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Abstract Untethered magnetic soft robots capable of performing adaptive locomotion and shape reconfiguration open up possibilities for various applications owing to their flexibility. However, magnetic soft robots are typically composed of soft materials with fixed modulus, making them unable to exert or withstand substantial forces, which limits the exploration of their new functionalities. Here, water‐induced, shape‐locking magnetic robots with magnetically controlled shape change and water‐induced shape‐locking are introduced. The water‐induced phase separation enables these robots to undergo a modulus transition from 1.78 MPa in the dry state to 410 MPa after hydration. Moreover, the body material's inherent self‐healing property enables the direct assembly of morphing structures and magnetic soft robots with complicated structures and magnetization profiles. These robots can be delivered through magnetic actuation and perform programmed tasks including supporting, blocking, and grasping by on‐demand deformation and subsequent water‐induced stiffening. Moreover, a water‐stiffening magnetic stent is developed, and its precise delivery and water‐induced shape‐locking are demonstrated in a vascular phantom. The combination of untethered delivery, on‐demand shape change, and water‐induced stiffening properties makes the proposed magnetic robots promising for biomedical applications.

Abstract Elastomers are widely used in daily life; however, the preparation of degradable and recyclable elastomers with high strength, high toughness, and excellent crack resistance remains a challenging task. In this report, a polycaprolactone‐based poly(urethane‐urea) elastomer is presented with excellent mechanical properties by optimizing the arrangement of hard segment clusters. It is found that long alkyl chains of the chain extenders lead to small and evenly distributed hard segment clusters, which is beneficial for improving mechanical properties. Together with the multiple hydrogen bond structure and stress‐induced crystallization, the obtained elastomer exhibits a high strength of 63.3 MPa, an excellent toughness of 431 MJ m−3 and an outstanding fracture energy of 489 kJ m−2, while maintaining good recyclability and degradability. It is believed that the obtained elastomer holds great promise in various application fields and it contributes to the development of a sustainable society.

IntroductionThe micronutrient deficiency of iron and boron is a common issue affecting the growth of rapeseed (Brassica napus). In this study, a non-destructive diagnosis method for iron and boron deficiency in Brassica napus (genotype: Zhongshuang 11) using hyperspectral imaging technology was established.MethodsThe recognition accuracy was compared using the Fisher Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) recognition models. Recognition results showed that Multiple Scattering Correction (MSC) could be applied for the full band hyperspectral data processing, while the LDA models presented better performance on establishing the leaf iron and boron deficiency symptom recognition than the SVM models.ResultsThe recognition accuracy of the training set reached 96.67%, and the recognition rate of the prediction set could be 91.67%. To improve the model accuracy, the Competitive Adaptive Reweighted Sampling algorithm (CARS) was added to construct the MSC-CARS-LDA model. 33 featured wavelengths were selected via CARS. The recognition accuracy of the MSC-CARS-LDA training set was 100%, while the recognition accuracy of the MSC-CARS-LDA prediction set was 95.00%.DiscussionThis study indicates that, it is capable to identify the iron and boron deficiency in rapeseed using hyperspectral imaging technology.

Abstract Underwater adhesives receive extensive attention due to their wide applications in marine explorations and various related industries. However, current adhesives still suffer from excessive water absorption and lack of spontaneity. Herein, we report an autonomous underwater adhesive based on poly(2-hydroxyethyl methacrylate-co-benzyl methacrylate) amphiphilic polymeric matrix swollen by hydrophobic imidazolium ionic liquid. The as-prepared adhesive is tough and flexible, showing little to none instantaneous underwater adhesion onto the PET substrate, whereas its adhesion energy on the substrate can grow more than 5 times to 458 J·m−2 after 24 hours. More importantly, this process is entirely spontaneous, without any external pressing force. Our comprehensive studies based on experimental characterizations and molecular dynamic simulations confirm that such autonomous adhesion process is driven by water-induced rearrangement of the functional groups. It is believed that such material can provide insights into the development of next-generation smart adhesives.

