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Highlights This study introduces a novel strategy to enhance the high‐temperature electrical performance of the silicone elastomer (SE), while ensuring control over its thermal and mechanical properties for SiC device packaging insulation application. For the same, the ultra‐low‐content inorganic/organic SE nanocomposites are prepared and tested (at room temperature and 150°C) by grafting polyhedral oligomeric silsesquioxane (POSS) nanofillers and doping organic semiconductors. It is found that grafting POSS nanofillers enhances the SE's thermal and mechanical properties. Moreover, doping the grafted SE with different organic semiconductors (ITIC, PCBM, and NTCDA) further improves its electrical properties and charge dynamics at 150°C. The optimal doping content for ITIC, PCBM, and NTCDA is found to be 0.05, 0.10, and 0.15 wt%, respectively. Among these, NTCDA exhibits superior electrical performance at 150°C. Particularly, compared to pure SE, NTCDA doping and POSS grafting reduce the electrical conductivity by an order of magnitude and increase the breakdown strength, charge hopping activation energy, and trap energy level by 65.5%, 0.20 eV and 0.73 eV, respectively. This study finds that organic semiconductors outperform nanostructures in inhibiting electron injection and immobilizing free electrons at high temperatures. Nano‐POSS grafting enhances material properties by reinforced molecular chains. Charge dynamics is studied by space charge and current integrated charge at HT. Organic semiconductors improve electrical properties and charge dynamics at HT. Organic semiconductors outperform nanofillers in immobilizing electrons at HT. The ideal organic semiconductor doping level correlates with its energy gap. [ABSTRACT FROM AUTHOR]

Plant‐derived exosomes (PEs) possess an array of therapeutic properties, including antitumor, antiviral, and anti‐inflammatory capabilities. They are also implicated in defensive responses to pathogenic attacks. Spinal cord injuries (SCIs) regeneration represents a global medical challenge, with appropriate research concentration on three pivotal domains: neural regeneration promotion, inflammation inhibition, and innovation and application of regenerative scaffolds. Unfortunately, the utilization of PE in SCI therapy remains unexplored. Herein, we isolated PE from the traditional Chinese medicinal herb, Lycium barbarum L. and discovered their inflammatory inhibition and neuronal differentiation promotion capabilities. Compared with exosomes derived from ectomesenchymal stem cells (EMSCs), PE demonstrated a substantial enhancement in neural differentiation. We encapsulated isoliquiritigenin (ISL)‐loaded plant‐derived exosomes (ISL@PE) from L. barbarum L. within a 3D‐printed bionic scaffold. The intricate construct modulated the inflammatory response following SCI, facilitating the restoration of damaged axons and culminating in ameliorated neurological function. This pioneering investigation proposes a novel potential route for insoluble drug delivery via plant exosomes, as well as SCI repair. The institutional animal care and use committee number is UJS‐IACUC‐2020121602. [ABSTRACT FROM AUTHOR]

26650 LiFePO4 battery, as an ideal energy storage battery for the smart grid system, has the shortcomings of fast aging speed and large dispersion of aging trend, which is the reason for accelerating the 26650 battery system aging. However, it is noted that the 26650 LiFePO4 battery with high aging trend dispersion shows the characteristics of grouping. Therefore, to prolong the 26650 battery system life, this paper proposes a state-of-charge (SOC) and state-of-health (SOH) double-layer equalization scheme for 26650 LiFePO4 batteries based on a multi-agent blackboard system (MABS) that utilizes these characteristics. Based on MABS, the battery units with similar SOH are clustered into a group by a hierarchical-clustering algorithm. Then, SOH balancing is performed by changing the depth of charge and discharge (DOD) between groups, and SOC balancing is performed within the group. MATLAB simulation results verify the effectiveness of the proposed scheme in ensuring the balance of battery charge and discharge and prolonging the life of the battery energy storage system (BESS). [ABSTRACT FROM AUTHOR]

Electrocatalytic CO2 reduction (ECR) has the potential to generate low-carbon fuels that can alleviate energy scarcity and reduce greenhouse gas emissions. In this study, we prepared a range of Pb–Zn bimetallic catalysts with a core–shell structure using a simple chemical reduction technique based on the differing activity characteristics of the metals. The highest faradaic efficiency for formate (FEformate) was achieved using Pb3Zn1 as the catalyst, with a value of 95.3% at −1.26VRHE in an H-cell (0.5 M KHCO3) and a current density of 11.18 mA cm−2. Notably, in the flow-cell (1 M KOH), FEformate exceeded 90% across a wide potential window, with a maximum FEformate value of 98.4% being achieved. The excellent catalytic performance of the bimetallic catalyst is attributed to its larger specific surface area and faster ECR kinetics, and the synergistic interaction between Pb and Zn improves the selectivity for formate production. [ABSTRACT FROM AUTHOR]

A series of Pb–Sn catalysts were synthesized via facile chemical reduction for electrocatalytic CO2 reduction (ECR). The optimized sample (Pb7Sn1) achieved 90.53% formate faradaic efficiency (FE) at a potential of −1.9 V vs. Ag/AgCl. Electrochemical and material evaluation reveals that its high performance can be attributed to the rich active sites exposed by the high specific surface area of the electrode. In addition, the synergy between Pb and Sn is also a strong contributor to the high selectivity of formate. This work provides some insights into the preparation of simple and efficient ECR catalysts. [ABSTRACT FROM AUTHOR]

• We propose a novel multi-head graph second-order pooling method for graph transformer networks. • We normalize the covariance representation with an efficient feature dropout for generality. • We fuse the first- and second-order information adaptively. • Our proposed model is superior or competitive to state-of-the-arts on six benchmarks. Graph transformer networks (GTNs) have great potential in graph-related tasks, particularly graph classification. GTNs use self-attention mechanism to extract both semantic and structural information, after which a class token is used as the global representation for graph classification.However, the class token completely abandons all information held by nodes, which leads to a huge loss of information and neglects the dependencies among different feature dimensions. Therefore, we propose a M ulti-head G lobal S econd- O rder P ooling (MGSOP) to utilize the rich second-order statistics of all nodes. To this end, a second-order pooling module incorporated with multi-head structure generates multiple covariance representations for GTNs. Then, the first-order representation and concatenation of all covariance matrices are combined by an adaptive fusion module for better performance on different types of data. Furthermore, we introduce an efficient dropout-based normalization to utilize the geometry of covariance representation. Experiments conducted on six real-world graph benchmarks show our MGSOP outperforms its counterparts and achieves competitive results against state-of-the-arts. [ABSTRACT FROM AUTHOR]

This paper reports an enhancement of the nonlinear conductivity, thermal and mechanical properties of micro-silicon carbide/silicone elastomer (m-SiC/SE) composites by adding nano-aluminum nitride (n-AlN) for power module encapsulation applications. The electrical properties (such as nonlinear conductivity characteristics and transient permittivity obtained from polarization current, and trap distributions obtained from thermally stimulated depolarization current) and material properties (including thermo-gravimetric analysis, coefficient of thermal expansion (CTE), and thermal conductivity, tensile strength, strain at break and Young’s modulus) of the pure SE, m-SiC/SE microcomposites, m-SiC/n-AlN/SE hybrid composites are investigated. The effect of the m-SiC fillers and n-AlN fillers on physicochemical properties of the SE matrix is analyzed by FT-IR spectroscopy and crosslinking degree. The measured nonlinear conductivity and transient permittivity are used for electric field simulation under DC stationary and square voltages. It is found that the addition of n-AlN fillers in the SE hybrid composite improves the nonlinear conductivity characteristics and mitigates the electric field under DC stationary and square voltages, compared to the SE microcomposite. Furthermore, the m-SiC/n-AlN/SE hybrid composite has a higher thermal degradation temperature, thermal conductivity, tensile strength, Young’s modulus, and crosslinking degree than the SE microcomposite, whereas their CTE and strain at break are lower. It is elucidated that the m-SiC/n-AlN/SE hybrid composite with enhanced nonlinear conductivity and material properties is a promising packaging material for high-voltage power modules. [ABSTRACT FROM AUTHOR]

