Calcium: A comprehensive review on quantification,interaction with milk proteins and implications for processing of dairy products

Calcium (Ca) is a key micronutrient of high relevance for human nutrition that also influences the texture and taste of dairy products and their processability. In bovine milk, Ca is presented in several speciation forms, such as complexed with other milk components or free as ionic calcium while being distributed between colloidal and serum phases of milk. Partitioning of Ca between these phases is highly dynamic and influenced by factors, such as temperature, ionic strength, pH, and milk composition. Processing steps used during the manufacture of dairy products, such as preconditioning, concentration, acidification, salting, cooling, and heating, all contribute to modify Ca speciation and partition, thereby influencing product functionality, product yield, and fouling of equipment. This review aims to provide a comprehensive understanding of the influence of Ca partition on dairy products properties to support the development of kinetics models to reduce product losses and develop added-value products with improved functionality. To achieve this objective, approaches to separate milk phases, analytical approaches to determine Ca partition and speciation, the role of Ca on protein–protein interactions, and their influence on processing of dairy products are discussed.     

A new version of Kovarik’s approximate orthogonalization algorithm without matrix inversion

In 1970 Kovarik proposed approximate orthogonalization algorithms. One of them (algorithm B) has quadratic convergence but requires at each iteration the inversion of a matrix of similar dimension to the initial one. An attempt to overcome this difficulty was made by replacing the inverse with a finite Neumann series expansion involving the original matrix and its adjoint. Unfortunately, this new algorithm loses the quadratic convergence and requires a large number of terms in the Neumann series which results in a dramatic increase in the computational effort per iteration. In this paper we propose a much simpler algorithm which, by using only the first two terms in a different series expansion, gives us the desired result with linear convergence. Systematic numerical experiments for collocation and Toeplitz matrices are also described.     

Degradation of acephate and its metabolite methamidophos in rice during processing and storage

The degradation of acephate and its metabolite methamidophos during different stages of commercial processing, homing processing, and storage was assessed. Residues were determined by a simple gas-chromatographic method using a flame photometry detector. Acephate and methamidophos mostly remained in rice hull fractions, and hulling significantly reduced acephate and methamidophos in rice. Commercial processing caused the loss of 86% of acephate and 35.9% of methamidophos from rough brown rice to polished rice, whereas home processing caused the loss of 83.9% of acephate and 70% of methamidophos from polished rice to cooked rice. Washing for 5, 15, and 30 min (with tap water, 0.9% NaCl, and 0.1% Na₂CO₃) caused an average loss in the range of 9.8%-35.3% of acephate and 9.7%-45.2% of methamidophos. Extending washing time and adding a small amount of soda into the washing solution can efficiently eliminate acephate and methamidophos. The stability of acephate and methamidophos in polished rice was studied at different storage intervals, from 7 to 42 days at ambient temperatures (25 °C). Methamidophos was found to be more persistent than acephate.     

DLC涂层应用于活塞环

本文介绍了采用PVD处理方法获得的DLC涂层,针对DLC涂层应用于活塞环,提高活塞环耐磨、减摩性能做了重点介绍,并叙述了该领域的发展现状及趋势。     

Content‐Aware Automatic Photo Enhancement

Automatic photo enhancement is one of the long‐standing goals in image processing and computational photography. While a variety of methods have been proposed for manipulating tone and colour, most automatic methods used in practice, operate on the entire image without attempting to take the content of the image into account. In this paper, we present a new framework for automatic photo enhancement that attempts to take local and global image semantics into account. Specifically, our content‐aware scheme attempts to detect and enhance the appearance of human faces, blue skies with or without clouds and underexposed salient regions. A user study was conducted that demonstrates the effectiveness of the proposed approach compared to existing auto‐enhancement tools.     

基于语义的智能信息处理技术的研究

智能信息处理是模拟人或者自然界其他生物处理各种信息的行为,是当前信息处理技术向多样化、集成化与智能化方向的发展,具有很高的理论研究和应用价值.经过多年的研究和探索,智能信息处理技术已经取得较大的发展,但在实际应用中还存在许多问题需要解决和完善.分析了基于概念图的语义研究在智能信息处理中的应用,并设计与实现了一个基于概念图的智能答疑系统CGQAS,通过实验结果验证了基于概念图的智能信息处理的可行性和有效性.     

