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Recent climate change and vegetation greening have important implications for global terrestrial hydrological cycles and other ecosystem functions, raising concerns about the watershed water supply capacity for large water diversion projects. To address this emerging concern, we built a hybrid model based on the Coupled Carbon and Water (CCW) and Water Supply Stress Index (WaSSI) models and conducted a case study on the upper Han River basin (UHRB) in Central China that serves as the water source area to the middle route of the South-to-North Water Diversion Project (SNWDP). Significant vegetation greening occurred in the UHRB during 2001–2018, largely driven by the widespread afforestation in the region, with the normalized difference vegetation index increasing at a rate of 0.5±0.1 % yr−1 (p<0.05) but with no significant trends in climate during the same period (albeit with large interannual variability). Annual water yield greatly decreased, and vegetation greening alone induced a significant decrease in water yield of 3.2±1.0 mm yr−1 (p<0.05). Vegetation greening could potentially reduce the annual water supply by 7.3 km3 on average, accounting for 77 % of the intended annual water diversion volume of the SNWDP. Although vegetation greening can bring enormous ecosystem goods and services (e.g., carbon sequestration and water quality improvement), it could aggravate the severity of hydrological drought. Our analysis indicated that vegetation greening in the UHRB reduced about a quarter of water yield on average during drought periods. Given the future warming and drying climate is likely to continue to raise evaporative demand and exert stress on water availability, the potential water yield decline induced by vegetation greening revealed by our study needs to be taken into account in the water resources management over the UHRB while reaping other benefits of forest protection and ecological restoration.

Background and Aims Carbon (C) allocation plays important role in plant adaptation to water and nutrient stress. However, the effects of drought and nutrient deficit on the allocation of recently fixed C in plant-soil-microbe system remain largely unknown. Methods We studied the response of C allocation of Sophora moorcroftiana (an indigenous pioneer plant in Tibet) in plant-soil-microbe system to drought, nitrogen (N) and phosphorus (P) deficit using a microcosm experiment. The 13CO2 continuous labeling was used to trace C transport through the plant-soil-microbe system. Results Drought significantly reduced C allocation to stem and root but increased allocation to soil. Deficit of N and P significantly increased C allocation to root under well-watered conditions, while P deficit significantly increased allocation to stem but decreased allocation to leaf under drought conditions. Carbon allocation to microbes was mainly affected by nutrient deficit, and 13C amounts in microbial biomass was decreased by N deficit and increased by P deficit. Stem 13C amount was positively related to net photosynthetic rate and leaf 13C amount, suggesting that plants preferentially allocate C to stem. Soil 13C amount decreased and 13C amount in microbial biomass first decreased and then increased with increasing plant 13C amount, indicating that high plant C supply did not drive high amounts of C transferred to soil and microbes. Conclusion We proved that drought and nutrient deficit interactively affected C allocation in plant-soil-microbe system, and revealed a U-shaped relationship between plant C supply and the amounts of C transferred to microbes.

The BEPCII project is for upgrading the Beijing Electron Positron Collider to reach a higher luminosity. The cryogenic system has been firstly designed and deployed in BEPCII, which provides cooling capacity for SRF cavities, SCQ and SSM. The cryogenic control system consists of Siemens PLC for the refrigerator control and “PLC + IOC” for superconducting device control. The BEPCII machine commissioning with beam started in October 2006. This paper describes the design and the development of the cryogenic control system.

BACKGROUND: Gastric cancer (GC) has a high incidence and high mortality rate among Asian countries, and distinguishing predictive prognosis biomarkers for GC are essential. Cancer-associated fibroblasts (CAFs) play a significant role in the progression, immune evasion, and therapeutic resistance of GC. Therefore, CAF-associated genes might have huge potential as prognostic biomarkers for predicting tumor progression and survival rate in GC pateints. METHODS: A sum of 1,134 GC patients from the The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE62254, and GSE84437 datasets as well as GC cohorts from Xijing hospital were included. Firstly, we performed univariate Cox regression analysis to identify CAF-associated prognostic genes. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to develop a CAF gene signature (CAFGS) in the TCGA-STAD training cohort. CAFGS’s predictive performance was examined in both the training and validation cohorts, and the relationship between CAFGS and the tumor microenvironment (TME) was investigated by ssGSEA, CIBERSORT, TIMER, and ESTIMATE. Finally, a nomogram of CAFGS was established. RESULTS: Ten CAF-associated genes (ANGPTL4, CPNE8, CST2, HTR1F, IL1RAP, NR1D1, NTAN1, OLFML2B, TMEM259, and VTN) were identified to develop CAFGS. A high CAFGS score represented a worse outcome for GC patients in four cohorts, and a strong correlation was found between CAFGS and the infiltration of immune cells. We showed that CAFs contribute to immune evasion and unfavorable prognoses of GC patients by promoting the formation of an immunosuppressive microenvironment, and a high level of CAF infiltration may attenuate the efficacy of immunotherapy. The nomogram based on CAFGS showed reasonable predictive ability and may deliver great clinical net benefits. CONCLUSIONS: We established a CAFGS model with 10 CAF-associated genes that had a great predictive value for GC prognosis and survival rate evaluation. This study could provide a novel insight for investigating the role of CAFs in GC.