Summary: CO2 reduction to produce value‐added chemicals/fuels is generally considered as an effective way to solve the energy crisis and global warming. However, the greatest challenge to the technology is the lack of high‐performance catalysts as this process is quite sluggish under mild conditions. Herein, we have carefully prepared a series of bimetallic PbxCdy nanoparticles (NPs) as well as their monometallic counterparts via a facile chemical reduction. Electrocatalytic performances of obtained catalysts were evaluated with respect to chemical composition, electrolytic potential, and so on. All of them exhibit high performance and achieve high faradaic efficiency for HCOOH production (FEHCOOH) over a voltage window of −1.16 to −1.26 V vs the reversible hydrogen electrode (VRHE). Among them, Pb3Cd1 achieved a maximum FEHCOOH of 96% at −1.16 VRHE and a desirable stability over 12 hours of continuous electrolysis. The excellent performance of Pb3Cd1 can be attributed to the huge specific area of NPs and the synergistic effect of the components. This study shows that efficient bimetallic PbxCdy electrocatalysts have a large application potential for highly selective HCOOH production from CO2. Highlights: Bimetallic PbCd nanoparticles were synthesized by facile chemical reduction for electrocatalytic CO2 reduction.PbCd nanocatalysts performed well in highly active, selective, and stable HCOOH electrosynthesis from aqueous CO2.Pb3Cd1 achieved maximum HCOOH faradaic efficiency of 96% at −1.16 VRHE, a record as far as we know.A stable current density (>7 mA cm−2) can be kept after a 12‐hours continuous electrolysis. [ABSTRACT FROM AUTHOR]

Long short-term memory (LSTM) networks are widely used to handle temporal or sequential data, and have great potential for video recognition. Existing LSTM-based video recognition methods either insert LSTM modules at the end of 2D convolutional neural networks (CNNs), called global LSTM methods, or build networks solely by stacking multiple LSTM modules. Unfortunately, these LSTM-based video recognition methods are not competitive, compared to state-of-the-art 3D CNNs or two-stream CNNs. In order to fully explore the potential of LSTM, this paper rethinks its role in video recognition network architectures and proposes a novel Temporal Grafter Network (TGN). Specifically, we develop an efficient and effective variant of convolutional LSTM module, which is grafted between different stages of very deep 2D CNNs for temporal modeling and delivery. Our TGN can capture local motion patterns of varying scales inherent in feature maps from high to low resolutions, while attending to the spatial context information and modeling global temporal dependency across the whole video. The proposed TGN can capture and transmit temporal information throughout very deep 2D CNNs, overcoming the downsides of existing LSTM-based methods and being able to make full use of the potential of LSTM for effective video recognition and early action recognition. We perform extensive ablation study to verify the effectiveness of our proposed methods, and experiments on three widely used video benchmarks show that our methods can achieve performance matching or better than the state-of-the-arts. [ABSTRACT FROM AUTHOR]

Object detection is usually solved by learning a deep architecture involving classification and localization tasks, where feature learning for these two tasks is shared using the same backbone model. Recent works have shown that suitable disentanglement of classification and localization tasks has the great potential to improve performance of object detection. Despite the promising performance, existing feature disentanglement methods usually suffer from two limitations. First, most of them only focus on the disentangled proposals or predication heads for classification and localization tasks after RPN. While little consideration has been given to that the features for these two different tasks actually are obtained by a shared backbone model before RPN. Second, they are suggested for two-stage objectors and are not applicable to one-stage methods. To overcome these limitations, this paper presents a novel fully task-specific feature learning method for one-stage object detection. Specifically, our method first learns disentangled features for classification and localization tasks using two separated backbone models, where auxiliary classification and localization heads are inserted at the end of the two backbone models for providing a fully task-specific features for classification and localization. Then, a feature interaction module is developed for aligning and fusing task-specific features, which are further used to produce the final detection result. Experiments on MS COCO show that our proposed method (dubbed CrabNet) can achieve clear improvement over counterparts with increasing limited inference time, while performing favorably against state-of-the-arts. [ABSTRACT FROM AUTHOR]

Weakly supervised semantic segmentation (WSSS) based on bounding box annotations has attracted considerable recent attention and has achieved promising performance. However, most of existing methods focus on generation of high-quality pseudo labels for segmented objects using box indicators, but they fail to fully explore and exploit prior from bounding box annotations, which limits performance of WSSS methods, especially for fine parts and boundaries. To overcome above issues, this paper proposes a novel Pixel-as-Instance Prior (PIP) for WSSS methods by delving deeper into pixel prior from bounding box annotations. Specifically, the proposed PIP is built on two important observations on pixels around bounding boxes. First, since objects are usually irregularity and tightly close to bounding boxes (dubbed irregular-filling prior), so each row or column of bounding boxes basically have at least one pixel belonging to foreground objects and background, respectively. Second, pixels near the bounding boxes tend to be highly ambiguous and more difficult to classify (dubbed label-ambiguity prior). To implement our PIP, a constrained loss alike multiple instance learning (MIL) and a labeling-balance loss are developed to jointly train WSSS models, which regards each pixel as a weighted positive or negative instance while considering more effective prior (i.e., irregular-filling and label-ambiguity priors) from bounding box annotations in an efficient way. Note that our PIP can be flexibly integrated with various WSSS methods, while clearly improving their performance with negligible computational overload in training stage. The experiments are conducted on most widely used PASCAL VOC 2012 and Cityscapes benchmarks, and the results show that our PIP has a good ability to improve performance of various WSSS methods, while achieving very competitive results. [ABSTRACT FROM AUTHOR]

The pharmacological activities of liquiritin (LT) are greatly limited by its insolubility and low oral absorption. The purpose of this study was to prepare LT-hydroxypropyl-beta-cyclodextrin inclusion complex (LT-HP-β-CD) to increase water solubility, oral bioavailability and antitumor effect of LT. Herein, saturated aqueous solution method was applied to prepare the LT-HP-β-CD prior to characterization via scanning electron microscope (SEM), infrared radiation (IR) spectroscopy, X-ray diffraction analysis (XRD), and differential scanning calorimetry (DSC). Also, in vitro release and in vivo pharmacokinetics were evaluated. Moreover, the anti-tumor activity of the formulation was investigated in the A549 lung cancer cells. The results of SEM, IR, XRD and DSC showed that LT-HP-β-CD was successfully formulated. In vitro release and oral bioavailability of LT-HP-β-CD compared with the free LT was significantly higher. Successfully, antitumor effect of LT was remarkably enhanced by the preparation of LT-HP-β-CD. Altogether, the LT-HP-β-CD represents a potential carrier for enhancing the water solubility and oral bioavailability of LT coupled with antitumor activity enhancement. [Display omitted] [ABSTRACT FROM AUTHOR]

