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Abstract Bovine parainfluenza virus type 3 (BPIV3) is a viral respiratory pathogen that infects cattle and causes significant economic losses. We generated a recombinant adenovirus called rHAd5-F + HN by expressing the fusion (F) and hemagglutinin-neuraminidase (HN) glycoprotein of BPIV3 using the human adenovirus serotype 5 (rHAd5). We evaluated its effects on humoral and cellular immune responses in mice (n = 45) and calves (n = 9). Serum antibody responses were assessed by enzyme-linked immunosorbent assay (ELISA), hemagglutination inhibition (HI), and neutralising antibodies (NAb). After boosting immunity with rHAd5-F + HN, mice produced significantly higher levels of antibodies against the BPIV3 genotype A and genotype C strains. The production of antibodies exceeded those produced by adenoviruses rHAd5-F and rHAd5-HN, which express the F and HN glycoprotein, respectively. The percentages of splenic CD3+/CD8+T lymphocytes and IL-4+ cytokines in rHAd5-F + HN mice were considerably higher than those in the control group. Mice immunised with rHAd5-F + HN exhibited much lower viral loads in the lungs and tracheas compared to the control group. Additionally, the lungs of mice vaccinated with rHAd5-F + HN showed no notable histopathological changes. On the other hand, rHAd5-F + HN produced a humoral immune response in calves. Following the booster intramuscular injection with the rHAd5-F + HN, the serum antibody levels against BPIV3 genotype C strain were 1:20 452, 1:1024, and 1:426 in calves, as detected by ELISA, HI, and NAb, respectively. The HI and NAb levels against the BPIV3 genotype A strain were 1:213 and 1:85 in calves, respectively. These results indicate that rHAd5-F + HN effectively induced immunity against BPIV3 infection.

ObjectiveThis study aims to apply different machine learning (ML) methods to construct risk prediction models for pulmonary embolism (PE) in hospitalized patients, and to evaluate and compare the predictive efficacy and clinical benefit of each model.MethodsWe conducted a retrospective study involving 332 participants (172 PE positive cases and 160 PE negative cases) recruited from Guangdong Medical University. Participants were randomly divided into a training group (70%) and a validation group (30%). Baseline data were analyzed using univariate analysis, and potential independent risk factors associated with PE were further identified through univariate and multivariate logistic regression analysis. Six ML models, namely Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), Support Vector Machine (SVM), and AdaBoost were developed. The predictive efficacy of each model was compared using the receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). Clinical benefit was assessed using decision curve analysis (DCA).ResultsLogistic regression analysis identified lower extremity deep venous thrombosis, elevated D-dimer, shortened activated partial prothrombin time, and increased red blood cell distribution width as potential independent risk factors for PE. Among the six ML models, the RF model achieved the highest AUC of 0.778. Additionally, DCA consistently indicated that the RF model offered the greatest clinical benefit.ConclusionThis study developed six ML models, with the RF model exhibiting the highest predictive efficacy and clinical benefit in the identification and prediction of PE occurrence in hospitalized patients.

Simulating wind turbine blade icing quickly is important for wind farms to issue early warnings and effectively deal with the adverse effects of cold weather. However, current numerical simulation methods suffer from high computational costs and lack straightforward acceleration techniques for practical ice prediction. Here, we developed a fast and simple blade icing simulation method via an integrated physical simulation and statistical analysis method. This method consists of two steps: firstly, numerical simulation with CFD, and secondly, table look-up calculations. Over 10,000 sets of wind turbine blade icing simulations based on FENSAP-ICE and an NACA64-A17 wing were conducted to develop this method and analyze the influences of environmental factors on blade icing. The results show that ice thickness generally increases with an increase in wind speed, a decrease in temperature, and an increase in liquid water content (LWC), but there is a nonlinear relationship between them. For example, ice thickness has a linear relationship with the LWC within a certain range but hardly changes with a LWC beyond that range. The validation results show that the fast simulation method established in this paper has good consistency with the original numerical simulation method. It can greatly improve the computational efficiency of icing simulations while retaining the accuracy of numerical simulations. It takes less than 1 s to complete over 1000 sets of icing simulations, which offers potential for the fast prediction of wind turbine blade icing in the future.