Abstract Citrus fruit coloration is one of the vital quality traits that is determined primarily by the composition and content of carotenoids. Natural citrus fruit pigment mutants are available to study diverse and complex carotenoid metabolism. Here, ‘Jinlegan’ (MT) tangor is a spontaneous bud mutant derived from ‘Shiranuhi’ (WT) with distinctive bright yellow fruit. High performance liquid chromatography (HPLC) analysis revealed that the yellowish MT flavedo and pulp were primarily caused by the decrease in total carotenoid content. The total carotenoid content in MT flavedo was reduced by 75% (79.98 μg/g DW) compared with that in WT (318.40 μg/g DW), including approximately 84%, 80%, and 60% reductions in the contents of β-cryptoxanthin, violaxanthin and zeaxanthin, respectively. The total carotenoid content in MT pulp was 60% lower (10.09 μg/g DW) than that in WT pulp (26.61 μg/g DW), which was mainly due to a 70% and 30% decrease in the contents of β-cryptoxanthin and zeaxanthin, respectively. To explore the molecular mechanism underlying carotenoid variation in MT, RNA-seq analyses were performed on the flavedo and pulp of WT and MT at five developmental stages. The reduced expression of phytoene synthase (Cr PSY) and β-carotene hydroxylase 1 (Cr BCH1) in the flavedo and pulp of MT at the breaker stage might be the major cause of the reduction in carotenoids. Weighted gene co-expression network analysis (WGCNA) further identified 23 key transcription factors that are closely associated with carotenoid accumulation. This study demonstrated a comprehensive picture of the metabolic and transcriptional alterations of a unique yellowish citrus fruit mutant, which provides new insights into the molecular regulation of carotenoid accumulation in citrus fruit.

It is well known that heat is generated when an electric current passes through an electrical conductor. While various applications in our daily lives and industries utilize the heating of electronic conductors, little attention has been paid to the potential of ionic conductors for heating purposes. This is because of the “inevitable” electrochemical reactions, which can result in unwanted electrolysis of conductors, corrosion of electrodes, and surface fouling. This paper reports the Joule heating of ionic conductors without electrochemical reactions. Electricity with a zero-phase frequency is employed to suppress the electrolysis of ionic conductors at high voltages. Demonstrations with various ionic conductors, both liquids and solids, show highly efficient energy conversion free of electrochemical reactions. This heating method is simple, direct, fast, clean, and uniform, and it has great potential in numerous industrial and household applications.

Abstract The increase in CO2 concentration in the atmosphere has led to global warming, which draws great attention all over the world. Adsorption is considered as an effective method for CO2 capture and stabilizing the increasing CO2 concentration. Metal–organic frameworks (MOFs) are promising materials for carbon capture. However, the direct use of MOF powders may lead to issues such as high pressure drop, pipe clogging, and handling difficulties in applications. Herein, a phase inversion strategy is reported to prepare SIFSIX‐3‐Ni@PAN composite beads. The prepared composites exhibit hierarchically porous structure with uniform MOF distribution inside the materials and good mechanical stability. The MOF content can be well controlled and composites with up to 70% loading are prepared. Finally, the obtained materials possess high CO2 capture capacity, even at low CO2 concentrations (1.19 mmol g−1 at 0.01 bar and 298 K).

Hybrid pairing of the corresponding silkworm species is a pivotal link in sericulture, ensuring egg quality and directly influencing silk quantity and quality. Considering the potential of image recognition and the impact of varying pupal postures, this study used machine learning and deep learning for global modeling to identify pupae species and sex separately or simultaneously. The performance of traditional feature-based approaches, deep learning feature-based approaches, and their fusion approaches were compared. First, 3600 images of the back, abdomen, and side postures of 5 species of male and female pupae were captured. Next, six traditional descriptors, including the histogram of oriented gradients (HOG), and six deep learning descriptors, including ConvNeXt-S, were utilized to extract significant species and sex features. Finally, classification models were constructed using the multilayer perceptron (MLP), support vector machine, and random forest. The results indicate that the {HOG + ConvNeXt-S + MLP} model excelled, achieving 99.09% accuracy for separate species and sex recognition and 98.40% for simultaneous recognition, with precision–recall and receiver operating characteristic curves ranging from 0.984 to 1.0 and 0.996 to 1.0, respectively. In conclusion, it can capture subtle distinctions between pupal species and sexes and shows promise for extensive application in sericulture.

Response regulator (RR) is an important component of the cytokinin (CK) signal transduction system associated with root development and stress resistance in model plants. However, the function of RR gene and the molecular mechanism on regulating the root development in woody plants such as citrus remain unclear. Here, we demonstrate that CcRR5, a member of the type A RR, regulates the morphogenesis of root through interacting with CcRR14 and CcSnRK2s in citrus. CcRR5 is mainly expressed in root tips and young leaves. The activity of CcRR5 promoter enhanced by CcRR14 was proved with transient expression assay. Seven SnRK2 family members with highly conserved domains were identified in citrus. Among them, CcSnRK2.3, CcSnRK2.6, CcSnRK2.7, and CcSnRK2.8 can interact with CcRR5 and CcRR14. Phenotypic analysis of CcRR5 overexpressed transgenic citrus plants indicated that the transcription level of CcRR5 was associated with root length and lateral root numbers. This was also correlated to the expression of root-related genes and thus confirmed that CcRR5 is involved in the root development. Taken together, the results of this study indicate that CcRR5 is a positive regulator of root growth and CcRR14 directly regulates the expression of CcRR5. Both CcRR5 and CcRR14 can interact with CcSnRK2s.