This article explores the potential of epoxy resin/silicon carbide whisker (EP/SiCw) composites (1 wt%, 2 wt%, 3 wt%, 4 wt%, 5 wt%) as the field-dependent conductivity (FDC) packaging materials for the high-voltage power modules by investigating their thermal and electrical properties at different temperatures. The cross-sectional morphology of the prepared materials is characterized by field emission-scanning electron microscopy (FE-SEM). The thermal analysis consists of differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The electrical properties, such as dc conductivity, dielectric spectroscopy, thermally stimulated discharge current (TSDC), space charge distribution, and dc breakdown strength, are measured. The molecular orbital energy levels of the EP and SiCw monomers are calculated by quantum chemical calculation (QCC) to analyze the effect of EP interfacial trap sites on the electrical properties. The effect of the EP/SiCw interfacial charges and electrical field distortion on the electrical properties of the EP/SiCw composites with different filler content is investigated by the finite-element method (FEM) simulation. It is found that the 2 wt% EP/SiCw composite has a better thermal performance. The 1 wt% has lower real permittivity, lower trap density, lower space charge accumulation, and higher breakdown strength. The EP/SiCw composites have a higher trap level than the pure EP. The nonlinearity percolation threshold of the EP/SiCw composites is 3 wt%. As the filler content increases, the nonlinear conductivity coefficient of the EP/SiCw composites becomes higher, whereas the breakdown strength decreases due to the electric field distortion near the electrodes caused by the apparent hetero charge accumulation at high filler content. [ABSTRACT FROM AUTHOR]

BACKGROUND This study focused on the development of a self‐nanoemulsifying drug delivery system (SNEDDS) to improve, potentially, the solubility and oral bioavailability of liquiritin (LQ). METHODS: The solubility of LQ in different types of excipient, namely oils (OLs), emulsifiers (EMs), and co‐emulsifiers (CO‐EMs), was evaluated, and a pseudo‐ternary phase diagram (PTPD) and the formulation optimization were established. The prepared self‐nanoemulsifying drug delivery system of liquiritin (LQ‐SNEDDS) was assessed using droplet size (DS), zeta potential (ZP), polydispersity index (PDI), droplet morphology, drug release in vitro, and oral bioavailability. RESULTS: After the dilution of the LQ‐SNEDDS, a transparent nanoemulsion was obtained with an acceptable DS (24.70 ± 0.73 nm), ZP (−18.69 ± 1.44 mV), and PDI (0.122 ± 0.006). The LQ‐SNEDDS that was developed had a better release rate in vitro than the free LQ suspension. Pharmacokinetic evaluation showed that the relative oral bioavailability of LQ‐SNEDDS was increased by 5.53 times, and LQ‐SNEDDS exhibited a delayed half life and longer retention time in comparison with those of free LQ. Similarly, LQ‐SNEDDS had a better urate lowering effect and provided better organ protection than free LQ at the same dose (P < 0.05). CONCLUSIONS: The incorporation of LQ into SNEDDS could serve as a promising approach to improve the solubility, oral bioavailability, and anti‐hyperuricemic effect of LQ. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

In this work, aero-optical imaging deviation is investigated for a blunt-headed front-window aircraft, and the deflection angle is introduced to calculate the imaging deviation. This work mainly analyzes the influence of optical sensor position and line of sight (LOS) angle changes on imaging deviation. The results show that the imaging deviation monotonically increases with the increase of LOS angle when the sensor position is in front, and the value of imaging deviation is large. When the sensor position is at the back, the imaging deviation increases with the increase of LOS angle, then decreases, and then increases in the reverse direction, and the value of the imaging deviation is small. [ABSTRACT FROM AUTHOR]

In this study, a novel homogeneous polysaccharide (HVP-1) was purified from the Volvariella volvacea. Its structural characteristics and anti-oxidant activity in vitro were further evaluated. The results revealed that HVP-1 was composed of mannose, glucose, galactose and arabinose in a molar ratio (mol %) of 55.37: 15.74: 25.20: 3.69. Its main chain consisted of →4)- β -D-Gal p -(1→, →6)- α -D-Glc p -(1→, →3)- α -D-Glc p -(1→, →4)- β -D-Man p -(1→ and →3,6)- β -D-Man p -(1→. The branched structure α -L-Ara f -(1→, →2)- β -D-Glc p -(1→ and →6)- β -D-Man p -(1→ were connected to →3,6)- β -D-Man p -(1→ through the O -3 position. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) showed that HVP-1 had porous sheet-like structure with a triple helix conformation. Anti-oxidant activity experiments showed that HVP-1 alleviated H 2 O 2 -induced oxidative damage by reducing the accumulation of reactive oxygen species, increasing the activity of related enzymes in cells, and activating the Nrf2/HO-1 signaling pathway. These results suggested that HVP-1 had the potential to be used as a natural anti-oxidant in functional foods and pharmaceuticals. • A novel homogeneous polysaccharide HVP-1 was isolated and purified from Volvariella volvacea. • The structure and anti-oxidant activity of HVP-1 were characterized. • HVP-1 could alleviate the accumulation of reactive oxygen species and enhance related enzyme activities. • HVP-1 activated the Nrf2/HO-1 signaling pathway. [ABSTRACT FROM AUTHOR]

• Proposed method uses UAV for efficient rapeseed wind response video capture. • Seedling wind prediction for rapeseed lodging: indicators for large-scale cultivation. • By optimizing algorithms, the model's predictive accuracy improved. Farmers commonly enhance rapeseed grain yield by increasing nitrogen fertilizer application and planting density, but this raises lodging susceptibility. Lodging in rapeseed not only substantially diminishes yield and quality but also hampers mechanized harvesting. Thus, timely and accurate prediction of rapeseed lodging resistance, along with targeted field management, is imperative for enhanced productivity. However, current research on timely and accurate prediction of rapeseed lodging resistance remains limited. This study employs unmanned aerial vehicle (UAV) imagery in conjunction with machine learning techniques. UAVs equipped with cameras and downward airflow stimulation are utilized to capture wind-induced responses in rapeseed leaves and extract relevant parameters. Wind-induced response characteristics of rapeseed under different cultivation conditions are analyzed, the relationship between rapeseed vegetation indices and intrinsic properties is explored, and the obtained parameters are subjected to principal component analysis. Using the maturity stage rapeseed lodging index as the output, a predictive model for early-stage lodging is established, comparing the Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP), Particle Swarm Optimization-optimized Backpropagation Neural Network (PSO-BP), and Cuckoo Search-optimized Support Vector Machine (CS-SVM) models. The results reveal a significant correlation between Rapeseed seedling-stage wind-induced response characteristics, certain vegetation indices, and lodging index. Three lodging index prediction models are created using the first four principal components from the analysis, yielding promising outcomes for all three periods (5-leaf stage, 10-leaf stage, and 10 days after the 10-leaf stage) and overall predictions. Among these models, the PSO-BP model exhibits superior performance in predicting rapeseed lodging index (R2 = 0.67, RMSE = 0.464, MAPE = 12.15). Therefore, leveraging wind-induced response characteristics and vegetation indices during the early growth stage enables a certain level of prediction for rapeseed lodging resistance in the mature stage. This study's findings contribute theoretical and technical support to the intelligent and precise management of large-scale rapeseed production. [ABSTRACT FROM AUTHOR]