In traditional cemented carbides, Co is mainly used as a binder. Recently, replacing Co with medium- to high-entropy alloys has shown significant improvements in hardness, fracture toughness, high-temperature oxidation resistance, and corrosion resistance, making it a research focus globally. Both the typical grain refiner Cr3C2 and medium- to high-entropy alloy binders affect the WC grain size in cemented carbides. This study investigates the synergistic grain refinement mechanism of Cr3C2 and medium- to high-entropy alloy binders on WC grains and their impact on the microstructure and mechanical properties of cemented carbides. The results show that increasing the Cr3C2 addition refined WC grains in the WC-CoNiFe alloy, increased coercivity, and enhanced hardness, with transverse rupture strength first increasing and then decreasing. The alloy achieved optimal performance at 0.6 wt.%Cr3C2, with a hardness of 91.25 HRA and transverse rupture strength of 3883.2 MPa.

Electrorheological (ER) technology is an advanced technology based on ER effects. The most common material in ER technology is an electrorheological fluid (ERF), which is a type of smart soft material. The viscosity of ERF is reversibly adjustable by an applied electric field. A new type of electroresponsive soft material, electrorheological elastomer (ERE), which is a derivative of ERFs, has attracted wide attention due to its advantages of not precipitating and easy packaging. ER materials are widely applied in mechanical engineering due to their reversibly tunable characteristics, fast response, and low energy consumption. In addition to basic ER material fabrication and application, ER technology is also used in energy material preparation, oil transportation, and energy storage. The application of ER technology in the energy field provides a good example of the potential applications of ER technology in other fields. This article systematically summarizes the research status and future development prospects of ER technology in materials, energy, and mechanical engineering from the mechanism to application, combined with the latest research results.

Highlights The split-ring topography is studied systematically from wettability, evaporation assembly to optoelectronic devices. An efficient dual-function laser etching scheme has been developed to fabricate the split-ring lyophilic pattern and the lateral electrode array simultaneously. A non-contact human-machine interface based on CsPbBr3 perovskite photodetector arrays has been successfully applied to wearable devices, automobile displays, robot remote control.

Introduction: As a valuable genetic resource, native birds can contribute to the sustainable development of animal production. Tibetan chickens, known for their special flavor, are one of the important local poultry breeds in the Qinghai–Tibet Plateau. However, Tibetan chickens have a slow growth rate and poor carcass traits compared with broilers. Although most of the research on Tibetan chickens focused on their hypoxic adaptation, there were fewer studies related to skeletal muscle development.Methods: Here, we performed the transcriptional sequencing of leg muscles from Tibetan chicken embryos at E (embryonic)10, E14, and E18.Results: In total, 1,600, 4,610, and 2,166 DE (differentially expressed) mRNAs, 210, 573, and 234 DE lncRNAs (long non-coding RNAs), and 52, 137, and 33 DE miRNAs (microRNAs) were detected between E10 and E14, E10 and E18, and E14 and E18, respectively. Functional prediction showed several DE mRNAs and the target mRNAs of DE lncRNAs and DE miRNAs were significantly enriched in sarcomere organization, actin cytoskeleton organization, myofibril, muscle fiber development, and other terms and pathways related to muscle growth and development. Finally, a lncRNA–miRNA–mRNA ceRNA (competing endogenous RNA) network associated with muscle growth and development, which contained 6 DE lncRNAs, 13 DE miRNAs, and 50 DE mRNAs, was constructed based on the screened DE RNAs by Gene Ontology (GO) enrichment. These DE RNAs may play a critical regulatory role in the skeletal muscle development of chickens.Discussion: The results provide a genomic resource for mRNAs, lncRNAs, and miRNAs potentially involved in the skeletal muscle development of chickens, which lay the foundation for further studies of the molecular mechanisms underlying skeletal muscle growth and development in Tibetan chickens.

ObjectiveThe incidence of thyroid dysfunction (TD) and major depressive disorder (MDD) is increasing year by year in the general population. However, the prevalence and correlates of TD in first-episode drug-naive (FEDN) MDD patients have not been explored. This study sought to fill this gap and examine the association between TD and MDD.MethodsWe recruited 1,289 FEDN MDD patients aged 18 ~ 45 years. A total of 1,289 FEDN MDD outpatients were recruited. Demographical and suicide data were collected for each patient, and lipid profiles, thyroid function, and fasting blood glucose (FBG) levels were measured. The Hamilton Depression Scale 17 (HAMD-17) was assessed for depression.ResultsThe prevalence of TD in young FEDN MDD patients was 64.86%. Compared with those without TD, patients with TD had longer duration of illness, greater HAMD score, higher BMI, TG, TC, and LDL-C levels, and higher suicide attempt rates, but lower HDL-C and FBG levels. Further logistic regression indicated that duration of illness, HAMD score, TC, HDL-C, BMI, and FBG levels were significantly associated with TD.LimitationsNo causal relationship can be drawn due to the cross-sectional design.ConclusionTD is common in young FEDN MDD patients. So clinicians should monitor thyroid function in patients with MDD.

