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Atomically dispersed Co2+ on MgAlOx derived from CoMgAl-LDH was offered in a one-pot catalytic transformation of ethanol into the C4–10 alcohols process, which could boost the C4–10 alcohols yield of ethanol valorization at relatively low temperature.

An efficient synthesis method will allow a large number of tetramic acid analogues to be synthesized for property and potency optimization. In this study, a facile and efficient method was described for the synthesis of 3-acyltetramic acids. The synthesis was accomplished mainly via (1) mild intramolecular cyclization and (2) the formation of β-ketoamides between nucleophiles and acyl Meldrum's acids. 3-Acyltetramic acid exhibited phytotoxicity against

Background: High-Performance Liquid Chromatography (HPLC)-Ultraviolet (UV) and Liquid Chromatography (LC)-Mass Spectrometry (MS)/MS methods have been used to analyse abiraterone (ART); however, a single-quadrupole mass spectrometer with LC-MS systems has never been used to analyse ART. Objective: The study aimed to establish a novel, simple assay of quantitating ART in rat plasma through LC-MS. Method: The analytical procedure involved the extraction of ART and D4-ART (internal standard, IS) from rat plasma through simple protein precipitation. Chromatographic separation was achieved using an isocratic mobile phase (acetonitrile: 5 mM ammonium formate with 0.1% formic acid, 50:50 v/v) at a flow rate of 0.30 mL/min on a Waters XBridge® C18 column with a total run time of 5 min. LC-MS ion transitions monitored were 350.1 and 354.1 for ART and IS, respectively. The method was validated, and the results met acceptance criteria. Results: The lower limit of quantitation achieved was 1 ng/mL, and linearity was 1-8000 ng/mL. The intra- and inter-day precisions were 1.26%-14.20% and 5.49%-13.08%, respectively, in rat plasma. Conclusion: LC-MS offers a novel, specific, sensitive, and accurate method for quantifying ART and it was successfully applied to pharmacokinetic studies of ART in rats.

Emotion categories configure the basic semantic knowledge of the human cognitive structure. Previous studies with people with Williams syndrome (WS) investigated their ability to process basic emotions and the dimensions of emotional valences. However, little is known about the categorization of emotions from the subordinate perspective of lexical words in people with WS. In this study, emotion priming was used as the research paradigm. Three types of emotional valence were used as stimuli: positive, neutral, and negative. Each emotional valence was used as a prime matched to a target in one of these same three types of emotional valence. All participants were asked to judge whether the prime and the target were matched in their emotional valence. People with WS (n = 14, 11M/3F, CA = 10.49, and MA = 6.57) showed priming patterns for emotion valences like those of the typically developing controls. When positive primes were presented, accuracy was higher for positive and negative targets than neutral targets. When neutral primes were presented, accuracy was highest for negative targets. When negative primes were presented, accuracy was the lowest for negative targets. All participants showed high priming accuracy for positive emotions; however, they confused neutral with positive targets. A negative priming effect was observed when negative primes preceded negative targets. Considering previous findings that people with WS show developmental delays in the basic emotions of anger and surprise, this study concludes that people with WS responded least accurately to the classification of emotional valence. The findings regarding the categorization of emotions in people with WS not only advance our understanding of their emotion knowledge and socioemotional cognition but also confirm the superficial enrichment of lexical semantics with weak conceptual change in people with WS. This weakness may result in impaired contextual integration in people with WS.

The Proto-Tethys Ocean played an important role in the formation and evolution of the East Asian continental blocks, and the final closure of the Proto-Tethys Ocean may have led to the first assembly of nearly all East Asian blocks at the northern margin of Gondwana. However, controversy remains about the reconstruction of East Asian blocks at the northern margin of Gondwana. The Tibetan Plateau is located in the northern margin of Gondwana and recorded the entire tectonic evolution from continental rift and drift to subduction and collision during the early Paleozoic. Therefore, it is an important region in which to address tectonic evolution processes of the Proto-Tethys Ocean and Gondwana. Here, we present petrology, zircon U-Pb, Sr-Nd-Hf isotope, and whole-rock geochemical data from newly recognized intermediate-mafic magmatic rocks from the Amdo microcontinent of central Tibet, with a view to gain insights into the nature and geotectonic evolution of the northern margin of Gondwana. Zircon grains from meta-andesites and meta-basites in Amdo yielded magmatic crystallization ages of 490 Ma and 455−450 Ma, respectively. The meta-andesites are characterized by enrichment in large ion lithophile elements (e.g., Rb, Th, U, and K) and depletion in high field strength elements (e.g., Nb, Ta, and Ti) with positive zircon εHf(t) values (+3.4 to +6.4), which were probably derived from partial melting of a depleted mantle source enriched by minor fluids from subducted sediments in a continental arc setting. The meta-basites are tholeiitic and exhibit both mid-ocean-ridge basalt (e.g., flat rare earth element patterns) and arc-like (e.g., elevated Th/Yb ratios) geochemical affinities, in combination with negative zircon εHf(t) (−4.6 to −0.3) and whole-rock εNd(t) (−0.21 to −0.45) values, suggesting that they were probably generated by varying degrees of partial melting of a spinel peridotite source with ∼5%−10% crustal assimilation in a back-arc setting. In this regard, we favor the interpretation that the Amdo microcontinent experienced long-lasting (ca. 530−450 Ma) subduction of the Proto-Tethys Ocean slab before the subsequent collisional accretion of microcontinents. Integrating results from previous studies, we propose that the Amdo microcontinent, South Qiangtang terrane, Qilian-Qaidam terrane, and other East Asian blocks were all located at the northern margin of East Gondwana, which recorded the arc-related magmatism along the proto-Tethyan margin in the early Paleozoic. The closure of the Proto-Tethys Ocean and initial collision along the East Gondwana Proto-Tethyan margin may have been diachronous between ca. 455 and 430 Ma.