[Display omitted] • Combined heating and cooling CO 2 system with mechanical subcooling is proposed. • Hydrocarbon mixture is used in mechanical subcooling cycle to improve performance. • Machine learning method is adopted to develop the model and optimize the system. • Multi-objective optimization is conducted considering energy, pollutant and cost. • Optimum hydrocarbon mixture and corresponding concentration ratio is recommended. To meet the simultaneous needs of high temperature disinfection and freezing in the field of food processing, a new concept of combined heating and cooling transcritical CO 2 system integrated with dedicated mechanical subcooling utilizing hydrocarbon mixture is proposed. The system performance in terms of thermodynamics, economy and environment is studied and compared with the baseline combined heating and cooling transcritical CO 2 system and four traditional combined heating and cooling solutions, considering the influence of temperature glide and the heat transfer deterioration. The new proposed system is further optimized by using the machine learning method of artificial neural network and non-dominated sorting genetic algorithm. Multi-objective optimization is conducted considering the objective function of energy efficiency, initial capital cost and life cycle carbon emissions of the new system, to obtain the optimum components and concentration ratio of the hydrocarbon mixture. The results indicate the thermodynamic performance and environmental benefits of subcooling subsystem with hydrocarbon mixture are better than those of the pure system. In contrast to that using pure R290 and R601, the coefficient of performance is enhanced by 8.20 % and 8.13 % and the life cycle carbon emission is reduced by 8.54 % and 9.31 %, respectively, when R290/R601 (50/50) is used. However, the initial capital cost is 9.25 % and 10.23 % higher than that of pure R290 and R601, respectively. Finally, the hydrocarbon mixture corresponding to the optimal design point is R1270/R601a (53/47), the corresponding discharge pressure is 12.86 MPa, and the subcooling degree is 37.50 °C. This study can provide a theoretical reference for the application of CO 2 refrigeration and heat pump technology. [ABSTRACT FROM AUTHOR]

This work focuses on the performance of epoxy microcomposites, nanocomposites, and micro–nano hybrid composites as the packaging material of the power modules. The experiments consist of thermal conductivity, differential scanning calorimetry (DSC), space charge, dc electrical conductivity, thermally stimulated depolarization current (TSDC), and dielectric spectroscopy measurements. Moreover, the ac stationary electric field simulation and the dc transient electric field simulation are performed to analyze the electrical performance of the epoxy composites as the packaging materials in the power module structure under ac voltage and dc voltage, respectively. The ac field simulation uses dielectric spectroscopy data to obtain the electric field and power loss of the epoxy composites at different temperatures and frequencies under the ac voltage. On the other side, the dc electrical conductivity and TSDC experiment data are used for the dc transient electric field simulation to obtain the electric field considering the space charge under the dc voltage. The results show that the optimal addition of the filler content (20 wt% micro-AlN and 5 wt% nano-AlN) in the epoxy micro–nano hybrid composites can reduce the power loss and electric field at 150 °C and 1 MHz, under the ac condition. Furthermore, considering the space charge under the dc voltage, the electric field can also be reduced in epoxy micro–nano hybrid composites compared to pure epoxy. [ABSTRACT FROM AUTHOR]

This paper focuses on the potential of epoxy resin/aluminum nitride (EP/AIN) nanocomposites through experiments and simulation for the packaging material of a 15 kV SiC-IGBT module. For this purpose, space charge, AC breakdown, thermal conductivity and glass transition temperature $(T_{\mathrm{g}})$ are measured. The electric stress reduction effect in EP/AIN nanocomposites is compared to the traditional packaging material at high-frequency AC and square voltages at 150 °C using the electric field simulation. The experimental results show that the 2 wt% EP/AIN nanocomposite exhibits the least space charge accumulation, highest AC breakdown strength and $T_{\mathrm{g}}$ amongst the tested nanocomposites. The offset of metallization layers plays a crucial role in the impact of the electrical properties of packaging materials on the electric field of the packaging structure. When the offset of metallization layers is zero, the maximum electric stress in the EP/AIN nanocomposites is lower than the traditional packaging material, both under the AC and square voltages. In the EP/AIN nanocomposites, as the frequency or the nano-AIN content increases, the maximum electric stress decreases under the AC voltages. Traditional packaging materials have a steeper transient electric field variation than EP/AIN nanocomposites, although the transient process is smoother at higher frequencies under square voltages for all the considered materials. A simplified physical model is proposed to explain the electric field distribution variation in the packaging structure under the AC voltages. [ABSTRACT FROM AUTHOR]

Well-annotated training samples show necessity in achieving high performance of object detection, but collection of massive samples is extremely laborious and costly. Recently, cut-paste based methods show the potential to augment the training samples by cutting the foreground instances and pasting them on some background regions. However, existing cut-paste based methods hardly guarantee the quality of synthetic images due to lack of mechanism to ensure rationality of the pasted instances (e.g., context, geometry and diversity), limiting the effectiveness of data augmentation. To overcome above issues, this paper proposes a novel Constrained Online Cut-Paste (COCP) method, making an attempt to effectively and efficiently augment training data for improving performance of object detection. Specifically, our COCP generates synthetic images by switching instances of same class from various image pairs in each training mini-batch, ensuring context coherence between the cut instances and the pasted backgrounds. Furthermore, two constraints based on geometric consistency and sample diversity are developed to eliminate counterproductive and meaningless switched instances those suffer from significant geometric discrepancy or lack variations, further improving quality of the synthetic images. The experiments are conducted on both MS COCO and PASCAL VOC datasets using various state-of-the-art detectors (e.g., Faster R-CNN, RetinaNet, FCOS and Mask R-CNN). The results show that our proposed COCP can be well generalized to various datasets and detectors with clear performance gains, while performing favorably against its counterparts. [ABSTRACT FROM AUTHOR]

Herein, a nano-micelle drug delivery system was developed to orally improved zingerone's bioavailability and its antitumor effect. Indeed, zingerone-loaded d-α-tocopheryl polyethylene glycol succinate micelles (ZTMs) were effectively prepared, characterised and assessed. The ZTMs had diameter, polydispersity index, and zeta potential of 50.62 ± 0.25 nm, 0.168 ± 0.006, and −28.07 ± 0.33 mV, respectively, coupled with a high entrapment efficiency (m/m, %) were 94.71 ± 2.02. The release rate of ZTMs in three media was significantly greater than that of free zingerone. Intriguingly, results obtained from pharmacokinetic studies showed that the oral bioavailability of the ZTMs was enhanced by 5.10 times in comparison with the free zingerone. Further, the half inhibitory concentration (IC50) of ZTMs and free zingerone was 7.56 μg/ml and 14.30 μg/ml, respectively, on HepG2 cells. Hence, ZTMs may be used as a potential approach to enrich the solubility, bioavailability, and concomitant anti-proliferative effect of zingerone in vitro. [ABSTRACT FROM AUTHOR]

Colon cancer is a common malignant disease with high morbidity and mortality, and miRNA dysfunction has been confirmed as an important reason for cancer development. Several studies have verified miR-605-3p as a tumor inhibitor while its roles in colon cancer remain uncertain. In this study, the specimen of the patients and the cell lines of colon cancer were used to observe the expression of miR-605-3p, and the CCK-8, Transwell assay, and flow cytometry assay were used to observe the functions of miR-605-3p in colon cancer cells. The downstream factors of miR-605-3p were predicted by TargetScan and then were verified by dual-luciferase reporter assay. Moreover, western blot was used to investigate the effect of miR-605-3p on Wnt/β-catenin signal pathway. The result showed that miR-605-3p was extremely downregulated in the pathological tissues and tumor cells, and miR-605-3p could effectively induce the apoptosis and impede the proliferation and invasion of the tumor cells. It was found that KIF3B was a target of KIF3B; decreased KIF3B could reverse the effects of miR-605-3p on colon cancer. Besides, the inactivated Wnt/β-catenin pathway was also observed in colon cells when miR-605-3p was upregulated, and the phenomenon could be rescued by KIF3B upregulation. In conclusion, miR-605-3p could inactivate the Wnt/β-catenin pathway induced via promoting KIF3B expression. [ABSTRACT FROM AUTHOR]

Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potential for improving representation and generalization abilities of deep CNNs. However, integration of global covariance pooling into deep CNNs brings two challenges: (1) robust covariance estimation given deep features of high dimension and small sample size; (2) appropriate usage of geometry of covariances. To address these challenges, we propose a global Matrix Power Normalized COVariance (MPN-COV) Pooling. Our MPN-COV conforms to a robust covariance estimator, very suitable for scenario of high dimension and small sample size. It can also be regarded as Power-Euclidean metric between covariances, effectively exploiting their geometry. Furthermore, a global Gaussian embedding network is proposed to incorporate first-order statistics into MPN-COV. For fast training of MPN-COV networks, we implement an iterative matrix square root normalization, avoiding GPU unfriendly eigen-decomposition inherent in MPN-COV. Additionally, progressive $1\times 1$ 1 × 1 convolutions and group convolution are introduced to compress covariance representations. The proposed methods are highly modular, readily plugged into existing deep CNNs. Extensive experiments are conducted on large-scale object classification, scene categorization, fine-grained visual recognition and texture classification, showing our methods outperform the counterparts and obtain state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Recently, bisdemethoxycurcumin (BDMC), a constituent of turmeric, has been studied widely in view of their various therapeutic effects, namely anti-oxidant, anti-cancer, anti-diabetic, and anti-inflammatory. Since ancient times, turmeric has been extensively used as a naturally occurring traditional Chinese medicine (TCM) and as a crucial home remedy for treatment of many health problems such as inflammation and pain. However, the action of anti-gouty arthritis and analgesic activity of its constituents, especially BDMC, have not been scientifically reported yet. Despite the various bioactivities of BDMC, its utilization in clinics has been restricted owing to poor solubility and bioavailability. This research aimed at enhancing oral bioavailability and pharmacokinetic of BDMC via liposome formulation which was modified with d-α-tocopherol polyethylene glycol 1000 succinate (TPGS or vitamin E TPGS) and was characterized using various parameters both in vitro and in vivo. Also, the analgesic and anti-gouty activities of BDMC-loaded TPGS-modified liposomes were investigated by assessing pain threshold and serum uric acid level in potassium oxonate–induced hyperuricemic rats. As the result, BDMC-loaded TPGS-modified liposomes were formulated successfully with optimal physiochemical properties such as 75.98 ± 5.46 nm (particle size), 0.246 ± 0.011 (polydispersity index), − 38.21 ± 0.29 mV (zeta potential), 96.98 ± 0.17 (encapsulation efficiency (EE%)), and 4.84 ± 0.0089 (drug loading capacity (DL%)). Moreover, the oral bioavailability of liposomized BDMC was approximately 10-fold greater than free BDMC in vivo and in vitro cumulative release rates in pH 1.2 (78%) and pH 7 (68%) respectively. This significantly improved the sustaining drug effect of BDMC compared with free form. In addition, BDMC-TPGS liposome acted as a xanthine oxidase inhibitor to evidently reduce uric acid level in potassium oxonate–induced hyperuricemic rats and remarkably increase pain threshold capacity and reaction time in hot plate test at a dose-dependent manner. Altogether, BDMC-conjugated TPGS liposome could act as favorable nanocarriers against gouty arthritis and intense pain with prospect of overcoming the limitation of BDMC application. [ABSTRACT FROM AUTHOR]

Peripheral biomarkers indicative of brain pathology are critically needed for early detection of Parkinson's disease (PD). In this study, using NanoString and digital PCR technologies, we began by screening for alterations in genes associated with PD or atypical Parkinsonism in erythrocytes of PD patients, in which PD-related changes have been reported, and which contain ~ 99% of blood α-synuclein. Erythrocytic CHCHD2 mRNA was significantly reduced even at the early stages of the disease. A significant reduction in protein and/or mRNA expression of CHCHD2 was confirmed in PD brains collected at autopsy as well as in the brains of a PD animal model overexpressing α-synuclein, in addition to seeing a reduction of CHCHD2 in erythrocytes of the same animals. Overexpression of α-synuclein in cellular models of PD also resulted in reduced CHCHD2, via mechanisms likely involving altered subcellular localization of p300 histone acetyltransferase. Finally, the utility of reduced CHCHD2 mRNA as a biomarker for detecting PD, including early-stage PD, was validated in a larger cohort of 205 PD patients and 135 normal controls, with a receiver operating characteristic analysis demonstrating > 80% sensitivity and specificity. [ABSTRACT FROM AUTHOR]

The agricultural waste is large in number and the utilization rate is extremely low in China, requiring remediated. Formatting the project system and introducing the Public-Private-Partnership (PPP) mode are inevitable to realize the specialization and socialization in resource utilization of agricultural wastes. However, the confusion of financing, management, responsibilities of participants and difficulties in coordinating interests limit the expected effect of the resource utilization of agricultural wastes (RUAW). To this end, combined with the examination of actual cases, this paper constructs a tripartite evolutionary game model of RUAW PPP projects among local government, social capital and farmers, then conducts simulation and case study. We find that the local government does not supervise, social capital acts opportunistically, and farmers choose to cooperate is the evolutionary stable situation, and the cost of supervision for local government and the reward and punishment mechanism of local government to social capital will largely influence the strategy choice of the stakeholders. Strengthening the local government's sense of responsibility and regulatory capacity, optimizing the reward and punishment system, vigorously making technological innovations, and improving the operational capacity of the special purpose vehicle can effectively improve the efficiency of cooperation. The results of the study have some guiding significance for further improving the level of circular agriculture in China even in developing countries and forming a more complete system of resource utilization of agricultural wastes. • The PPP model was used in projects of resource utilization of agricultural wastes. • The local government plays an important role in coordinating between social capital and farmers. • The probability that the social capital will act opportunistically in the PPP project is extremely high. • Farmers' willingness to cooperate is sometimes fragile. [ABSTRACT FROM AUTHOR]

Highly sensitive uncooled mid-wave infrared (MWIR) photodetectors have a very wide range of applications ranging from the sensor and image to communications. Traditional MWIR detection semiconductors require liquid nitrogen cooling to depress dark current, which impeded the wide applications of devices. Here, we report a metal electrode-enhanced double parallel BP/InSe/BP van der Waals heterostructure uncooled MWIR photodetector. The device exhibits ultrahigh light on/off ratio of 108 and a very low dark current of 0.16 pA. The competitive performance includes high photoresponsivity (R) of 27.8 A W−1, excellent specific detectivity (D*) of 3.8 × 1012 cm Hz1/2 W−1, very low noise equivalent power (NEP) of 3.7 × 10−16 W Hz−1/2, and fast response speed of τr = 3.5 μs and τd = 2.4 μs in the visible range. Notably, in the MWIR range, the light on/off ratio of ∼104, NEP of 3.0 × 10−13 W Hz−1/2, and D* of 4.8 × 109 cm Hz1/2 W−1 was realized. The work sheds light on developing a high-performance uncooled MWIR photodetector by designed band alignment. [ABSTRACT FROM AUTHOR]

