Search

It has been controversial whether the matching of learning styles with teaching environment has improved the teaching effects. This paper constructs matching modes by choosing Sternberg's three learning styles (liberal leaning, internal scope and global level) and adopts curriculum comprehensiveness and instructing modes. The research, based on data of off-line teaching collected from 456 college students in China, finds that (a) direct effect: three learning styles have significant effects on eight dimensions of learners' cognitive information processing (CIP); (b) matching effect: the alignment of learners' liberal leaning and instructing modes has a direct impact on the eight dimensions of learners' CIP; the alignment of learners' global level and curriculum characteristics has a direct impact on the 7 dimensions; the alignment of learners' internal scope and instructing modes have no significant direct impact on the 7 dimensions; (c) moderating effect of the mandatory use of IT (MUIT): MUIT may restrain or strengthen effects of some matching modes on some dimensions of CIP. The key conclusion is that whether personalized instructing based on learners' characteristics can improve teaching results requires the selection of appropriate matching modes. Not all matching modes have matching effects, and matching effect is influenced by MUIT. [ABSTRACT FROM AUTHOR]

This study aims to explore the difference between on-line and off-line teaching and comprehensively evaluate the of elearning system operation effect as both technology-mediated learning and an open information system. This study develops “process-situation-result” (PSR) network, a comprehensive learning system evaluation model. It empirically analyzes the PSR models under off-line and on-line teaching, as well as the intermediary role of e-learning situation in the impact of e-learning process on elearning results. The results show: (1) Learners' perception of e-learning situation is obviously different between off-line and on-line teaching. (2) The eight dimensions of e-learning process have no significant direct impact on e-learning outcome Except in on-line teaching groups, SF (getting self-feedback) has a significantly positive influence. In off-line teaching, GA (gaining attention), IO (informing learner of the objectives), and PG (providing learning guidance) have indirect effects on e-learning. (3) GA, IO and PG have a direct impact on e-learning situation in both on-line and off-line teaching, and only RK (Stimulating recall of prior knowledge) has an impact only in on-line teaching. The other four dimensions have no direct impact on e-learning We provide a theoretical framework for the integration of technology and teaching, on-line teaching and off-line teaching. [ABSTRACT FROM AUTHOR]

An optimal preventive maintenance policy and optimization method of operation parameters for a production line consisting of multiple execution units is described herein. According to the characteristics of the production unit, the relationship between the reliability and operating parameters of the execution unit is established, as well as its relationship between the operating parameters and maintenance cost. The minimum maintenance cost and effective operating speed is selected as the objective, and the optimal parameters are derived by heuristic algorithm. Finally, a numerical example and simulation experiments are shown which validated the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Precision agriculture has been increasingly practised in recent years. Under precision management, farmland is divided into several management zones to implement different strategies and improve irrigation water productivity and revenues. In this research, six soil properties (silt, sand, soil moisture content, available nitrogen, electrical conductivity and elevation) were selected, and fuzzy c-means clustering was used to delineate management zones. The field was divided into three zones. The differences in the mean of the soil properties among the zones were large and within a zone were small. The coefficient of variation of the properties and yield were also smaller than that before classification. The optimization was carried out by using a genetic algorithm based on the Jensen model. Three objective functions were set as maximum yield, maximum irrigation water productivity (IWP) and maximum revenue, and the weights were kept equal to 1/3. The WHCNS (soil water heat carbon nitrogen simulator) model was used to simulate the maize yield under optimized irrigation schedule for the three management zones and to calculate IWP and revenue. Compared with uniform management, IWP and revenue were increased by 0.6 kg m−3 and $61 ha−1, respectively. The optimized irrigation schedule can be used as a reference for the actual irrigation management. It can increase the IWP and revenue under the premise of achieving the target yield. The results show that the method can guide precision agricultural production and management in large-scale farmland. [ABSTRACT FROM AUTHOR]

Technology-mediated learning (TML) has turned out to be essential in classroom in higher education. How to evaluate the effect of TML has become a critical issue in research and practice. Yet, there exists very little understanding of how to measure the effect of TML on learning process. The existing research results are difficult to be used in teaching design. This paper develops an instrument as a diagnostic tool to comprehensively evaluate the effect of TML on learning process. This instrument focuses on the relationship among IT, cognitive information processing, and instructional process. Based on cognitive information processing theory and Gagné’s instructional theory, definition and measurement of 8 constructs are identified and designed. In a sample of 181 undergraduates in nine majors, the study finds that this instrument has higher reliability, better convergent validity and discriminant validity. This instrument can help provide rich information about whether and how TML affects instructional events and learning activities effectively. At the same time, it can be a guiding tool for more effective applications of TML in instructional event design. [ABSTRACT FROM AUTHOR]

The distribution characteristics of the oil-water contact are the basis for the reservoir exploration and development and reserves evaluation. The reservoir with a tilted oil-water contact has a unique formation mechanism, and the understanding of its distribution and formation mechanism will directly affect the evaluations for the reservoir type, well deployment, selection of well pattern and type, determination of test section, and reserves evaluation. Based on the analysis of reservoir characteristics, petrophysical properties and geological structure in 40 reservoirs worldwide with tilted oil-water contacts, the progress of the research on the formation mechanisms of titled oil-water contacts is summarized in terms of the hydrodynamic conditions, reservoir heterogeneity, neotectonic movement and oil-gas exploitation. According to the formation mechanism of tilted oil-water contacts and the needs of exploration research, different aspects of research methods are summarized and classified, such as the calculation of equipotential surfaces for oil and water in the formation, analysis of formation pressure and analysis of reservoir physical properties and so on. Based upon statistical analysis, it is suggested that the degree of the inclination of the oil-water contact be divided based on the dip of oil-water contact (DipTOWC). The tilted oil-water contact is divided into three categories: large dip (DipTOWC≥55 m/km), medium dip (4 m/km≤DipTOWC<55 m/km), and small dip (DipTOWC<4 m/km). The classification and evaluation method can be combined with structure amplitude and reservoir property. The formation mechanism of domestic and international reservoirs with tilted oil-water contacts are summarized in this paper, which have important significance in guiding the exploration and development of the oilfield with tilted oil-water contacts, reserves evaluation, and well deployment. [ABSTRACT FROM AUTHOR]

Agricultural water management is the core part of agricultural efficient water use in irrigation districts, which provides basic guarantee and decision-support for improving the efficiency of water production. This study was conducted in three typical irrigation districts in Huang-huai-hai river basin of north China. The evaluation index system of agricultural water management in irrigation districts was established which included technology index, engineering index, management index, environment index and economic index, classified 5 sorts of second-grade indices, 14 third-grade indices and 35 fourth-grade indices. The weight of each index was confirmed through improved AHP method. The grades of agricultural water management of Fenhe, Shijin and Renmin Shengliqu irrigation districts in Huang-huai-hai riverbasin were obtained using Grey Correlation method and Fuzzy Comprehensive Evaluation method. Results showed that the evaluation indices ranked according to the descending order of their weights as engineering index, 0.2147; management index, 0.2138; technology index, 0.2128; economics index, 0.1797; environment index, 0.1791 in the criterion level. The engineering and management index were the most two important factors which influenced the agricultural water management in irrigation districts. The grades of Fenhe, Shijin and Renmin Shengliqu irrigation districts were good, good and average, respectively. The study provides a theoretical basis in improving the level of agricultural water management and water use efficiency in irrigation districts of north China. [ABSTRACT FROM AUTHOR]

