Effect of different initiators on temperature-sensitive monolithic columns and application in online enrichment of β-sitosterol

Three temperature-sensitive monolithic columns were prepared by atom transfer radical polymerization and oxidation–reduction method using the initiator systems of CCl₄/FeCl₂, BPO/DMA, and APS/TEMED, respectively. The three monoliths were characterized by scanning electron microscopy, nitrogen adsorption, and thermogravimetric analysis. The obtained monolithic columns were used as on-line solid phase extraction sorbent coupled with high-performance liquid chromatography for the enrichment of β-sitosterol. By comparing some influencing factors on the adsorption, the optimum temperature-sensitive monolithic column which was initiated by CCl₄/FeCl₂ was selected for enrichment of β-sitosterol from plant oil. The maximum adsorption capacity of the monolith for β-sitosterol was 10.0031 mg/g. The limit of detection and limit of quantitation were 0.039 and 0.13 mg/mL, respectively. The recovery was in the range of 90.21–98.26%. The results showed that the monolith had better selectivity for β-sitosterol and could be used for enrichment of β-sitosterol in food samples. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47683.     

Effect of Pin Diameters on the Wear Characteristics of Friction Pairs

Strength of Materials - The tribological tests are carried out to assess the effect of pin diameters on wear characteristics via changing contact stresses and sliding speeds to provide support for...     

Theoretical calculation and evaluation of n +~(240,242,244)Pu reactions

The nuclear data of n+~(240;242;244)Pu reactions for incident energy below 200 MeV are calculated and evaluated to meet the requirement in the design of an accelerator-driven subcritical system. The optical model is used to calculate the total, nonelastic, shape elastic cross sections, shape elastic scattering angular distributions, and transmission coefficients. The distorted-wave Born approximation is applied to calculate the direct inelastic scatterings to the discrete excited states. The nuclear reaction statistical models and fission theory are applied to describe neutron, proton, deuteron, triton, helium-3, alpha and c emissions, and fission consistently. The results thus obtained are compared with experimental data and the evaluated data obtained from ENDF/B-VII.1 and JENDL-4.0.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

Bio-inspired power control and channel allocation for cellular networks with D2D communications

With the tremendous increment of traffic in the next generation mobile networks, device to device (D2D) communication is proposed to relieve the traffic burden of the base station and improve the overall network capacity. It supports direct communications between devices and could reuse the resources of cellular users (CUs). Despite the advantages, D2D communications bring great challenges in interference management. In this paper, we study the power control and channel allocation problems in three scenarios: (1) one CU and one D2D pair; (2) one CU and multiple D2D pairs; (3) multiple CUs and multiple D2D pairs. The goal is to coordinate the mutual interferences and maximize the overall network capacity. We derive sufficient conditions to guarantee the efficiency of D2D communications in scenarios with one CU and one D2D pair. We propose the bio-inspired PSO-P power control algorithm for the scenarios with one CU and multiple D2D pairs, and the PSO-CP algorithm for the scenarios with multiple CUs and multiple D2D pairs to jointly assign channels and powers. Simulation results show that the proposed algorithms are efficient in improving the overall network capacity.

     

Propagation of surface cracks on beam blank in the mould during continuous casting

ABSTRACT

We focus on crack propagation to investigate surface cracks in the mould during continuous casting, based on the crack initiation mechanism proposed in previous studies. The temperature and stress data of a solidified shell were extracted, and an extended finite element model based on the continuous damage theory of elastic–plastic materials was developed to simulate surface crack propagation. The results showed that, in the cracked area, stress concentration occurred at the crack tip, and the element split open and the crack propagated when the maximum principal stress in the stress concentration area reached the critical value. Prefabricated cracks in the fillet and web mainly developed into longitudinal cracks in the mould. The theoretical mechanism of this study was found to be the same as the crack propagation mechanism observed during the actual production of beam blanks. Thus, this study reveals the theoretical principle of crack initiation and propagation and can provide theoretical guidance for controlling surface cracks during beam blank continuous casting.     

Self-determined nudging: a system concept for human–machine interaction

Humans sometimes struggle when making decisions, because what they want to do in a specific moment can differ from what they feel they should do in general. This phenomenon can also be found in situations of human–machine interaction. In order to support humans in making decisions about their behavior, a new form of support is proposed, which is especially suitable for human–machine interaction: self-determined decision-making with nudging methods (or shortly: self-determined nudging). In this concept, firstly the aspirations of the human are assessed and then supporting mechanisms are offered to guide humans towards their self-set goals. With this procedure, machines can for example support humans in driving safely or economically, help them refraining from scheduling other appointments in their gym-timeslots or push them towards going to bed on time. While originally nudging is based on libertarian paternalism, the concept of self-determined nudging enables the person to decide which goals to get nudged towards. By different examples, it is shown that nudging ideas are already present in numerous technical applications. Then, it is demonstrated how the aspect of self-determination can enrich these approaches. Moreover, already existing as well as potential new implementations of self-determined nudging in the automotive domain are described. As an outlook, the set-up of a study on automated driving is presented.

     

SMTIBEA: a hybrid multi-objective optimization algorithm for configuring large constrained software product lines

Software and Systems Modeling - A key challenge to software product line engineering is to explore a huge space of various products and to find optimal or near-optimal solutions that satisfy all...