Salt stress damage to plants has been becoming a global concern for agriculture. The application of potassium fulvic acid (PFA) is a promising strategy to alleviate the damage to plants and improve soil quality. However, the study of PFA on plant growth and rhizosphere microbial community remains limited. In this study, microcosmic experiments were conducted to verify the effect of PFA on citrus. Trifoliate orange (Poncirus trifoliata), the most important citrus rootstock, was used to evaluate the effect of PFA on salt damage. The results showed that PFA significantly increased the contents of chlorophyll a, chlorophyll b and carotenoid by 30.09%, 17.55% and 27.43%, and effectively avoided the yellowing and scorching of leaves under salt stress. Based on the results of two-way ANOVA, the mitigation of salt stress on trifoliate seedlings primarily attributed to the enhancement of protective enzyme activities, K+/Na+ ratio and the contents of soluble sugar, soluble protein and proline. Moreover, PFA enhanced neutral protease (S-NPT), sucrase (S-SC) and urease (S-UE) of rhizosphere soil and improved soil nutrition status. The abundance of Bacillus, a kind of rhizosphere beneficial bacteria, was improved by PFA under salt stress, which was mainly associated with the increased activities of S-NPT, S-SC and S-UE. Overall, the application of PFA showed great potential for the alleviation of salt damage on citrus.

Abstract Developing smart iontronic materials is highly desired for eradicating the widely occurring potential short‐circuit hazard and subsequent safety problems caused by high ambient humidity. In this work, a humidity‐responsive ionogel (HRIG) based on a poly(benzyl methacrylate) matrix swollen by hydrophobic ionic liquid and hygroscopic lithium salt is reported. The HRIG exhibits an anomalous decrease in ionic conductivity upon hydration by increased humidity, totally differing from traditional ionic conductors, which are usually more conductive due to the plasticizing effect of water molecules. This unique ionogel shows a dramatic decrease in ionic conductivity (as much as 102) when exposed to humidity. The conductive pathway within the HRIG would be shut down spontaneously above a critical relative humidity due to water‐induced phase separation. Moreover, this transition can be perfectly reversed when the ambient humidity drops. A humidity‐responsive smart supercapacitor that can be switched on and off by capturing humidity changes is designed for demonstration. It is believed that such unusual HRIG material will provide new insights into the development and applications of smart iontronics.

ABSTRACT Aims/Introduction The union of dipeptidyl peptidase‐4 inhibitors and insulin in patients with type 2 diabetes and chronic kidney disease provides satisfactory glucose management without increasing adverse events (AEs). This research appraised the therapeutic effect and safety of combination therapy in patients with type 2 diabetes and chronic kidney disease. Materials and Methods We carried out a meta‐analysis of randomized controlled trials to analyze AEs, hypoglycemia, serious AEs, severe hypoglycemia, estimated glomerular filtration rate, fasting plasma glucose, glycated hemoglobin, insulin dose, low‐density lipoprotein cholesterol, uric acid and weight between combination treatment groups and control groups by searching the Cochrane Library, Excerpta Medica Database (Embase), PubMed and Web of Science databanks until October 2020. Results Five studies (6 trials, 1,278 participants) met the inclusion criteria. The evidence quality ranged from moderate to high. Glycated hemoglobin (standardized mean difference −0.29, 95% confidence interval −0.44 to −0.14) and insulin dose (standardized mean difference −0.16, 95% confidence interval −0.29 to −0.02) were obviously smaller in the combination cure patients than in the control patients. Compared with the control groups, combination treatment did not increase AEs, hypoglycemia, serious AEs or severe hypoglycemia. Conclusions This study showed the effectiveness and safety of dipeptidyl peptidase‐4 inhibitors bonded with insulin in patients with type 2 diabetes and chronic kidney disease, but the protective actions of this cure on kidney and cardiovascular outcomes, as well as the functions of other dipeptidyl peptidase‐4 inhibitors, need to be affirmed by more good‐quality randomized controlled trials.

