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Using Fe-modified biochar (Fe-B) to capture phosphorus in eutrophic water and then reusing it as a phosphorus fertilizer for agricultural production is a sustainable way to remediate surface water eutrophication and develop agriculture. However, the adsorption efficiency of Fe-modified biochar is influenced by a variety of factors including methods to produce biochar and surface water environment. In this review, we analyze different methods to manufacture Fe-B and their efficacy for phosphate adsorption. Other factors we analyzed include pH value, coexisting ions, biochar application rate, temperature which have shown to affect the capacity of Fe-B to adsorb phosphorus. We also discuss the potential of Fe-B and the phosphorus it adsorbed to be reused as a slow-release phosphorus fertilizer for agricultural production, as well as the perspective of Fe -modified biochar (Fe-B) and its applications.

With the increasing penetration of distributed power sources, the stochastic and fluctuating nature of distributed power sources poses a great challenge to the reactive power optimization of the distribution network system. In this study, a dynamic reactive power optimization model with two-stage robust optimization is established, proposing whether the energy storage is charged or discharged. The number of groups of group-switching capacitors is taken as the variables in the first stage. The power of the energy storage charging and discharging and the amount of static reactive power compensator compensation are placed in the second stage. The control strategy in the first stage ensures that the control strategy in the second stage can maintain the safe and stable operation of the distribution network under the worst scenarios. The grid-storage joint optimization technology based on distributed architecture establishes an optimization planning model for the distribution network energy storage system with the goal of optimal technical and economic performance of the transmission and distribution network and considering the constraints of safe and stable operation of the transmission and distribution network, respectively. The PG&E-69 node system arithmetic example is used to verify the effectiveness and feasibility of the proposed model and algorithm. The results of the arithmetic example show that the strategy obtained based on the robust optimization model can achieve voltage magnitude stability within the safety range of 1.0-1.05 p.u. in the simulation scenario that has the best economy. At the same time, the mismatches of each distribution system under cooperative planning are all 0, which indicates that the proposed optimization strategy can fully cooperate with the resources of transmission and distribution networks, promote the safe consumption of clean energy, effectively improve the economy of transmission and distribution networks, and achieve the goal of “mutual benefit and win-win”.

In order to improve the economy of microgrid construction and operation, and meet the personalized demand for reliability of various types of microgrids, an integrated flexible planning method for microgrid is proposed to adapt to multiple scenarios. Based on the judgment results of type and composition, a two-layer model including capacity planning and grid planning is established. The lower-level capacity planning takes the minimum operation cost of micro-source construction as the goal and adopts the mixed integer optimization algorithm to solve it. The upper layer grid planning takes the minimum cost of network construction and operation as the goal, and uses the particle swarm optimization algorithm to solve it. A closed-loop integrated planning system consisting of judgment, capacity planning, and grid planning is formed. The system can meet the personalized reliability requirements of different microgrids by flexibly adjusting the independent operation duration constraints and the load outage attention parameters. The example shows that the proposed method can effectively reduce the construction and operation cost of microgrid, and has a good adaptability to different types and components and different reliability requirements.

Existing single-stage planning and multi-stage non-rolling planning methods for distribution networks have problems such as low equipment utilization efficiency and poor investment benefits. In order to solve the above problems, this paper firstly proposes a multi-stage rolling planning method for distribution networks based on analyzing the limitations of the existing planning methods, which divides the planning cycle of the distribution network into multiple planning stages, and makes rolling amendments to the planning scheme of each stage according to the latest information during the planning cycle. Then, a multi-stage rolling planning model of distribution network taking into account conditional value at risk is established with the objective of minimizing the total investment and operation cost of the distribution network. On the one hand, the users' electricity bill is taken into account in the objective function, and the necessity of this part of the benefits is demonstrated. On the other hand, the conditional value at risk is used to quantify the uncertainty of the operation cost in the process of the expansion planning of the distribution network, which reduces the operation cost risk of the distribution network. Next, this paper uses the rainflow counting method to characterize the capacity decay characteristics of energy storage in the distribution network, and proposes an iterative solution framework that considers energy storage capacity decay to solve the proposed model. Finally, the proposed method is applied to an 18-node distribution network planning case. This confirms that the multi-stage rolling planning method could improve the investment benefits and reduce the investment cost by approximately 27.27%. Besides, it will increase the total cost by approximately 2750 USD in the case if the users' electricity bill is not taken into account. And the maximum capacity of energy storage may decay to 87.6% of the initial capacity or even lower during operation, which may cause the line current to exceed the limit if it is not taken into account. [ABSTRACT FROM AUTHOR]

