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The non-Newtonian fluids possess captivating heat transfer applications in comparison to the Newtonian fluids. Here, a new type of non-Newtonian fluid named Reiner–Rivlin nanofluid flow over a rough rotating disk with Cattaneo–Christov (C–C) heat flux is studied in a permeable media. The stability of the nanoparticles is augmented by adding the gyrotactic microorganisms in the nanofluid. The concept of the envisaged model is improved by considering the influences of Arrhenius activation energy, chemical reaction, slip, and convective conditions at the boundary of the surface. The entropy generation is evaluated by employing the second law of thermodynamics. The succor of the Shooting scheme combined with the bvp4c MATLAB software is adapted for the solution of extremely nonlinear system of equations. The noteworthy impacts of the evolving parameters versus engaged fields are inspected through graphical illustrations. The outcomes show that for a strong material parameter of Reiner–Rivlin, temperature, and concentration profiles are enhanced. The behavior of Skin friction coefficients, local Nusselt number, Sherwood number, and local density number of motile microorganisms against the different estimates of emerging parameters are represented in tabular form. The authenticity of the intended model is tested by comparing the presented results in limiting form to an already published paper. A proper correlation between the two results is attained.

In this investigation, the entropy generation, heat transfer, and Fe3O4-water ferro-nanofluid flow within a porous ribbed microchannel heat sink in the presence of a constant magnetic field are investigated, and their impacts are analyzed for single-phase and two-phase approaches. The values of dimensionless numbers, namely Hartmann and the Reynolds numbers are in the range of 0 ≤ Ha ≤ 10 and 10 ≤ Re ≤ 80. Additionally, the porosity percentage and volume fraction of nanoparticles are in the range of 0 ≤ e ≤ 75 % and 0 ≤ ϕ ≤ 2 %, respectively. The influences of dimensionless numbers and porosity percentage in three cases of the microchannel (Cases A.1, A.2, and A.3) are investigated. This study provides a comparison between assumed parameters. It is demonstrated that in all cases, variables such as porosity percentage, Reynolds and Hartmann numbers are directly related to the enhancement of the heat transfer coefficient. Also, in the single-phase model, the dimensionless heat transfer coefficient has a lower amount compared to the two-phase model, and the only exception is for ϕ = 0%.

Rabies virus (RV) is the most widely used vector for mapping neural circuits. Previous studies have shown that the RV glycoprotein can be a target to improve the retrograde transsynaptic tracing efficiency. However, the current versions still label only a small portion of all presynaptic neurons. Here, we reshuffled the oG sequence, a chimeric glycoprotein, with positive codon pair bias score (CPBS) based on bioinformatic analysis of mouse codon pair bias, generating ooG, a further optimized glycoprotein. Our experimental data reveal that the ooG has a higher expression level than the oG in vivo, which significantly increases the tracing efficiency by up to 12.6 and 62.1-fold compared to oG and B19G, respectively. The new tool can be used for labeling neural circuits Therefore, the approach reported here provides a convenient, efficient and universal strategy to improve protein expression for various application scenarios such as trans-synaptic tracing efficiency, cell engineering, and vaccine and oncolytic virus designs. Supplementary Information The online version contains supplementary material available at 10.1186/s13041-021-00821-7.

In this paper we give Hadamard inequalities for exponentially $ (\alpha, h-m) $-convex functions using Riemann-Liouville fractional integrals for strictly increasing function. Results for Riemann-Liouville fractional integrals of convex, $ m $-convex, $ s $-convex, $ (\alpha, m) $-convex, $ (s, m) $-convex, $ (h-m) $-convex, $ (\alpha, h-m) $-convex, exponentially convex, exponentially $ m $-convex, exponentially $ s $-convex, exponentially $ (s, m) $-convex, exponentially $ (h-m) $-convex, exponentially $ (\alpha, h-m) $-convex functions are particular cases of the results of this paper. The error estimations of these inequalities by using two fractional integral identities are also given.

The graph energy $ E(G) $ of a simple graph $ G $ is sum of its absolute eigenvalues where eigenvalues of adjacency matrix $ A(G) $ are referred as eigenvalues of graph $ G $. Depends upon eigenvalues of different graph matrices, several graph energies has been observed recently such as maximum degree energy, Randi$ \acute{c} $ energy, sum-connectivity energy etc. Depending on the definition of a graph matrix, the graph energy can be easily determined. This article contains upper bounds of several graph energies of $ s $-regular subdivision graph $ S(G) $. Also various graph energies of complete graph are mentioned in this article.

