in the gas-liquid interface were studied during the test. This kind of vane transports liquid through the rectangular area between the vane and the wall. The velocity flows along the vane of different liquid volume fractions in the tank were different at the beginning ( t < 0.8 s ) compared with the end of the test. The liquid relocation time was less than 0.8 s while the liquid volume fraction was larger than 25%. The liquid relocation time was prolonged when the liquid volume fraction was less than 25%. The liquid climbing height along the vane under microgravity increased as the volume fraction of liquid reduced. The climbing velocity of the liquid is half reduction when the liquid volume fraction is small. The time for the liquid transferred from the top of the tank to the liquid outlet can be obtained by climbing velocity. It shows that the maneuverability of the satellite decreases at the end of its life. The above results are applicable to all propellant tank with vertical vanes. These results provide a favorable reference for further optimized design of vertical vane-type propellant tanks.

Hydrothermal vents play important roles in the dynamic process of the stratosphere and the circulation of energy materials. Nowadays, invasive devices such as vane-type flow meter and turbine flow meter are commonly utilized to estimate the flow rates of hydrothermal vents. In- situ observation data obtained by LDCP system and CFD methods will be combined to solve the blind area of LDCP system during in-situ observation measurements. The flow rates profiles obtained in this project will improve the research on the circulation of energy materials and mineralization.

Objective To investigate that whether an association between marital status and the female breast cancer risk exists. Methods The MEDLINE, EMBASE and PsycINFO databases were searched from their inception to July 2019. The Newcastle-Ottawa Scale was used to rate the methodological quality of included studies. Study data were pooled using random-effects meta-analyses to compare the breast cancer risk between unmarried, widowed, divorced or lifelong single women and married women. This study is registered with PROSPERO (number CRD42018112368). Results Forty-nine publications were included in the meta-analysis. Compared with married women, unmarried and lifelong single women had an elevated risk of breast cancer, and the pooled ORs of case-control studies were 1.20 (95% CI: 1.07 to 1.35) and 1.24 (95% CI: 1.05 to 1.45), respectively. In the subgroup analyses under these two comparisons, hospital-based estimates and multivariate-adjusted estimates demonstrated a strong association, while population-based estimates and age-adjusted estimates produced nonsignificant results. The pooled OR of cohort studies examining the effect of being a lifelong single woman was 1.10 (95% CI: 1.04 to 1.16). Heterogeneity was moderate to substantial across case-control studies (I2: 46% to 82%), which may be partially explained by differences in geographic regions, publication years and control types. Possible publication bias was indicated by the funnel plot and Egger’s test (P = 0.03). Conclusions Marital status may correlate with the risk of developing female breast cancer. However, suboptimal selection of controls, insufficient exploration of confounding effects, inadequate ascertainment of marital status, and possible publication bias may have limited the quality of the available evidence. Overall, conclusions that marital status is an independent risk factor for breast cancer could not be drawn, and further prospective rigorous cohort studies are warranted.

The influence of the curing temperature (150 °C, 200 °C, 250 °C, and 300 °C) and curing time (4 h, 8 h, and 12 h) on the mechanical properties and shrinkage development of reactive powder concrete (RPC) was studied, and a curing regime for improving its mechanical properties is proposed. Test results show that the compressive and flexural strengths of specimens increase at curing temperatures of 200 °C to 250 °C, but decrease at curing temperature of 300 °C. Meanwhile, shrinkage measurement results indicate that the ultimate shrinkage of high-temperature cured RPC at 50% relative humidity (RH) is lower than in the control group. Scanning electron microscope results reveal that high-temperature curing improves the microscopic pore structure of RPC and makes the interfacial transition zone denser. Furthermore, the dry-heat curing regime can accelerate the cement hydration process, and tobermorite or xonotlite was found to be one of the major crystalline hydrates at high temperature.