Optical detection is an indispensable part of microfluidic systems for nutrient determination in seawater. Coupling total internal reflection capillaries with microfluidic chips is a practical alternative to increase the optical path length for high-sensitivity and a low detection limit in colorimetric assays, which has not been applied in microfluidic devices for seawater nutrients. Here, we present an online microfluidic system which integrated a total internal reflection capillary made of Teflon AF 2400 for the high-sensitivity detection of nitrite and nitrate in seawater. The off-chip capillary lengthens the optical path without changing the internal flow path of the microfluidic chip, enhancing the sensitivity, reducing the detection limit and widening the dynamic range of the system, which significantly improves the performance of the microfluidic system based on wet-chemistry. The detection limit for nitrite is 0.0150 μM using an external 20 cm capillary and 0.0936 μM using an internal 5 cm absorption cell, providing an over 6-fold improvement. Laboratory analysis of surface seawater samples collected from the South China Sea with this system and a one-month online deployment of an autonomous analyzer developed based on this system at a station revealed correlations between the nitrite and nitrate with tide, salinity and chlorophyll over slight variations and narrow ranges, demonstrating the high-sensitivity of this method. [ABSTRACT FROM AUTHOR]

Background: Germline mutations have been identified in a small number of hereditary cancers, but the genetic predisposition for many familial cancers remains to be elucidated. Methods: This study identified a Chinese pedigree that presented different cancers (breast cancer, BRCA; adenocarcinoma of the esophagogastric junction, AEG; and B‐cell acute lymphoblastic leukemia, B‐ALL) in each of the three generations. Whole‐genome sequencing and whole‐exome sequencing were performed on peripheral blood or bone marrow and cancer biopsy samples. Whole‐genome bisulfite sequencing was conducted on the monozygotic twin brothers, one of whom developed B‐ALL. Results: According to the ACMG guidelines, bioinformatic analysis of the genome sequencing revealed 20 germline mutations, particularly mutations in the DNAH11 (c.9463G > A) and CFH (c.2314G > A) genes that were documented in the COSMIC database and validated by Sanger sequencing. Forty‐one common somatic mutated genes were identified in the cancer samples, displaying the same type of single nucleotide substitution Signature 5. Meanwhile, hypomethylation of PLEK2, MRAS, and RXRA as well as hypermethylation of CpG island associated with WT1 was shown in the twin with B‐ALL. Conclusions: These findings reveal genomic alterations in a pedigree with multiple cancers. Mutations found in the DNAH11, CFH genes, and other genes predispose to malignancies in this family. Dysregulated methylation of WT1, PLEK2, MRAS, and RXRA in the twin with B‐ALL increases cancer susceptibility. The similarity of the somatic genetic changes among the three cancers indicates a hereditary impact on the pedigree. These familial cancers with germline and somatic mutations, as well as epigenomic alterations, represent a common molecular basis for many multiple cancer pedigrees. [ABSTRACT FROM AUTHOR]

To overcome the shortcoming of the Fuzzy C-means algorithm (FCM)—that it is easy to fall into local optima due to the dependence of sub-spatial clustering on initialization—a Multi-Strategy Tuna Swarm Optimization-Fuzzy C-means (MSTSO-FCM) algorithm is proposed. Firstly, a chaotic local search strategy and an offset distribution estimation strategy algorithm are proposed to improve the performance, enhance the population diversity of the Tuna Swarm Optimization (TSO) algorithm, and avoid falling into local optima. Secondly, the search and development characteristics of the MSTSO algorithm are introduced into the fuzzy matrix of Fuzzy C-means (FCM), which overcomes the defects of poor global searchability and sensitive initialization. Not only has the searchability of the Multi-Strategy Tuna Swarm Optimization algorithm been employed, but the fuzzy mathematical ideas of FCM have been retained, to improve the clustering accuracy, stability, and accuracy of the FCM algorithm. Finally, two sets of artificial datasets and multiple sets of the University of California Irvine (UCI) datasets are used to do the testing, and four indicators are introduced for evaluation. The results show that the MSTSO-FCM algorithm has better convergence speed than the Tuna Swarm Optimization Fuzzy C-means (TSO-FCM) algorithm, and its accuracies in the heart, liver, and iris datasets are 89.46%, 63.58%, 98.67%, respectively, which is an outstanding improvement. [ABSTRACT FROM AUTHOR]