Modelling crop evapotranspiration (ET) response to different planting scenarios in an irrigation district plays a significant role in optimizing crop planting patterns, resolving agricultural water scarcity and facilitating the sustainable use of water resources. In this study, the SWAT model was improved by transforming the evapotranspiration module. Then, the improved model was applied in Qingyuan Irrigation District of northwest China as a case study. Land use, soil, meteorology, irrigation scheduling and crop coefficient were considered as input data, and the irrigation district was divided into subdivisions based on the DEM and local canal systems. On the basis of model calibration and verification, the improved model showed better simulation efficiency than did the original model. Therefore, the improved model was used to simulate the crop evapotranspiration response under different planting scenarios in the irrigation district. Results indicated that crop evapotranspiration decreased by 2.94% and 6.01% under the scenarios of reducing the planting proportion of spring wheat (scenario 1) and summer maize (scenario 2) by keeping the total cultivated area unchanged. However, the total net output values presented an opposite trend under different scenarios. The values decreased by 3.28% under scenario 1, while it increased by 7.79% under scenario 2, compared with the current situation. This study presents a novel method to estimate crop evapotranspiration response under different planting scenarios using the SWAT model, and makes recommendations for strategic agricultural water management planning for the rational utilization of water resources and development of local economy by studying the impact of planting scenario changes on crop evapotranspiration and output values in the irrigation district of northwest China. [ABSTRACT FROM AUTHOR]

Study the circumferential contour of the deformation zone in the strip warm rolling, according the flow stress characteristic of warm deformation, the contact arc of deformation area is divided into three different curvature arc, the roller elastic flattening model of deformation zone is established using the method of quadratic curve fitting. The roller circumferential contour was calculated that iterative solver the roller elastic flattening deformation area and the distribution of rolling force along the rolling direction. Deformation process of warm-rolling was simulated using ANSYS/LS-DYNA finite element, the trend with simulation and calculated in the forward and backward slip zone is accordance, the model is more consistent with deformation process of the strip warm rolling. [ABSTRACT FROM AUTHOR]

A massive bloom of green macroalgaeUlva proliferaoccurred in June 2008 in the Yellow Sea, resulting in perhaps the largest “green tide” event in the history of bloom research. The covered area is about 1,200 km2and the impacted area reached 40,000 km2on 31 May. This also occurred in the following two years, 2009 and 2010. We analyzed the satellite data from MODIS and the results showed that sea surface temperature increased 1–3°C inU. proliferabloom locations. The macroalgae in the water may have been the cause of the increase of sea surface temperatures. Rapid increases ofU. proliferabiomass during the blooms may have increased radiation absorption of the water, and thus enhanced the rate of heating at the sea surface. The present study represents a preliminary observation, which is an important step for understanding influences of macroalgae on ocean surface conditions. [ABSTRACT FROM AUTHOR]

The diurnal sea surface temperature (D-SST, which is the daytime SST minus the night-time SST) and its relationship with heavy phytoplankton blooms were observed using satellite and in situ data. Two phytoplankton bloom events covering large areas in the East China Sea (ECS) were analysed to investigate the reactions among D-SST, chlorophyll-a (chl-a) concentration, suspended sediment (SS), coloured dissolved organic matter (CDOM), wind speed (WS) and solar radiation (SR). The results showed a positive relationship between D-SST and chl-a concentration in phytoplankton bloom areas. Further analyses of 12 major phytoplankton bloom events (total area >1000 km2) occurring between 2000 and 2005 in the ECS, accompanied by in situ observation data in Daya Bay, confirmed a positive correlation between chl-a concentration and D-SST. These results showed that an increase in D-SST may be found in heavy phytoplankton bloom areas. The present study represents an important step for understanding the influence of phytoplankton on ocean conditions. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) occur frequently in the South China Sea (SCS), causing enormous economic losses in aquaculture. We analyzed historical HAB records during the period from 1980 to 2003 in SCS. We found that HABs-affected areas have expanded and the frequency of HABs varied during this period. The seasonal and annual variations, as well as causative algal species of HABs are different among the four regions. Areas with frequent HABs include the Pearl River Estuary (China), the Manila Bay (the Philippines), the Masinloc Bay (the Philippines), and the western coast of Sabah (Malaysia). HABs occurred frequently during March–May in the northern region of SCS, May–July in the eastern region, July in the western region, and year-round in the southern region. Among the species that cause HABs, Noctiluca scintillans dominated in the northern region, and Pyrodinium bahamense in the southern and eastern regions. Causative species also varied in different years for the entire SCS. Both P. bahamense and N. scintillans were the dominant species during 1980–2003. Some species not previously recorded formed blooms during 1991–2003, including Phaeocystis globosa, Scrippsiella trochoidea, Heterosigma akashiwo, and Mesodinium rubrum. Variations in HABs are related to various regional conditions, such as a reversed monsoon wind in the entire SCS, river discharges in the northern area, upwelling in Vietnam coastal waters during southwest winds and near Malaysia coastal waters during northeast winds, and eutrophication from coastal aquaculture in the Pearl River estuary, Manila Bay, and Masinloc Bay. [ABSTRACT FROM AUTHOR]

Ca2+ overload and reactive oxygen species can injure mitochondria during ischemia and reperfusion. We hypothesized that mitochondrial injury occurs during cardiac resuscitation, causing release of cytochrome c to the cytosol and bloodstream while activating apoptotic pathways. Plasma cytochrome c was measured using reverse-phase HPLC and Western immunoblotting in rats subjected to 4 or 8 mm of untreated ventricular fibrillation and 8 mm of closed-chest resuscitation followed by 240 mm of postresuscitation hemodynamic observation. A sham group served as control. Plasma cytochrome c rose progressively to levels 10-fold higher than in sham rats 240 mm after resuscitation (P < 0.01), despite reversal of whole body ischemia (decreases in arterial lactate). Cytochrome c levels were inversely correlated with left ventricular stroke work (r = -0.40, P = 0.02). Western immunoblotting of left ventricular tissue demonstrated increased levels of 17-kDa cleaved caspase-3 fragments in the cytosol. Plasma cytochrome c was then serially measured in 12 resuscitated rats until the rat died or cytochrome c returned to baseline. In three survivors, cytochrome c rose slightly to ⩽ µg/ml and returned to baseline within 96 h. In nine nonsurvivors, cytochrome c rose progressively to significantly higher maximal levels [4.6 (SD 2.0) vs. 1.6 (SD 0.3) µ/ml, P = 0.029] and at faster rates [0.7 (SD 0.5) vs. 0.1 (SD 0.1) µ·ml-1·h-1, P = 0.046] than in survivors. Plasma cytochrome c may represent a novel in vivo marker of mitochondrial injury after resuscitation from cardiac arrest that relates inversely with survival outcome. [ABSTRACT FROM AUTHOR]

A new kind of amphiphilic derivative of carboxymethylchitosan, a group of (2-hydroxyl-3-butoxyl)propylcarboxymethylchitosans (HBP-CMCHS), has been synthesized, and the surface and aggregate properties have been studied by means of surface tension, surface pressure and fluorescence measurements. HBP-CMCHS can adsorb on the surface to decrease the surface tension of the solution. The adsorption film was quite stable, which can make the relative compressed pressure increase dramatically with the decrease of the surface area. In solution, hydrophobic aggregations were identified by the decrease in the ratio of the fluorescence emission intensity of the first and third pyrene vibronic peaks (I1/I3). Results showed that the aggregation began to form at a concentration similar to that of the polymer transfer to the air–water interface. Aggregate formation of the polymers is a gradually compact process with hydrophobic associations. Increase of DS and addition of NaCl to the HBP-CMCHS solution can make the surface tension decrease, make the aggregation occur at lower concentration, and make the aggregation more hydrophobic. [Copyright &y& Elsevier]

Mitoxantrone (MXT), an anti-tumor antibiotic, shows irreversible electrochemical behavior at a waxed graphite electrode in a 0.05 M Tris–HCl buffer (pH 7.4) solution. The interaction between MXT and calf thymus DNA (ctDNA) in solution has been studied using cyclic voltammetry. An electrochemical equation suitable for examining the binding of irreversibly electroactive molecules to DNA is established. Determination of diffusion coefficients of both free and binding MXT (Df, Db), the binding constant (K) and binding site size (s base pairs per molecule, bp) of MXT with DNA was performed on the basis of the equation. A nonlinear fit analysis of the experimental data yielded: Df=3.76×10−5 cm2 s−1, Db=2.73×10−7 cm2 s−1, K=8.7×109 cm3 mol−1, s=2.8 bp. The results demonstrate that MXT binds tightly to ctDNA and covers three base pairs. The anthraquinone of MXT, which is a planar heterocyclic ring, intercalates between the DNA''s base pairs. The two aminoethylamino side-chains of the drug fit to the major groove reinforce the combination of MXT and DNA. The results show that MXT is a DNA intercalator with a high binding constant compared to those of other anthraquinones. [Copyright &y& Elsevier]