The article explores the effect of Hall current, thermal radiation, and magnetic field on hybrid nanofluid flow over the surface of a spinning disk. The motive of the present effort is to upgrade the heat transmission rate for engineering and industrial purposes. The hybrid nanofluids as compared to the conventional fluids have higher thermal properties. Therefore, in the present article, a special class of nanoparticles known as carbon nanotubes (CNTs) and iron ferrite nanoparticles are used in the base fluid. The system of modeled equations is depleted into dimensionless differential equations through similarity transformation. The transform equations are further solved through the Parametric Continuation method (PCM). For the parametric study, the physical parameters impact on velocity, energy, mass transmission, and motile microorganism’s concentration profiles have been sketched. The obtained results are compared with the existing literature, which shows the best settlement. It concluded that the heat transmission rate reduces for Hall current and rises with radiative parameter. The results perceived that the addition of CNTs in carrier fluid is more efficacious than any other types of nanoparticles, due to its C–C bond. CNTs nanofluid can be more functionalized for the desired achievement, which can be utilized for a variety of applications by functionalization of non-covalent and covalent modification.

Energy consumption efficiency during resource allocation is crucial for large scale networks. The evolution of space division multiplexing elastic optical networks (SDM-EONs) has presented tremendous spatial dimensions over single-mode networks to manage transmission of largetraffic volumes, during peak load of the fluctuating traffic. However, due to large capacitytransmission rates, the resource allocation challenges have led to incremental energy consumption. This is due to the impact of crosstalk (XT), which occurs between active adjacent cores, during core switching, and increasing service disruptions caused by rampant link failures. To address the above issues, this article proposes a distance-adaptive energy-aware resource allocation (DERA) algorithm using a survival multipath scheme. The DERA algorithm implements the concept of the survival multipath scheme with Spectrum Compactness (SC) to minimize dynamic XT effects in SDM-EONs, during resource allocation. The objective is to improve spectral efficiency to save energy consumption, when the load of the fluctuating traffic peaks. During Routing, Modulation, Spectrum, and Core Allocation (RMSCA), the DERA algorithm can efficiently allocate resources in a survival multipath scheme. The performance of the DERA-RMSCA is compared with the two Multipath Protection (MPP) schemes, PRIME-RMSCA, and CMDE-RMSCA. The results demonstrate that DERA-RMSCA can achieve a better performance compared with PRIME-RMSCA, and CMDE-RMSCA.

The aim of this paper is to generalize the results regarding fractals and prove escape conditions for general complex polynomial. In this paper we state the orbit of a newly defined iterative scheme and establish the escape criteria in fractal generation for general complex polynomial. We use established escape criteria in algorithms to generate Mandelbrot and Multi-corns sets. In addition, we present some graphs of quadratic, cubic and higher Mandelbrot and Multi-corns sets and discuss how the alteration in parameters make changes in graphs.

Computational prediction of facial aesthetics has attracted ever-increasing research focus, which has wide range of prospects in multimedia applications. The key challenge lies in extracting discriminative and perception-aware features to characterize the facial beautifulness. To this end, the existing schemes simply adopt a direct feature mapping, which relies on handcraft-designed low-level features that cannot reflect human-level aesthetic perception. In this paper, we present a systematic framework towards designing biology-inspired, discriminative representation for facial aesthetic prediction. First, we design a group of biological experiments that adopt eye tracker to identify spatial regions of interest during the facial aesthetic judgments of subjects, which forms a Bio-inspired Facial Aesthetic Ontology (Bio-FAO) and is made public available. Second, we adopt the cutting-edge convolutional neural network to train a set of Bio-inspired Attribute features, termed Bio-AttriBank, which forms a mid-level interpretable representation corresponding to the aforementioned Bio-FAO. For a given image, the facial aesthetic prediction is then formulated as a classification problem over the Bio-AttriBank descriptor responses, which well bridges the affective gap, and provides explainable evidences on why/how a face is beautiful or not. We have carried out extensive experiments on both JAFFE and FaceWarehouse datasets, with comparisons to a set of state-of-the-art and alternative approaches. Superior performance gains in the experiments have demonstrated the merits of the proposed scheme.

In this paper, we present a method called density-aware convolutional neural network (DensityCNN) to perform the crowd counting task in various crowded scenes. The key idea of the DensityCNN is to utilize high-level semantic information to provide guidance and constraint when generating density maps. To this end, we implement the DensityCNN by adopting a multi-task CNN structure to jointly learn density-level classification and density map estimation. The density-level classification task learns multi-channel semantic features that are aware of the density distributions of the input image. This task is accomplished via our specially designed group-based convolutional structure in a supervised learning manner. In the density map estimation task, these semantic features are deployed together with high-dimension convolutional features to generate density maps with lower count errors. Extensive experiments on four challenging crowd datasets (ShanghaiTech, UCF_CC_50, UCF-QNCF, and WorldExpo’10) and one vehicle dataset TRANCOS demonstrate the effectiveness of the proposed method.