Abstract Background Intestinal obstruction can result in inflammatory injury to distant organs, especially the lungs. Stellate ganglion block (SGB) provides sympathetic nervous homeostasis and inhibits the systemic inflammatory response. This study aimed to investigate whether SGB can alleviate acute lung injury by inhibiting phospholipase A2 expression in rats. Methods Thirty healthy male Sprague–Dawley rats were divided into three groups: C group (sham-operated); CLP group (cecal ligation and puncture with intestinal obstruction), and cervical sympathetic trunk transection (CSTT) group (transection of the cervical sympathetic trunk following CLP).Arterial blood samples were obtained to determine the ratio of partial arterial pressure of oxygen (PaO2) to fraction of oxygen in inspired air (FiO2). Venous blood samples were used to evaluate the serum concentrations of chemokines, tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-10 using enzyme-linked immunosorbent assays. Following euthanasia, the lungs were isolated to estimate the wet/dry lung weight (W/D) ratio, evaluate the pathological damage to lung tissues on microscopy, and determine secretory-type phospholipase A2 (sPLA2) expression using western blotting. Results Rats in the CLP group showed increased fatigue, decreased activity levels, and coarse, gray hair. The levels of chemokines, TNF-α, and IL-6 in the CLP and CSTT groups were higher than those in the C group. However, the levels were lower in the CSTT group than those in the CLP group. IL-10 levels in the CLP group were higher and lower than those in the C and CSTT groups, respectively. W/D ratios and PaO2/FiO2 in the CLP and CSTT groups were higher than those in the C group, whereas these ratios in the CSTT group were lower than those in the CLP group. No lung injury was noted in group C, and the lung injury scores were lower in the CSTT group than those in the CLP group. sPLA2 expression levels in the CLP group were higher than those in the C group, whereas these levels in the CSTT group were lower than those in the CLP group. Conclusions sPLA2 overexpression in the lungs may be a pathogenic factor in acute lung injury. CSTT alleviated acute lung injury by inhibiting sPLA2 expression.

Abstract Background Breast cancer has remained the most common malignancy in women over the past two decades. As lifestyle and living environments have changed, alterations to the disease spectrum have inevitably occurred in this time. As molecular profiling has become a routine diagnostic and objective indicator of breast cancer etiology, we analyzed changes in gene expression in breast cancer populations over two decades using The Cancer Genome Atlas database. Methods We performed Heatmap and Venn diagram analyses to identify constantly up- and down-regulated genes in breast cancer patients of this cohort. We used Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to visualize associated functional pathways. Results We determined that three oncogenes, PD-L2, ETV5, and MTOR and 113 long intergenic non-coding RNAs (lincRNAs) were constantly up-regulated, whereas two oncogenes, BCR and GTF2I, one tumor suppression gene MEN1, and 30 lincRNAs were constantly down-regulated. Up-regulated genes were enriched in “focal adhesion” and “PI3K-Akt signaling” pathways, etc., and down-regulated genes were significantly enriched in “metabolic pathways” and “viral myocarditis”. Eight up-regulated genes exhibited doubled or higher expression and the expression of three down-regulated genes was halved or lowered and correlated with long-term survival. Conclusions In this study, we found that gene expression and molecular pathway enrichments are constantly changing with time, importantly, some altered genes were associated with prognostics and are potential therapeutic targets, suggesting that the current molecular subtyping system must be updated to keep pace with this dynamic change.