The Oulongbuluke Block is an integral part of the Columbia and Rodinia supercontinents, but the lack of rock records from the transitional period between the Columbia and Rodinia supercontinents during the mid–late Mesoproterozoic has impeded our understanding of the tectonic relationship of the Oulongbuluke Block, which lies between the Columbia and Rodinia supercontinents. In this contribution, we present a systematic petrographic, geochemical, and zircon U-Pb-Hf investigation of newly discovered metamafic rocks in the Oulongbuluke Block. The results show that the metamafic rocks have a protolith age of ca. 1.35 Ga and an arcrelated metamorphic age of ca. 1.11–1.09 Ga. The metamafic rock samples are geochemically characterized by relatively high FeOT/MgO and FeOT and low SiO2, MgO, and K2O + Na2O, which shows tholeiitic affinity. These metamafic rocks exhibit slight light rare earth element (LREE) depletion and flat heavy rare earth element (HREE) content with no obvious Eu anomalies and slightly negative Nb, Sr, and Zr anomalies. These conditions are similar to those of enriched midoceanic-ridge basalt (E-MORB) and normal mid-oceanic-ridge basalt (N-MORB). The metamorphic rocks studied also have positive zircon εHf(t) values (2.96–7.04). Hence, the protoliths of the metamafic rocks may have been produced by variable degrees of melting of spinel-phase lherzolite mantle in a mid-oceanic ridge setting that was probably induced by a mantle plume. The presence of metamafic rocks indicates that the Oulongbuluke Block experienced the final breakup of the Columbia supercontinent at ca. 1.35 Ga, and the ca. 1.11–1.09 Ga arc-related metamorphism coincided with the convergence of the Rodinia supercontinent. The tectonic setting of the Oulongbuluke Block changed from a mid-oceanic ridge setting to an arc setting during the mid–late Mesoproterozoic, which was likely a response to the transition from the Columbia supercontinent to Rodinia supercontinent.

The antagonistic behavior in the crowd usually exacerbates the seriousness of the situation in sudden riots, where the antagonistic emotional contagion and behavioral decision making play very important roles. However, the complex mechanism of antagonistic emotion influencing decision making, especially in the environment of sudden confrontation, has not yet been explored very clearly. In this paper, we propose an Emotional contagion-aware Deep reinforcement learning model for Antagonistic Crowd Simulation (ACSED). Firstly, we build a group emotional contagion module based on the improved Susceptible Infected Susceptible (SIS) infection disease model, and estimate the emotional state of the group at each time step during the simulation. Then, the tendency of crowd antagonistic action is estimated based on Deep Q Network (DQN), where the agent learns the action autonomously, and leverages the mean field theory to quickly calculate the influence of other surrounding individuals on the central one. Finally, the rationality of the predicted actions by DQN is further analyzed in combination with group emotion, and the final action of the agent is determined. The proposed method in this paper is verified through several experiments with different settings. The results prove that the antagonistic emotion has a vital impact on the group combat, and positive emotional states are more conducive to combat. Moreover, by comparing the simulation results with real scenes, the feasibility of our method is further confirmed, which can provide good reference to formulate battle plans and improve the win rate of righteous groups in a variety of situations., 14 pages, 9 figures