In the article, we present the sharp upper and lower bounds for the arithmetic mean in terms of new Seiffert-like means, which give some refinements of the results obtained in [ 1 ]. As applications, two new inequalities for the sine and hyperbolic sine functions will be established.

This article proposes a fast and accurate network for surface defect detection, termed SDDNet. SDDNet mainly addresses two challenging issues—large texture variation and small size of defects—by introducing two modules: feature retaining block (FRB) and skip densely connected module (SDCM). FRB fuses multiple pyramidal feature maps with different resolutions and is plugged on the top of pooling layers, aiming to preserve the texture information, which may be lost because of downsampling. SDCM is designed to propagate the fine-grained details from low- to high-level feature maps for better prediction of defects, especially small defects. Extensive experiments conducted on the publicly available data sets NEU-DET (88.8% mAP), DAGM (99.1% mAP), and Magnetic-Tile (93.4% mAP) have demonstrated the effectiveness of the proposed SDDNet and its feasibility for real-time industrial applications.

The durable application of polylactide (PLA) under atmospheric conditions is restricted by its poor ultraviolet (UV) stability. To improve the UV stability of polymers, titanium dioxide (TiO2) is often used as a UV light capture agent. However, TiO2 is also a photocatalytic agent, with detrimental effects on the polymer properties. To overcome these two conflicting issues, we used the following approach. TiO2 nanoparticles were first coated with silicon dioxide (SiO2) (with a SiO2 shell content of 5.3 wt %). Subsequently, poly(d-lactide) (PDLA) was grafted onto TiO2@SiO2 nanoparticles, approximately 20 wt %, via a ring-opening polymerization of d-lactide to obtain well-designed double-shell TiO2@SiO2-g-PDLA nanohybrids. These double-shell nanoparticles could be well dispersed in a poly(l-lactide) (PLLA) matrix making use of the stereocomplexation between the two enantiomers. In our concept, the inner SiO2 shell on the TiO2 nanoparticles prevents the direct contact between TiO2 and the PLLA matrix and hence considerably restricts the detrimental photocatalytic effect of TiO2 on PLLA degradation. Additionally, the outer PDLA shell facilitates an improved dispersion of these nanohybrid particles by interfacial stereocomplexation with its enantiomer PLLA. As a consequence, the PLLA/TiO2@SiO2-g-PDLA nanocomposites simultaneously possess excellent UV-shielding property, high(er) tensile strength (>60 MPa), and superior UV resistance, for example, the mechanical properties remain at a level of >90% after 72 h of UV irradiation. In our view, this work provides a novel strategy to make advanced PLA nanocomposites with improved mechanical properties and excellent UV resistance, which enables potential application of PLA in more critical areas such as in durable packaging and fiber/textile applications.

A HO· detection method based on UV–visible spectrophotometry was established to study the generation and influence mechanism of HO· during electrical advanced oxidation processes (EAOPs), and to analyze the HO· degradation mechanism of pyridine. The ability of HO· capturing agents, salicylic acid (SA) and terephthalic acid (TA) were compared. Compared with SA, TA has a larger cumulative capture of HO· and a higher capture efficiency. The effects of electrochemical conditions were investigated by using TA as a scavenger. The results show that the foam nickel electrode has higher energy efficiency. With the increase of electrolyte concentration, the rate of electron migration in solution is accelerated, which greatly improves the yield of HO·. At the same time, alkaline conditions are more conducive to the formation of HO·. The increase of current density can accelerate the generation of HO·. The degradation mechanism of pyridine in the electrochemical system under different pH conditions was studied. The GC–MS analysis showed that the degradation products of pyridine were different in electrochemical treatment. The main reason was that pH affected the ring opening mode of HO· to pyridine.