MicroRNAs (miRs) are reported to regulate myocardial infarction (MI). This study was performed to investigate the function and mechanism of miR-17-5p in myocardial remodelling after MI. Initially, a mouse model of MI was established and MI mice were infected with lentivirus antago-miR-17-5p vector. High expression of miR-17-5p was found in myocardial tissues after MI. After inhibiting miR-17-5p expression, myocardial fibrosis, scarring, and cardiomyocyte apoptosis were improved, LC3-II/LC3-I ratio and Beclin-1 expression were decreased but p62 expression was increased. The dual-luciferase assay suggested that miR-17-5p targeted STAT3 and negatively regulated its expression. Then, after inhibiting STAT3 expression using STAT3 inhibitor S31-201, the fibrosis, scarring, and cardiomyocyte apoptosis were deteriorated, along with the rise of LC3-II/LC3-I and Beclin-1 expression, the reduction of p62 expression and the reversion of MI attenuation. In conclusion, inhibition of miR-17-5p can inhibit myocardial autophagy through targeting STAT3 and then inhibit myocardial remodelling, thereby protecting the myocardium after MI.

Rock grain size parameter is the key parameter of reservoir rock physics analysis. The study found that the relationship between the NMRT2spectrum and rock grain size distribution curve is directly related to NMRT2distribution and grain size distribution of rock, so you can use T2 to retrieve the size distribution of rock NMR spectral data. Based on the calculation of the rock core experiment results of grain size distribution by NMR T2 distribution using the conversion method of piecewise nonlinear calibration for each core, adjusting the calibration parameters to make the grain size distribution calculated with the core analysis of grain size distribution approximation, the error is minimum to obtain each core scale parameter conversion. In the end, the core parameters are classified according to the parameters of pore and permeability. Finally, according to the actual NMR T2 distribution curve inversion of underground rock granularity, the inversion results contrast with the core analysis results, and the reliability of the method is verified to provide accurate, continuous rock size distribution profile analysis of geological reservoir rock physics.

In momentum space, the nodal loop is regarded as a ring-shaped band degeneracy and is classified into type-I and type-II configurations depending on the positive/negative dispersions of the degenerating bands. Here, we experimentally observe a new class of nodal loop in the photonic band structure, employing an artificially designed bilayer metasurface. Such degeneracy, termed type-III nodal loop, is formed by the crossing between a resonant flat band and a positively dispersive band and is protected by mirror symmetry Mz, which manifests in the metasurface’s bilayer architecture. Furthermore, the sequential topological transitions of band degeneracy from the nodal loop via Dirac point to gapped phase are demonstrated at the metasurfaces. Such transitions are enabled by the bilayer design and end with a pair of edge states on the domain wall of gapped systems. Our work reveals that properly engineered bilayer metasurfaces offer rich physics and vast flexibility in two-dimensional topological photonic research through assembling and tunning more symmetries and degrees of freedom along the stacking direction.

A microfluidic device with a microvalve incorporated with intelligent giant electrorheological fluid (GERF) was proposed to actively and accurately control micro-droplet merging in various droplet scales. The GERF is a suspension without an additional electric field, and its viscosity can be increased with the increase in the voltage. A chamber composed of an expanded channel with thin membranes on both sides and several pillars is used to realize droplet merging. The chamber can restrict droplet flow to ensure droplet contact. When the pressure is applied by the microvalve, the membranes would pump up to the merging chamber. Thus, the pressure difference between the merging chamber and GERF channel could be controlled by the membranes’ deformation and influence the merging of the droplets. Therefore, the number of merged droplets from zero to five can be controlled when the flow rate of both the continuous phase and the discrete phase was 0.5 µl/min or from four to zero when the flow rate of the continuous phase was 0.8 µl/min and the discrete phase was 0.2 µl/min. The micro-chip can be easily fabricated without complex equipment, and only a pair of electrodes are required to control the microvalve. Thus, the proposed device has excellent application prospects in chemical synthesis and single-cell analysis.

Background: Structural variations (SVs) are common genetic alterations in the human genome that could cause different phenotypes and diseases, including cancer. However, the detection of structural variations using the second-generation sequencing was limited by its short read length, which restrained our understanding of structural variations.Methods: In this study, we developed a 28-gene panel for long-read sequencing and employed it to Oxford Nanopore Technologies and Pacific Biosciences platforms. We analyzed structural variations in the 28 breast cancer-related genes through long-read genomic and transcriptomic sequencing of tumor, para-tumor, and blood samples in 19 breast cancer patients.Results: Our results showed that some somatic SVs were recurring among the selected genes, though the majority of them occurred in the non-exonic region. We found evidence supporting the existence of hotspot regions for SVs, which extended our previous understanding that they exist only for single nucleotide variations.Conclusion: In conclusion, we employed long-read genomic and transcriptomic sequencing to identify SVs from breast cancer patients and proved that this approach holds great potential in clinical application.