Morphogenesis of root is a vital factor to determine the root system architecture. Cytokinin response regulators (RRs) are the key transcription factors in cytokinin signaling, which play important roles in regulating the root morphogenesis. In this study, 29 RR proteins, including 21 RRs and 8 pseudo RRs, were identified from the genome of citrus, and termed as CcRR1-21 and CcPRR1-8, respectively. Phylogenetic analysis revealed that the 29 CcRRs could be classified into four types according to their representative domains. Analysis of cis-elements of CcRRs indicated that they were possibly involved in the regulation of growth and abiotic stress resistance in citrus. Within the type A and type B CcRRs, CcRR4, CcRR5, CcRR6 and CcRR16 highly expressed in roots and leaves, and dramatically responded to the treatments of hormones and abiotic stresses. CcRR2, CcRR10, CcRR14 and CcRR19 also highly expressed in roots under different treatments. Characteristic analysis revealed that the above 8 CcRRs significantly and differentially expressed in the three zones of root, suggesting their functional differences in regulating root growth and development. Further investigation of the 3 highly and differentially expressed CcRRs, CcRR5, CcRR10 and CcRR14, in 9 citrus rootstocks showed that the expression of CcRR5, CcRR10 and CcRR14 was significantly correlated to the length of primary root, the number of lateral roots, and both primary root and the number of lateral roots, respectively. Results of this study indicated that CcRRs were involved in regulating the growth and development of the root in citrus with different functions among the members.

Different soybean varieties vary greatly in their nutritional value and composition. Screening for superior varieties is also essential for the development of the soybean seed industry. The objective of the paper was to analyze the feasibility of terahertz (THz) frequency-domain spectroscopy and chemometrics for soybean variety identification. Meanwhile, a grey wolf optimizer-support vector machine (GWO-SVM) soybean variety identification model was proposed. Firstly, the THz frequency-domain spectra of experimental samples (6 varieties, 270 in total) were collected. Principal component analysis (PCA) was used to analyze the THz spectra. After that, 203 samples from the calibration set were used to establish a soybean variety identification model. Finally, 67 samples from the test set were used for prediction validation. The experimental results demonstrated that THz frequency-domain spectroscopy combined with GWO-SVM could quickly and accurately identify soybean varieties. Compared with discriminant partial least squares (DPLS) and particles swarm optimization support vector machine, GWO-SVM combined with the second derivative could establish a better soybean variety identification model. The overall correct identification rate of its prediction set was 97.01%.

Soybeans have the characteristics of balanced amino acid species and high nutritional value. In this article, the feasibility of the identification soybean from three typical origins (Argentina, the United States and China) by interval partial least squares (iPLS) optimized terahertz (THz) spectroscopy combined with chemometrics was investigated. Firstly, the THz frequency-domain spectrum was optimized using iPLS. Then, 168 soybean samples were selected as the correction set, and soybean origin identification models were respectively built using the extreme learning machine (ELM), genetic algorithm support vector machine (GA-SVM), and artificial bee colony algorithm support vector machine (ABC-SVM) combined with 8 pre-processing techniques. Finally, the models were verified through 57 samples of the test set and the comprehensive identification accuracy rate of the ABC-SVM model reached 94.74%. The experimental results showed that after iPLS optimization and appropriate pre-processing technique, THz spectroscopy and chemometrics could accurately identify the origin of soybean.

Renal fibrosis, in particular tubulointerstitial fibrosis, which is characterized by an increased extracellular matrix (ECM) formation and development in the interstitium, is the common end pathway for nearly all progressive kidney disorders. One of the sources for this matrix is the epithelial to mesenchymal transition (EMT) from the tabular epithelium. The driving force behind it is some profibrotic growth factors such as transforming growth factor-β (TGF-β) which is responsible for the formation of collagen in renal fibrosis. miR-29c, which is an antifibrotic microRNA, downregulates renal interstitial fibrosis by downregulating the TGF-β and collagen. However, it is not known whether miR-29c mediates the TGF-β1-driven PI3K-Akt pathway and Col-1 triggering within NRK-52E cultures. The main objective of this investigation was to examine the influence of miR-29c on the downregulation of the TGF-β1-driven PI3K-Akt pathway and Col-1 triggering in NRK-52E cultures. This study revealed that miR-29c inhibited TGF-β1 expression in NRK-52E cell cultures. Overexpression of miR-29c significantly inhibits NRK-52E culture proliferation mediated by TGF-β1. miR-29c inhibited the expression of Col-1 and decreased PI3K/Akt phosphorylation. These findings revealed a novel mechanism by which miR29c inhibits the proliferation of renal interstitial fibrotic cultures by downregulating the PI3k-Akt pathway, which is controlled by TGF-β1.