People in crowd scenes often exhibit the characteristic of imbalanced distribution. On the one hand, people size varies largely due to the camera perspective. People far away from the camera look smaller and are likely to occlude each other, whereas people near to the camera look larger and are relatively sparse. On the other hand, the number of people also varies greatly in the same or different scenes. This article aims to develop a novel model that can accurately estimate the crowd count from a given scene with imbalanced people distribution. To this end, we have proposed an effective multi-level convolutional neural network (MLCNN) architecture that first adaptively learns multi-level density maps and then fuses them to predict the final output. Density map of each level focuses on dealing with people of certain sizes. As a result, the fusion of multi-level density maps is able to tackle the large variation in people size. In addition, we introduce a new loss function named balanced loss (BL) to impose relatively BL feedback during training, which helps further improve the performance of the proposed network. Furthermore, we introduce a new data set including 1111 images with a total of 49 061 head annotations. MLCNN is easy to train with only one end-to-end training stage. Experimental results demonstrate that our MLCNN achieves state-of-the-art performance. In particular, our MLCNN reaches a mean absolute error (MAE) of 242.4 on the UCF_CC_50 data set, which is 37.2 lower than the second-best result.

5-Substituted benzylidene 3-acylthiotetronic acids are antifungal. A series of 3-acylthiotetronic acid derivatives with varying substitutions at the 5-position were designed, synthesized, and characterized, based on the binding pose of 3-acyl thiolactone with the protein C171Q KasA. Fungicidal activities of these compounds were screened against Valsa Mali, Curvularia lunata, Fusarium graminearum, and Fusarium oxysporum f. sp. lycopersici. Most target compounds exhibited excellent fungicidal activities against target fungi at the concentration of 50 μg·mL−1. Compounds 11c and 11i displayed the highest activity with a broad spectrum. The median effective concentration (EC50) values of 11c and 11i were 1.9–10.7 and 3.1–7.8 μg·mL−1, respectively, against the tested fungi, while the EC50 values of the fungicides azoxystrobin, carbendazim, and fluopyram were respectively 0.30, 4.22, and > 50 μg·mL−1 against V. Mali; 6.7, 41.7, and 0.18 μg·mL−1 against C. lunata; 22.4, 0.42, and 0.43 μg·mL−1 against F. graminearum; and 4.3, 0.12, and > 50 μg·mL−1 against F. oxysporum f. sp. lycopersici. The structures and activities of the target compounds against C. lunata were analyzed to obtain a statistically significant comparative molecular field analysis (CoMFA) model with high prediction abilities (q2 = 0.9816, r2 = 0.8060), and its reliability was verified. The different substituents on the benzylidene at the 5-position had significant effects on the activity, while the introduction of a halogen atom at the benzene ring of benzylidene was able to improve the activity against the tested fungi.

BACKGROUND Chlorothalonil is a conventional chloroaromatic fungicide and is toxic to many aquatic species. This study was designed to investigate the effects of six flavonoids on the photolysis of chlorothalonil under sunlight and artificial light. RESULTS Flavonoids sensitized the photolysis of chlorothalonil under sunlight and artificial light by 6.7-18.3 and 2.4-7.5 times, respectively, in comparison with a flavonoid-free control. Photosensitization effect of each of the six flavonoids was greater under sunlight irradiation than under high-pressure mercury lamp irradiation. Cyanidin showed greater photosensitization effects than luteolin, galangin, quercetin, morin and kaempferol. Chlorothalonil underwent photo-reductive dechlorination and no hydrolysis product was formed in the presence of flavonoids. Hydroxyl and hydrogen radicals were detected in the absence and presence of cyanidin, respectively, under light irradiation. CONCLUSION The photosensitization effect of flavonoids on chlorothalonil photolysis is apparently related to flavonoid structure and might be due to their hydrogen donation capacity. These results highlight benefit of using flavonoids to manage aquatic pollution and reduce aquatic toxicity, and have great relevance in predicting the degradation kinetics and biological impacts of chlorothalonil in surface water. © 2020 Society of Chemical Industry.

Flavonoids can sensitize and quench the photolysis of pesticides such as profenofos in surface water. Profenofos has been frequently detected in surface and underground water. The present study investigated the photolysis of profenofos under various conditions, including natural and artificial light illumination, with and without cyanidin-3-O-glucoside (Cy3G) and in pure and surface water. The degradation half-lives of profenofos in distilled water with 10 equivalents Cy3G of profenofos were 21.7 min, 9.5 h, 12.5 h and 180 h under high-pressure mercury light, UV, Xenon lamp and solar irradiation, respectively, while those without Cy3G were 8.1 min, 6.1 h, 8.2 h and 89.9 h, respectively. The photolysis rate of profenofos under sunlight and artificial light was reduced by 1.5-2.7 times due to Cy3G, compared to the Cy3G-free control. Under sunlight irradiation, the effects of Cy3G on profenofos photolysis were larger than those under high-pressure mercury lamp irradiation. Cy3G also significantly reduced the photolysis rate of profenofos under different pH conditions and in natural water. In addition, Cy3G exhibited a significant capacity of scavenging hydroxyl radicals and quenching

In this work, we explore the limiting behavior of Riemann solutions to the Euler equations in isentropic gas dynamics with general pressure law. We demonstrate that in the distributional sense the delta wave of zero-pressure gas dynamics is formed by a limit solution. Finally, to present the concentration phenomena, we also offer some numerical outcomes.

