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Inorganic salts usually demonstrate simple phasal behaviors in dilute aqueous solution mainly involving soluble (homogeneous) and insoluble (macrophase separation) scenarios. Herein, we report the discovery of complex phase behavior involving multiple phase transitions of clear solution – macrophase separation – gelation – solution – macrophase separation in the dilute aqueous solutions of a structurally well-defined molecular cluster [Mo7O24]6− macroanions with the continuous addition of Fe3+. No chemical reaction was involved. The transitions are closely related to the strong electrostatic interaction between [Mo7O24]6− and their Fe3+ counterions, the counterion-mediated attraction and the consequent charge inversion, leading to the formation of linear/branched supramolecular structures, as confirmed by experimental results and molecular dynamics simulations. The rich phase behavior demonstrated by the inorganic cluster [Mo7O24]6− expands our understanding of nanoscale ions in solution.

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of the main sources of clean and renewable energy. In this study, daily Rs values at seven meteorological stations in Iran (Ahvaz, Isfahan, Kermanshah, Mashhad, Bandar Abbas, Kerman and Tabriz) over 2010-2019 were estimated using empirical models, support vector machine (SVM), SVM coupled with cuckoo search algorithm (SVM-CSA) and multi-model approach in the form of two structures. In structure 1, data from each station were divided into training and testing sets. In structure 2, data from the former four stations were used for model training, and those from the latter three stations were used to test the models. The results showed that using meteorological parameters improved estimation accuracy compared with the use of geographical parameters for both SVM and SVM-CSA models. Coupling the CSA to SVM did improve the accuracy of radiation estimates, reducing RMSE by up to 38% (Kermanshah station) and 36% (Tabriz station) for the first structure and about 42.4% (Tabriz station) for the second. Performance analysis of the models over three intervals including, the first, middle and last third of measured radiation values at each station showed that for both structures (except at Tabriz station), the best model performance in under- and over-estimation sets of radiation values was obtained, respectively, in the first third interval (first structure, Mashhad station, RMSE = 28.39 J.cm

There are widespread Mesozoic-Cenozoic terrestrial volcanic activities in East China, and they produced favorable geologic factors for the volcanic reservoirs. To reveal the spatio-temporal evolution of regional volcanisms and their tectonic setting, we subdivide Mesozoic-Cenozoic volcanic activities into 6 volcanic cycles (I-VI), and summarize the temporal-spatial distribution, rock association and tectonic setting of each cycle. The Cycle I forms a post-orogenic intraplate bimodal volcanic association. The cycles II and III include arc volcanic associations formed in compressional and extensional subduction environments, respectively. The Cycle IV contains a post-orogenic arc bimodal association. The Cycle V is a basaltic association of tholeiite series under initial rift setting, and the Cycle VI is basaltic association of alkaline series under typical rift setting. The volcanic strata between each cycle are bounded by regional unconformity. The above 6 volcanic cycles correspond to 6 sequential stages of tectonic evolutions from the Early Jurassic post-orogeny, the Mid-Jurassic-Cretaceous subduction of the paleo-Pacific Plate to the Cenozoic marginal rifting. According to the geological characteristics of volcanic reservoirs in different volcanic cycles, it is put forward that the Cycle V is the major formation period of volcanic reservoirs in East China and should be the focus of exploration, and that the volcanic reservoirs of the Cycle IV are also worthy of attention.

This study appraised and compared the performance of process-based hydrological SWAT (soil and water assessment tool) with a machine learning-based multi-layer perceptron (MLP) models for simulating streamflow in the Upper Indus Basin. The study period ranges from 1998 to 2013, where SWAT and MLP models were calibrated/trained and validated/tested for multiple sites during 1998–2005 and 2006–2013, respectively. The performance of both models was evaluated using nash–sutcliffe efficiency (NSE), coefficient of determination (R2), Percent BIAS (PBIAS), and mean absolute percentage error (MAPE). Results illustrated the relatively poor performance of the SWAT model as compared with the MLP model. NSE, PBIAS, R2, and MAPE for SWAT (MLP) models during calibration ranged from the minimum of 0.81 (0.90), 3.49 (0.02), 0.80 (0.25) and 7.61 (0.01) to the maximum of 0.86 (0.99), 9.84 (0.12), 0.87 (0.99), and 15.71 (0.267), respectively. The poor performance of SWAT compared with MLP might be influenced by several factors, including the selection of sensitive parameters, selection of snow specific sensitive parameters that might not represent actual snow conditions, potential limitations of the SCS-CN method used to simulate streamflow, and lack of SWAT ability to capture the hydropeaking in Indus River sub-basins (at Shatial bridge and Bisham Qila). Based on the robust performance of the MLP model, the current study recommends to develop and assess machine learning models and merging the SWAT model with machine learning models.