A new gridded spatio-temporal big data fusion method is proposed for the organization and management of cropland big data, which could serve the analysis application of cropland quality evaluation and other analyses of geographic big data. Compared with traditional big data fusion methods, this method maps the spatio-temporal and attribute features of multi-source data to grid cells in order to achieve the structural unity and orderly organization of spatio-temporal big data with format differences, semantic ambiguities, and different coordinate projections. Firstly, this paper constructs a dissected cropland big data fusion model and completes the design of a conceptual model and logic model, constructs a cropland data organization model based on DGGS (discrete global grid system) and Hash coding, and realizes the unified management of vector data, raster data and text data by using multilevel grids. Secondly, this paper researches the evaluation methods of grid-scale adaptability, and generates distributed multilevel grid datasets to meet the needs of cropland area quality evaluation. Finally, typical data such as soil organic matter data, road network data, cropland area data, and statistic data in Da'an County, China, were selected to carry out the experiment. The experiment verifies that the method could not only realize the unified organization and efficient management of cultivated land big data with multimodal characteristics, but also support the evaluation of cropland quality. [ABSTRACT FROM AUTHOR]

Landslide susceptibility evaluation (LSE) is a critical issue for disaster prevention. Limited by labor cost and observation technology, landslide samples are extremely limited in dense vegetation‐covered and remote areas, making the common supervised learning model underfit with limited samples. Therefore, the reliability of analysis results in mountainous areas is low. Transfer learning can achieve reliable assessment without the need for representative samples. However, transfer learning suffers from environmental heterogeneity in regional LSE and may transfer incorrect classification knowledge of landslide features from dissimilar environments. Aiming at these challenges, we proposed a geo‐environment‐aware LSE method based on unsupervised adversarial transfer learning. The key is to consider the difference in landslide features in different geo‐environments. The study areas were first divided into multiple sub‐environments, and the similarity between the sub‐environments was calculated. Then an environment‐aware adversarial transfer model was built for fine‐grained aligning of the landslide feature with similar sub‐environments and for reducing negative transfer between dissimilar environments. The fitted classification model was employed to predict the target regions and to generate the final LSE. The experimental results indicated that the proposed method achieves reliable LSE for sample‐free regions. The accuracy of the proposed method is 7–12% better than commonly used methods such as support vector machines, random forests, and artificial neural networks. The performance of the proposed method is even close to the results of supervised learning with the presence of representative samples, and it also performs more globally and objectively in susceptibility mapping. These results reveal that the proposed method effectively transfers the knowledge of landslide susceptibility from other regions to the sample‐free region. [ABSTRACT FROM AUTHOR]

In July 2021, a flooding event, which attracted the attention of the whole country and even the world, broke out in Henan, resulting in dramatic losses across multiple fields (e.g., economic and agricultural). The basin at the junction of Hebi, Xinxiang, and Anyang was the most affected region, as the spread of water from the Wei river submerged surrounding agricultural land (e.g., corn-dominated). To comprehensively evaluate the flooding impacts, we proposed a framework to detect the flooding area and evaluated the degree of loss using satellite time series data. First, we proposed a double-Gaussian model to adaptively determine the threshold for flooding extraction using Synthetic Aperture Radar (SAR) data. Then, we evaluated the disaster levels of flooding with field survey samples and optical satellite images. Finally, given that crops vary in their resilience to flooding, we measured the vegetation index change before and after the flooding event using satellite time series data. We found the proposed double-Gaussian model could accurately extract the flooding area, showing great potential to support in-time flooding evaluation. We also showed that the multispectral satellite images could potentially support the classification of disaster levels (i.e., normal, slight, moderate, and severe), with an overall accuracy of 88%. Although these crops were temporarily affected by this flooding event, most recovered soon, especially for the slightly and moderately affected regions. Overall, the distribution of resilience of these affected crops was basically in line with the results of classified disaster levels. The proposed framework provides a comprehensive aspect to the retrospective study of the flooding process on crops with diverse disaster levels and resilience. It can provide rapid and timely flood damage assessment and support emergency management and disaster verification work. [ABSTRACT FROM AUTHOR]

Sewer blockages delay sewage discharge or cause it to overflow, which pollutes the environment and is a public health hazard. This necessitates the quick and accurate identification and positioning of sewer blockages. Following a sewer blockage, the sewage is intercepted and the liquid level at the upstream and downstream of the blocking point changes. This study established a method for identifying sewer blockages by analyzing the range and rate of the liquid level change at the upstream and downstream of the blocking point. Through pilot-scale and full-scale experiments, this study summarized the threshold values of the liquid level change rate and the liquid level fluctuation range of the drainage pipeline in normal operation, as well as the threshold values of the liquid level change rate and the liquid level fluctuation range of the upstream and downstream of the sewer blocking point. Moreover, the sewer blockage identification matrix was completed. Sewer blockage in rural areas can be identified and positioned using mathematical tools such as the data-driven model. This research method allows for real-time monitoring and timely warning of the sewer status, thereby reducing the labor and material consumption and unnecessary earthwork excavation to ensure the stable operation of the drainage pipeline. [ABSTRACT FROM AUTHOR]