A rapid method for investigation of the interaction of DNA and electroactive ligands based on an electrochemical equation for irreversible processes is presented. The binding constant (K) and the size of binding site (s) are simultaneously obtained from the dependence of the current on the amount of added DNA in voltammetry. A non-intercalative binder (Hoechst 33258) and two DNA-intercalators (mitoxantrone (MXT) and actinomycin D (AMD)) were examined in experiments. It was found that the binding constant of Hoechst 33258, mitoxantrone and actinomycin D, were 2.1×108, 8.9×109 and 9.1×109 cm3 mol−1; and the size of their binding sites were 4, 3 and 8, respectively. The study provides a convenient and sensitive approach for estimating affinity parameters and outlining the interaction between DNA and electroactive targeting compounds. [Copyright &y& Elsevier]

An electrochemical method was used to probe the interaction of actinomycin D (AMD) and calf thymus DNA (ctDNA) in phosphate buffer solution (pH 7.0) at an oxidized waxed graphite electrode. AMD showed a pair of nonsymmetric peaks at −0.51 and 0.19 V in cyclic voltammetry. As a result of reaction with ctDNA, the voltammetric peaks of AMD disappeared. The diffusion coefficient of free AMD (Df=1.9×10−5 cm2 s−1), binding constant (K=7.54×109 cm3 mol−1) and binding site size (s=8.1) of the AMD–DNA complex were obtained simultaneously by nonlinear fit analysis of voltammetric data based on an electrochemical equation, which was derived to examine the interaction of DNA and irreversibly electroactive compounds. The results demonstrate that AMD binds tightly to ctDNA. The AMD phenoxazone ring intercalates between the DNA base pairs. The two side chains of the depsipeptide extend along the minor groove of DNA and cover eight base pairs. The study provides a convenient and sensitive approach to estimate affinity parameters of the interaction between DNA and targeting compounds. [Copyright &y& Elsevier]

Improving the spatial pattern of agricultural systems has become a promising approach for enhancing agricultural productivity and sustainability. However, previous studies have often focused on the influence of natural factors on crop distribution, ignoring factors such as human activities, socio-economic level and ecological environment. This study aims to investigate the influence of natural factors and social environmental drivers on the optimal pattern of multiple crops and evaluate the potential of optimal patterns to enhance agricultural productivity and sustainability. Here, we present a multi-criteria approach integrating natural and social environment system factors and set up three assessment scenarios: crop growth suitability (CGS), crop planting suitability (CPS), and crop planting competitiveness (CPC). Applying this approach to the Shiyang River basin in China as a case study, we assessed the suitability and competitiveness of single crops. To maximize agriculture competitiveness, we optimized the structure of the multi-crop system, and a method was proposed to identify highly suitable intercropping areas using crop competitiveness conflicts. Regional crop water consumption, water productivity, and economic benefits were calculated to analyze the potential for agricultural intensification under different optimization patterns. We found that the weights of four categories factors of location, socio-economic conditions, productivity, and environment protection accounted for 26.9%, 7.5%, 13.7%, and 4.5%, respectively, and the weight of social environmental influence indicators had accounted for about 43.5%, which cannot be ignored. The distribution area above moderate suitability (L2) in the CPS and CPC scenarios was about 7.92% - 30.03% and 6.14% - 26.4% higher than the CGS scenario, respectively. Social environmental factors are important to consider in assessing the suitability of crops. From the spatial structure, three optimization patterns all suggested increasing the planting proportion of wheat and potato in the future. The optimization patterns in CPC scenario could reduce total crop water demand by 91.86 to 175.77 million cubic meters compared with 2020 while showing great potential to improve crop water productivity and net output per cubic meter of water. Furthermore, we offered recommendations for the layouts of common intercropping systems in Northwest China based on the proposed method for identifying high suitability zones. This study emphasizes the importance of considering multiple environments to accurately assess crop suitability and achieve sustainable agricultural. The results could provide useful insights for managing and optimizing diverse planting systems, addressing growing concerns surrounding food and water security in resource-constrained regions. [Display omitted] • Human activities and social environment have not received sufficient attention for their impacts on agricultural patterns. • Proposed a novel approach to crop suitability assessment and structural optimization integrating natural and social systems. • Optimized patterns under the CPC scenario reduced water consumption and improved water productivity and net water benefits. • Findings emphasize the importance of considering human activities and social environmental drivers in agricultural planning. • Crop management based on dual environmental assessments provides a practical solution to promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

Remote sensing technology is widely used to obtain evapotranspiration (ETa), but whether it can distinguish the differences in farmland energy balance components and ETa under different irrigation methods has not been studied. We used Landsat 8 data as the primary dataset to drive the METRIC model and inverted the surface parameters and ETa of the Shiyang River Basin from 2014 to 2018. After improving the METRIC model using Ta obtained by the regression method instead of interpolation to calculate the net radiation flux (Rn), R2 was improved from 0.45 to 0.53, and the RMSE was reduced from 61 W/m2 to 51 W/m2. The ETa estimation results on satellite overpass days performed well, with R2 equal to 0.93 and RMSE equal to 0.48 mm when compared with the Eddy covariance method (EC) observations. Subsequently, the different growth stages and daily average ETa estimates of maize were compared with three observations (water balance, WB; Bowen ratio and energy balance method, BREB; and EC). The daily estimates of ETa correlate well with the observations of BREB (R2BI = 0.82, R2DI = 0.92; RMSEBI = 0.46 mm/day, RMSEDI = 0.32 mm/day) and EC (R2BI = 0.85, R2DI = 0.92; RMSEBI = 0.45 mm/day, RMSEDI = 0.34 mm/day), and the estimation for drip irrigation was found to be better than for border irrigation. The total accuracy of the ETa estimation on the five-year overpass day of maize farmland reached R2 = 0.93 and RMSE = 0.48 mm. With sufficient remote sensing data, the 4-year average ETa of maize was 31 mm lower for DI than for BI, and the mean value of ETa obtained from the three observation methods was 40 mm. The METRIC model can be used to distinguish ETa differences between the two irrigation methods in maize farmlands. [ABSTRACT FROM AUTHOR]

In this study, we analysed the interannual variability of sea surface temperature (SST), sea surface wind (SSW), and sea level anomaly (SLA) in the South China Sea (SCS) during 1985–2016 using monthly reanalysis and satellite datasets. An empirical orthogonal function (EOF) analysis was performed to evaluate the interannual variability of each variable. The warming rate of SST was 0.18 ± 0.26°C decade−1 in the SCS. The first EOF of SST was characterized by basin-wide warming, with the highest anomalies in the northern deep basin. The first temporal coefficient of SST was negatively correlated with the Niño 3.4 index, with a lag of 6 mo. The mean rising rate of SLA was 7.6 cm decade−1, with the greatest trend in the coastal water of Vietnam, which exhibited a similar spatial pattern with the first EOF of SLA. The temporal coefficient of SLA was negatively correlated with that of SST, with a lag of 5 mo. The trend of SSW was around 0.8 m s−1 decade−1 over the SCS. The first EOF of SSW was characterized by an anticyclonic pattern. The temporal coefficient was correlated with that of SST, with a lead of 2 mo. Wavelet coherence was used to investigate the cross-correlation relationship between SST and other variables. SST and SLA had a strong negative correlation in the 8–16-mo (1–1.5 yr) band. The high positive wavelet coherencies between SST and SSW and Niño 3.4 were mainly in the 32–64 mo (3–5 yr) band in the SCS. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) is a malignant tumor that threatens human life and health. The development of a new NSCLC risk assessment model based on electronic medical records has great potential for reducing the risk of cancer recurrence. In this process, machine learning is a powerful method for automatically extracting risk factors and indicating impact weights for NSCLC deaths. However, when the number of samples reaches a certain value, it is difficult for machine learning to improve the prediction accuracy, and it is also challenging to use the characteristic data of subsequent patients effectively. Therefore, this study aimed to build a postoperative survival risk assessment model for patients with NSCLC that updates the model parameters and improves model accuracy based on new patient data. The model perspective was a combination of particle filtering and parameter estimation. To demonstrate the feasibility and further evaluate the performance of our approach, we performed an empirical analysis experiment. The study showed that our method achieved an overall accuracy of 92% and a recall of 71% for deceased patients. Compared with traditional machine learning models, the accuracy of the model estimated by particle filter parameters has been improved by 2%, and the recall rate for dead patients has been improved by 11%. Additionally, this study outcome shows that this method can better utilize subsequent patients' characteristic data, be more relevant to different patients, and help achieve precision medicine. [ABSTRACT FROM AUTHOR]