Colorectal cancer (CRC) is a major leading cause of cancer mortality worldwide in which dysregulated protein synthesis plays an etiologic role. The eukaryotic elongation factor 1 A1 (eEF1A1) exerts significant effects on protein synthesis by contributing to peptide chain extension. Whereas its role in CRC remains to be investigated. In this study, we found that the mRNA and protein levels of eEF1A1 were significantly upregulated in CRC cell lines and tissues. Elevated expression of eEF1A1 was correlated with shorter overall survival in 94 CRC patients. The inhibition of proliferation and cell cycle block were observed in CRC cells after eEF1A1 downregulation. Mechanistically, weighted gene correlation network analysis and further Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that mitogen-activated protein kinases (MAPKs) signaling pathways were significantly enriched in high-eEF1A1 expression group, and the levels of phosphorylated p38/JNK/ERK MAPK were dramatically decreased after eEF1A1 downregulation. Overexpression of eEF1A1 in CRC correlated with a poor prognosis. Collectively, this study determined the oncogenic role of eEF1A1 in CRC proliferation and tumorigenesis. eEF1A1 might be a promising therapeutic target and prognostic biomarker in CRC.

De novo lipogenesis (DNL) is a dynamic process that converts excess carbohydrates into fatty acids to maintain cellular homeostasis. Dysregulation of DNL is associated with diverse obesity-related diseases and many tumor types. Therefore, monitoring DNL in real-time with high sensitivity should be highly beneficial when screening therapeutic agents for their potential use as obesity treatments.A sequence coding for Gaussia luciferase (GLuc) preceded by a 2A peptide was inserted into the murine fatty acid synthase (FASN) genetic locus by homologous recombination to generate FASN-2A-GLuc mice. The luciferase mouse model was evaluated in conditions of physical and pharmacological stimuli by in vivo and ex vivo imaging.The distribution of bioluminescence signals in different organs was identical to the FASN expression: high in white fat, brown fat, and the lungs. In addition, the bioluminescence signals accurately recapitulated the dynamic change of FASN in response to fasting and refeeding conditions. Moreover, with this murine reporter model, we also discovered that fatostatin, a synthetic inhibitor of sterol regulatory element-binding proteins, effectively inhibited DNL in multiple organs, especially in adipose tissues under a high-carbohydrate diet.Our FASN-2A-GLuc reporter mouse model proved to be a sensitive visualization tool for monitoring both systemic and organ-specific DNL in real time.

Nature-like fishway arrangements are commonly used because these structures imitate the characteristics of natural rivers and effectively allow fish to migrate past river sections blocked by hydraulic structures. In this paper, physical models were analyzed, and the velocity distributions of two different fishway structures (Types I and II) were compared. Results showed that the maximum mainstream velocity of the Type I structure was 5.3% lower than that of the Type II structure. However, the average mainstream velocity of the Type I structure was 21.1% greater than that of the Type II structure. The total per-cycle length of the mainstream path in the Type II structure was 2.1 times greater than that of the Type I structure, which indicated that the length of the mainstream path was somewhat proportional to the average velocity of the mainstream. When the flow rate was kept constant, increases in the velocity of the main flow associated with changes in the internal structure of the fishway decreased the average velocity of the main flow, while decreases in the total length of the flow path led to increases in the average velocity of the main flow. Due to frictional head loss along the fishway and local head loss, as well as the overlaps between these factors, the overall flow rate gradually decreased every cycle, despite periodic fluctuations.

The paper uses 2018 data to construct a numerical general equilibrium model containing 26 economies, and adds global value chain and added-value trade into the structure, and systematically simulates the economic effects of China’s response to three scenarios of nine categories of CPTPP policy selection. In line with the simulation results, under the four scenarios in which China takes unilateral measures to deal with the impact of CPTPP, the policy effectiveness from high to low separately includes: the construction of China–Japan–Korea free-trade agreement, the entry into force of RCEP and the further opening-up. In the two scenarios in which China joins the CPTPP, the effect of joining the agreement with the first batch of expansion countries is better, while the effect of joining the CPTPP later is slightly worse. After the United States returned to CPTPP, China chose three scenarios in which the economic effects, from high to low, were to optimize the business environment, take no measures and join CPTPP with the United States. Among the three different options, the economic benefit of China’s active choice to join CPTPP is the best. Second is the effect of China’s unilateral measures on CPTPP. However, once the United States returns to CPTPP, it will bring adverse impact on China. The effective measure to deal with it is to optimize the business environment to reduce the cost of the trade.