Weakly supervised object detection (WSOD) has attracted more and more attention since it only uses image-level labels and can save huge annotation costs. Most of the WSOD methods use Multiple Instance Learning (MIL) as their basic framework, which regard it as an instance classification problem. However, these methods based on MIL tends to converge only on the most discriminate regions of different instances, rather than their corresponding complete regions, that is, insufficient integrity. Inspired by the habit of observing things by the human, we propose a new method by comparing the initial proposals and the extension ones to optimize those initial proposals. Specifically, we propose one new strategy for WSOD by involving contrastive proposal extension (CPE), which consists of multiple directional contrastive proposal extensions (D-CPE), and each D-CPE contains encoders based on LSTM network and corresponding decoders. Firstly, the boundary of initial proposals in MIL is extended to different positions according to well-designed sequential order. Then, CPE compares the extended proposal and the initial proposal by extracting the feature semantics of them using the encoders, and calculates the integrity of the initial proposal to optimize the score of the initial proposal. These contrastive contextual semantics will guide the basic WSOD to suppress bad proposals and improve the scores of good ones. In addition, a simple two-stream network is designed as the decoder to constrain the temporal coding of LSTM and improve the performance of WSOD further. Experiments on PASCAL VOC 2007, VOC 2012 and MS-COCO datasets show that our method has achieved the state-of-the-art results., Comment: 15 pages,12 figures, accepted to IEEE Transactions on Image Processing

Trajectory prediction is a fundamental and challenging task for numerous applications, such as autonomous driving and intelligent robots. Current works typically treat pedestrian trajectories as a series of 2D point coordinates. However, in real scenarios, the trajectory often exhibits randomness, and has its own probability distribution. Inspired by this observation and other movement characteristics of pedestrians, we propose a simple and intuitive movement description called a trajectory distribution, which maps the coordinates of the pedestrian trajectory to a 2D Gaussian distribution in space. Based on this novel description, we develop a new trajectory prediction method, which we call the social probability method. The method combines trajectory distributions and powerful convolutional recurrent neural networks. Both the input and output of our method are trajectory distributions, which provide the recurrent neural network with sufficient spatial and random information about moving pedestrians. Furthermore, the social probability method extracts spatio-temporal features directly from the new movement description to generate robust and accurate predictions. Experiments on public benchmark datasets show the effectiveness of the proposed method.

The objective of the present exploration is to examine the nanoliquid flow amid two horizontal infinite plates. The lower plate is stretchable and permeable. The uniqueness of the flow model is assimilated with the Hall effect, variable thermal conductivity, thermal radiation, and irregular heat source/sink. Transmission of mass is enhanced with the impression of chemical reaction incorporated with activation energy. Appropriate similarity transformation is applied to transform the formulated problem into ordinary differential equations (ODEs). The numerical solution is obtained by employing MATLAB software function bvp4c. The dimensionless parameters are graphically illustrated and discussed for the involved profiles. An increasing behavior is exhibited by the temperature field on escalating the Brownian motion, thermophoresis parameter, variable thermal conductivity, and radiation parameter. For larger values of Schmidt number and chemical reaction parameter, the concentration profile deteriorates, while a reverse trend is seen for activation energy. The rate of heat transfer is strengthened at the lower wall on amplifying the Prandtl number. A comparative analysis of the present investigation with already published work is also added to substantiate the envisioned problem.

Continental arcs in active continental margins (especially deep-seated arc magmatism, anatexis, and metamorphism) can be extremely significant in evaluating continent building processes. In this contribution, a Paleozoic continental arc section is constructed based on coeval granulite-facies metamorphism, anatexis, and magmatism on the northern margin of the Qilian Block, which record two significant episodes of continental crust growth. The deeper layer of the lower crust mainly consists of medium-high pressure mafic and felsic granulites, with apparent peak pressure-temperature conditions of 11–13 kbar and 800–950 °C, corresponding to crustal depths of ~35–45 km. The high-pressure mafic granulite and local garnet-cumulate represent mafic residues via dehydration melting involving breakdown of amphibole with anatectic garnet growth. Zircon U-Pb geochronology indicates that these high-grade metamorphic rocks experienced peak granulite-facies metamorphism at ca. 450 Ma. In the upper layer of the lower crust, the most abundant rocks are preexisting garnet-bearing metasedimentary rocks, orthogneiss, and local garnet amphibolite, which experienced medium-pressure amphibolite-facies to granulite-facies metamorphism at depths of 20–30 km at ca. 450 Ma. These metasedimentary rocks and orthogneiss have also experienced partial melting involving mica and rare amphibole at 457–453 Ma. The shallow to mid-crust is primarily composed of diorite-granodiorite batholiths and volcanic cover with multiple origin, which were intruded during 500–450 Ma, recording long-term crustal growth and differentiation episode. As a whole, two episodes of continental crust growth were depicted in the continental arc section on the northern margin of the Qilian Block, including: (a) the first episode is documented in a lithological assemblage composing of coeval mafic-intermediate intrusive and volcanic rocks derived from partial melting of modified lithospheric mantle and subducted oceanic crust during southward subduction of the North Qilian Ocean at 500–480 Ma; (b) the second episode is recorded in mafic rocks derived from partial melting of modified lithospheric mantle during transition from oceanic subduction to initial collision at 460–450 Ma.