Abstract The organ-on-a-chip (OOAC) is in the list of top 10 emerging technologies and refers to a physiological organ biomimetic system built on a microfluidic chip. Through a combination of cell biology, engineering, and biomaterial technology, the microenvironment of the chip simulates that of the organ in terms of tissue interfaces and mechanical stimulation. This reflects the structural and functional characteristics of human tissue and can predict response to an array of stimuli including drug responses and environmental effects. OOAC has broad applications in precision medicine and biological defense strategies. Here, we introduce the concepts of OOAC and review its application to the construction of physiological models, drug development, and toxicology from the perspective of different organs. We further discuss existing challenges and provide future perspectives for its application.

An on-line modified least-squares identification algorithm is proposed for linear time-varying systems with bounded disturbances under relaxed excitation conditions. An extra term which enhances the tracking ability for time-varying parameters is added to the covariance's update law. An indicator of the regressor's excitation level based on the maximum eigenvalue of the covariance matrix is developed. By combining the maximum eigenvalue with its variation trend shown by the sensitivity of the maximum eigenvalue to change in the covariance matrix, a novel identification law, which is switched between a modified least-squares algorithm and a gradient algorithm based on fixed σ-modification, is proposed. The boundedness of the estimation error and the covariance matrix are guaranteed via Lyapunov stability theory. The superiority of the proposed method is verified by simulations.

Recently, polypropylene (PP) is considered as the potential recyclable HVDC cable insulation material. Ethylene-based copolymer (EBC) and propylene-based copolymer (PBC) were introduced into PP to tailor the properties of PP and make it more capable for HVDC cable insulation application. This paper focused on the effects of two additions on those propertied such as microstructure, thermal properties, electrical properties and space charge accumulation of PP. The results indicated that PBC was uniformly dispersed in the matrix of PP without adhesion, and its particle size did not increase with the increase of its content in the matrix. With the increase of PBC, the glass transition peak of polypropylene decreased slowly, indicating a better performance on flexibility at low temperature. With the increase of content of copolymer, the DC volume resistivity of the composite material decreased gradually, but samples with PBC had higher resistivity than samples with EBC. In the term of space charge, the addition of PBC could help suppressing the accumulation of space charge better. To sum up, PP/PBC composite material could be an option for recyclable DC cable insulation material.

AbstractA buried hill reservoir is a special type of bedrock reservoir, in which fractures are the important reservoir space and main percolation path. However, due to the characteristics of the buried hill reservoir such as deep burial depth and high formation pressure, the fracture width of deep formation is generally in micron level, and the randomness of spatial development brings great difficulties to logging identification and reservoir parameter calculation. Based on the fracture porosity and saturation model of the dual pore model, this paper puts forward the theory of identifying fracture type of buried hill fractured reservoir by using conductivity efficiency. The results show that (1) the fracture angle has no effect on the conductivity efficiency. And we cannot distinguish a high-angle fracture from a low-angle fracture by conductivity efficiency. (2) The values of porosity and water saturation are not directly related to the conductivity efficiency. But porosity and water saturation will affect the connectivity of water in the reservoir and indirectly affect the conductivity efficiency. (3) The conductivity efficiency of the network fracture is usually less than that of the dissolution fracture.

Nonlocal means (NLM), a patch-based nonlocal recovery paradigm, has attracted much attention in recent decades. The decay parameter will greatly affect restoration performance of the NLM method. However, the existing NLM methods with decay parameter adaptation cannot determine this parameter effectively. To address this problem, we have proposed the minimum mean square error (MSE) based decay parameter adaptation method for the NLM denoising. In the proposed method, the globally optimal decay parameter is determined to produce the pre-denoised image based on the derived relation between the global minimum MSE and the decay parameter. Then, the pixel-wise MSE is estimated based on the pre-denoised result and the corresponding method noise. Finally, the optimal pixel-wise decay parameter is obtained by minimizing the pixel-wise MSE to produce the estimated restored image and the boosting strategy is implemented on this image to generate the final denoised result. Extensive simulations on the standard test images and real images corrupted with Gaussian noise and speckle noise demonstrate that the proposed method significantly outperforms some compared NLM methods in noise reduction and detail preservation and can provide better restoration performance than other state-of-the-art denoising methods in most cases in terms of objective metrics and human vision.