• PET and ground-based ET 0 estimation are integrated to reflect the spatiotemporal variability and improve ET 0 accuracy. • A distributed interval nonlinear multiobjective programming (DINMP) model is proposed. • Uncertainties, conflicting objectives, spatial information, and marginal benefit are fully considered in DINMP model. • DINMP is applied to a real-world case and the results can contribute to the sustainable development of agriculture. Considering the uncertainties in agricultural system and spatiotemporal variability in evapotranspiration and precipitation, a distributed interval nonlinear multiobjective programming (DINMP) model was developed for optimal allocation of limited irrigation water resources in the middle reaches of Heihe River basin. The meteorological data from meteorological stations were used to estimate reference crop evapotranspiration (ET 0) through FAO56 Penman-Monteith (PM) equation, and then the remote sensing MOD16/PET data were fitted by linear regression model according to the FAO56 PM results. The 95% confidence interval was used to further improve the accuracy of the fitting results. Thus, satellite-based potential evapotranspiration (PET) and ground-based ET 0 estimation were integrated to not only reflect the spatial and temporal variability but also guarantee the accuracy of the ET 0. In the terms of precipitation, spatial interpolation was used to spatial information of precipitation. Based on these spatiotemporal data, a DINMP with three objectives, including maximizing economic benefits and water saving as well as minimizing water shortage of critical growth periods, was formulated, and further solved by fuzzy coordination method. The optimal allocation scheme improves the irrigation water productivity by [0.50, 0.66] kg/m3, and decreases net irrigation water allocation by [0.33, 1.01] ×108 m3. These results show that DINMP can not only consider the uncertainties and multiple objectives in agricultural water management, but also improve the spatial resolution of optimal water allocation strategies. The framework of this study can provide a reference for agricultural water managers in similar areas to obtain more reasonable water allocation schemes. [ABSTRACT FROM AUTHOR]

Crop models are widely used to assist in agricultural management decision-making and water productivity optimization. However, traditional crop models often depend on artificial and specific field management inputs, posing challenges in maintaining crops within a desired stress range. Consequently, the derived optimization schemes from these models become highly uncertain. Moreover, the complexity of the mechanisms involved and the multitude of parameters make it challenging to apply traditional crop models uniformly across various crops and regions. In this study, we have developed a novel crop model called WHCrop (Water-Heat Driven Crop model) that effectively captures, reflects, and controls the impact of various environmental factors (meteorology, topography, soil, and management) on crop growth process. The WHCrop model combines the simulation principles of biomass and yield from the CERES module in the DSSAT model, along with the soil water balance from the AquaCrop model, to estimate the dynamics of crop growth and production processes. Results indicated that WHCrop-based simulations, including canopy cover (CC), daily evapotranspiration (ET), and yield, matched well with ground-based measurements, and were better than the traditional crop model (DSSAT and AquaCrop) at both field and regional scales, especially under deficient irrigation conditions. Besides capturing the key variables associated with crop growth, WHCrop model could reproduce the adaptive response of these various to regional-scale temperature changes. Notably, the WHCrop model could effectively minimize uncertainties resulting from individual environmental change, thanks its incorporation of dynamic response mechanisms for crop growth under stress factors. Overall, the novel and informative WHCrop model offers some advantages over traditional crop models since it allows for optimal decision making to be derived from the randomly different inputs. As a result, the WHCrop model proves instrumental in assisting decision-makers in formulating critical water allocation strategies and developing effective management recommendations to enhance regional agricultural water productivity. • WHCrop model simulates crop growth dynamics using water and heat drive. • WHCrop model enables randomly varied inputs for optimal decision-making. • WHCrop model simulates daily crop growth responses to water stress and climate changes. • WHCrop model needs fewer and readily available input data than traditional crop model. • WHCrop outperformed traditional crop models in simulating crop growth across scales. [ABSTRACT FROM AUTHOR]

Atmospheric longwave downward radiation (Ld) is one of the significant components of net radiation (Rn), and it drives several essential ecosystem processes. Ld can be estimated with simple empirical methods using atmospheric emissivity (εa) submodels. In this study, eight global models for εa were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the Rn estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert's equation coefficient should not be considered a constant value for use in εa estimation, nor in time or location. [ABSTRACT FROM AUTHOR]

There is an urgent need to ensure regional food security and increase irrigation water productivity in response to water shortages in arid and semi-arid regions. Previous studies of the optimal allocation of irrigation water did not consider simultaneously optimizing across multiple crops or at different growth stages. This paper describes the development of an irrigation water optimization model that uses a crop water allocation priority (CWAP) model. The CWAP value was determined by quantifying the changes in three indicators: yield, economic benefits, and irrigation water productivity. Maximum yield, maximum economic benefits, and minimum irrigation shortage (at the critical crop and growth stage) were used as the objective functions of a non-linear multi-objective optimization model. The largest irrigation district in the northern arid area of China, Hetao Irrigation District (HID), was chosen to prototype this model. The optimization results, using CWAP, showed that yield, economic benefits, irrigation water productivity, and water productivity could be increased, respectively, by up to 13.38%, 13.40%, 2.30%, and 6.29%, for most crops when compared with optimization results without CWAP. Comparison of the optimized net irrigation quantities with the actual net irrigation quantities showed that optimization reduced water usage by up to 60.77% for wheat, 51.24% for corn, and 63.59% for sunflower. Blue water utilization under optimal irrigation conditions decreased by 1.12% for wheat, 2.91% for corn, and 9.91% for sunflower, compared with those in actual irrigation scenario. This method of optimizing irrigation water allocation in arid areas using CWAP provides decision-makers with accurate water-saving irrigation protocols that will reduce demand for water resources and promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

Background: The progression of atrial fibrillation (AF) from paroxysmal to persistent forms remains a major clinical challenge. Abnormal sarcoplasmic reticulum (SR) Ca(2+) leak via the ryanodine receptor type 2 (RyR2) has been observed as a source of ectopic activity in various AF models. However, its potential role in progression to long-lasting spontaneous AF (sAF) has never been tested. This study was designed to test the hypothesis that enhanced RyR2-mediated Ca(2+) release underlies the development of a substrate for sAF and to elucidate the underlying mechanisms.Methods and Results: CREM-IbΔC-X transgenic (CREM) mice developed age-dependent progression from spontaneous atrial ectopy to paroxysmal and eventually long-lasting AF. The development of sAF in CREM mice was preceded by enhanced diastolic Ca(2+) release, atrial enlargement, and marked conduction abnormalities. Genetic inhibition of Ca(2+)/calmodulin-dependent protein kinase II-mediated RyR2-S2814 phosphorylation in CREM mice normalized open probability of RyR2 channels and SR Ca(2+) release, delayed the development of spontaneous atrial ectopy, fully prevented sAF, suppressed atrial dilation, and forestalled atrial conduction abnormalities. Hyperactive RyR2 channels directly stimulated the Ca(2+)-dependent hypertrophic pathway nuclear factor of activated T cell/Rcan1-4, suggesting a role for the nuclear factor of activated T cell/Rcan1-4 system in the development of a substrate for long-lasting AF in CREM mice.Conclusions: RyR2-mediated SR Ca(2+) leak directly underlies the development of a substrate for sAF in CREM mice, the first demonstration of a molecular mechanism underlying AF progression and sAF substrate development in an experimental model. Our work demonstrates that the role of abnormal diastolic Ca(2+) release in AF may not be restricted to the generation of atrial ectopy but extends to the development of atrial remodeling underlying the AF substrate. [ABSTRACT FROM AUTHOR]

