A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Combined effects of wheat gluten and carboxymethylcellulose on dough rheological behaviours and gluten network of potato–wheat flour-based bread

Incorporating high level of potato flour into wheat flour enhances nutritional values of bread but induces a series of problems that lead to the decline of the bread quality. To overcome the barrier, wheat gluten and carboxymethylcellulose (CMC) were added into potato–wheat composite flour to improve dough machinability and bread quality. The rheological properties, thermo-mechanical properties and microstructures of dough were investigated. The results showed that the interaction between gluten and CMC mitigated the discontinuity of gluten matrix and gluten protein aggregation caused by the addition of potato flour, which yielded a more branched and compact gluten network. The compact three-dimensional viscoelastic structure induced improvements of gas retention capacity and dough stability, making it mimic the machinability properties of wheat flour dough. Bread qualities were apparently improved with the combined use of 4% gluten and 6% CMC, of which specific volume increased by 42.86%, and simultaneously, hardness reduced by 75.93%.     

Heat propagation in thermally conductive polymers of PA6 and hexagonal boron nitride

Thermally conductive polymers offer new possibilities for the heat dissipation in electric and electronic components, for example, by a three‐dimensional shaping of the heat sinks. To face safety regulations, improved fire performance of those components is required. In contrast to unfilled polymers, those materials exhibit an entirely different thermal behavior. To investigate the flammability, a phosphorus flame retardant was incorporated into thermally conductive composites of polyamide 6 and hexagonal boron nitride. The flame retardant decreased the thermal conductivity only slightly. However, the burning behavior changed significantly, due to a different heat propagation, which was investigated using a thermographic camera. An optimum content of hexagonal boron nitride for a sufficient thermal conductivity and fire performance was found between 20 and 30 vol%. The improvement of the fire performance was due to a faster heat release out of the pyrolysis zone and an earlier decomposition of the flame retardant. For higher contents of hexagonal boron nitride, the heat was spread faster within the part, promoting an earlier ignition and increasing the decomposition rate of the flame retardant.     

Facile synthesis of Li 2 ZrO 3 -modified LiNi 0.5 Mn 0.5 O 2 cathode material from a mechanical milling route for lithium-ion batteries

Li2ZrO3-modified LiNi0.5Mn0.5O2 materials with improved electrochemical performance were directly synthesized by a simple mechanical milling route with ZrO2, Li2CO3 and Ni0.5Mn0.5(OH)2 precursors...     

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.