Isoliquiritigenin (ISL) has a great variety of pharmacological effects especially liver cancer therapy, but its poor solubility, bioavailability and liver targeting have limited its clinical use. In order to solve the aforementioned shortcomings, the TPGS-modified proliposomes loaded with ISL (ISL-TPGS-PLP) was prepared in this study. ISL-TPGS-PLP was fabricated via thin-film dispersion method and was characterized by the appearance, particle size, zeta potential and morphology. HPLC was used to evaluate entrapment efficiency (EE), in vitro release and stability of ISL-TPGS-PLP single or combined while appropriate physicochemical parameters were measured with DLS. Meanwhile, the pharmacokinetics and tissue distribution were also studied after oral administration. The results demonstrated that ISL-TPGS-PLP had a mean size of 23.8 ± 0.9 nm, high EE of 97.33 ± 0.40%. More importantly, nearly 90% ISL was released from ISL-TPGS-PLP within 24 h while only 50% was released from ISL suspension. In the pharmacokinetics study, the area under the curve (AUC 0-24h) of ISL-TPGS-PLP was 1.53 times higher than that of ISL suspension. The Tissue distribution study showed that the ISL released from ISL-TPGS-PLP was higher in the liver than the free ISL suspension. Altogether, ISL-TPGS-PLP could ameliorate the ISL solubility, bioavailability and liver targeting ability, suggesting that ISL-TPGS-PLP could serve as a promising nanocarrier for liver cancer therapy. [ABSTRACT FROM AUTHOR]

This study was designed to investigate the bioavailability and targeting of myricetrin-loaded ternary micelles modified with and without TPGS. The particle diameters of myricetrin-loaded micelles and myricetrin-loaded-TPGS micelle were 30.93 ± 1.34 nm and 26.42 ± 0.89 nm, respectively, while their respective encapsulation efficiencies (m/m, %) were 83.3 ± 1.08 and 93.8 ± 1.18. The release rate of myricetrin in the micellar system clearly exceeded the free myricetrin in the three media (pH 6.8 phosphate buffer, pH 1.2 HCl solution and double distilled water). In vivo studies displayed that the bioavailability of myricetrin mixed micelles was remarkably improved than the free drug after oral administration. Moreover, the results of tissue distribution showed that myricetrin-loaded-TPGS micelles accumulated well in the liver tissue. Based on these results, it was speculated that myricetrin-loaded-TPGS micelles might act as a promising carrier for liver targeting with improved hepatic concentration of myricetrin compared with the myricetrin-loaded micelles. [ABSTRACT FROM AUTHOR]

Abstract The harmful algal blooms are becoming increasingly problematic in the regions that drinking water production depends on surface waters. With a global occurrence, microcystins are toxic peptides produced by multiple cyanobacterial genera in the harmful algal blooms. In this study, we examined the effects of microcystin-LR (MC-LR), a representative toxin of the microcystin family, on vascular development in zebrafish and the apoptosis of human umbilical vein endothelial cells (HUVECs). In zebrafish larvae, MC-LR induced angiodysplasia, damaged vascular structures and reduced lumen size at 0.1 μM and 1 μM, leading to the decrease of the blood flow area in the blood vessels and brain hemorrhage, which showed that MC-LR could dose-dependently inhibit vascular development and cause vascular dysfunction. In MC-LR treated HUVECs, the proportion of early apoptosis and late apoptosis cells increased in a concentration-dependent manner. Different concentrations of MC-LR could also activate caspase 3/9 in HUVECs, increase the level of mitochondrial ROS and reduce mitochondrial membrane potential. Additionally, MC-LR could promote the expression of p53 and inhibit the expression of PCNA. The findings showed that MC-LR could promote apoptosis of HUVECs through the mitochondrial signaling pathway. Combined with these results, MC-LR may promote vascular endothelial cell apoptosis through mitochondrial signaling pathway, leading to angiodysplasia and vascular dysfunction. Graphical abstract Image 1 Highlights • Microcystin-LR induces angiodysplasia and vascular dysfunction. • Microcystin-LR damages vascular structures and reduces lumen size. • Microcystin-LR reduces vascular patency. • Microcystin-LR causes brain hemorrhage. • Microcystin-LR promotes cell apoptosis by the mitochondrial signaling pathway. [ABSTRACT FROM AUTHOR]

Abstract In this present study, we investigated the anti-hyperuricemic and anti-gouty arthritis effect of a puried water-soluble polysaccharide (LJP-1) obtained from Lonicera japonica. A series of characterization of the purified polysaccharide were carried out in this paper. Monosaccharide analysis showed that LJP-1 composed of glucuronic acid, glucose, galactose, arabinose, and xylose at the ratio of 2.43:1:2.09:1.95:1.96, respectively. The estimated molecular weight of LJP-1 was 17.5 kDa. LJP-1 belonged to pyranose and possessed α- and β -glycosidic configurations. Congo red test showed that LJP-1 had a spatial triple helix structure. In pharmacodynamic experiments, the anti-hyperuricemic activity of LJP-1 was studied using hyperuricemic SD rat model induced via potassium oxonate and hypoxanthine. The result showed that LJP-1 could obviously decrease the serum uric acid level and suppress xanthine oxidase (XOD) activity. Moreover, in the gouty arthritis model established by sodium urate crystals, the degree of swelling of the ankle joint, IL-1β, IL-6, TNF-α and COX-2-related inflammatory factors levels in murine serum all declined. Taken together, these results demonstrated that LJP-1 has anti-gouty arthritis effect. Therefore, LJP-1 could serve as a promising candidate for developing novel natural anti-gouty agent. Highlights • A new purified polysaccharide fraction (named LJP-1) was purified from Lonicera japonica. • The structure features of LJP-1 were elucidated. • The anti-hyperuricemic and anti-gouty arthritis activities of LJP-1 were investigated. • Findings showed that LJP-1 could be a promising candidate for preventing and treating gout induced by toxic chemicals. [ABSTRACT FROM AUTHOR]

Highlights • Extruded Zn-0.02 Mg-0.02Cu alloy had superior mechanical properties. • The Zn-based alloy exhibited no toxicity in zebrafish embryos model. • The Zn-based alloy showed good biocompatibility in vivo subcutaneous tissue. Abstract In this study, hot extruded pure Zn and Zn-0.02Mg-0.02Cu alloy were prepared. Compared with the pure Zn, the tensile yield strength, ultimate tensile strength and hardness of the Zn-based alloy were significantly improved, reaching 216.29 ± 3.27 MPa, 262.25 ± 5.02 MPa and 74.40 ± 1.84 HV, respectively, satisfying the criteria of biodegradable stents. Electrochemical corrosion and immersion test showed that the corrosion rates of the Zn-based alloy were higher than those of pure Zn. In addition, the Zn-based alloy exhibited excellent biocompatibility for the development of zebrafish embryos and in vivo subcutaneous tissue without severe inflammatory response. These results indicate that the novel Zn-based alloy has a huge potential in cardiovascular stents. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract [6]-Shogaol, an alkylphenol compound purified from the root and stem of ginger (Zingiber officinale), has attracted considerable interest due to its potential anticancer, antioxidative and antirheumatic properties. However, the oral bioavailability of [6]-shogaol has been severely limited because of its poor solubility. In this study, a significant quantity of high-purity [6]-shogaol (yield: 3.6%; purity: 98.65%) was extracted and encapsulated in solid lipid nanoparticles (SLNs) via high-pressure homogenization (encapsulation efficiency: 87.67%) to improve its solubility and oral bioavailability. The resulting [6]-shogaol-loaded solid lipid nanoparticles (SSLNs) were stable, homogeneous and well-dispersed. Its mean particle size and zeta potential were 73.56 ± 5.62 nm and −15.2 ± 1.3 mV, respectively. Importantly, the in vitro release profile and in vivo oral bioavailability of SSLNs were significantly improved compared with the free drug. Furthermore, the SSLNs could remarkably lower the uric acid level via inhibiting the activity of xanthine oxidase and reduce the production of interleukin-1β (IL-1β) and tumor necrosis factor (TNF-α) in the hyperuricemia/gouty arthritis rat model, when compared to the free [6]-shogaol. Collectively, SLNs could serve as a promising drug delivery system to improve the oral bioavailability of [6]-shogaol for effective treatment of gouty arthritis. [ABSTRACT FROM AUTHOR]

