Solar-driven CO_(2) conversion to methane and methanol using different nanostructured Cu_(2)O-based catalysts modified with Au nanoparticles

This work describes the use of TiO_(2)nanotubes-based electrodes(TNT)modified with Cu_(2)O nanostructures and gold nanoparticles for the photoelectroreduction of CO_(2)to produce value-added compounds.A thin layer of polydopamine was used as both an adherent agent and an electron transfer mediator,due to itsπ-conjugated electron system.The highest production yield was achieved using a TNT@PDA/Nc/Au40%electrode,with Faradaic efficiencies of 47.4%(110.5μM cm^(-2))and 27.8%(50.4μM cm^(-2))for methanol and methane,respectively.The performance of the photoelectrodes was shown to be Cu_(2)O facet-dependent,with cubic structures leading to greater conversion of CO_(2)to methanol(43%)and methane(27%),compared to the octahedral morphology,while a higher percentage of metallic gold on the nanostructured Cu_(2)O surface was mainly important for CH4production.Density functional theory(DFT)calculations supported these findings,attributing the superior photoelectrocatalytic performance of the TNT@PDA/Nc/Au40%electrode for CH4generation to the formation of an OCH3intermediate bonded to Au atoms.Studies using isotope-labeling and analysis by gas chromatograph-mass(GC-MS)demonstrated that13CO_(2)was the source for photoelectrocatalytic generation of13CH3OH and13CH313CH2OH.

A Deeper Understanding of the CO_(2)Emission Pathway Under China’s Carbon Emission Peak and Carbon Neutrality Goals

Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of the United Nations General Assembly in September 2020,President Xi Jinping announced that China would adopt more vigorous policies and measures against climate change.

Prediction of ENSO using multivariable deep learning

本文基于残差神经网络和观测数据构建了一套深度学习多因子预报测模型,以改进厄尔尼诺-南方涛动(ENSO)的预报.该模型基于最大信息系数进行因子时空特征提取,并根据泰勒图的评估标准可自动确定关键预报因子进行预报.该模型在超前8个月以内的预报性能要优于当前传统的业务预报模式.2011–2018年间,该模型的预报性能优于多模式集成预报的结果.在超前6个月预报时效上,模型预报相关性可达0.82,标准化后的均方根误差仅为0.58°C,多模式集成预报的相关性和标准化后的均方根误差分别为0.70和0.73°C.该模型春季预报障碍问题有所缓解,并且自动选取的关键预报因子可用于解释热带和副热带热动力过程对于ENSO变化的影响.

Estimating the value of a statistical life in China: A contingent valuation study in six representative cities

The value of a statistical life(VSL)is a crucial tool for monetizing health impacts.To explore the VSL in China,this study examines people’s willingness to pay(WTP)to reduce death risk from air pollution in six representative cities in China based on face-to-face contingent valuation interviews(n=3936)from March 7,2019 to September 30,2019.The results reveal that the WTP varied from CNY 455 to 763 in 2019(USD 66-111),corresponding to a VSL range of CNY 3.79-6.36 million(USD 549395-921940).The VSL in China in 2019 is estimated to be CNY 4.76 million(USD 689659).The statistics indicate that monthly expenditure levels,environmental concerns,risk attitudes,and assumed market acceptance,which have seldom been dis‐cussed in previous studies,significantly impact WTP and VSL.These findings will serve as a reference for ana‐lyzing mortality risk reduction benefits in future research and for policymaking.

Arctic Oscillation and Antarctic Oscillation in Internal Atmospheric Variability with an Ensemble AGCM Simulation

In this study, we investigated the features of Arctic Oscillation （AO） and Antarctic Oscillation （AAO）, that is, the annular modes in the extratropics, in the internal atmospheric variability attained through an ensemble of integrations by an atmospheric general circulation model （AGCM） forced with the global observed SSTs. We focused on the interannual variability of AO/AAO, which is dominated by internal atmospheric variability. In comparison with previous observed results, the AO/AAO in internal atmospheric variability bear some similar characteristics, but exhibit a much clearer spatial structure： significant correlation between the North Pacific and North Atlantic centers of action, much stronger and more significant associated precipitation anomalies, and the meridional displacement of upper-tropospheric westerly jet streams in the Northern/Southern Hemisphere. In addition, we examined the relationship between the North Atlantic Oscillation （NAO）/AO and East Asian winter monsoon （EAWM）. It has been shown that in the internal atmospheric variability, the EAWM variation is significantly related to the NAO through upper-tropospheric atmospheric teleconnection patterns.

