Search

A green and efficient method for the synthesis of oxadiazaborole, dioxazaborinine, and oxadiazaborinine from the reactions of phenylboronic acid with amidoxime, α-hydroxyl oxime and α-hydroxyl hydrazone, respectively, is described. The reactions were performed under catalyst-free and mild conditions. All products can be rapidly purified by filtration and washing. In addition, a set of iminoboronates were prepared following a one-pot multicomponent reaction procedure using α-hydroxyl hydrazone, salicylaldehyde and boronic acid derivatives as starting materials and their photophysical properties were assessed. Then, cross-coupling reactions can be carried out smoothly on some target compounds, which may help develop new boron masking strategies.

Metal-organic frameworks (MOFs) have received extensive attention in the field of biomedicine, particularly serving as multifunctional theranostic nanoplatforms by integrating chemodrugs, imaging agents, and targeting agents. Herein, we report a facile strategy for the fabrication of a hollow and monodisperse MOF (denoted

Idiopathic interstitial pneumonia (IIP) is a group of progressive lower respiratory tract diseases of unknown origin characterized by diffuse alveolitis and alveolar structural disorders leading to pulmonary fibrillation and hypertension, pulmonary heart disease, and right heart failure due to pulmonary fibrosis, and more than half of them die from respiratory failure. To address these problems of overly complex prediction methods and large data sets involved in the prediction process of interstitial pneumonia, this paper proposes a prediction model for interstitial pneumonia which is based on the Gaussian Parsimonious Bayes algorithm. Three usual tests of pneumonia, specifically from various patients, were collected as the sample set. These samples are divided into training and testing sets. Additionally, a cross-validation strategy was used to avoid the overfitting problem. The results showed that the prediction model based on the Gaussian Parsimonious Bayes algorithm predicted 92% accuracy on the test set, and the Parsimonious Bayes method could directly predict the final detection of interstitial pneumonia based on the usual pneumonia test pneumonia. In addition, it was found that the closer the data distribution of the sample set was to a normal distribution, the higher the prediction accuracy was, and then, after excluding pneumonia from the test below 60 points, the prediction accuracy reached 96%.

To decrease d-lactic acid production cost, sugarcane molasses and soybean meal, low-cost agro-industrial wastes, were selected as feedstock. First, sugarcane molasses was used directly by Lactobacillus delbrueckii S-NL31, and the nutrients were released from soybean meal by protease hydrolysis. Subsequently, to ensure intensive substrate utilization and enhanced d-lactic acid production from sugarcane molasses and soybean meal, adaptation of L. delbrueckii S-NL31 to substrates was performed through adaptive laboratory evolution. After two-phase adaptive laboratory evolution, the evolved strain L. delbrueckii S-NL31-CM3-SBM with improved cell growth and d-lactic acid production on sugarcane molasses and soybean meal was obtained. To decipher the potential reasons for improved fermentation performance, a metabolomics-based approach was developed to profile the differences of intracellular metabolism between initial and evolved strain. The in-depth analysis elucidated how the key factors exerted influence on d-lactic acid biosynthesis. The results revealed that the enhancement of glycolysis pathway and cofactor supply was directly associated with increased lactic acid production, and the reinforcement of pentose phosphate pathway, amino acid metabolism, and oleic acid uptake improved cell survival and growth. These might be the main reasons for significantly improved d-lactic acid production by adaptive laboratory evolution. Finally, fed-batch simultaneous enzymatic hydrolysis of soybean meal and fermentation process by evolved strain resulted in d-lactic acid levels of 112.3 g/L, with an average production efficiency of 2.4 g/(L × h), a yield of 0.98 g/g sugar, and optical purity of 99.6%. The results show the applicability of d-lactic acid production in L. delbrueckii fed on agro-industrial wastes through adaptive laboratory evolution.

Amphiphobic surfaces have been developed for various applications. However, the harsh construction conditions and multistep processes limit their practical application. Especially for those with a particular surface roughness and morphology, the amphiphobic property might provide a slight deformation. Here, a facile large-area construction of transparent and flexible amphiphobic coatings with excellent fold resistance has been established by simple casting of the fluorinated liquid nitrile-butadiene rubber (F-LNBR) followed by solvent-free photocuring. It was found that the fluorocarbon groups could concentrate onto the coating surface during the UV-induced photocuring. With a certain coating amount, a stable oleophobic coating was achieved with static contact angles of about 95° and 111° for nonpolar oil (n-hexadecane) and polar oil (diiodomethane). Most importantly, the static contact angles of water and diiodomethane of the amphiphobic coatings on the iron sheet increased after bending and remained around 131° and 120° after being completely folded in half for 100 cycles because the inner fluorocarbon groups could be squeezed out from the flexible cross-linked rubber matrix as a reservoir. Such features indicated the promising self-cleaning and surface protection of the proposed transparent and flexible amphiphobic coatings for deformable substrates.

The existing automatic medical volume segmentation methods are usually not accurate enough, and manually editing the segmentation result is still very tedious. The paper proposes a novel editing framework for medical volume data segmentation by providing users simple and convenient 3D interactions under the visual guidance of segmentation uncertainty measurements. In the system, the volume data will be visualized in a combination of volume rendering and surface rendering. Since it is hard for users to obtain volume data information as context from surface rendering, we have designed uncertainty metrics based on mesh shape descriptors and volume image structure descriptors. The measures are mapped and rendered on the segmentation boundary mesh to indicate the uncertainty of the current segmentation boundary, which can guide users in finding a optimal editing region to start editing. Existing interactive volume segmentation editing methods usually have a demand of per-slice 2D interactions which are inconvenient and time-consuming. Compared to these methods, our system allows users to use sketch-based interactions to generate editing slices of custom shapes, and refine the contours on 2D slices to edit the current medical segmentation result. The edit results will be propagated to the 3D volume using Laplacian mesh editing techniques, which makes only a few slice interactions required. The experiments have shown that our method can effectively improve the accuracy of segmentation results. Compared with the similar methods, the number of interactions is also effectively reduced.