[Display omitted] • Classical optimal planting pattern (COPP) can improve regional water productivity. • The first assessment regarding the impact of COPP on food-energy-water-carbon nexus. • COPP can decrease carbon neutrality capacity by 13.09% in China's major arid area. • Need to redefine "optimum" planting pattern under the context of global warming. Global warming, water scarcity and limited land resources are the most challenging problems facing agriculture to ensure food security for the expected 9 billion people in 2050. To solve these problems, the classical optimal planting pattern, based on crop suitability evaluation method, is often adopted to reallocate water and land resources. However, whether or not the classical optimal planting pattern, which only considers environmental conditions in crop suitability evaluation, is beneficial to the regional carbon neutrality goal and saves water and energy resources has rarely been explored. Here, China's major arid food production area, the middle reaches of Heihe River Basin, is chosen as the demonstration to explore this issue. The classical optimal planting pattern obtained by crop suitability evaluation is compared with current planting in terms of planting distribution, carbon sequestration, energy consumption and water productivity from 2002 to 2016. Interestingly, the results indicate that optimal planting would reduce the regional net carbon sequestration capacity by up to 13.09% and increase regional carbon emissions by up to 22%, which is harmful to reach the commitment of carbon neutrality goal in China. Contrary, optimal crop planting pattern can increase regional water productivity by 1.74–32.59% and economic benefits by 1.52–30.55% while having little impact on energy consumption and water consumption. Considering the contradictions effects of classical optimal planting pattern on the food-energy-water-carbon nexus, we strongly recommend redefining the "optimal" in crop planting management by taking impacts on carbon into consideration to alleviate the crisis of global warming. [ABSTRACT FROM AUTHOR]

Drip irrigation combined with film mulching significantly improved water saving and agricultural efficiency in arid and semi-arid regions. However, the impact of various irrigation technical parameters under plastic film-mulched (PM) drip irrigation on water consumption and maize yield (Zea mays L.) for seed production is still unclear. Field experiments were conducted between 2016 and 2018 in Northwest China to investigate the effects of irrigation technical parameters (dripper discharge and irrigation interval) on biomass, grain yield, water, and nitrogen (N) use efficiency of the PM-maize for seed production. Four dripper discharges (1.38 L h−1, 2.0 L h−1, 2.5 L h−1, 3.0 L h−1) and five irrigation intervals (6 days, 8 days, 10 days, 12 days, 14 days) were selected. The normalized yield was used to analyze the effect of different treatments on the yield to eliminate the differences caused by uncontrollable factors, such as precipitation and temperature between different years. The results indicated a quadratic function among the final aboveground biomass, grain yield of maize for seed production, and irrigation intervals, with the highest value observed at 8 days irrigation interval. Both yield and nitrogen use efficiency measured as partial factor productivity of nitrogen (PFPN) decreased rapidly as the irrigation interval exceeded 10 days. When the irrigation interval increased from 10 to 14 days, the relative grain yield decreased between 6.5 and 16.0%, while the PFPN decreased between 1.1 and 99.2 kg kg−1. Crop evapotranspiration (ET) initially decreased and then increased as the irrigation interval increased. The water productivity (WPY-ET) was the highest at the irrigation interval of 8 days. The PFPN increased between 6.6 and 42.8 kg kg−1 at the dripper discharge of 3.0 L h−1 when compared with dripper discharge of 2.5 L h−1. The study showed an optimal dripper discharge–irrigation interval combination for maximizing water-resources utilization and yield increase. When biomass, grain yield, ET, and WPY-ET are considered simultaneously, the most suitable irrigation technical parameters of maize for seed production in Northwest China are the combination of 2.5 L h−1 and 8 days. Furthermore, a combination of 3.0 L h−1 and 8 days is more conducive to reducing fertilizer costs. [ABSTRACT FROM AUTHOR]

Ocean acidification, a consequence of the ocean absorbing about a third of the anthropogenic carbon dioxide (CO2) emitted into the atmosphere, is poised to affect biogeochemical cycles and the seawater chemical system. Traditional research methods, such as field and in situ sampling, are precise and reliable, but are inherently limited in spatial and temporal coverage and resolution. This article summarizes remotely sensed products, including air-sea CO2 fluxes, total alkalinity, suspended calcite (particulate inorganic carbon), particulate organic carbon and calcification rates, which can be used to observe ocean acidification indirectly. Confounding factors and limitations of algorithms are major sources of errors. This article also discusses remote-sensing algorithms and satellite technology developments. Remote sensing, considering its great advantages and successful applications in climate change, will be an important tool in future studies of ocean acidification. [ABSTRACT FROM AUTHOR]

Abstract: Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology. [Copyright &y& Elsevier]

Spatial and temporal variability of soil properties, irrigation schedules, and fertilization management play an important role in crop growth and yield in agricultural systems. However, how to improve and accurately predict crop yield in different management zones (MZs) within a large-scale field are important but rarely discussed. In this study, coefficient of variation, linear correlations, partial least squares discriminant analysis and quantile regression were used to quantify relationships between crop and soil properties, and determine key explanatory factors of yield, and to identify suitable ways to improve crop yield among MZs. At the temporal scale, coefficients of variation of crop growth parameters (LAI and biomass), and correlations of crop growth parameters with soil water content and available nitrogen varied during crop growth stages in MZs across years. Crop–soil correlations varied with time and were most pronounced in heading and filling stages when LAI and biomass approached maximum values, respectively. At the spatial scale, 22 explanatory factors belonging to four categories: soil physical properties, initial soil properties, soil water and nitrogen dynamics, and topography were compared. Results showed that among the four categories, initial soil properties had the greatest influence on yield across the whole field, whereas soil water and nitrogen dynamics were the most influential for individual MZs. Key explanatory factors of yield varied across MZs in 2017 and 2018. Although key explanatory factors varied across years within a MZ, some remained unchanged, especially soil physical properties. Based on the quantile regression results, the same key explanatory factors might appear in MZs, but the reference ranges were different. For more sustainable and efficient agricultural production, distributed integrated management, including soil amelioration before sowing, and irrigation and N fertilization scheduling during the crop growth period should be implemented in MZs based on the spatial-temporal variability of soil properties. • Spatial variability of crop growth parameters varies during growth stages in management zones (MZs). • Correlations of crop growth parameters with soil and nitrogen dynamics vary in growth stages. • The relative contributions of explanatory factors in MZs are different from that across the whole field. • The combination of partial least squares discriminant analysis and quantile regression can determine the reference ranges of key explanatory factors in MZs. [ABSTRACT FROM AUTHOR]

P1, P3, P5 are the irrigation intervals at 6, 10, 14 days, respectively. P5D are treatments with an irrigation interval of P5 The original article has been corrected. [Extracted from the article]

Variability of soil properties within large-scale fields not only exists in the horizontal domain, but also in the vertical direction, causing spatial variability in yield. Three yield zones were delineated based on measured yield in 2017 and 2018 within a large field in northwest China. The Soil Water Heat Carbon Nitrogen Simulator (WHCNS) model was calibrated and used to simulate yield, nitrogen uptake (N u), water use efficiency (WUE), fertilizer N (nitrogen) use efficiency (FNUE), deep percolation (DP), nitrate leaching (NL) and residual nitrate (RN) at each sampling point in different yield zones. Based on the simulations, there were significant differences in N u , WUE, FNUE, DP, NL and RN in 0–100 cm and 100–160 cm soil layers among the three yield zones. DP, NL and RN in the layers were strongly determined by the interaction of zone and year (p < 0.05), thus yielding consistent patterns mainly determined by soil properties and meteorological factors. The modelled ranges of DP, NL, and RN (0–160 cm) were 25–119 mm, 15–94 kg ha−1, and 178–476 kg·ha−1 respectively, across the field. Soil texture in the maize main root zone (0–100 cm) has a great influence on yield and N u , and in the 100–160 cm layer upon DP and NL. RN was abundant after harvest and should be taken into account to determine the nitrogen fertilization demand for the following crop. The study showed that the process of delineating zones can be based on historical yield, making it feasibly easier than mapping soil properties. In view of the fact that there were large losses of water and nitrogen with uniform irrigation and fertilization management, the effects of vertically variable soil properties should be considered in future precision agriculture research, to achieve higher economic benefits and utilization efficiency. Unlabelled Image • Uniform management with excessive irrigation and fertilization caused a high risk of deep percolation and N leaching. • Deep percolation and N leaching were significantly different between yield zones within a field. • Residual N should be considered in fertilization management. • Precise irrigation and fertilization management could significantly reduce loss of water and nitrogen in northwest China. [ABSTRACT FROM AUTHOR]