The stereo matching technology has been widely used nowadays for robot guidance, depth of field rendering, and video processing applications. The binocular stereo matching technology collects two images of the same scene from different views, computes the disparity, and then determines the 3-D depth of the object using the triangulation theory. In this paper, we propose a new deep-learning-based stereo matching algorithm called convolutional neural network WTADP (CNN-WTADP). The commonly used WTA method ignores the disparity constraint of the neighboring pixels and is prone to be affected by noise, so the obtained original disparity map may contain a lot of abnormal values and mismatched points. To solve this problem, we construct a CNN for matching cost computation and use a novel global method of dynamic programming based on WTA for disparity selection. Steps for the CNN-based computation of the matching cost are presented, and the post-processing algorithm is used to obtain the final determination of the disparity map. The Middlebury stereo dataset and stereo evaluation are used to compare the proposed algorithm with other methods. The experiments and its results demonstrate the ability of the proposed algorithm to match the images more effectively.

Depth image-based rendering (DIBR) is one of the main techniques in interactive 3D video systems. But a critical problem of DIBR is that how to eliminate the holes appearing in virtual view images. In this paper, an improved depth image based virtual view synthesis algorithm is proposed. In depth map pre-processing, only local areas of the depth map with sudden changes are pre-processed by the asymmetric filter. After this, we combine the forward and inverse 3D-warping to synthesize the virtual view. Firstly, it warps the left image to the virtual view and then only reversely warps the region of the holes in the virtual view to the right view to get the lost information of holes. Compared with the traditional method which have to warp the two whole images, computation cost can be reduced by 30% efficiently. Finally, we employ an improved image inpainting based on depth information to fill hole regions. We have improved the method in two portions: 1) depth information is added to the priority computation and searching the best matching patch and 2) as the filling proceeds, the confidence term of the newly inpainted pixels is updated with the mean square error (MSE) of pixels in the target matching patch and the source matching patch. Experimental results show significant objective and subjective gains of the proposed method in comparison to the reference methods.

Sample pretreatment plays important role in the analysis and detection of trace pollutants in complex matrices, such as environmental and biological samples. The adsorption materials of sample pretreatment receive considerable attention, which has a significant effect on the sensitivity and selectivity of the analytical method. In this work, the porous hexagonal boron nitride (h-BN) was utilized as a coating material of solid-phase microextraction (SPME) to extract and preconcentrate polycyclic aromatic hydrocarbons (PAHs) prior to separation and detection with GC-FID. Attributed to the multiple interactions including hydrophobicity, hydrogen bonding and strong π–π interaction, the h-BN coating showed excellent extraction performance for PAHs. Under the optimal conditions, the method showed the linear relationship in the range of 0.1–50 ng mL−1 for acenaphthene, 0.05–50 ng mL−1 for pyrene, and 0.02–50 ng mL−1 for fluorene, phenanthrene and anthracene with a correlation coefficient (R2) not lower than 0.9910. The enrichment factors were achieved between 1526 and 4398 for PAHs with h-BN as SPME fiber coating. The detection limits were obtained in the range of 0.004–0.033 ng mL−1, which corresponds to 0.08–0.66 ng g−1 for soil. The method was successfully applied to analysis of real soil samples. The recoveries were determined between 78.0 and 120.0% for two soil samples. The results showed that h-BN material provided a promising alternative in sample pretreatment and analysis.

Abstract This letter raised some concerns about the study by Karampitsakos et al. in a recent issue of Respiratory Research.

For the purpose of resolving the phenomenon of network congestion in the process of many-to-one communication in multimedia networks at present, the optimal fitting method of nonlinear simultaneous equations (OFMNSEs) is applied to the multimedia transmission congestion control system in this paper. The rate control and resource scheduling are effectively combined, and a clustering network structure is used to activate the congestion control method in turn based on the cluster header and intracluster-related indexes. Finally, it can be known through the analysis of the simulation results that the OFMNSE algorithm put forward in this paper can improve the congestion issue of the multimedia network transmission process and reduce the packet loss rate of data during the transmission effectively under the condition of different relative cache sizes compared with the conventional algorithm.

Infrared image segmentation is a useful and challenging research subject due to its inherent limitations, such as complicated noises, vague edges, and low contrast in infrared images. Active contour models have a wide range of applications for infrared image segmentation. A gradient vector flow (GVF) model and other external force field models have been proposed to improve the noise robustness and weak edge protection to a certain extent. To further address these issues, this paper presents a novel edge-preserving active contour model using guided filter and harmonic surface function for infrared image segmentation. Guided filter is applied to obtain the edge map, reducing the noise interference effectively and collecting more detailed information of the infrared images such as the edges. Then, a harmonic surface function is added into the smoothness term to make the proposed model possess both the abilities of fast convergence and weak edge protection. Besides, we incorporate the information of external force field into the proposed model to preserve the weak boundaries. Compared with adaptive diffusion flow, the proposed method has increased 4% and 2% in precision and F1 measure, respectively.