To decrease d-lactic acid production cost, sugarcane molasses and soybean meal, low-cost agro-industrial wastes, were selected as feedstock. First, sugarcane molasses was used directly by

Sodium p-styrene sulfonate (SSS) was successfully grafted on the surface of 316 stainless steel surfaces (SS-SCA-SSS) via Thiol-ene click reactions with the aim to improve its antibacterial properties. Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), laser scanning confocal microscopy (LSM) and contact angle measurements were employed to analyze physico-chemical characteristics of the modified SS. The antibacterial properties of SS-SCA-SSS was evaluated using a bacterial strain of Escherichia coli (E. coli). The antibacterial efficiency results showed that the SS-SCA-SSS surface exhibited satisfactory long-term antibacterial capability against E. coli. Bacterial adhesion of both SS-SCA-SSS and reused SS-SCA-SSS was reduced to 18% of those on SS. The positive results obtained in this study indicate the high potential of SSS grafting on SS surfaces for practical usages.

To understand the impacts of high hydrostatic pressure (HHP) processing on the microstructure and properties of pectin, an aqueous solution of apple pectin (50 g/L) was treated at 200, 400, and 600 MPa for 30 min. The chemical structure and properties of resultant pectin were characterized and compared with those of native pectin (0.1 MPa). The contents of α-1,4-linked d -galacturonic acid and reducing sugar in pectin did not change after HHP, whereas the degree of esterification of pectin increased slightly. Fourier transform infrared spectroscopy showed that no chemical conversion of pectin occurred during HHP process. For the first time, molecular dynamics simulation revealed that the hydrophobic hydration of the methyl group dramatically improved under HHP, thereby enhancing pectin dissolution in water. In turn, this result increased the aqueous pectin solution's apparent viscosity and stability, which are very important for fruit- and vegetable-based products containing pectin.

Video annotation is an effective way to facilitate content-based analysis for videos. Automatic machine learning methods are commonly used to accomplish this task. Among these, active learning is one of the most effective methods, especially when the training data cost a great deal to obtain. One of the most challenging problems in active learning is the sample selection. Various sampling strategies can be used, such as uncertainty, density, and diversity, but it is difficult to strike a balance among them. In this paper, we provide a visualization-based batch mode sampling method to handle such a problem. An iso-contour-based scatterplot is used to provide intuitive clues for the representativeness and informativeness of samples and assist users in sample selection. A semisupervised metric learning method is incorporated to help generate an effective scatterplot reflecting the high-level semantic similarity for visual sample selection. Moreover, both quantitative and qualitative evaluations are provided to show that the visualization-based method can effectively enhance sample selection in active learning.

The nanoscale microporous carbide-derived carbon (nano-CDC) is synthesized by chlorination of silicon carbide nano-powder with a particle diameter around 60 nm and further pore-tuned by KOH activation with different KOH/nano-CDC ratios. Based on the higher specific surface area (SSA), a hierarchical micro- and meso-pore structure (especially for the greatly produced mesopores), and the shorter inherent ion transport distance within porous nano-carbons, the KOH-activated nano-CDC exhibits superior supercapacitive performances. Its specific capacitance is up to 141 F g−1, 156% increase compared with that of pristine nano-CDC (54 F g−1). Most interestingly, the cyclic voltammogram curve of the activated nano-CDC can keep a rectangular-like shape even at a scan rate of 5000 mV s−1, exhibiting significantly better power performance. This work confirms that constructing favorable pore structure in nanometer-sized porous carbons is an effective strategy for fabricating high-power supercapacitors.

A Content-Addressable Memory (CAM) is a memory that implements the lookup-table function in a single clock cycle using dedicated comparison circuitry. CAMs are especially popular in network routers for packet forwarding and packet classification, but they are also beneficial in a variety of other applications that require high-speed table lookup. The main CAM design challenge is to reduce power consumption associated with the large amount of parallel active circuitry, without sacrificing speed or memory density. In this project, a low power content-addressable memory using pipelined hierarchical search scheme is implemented. The search operation is pipelined and the match-lines are broken to several segments. Whenever the stored words fail to match in their initial segments, the search operation is discontinued for subsequent segments, hence the power is saved. The proposed scheme has been implemented in a 64×64 bit ternary CMOS CAM. The schematics of both the pipelined and non-pipelined CAMs are designed. PSPICE power simulation is used to extract the power consumption of both memory designs. The simulation results demonstrate an effective overall power reduction in the pipelined CAM compared to non-pipelined architecture for the given example memory pattern.

This paper presents a new human face generation method using a three-dimensional deformation technique. The deformation technique allows interactive alignment of features in the general geometric face model with the features of the multi-direction images of the specific human face which are pre-provided by the animator. The deformation result is a 3D face model of the specific human face; it precisely reflects the corresponding features of the specific human face. This deformation technique also provide an available approach to obtaining models of facial expression. To enhance the realism, we employ a new multi-direction texture mapping technique which gets photometric information from multi-direction images of the specific human face to diminish the texture distortion.