Recent global climate change and vegetation greening have important implications to Earth’s global biogeochemical cycles and climate, raising concern about the water supply of water diversion projects. To quantify how such a greening trend impacts local water balance and the capacity of water supply, we built a hybrid model based on the Coupled Carbon and Water (CCW) and Water Supply Stress Index (WaSSI) models. We conducted a case study using the Upper Han River basin (UHRB) in southern China that serves as the water source area to the middle route of the South-North Water Diversion Project (SNWDP). Significant vegetation greening occurred in the UHRB during 2001–2018, with the normalized difference vegetation index increasing at a rate of 0.5 % yr−1 (p

Hepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis, however, biomarkers for the prognostic assessment of HCC remain suboptimal. Consequently, we aimed to develop a reliable tool for prognostic estimation of HCC.Differentially expressed genes (DEGs) between HCC and adjacent normal tissues in 3 Gene Expression Omnibus (GEO) datasets were identified, followed by hub gene selection and least absolute shrinkage and selection operator (LASSO) Cox regression to develop a prognostic gene signature. Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent area under the curve (AUC), and integrated value of time-dependent AUC (iAUC) were used to assess the relationship between predictors and clinical outcomes in the training and validation datasets. Then we built nomograms including gene signature and clinicopathological factors to forecast the probability of death. Moreover, we performed quantitative real-time PCR (qPCR) to compare the expression of prognostic genes between HCC and adjacent normal tissues. Finally, the relationship between prognostic genes and tumor microenvironment (TME) was investigated using immune cell infiltration algorithms and single cell transcriptomic database.Eight prognostic genes (We have established and validated an eight-gene based prognostic model, which could be an effective tool for the prognostic evaluation of HCC patients.

In this study, we established a SEQR model for the spread of COVID-19. The impact of city lockdown measures and other factors on the spread of the epidemic was discussed in this paper through dynamic analysis and numerical simulation of the model. The research results showed that the input ratio of the exposed population should be controlled to at least 0.001 if the government wanted to effectively control the epidemic. Closing the city was the most effective way. The exposed population of COVID-19 in Xiaogan City was hoping to be cleared on February 29 under strict control. The closed city could be released around March 28. But at the same time, we should pay attention to prevent the virus from entering it again. The peak number of existing patients would reduce by about 1,400 if city lockdown measures were taken in Xiaogan City four days in advance.

It has been demonstrated that the utilization of a monolingual corpus in neural Grammatical Error Correction (GEC) systems can significantly improve the system performance. The previous state-of-the-art neural GEC system is an ensemble of four Transformer models pretrained on a large amount of Wikipedia Edits. The Singsound GEC system follows a similar approach but is equipped with a sophisticated erroneous data generating component. Our system achieved an F0:5 of 66.61 in the BEA 2019 Shared Task: Grammatical Error Correction. With our novel erroneous data generating component, the Singsound neural GEC system yielded an M2 of 63.2 on the CoNLL-2014 benchmark (8.4% relative improvement over the previous state-of-the-art system).

Affect recognition is an important component towards the better interaction between human and machines. Applications of emotion recognition in speech can be found in several areas such as human computer interaction and call centres. In recent years, Deep Neural Networks (DNN) have been used with great success in recognizing emotions. In this paper, we present a new model for continuous emotion recognition from speech. Our model, which was trained end-to-end, is comprised of a Convolutional Neural Network (CNN), which extracts features from the raw signal, and stacked on top of it a 2-layer Long Short-Term Memory (LSTM), so as to consider the contextual information in the data. Our model significantly outperforms, in terms of concordance correlation coefficient, the state-of-the-art methods for the RECOLA database.

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Real-time fault detections are needed in systems which require high reliability. Some methods like online BIST can detect fault on runtime, but it cannot real-time detect the fault. In this article, three online self-checking methods for built-in fault detection will be presented. These detection methods not only can real-time detect the fault, but can also locate the fault where logic blocks have undergone an SEU by comparing their configuration data. The testing result shows that the method proposed in this article have better performance than that of online BIST Keywords-fault detection; real-time; BIST; self-checking; FPGA

A Monte Carlo program based on Geant3 has been developed for BESII detector simulation. The organization of the program is outlined, and the digitization procedure for simulating the response of various sub-detectors is described. Comparisons with data show that the performance of the program is generally satisfactory., Comment: 17 pages, 14 figures, uses elsart.cls, to be submitted to NIMA

The accelerator driven sub-crit. system (ADS) in China is a kind of transmutation machine to minimize nuclear waste. As one of the important parts in ADS, injector will be built at IHEP,CAS. Injector I needs two cryomodules operating at 2K cryogenic environment to realize a 10MeVproton beam energy. Each cryomodule includes seven spoke cavities and sevensuperconducting magnets. This paper describes the overall design of the cryogenic system, including the cooling flow chart, heat loads estn., the structure of the operation cryomodule and some of the key components. [on SciFinder(R)]