Secondary pores are the main reservoir space and transportation channel of oil and gas in reef limestone reservoir. At present, the main method of calculating secondary porosity is restricted by the morphological characteristics of porosity spectrum, regional artificial influence, and accuracy of calculation. We present a new method for calculating secondary porosity of reef limestone reservoir by the nuclear magnetic resonance T2 spectrum which is calibrated by casting thin section. We begin with analyzing and determining the high correlation between the surface porosity of casting thin section and the total porosity. The objective is confirming the feasibility of the method of calculating secondary porosity by using thin-section information calibrate. Then, we use the surface porosity of thin section as the calibrating data and find the T2 relaxation time corresponding to the best correlation between the secondary porosity and the secondary surface porosity of casting thin section, that is, the T2 cutoff value of secondary porosity, through the Monte Carlo method. Finally, we calculate the secondary porosity by using the functional relationship between the secondary surface porosity and the surface porosity. The statistical analysis shows that the method of calculating secondary porosity effectively improves the calculation accuracy of secondary porosity. The secondary porosity calculation results have a high correlation with the reservoir productivity.

Magnetorheological gel (MRG) excels in the material properties in term of adjustability and sedimentation performance, which could upgrade the performances of the current magnetorheological fluid based adjustable devices for structural control and vibration mitigation. However, the characterization and modelling of the stress-strain hysteresis responses of MRG has not been reported in the past, which are fundamental steps towards engineering applications. In this study, the stress-strain hysteresis of polyurethane based MRG sample with 60% carbonyl iron particle weight fraction was characterized under sinusoidal shear excitations with broad ranges of strain amplitude (5%–100%), excitation frequency (0.1 Hz–2 Hz) and magnetic fields (0–0.91 T). Significant stress overshooting phenomenon were observed under the application of low magnetic fields (0.27 T). A structurally-simple and accurate phenomenological model has been established to capture this unique nonlinearity. By validating the experimental results, the proposed model accurately predicts the hysteretic behaviour and the overshoot of the MRG under the excitation scenarios and the magnetic fields considered. Finally, the support vector machine (SVM) was implemented to provide the solution to the model generalization. The SVM-assisted model showed good agreement with the experimental data and can benefit the efficiency and viability in developing controllable MRG-based devices and system.

In this study, we designed and manufactured a series of different microstructure topographical cues for inducing neuronal differentiation of cells in vitro, with different topography, sizes, and structural complexities. We cultured PC12 cells in these microstructure cues and then induced neural differentiation using nerve growth factor (NGF). The pheochromocytoma cell line PC12 is a validated neuronal cell model that is widely used to study neuronal differentiation. Relevant markers of neural differentiation and cytoskeletal F-actin were characterized. Cellular immunofluorescence detection and axon length analysis showed that the differentiation of PC12 cells was significantly different under different isotropic and anisotropic topographic cues. The expression differences of the growth cone marker growth-associated protein 43 (GAP-43) and sympathetic nerve marker tyrosine hydroxylase (TH) genes were also studied in different topographic cues. Our results revealed that the physical environment has an important influence on the differentiation of neuronal cells, and 3D constraints could be used to guide axon extension. In addition, the neurotoxin 6-hydroxydopamine (6-OHDA) was used to detect the differentiation and injury of PC12 cells under different topographic cues. Finally, we discussed the feasibility of combining the topographic cues and the microfluidic chip for neural differentiation research.

The charge transport in polypropylene was studied under DC electric fields at different temperatures. By the experimental measurement and simulation of the BCT model, we studied conduction currents, breakdown strength, and space charge distribution. In particular, the conduction characteristics under high temperature and high field, especially the conduction characteristics before the breakdown, were studied by systematic experiments, and the conduction characteristics and the breakdown mechanism were further studied by simulation. The results show that in the process of measuring conduction currents until breakdown, both high temperature and high electric field will promote charge transport. However, the free volume will increase at high temperature, which will easily lead to faster charge transport and breakdown. In the breakdown process at different temperatures, there are different breakdown mechanisms. At 20–60 °C, the electric breakdown process has mainly occurred in polypropylene film, and the breakdown strength is almost unchanged. At 80 °C, electric breakdown and thermal breakdown act together, and the charge transport is faster, and the breakdown field becomes smaller. Finally, we conclude that thermal stress plays a very important role in charge transport. In a high-temperature environment, the volume expansion of polypropylene will promote charge transport, and the insulation of polypropylene capacitor films will be damaged.