Oil spills in oceans have substantial influence on marine ecosystems. This study investigates 21 oil spills in the world. Analyzing Chlorophyll-a (Chl-a) from Moderate Resolution Imaging Spectroradiomerer (MODIS) data after Penglai oil spills on 4 June 2011, found a bloom with peak value of Chl-a (13.66 mg m−3) spread over an area of 800 km2 during 18–25 June 2011, and a pronounced increase in the monthly Chl-a concentration (6.40 mg m−3) on June 2012 in the Bohai Sea. Out of the 21 oil spills, 14 blooms were observed, while 11 blooms associated with oil spills in the time interval of 3–10 months. In total, about 75% blooms occurred during June–August. Among all 14 blooms, 72% appeared when temperature was warm (20–30 °C), 7% appeared when temperature was low (10–20 °C), and the remaining 21% occurred when temperature was lower than 10 °C. This research concludes that the odds of a phytoplankton bloom after an oil spillage are higher at the time of higher temperature (>20 °C). The short-term impact of the oil spills on ecosystem could mainly depend on the quantity and composition of oil, while the long-term impact of the oil spills on ecosystem could be related to biodegradation of microorganisms. [ABSTRACT FROM AUTHOR]

When planning agricultural production, planting area and water allocation are two major subjects faced by decision makers. In this study, a framework integrated Nerlove supply response model (Nerlove model) and interval fuzzy credibility-constraint bi-level programming (IFCBP) model is developed for planning the agricultural production in arid and semi-arid regions. Through Nerlove model, the planning process of crop planting area was described as an economic problem for forecasting farmers' behavior rather than an optimization problem for allocating farmland resources, and the relationship between crop planting area and market price can be obtained and further provide credible future crop planting area information. The IFCBP model can not only deal with uncertainties presented as interval and fuzzy numbers but also examine the credibility of the constraints and handle tradeoffs between two-level decision makers. To solve the IFCBP model, a solution method based on the interval interactive algorithm and credibility-cut method is proposed. Then, to verify the validity of the developed framework and solving method for agricultural production planning, they were applied to a real-case in the middle reaches of the Heihe River basin, northwest China. The forecasting results obtained from Nerlove model have better performance in predicting the future planting area of corn and vegetable than wheat, indicating that wheat plays a more vulnerable role in the decision-making process of planting area owing to its higher substitutability. The results show that the proposed framework can tackle two-level decision makers' concerns under uncertainties featured as inexact and fuzzy numbers, which can help regional managers plan future resources effectively. Furthermore, a comparison was made between IFCBP and two corresponding single-level models in this study. The comparison indicates that the developed model provides an effective tradeoff between two decision makers from different decision-making levels in IFCBP. The developed framework provides managers an effective way to plan agricultural production in arid and semi-arid regions, and the developed model and related thinking may help solve similar problems. • An agricultural production planning approach based on interval fuzzy credibility-constrained bi-level programming (IFCBP) and Nerlove supply response theory. • Both objective and subject factors are considered through the entropy method and analytic hierarchy process method separately. • This approach is applied to a case study for planning crop planting area and irrigation-water allocation. • The results can support water managers formulate more efficient agricultural production planning strategy. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel regional grid-scale crop dynamic layout optimization model was constructed. • Multiyear crop layout plan was obtained by considering inter-annual impacts. • Spatial variance of parameters and neighbourhood effects of crop units were noted. • Overall government planning and farmers' crop rotation behaviour were regarded. • Stakeholders and their multi-objective planting preferences were balanced. Rapid population growth has led to an increasing demand for food, accompanied by an increase in the resources invested in producing food, and the extensive food production practices have placed a huge burden on the environment. There is an urgent desire of need to find a sustainable model of food production. Therefore, this study attempted to develop a dynamic regional grid-scale crop layout model (ABCAMODP-Crop) combining agent-based model, multi-objective programming, dynamic programming and cellular automata model to promote more sustainable food production from a supply-side perspective. The model can: (1) take into account the planting preferences and practical behaviours of government and farmer as stakeholders in crop layout; (2) further weigh the conflicts among the various objectives that stakeholders are concerned with from resource, environmental, nutritional and economic dimensions; (3) consider the impact of the previous year's crop layout on the next year's crop placement; and (4) obtain grid-scale accurate crop layout solutions by considering the spatial variability of optimization parameters and the neighborhood effects of crop layout cells. The model was applied to the Shiyang River Basin in China to verify its usefulness. Over the entire planning period, crop layout schemes optimized with the objective of integrating irrigation water productivity, environmental impact, nutrient availability and economic benefits have higher comprehensive benefits than the original scheme, with an increase in average irrigation water productivity per unit area of 14.55%, an increase in total yield of 14.45%, an increase in total carbohydrate availability of 7.39%, an increase in total calcium availability of 18.74%, an increase in total net carbon sequestration of 8.05%, an increase in total net benefit of 20.08%. The model developed allows for a holistic view of crop layout and guides decision-makers in a rational distribution of regional crops, thus promoting more sustainable food production. It can equally be extended to other regions as a generic modelling framework. [ABSTRACT FROM AUTHOR]

Background. Renal fibrosis is a common outcome of all pathological types of chronic kidney disease (CKD). However, the noninvasive detection of renal fibrosis remains a challenge. Methods. We collected urine samples from 154 biopsy-proven IgA nephropathy (IgAN) patients and 61 healthy controls. The expression of mTOR was measured and the correlation with renal function parameter and pathological indicators. The receiver operating characteristic (ROC) curve for the diagnosis of IgAN and renal fibrosis was calculated. Results. The urinary mammalian target of rapamycin (mTOR) expression was decreased in IgAN patients. The expression of mTOR was correlated with serum creatinine, blood urea nitrogen, estimated glomerular filtration rate, 24 h proteinuria, and cystatin C. Further, the urinary mTOR expression was significantly decreased in severe renal fibrosis patients compared with mild or moderate renal fibrosis patients. Urinary mTOR expression was correlated with score of tubulointerstitial fibrosis (TIF) and score of glomerular sclerosis. The ROC curve showed that mTOR can diagnose IgAN at a cut-off value of 0.930 with the sensitivity of 90.2% and specificity of 73.8% and renal fibrosis at a cut-off value of 0.301 with the sensitivity of 71.7% and specificity of 64.8%. Conclusion. Urinary mTOR mRNA expression was a potential biomarker for diagnosis of IgAN and renal fibrosis in IgAN patients. [ABSTRACT FROM AUTHOR]

A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2–4 years during 2003–2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3–5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale. [ABSTRACT FROM AUTHOR]

This study investigates the processes of occasional sea surface temperature (SST) fronts and their impacts on chlorophyll-a concentration (chl-a) in the South China Sea (SCS), based on satellite remote sensing and in situ observations in 2009-2013. The SST fronts were detected by an entropy-based edge detection algorithm method from satellite-derived SST images with a 0.011° grid size. Three offshore SST front case studies (S1, S2 and S3) at the peripheries of eddies in the northern SCS were studied. In case S1 in September 2013, two SST fronts were detected with gradient magnitudes (GMs) greater than 0.06°C km-1 in the cyclonic eddy and 0.08°C km-1 in the periphery waters, and the fronts only existed for one and two days, respectively. After three and seven days, the high chl-a was found in the strong SST front waters which were about 51 and 54% higher than the concentration in the surrounding waters. The depth of the maximum chl-a elevated from the subsurface (50 m) to the surface. In case S2 in August 2013, two SST fronts were detected at the periphery of an anti-cyclonic eddy with GM stronger than 0.06°C km-1 and only existed for one day. After two days, the chl-a in the SST front waters was about 40% higher than the levels in the surrounding waters. In case S3 in June 2009, the GM of the eddy-feature SST front was stronger than 0.12°C km-1 and existed for three days, which was generated by tropical cyclone Linfa. The chl-a in the eddy-feature phytoplankton bloom was 6 times higher than in the surrounding waters. The results show that, in general, occasional offshore SST fronts at peripheries of eddies have stronger influence on surface chl-a, comparing to those seasonal coastal and permanent offshore SST fronts, via ‘Wind Pump’ effects. [ABSTRACT FROM AUTHOR]