Palmer Drought Severity Index (PDSI) is known as a robust agricultural drought index since it considers the water balance conditions in the soil. It has been widely used as a reference index for monitoring agricultural drought. In this study, the PDSI time series were calculated for nine synoptic stations to monitor agricultural drought in semi-arid region located at Zagros mountains of Iran. Autoregressive Moving Average (ARMA) was used as the stochastic model while Radial Basis Function Neural Network (RBFNN) and Support Vector Machine (SVM) were applied as Machine Learning (ML)-based techniques. According to the time series analysis of PDSI, for the driest months the most PDSI drought events are normal drought and mild drought conditions. As an innovation, Dragonfly Algorithm (DA) was used in this study to optimize the SVM’s parameters, called as the hybrid SVM-DA model. It is worthy to mention that the hybrid SVM-DA is developed as a meta-innovative model for the first time in hydrological studies. The novel hybrid SVM-DA paradigm could improve the SVM’s accuracy up to 29% in predicting PDSI and therefore was found as the superior model. The best statistics for this model were obtained as Root Mean Squared Error (RMSE) = 0.817, Normalized RMSE (NRMSE) = 0.097, Wilmott Index (WI) = 0.940, and R = 0.889. The Mean Absolute Error values of the PDSI predictions via the novel SVM-DA model were under 0.6 for incipient drought, under 0.7 for mild and moderate droughts. In general, the error values in severe and extreme droughts were more than the other classes; however, the hybrid SVM-DA was the best-performing model in most of the cases.

Satellite- and reanalysis-based precipitation products are important data source for precipitation, particularly in areas with a sparse gauge network. Here, five open-access precipitation products, including the newly released China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) reanalysis dataset and four widely used bias-adjusted satellite precipitation products [SPPs; i.e., Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 Version 7 (TMPA 3B42V7), Climate Prediction Center (CPC) morphing technique satellite-gauge blended product (CMORPH-BLD), Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR)], were assessed. These products were first compared with the gauge observed data collected for the upper Huaihe River basin, and then were used as forcing data for streamflow simulation by the Xin’anjiang (XAJ) hydrological model under two scenarios with different calibration procedures. The performance of CMADS precipitation product for the Chinese mainland was also assessed. The results show that: (1) for the statistical assessment, CMADS and CMORPH-BLD perform the best, followed by TMPA 3B42V7, CHIRPS, and PERSIANN-CDR, among which the correlation coefficient (CC) and root-mean-square error (RMSE) values of CMADS are optimal, although it exhibits certain significant negative relative bias (BIAS; −22.72%); (2) CMORPH-BLD performs the best in capturing and detecting rainfall events, while CMADS tends to underestimate heavy and torrential precipitation; (3) for streamflow simulation, the performance of using CMADS as input is very good, with the highest Nash-Sutcliffe efficiency (NSE) values (0.85 and 0.75 for calibration period and validation period, respectively); and (4) CMADS exhibits high accuracy in eastern China while with significant negative BIAS, and the performance declines from southeast to northwest. The statistical and hydrological evaluations show that CMADS and CMORPH-BLD have high potential for observing precipitation. As high negative BIAS values showed up in CMADS evaluation, further study on the error sources from original data and calibration algorithms is necessary. This study can serve as a reference for selecting precipitation products in data-scarce regions with similar climates and topography in the Global Precipitation Measurement (GPM) era.

Main conclusionThe molecular mechanism underlying white petal color inBrassica napuswas revealed by transcriptomic and metabolomic analyses.AbstractRapeseed (Brassica napusL.) is one of the most important oilseed crops worldwide, but the mechanisms underlying flower color in this crop are known less. Here, we performed metabolomic and transcriptomic analyses of the yellow-flowered rapeseed cultivar ‘Zhongshuang 11’ (ZS11) and the white-flowered inbred line ‘White Petal’ (WP). The total carotenoid contents were 1.778-fold and 1.969-fold higher in ZS11 vs. WP petals at stages S2 and S4, respectively. Our findings suggest that white petal color in WP flowers is primarily due to decreased lutein and zeaxanthin contents. Transcriptome analysis revealed 10,116 differentially expressed genes with a fourfold or greater change in expression (P-value less than 0.001) in WP vs. ZS11 petals, including 1,209 genes that were differentially expressed at four different stages and 20 genes in the carotenoid metabolism pathway.BnNCED4b, encoding a protein involved in carotenoid degradation, was expressed at abnormally high levels in WP petals, suggesting it might play a key role in white petal formation. The results of qRT-PCR were consistent with the transcriptome data. The results of this study provide important insights into the molecular mechanisms of the carotenoid metabolic pathway in rapeseed petals, and the candidate genes identified in this study provide a resource for the creation of newB. napusgermplasms with different petal colors.