Purpose: To study the longitudinal rehabilitation of binocular visual function in adolescent intermittent exotropia (IXT) after successful surgery and compare the results with those of a normal population. The role of binocular function in ocular alignment stability was also evaluated postoperatively. Methods: In this prospective study, 30 adolescents with IXT successfully corrected after 1 month were followed for 12 months, and 30 children with normal vision were enrolled as controls. Stereopsis, the fusional vergence amplitude, sensory fusion, and accommodative flexibility were measured to assess binocular function at baseline and 6 and 12 months postoperatively. The controls were tested once when they were enrolled in the study. Results: The deviation was −32.00 ± 8.60 prism diopters (PD) at distance fixation and −36.0 ± 9.10 PD at near fixation preoperatively with an average correction of 28.53 ± 3.79 PD and 30.67 ± 1.34 PD at 1 month postoperatively. Distance stereoacuity and near stereoacuity improved from 1 to 12 months postoperatively (p = 0.025 and p = 0.041, respectively). Compared with the controls, the fusional convergence reserve at distance (p = 0.025) and near (p = 0.033) fixations and fusion reserve ratio at distance (p = 0.000) and near (p = 0.000) fixations remained subnormal, whereas sensory fusion (p = 0.237), distance stereopsis (p = 0.120), and the fusional divergence amplitude at a distance (p = 0.168) were normal. However, no significant correlations were found between binocular functions at 1 month postoperatively and the postoperative drift. Conclusion: Binocular function significantly improved from before to after successful corrective surgery and continued to improve from 1 to 12 months postoperatively in adolescents with IXT. No significant correlations were found between binocular functions at 1 month postoperatively and ocular alignment stability. [ABSTRACT FROM AUTHOR]

Abstract Background Activation of MEK5 in many cancers is associated with carcinogenesis through aberrant cell proliferation. In this study, we determined the level of phosphorylated MEK5 (pMEK5) expression in human colorectal cancer (CRC) tissues and correlated it with clinicopathologic data. Methods pMEK5 expression was examined by immunohistochemistry in a tissue microarray (TMA) containing 335 clinicopathologic characterized CRC cases and 80 cases of nontumor colorectal tissues. pMEK5 expression of 19 cases of primary CRC lesions and paired with normal mucosa was examined by Western blotting. The relationship between pMEK5 expression in CRC and clinicopathologic parameters, and the association of pMEK5 expression with CRC survival were analyzed respectively. Results pMEK5 expression was significantly higher in CRC tissues (185 out of 335, 55.2%) than in normal tissues (6 out of 80, 7.5%; P < 0.001). Western blotting demonstrated that pMEK5 expression was upregulated in 12 of 19 CRC tissues (62.1%) compared to the corresponding adjacent nontumor colorectal tissues. Overexpression of pMEK5 in CRC tissues was significantly correlated to the depth of invasion (P = 0.001), lymph node metastasis (P < 0.001), distant metastasis (P < 0.001) and high preoperative CEA level (P < 0.001). Consistently, the pMEK5 level in CRC tissues was increased following stage progression of the disease (P < 0.001). Analysis of the survival curves showed a significantly worse 5-year disease-free (P = 0.002) and 5-year overall survival rate (P < 0.001) for patients whose tumors overexpressed pMEK5. However, in multivariate analysis, pMEK5 was not an independent prognostic factor for CRC (DFS: P = 0.139; OS: P = 0.071). Conclusions pMEK5 expression is correlated with the staging of CRC and its expression might be helpful to the TNM staging system of CRC.

Virtual Landslide Disaster environments are important for multilevel simulation, analysis and decision-making about Landslide Disasters. However, in the existing related studies, complex disaster scene objects and relationships are not deeply analyzed, and the scene contents are fixed, which is not conducive to meeting multilevel visualization task requirements for diverse users. To resolve the above issues, a construction method for Personalized Virtual Landslide Disaster Environments Based on Knowledge Graphs and Deep Neural networks is proposed in this paper. The characteristics of relationships among users, scenes and data were first discussed in detail; then, a knowledge graph of virtual Landslide Disaster environments was established to clarify the complex relationships among disaster scene objects, and a Deep Neural network was introduced to mine the user history information and the relationships among object entities in the knowledge graph. Therefore, a personalized Landslide Disaster scene data recommendation mechanism was proposed. Finally, a prototype system was developed, and an experimental analysis was conducted. The experimental results show that the method can be used to recommend intelligently appropriate disaster information and scene data to diverse users. The recommendation accuracy stabilizes above 80% – a level able to effectively support The Construction of Personalized Virtual Landslide Disaster environments. [ABSTRACT FROM AUTHOR]