Table S1: U-Th-Pb LA-ICP-MS data of zircons from metamafic rocks in the Oulongbuluke Block. Table S2: LA-MC-ICP-MS Lu-Hf isotope data of zircons from metamafic rocks in the Oulongbuluke Block. Table S3: Major and trace element compositions of metamafic rocks in the Oulongbuluke Block.

The fractional ( 3 + 1 ) -dimensional nonlinear Schrodinger equation with cubic–quintic–septic nonlinearities plays a significant role in the study of ultra-short pulses in highly nonlinear optical phenomena. The main purpose of this work is to determine the solution of ( 3 + 1 ) -dimensional nonlinear Schrodinger equation containing cubic–quintic–septic nonlinearities with conformal temporal operator. The solution of the considered problem is investigated using an adaptation of the residual power series method for the conformal fractional derivative. To illustrate the authenticity of the residual power series method to solve the nonlinear conformable Schrodinger equation with cubic–quintic–septic nonlinearities, three test applications are considered subject to different initial conditions. The variations of wave solutions of the applications corresponding to changes in the conformal derivative are depicted through graphical illustrations. The numerical comparisons confirm the accuracy of the presented results for the conformal ( 3 + 1 ) -dimensional nonlinear Schrodinger equation. The obtained results indicate the accuracy, suitability and competency of the residual power series method to examine other nonlinear conformable fractional differential equations arising in optics and other areas of physics.

The degradation rate of lignocellulose and methane (CH4) content must be improved through anaerobic fermentation process engineering in order to promote the proper operation of anaerobic organic waste removal without secondary pollution and low cost. The present study investigates mesophilic anaerobic fermentation of dairy manure (DM) under weak magnetic and low operation voltage (0.3–0.8 V). The results showed that the effect of electric and magnetic fields (EMF) can significantly enhance the fermentation, and improve the CH4 content of biogas and accelerate the degradation rate of lignocellulose. Fe-C microelectrolysis intensified the anaerobic fermentation of DM, the highest CH4 content was 87%, the cellulose degradation rate was 36%, increased by 125%, and the lignin degradation rate was 23%, increased by 203%, under loading 0.5 V voltage and weak magnetic field. Metagenome sequence results showed that EMF and Fe-C microelectrolysis can not only promote the microbial diversity, but also increase the abundance of functional microorganisms at various stages. This finding provides theoretical support and foundation for the extraordinary efficiency degradation of lignocellulose and the electric and magnetic regulation of anaerobic fermentation microorganism system.

The present study aims to discuss the effect of escitalopram in glial cell line-derived neurotrophic factor (GDNF), brain-derived neurotrophic factor (BDNF) levels, and 5-Hydroxytryptamine (5-HT) in obsessive–compulsive disorder rats. A total of 42 rats were divided into three groups randomly: control group (n = 14), model group (n = 14) (obsessive–compulsive disorder group), and escitalopram group (n = 14) (model + obsessive–compulsive disorder group + escitalopram treatment). The open-field method was used to test the rat behavior, enzyme-linked immunosorbent assay (ELISA) was used to determine the serum GDNF and BDNF levels. In addition, Western blot was used to determine the brain tissue protein levels of GDNF and BDNF and high-performance liquid chromatography + electrochemistry method to determine the 5-HT level of brain tissue. Visiting place was changed, rotational frequency and fixed duration enhanced in escitalopram group compared to model group (P

The dynamics of GPCRs (G protein-coupled receptors) coupling for cognate G proteins play a critical role in signal transduction. Herein, we reported a site-specifically labelled small-sized fluorescent pair 7-HC/FlAsH ((7-hydroxycoumarin-4-yl)-ethylglycine/fluorescein arsenical hairpin) for fluorescence lifetime based FRET (fluorescence resonance energy transfer) to reveal conformational differences of Gαi1 (inhibitory G proteins) and Gαs (stimulatory G proteins) upon β2AR (β2-adrenergic receptor) coupling. It offers a new generally applicable method to probe protein dynamic interactions or conformational changes.