Impact of the gut microbiota on rodent models of human disease

Traditionally bacteria have been considered as either pathogens, commensals or symbionts. The mammal gut harbors 1014 organisms dispersed on approximately 1000 different species. Today, diagnostics, in contrast to previous cultivation techniques, allow the identification of close to 100% of bacterial species. This has revealed that a range of animal models within different research areas, such as diabetes, obesity, cancer, allergy, behavior and colitis, are affected by their gut microbiota. Correlation studies may for some diseases show correlation between gut microbiota composition and disease parameters higher than 70%. Some disease phenotypes may be transferred when recolonizing germ free mice. The mechanistic aspects are not clear, but some examples on how gut bacteria stimulate receptors, metabolism, and immune responses are discussed. A more deeper understanding of the impact of microbiota has its origin in the overall composition of the microbiota and in some newly recognized species, such as Akkermansia muciniphila, Segmented filamentous bacteria and Faecalibacterium prausnitzii, which seem to have an impact on more or less severe disease in specific models. Thus, the impact of the microbiota on animal models is of a magnitude that cannot be ignored in future research. Therefore, either models with specific microbiota must be developed, or the microbiota must be characterized in individual studies and incorporated into data evaluation.

Impacts of Irrigation and Vegetation Growth on Summer Rainfall in the Taklimakan Desert

In recent decades,a greening tendency due to increased vegetation has been noted around the Taklimakan Desert(TD),but the impact of such a change on the local hydrological cycle remains uncertain.Here,we investigate the response of the local hydrological cycle and atmospheric circulation to a green TD in summer using a pair of global climate model(Community Earth System Model version 1.2.1)simulations.With enough irrigation to support vegetation growth in the TD,the modeling suggests first,that significant increases in local precipitation are attributed to enhanced local recycling of water,and second,that there is a corresponding decrease of local surface temperatures.On the other hand,irrigation and vegetation growth in this low-lying desert have negligible impacts on the large-scale circulation and thus the moisture convergence for enhanced precipitation.It is also found that the green TD can only be sustained by a large amount of irrigation water supply since only about one-third of the deployed water can be“recycled”locally.Considering this,devising a way to encapsulate the irrigated water within the desert to ensure more efficient water recycling is key for maintaining a sustainable,greening TD.

Credit Card Fraud Detection Using Weighted Support Vector Machine

Credit card fraudulent data is highly imbalanced, and it has presented an overwhelmingly large portion of nonfraudulent transactions and a small portion of fraudulent transactions. The measures used to judge the veracity of the detection algorithms become critical to the deployment of a model that accurately scores fraudulent transactions taking into account case imbalance, and the cost of identifying a case as genuine when, in fact, the case is a fraudulent transaction. In this paper, a new criterion to judge classification algorithms, which considers the cost of misclassification, is proposed, and several undersampling techniques are compared by this new criterion. At the same time, a weighted support vector machine (SVM) algorithm considering the financial cost of misclassification is introduced, proving to be more practical for credit card fraud detection than traditional methodologies. This weighted SVM uses transaction balances as weights for fraudulent transactions, and a uniformed weight for nonfraudulent transactions. The results show this strategy greatly improve performance of credit card fraud detection.

LUMP AND INTERACTION SOLUTIONS TO LINEAR (4+1)-DIMENSIONAL PDES

Taking a class of linear(4+1)-dimensional partial differential equations as examples, we would like to show that there exist lump solutions and interaction solutions in(4+1)-dimensions. We will compute abundant lump solutions and interaction solutions to the considered linear(4+1)-dimensional partial differential equations via symbolic computations,and plot three specific solutions with Maple plot tools, which supplements the existing literature on lump, rogue wave and breather solutions and their interaction solutions in soliton theory.