Rapidly growing population has led to increasing food demands and greater food system pressure. It is urged to find a way to improve the sustainability of food system. Therefore, this study attempted to develop a regional crop layout model (CAMOO-Crop) combining cellular automata model with multi-objective optimization model to improve food system sustainability. The model can (1) consider the carbon sequestration of farmland vegetation, carbon emissions from production inputs, and human demand for crop nutrient supply, (2) balance the trade-offs among multiple dimensions of resource, environment, economy and nutrition in the crop food system, (3) obtain grid-scale crop space layout schemes considering special distribution. The model was applied to the Shiyang River Basin in China to verify its effectiveness. After optimization, crop water productivity per unit area increased by 2.12%, carbon sequestration increased by 0.32%, carbon emission decreased by 1.87%, the net benefit increased by 2.66%, carbohydrate supply decreased by 0.19%, calcium supply increased by 5.74%. In addition, a cropland-scale food system sustainability evaluation index system was constructed, and the Food System Sustainability Index (FSSI) and Coupling Coordination Degree (CCD) were introduced to evaluate the sustainability of food systems under different crop layout scenarios. The results showed that compared with single-objective model scenario and the status quo, CAMOO-Crop model performed best, with FSSI from 0.70 to 0.91; CCD from 0.83 to 0.95. The developed model can promote sustainable development of the regional food system and guide decision-makers to rationally distribute regional crops. [Display omitted] • A novel crop layout framework was developed to improve food system sustainability. • A model for coupling cellular automata and multi-objective programming was provided. • Trade-offs between resource, environment, economy and nutrition were realized. • A farmland scale food system sustainability evaluation system was constructed. • Layout options were developed for decision-makers considering special distribution. [ABSTRACT FROM AUTHOR]

Pharmacological therapies for cardiovascular diseases are limited by short-term pharmacokinetics and extra-cardiac adverse effects. Improving delivery selectivity specifically to the heart, wherein therapeutic drug levels can be maintained over time, is highly desirable. Nanoparticle (NP)-based pericardial drug delivery could provide a strategy to concentrate therapeutics within a unique, cardiac-restricted compartment to allow sustained drug penetration into the myocardium. Our objective was to explore the kinetics of myocardial penetration and retention after pericardial NP drug delivery. Fluorescently-tagged poly(lactic- co -glycolic acid) (PLGA) NPs were loaded with BODIPY, a fluorophore, and percutaneously administered into the pericardium via subxiphoid puncture in rabbits. At distinct timepoints hearts were examined for presence of NPs and BODIPY. PLGA NPs were found non-uniformly distributed on the epicardium following pericardial administration, displaying a half-life of ~ 2.5 days in the heart. While NPs were mostly confined to epicardial layers, BODIPY was capable of penetrating into the myocardium, resulting in a transmural gradient. The distinct architecture and physiology of the different regions of the heart influenced BODIPY distribution, with fluorophore penetrating more readily into atria than ventricles. BODIPY proved to have a long-term presence within the heart, with a half-life of ~ 7 days. Our findings demonstrate the potential of utilizing the pericardial space as a sustained drug-eluting reservoir through the application of nanoparticle-based drug delivery, opening several exciting avenues for selective and prolonged cardiac therapeutics. [ABSTRACT FROM AUTHOR]

Ineffective control over industrialization and urbanization has exposed the shortcomings of land resource management. The overexploitation of limited high-quality land resources is exacerbating the global ecological and food crisis. There is an urgent need to change from "expansion" to "intensification" in land resource utilization. Taking the northwest oasis region of China as a case study, a spatio-temporal optimization model of land use and land cover (LULC) based on dynamic competitiveness evaluation was constructed, and four simulation scenarios, including natural growth without policy intervention (SN), economic priority (SE), food security (SF) and ecological protection (SP), were set up to evaluate and predict the contribution of land intensification to regional carbon neutrality. The results show that the total carbon emissions in the study region will rise sharply by 157.56% in 2030 compared with 2020 without policy intervention (SN). In contrast, all three land intensification scenarios have great emission reduction potential: total regional carbon emissions can be reduced by 21.15% (SE), 22.78% (SF), and 51.72% (SP), respectively, compared with SN. Notably, the implementation of the ecological protection policy (SP) in the region will result in an average carbon emission per unit of GDP of 0.57 t/104 yuan in 2030, which is 25.44% lower than in 2020, implying a downward trend in carbon emissions per GDP between 2020 and 2030, and SP scenario will see the region achieve carbon peaking before 2030. The results can provide novelty methods and policy opinions for optimal land management from the perspective of a low-carbon city. [ABSTRACT FROM AUTHOR]

It is urgent to determine the crop critical irrigation period and the priority of crop water irrigation in arid and semi-arid regions to cope with agricultural water shortage. In this study, a method combining Agricultural Production Systems Simulator (APSIM) crop model with grey relational analysis was proposed to determine the irrigation priority of wheat, maize, and sunflower in the irrigation water distribution to ensure food security, and applied to the Hetao Irrigation District (HID) in China. Crop irrigation priority was determined by crop yield, water supply demand ratio (SDR), and water productivity (WP). The maximum yield, maximum water productivity and minimum water stress (crop growth stage) were evaluated. The obtained results indicate that: (1) When the irrigation scenario was 100%, the critical irrigation period for wheat was the first 10 days after sowing and 40–61 days after sowing; The critical irrigation priority for maize was 20–30 days after sowing and 61–81 days after sowing; And the critical irrigation priority for sunflower was 30–61 days after sowing. (2) In early May, irrigation priority was wheat priority to maize, while maize was a priority to wheat in mid to late May. In June, sunflower priority to wheat and maize irrigation. From early to middle July, irrigation priority to maize, and from late July to late August, sunflower water irrigation priority to maize. The method of to identify irrigation priority and crop priority to provide irrigation decision for allocating agriculture water resources. [Display omitted] • A novel method based on crop model and grey relational analysis is proposed. • The best irrigation time after sowing wheat, maize, and sunflower is identified. • Priority for intercrop water irrigation at the same time is proposed. • The effects of water stress, water productivity, and yield is considered. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions from irrigation and nitrogen fertilizer applications in agriculture are attracting increasing attention, and the development of low-carbon agriculture has become an inevitable trend in the implementation of carbon neutrality. However, the optimization of water and nitrogen in crop planting still lacks precise management at the grid scale. From the perspective of agricultural carbon emission reduction, this study proposes a precise regional water and nitrogen management approach that can optimize irrigation and nitrogen fertilizer application in space and time. In this study, a coupled crop water-nitrogen production function model was constructed by analyzing the response relationship between nitrogen and water on crop yield. The verification results showed that the model had superior fitting accuracy, with R2 and NRMSE values of 0.88, 10.50%, 0.8 and 7.76% for maize and wheat, respectively. After combining the water-nitrogen coupling function with the cellular automaton model, a spatiotemporal optimization model was developed to realize grid-scale regional water and nitrogen management. The case study showed that the optimized irrigation and nitrogen scheme could save 2.73% of agricultural water, decrease nitrogen fertilizer use by 9.69%, and reduce carbon emissions by 4.39%. Correlation analysis of irrigation and fertilization can provide accurate guidance for regional irrigation and fertilization systems. Therefore, considering the contribution of agricultural "carbon reduction sources" to carbon neutrality, water saving, and nitrogen reduction should be considered in low-carbon agricultural development, which is conducive to the green and sustainable development of agriculture. [Display omitted] • Established the response relationship between water-nitrogen and yield. • A grid-scale water-nitrogen coupling optimization model is developed. • Realized the spatiotemporal optimization of crop water and nitrogen. • Maintaining crop yield while water-saving and nitrogen-reducing. • Provided irrigation and nitrogen fertilization solutions for low carbon emission. [ABSTRACT FROM AUTHOR]