High-voltage LiNi0.5Mn1.5O4 nanorods were prepared through a low-cost and environment-friendly strategy with MnO2 nanorods as manganese source. The resulting LiNi0.5Mn1.5O4 nanorods showed satisfactory rod-like morphology and obvious characteristic diffraction peaks of LiNi0.5Mn1.5O4. According to the research results of electrochemical properties, the obtained LiNi0.5Mn1.5O4 nanorods showed excellent cycling stability. When cycled at 1.0 C, this sample exhibited 125.2 mAh g−1 at the first cycle in the voltage range of 3.4–5.0 V. After 200 cycles, the satisfactory capacity of 119.8 mAh g−1 could be obtained with outstanding retention of 95.7%, which was far more advantageous than that of the LiNi0.5Mn1.5O4 particles (78.1%). Moreover, the LiNi0.5Mn1.5O4 nanorods could show a superior capacity of 93.4 mAh g−1 at 10 C, whiles the LiNi0.5Mn1.5O4 particles only exhibited 58.5 mAh g−1. These results indicated that the obtained LiNi0.5Mn1.5O4 nanorods possessed great potential and application prospect to be a promising 5.0 V cathode material.

To improve the high-voltage cycling stability and rate capability, the Mg2+ and Ti4+ co-doping strategy is firstly proposed to modify the LiCoO2 cathode material. The synergistic effect of co-doping with Mg2+ and Ti4+ ions on the structure, morphology and high-voltage electrochemical performance of LiCoO2 is investigated. For the co-doped sample, the introduction of Mg2+ and Ti4+ ions can efficiently optimize the particle size distribution and reduce the aggregation behavior. Compared with the undoped and single-doped samples, the Mg2+ and Ti4+ co-doped LiCoO2 sample presents better high-voltage cycling stability and rate capability due to the fact that the Mg2+ and Ti4+ ions co-doping can make full use of the respective advantages of Mg2+-doping and Ti4+-doping. When cycled at 1.0 C, the co-doped sample exhibits an initial discharge capacity of 179.6 mAh g−1 in the voltage range of 2.75–4.5 V. After 100 cycles, the capacity retention of this sample can reach up to 82.6%. Moreover, the co-doped sample shows better rate performance with high discharge capacity of 151.4 mAh g−1 at 5.0 C. These outstanding results may be attributed to the suppressed phase transition, decreased charge transfer resistance, improved thermal stability, enhanced electrical conductivity and uniform particle size distribution of the Mg2+ and Ti4+ co-doped LiCoO2 sample.

The importance order of causes of a railway signaling system hazard is important for the arrangement of control measures for eliminating or controlling the system hazard. In order to obtain a reasonable importance order, a novel importance order analysis method based on complex networks is proposed in this article. In this article, to characterize the causes from a topological perspective, a comprehensive topology characteristic is proposed. It is built on the top of three typical topology characteristics with the weighted Euclidean distance. Then, an influence coefficient matrix is proposed to measure the causal influence between causes. Based on the proposed topology characteristic and matrix, an algorithm is designed to identify the importance order of causes. To verify the effectiveness of the proposed method, a case study on a Chinese high-speed railway signaling system hazard is performed. The results show that the proposed method is feasible for the arrangement of control measures to eliminate or control system hazards and performs better than the traditional complex network-based methods in terms of avoiding conflicting and rough results.

The magnesium (Mg) and silicon (Si) co-doped LiNi0.5Mn1.5O4 sample has been obtained by sol-gel method. The effects of co-doping with magnesium and silicon ions on the phase structure, morphology and electrochemistry characteristics of LiNi0.5Mn1.5O4 are investigated by a series of physico-chemical characterizations. XRD results demonstrate that the magnesium and silicon ions successfully enter into the spinel structure and make the lattice parameter slightly increased. Moreover, the magnesium and silicon ions co-doped sample presents superior cycling stability. When cycled at 0.5 C, this sample still delivers 121 mAh g−1 after 100 cycles with outstanding retention of 98.86%, while the undoped LiNi0.5Mn1.5O4 sample only exhibits 104.5 mAh g−1 after 100 cycles with low retention of 79.17%. In addition, the Mg2+ and Si4+ co-doped sample shows outstanding rate capability and low charge transfer resistance.