PurposeThe purpose of this paper is to reveal the co-editing mechanism aiming at content creation, and an entry of online encyclopedia is taken as a case, for the purpose of promoting and enhancing the development of wiki-based digital humanities projects (WDHPs), specifically, the projects that focus on gathering contextual information in the culture heritage domain.Design/methodology/approachAn exploratory study was conducted by three steps. A representative entry’s editorial records were reorganized to obtain a data set of discussion statements (n=608), based on which linked-structures were built, and PageRank algorithm was used to analyze the co-editing process. Skewness statistic was applied to measure the consensus of co-editing, and consensus evolution over time was explored. Linear or curve fitting was performed to analyze the correlation between consensus evolution and its influential factors.FindingsIn WDHPs, co-editing activity of content creation can be considered as a large-scale group discussion, consensus can evaluate the efficiency of co-editing, which evolves with time and is influenced by the number of statements, breadth and depth of argumentation structure. Taking “Mogao Grottoes” as an example, group discussions around 15 key issues dominate the content creating process, consensus is on a rise with time, finally reaches a relatively high level, and consensus evolution is more influenced by breadth than by depth of argumentation structure, which indicates that co-editing efficiency of “Mogao Grottoes” is fine and more argumentation in a depth manner should be guided.Practical implicationsFor researchers of WDHPs, it is beneficial to apply online encyclopedia platform combining with consensus analysis to develop WDHPs. For designers of WDHPs, the elements related to argumentation structure can be absorbed into the design to promote co-editing in an effective manner. For DH researchers, the analytic procedure can be beneficial of revealing the interest of contributors in a specific DH field.Originality/valueThis research is novel in comprehensively understanding co-editing mechanism of content creation in WDHPs, resulting in a three-step analytic procedure of presenting co-editing process, evaluating and improving co-editing efficiency.

SLM-processed 316L stainless steel exhibits promoted mechanical and corrosion performances, compared with the conventionally manufactured counterparts, and has been successfully applied in many fields. The anisotropic microstructure of SLM-processed materials, caused by the layer-wise fashion of SLM processing, not only results in the anisotropy of mechanical properties but also leads to the anisotropic corrosion behavior. In this study, the influence of microstructural differences of SLM-processed 316L stainless steel along the building direction on corrosion behavior was investigated. Firstly, the influence of laser scan speed on the microstructure, hardness, and corrosion behavior of SLM-processed 316L stainless steel samples was evaluated. Then, the sample with the highest relative density and the best hardness and corrosion resistance was selected to further investigate the influence of microstructural differences along the building direction on the corrosion behavior. Results showed that the corrosion resistance improved with the increase of distance from bottom plane along the building direction. Microstructure and phase analysis revealed that the microstructural differences in crystallographic orientation and grain size along the building direction of SLM-processed 316L stainless steel led to the different corrosion behavior.

Aromatic alcohols are essential components of many solvents, coatings, plasticizers, fine chemicals, and pharmaceuticals. Traditional manufacturing processes involving the oxidation of petroleum-de...

In this work, the absorption and purification of H2S by palladium-copper liquid phase catalysis solution applied voltage was performed. The effects of electrochemical conditions, oxygen concentration, electrode material, voltage intensity and electrode plate spacing on the electrohydraulic synergetic purification were investigated by measuring H2S removal efficiency. The removal efficiency of H2S by electrochemical and liquid phase catalysis was better than that of pure liquid phase catalysis or pure electrochemistry. In the entire reaction system, oxygen played an important role in the production of active intermediate substances and the recovery of catalyst activity. The better electrode material was graphite electrode; the purification efficiency was slightly improved under large voltage conditions, along with the increase of energy consumption; the optimum electrode plate spacing was 5 cm. The mechanism of H2S gas purification with palladium and copper catalyst under external voltage was investigated in the selected conditions. In the reaction system, one portion of H2S was combined with metal ions to form metal sulfide precipitation. These metal sulfide precipitate was dissolved by electrochemical action and existed as ions in the solution to maintain their catalytic activity. The other portion of H2S was reduced to sulfur and SO42- under the catalytic oxidation of transitional metals and electroactive substances. Electroactive substances could restore certain catalytic activity of metal catalytic ions and form a catalytic cycle, which improved the purification efficiency of H2S.

Forster resonance energy transfer (FRET) is a widely used distance measurement method to illustrate protein conformational dynamics. The FRET method relies on the distance between donor and acceptor, as well as the labelling efficiency, the size and the properties of the fluorophores. Here, we labelled a pair of small fluorophores and calculated the energy transferred efficiency through fluorescence lifetime analysis, which can provide more reliable distance measurement than intensity attenuation. The donor fluorophore, 7-hydroxycoumarin-4-yl-ethylglycine (HC), was genetically incorporated into specific sites of PYL10, obtaining complete labelling efficiency. The acceptor fluorophore, Alexa488, was labelled through the disulfide bond, whose labelling efficiency was estimated through both absorption peaks and lifetime populations. Fluorescence lifetime and anisotropy analysis showed ABA-induced local conformation changes and dynamics of several HC incorporation sites of PYL10. The lifetime-based FRET distance measurement illustrated the conformation changes of PYL10 with or without ABA application, which is consistent with the previously reported crystal structures.