Numerical experimental study on the potential climatic impacts oflarge-scale wind farms in China

Wind energy has been rapidly developed in China during the past decades and the installed capacity has been the largest in the world. In the future, utilization of wind power is still expected to carry out in China mainly with a large-scale centralized layout. Here, we examine the potential climatic impacts of large-scale windfarms associated with deployment scale in China using numerical experiments, in which four deployment scenarios were designed. These four scenarios represented relatively small- (484 GW), medium- (2165 GW) and large-scale (3490 GW and 5412 GW) installed wind power capacities, respectively. Results showed that turbulent kinetic energy, wind velocity, and air temperature varied consistently within those windfarms with the largest changes in turbine hub heights. Moreover, the above relatively large- scale windfarms could induce regional wanning with a maximum of above 0.8 °C in North China. This regional warming may be linked to an anomalous circulation pattern with a negative pressure anomaly center in Northeast China and a positive pressure anomaly center in the middle and lower reaches of the Yangtze-Huaihe River Basin.

Disruption of the TWEAK/Fn14 pathway prevents 5-fluorouracil-induced diarrhea in mice

AIM To clarify the roles of TWEAK and its receptor Fn14 in 5-fluorouracil(5-FU)-induced diarrhea.METHODS Diarrhea was induced in wild-type(WT), Fn14 knockout(KO), and IL-13 receptor(IL-13R)α1 KO BALB/c mice using a single injection of 5-FU. Histological analysis, cytokine analysis, and flow cytometry was performed on ileal tissues and cells. Murine colon carcinomabearing mice were co-treated with an anti-TWEAK antibody and 5-FU. Embryonic fibroblast response to cytokines was also analyzed.RESULTS5-FU induced high Fn14 expression in epithelial cells. The severity of 5-FU-induced diarrhea was lower in Fn14 KO mice compared with WT mice. Administration of anti-TWEAK antibody reduced 5-FU-induced diarrhea without affecting the antitumor effects of 5-FU in vivo. 5-FU-induced expression of IL-13, IL-17 A, TNF-α, and IFN-γ in the ileum was Fn14 dependent. The severity of 5-FU-induced diarrhea was lower in IL-13Rα1 KO mice, indicating major role for IL-13 signaling via IL-13Rα1 in pathogenesis. We found that IL-13Rα2, an IL-13 neutralizing/cell protective receptor, was strongly induced by IL-33 in vitro and in vivo. IL-13Rα2 was upregulated in the ileum of 5-FU-treated Fn14 KO mice. Thus, the deletion of Fn14 upregulated IL-13Rα2 expression, which reduced IL-13 expression and activity. CONCLUSION Disruption of the TWEAK/Fn14 pathway affects several interconnected pathways, including those associated with IL-13, IL-33, and IL-13Rα2, to attenuate 5-FUinduced intestinal side effects.

RIEMANN-HILBERT PROBLEMS OF A SIX-COMPONENT MKDV SYSTEM AND ITS SOLITON SOLUTIONS

Based on a 4 x 4 matrix spectral problem, an AKNS soliton hierarchy with six potentials is generated. Associated with this spectral problem, a kind of Riemann-Hilbert problems is formulated for a six-component system of mKdV equations in the resulting AKNS hierarchy. Soliton solutions to the considered system of coupled mKdV equations are computed, through a reduced Riemann-Hilbert problem where an identity jump matrix is taken.

High resolution crop intensity mapping using harmonized Landsat-8 and Sentinel-2 data