At present, a hyperspectral image has a significant advantage in the aspect of application because of its high spectral resolution. However, owing to the limit of communication capacity, a hyperspectral image must be compressed. In this paper, we develop and propose a fractal lossy hyperspectral image compression method based on prediction. First, we exploit spatial correlation by applying predictive lossy compression to obtain a reference band of high quality. Then, the local similarity between the two adjacent bands is used through fractal encoding using a local search algorithm. Next, we encode the fractal parameters and the error and fractal residual is transformed by discrete cosine transform, quantized, and entropy encoded to improve the decoded quality. Through experiments, we demonstrate that the proposed algorithm leads to considerably improved performance in compression compared with the other well-known methods. Finally, we validate whether the compression affects the data in the hyperspectral images through classification. The results indicate that the accuracy of classification obtained for the reconstructed image is marginally less than the accuracy reported for the original data set; however, the loss in accuracy is less than 1% and thus acceptable.

Video compression has become more and more important nowadays along with the increasing application of video sequences and rapidly growing resolution of them. H.264 is a widely applied video coding standard for academic and commercial purposes. And fractal theory is one of the most active branches in modern mathematics, which has shown a great potential in compression. In this paper, this study proposes an improved inter prediction algorithm for video coding based on fractal theory and H.264. This study take the same approach to make intra predictions as H.264 and this study adopt the fractal theory to make inter predictions. Some improvements are introduced in this algorithm. First, luminance and chrominance components are coded separately and the partitions are no longer associated as in H.264. Second, the partition mode for chrominance components has been changed and the block size now rages from 16 × 16 to 4 × 4, which is the same as luminance components. Third, this study introduced adaptive quantization parameter offset, changing the offset for every frame in the quantization process to acquire better reconstructed image. Comparison between the improved algorithm, the original fractal compress algorithm and JM19.0 (The latest H.264/AVC reference software) confirms a slightly increase in Peak Signal-to-Noise Ratio, a significant decrease in bitrate while the time consumed for compression remains less than 60% of that using JM19.0.

In high-conversion atom transfer radical polymerization (ATRP), all the reactions, such as radical termination, radical deactivation, dormant chain activation, monomer propagation, etc. could become diffusion controlled sooner or later, depending on relative diffusivities of the involved reacting species. These diffusion-controlled reactions directly affect the rate of polymerization and the control of polymer molecular weight. A model is developed to investigate the influence of diffusion-controlled reactions on the high conversion ATRP kinetics. Model simulation reveals that diffusion-controlled termination slightly increases the rate, but it is the diffusion-controlled deactivation that causes auto-acceleration in the rate (“gel effect”) and loss of control. At high conversions, radical chains are “trapped” because of high molecular weight. However, radical centers can still migrate through (1) radical deactivation–activation cycles and (2) monomer propagation, which introduce “residual termination” reactions. It is found that the “residual termination” does not have much influence on the polymerization kinetics. The migration of radical centers through propagation can however facilitate catalytic deactivation of radicals, which improves the control of polymer molecular weight to some extent. Dormant chain activation and monomer propagation also become diffusion controlled and finally stop the polymerization when the system approaches its glass state.

When partial discharge and overheating occurred inside SF6 insulated electrical equipment, the status of SF6 electrical equipment can be monitored and the development trend of insulation defect inside equipment can be expected through inspecting dissolved products. Raman spectra have more advantages compare with traditional SF6 decomposition products inspection technique. Optimization of geometrical configuration of gas products and calculation of Raman spectra frequency are conducted in this research on the level of 6-31G (2df, p) basis set by utilizing The Density Functional Theory (DFT) and B3LYP method; and calculated shift is compared with actually measured shift of NIST. In addition, the relativity of calculated value and actually measured value of National Institute of Standards and Technology (NIST) is researched by utilizing correlation coefficient R2 through linear regression. The result proves reliability of calculating Raman spectra of SF6 decomposition gas product by DFT method and feasibility of using Raman spectra to qualitatively identify SF6 decomposition gas products.