In this paper, we present a novel crowd behavior evolution method with emotional contagion in political rallies. We first analyze the most representative political rally scenes in detail and model them into two kinds of abstract scenario. Furthermore, the “extroversion” and “empathy” factors from the OCEAN model are chosen to describe the most important individual personalities in such scenarios. Based on this, an improved emotional contagion model is proposed by combining the Susceptible-Infected-Recovered model and individual personality under different political viewpoints. Finally, the crowd in a political rally is driven to move according to the new potential moving direction generated by emotional contagion and the original direction of the individual together. The experiments show that our method can intuitively demonstrate the emotional changes of those individuals with different political perspectives and reasonably simulate the crowd movement under the political rally scenes.

Sparse labeling of neurons contributes to uncovering their morphology, and rapid expression of a fluorescent protein reduces the experiment range. To achieve the goal of rapid and sparse labeling of neurons in vivo, we established a rapid method for depicting the fine structure of neurons at 24 h post-infection based on a mutant virus-like particle of Semliki Forest virus. Approximately 0.014 fluorescent focus-forming units of the mutant virus-like particle transferred enhanced green fluorescent protein into neurons in vivo, and its affinity for neurons in vivo was stronger than for neurons in vitro and BHK21 (baby hamster kidney) cells. Collectively, the mutant virus-like particle provides a robust and convenient way to reveal the fine structure of neurons and is expected to be a helper virus for combining with other tools to determine their connectivity. Our work adds a new tool to the approaches for rapid and sparse labeling of neurons in vivo. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12264-019-00362-z) contains supplementary material, which is available to authorized users.

In the process of slug test in the field, mud and debris may infiltrate into the aquifer during the formation of the test well, and a poorly permeable annulus area appears around the test well wall. This is called the positive well-skin effect, which can have a significant impact on the results of slug tests due to the characteristics of a slug test. Therefore, to carry out the research on the determination of aquifer permeability coefficients by slug test under the influence of positive well-skin effect, a mathematical model of a slug test considering the positive well-skin effect was constructed. The Laplace transform method and the AWG algorithm were used to solve for a series of standard curves, and specific steps were given for calculating aquifer permeability coefficients by slug test under the influence of positive well-skin effect. Meanwhile, an indoor test model with positive well-skin effect was constructed, then several sets of slug tests and pumping tests with different excitation strengths were carried out. Based on this study, the presence of positive well-skin layer had a great impact on the aquifer permeability coefficient determined from both the pumping test and Kipp model of slug test, resulting in smaller results. The HWS model overcomes the influence of positive well-skin effect. This will further improve the theory of slug test, increase the accuracy of slug test in determining the permeability coefficient, and promote the application scope of slug test. It is therefore possible to discern the well-skin factor and determine the aquifer permeability coefficient by fitting the slug test data to a standard curve.

Emotional recognition is a key aspect of mentalizing other people's minds. People with Williams syndrome (WS) are reported to be hypersocial and empathetic; however, few studies have investigated their emotion processing ability.This study aimed to examine emotion knowledge in people with WS and to further understand their emotion-related mentalizing ability.Six basic emotions (happiness, sadness, anger, fear, disgust, and surprise) were tested by narrating scenarios targeting specific emotions. Participants with WS (n = 16, 8F/8 M, CA = 8.46, MA = 5.27) listened to each scenario and pointed to an emoticon displayed on a card. Correct percentages of each target emotion and replacement by other emotions were analyzed. Comparison groups comprised mental age-matched controls (n = 16, 8F/8 M, CA = 5.26) and chronological age-matched controls (n = 16, 8 F/8 M, CA = 8.31), sixth graders (n = 20, 10F/10M, CA = 12.04), and college students (n = 20, 10F/10M, CA = 20.03). All were Chinese-speaking participants with right handedness.People with WS were delayed compared to the mental age-matched group but differed from the chronological age-matched group in emotion processing. The 6th graders showed different patterns from college students, suggesting that development of emotion processing takes time.These findings suggest (1) a gap in the maturation of emotion knowledge between people with WS and typically developing controls, (2) a nonequivalent chronological emotion-related mentalizing ability in people with WS, and (3) developmental changes in emotion processing from childhood to adulthood.