Purpose. To evaluate whether clinical measures of postoperative binocular functions could predict the long-term stability of postoperative ocular alignment in children with intermittent exotropia. Methods. A retrospective study was performed in thirty-nine children (median: 7 years) who have been surgically treated from intermittent exotropia without overcorrection (less than 10 prism diopters [pd] of exodeviation at 1 month postoperatively). Angles of deviation and binocular functions were measured preoperatively and at 1 month, 6 months, and the final follow-up visit (≥24 months) postoperatively. We examined the relationships between postoperative drift (change of ocular alignment) and binocular functions (sensory fusion, fusional convergence amplitude, and stereoacuity). Results. The surgical success rate (esophoria/tropia ≤5 pd to exophoria/tropia ≤10 pd) dropped to 76.9% at 6 months after surgery and to 53.8% at individuals' last visit (mean: 37 months). The mean exodrift was 7.7 ± 9.2 pd from the postoperative month 1 to the final visit (p < 0.001) on distance fixation. Distance stereoacuity, central fusion, and fusional convergence amplitude significantly improved following surgery (p < 0.05). However, no significant correlation was found between their binocular functions measured at the beginning of each follow-up period and the postoperative drift (all p > 0.13). Conclusion. Our findings suggest that the clinical measures of sensory fusion, fusional convergence amplitude, and stereoacuity cannot serve as a robust predictor for the long-term stability of postoperative ocular alignment in patients who underwent successful surgery without overcorrection at 1 month postoperatively. [ABSTRACT FROM AUTHOR]

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called the hydraulic drive unit (HDU), is employed to drive the joints of these robots. However, there are some common problems in the HDU resulted from hydraulic systems, such as strong nonlinearity, asymmetry dynamic characteristics between positive and negative moving directions of the piston rod, and time-varying parameters. It is difficult to obtain the desired control performance by just using classical control methods such as the traditional PID control. In this paper, a position controller that combines fuzzy terminal sliding mode control (FTSMC) and time delay estimation (TDE) is proposed, in which FTSMC adopts a compound reaching law which combines the tangent function and the exponential reaching law. Moreover, the fuzzy control is introduced to adjust the parameters of the reaching law in real time to improve the adaptability of FTSMC. Based on FTSMC, the external uncertain disturbance of the HDU position control system is estimated by TDE, which ensures the simplicity of system modeling and the normal application of FTSMC. Finally, the control effects of the controller combining FTSMC and TDE are verified on the HDU performance test platform and the load simulation experiment platform. The experimental results show that the proposed controller greatly improves the system position control performance and has a strong disturbance rejection ability and a good adaptability under different working conditions. The above research results can provide an important reference and experimental basis for the inner loop of compliance control of legged robots. [ABSTRACT FROM AUTHOR]

The human–cyber–physical world produces a considerable volume of multi-modal spatio-temporal data, thus leading to information overload. Visual variables are used to transform information into visual forms that are perceived by the powerful human vision system. However, previous studies of visual variables focused on methods of 'drawing information' without considering 'intelligence' derived from balancing 'importance' and 'unimportance'. This paper proposes semantic visual variables to support an augmented geovisualization that aims to avoid exposing users to unnecessary information by highlighting goal-oriented content over redundant details. In this work, we first give definitions of several concepts and then design a semiotic model for depicting the mechanisms of augmented geovisualization. We also provide an in-depth discussion of semantic visual variables based on a hierarchical organization of the original visual variables, and we analyse the critical influencing factors that affect the choice of visualization forms and visual variables. Finally, a typical application is used to illustrate the relevance of this study. [ABSTRACT FROM AUTHOR]