An increase in crop intensity could improve crop yield but may also lead to a series of environmental problems, such as depletion of ground water and increased soil salinity. The generation of high resolution(30 m) crop intensity maps is an important method used to monitor these changes, but this is challenging because the temporal resolution of the 30-m image time series is low due to the long satellite revisit period and high cloud coverage. The recently launched Sentinel-2 satellite could provide optical images at 10–60 m resolution and thus improve the temporal resolution of the 30-m image time series. This study used harmonized Landsat Sentinel-2(HLS) data to identify crop intensity. The sixth polynomial function was used to fit the normalized difference vegetation index(NDVI) and enhanced vegetation index(EVI) curves. Then, 15-day NDVI and EVI time series were then generated from the fitted curves and used to generate the extent of croplands. Lastly, the first derivative of the fitted VI curves were used to calculate the VI peaks;spurious peaks were removed using artificially defined thresholds and crop intensity was generated by counting the number of remaining VI peaks. The proposed methods were tested in four study regions, with results showing that 15-day time series generated from the fitted curves could accurately identify cropland extent. Overall accuracy of cropland identification was higher than 95%. In addition, both the harmonized NDVI and EVI time series identified crop intensity accurately as the overall accuracies, producer’s accuracies and user’s accuracies of non-cropland, single crop cycle and double crop cycle were higher than 85%. NDVI outperformed EVI as identifying double crop cycle fields more accurately.

An ocean current inversion accuracy analysis based on a Doppler spectrum model

Microwave remote sensing is one of the most useful methods for observing the ocean parameters. The Doppler frequency or interferometric phase of the radar echoes can be used for an ocean surface current speed retrieval,which is widely used in spaceborne and airborne radars. While the effect of the ocean currents and waves is interactional. It is impossible to retrieve the ocean surface current speed from Doppler frequency shift directly. In order to study the relationship between the ocean surface current speed and the Doppler frequency shift, a numerical ocean surface Doppler spectrum model is established and validated with a reference. The input parameters of ocean Doppler spectrum include an ocean wave elevation model, a directional distribution function, and wind speed and direction. The suitable ocean wave elevation spectrum and the directional distribution function are selected by comparing the ocean Doppler spectrum in C band with an empirical geophysical model function（CDOP）. What is more, the error sensitivities of ocean surface current speed to the wind speed and direction are analyzed. All these simulations are in Ku band. The simulation results show that the ocean surface current speed error is sensitive to the wind speed and direction errors. With VV polarization, the ocean surface current speed error is about 0.15 m/s when the wind speed error is 2 m/s, and the ocean surface current speed error is smaller than 0.3 m/s when the wind direction error is within 20° in the cross wind direction.

Multiobjective Optimal Design of Underwater Acoustic Projector with Porous Piezocomposite Active Elements

This paper concerns the optimization problem for multilayered ultrasonic transducer with active porous piezoelectric layer. The dependences of the effective moduli for porous piezoelectric material on porosity have been previously obtained and allowed to decrease the number of design variables. The multiobjective optimization problem based on the Pareto-frontier calculation has been solved using the live-link of finite-element (FE) package Comsol Multiphysics with MATLAB.

Workflow-Based Platform Design and Implementation for Numerical Weather Prediction Models and Meteorological Data Service

In this paper, we present a set of best practices for workflow design and implementation for numerical weather prediction models and meteorological data service, which have been in operation in China Meteorological Administration (CMA) for years and have been proven effective in reliably managing the complexities of large-scale meteorological related workflows. Based on the previous work on the platforms, we argue that a minimum set of guidelines including workflow scheme, module design, implementation standards and maintenance consideration during the whole establishment of the platform are highly recommended, serving to reduce the need for future maintenance and adjustment. A significant gain in performance can be achieved through the workflow-based projects. We believe that a good workflow system plays an important role in the weather forecast service, providing a useful tool for monitoring the whole process, fixing the errors, repairing a workflow, or redesigning an equivalent workflow pattern with new components.

EnKF Assimilation of Satellite-retrieved Cloud Water Path to Improve Tropical Cyclone Rainfall Forecast

Tropical cyclone(TC) rainfall forecast has remained a challenge. To create initial conditions with high quality for simulation, the present study implemented a data assimilation scheme based on the EnKF method to ingest the satellite-retrieved cloud water path(C_(w)) and tested it in WRF. The scheme uses the vertical integration of forecasted cloud water content to transform control variables to the observation space, and creates the correlations between C_(w) and control variables in the flow-dependent background error covariance based on all the ensemble members, so that the observed cloud information can affect the background temperature and humidity. For two typhoons in 2018(Yagi and Rumiba), assimilating C_(w) significantly increases the simulated rainfalls and TC intensities. In terms of the average equitable threat score of daily moderate to heavy rainfall(5-120 mm), the improvements are over 130%, and the dry biases are cut by about 30%. Such improvements are traced down to the fact that C_(w) assimilation increases the moisture content, especially that further away from the TC center, which provides more precipitable water for the rainfall,strengthens the TC and broadens the TC size via latent heat release and internal wind field adjustment.