This paper presents a combined spheropolyhedral discrete element (DE)–finite element (FE) computational approach to simulating vertical plate loading on cohesionless soils such as gravels. The gravel particles are modeled as discrete elements, and the plate is modeled as a deformable FE continuum. The simulations provide a meaningful step toward better understanding how deformable bodies transmit loads to granular materials. The DE–FE contact algorithm is verified through comparison with an analytical solution for impact between two symmetric bars. A parametric study is conducted to ensure boundary effects are not significantly influencing the simulations. Numerical simulations are compared to experimental test results of lightweight deflectometer loading on a gravel base course with satisfactory agreement. Future developments of the approach intend to simulate wheel loading of military aircraft on unsurfaced airfields.

A drone-based system for monitoring of laser-induced fluorescence from the aquatic environment was constructed. Fixed-range remote-sensing demonstration measurements were performed, and field recordings of natural river water fluorescence, oil-slicks as well as dye-marked natural water volumes were taken at drone flying heights of about 10 m. Our fluorosensor, weighing only 1.5 kg, and carried by a commercial drone, illustrates how airborne remote sensing based on fluorescence can be made cost-effective and readily applicable, while presently only in ambient low-light-level conditions.

Many epidemiological studies have shown that airborne particulate matter (PM) is a risk factor for multiple respiratory diseases and increased hospitalization rates. Fine PM (PM2.5, diameter

Electric-field-driven oxygen ion evolution in the metal/oxide heterostructures emerges as an effective approach to achieve the electric-field control of ferromagnetism. However, the involved redox reaction of the metal layer typically requires extended operation time and elevated temperature condition, which greatly hinders its practical applications. Here, we achieve reversible sub-millisecond and room-temperature electric-field control of ferromagnetism in the Co layer of a Co/SrCoO

Effective monitoring of flying insects is of major societal importance in view of the role of insects as indispensable pollinators, destructive disease vectors and economically devastating agricultural pests. The present paper reports on monitoring of flying agricultural pests using a continuous-wave lidar system in a rice-field location in Southern China. Using a Scheimpflug arrangement, range resolution over several 100 m long observational paths was achieved. The system operates with two perpendicularly polarized near-infrared lasers, which are activated intermittently, and back-scattered radiation from insects was recorded by a linear array detector placed after a linear polarizer. Our polarization sensitive system was used to monitor the flying insect diurnal activity and also the influence of changes in weather conditions, e.g., the occurrence of rain. Activity strongly peaked at dusk and rose again, although to a lower extent, just before dawn. At the onset of rainfall, a strong increase in insect counts occurred which was interpreted as the rain-induced bringing down of high-altitude migrant insects.

Recent researches have already shown that graphene can be a very promising candidate for reducing friction and wear by being coated on various moving mechanical assemblies. Although its excellent lubricative properties have been examined in different environments experimentally, the effect of conditions on graphene tribology performance are not well-understood. This research demonstrates the friction and wear mechanisms of graphene at nanoscale by first-principles calculations performed under two different conditions: in vacuum and in hydrogen. Besides, this report has revealed the difference of tribological performance between graphene coating and graphite powder in vacuum. It is shown that the graphene coating has lower adhesion than graphite powder because of less dangling bonds. Furthermore, with the perfect lamellar structure and low surface energy, graphene sheets exhibits promising wear resistance. Additionally, the adhesion and wear resistance of graphene sheets can be improved by hydrogen-induced flexible electrons. The computational simulations show that the higher adhesion originates from hydrogen adsorption. It is really helpful for the ruptured graphene to extend the wear life by hydrogen passivation.

In order to clarify the differences of very high cycle fatigue (VHCF) behavior of nickel based superalloy IN718 with different loading frequencies, stress-controlled fatigue tests were carried out by using ultrasonic testing method (20 KHz) and rotary bending testing method (52.5 Hz), both at room temperatures, to establish stress versus cycles to failure (S-N) relationships. Results disclosed that cycles to failure at a given stress level increased with an increase of the applied frequency, i.e., the higher frequency produced an upper shift of the S-N curves. Fractographic analysis suggested that crack initiation and propagation behaviors had large differences: cracks in low-frequency tests preferentially initiated from multiple sources on the specimen surface, while in high-frequency tests, cracks mostly originated from a unique source of subsurface inclusions. Subsequently, frequency-involved modeling was proposed, based on the damage accumulation theory, which could well illustrate qualitatively those comparisons due to different loading frequencies.