Net community production (NCP) in the surface water of the northern Gulf of Mexico (nGOM) and its coupling with the CO2 system were examined during the productive spring season. NCP was estimated using multiple approaches: (1) underway O2 and Ar ratio, (2) oxygen changes during light/dark bottle oxygen incubations, and (3) non-conservative changes in dissolved inorganic carbon or nutrients. These methods all showed high spatial variability of NCP and displayed similar patterns along the river–ocean mixing gradient, showing high production rates in plume regions. NCP O2Ar estimated from high-resolution O2 and Ar underway measurement indicated heterotrophic conditions at the high-nutrient and high-turbidity Mississippi River end (-51.3±11.9 mmol C m -2 d -1 when salinity < 2) resulting from the influence of terrestrial carbon input and light limitation on photosynthesis. High NCP O2Ar rates (105.0±59.2 mmol C m -2 d -1 , up to 235.4 mmol C m -2 d -1) were observed in the Mississippi and Atchafalaya plumes at intermediate salinities between 15 and 30 where light and nutrients were both favorable for phytoplankton production. NCP O2Ar rates observed in the high-salinity, oligotrophic offshore waters (salinity > 35.5) were close to zero due to nutrient limitation. Air–sea CO2 fluxes generally showed corresponding changes, from being a strong CO2 source in the river channel (55.5±7.6 mmol C m -2 d -1), to a CO2 sink in the plume (-13.4±5.5 mmol C m -2 d -1), and to being nearly in equilibrium with the atmosphere in offshore waters. Overall, the surface water of the nGOM was net autotrophic during spring 2017, with an area-weighted mean NCP O2Ar of 21.2 mmol C m -2 d -1 , and was a CO2 sink of - 6.7 mmol C m -2 d -1. A temporal mismatch between in situ biological production and gas exchange of O2 and CO2 was shown through a box model to result in decoupling between NCP O2Ar and CO2 flux (e.g., autotrophic water as a CO2 source outside the Mississippi River mouth and heterotopic water as a CO2 sink in the Atchafalaya coastal water). This decoupling was a result of in situ biological production superimposed on the lingering background pCO2 from the source water because of the slow air–sea CO2 exchange rate and the buffering effect of the carbonate system. [ABSTRACT FROM AUTHOR]

A novel method called knowledge-guided spatio-temporal consistent correlation analysis (KSTCCA) was developed to discover reliable deformation features induced by multiple factors based on multimode landslide monitoring data. Compared to conventional approaches, KSTCCA integrates both temporal and spatial correlation analysis to improve the consistency of deformation patterns and capture the spatio-temporal heterogeneities in multimode monitoring data. KSTCCA considers both the landslide deformation mechanisms and the relationships between different influential factors as knowledge. Moreover, the method extracts the morphological structures of monitoring curves based on a seven-point approach and identifies knowledge rules using the k-means clustering method. Under the guidance of prior knowledge, a spatial correlation analysis is conducted based on support vector regression, and a temporal correlation analysis of the time lag is carried out based on the morphological structure features. Finally, three kinds of typical monitoring data, including deformation, rainfall, and reservoir water level data collected in the Baishuihe landslide area, China, are used for experimental analysis to verify the validity of the proposed method. [ABSTRACT FROM PUBLISHER]

Approximately 25–30% of colorectal cancer (CRC) cases are expected to result from a genetic predisposition, but in only 5–10% of these cases highly penetrant germline mutations are found. The remaining CRC heritability is still unexplained, and may be caused by a hitherto-undefined set of rare variants with a moderately penetrant risk. Here we aimed to identify novel risk factors for early-onset CRC using whole-exome sequencing, which was performed on a cohort of CRC individuals (n = 55) with a disease onset before 45 years of age. We searched for genes that were recurrently affected by rare variants (minor allele frequency ≤0.001) with potentially damaging effects and, subsequently, re-sequenced the candidate genes in a replication cohort of 174 early-onset or familial CRC individuals. Two functionally relevant genes with low frequency variants with potentially damaging effects, PTPN12 and LRP6, were found in at least three individuals. The protein tyrosine phosphatase PTP-PEST, encoded by PTPN12, is a regulator of cell motility and LRP6 is a component of the WNT-FZD-LRP5-LRP6 complex that triggers WNT signaling. All variants in LRP6 were identified in individuals with an extremely early-onset of the disease (≤30 years of age), and two of the three variants showed increased WNT signaling activity in vitro. In conclusion, we present PTPN12 and LRP6 as novel candidates contributing to the heterogeneous susceptibility to CRC. [ABSTRACT FROM AUTHOR]

Water shortage and poor soil fertility are the main factors restricting the sustainable development of peanut production in semi-arid areas of Northeast China. It is thus essential to have a deep understanding of the soil water-nitrogen dynamics and crop water/nitrogen use for developing water and nutrient strategies. Three levels of irrigation treatment (W 65 , 65% of field capacity; W 55 , 55% of field capacity; W 45 , 45% of field capacity) and a rain-fed treatment (CK) were implemented in field experiments conducted for peanut during the growing seasons of 2016 and 2017 in Liaoning, Northeast China. The AHC (Agro-Hydrological & chemical and Crop systems simulator) model was calibrated and validated, and then applied to assess peanut yield, water productivity (WP) and nitrogen use efficiency (NUE) for the present situation and future irrigation scenarios. The results indicated that the AHC model was capable of simulating soil water and nitrogen status and peanut growth. Simulations of soil water/nitrogen contents and crop growth indicators (Leaf area index, aboveground biomass, plant height and yield) fitted well with field observations. Simulated dynamics showed that 9–21% of the total water input and 14–27% of the total N input were leached out the root zone (0–60 cm). Rainfall was the main cause of water percolation and nitrogen leaching. The highest average yield (5701 kg ha–1) and NUE (26.77 kg kg–1) were obtained in the W 55 treatment. The WP was not obviously decreased under the W 55 treatment, and was only 4.1% lower than that of the CK treatment, in which the WP was highest. Based on scenario analysis with the consideration of crop yield, WP and NUE, the optimal irrigation amount of 80–97 mm is recommended for peanut cultivation in this region. We demonstrated that the AHC model could be used to develop water management strategies for peanuts in Northeast China to conserve water while sustaining agriculture. • AHC model showed good performances in simulating water and nitrogen dynamics and peanut growth. • Water percolation and nitrogen leaching mainly occurred due to heavy rainfall events. • Evapotranspiration and crop N uptake accounted for 75%− 87% and 74%− 97% of the total water and nitrogen inputs. • The 80–97 mm irrigation is recommended for peanut cultivation. [ABSTRACT FROM AUTHOR]