The pressures of frequent extreme weather, water shortages and increasing food demand pose a continued challenge of maintaining the sustainable development of irrigated agricultural systems. Although rational arable land management is fundamental to alleviating these pressures, the relationship between cropping patterns and irrigation sustainability is understudied. Using the Hexi Corridor as an example, a maximum entropy machine learning model was used to determine the optimal cropping pattern based on crop suitability and to explore the impact mechanism of the optimal cropping pattern on the irrigation sustainability index (SI) from the perspective of reliability, resilience, and vulnerability. An optimal cropping pattern was conducive to sustainable irrigation and reduced irrigation water use by 21.03% from 1960 s to 2010 s with no continued agricultural expansion. Thus, the challenges of food security and sustainability for similar regions, and globally, can be met but will require major changes in cropping planning and management. [Display omitted] • Crop suitability is an important basis for determining optimal cropping patterns. • Irrigation sustainability is assessed under optimal cropping patterns. • Adjusting the cropping pattern is an effective way to alleviate water scarcity. • Sustainable irrigation development needs more attention. [ABSTRACT FROM AUTHOR]

The orientation relationships between Cr precipitates and matrix in a Cu–Cr–Zr alloy with various aged states were investigated by transmission electron microscopy and High-resolution transmission electron microscopy, and the crystallographic transformations of orientation relationships were also analyzed by stereographic projection and discussed. Four kinds of orientation relationships were detected in the precipitation process of Cu–Cr–Zr alloy, and coexistence of Cr precipitates with Nishiyama-Wassermann relationship and Pitsch relationship was found in the peak-aged Cu–Cr–Zr alloy. The occurrence for cube-on-cube and Pitsch relationship in Cu–Cr–Zr alloy was thought to be caused by the retardation of additions and heterogeneous nucleation of Cr precipitates on dislocations respectively. Transformations of orientation relationships were observed during precipitation and the crystallographic rotation pathways of the transformations were represented by stereographic projection. The interrelationships of various orientation relationships were established by Bain strain and crystal rotation in the Cu–Cr–Zr alloy of this study. • Four kinds of ORs were detected during precipitation of Cu–Cr–Zr alloy. • Coexistence of N–W and Pitsch orientation was found in peak-aged Cu–Cr–Zr alloy. • Formation of Pitsch relationship may be related to heterogeneous nucleation. • Rotation pathways of ORs transformation are represented by stereographic projection. • Interrelationships of various ORs are established by Bain strain and crystal rotation. [ABSTRACT FROM AUTHOR]

Abstract: It is well known that tropical cyclones can cause upwelling, decrease of sea surface temperature, increase of chlorophyll-a (Chl-a) concentration and enhancement of primary production. But little is known about the response of dissolved oxygen (DO) concentration to a typhoon in the open ocean. This paper investigates the impact of a typhoon on DO concentration and related ecological parameters using in situ and remote sensing data. The in situ data were collected 1week after the passage of the super-typhoon Nanmadol in the northern South China Sea in 2011. An increase in DO concentration, accompanied by a decrease in water temperature and an increase in salinity and Chl-a concentration, was measured at sampling stations close to the typhoon track. At these stations, maximum DO concentration was found at a depth of around 5m and maximum Chl-a concentration at depths between 50 and 75m. The layer of high DO concentration extends from the surface to a depth of 35m and the concentrations stay almost constant down to this depth. Due to the passage of the typhoon, also a large sea level anomaly (21.6cm) and a high value of Ekman pumping velocity (4.0×10−4 ms−1) are observed, indicating upwelling phenomenon. At the same time, also intrusion of Kuroshio waters in the form of a loop current into the South China Sea (SCS) was observed. We attribute the increase of DO concentration after the passage of the typhoon to three effects: (1) entrainment of oxygen from the air into the upper water layer and strong vertical mixing of the water body due to the typhoon winds, (2) upwelling of cold nutrient-rich water which stimulates photosynthesis of phytoplankton and thus the generation of oxygen, which also increases the DO concentration due to cold water since the solubility of oxygen increase with decreasing water temperature, and, possibly, (3) transport of DO enriched waters from the Western Pacific to the SCS via the intrusion of Kuroshio waters. [Copyright &y& Elsevier]

Highlights: [•] An adjusted SW (MSW) model was proposed after considering mulching effect on ET. [•] The original SW model overestimated maize ET significantly over the whole season. [•] PM model performed well when canopy fully covered the substrate. [•] MSW model can simulate ET and Es well under film mulch without non-water stress. [ABSTRACT FROM AUTHOR]

Abstract: Background: Prognosis of patients with gastric cancer (GC) is generally poor due to the lack of non-invasive tools for GC detection. The purpose of present study was to identify a serum microRNA (miRNA) expression profile that can serve as a novel diagnostic biomarker for GC detection and to assess its clinical applications in monitoring disease progression. Methods: Serum samples were taken from 164 GC patients and 127 age- and gender-matched tumour-free controls. An initial screening of miRNA expression by Solexa sequencing was performed using serum samples pooled from 20 patients and 20 controls, respectively. Differential expression was validated using hydrolysis probe-based stem-loop quantitative reverse transcription polymerase chain reaction (qRT-PCR) in individuals samples, the samples were arranged in two phases. Results: The Solexa sequencing results demonstrated that 19 serum miRNAs were markedly upregulated in the GC patients compared to the controls. The qRT-PCR analysis further identified a profile of five serum miRNAs (miR-1, miR-20a, miR-27a, miR-34 and miR-423-5p) as a biomarker for GC detection. The analysis results showed that the expression level of five serum miRNAs was correlated to tumour stage. The areas under the receiver operating characteristic (ROC) curve of this five-serum miRNA signature were 0.879 (95% confidence interval (CI) 0.822–0.936) and 0.831 (95% CI 0.767–0.898) for the two sets of serum samples, respectively, markedly higher than those of the biomarkers carcinoembryonic antigen (CEA) (0.503) and carbohydrate antigen 19-9 (CA19-9) (0.600). Conclusions: We identified five-miRNA signature for GC diagnosis by genome-wide serum miRNA expression profiling. Expression levels of this serum miRNA-based biomarker also indicate tumour progression stages. [Copyright &y& Elsevier]

A trial fibrillation (AF), the most common human cardiac arrhythmia, is associated with abnormal intracellular Ca2+ handling. Diastolic Ca2+ release from the sarcoplasmic reticulum via "leaky" ryanodine receptors (RyR2s) is hypothesized to contribute to arrhythmogenesis in AF, but the molecular mechanisms are incompletely understood. Here, we have shown that mice with a genetic gain-of-function defect in Ryr2 (which we termed Ryr2R176Q/+ mice) did not exhibit spontaneous AF but that rapid atrial pacing unmasked an increased vulnerability to AF in these mice compared with wild-type mice. Rapid atrial pacing resulted in increased Ca2+/calmodulin-dependent protein kinase II (CaMKII) phosphorylation of RyR2, while both pharmacologic and genetic inhibition of CaMKII prevented AF inducibility in Ryr2R176Q/+ mice. This result suggests that AF requires both an arrhythmogenic substrate (e.g., RyR2 mutation) and enhanced CaMKII activity. Increased CaMKII phosphorylation of RyR2 was observed in atrial biopsies from mice with atrial enlargement and spontaneous AF, goats with lone AF, and patients with chronic AF. Genetic inhibition of CaMKII phosphorylation of RyR2 in Ryr2S2814A knockin mice reduced AF inducibility in a vagotonic AF model. Together, these findings suggest that increased RyR2-dependent Ca2+ leakage due to enhanced CaMKII activity is an important downstream effect of CaMKII in individuals susceptible to AF induction. [ABSTRACT FROM AUTHOR]