Summary: This study is focused on the isolation and characterisation of two purified polysaccharide fractions (namely PPEP‐1 and PPEP‐2) from Pleurotus eryngii (P. eryngii) and evaluation of their hypolipidaemic effects. The Congo red analysis indicated that PPEP‐2 but not PPEP‐1 possessed a triple‐helix conformation. The atomic force microscope analysis revealed that PPEP‐1 and PPEP‐2 showed different polysaccharide chain conformations. Importantly, the mice treated with PPEP‐1 showed significantly lowered serum levels of total cholesterol (TC), triglyceride (TG) and low‐density lipoprotein cholesterol (LDL‐c) and increased high‐density lipoprotein cholesterol when compared with the hyperlipidaemia mice induced by the high‐fat diet. However, PPEP‐2 revealed less hypolipidaemic effect than PPEP‐1. Additionally, both PPEP‐1 and PPEP‐2 demonstrated remarkable hypolipidaemic effects by decreasing levels of serum TC, TG and LDL‐c in the hyperlipidaemic model induced by P‐407. Taken together, our findings suggest that the P. eryngii polysaccharides, especially PPEP‐1, could be developed as a natural functional food supplement for preventing hyperlipidaemia. [ABSTRACT FROM AUTHOR]

Modeling images/videos with covariance matrices has attracted increasing attentions in various vision tasks, especially in visual classification. For covariances-based visual classification, measuring the distances between covariances is one of the key issues and has been studied for decades. Since the space of covariances is a Riemannian manifold, the geometrical structure of covariances should be favorably considered when designing distance metrics. Although this problem has been widely studied, designing an effective and efficient metric between high-dimensional covariances (HDCOV) for scalable classification is still an open problem. In this paper, we present an information geometry-based distance (IGBD) to tackle this challenge from the perspective of information geometry. Our idea is based on the fact that each covariance can be viewed as a zero-mean Gaussian distribution, and thus the distances between covariances are measured by those between the corresponding Gaussian distributions. The core of our method is to project each distribution, in the form of a set of random samples, to a vector on the tangent space of a common, known distribution on the statistical manifold, based on Fisher information metric and maximum likelihood method. On the tangent space, the Euclidean norm can be used to measure the distances between those sets of projection vectors (or equivalently distributions). The proposed IGBD for HDCOV is computationally efficient and easily combined with a linear support vector machine, suitable for scalable visual classification. The experiments are conducted on various kinds and sizes of benchmarks, and results show the proposed method is efficient and the combination of HDCOV can achieve very competitive performance. [ABSTRACT FROM AUTHOR]

The effect of microcystin-LR (MC-LR) at 50–1000 nmol/L on blood vessel development of zebrafish embryos has been explored. Upon exposure 72-h-post-fertilization (hpf), the hatching rate was significantly reduced and malformation and fatality rates were increased in a dose-dependent manner. MC-LR induced cell cycle arrest in the G0/G1-phase and damaged DNA structure in a dose-dependent manner. In human umbilical vein endothelial cells (HUVECs), MC-LR led to decreased activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) and increased lipid peroxidation. These findings indicated that MC-LR could cause oxidative DNA damage, which mediated cell cycle arrest and inhibited cell proliferation afterwards, and retarded the blood vessel development. [ABSTRACT FROM AUTHOR]

[Display omitted] As the global number of chronic wound patients rises, the financial burden and social pressure on patients increase daily. Stem cells have emerged as promising tissue engineering seed cells due to their enriched sources, multidirectional differentiation ability, and high proliferation rate. However, delivering them in vitro for the treatment of skin injury is still challenging. In addition, bacteria from the wound site and the environment can significantly impact wound healing. In the last decade, 3D bioprinting has dramatically enriched cell delivery systems. The produced scaffolds by this technique can be precisely localized within cells and perform antibacterial actions. In this review, we summarized the 3D bioprinting-based external delivery of stem cells and their antibiosis to improve wound healing. [ABSTRACT FROM AUTHOR]

With rapid development of deep convolutional neural networks (CNNs), more and more high–accuracy CNN architectures have been proposed for multimedia and vision applications. Among them, Bilinear CNN (B-CNN) performs outer product on the outputs of convolutional layers of two stream CNN models, and has attracted a lot of attentions due to its effectiveness in fine-grained categorization. However, the B-CNN fails to use the information inherent in different convolutional layers, meanwhile the cost of computing and storage is higher as evaluation requirements of two CNN models. In this paper, we propose a family of Hyperlayer Bilinear Pooling (HLBP) methods to overcome the limitations of B-CNN. Evaluating a single CNN model only once, our HLBP methods can effectively exploit the second-order statistics of features of multiple layers. Besides fine-grained categorization, we also apply the proposed HLBP methods to content-based image retrieval task. Extensive experiments on seven widely used benchmarks demonstrate that our HLBP methods are superior to the counterparts (e.g., B-CNN), achieving very competitive or better performance compared to state-of-the-arts on both fine-grained categorization and content-based image retrieval tasks. [ABSTRACT FROM AUTHOR]

[6]-Gingerol, one of the components of the rhizome of Ginger, has a variety of biological activities such as anticoagulant, antioxidative, antitumor, anti-inflammatory, antihypertensive, and so forth. However, as one of the homologous phenolic ketones, [6]-gingerol is insoluble in water which limits its applications. Herein, we prepared [6]-gingerol proliposomes through modified thin-film dispersion method, which was spherical or oval, and physicochemically stable with narrow size distribution. Surprisingly, in vitro release of [6]-gingerol loaded proliposome compared with the free [6]-gingerol was significantly higher and its oral bioavailability increased 5-fold in vivo. Intriguingly, its antitumor effect was enhanced in the liposome formulation. Thus, our prepared [6]-gingerol proliposome proved to be a novel formulation for [6]-gingerol, which significantly improved its antitumor effect. [ABSTRACT FROM AUTHOR]

Eight impurities ranging from 0.03 to 0.97% in anidulafungin bulk drug were detected by HPLC. Four impurities (Imp-I, Imp-II, Imp-III and Imp-VIII) among impurities were isolated from the self-prepared or marketed samples of anidulafungin bulk drug by means of preparative HPLC. A thorough study was undertaken to characterize these impurities and based on 1D ( 1 H, 13 C, H-D, DEPT 90 and 135) and 2D (COSY, TOCSY, HSQC, HMBC) NMR and ESI–MS spectral data. Based on the characterization data, Imp-I was found to be known open-chain hydrolysis product formed during the synthesis and degradation. Imp-II and Imp-III was lacked a methyl group at the C-4 and C-8 in anidulafungin, respectively, whereas Imp-VIII contained a methoxy group at the C-23. The latter three new impurities were identified as process-related substances. [ABSTRACT FROM AUTHOR]