Objective: E-selectin (SELE) mediates the rolling and adhesion of leukocytes on activated endothelial cells and plays a critial role in the pathogenesis of coronary artery disease (CAD). Associatons between the A561C and G98T polymorphisms of the SELE gene and CAD risk were investigated broadly, but the results were inconsistent. In the present study, we performed a meta-analysis to systematically evaluate the associations between the two polymorphisms and the risk of CAD. Methods: Comprehensive research was conducted to identify relevant studies. The fixed or random effect model was selected based on the heterogeneity among studies, which was evaluated with Q-test and Ι2. Meta-regression was used to explore the potential sources of between-study heterogeneity. Peters's linear regression test was used to estimate the publication bias. Results: Overall, 24 articles involving 3694 cases and 3469 controls were included. After excluding articles deviating from Hardy–Weinberg equilibrium in controls and sensitive analysis, our meta-analysis showed a significant association between the A561C ploymprphism and CAD in dominant (OR  = 1.84, 95% CI  = 1.56–2.16) and codominant (OR  = 1.74, 95% CI  = 1.49–2.03) models. As for the G98T polymorphism, significantly increased CAD risk was observed in dominant (OR  = 1.47, 95% CI  = 1.16–1.87) and codominant (OR  = 1.48, 95% CI  = 1.18–1.86) models, but after subgroup analysis, the association was not significant among Caucasians in dominant (OR  = 1.58, 95% CI  = 0.73–3.41) and codominant (OR  = 1.58, 95% CI  = 0.79–3.20) models. Conclusions: Despite some limitations, our meta-analysis suggested that the SELE gene polymorphisms (A561C, G98T) were significantly associated with increased risk of CAD. However, after subgroup analysis no significant association was found among Caucasians for the G98T polymorphism, which may be due to the small sample size and other confounding factors. Future investigations with multicenter, large-scale, and multi-ethnic groups are needed. [ABSTRACT FROM AUTHOR]

Background: Programmed death ligand-1 (PD-L1) has been identified as a factor associated with poor prognosis in a range of cancers, and was reported to be mainly induced by PTEN loss in gliomas. However, the clinical effect of PD-L1 and its regulation by PTEN has not yet been determined in colorectal cancer (CRC). In the present study, we verified the regulation of PTEN on PD-L1 and further determined the effect of PTEN on the correlation between PD-L1 expression and clinical parameters in CRC. Methods/Results: RNA interference approach was used to down-regulate PTEN expression in SW480, SW620 and HCT116 cells. It was showed that PD-L1 protein, but not mRNA, was significantly increased in cells transfected with siRNA PTEN compared with the negative control. Moreover, the capacity of PTEN to regulate PD-L1 expression was not obviously affected by IFN-γ, the main inducer of PD-L1. Tissue microarray immunohistochemistry was used to detect PD-L1 and PTEN in 404 CRC patient samples. Overexpression of PD-L1 was significantly correlated with distant metastasis (P<0.001), TNM stage (P<0.01), metastatic progression (P<0.01) and PTEN expression (P<0.001). Univariate analysis revealed that patients with high PD-L1 expression had a poor overall survival (P<0.001). However, multivariate analysis did not support PD-L1 as an independent prognostic factor (P = 0.548). Univariate (P<0.001) and multivariate survival (P<0.001) analysis of 310 located CRC patients revealed that high level of PD-L1 expression was associated with increased risks of metastatic progression. Furthermore, the clinical effect of PD-L1 on CRC was not statistically significant in a subset of 39 patients with no PTEN expression (distant metastasis: P = 0.102; TNM stage: P = 0.634, overall survival: P = 0.482). Conclusions: PD-L1 can be used to identify CRC patients with high risk of metastasis and poor prognosis. This clinical manifestation may be partly associated with PTEN expression. [ABSTRACT FROM AUTHOR]