Identification of agricultural pest insects is an important aspect in insect research and agricultural monitoring. We have performed a methodological study of how spectroscopic techniques and wing-beat frequency analysis might provide relevant information. An optical system based on the combination of close-range remote sensing and reflectance spectroscopy was developed to study the optical characteristics of different flying insects, collected in Southern China. The results demonstrate that the combination of wing-beat frequency assessment and reflectance spectral analysis has the potential to successfully differentiate between insect species. Further, studies of spectroscopic characteristics of fixed specimen of insects, also from Central China, showed the possibility of refined agricultural pest identification. Here, in addition to reflectance recordings also laser-induced fluorescence spectra were investigated for all the species of insects under study and found to provide complementary information to optically distinguish insects. In order to prove the practicality of the techniques explored, clearly fieldwork aiming at elucidating the variability of parameters, even within species, must be performed.

A gel, an aggregate of polymers with solvents, has dual attributes of solid and liquid as solvent migrates in and out of the polymer network. Indentation has recently been used to characterize the mechanical properties of gels. This paper evaluates the effects of large deformation and material nonlinearity on gel indentation through theoretical modeling and finite element analysis. It is found that large deformation significantly affects the interpretation of the experimental observations and the classical relation between indentation force and depth has limitations for large deformation. The material nonlinearity does not play a very important role on indentation experiment so that the poroelasticity is a good approximation. Based on these observations, this paper proposes an alternative approach to measure the mechanical properties of gels, namely, uniaxial compression experiment.

Silacycles play a very important role in modern organic chemistry and materials science. Construction of silacyclic skeletons via metal-mediated or catalyzed Si-C bond cleavage has attracted much recent attention. Several interesting and useful synthetic strategies have been reported in the literature. In this review, we have summarized recent developments on metal-mediated or catalyzed Si-C bond cleavage, which lead to the synthesis of silacycles, including silacyclobutenes, silacyclopentanes, silacyclopentadienes (siloles), 6-membered silacycles, and their derivatives.

Molecular dynamics simulations using embedded atom method (EAM) potential were performed to study nano-void growth and coalescence at grain boundary in face-centered cubic bicrystal copper. Thin-plate specimens subjected to uniaxial tension strain with one-void and two-void at the centered grain boundary were employed to analyze the effect of specimen size, temperature and applied strain rate on the stress-strain response, incipient yield strength and macroscopic effective Young’s modulus. The evolutions of dislocations, twin bands and void shapes under different specimen sizes were also presented. The obtained results show that, regardless of the void numbers, the specimen sizes, temperature, the applied strain rate had significant influence on the void shape evolution, stress-strain curve and incipient yield strength, while negligible effects on the macroscopic effective Young’s modulus except for the temperature. Moreover, the voids growth rate along the grain boundary was also found to be associated with the specimen sizes.

Gigacycle fatigue behaviors of two SNCM439 steels with different tensile strengthes were experimentally studied by rotating bending tests, to investigate the effects of the tensile strength obtained by different heat treatment processes on very high cycle fatigue failure mechanisms. The material with higher tensile strength of 1 710MPa exhibited typical gigacycle fatigue failure characteristics, whereas one with lower tensile strength of 1 010MPa showed only traditional fatigue limit during the tests and no gigacycle failure could be found even when the specimen ran up to more than 108 cycles. Metallographic and fractographic analysis were carried out by an optical microscope (OM) and scanning electron microscope (SEM). It showed two different crack initiation mechanisms that for the specimen with lower tensile strength the crack prefers surface initiation and for that with higher strength the crack initiates from subsurface inclusions revealed by a fish-eye like microstructure.

We propose a scheme to generate the entangled state of two $\Lambda $ -type three-level atoms trapped in a cavity. The atoms are initially prepared in their excited state and the cavity in vacuum state. Each atom has two possibilities to deexcite to one of the ground states. If two different polarized photons are detected subsequently, it is sure that both atoms are in different ground states. But which atom is in which ground state cannot be determined, the atoms are thus prepared in a superposition of two ground states, i.e., an entangled state. In comparison with the proposal of Hong and Lee [Phys. Rev. Lett. 89, 237901 (2002)], the requirement of a single polarized photon source can be avoided in our scheme.