Limonoids produced by citrus are a group of highly bioactive secondary metabolites which provide health benefits for humans. Currently there is a lack of information derived from research on the genetic mechanisms controlling the biosynthesis of limonoids, which has limited the improvement of citrus for high production of limonoids. In this study, the transcriptome sequences of leaves, phloems and seeds of pummelo (Citrus grandis (L.) Osbeck) at different development stages with variances in limonoids contents were used for digital gene expression profiling analysis in order to identify the genes corresponding to the biosynthesis of limonoids. Pair-wise comparison of transcriptional profiles between different tissues identified 924 differentially expressed genes commonly shared between them. Expression pattern analysis suggested that 382 genes from three conjunctive groups of K-means clustering could be possibly related to the biosynthesis of limonoids. Correlation analysis with the samples from different genotypes, and different developing tissues of the citrus revealed that the expression of 15 candidate genes were highly correlated with the contents of limonoids. Among them, the cytochrome P450s (CYP450s) and transcriptional factor MYB demonstrated significantly high correlation coefficients, which indicated the importance of those genes on the biosynthesis of limonoids. CiOSC gene encoding the critical enzyme oxidosqualene cyclase (OSC) for biosynthesis of the precursor of triterpene scaffolds was found positively corresponding to the accumulation of limonoids during the development of seeds. Suppressing the expression of CiOSC with VIGS (Virus-induced gene silencing) demonstrated that the level of gene silencing was significantly correlated to the reduction of limonoids contents. The results indicated that the CiOSC gene plays a pivotal role in biosynthesis of limonoids.

The objectives of this study were to detect coarse tree root and to estimate root biomass in the field by using an advanced 3D Ground Penetrating Radar (3D GPR) system. This study obtained full-resolution 3D imaging results of tree root system using 500 MHz and 800 MHz bow-tie antennas, respectively. The measurement site included two larch trees, and one of them was excavated after GPR measurements. In this paper, a searching algorithm, based on the continuity of pixel intensity along the root in 3D space, is proposed, and two coarse roots whose diameters are more than 5 cm were detected and delineated correctly. Based on the detection results and the measured root biomass, a linear regression model is proposed to estimate the total root biomass in different depth ranges, and the total error was less than 10%. Additionally, based on the detected root samples, a new index named “magnitude width” is proposed to estimate the root diameter that has good correlation with root diameter compared with other common GPR indexes. This index also provides direct measurement of the root diameter with 13%–16% error, providing reasonable and practical root diameter estimation especially in the field.

Firstly, our research group identified Sutai pigs’ phenotypes that exhibited extreme resistance and susceptibility to the Escherichia coli F18 respectively, and then eight ETEC (Enterotoxigenic Escherichia coli) F18-resistant piglets and eight ETEC F18-sensitive piglets were selected. Then, the TAP1 (Transporter associated with antigen processing) mRNA relative expression levels were analyzed in 11 tissues of the resistant and susceptible phenotypes. Simultaneously, we detected the genetic variations in exon 3 of the TAP1 gene and evaluated the TAP1 mRNA expression levels among the different genotype pigs to study the effects of the genetic variation on gene expression, and the E. coli F18 resistance. The results revealed higher expression levels in the resistant genotypes than that in the susceptible genotypes in 11 tissues, with significant differences in the spleen, lymph node, lung, thymus, duodenum and jejunum. Furthermore, a G729A mutation was identified in the TAP1 gene exon 3, and this mutation deviates from Hardy-Weinberg equilibrium (p < 0.01). The TAP1 mRNA levels in GG genotype were significantly higher than that in the other two genotypes, with significant differences in the liver, lung, kidney, thymus, lymph node, duodenum and jejunum tissues. We speculated that high expression of the TAP1 gene might confer resistance against the E. coli F18, the G729A mutation had a significant effect on the mRNA expression, and individuals with the GG genotype possessed a stronger ability to resist the E. coli F18 infection.

Fabrication and performance of a functional photonic-microfluidic flow cytometer is demonstrated. The devices are fabricated on a Pyrex substrate by photolithographically patterning the microchannels and optics in a SU-8 layer that is sealed via a poly(dimethylsiloxane) (PDMS) layer through a unique chemical bonding method. The resulting devices eliminate the free-space excitation optics through integration of microlenses onto the chip to mimic conventional cytometry excitation. Devices with beam waists of 6 μm and 12 μm in fluorescent detection and counting tests using 2.5 and 6 μm beads-show CVs of 9%–13% and 23% for the two devices, respectively. These results are within the expectations for a conventional cytometer (5%–15%) and demonstrate the ability to integrate the photonic components for excitation onto the chip and the ability to maintain the level of reliable detection.