Underwater wireless optical communication (UWOC) has attracted much attention recently due to its superiority of high transmission speed. In many UWOC applications, to establish communication links easier, the receiver has quite a wide field. However, the performance of the receiving field is affected by watertight encapsulation in practice, especially when the optical window is produced with plain glass. To study such an influence, in this paper, we first establish a theoretical model based on the Monte Carlo method. Then, we analyze the influence with different structure parameters of watertight encapsulation. The simulation results show that to reduce such an impact, the optical window should be thinner, the detector photosurface and optical window surface should be larger, and the space between the detector and optical window should be smaller. In the ideal situation, the largest workable receiving field is about 96° for UWOC. In other situations, the workable receiving field would be smaller. The simulation method and results presented in this paper are pragmatic and useful to UWOC receiver design.

Underwater wireless optical communication (UWOC) has attracted much attention recently, thanks to its high transmission speed. In many UWOC applications, the transmitter is based on light emitting diodes (LEDs). This is because it has up to a 120° divergence angle, which is helpful with establishing the communication link more easily. However, the light field of such a transmitter is affected by watertight encapsulation in practice. In this paper, we establish a theoretical model based on the Monte Carlo method to study this influence when the watertight optical window is based on plain glass. The results show that both the divergence angle and transmittance become smaller because of the optical window. In order to reduce this influence, the illumination surface, distance from the light source to the optical window, and thickness of the optical window should be smaller, while the optical window surface should be larger. In the ideal situation, the largest divergence angle is 94.4°, which is defined with full width at half-maximum (FWHM). The maximum transmittance is related to the optical materials of the window, while it is 93.54% for quartz glass. When light is modulated with on-off keying (OOK) format, if the signal-to-noise ratio (SNR) is larger than 40 at 0° radiation angle, the UWOC system could work when the angle is up to ± 48.7 ∘ . While the SNR reduces, the workable angle range decreases. The simulation model presented in this paper is convenient to analyze the influence of a watertight optical window with plain glass. The simulation results presented in this paper are useful to the UWOC transmitter design.

This article investigates new inequalities for generalized Riemann–Liouville fractional integrals via the refined $(\alpha ,h-m)$ ( α , h − m ) -convex function. The established results give refinements of fractional integral inequalities for $(h-m)$ ( h − m ) -convex, $(\alpha ,m)$ ( α , m ) -convex, $(s,m)$ ( s , m ) -convex, and related functions. Also, the k-fractional versions of given inequalities by using a parameter substitution are provided.

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

The endogenous cyclic tetradecapeptide SST14 was reported to stimulate all five somatostatin receptors (SSTR1–5) for hormone release, neurotransmission, cell growth arrest and cancer suppression. Two SST14-derived short cyclic SST analogues (lanreotide or octreotide) with improved stability and longer lifetime were developed as drugs to preferentially activate SSTR2 and treat acromegalia and neuroendocrine tumors. Here, cryo-EM structures of the human SSTR2–Gi complex bound with SST14, octreotide or lanreotide were determined at resolutions of 2.85 Å, 2.97 Å, and 2.87 Å, respectively. Structural and functional analysis revealed that interactions between β-turn residues in SST analogues and transmembrane SSTR2 residues in the ligand-binding pocket are crucial for receptor binding and functional stimulation of the two SST14-derived cyclic octapeptides. Additionally, Q1022.63, N2766.55, and F2947.35 could be responsible for the selectivity of lanreotide or octreotide for SSTR2 over SSTR1 or SSTR4. These results provide valuable insights into further rational development of SST analogue drugs targeting SSTR2.

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.

In recent years, crowd counting has increasingly drawn attention due to its widespread applications in the field of computer vision. Most of the existing methods rely on datasets with scarce labeled images to train networks. They are prone to suffer from the over-fitting problem. Further, these existing datasets usually just give manually labeled annotations related to the head center position. This kind of annotation provides limited information. In this paper, we propose to exploit virtual synthetic crowd scenes to improve the performance of the counting network in the real world. Since we can obtain people masks easily in a synthetic dataset, we first learn to distinguish people from the background via a segmentation network using the synthetic data. Then we transfer the learned segmentation priors from synthetic data to real-world data. Finally, we train a density estimation network on real-world data by utilizing the obtained people masks. Our experiments on two crowd counting datasets demonstrate the effectiveness of the proposed method.

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.