Lightning is the main cause of transmission line failure, and it is important to improve the lightning protection level of the transmission line for the stability of the power system. Traditional solutions for the shielding failure of transmission lines is to use the electrical geometric model method. However, with the improvement of the voltage level, the physical size increases, and the calculation of lightning protection for ultrahigh-voltage dc lines has a greater difference with operating experience. Based on the Ningxia-Shandong dc transmission lines in China, this study utilised the lead development model to describe the flashover of insulators and the breakdown of the gaps. A comprehensive calculation method of shielding failure trip-out rate considering terrain, earth resistance and weather was proposed. The accuracy was much higher when compared with the traditional calculation and the result can be a reference for other similar calculation for dc lines.

Speckle reduction remains a critical issue for ultrasound image processing and analysis. The nonlocal means (NLM) filter has recently attached much attention due to its competitive despeckling performance. However, the existing NLM methods usually determine the similarity between two patches by directly utilizing the gray-level information of the noisy image, which renders it difficult to represent the structural similarity of ultrasound images effectively. To address this problem, the NLM method based on the simple deep learning baseline named PCANet is proposed by introducing the intrinsic features of image patches extracted by this network rather than the pixel intensities into the pixel similarity computation. In this approach, the improved two-stage PCANet is proposed by using Parametric Rectified Linear Unit (PReLU) activation function instead of the binary hashing and block histograms in the original PCANet. This model is firstly trained on the ultrasound database to learn the convolution kernels. Then, the trained PCANet is utilized to extract the intrinsic features from the image patches in the pre-denoised version of the noisy image to be despeckled. These obtained features are concatenated together to determine the structural similarity between image patches in the NLM method, based on which the weighted mean of all pixels in a search window is computed to produce the final despeckled image. Extensive experiments have been conducted on a variety of images to demonstrate the superiority of the proposed method over several well-known despeckling algorithm and the PCANet based NLM method using ReLU function and sigmoid function. Visual inspection indicates that the proposed method outperforms the compared methods in reducing speckle noise and preserving image details. The quantitative comparisons show that among all the evaluated methods, our method produces the best structural similarity index metrics (SSIM) values for the synthetic image, as well as the highest equivalent number of looks (ENL) value for the simulated image and the clinical ultrasound images.

Calcium carbonate biomimetic crystallization remains a topic of interest with respect to biomineralization areas in recent research. It is not easy to conduct high-throughput experiments with only a few macromolecule reagents using conventional experimental methods. However, the emergence of microdroplet array technology provides the possibility to solve these issues efficiently. In this article, surface-tension-confined droplet arrays were used to fabricate calcium carbonate. It was found that calcium carbonate crystallization can be conducted in surface-tension-confined droplets. Defects were found on the surface of some crystals, which were caused by liquid flow inside the droplet and the rapid drop in droplet height during the evaporation. The diameter and number of crystals were related to the droplet diameter. Polyacrylic acid (PAA), added as a modified organic molecule control, changed the CaCO3 morphology from calcite to vaterite. The material products of the above experiments were compared with bulk-synthesized calcium carbonate by scanning electron microscopy (SEM), Raman spectroscopy and other characterization methods. Our work proves the possibility of performing biomimetic crystallization and biomineralization experiments on surface-tension-confined microdroplet arrays.

Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend on a high-accuracy target with feature points that are difficult and costly to manufacture and. In complex light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of a high-accuracy target with certain-sized feature points for calibration is not feasible under such complex conditions. To solve these problems, a calibration method based on unknown-sized elliptical stripe images is proposed. With known intrinsic parameters, the proposed method adopts the elliptical stripes located on the parallel planes as a medium to calibrate BSVS online. In comparison with the common calibration methods, the proposed method avoids utilizing high-accuracy target with certain-sized feature points. Therefore, the proposed method is not only easy to implement but is a realistic method for the calibration of BSVS with optical filter. Changing the size of elliptical curves projected on the target solves the difficulty of applying the proposed method in different fields of view and distances. Simulative and physical experiments are conducted to validate the efficiency of the proposed method. When the field of view is approximately 400 mm × 300 mm, the proposed method can reach a calibration accuracy of 0.03 mm, which is comparable with that of Zhang’s method.