An accelerated thermal aging process was used to simulate the condition of paper insulation in transformer oil-paper systems. Optical parameters of the insulation paper after various aging intervals were analyzed with terahertz time-domain spectroscopy (THz-TDS) over the range 0.1~1.8 THz. The result shows that the paper had seven absorption peaks at 0.19, 0.49, 0.82, 1.19, 1.43, 1.53, and 1.74 THz, and density functional theory of B3LYP/6-311G+ (d, p) was used to simulate the molecular dynamics of the repeating component (cellobiose) of the cellulose paper. Theoretical spectra were consistent with experiment, which had absorption peaks at 0.18, 0.82, 1.47, and 1.53 THz in the same frequency range. At the same time, the paper samples after various aging intervals had different refractive indexes, and least squares fitting revealed a linear relationship between the degree of polymerization and the refractive index of the paper. Hence, this paper demonstrates that THz-TDS could be used to analyze the aging condition of transformer insulation paper and provides the theoretical and experimental basis for detection.

Carbon monoxide (CO) is one of the most important fault characteristic gases dissolved in power transformer oil. With the advantages of high sensitivity and accuracy, long-term stability, and short detection time, photoacoustic spectroscopy (PAS) has been proven to be one promising sensing technology for trace gas recognition. In this investigation, a tunable PAS experimental system based on a distributed-feedback (DFB) diode laser was proposed for recognizing dissolved CO in transformer oil. The molecular spectral line of CO gas detection was selected at 1.567 μm in the whole experiment. Relationships between the photoacoustic (PA) signal and gas pressure, temperature, laser power, and CO gas concentration were measured and discussed in detail, respectively. Finally, based on the least square regression theory, a novel quantitative identification method for CO gas detection with the PAS experimental system was proposed. And a comparative research about the gas detection performances performed by the PAS system and gas chromatography (GC) measurement was presented. All results lay a solid foundation for exploring a portable and tunable CO gas PAS detection device for practical application in future.

Acetylene C2H2 gas is one of the most important fault characteristic hydrocarbon gases dissolved in oil immersed power transformer oil. This paper reports the successful preparation and characterization of samarium oxide Sm2O3 decorated tin oxide SnO2 based sensors with hierarchical rod structure for C2H2 gas detection. Pure and Sm2O3 decorated SnO2 sensing structures were synthesized by a facile hydrothermal method and characterized by XRD, FESEM, TEM, EDS, and XPS measurements, respectively. Planar chemical gas sensors with the synthesis samples were fabricated, and their sensing performances to C2H2 gas were systematically performed and automatically recorded by a CGS-1 TP intelligent gas sensing analysis system. The optimum operating temperature of the Sm2O3 decorated SnO2 based sensor towards 50 μL/L of C2H2 is 260°C, and its corresponding response value is 38.12, which is 6 times larger than the pure one. Its response time is about 8–10 s and 10–13 s for recovery time. Meanwhile good stability and reproducibility of the decorated sensor to C2H2 gas are also obtained. Furthermore, the proposed sensor exhibits excellent C2H2 selectivity among some potential interface gases, like H2 and CO gas. All sensing results indicate the sensor fabricated with oxide Sm2O3 decorated SnO2 nanorods might be a promising candidate for C2H2 detection in practice.

Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models.

BACKGROUND: The citrus red mite is a worldwide citrus pest and a common sensitizing allergen of asthma and rhinitis. It has developed strong resistance to many registered acaricides, However, the molecular mechanisms of resistance remain unknown. we therefore used next generation sequencing technology to investigate the global transcriptomes between resistant strains and susceptible strains. RESULTS: We obtained 34,159, 30,466 and 32,217 unigenes by assembling the SS reads, RS reads and SS&RS reads respectively. There are total 17,581 annotated unigenes from SS&RS reads by BLAST searching databases of nr, the Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) with an E-value ≤ 1e-5, in which 7,075 unigenes were annotated in the COG database, 12, 712 unigenes were found in the KEGG database and 3,812 unigenes were assigned to Gene ontology (GO). Moreover, 2,701 unigenes were judged to be the differentially expressed genes (DEGs) based on the uniquely mapped reads. There are 219 pathways in all annotated unigenes and 198 pathways in DEGs that mapped to the KEGG database. We identified 211 metabolism genes and target genes related to general insecticide resistance such as P450 and Cytochrome b, and further compared their differences between RS and SS. Meanwhile, we identified 105 and 194 genes related to growth and reproduction, respectively, based on the mode of action of Hexythiazox. After further analyses, we found variation in sequences but not in gene expression related to mite growth and reproduction between different strains. CONCLUSION: To our knowledge, this is the first comparative transcriptome study to discover candidate genes involved in phytophagous mite resistance. This study identified differential unigenes related to general pesticide resistance and organism growth and reproduction in P. citri. The assembled, annotated transcriptomes provide a valuable genomic resource for further understanding the molecular basis of resistance mechanisms.