The impact of ocean data assimilation on seasonal predictions based on the National Climate Center climate system model

An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoobservations of sea surface temperature(SST),sea surface height(SSH),sea surface salinity(SSS),temperature and salinity(T/S)profiles were first generated in a free model run.Then,a series of sensitivity tests initialized with predefined bias were conducted for a one-year period;this involved a free run(CTR)and seven assimilation runs.These tests allowed us to check the analysis field accuracy against the"truth".As expected,data assimilation improved all investigated quantities;the joint assimilation of all variables gave more improved results than assimilating them separately.One-year predictions initialized from the seven runs and CTR were then conducted and compared.The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles,but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies.The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles,while surface data assimilation became more important at higher latitudes,particularly near the western boundary currents.The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables.Finally,a central Pacific El Ni?o was well predicted from the joint assimilation of surface data,indicating the importance of joint assimilation of SST,SSH,and SSS for ENSO predictions.

Obesity trends in Russia. The impact on health and healthcare costs

Similar to most developed countries, obesity rates inRussiahave been steadily increasing. This has led to a high burden of obesity related diseases and associated healthcare costs. The micro-simulation model has been utilized to project body mass index (BMI) and BMI related disease burden and healthcare costs. Incidence, mortality, survival and healthcare costs were collected for thirteen diseases. The results have been simulated for 3 hypothetical scenarios to project a potential impact of policy interventions: 1) assuming no reduction in BMI;2) 1% reduction in mean BMI across the population;3) 5% reduction in mean BMI across the population. Nearly 58% of the female population was obese (BMI ≥30 kg/m2) or overweight (BMI 25 -29.9 kg/m2) in 2010, and the prevalence is projected to decrease to 54% in 2050. The rates are predicted to increase for men from 51% in 2010 to 76% in 2050. The prevalence rates will triple for some obesity-related diseases. A one percent decrease in BMI across the population will save more than two billion US Dollars in 2030 and 2050. Despite female obesity prevalence starting at a higher point than the men, obesity is predicted to increase in males but not females. Disease and economic burden attributed to these obesity rates are still severe and the country should implement strong policies to tackle the obesity epidemic.

N2 fixation rate and diazotroph community structure in the western tropical North Pacific Ocean

In the present study, we report N2 fixation rate(15N isotope tracer assay) and the diazotroph community structure(using the molecular method) in the western tropical North Pacific Ocean(WTNP)(13°–20°N, 120°–160°E). Our independent evidence on the basis of both in situ N2 fixation activity and diazotroph community structure showed the dominance of unicellular N2 fixation over majority of the WTNP surface waters during the sampling periods.Moreover, a shift in the diazotrophic composition from unicellular cyanobacteria group B-dominated to Trichodesmium spp.-dominated toward the western boundary current(Kuroshio) was also observed in 2013. We hypothesize that nutrient availability may have played a major role in regulating the biogeography of N2 fixation.In surface waters, volumetric N2 fixation rate(calculated by nitrogen) ranged between 0.6 and 2.6 nmol/(L·d) and averaged(1.2±0.5) nmol/(L·d), with <10 μm size fraction contributed predominantly(88%±6%) to the total rate between 135°E and 160°E. Depth-integrated N2 fixation rate over the upper 200 m ranged between 150 μmol/(m^2·d)and 480 μmol/(m^2·d)average(225±105) μmol/(m^2·d). N2 fixation can account for 6.2%±3.7% of the depthintegrated primary production, suggesting that N2 fixation is a significant N source sustaining new and export production in the WTNP. The role of N2 fixation in biogeochemical cycling in this climate change-vulnerable region calls for further investigations.