The ability to follow a specified target person by a mobile robot plays an important role. The continuity of person following is a key factor to the performance and practicability. In the practical person following, the failure easily occurs when the target person is out of the sensing range of the robot, which destroys the continuity of the person following and still remains a challenge. To solve the problem of following recovery, a locating framework based on distributed odometries is proposed, which can locate the target effectively with a robot-end odometry and a target-end odometry. In this framework, the robot-end odometry and the target-end odometry are used to estimate poses of the robot and positions of the target person, respectively. These two odometries are fused with the combination of locations of the target person in the robot coordinate system. On this basis, the robot can obtain the estimated target location by receiving the position information from the target-end odometry with a wireless network, which is then transformed to the coordinate in the robot-end odometry. When a missing case occurs, the mobile robot can continue to retrieve the target person by moving along the sampling transformed positions. An implement with the robot-end LiDAR odometry and target-end wearable visual-inertial odometry is given to evaluate the proposed locating framework. Experiments reveal that a mobile robot can recover the normal person following even if the target person is far away from the robot.

Enantioselective metabolism of chiral pesticide in plants is very important. In vitro system has become an effective means to study the metabolism of pesticides in plants, but the study on the metabolism of chiral pesticides has not been reported. This work compared the enantiomer metabolic behavior of acephate and its metabolite methamidophos between tea cell suspensions and excised tea stem with leaves. (±)-Acephate could be absorbed and transferred well to top leaves by the cut end of excised stem after 24 h. (±)-Methamidophos was derived from the metabolism of (±)-acephate in tea plants at 3–5% in leaves and 2–3% in stems at 216 h. The content of (+)-methamidophos was 1.5 times higher than that of (−)-methamidophos in excised leaves. Though both (±)-acephate and (±)-methamidophos could be metabolized well by cell suspension, (±)-acephate and (±)-methamidophos was non-enantioselectively metabolized in cell suspension. It was shown that using the excised tea stem with leaves for chiral pesticide metabolism studies was much closer to intact plant than cell suspensions. This result also established an effective and easily available in vitro metabolic model for the study of enantioselective metabolism of chiral contaminants from environment.

Spatial source phase (SSP), derived from complex-valued functional magnetic resonance imaging (fMRI) data by data-driven methods, has unique capacity of identifying blood oxygenation-level dependent (BOLD)-related voxels from noisy voxels regardless of their amplitudes. However, the use of SSP constraint in sparse representation algorithms have rarely been studied. This study proposes a sparse representation method using SSP hard thresholding to achieve the sparsity of spatial components, enabling the use of initially complex-valued fMRI data and retaining the brain information embedded in noisy voxels and weak BOLD-related voxels with small phase values. Rank-1 matrix estimation is applied to sequentially update dictionary atoms and corresponding spatial components, followed by hard thresholding on spatial components based on SSP. The proposed method is evaluated using both simulated and experimental complex-valued data. The results show that the proposed method yields better performance than a complex-valued dictionary learning algorithm when using initially acquired complex-valued task-related fMRI data.

Analytical solutions of the fractional wave equation via Caputo-Fabrizio fractional derivative are presented in this paper. For this analysis, three cases are considered, the classical, the damped and the damped with a source term defined by fractional wave equations. We show that these solutions are special cases of the time fractional equations with exponential law. Illustrative examples are presented.

Installing obstructions in the path of the flowing stream in a Convergent-Divergent channel results in complex Reynolds Navier-Stokes (NS)-equations and an exact solution in this direction is not feasible. The current work is a notable attempt in this direction, reporting the evaluation of hydrodynamic forces faced by case-wise installation of infinite cylinders as obstacles to a continuous fluid stream. To be more specific, Newtonian fluid is initiated from inlet with bound of parabolic profile. The outlet of CD channel is carried with Neumann condition. The optimized path of installation of obstacle includes: (i) Two circular shaped cylinders are installed in left and right vicinity of CD throat (ii) Circular cylinder in right vicinity of CD throat is optimized with square cylinder (iii) Circular cylinder in left vicinity of CD throat is optimized with square cylinder. The flow field is mathematically modelled in terms of steady Reynolds NS-equations. The comparative solution is reported by using finite element method along rectangular and triangular elements as a hybrid meshing scheme. The obtained outcomes are shared by means of contour and line graphs. Optimized values of hydrodynamic forces subject to installed obstacles in convergent-divergent channel are reported by doing line integration around the outer surfaces of obstructions. It is observed that in each case, the obstructions in left vicinity of CD throat admits inciting values of drag coefficient as compared to obstruction rooted in right vicinity of CD throat.