Characterization of stainless steel parts by Laser Metal Deposition Shaping

Laser Metal Deposition Shaping (LMDS) is a new rapid manufacturing technology, which can build fully-dense metal components directly from the information transferred from a computer file by depositing metal powders layer by layer with neither mould nor tool. Typically, performed with stainless steel (SS) 316 powder, the orthogonal experiments combining with the ideal overlapping model were applied to ascertain the optimal processing parameters. Then the characteristics of microstructure, composition and phase of as-deposited cladding layers were analyzed through Scanning Electron Microscope (SEM) and X-ray diffraction (XRD), as well as relative model. Furthermore, the cooling rate and the solidification velocity during LMDS were evaluated based on empirical method. With the optimal parameters, some parts were fabricated without obvious defects, and then the mechanical properties of them were tested. Finally, the influencing regularities of critical parameters on microstructure and properties were concluded by comparison. The results prove that the microstructure of SS 316 deposits is composed of the slender dendrites growing epitaxially from the substrate, the mechanical properties are favorable and anisotropic, and the composition is uniform. Besides, the microstructure morphology and the mechanical properties are affected by the varied processing parameters at different degrees. Among them, the scanning speed shows the most remarkable effects on microstructure morphology, characteristic microscale, mechanical properties, as well as geometric shape of as-deposited parts.     

AN ALTERNATIVE PERSPECTIVE ON FUZZY SET-BASED APPROXIMATE REASONING

Abstract

On the subject of fuzzy set-based approximate reasoning, this paper attempts to present a perspective that is both rigorously stated and different from the standard approach as stated by Mamdani and many others. Functionally speaking, this alternative perspective produces results essentially the same as the standard one, and in fact we intend to prove that subject to certain assumptions the results will be exactly die same. We feel however that the alternative perspective offers advantages in that it makes a more appropriate and more understandable use of such concepts as fuzzy relations, the extension principle, and fuzzy composition. If indeed it can lead to a clearer and more widespread understanding of the approximate reasoning formalism then this could conceivably spark broader interest in fuzzy control and other applications.     

Scalable visibility color map construction in spatial databases

Recent advances in 3D modeling provide us with real 3D datasets to answer queries, such as “What is the best position for a new billboard?” and “Which hotel room has the best view?” in the presence of obstacles. These applications require measuring and differentiating the visibility of an object (target) from different viewpoints in a dataspace, e.g., a billboard may be seen from many points but is readable only from a few points closer to it. In this paper, we formulate the above problem of quantifying the visibility of (from) a target object from (of) the surrounding area with a visibility color map (VCM). A VCM is essentially defined as a surface color map of the space, where each viewpoint of the space is assigned a color value that denotes the visibility measure of the target from that viewpoint. Measuring the visibility of a target even from a single viewpoint is an expensive operation, as we need to consider factors such as distance, angle, and obstacles between the viewpoint and the target. Hence, a straightforward approach to construct the VCM that requires visibility computation for every viewpoint of the surrounding space of the target is prohibitively expensive in terms of both I/Os and computation, especially for a real dataset comprising thousands of obstacles. We propose an efficient approach to compute the VCM based on a key property of the human vision that eliminates the necessity for computing the visibility for a large number of viewpoints of the space. To further reduce the computational overhead, we propose two approximations; namely, minimum bounding rectangle and tangential approaches with guaranteed error bounds. Our extensive experiments demonstrate the effectiveness and efficiency of our solutions to construct the VCM for real 2D and 3D datasets.     

Self‐similarity for accurate compression of point sampled surfaces

Most surfaces, be it from a fine‐art artifact or a mechanical object, are characterized by a strong self‐similarity. This property finds its source in the natural structures of objects but also in the fabrication processes: regularity of the sculpting technique, or machine tool. In this paper, we propose to exploit the self‐similarity of the underlying shapes for compressing point cloud surfaces which can contain millions of points at a very high precision. Our approach locally resamples the point cloud in order to highlight the self‐similarity of the shape, while remaining consistent with the original shape and the scanner precision. It then uses this self‐similarity to create an ad hoc dictionary on which the local neighborhoods will be sparsely represented, thus allowing for a light‐weight representation of the total surface. We demonstrate the validity of our approach on several point clouds from fine‐arts and mechanical objects, as well as a urban scene. In addition, we show that our approach also achieves a filtering of noise whose magnitude is smaller than the scanner precision.