A high-quality and stable electron device of aligned gold nanogap arrays is demonstrated by using a well-controlled method with electron beam lithography and focused ion beam. Sub-30-nm nanogap arrays could be precisely fabricated with reproducibility. Field emission (FE) properties of the nanogaps are directly measured in the vacuum chamber of scanning electron microscopy with a nanomanipulator. Experimental investigation and calculations are carried out to reveal the transition process from the leakage current to the FE. Importantly, the controllable method could allow us to readily construct varying nanospacings. Besides, we also illustrate the independence of emission current on the vacuum degree over a large range, widening the applied range of the devices. These studies clearly demonstrate that electronic devices with sub-30-nm vacuum channel can be readily achieved by coupling varying nanogaps into nanostructures. It may pave the way for exploring the physics in tunneling transport devices, and therefore enable a new generation of high-performance, high-speed and low-cost electronic devices. [ABSTRACT FROM AUTHOR]

This paper presents a novel image descriptor to effectively characterize the local, high-order image statistics. Our work is inspired by the Diffusion Tensor Imaging and the structure tensor method (or covariance descriptor), and motivated by popular distribution-based descriptors such as SIFT and HoG. Our idea is to associate one pixel with a multivariate Gaussian distribution estimated in the neighborhood. The challenge lies in that the space of Gaussians is not a linear space but a Riemannian manifold. We show, for the first time to our knowledge, that the space of Gaussians can be equipped with a Lie group structure by defining a multiplication operation on this manifold, and that it is isomorphic to a subgroup of the upper triangular matrix group. Furthermore, we propose methods to embed this matrix group in the linear space, which enables us to handle Gaussians with Euclidean operations rather than complicated Riemannian operations. The resulting descriptor, called Local Log-Euclidean Multivariate Gaussian (L $^2$ EMG) descriptor, works well with low-dimensional and high-dimensional raw features. Moreover, our descriptor is a continuous function of features without quantization, which can model the first- and second-order statistics. Extensive experiments were conducted to evaluate thoroughly L$^2$ EMG, and the results showed that L $^2$ EMG is very competitive with state-of-the-art descriptors in image classification. [ABSTRACT FROM PUBLISHER]

Hybrid nanostructures of quantum dots(QDs) and metallic nanostructure are attractive for future use in a variety of optoelectronic devices. For photodetection applications, it is important that the photoluminescence (PL) of QDs is quenched by the metallic nanostructures. Here, the quenching efficiency of CdSe/ZnS core-shell quantum dots (QDs) with different sized gold nanoparticles (NPs) films through energy transfer is investigated by measuring the PL intensity of the hybrid nanostructures. In our research, the gold NPs films are formed by the post-annealing of the deposited Au films on the quartz substrate. We find that the energy transfer from the QDs to the Au NPs strongly depends on the sizes of the Au NPs. For CdSe/ZnS QDs direct contact with the Au NPs films, the largest energy transfer efficiency are detected when the resonance absorption peak of the Au NPs is nearest to the emission peak of the CdSe/ZnS QDs. However, when there is a PMMA spacer between the QDs layer and the Au NPs films, firstly, we find that the energy transfer efficiency is weakened, and the largest energy transfer efficiency is obtained when the resonant absorption peak of the Au NPs is farthest to the emission peak wavelength of CdSe/ZnS QDs. These results will be useful for the potential design of the high efficiency QDs optoelectronic devices. [ABSTRACT FROM AUTHOR]

An optimized perillaldehyde-loaded liposomal nanoformulation (PAH-LNF) was successfully applied to improve the pharmacological effect of perillaldehyde (PAH) in poloxamer 407-induced hyperlipidemia. Oral administration of PAH-LNF (240 mg/kg per body weight) in rats significantly enhanced solubility and relative bioavailability (270.7%) compared to the free PAH with about 2.7-, 1.5-, 1.3-, 1.3- and 1.5-fold increase in AUC, T 1/2 , MRT, C max and T max , respectively. Tissue distribution study also revealed the accumulation of PAH in the liver, lungs, spleen, kidney, brain and heart in order of decreasing affinity. Moreover, a significant decrease in serum total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) with simultaneous increase in high-density lipoprotein cholesterol (HDL-C) level was observed in the chemically-induced hyperlipidemic mice which further confirmed PAH’s anti-hyperlipidemic properties. Additionally, PAH-LNF also significantly increased the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) with a concurrent decrease in malondialdehyde (MDA) to affirm the antioxidant and hepatoprotective effects of PAH. Thus, liposomal nanoformulation promises to be a useful drug delivery system for the development of PAH. [ABSTRACT FROM AUTHOR]

The bag-of-features (BoF) model for image classification has been thoroughly studied over the last decade. Different from the widely used BoF methods which model images with a pre-trained codebook, the alternative codebook-free image modeling method, which we call codebookless model (CLM), attracts little attention. In this paper, we present an effective CLM that represents an image with a single Gaussian for classification. By embedding Gaussian manifold into a vector space, we show that the simple incorporation of our CLM into a linear classifier achieves very competitive accuracy compared with state-of-the-art BoF methods (e.g., Fisher Vector). Since our CLM lies in a high-dimensional Riemannian manifold, we further propose a joint learning method of low-rank transformation with support vector machine (SVM) classifier on the Gaussian manifold, in order to reduce computational and storage cost. To study and alleviate the side effect of background clutter on our CLM, we also present a simple yet effective partial background removal method based on saliency detection. Experiments are extensively conducted on eight widely used databases to demonstrate the effectiveness and efficiency of our CLM method. [ABSTRACT FROM AUTHOR]

Recently, the Earth Mover׳s Distance (EMD) has demonstrated its superiority in Gaussian mixture models (GMMs) based texture classification. The ground distances between Gaussian components of GMMs have great influences on performance of GMM matching, which however, has not been fully studied yet. Meanwhile, image features play a key role in image classification task, and often greatly impact classification performance. In this paper, we present a comprehensive study of ground distances and image features in texture classification task. We divide existing ground distances into statistics based ones and Riemannian manifold based ones. We make a theoretical analysis of the differences and relationships among these ground distances. Inspired by Gaussian embedding distance and product of Lie Groups distance, we propose an improved Gaussian embedding distance to compare Gaussians. We also evaluate for the first time the image features for GMM matching, including the handcrafted features such as Gabor filter, Local Binary Pattern (LBP) descriptor, SIFT, covariance descriptor and high-level features extracted by deep convolution networks. The experiments are conducted on three texture databases, i.e., KTH-TIPS-2b, FMD and UIUC. Based on experimental results, we show that the uses of geometrical structure and balance strategy are critical to ground distances. The experimental results show that GMM with the proposed ground distance can achieve state-of-the-art performance when high-level features are exploited. [ABSTRACT FROM AUTHOR]

• m-SiC/SE composites loses its nonlinear conductive property at high temperature. • n-AlN fillers' addition achieves stable nonlinear conductivity even at 250 °C. • No conductivity saturation shows up to 250 °C with the n-AlN fillers. • n-AlN fillers reduce low-field conductivity and increase switching electric field. • n-AlN fillers generate anchoring and bridging effect and heterogeneous interface. Due to the micro-silicon carbide/silicone elastomer (m-SiC/SE) composite above the percolation threshold loses its nonlinear conductive characteristics at high temperatures, it is unsuitable for high temperature applications. This paper reports the influence of the nano-AlN (n-AlN) fillers on nonlinear conductive characteristics of m-SiC/SE composites at high temperatures. It is found that the addition of the n-AlN fillers in m-SiC/SE composites achieves a stable nonlinear conductivity without a saturation trend up to 250 °C due to the anchoring and bridging effect of the n-AlN fillers, whereas the heterogenous m-SiC/n-AlN interface barrier decreases the conductivity at low fields and enhances the switching electric field, making it suitable for promising high temperature applications. [ABSTRACT FROM AUTHOR]