Nanographite sheets (NanoGs)/polypyrrole (PPy)/polymethacrylate (PMMA)–epoxy conductive films have been successfully prepared. NanoGs were prepared by treating the expanded graphite with sonication in aqueous alcohol solution. Then nanocomposite films were fabricated by in-situ polymerization of pyrrole in the presence of NanoGs by using epoxy resin and PMMA blends as copolymer matrix. From the thermogravimetric analysis, the introduction of epoxy resin and a few PMMA blends exhibited a beneficial effect on the thermal stability of pure PPy. According to the four-point probe test, the conductivity of the final nanocomposite films was about 1.5 × 10−3 s/cm. [ABSTRACT FROM AUTHOR]

Regulated deficit irrigation (RDI) is an important means by which the water use efficiency (WUE) of peanut can be improved and facilitates the sustainable development of the peanut industry. However, most studies of RDI have only focused on single growth periods, which limits the water-saving potential. In this study, continuous regulated deficit irrigation (CRDI) was used to significantly improve the WUE of peanut through an experiment employing a split-plot design. Three levels of water deficit treatment, severe (H1/J1, 45% field capacity), moderate (H2/J2, 55% field capacity), and mild (H3/J3, 65% field capacity), were applied in the flower pegging stage (H) and the pod setting stage (J). Moderate CRDI (H2J2) stably improved the instantaneous water use efficiency of peanut leaves. Yield was not significantly decreased under the H2J2 treatment, and was only 4.47% lower than that of the H3J2 treatment, in which the yield was the highest. The highest WUE was observed in the H2J2 treatment (1.87 kg·m−3). The first time that the soil water content reached the lower limit in the pod setting stage, the proline content in the H1J1 treatment was 13.57 times higher than that in the H3J3, indicating that peanuts in the H1J1 treatment experienced substantial drought stress. The second time that the lower limit of soil water content was reached, the proline content in the H1J1 treatment was 7.14 times higher than that in the H3J3 treatment, indicating that the peanut drought resistance was improved by the drought-rehydration exercise at the flower pegging stage and drought stress was alleviated in the pod setting stage. We conclude that moderate CRDI is beneficial to peanut drought resistance for arid and semi-arid areas, and significantly promoted higher WUE. • Moderate continuous regulated deficit irrigation (H2J2) improved the peanut WUE without reducing peanut yield. • Moderate continuous regulated deficit irrigation improved the peanut drought resistance by drought-rehydration exercise. • After drought resistance exercise, moderate continuous regulated deficit irrigation greatly increased IWUE during the pod setting stage. [ABSTRACT FROM AUTHOR]

The spatial conflicts in the construction of high-speed railways not only reduce project efficiency, but also lead to serious accidents. To address these key issues, this paper presents a dynamic simulation method for constructions processes based on a virtual geographic environment. This approach can facilitate the identification of conflicts in the construction scheme through accurately expressing and analysing the intricate spatio-temporal relations among railway facility components, construction equipment and the surrounding environment. First, a high-precision virtual geographic scene in which the construction process and methods can be visualized and modelled intuitively is established with terrain, imagery, and engineering 3D models. Then, the overall construction processes can be accurately simulated by a sequential display of the railway components and the behaviour of construction equipment. To simulate the behaviour of construction equipment, the linkage relations between each joint of construction machinery are accurately modelled and animation control parameters are extracted. Finally, a construction simulation of a high-speed railway bridge was performed, and the experimental results show that the proposed method can provide a scientific basis for the optimization of complex engineering construction schemes, safety hazard assessments, and related full life cycle tasks. [ABSTRACT FROM AUTHOR]

Summary: This paper attempts to investigate the relationship between topology and reliability of a distribution network associated with a singular value sequence (SVS) to accurately represent the crucial features of the distribution network topology, in which a novel algorithm called topology similarity analysis (TSA) is proposed for the first time and adopted to calculate the reliability indices of the distribution networks. Under such framework, SVS is treated as a similarity index that constructs a standard database of distribution network topology. Moreover, TSA outperforms other typical algorithms used in distribution network reliability assessment with a lower calculation costs and higher efficiency. Two case studies, eg, standard IEEE 33‐bus system and large‐scale practical 148‐bus system, are carried out at first to evaluate the effectiveness of the proposed approach. Then, TSA incorporated with splitting method is applied in the 148‐bus case. Simulation results demonstrate that TSA is 2 to 2000 times faster than that of other typical algorithms. Besides, the overall calculation time of TSA just grows insignificantly as the scale of the distribution network increases, together with a guaranteed less than 0.005% precision error. [ABSTRACT FROM AUTHOR]