Electronic structure and magnetic properties of Al‐doped Ca2Fe2O5 brownmillerite compounds

Polycrystalline Ca₂Fe_2?xAl_xO₅ (x = 0‐1.4) samples were prepared by conventional solid‐state reactions. Their crystalline/electronic structures and magnetic properties were characterized in detail. Powder X‐ray diffraction analyses revealed that the samples crystallized in orthorhombic brownmillerite‐type structures with the occurrence of the Pcmn‐Ibm2 phase separation in the region between x = 0.4 and 0.6. The results obtained from analyzing Raman scattering and X‐ray‐absorption fine‐structure spectra also indicated this phase separation. Although x in Ca₂Fe_2?xAl_xO₅ varies in a wide range from 0 to 1.4, the +3 oxidation state of Fe remained almost unchanged. Magnetization measurements revealed that all Ca₂Fe_2?xAl_xO₅ samples have weak ferromagnetic order, and both the saturation magnetization and coercive force are dependent on the temperature, x, and structure phases.     

Synthesis and characterization of decyl phosphonic acid,applications in emulsion polymerization and anti-corrosion coating

Alkyl phosphonic acids are amphiphilic structures consisting of non-polar organic hydrophobic groups and anionic inorganic hydrophilic groups, which makes them be able to behave as surfactants as well as smart corrosion inhibitors. A simple and high yield (up to 87%) pathway for synthesizing decyl phosphonic acid (DPA) is described. ¹H and ¹³C-NMR) as well as FTIR spectroscopy were used to characterize chemical structures and purity of the obtained product. Thermal properties and crystal structure of DPA were investigated using differential scanning calorimetry analysis (DSC) and thermogravimetric analysis (TGA). The stability of DPA in Oil-in-Water (O/W) and Water-in-Oil (W/O) emulsions was improved in the presence of ammonium persulfate (APS), which allowed us to measure their specific characteristics such as particle size and zeta potential (ξ) of micelles. Both emulsions were used for synthesizing polyaniline (PANI) by emulsion polymerization. Wettability of DPA on the mild steel surface was examined using contact angle measurements. Moreover, corrosion-inhibition properties studied by using electrochemical impedance spectroscopy (EIS) technique and salt spray test results revealed that DPA can be an efficient ingredient for anti-corrosion coating.     

电力变压器铁芯磁场和损耗分布的三维数值方法与实施(第三部分:铁芯搭迭区)

在第一和第二部分的基础上,本文着重讨论铁芯搭迭区局部磁场的分析模型和数值方法,并根据计算结果探讨各种搭迭形式及相关因素对磁场和损耗的影响,由此得出一些有利于铁芯搭迭设计的合理化建议。     

Identification of Bioactivity,Volatile and Fatty Acid Profile in Supercritical Fluid Extracts of Mexican arnica

Supercritical fluid extraction (SFE) is a sustainable technique used for the extraction of lipophilic metabolites such as pigments and fatty acids. Arnica plant is considered a potential candidate material with high antioxidant and antimicrobial activities. Therefore, in this study, a locally available Heterotheca inuloides, also known as Mexican arnica, was analyzed for the extraction of high-value compounds. Based on different pressure (P), temperature (T), and co-solvent (CoS), four treatments (T) were prepared. A maximum 7.13% yield was recovered from T2 (T = 60 °C, P = 10 MPa, CoS = 8 g/min), followed by 6.69% from T4 (T = 60 °C, P = 30 MPa, CoS = 4 g/min). Some bioactive sesquiterpenoids such as 7-hydroxycadalene, caryophyllene and δ-cadinene were identified in the extracts by GC/MS. The fatty acid profile revealed that the main components were palmitic acid (C16:0), followed by linoleic acid (C18:2ω6c), α-linolenic acid (C18:3ω3) and stearic acid (C18:0) differing in percent yield per treatment. Antibacterial activities were determined by the agar diffusion method, indicating that all the treatments exerted strong antibacterial activity against S. aureus, C. albicans, and E. coli strains. The antioxidant capacity of the extracts was also measured by three in vitro assays, DPPH, TEAC and FRAP, using Trolox as a standard. Results showed high antioxidant capacity enabling pharmaceutical applications of Mexican arnica.     

A Nom historical document recognition system for digital archiving

A Nom historical document recognition system is being developed for digital archiving that uses image binarization, character segmentation, and character recognition. It incorporates two versions of off-line character recognition: one for automatic recognition of scanned and segmented character patterns (7660 categories) and the other for user handwritten input (32,695 categories). This separation is used since including less frequently appearing categories in automatic recognition increases the misrecognition rate without reliable statistics on the Nom language. Moreover, a user must be able to check the results and identify the correct categories from an extended set of categories, and a user can input characters by hand. Both versions use the same recognition method, but they are trained using different sets of training patterns. Recursive X–Y cut and Voronoi diagrams are used for segmentation; k–d tree and generalized learning vector quantization are used for coarse classification; and the modified quadratic discriminant function is used for fine classification. The system provides an interface through which a user can check the results, change binarization methods, rectify segmentation, and input correct character categories by hand. Evaluation done using a limited number of Nom historical documents after providing ground truths for them showed that the two stages of recognition along with user checking and correction improved the recognition results significantly.     

Faceless identification based on temporal strips

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)² and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.

     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator

In this paper, we propose a two-mode adaptive fuzzy controller with approximation error estimator. In the learning mode, the controller employs some modified adaptive laws to tune the fuzzy system parameters and an approximation error estimator to compensate for the inherent approximation error. In the operating mode, the fuzzy system parameters are fixed, only the estimator is updated online. Mathematically, we show that the closed-loop system is stable in the sense that all the variables are bounded in both modes. We also establish mathematical bounds on the tracking error, state vector, control signal and the RMS error. Using these bounds, we show that controller's design parameters can be chosen to achieve desired control performance. After that, an algorithm to automatically switch the controller between two modes is presented. Finally, simulation studies of an inverted pendulum system and a Chua's chaotic circuit demonstrate the usefulness of the proposed controller.     

Impossible differential cryptanalysis of 7-round Advanced Encryption Standard (AES)

In 2000, Biham and Keller [Cryptanalysis of reduced variants of Rijndael, 3rd AES Conference, in press] presented an impossible differential cryptanalysis of the Advanced Encryption Standard (AES) up to 5 rounds. This was later improved in 2001 by Cheon et al. [Improved impossible differential cryptanalysis of Rijndael and Crypton, in: Lecture Notes in Comput. Sci., vol.  2288, Springer-Verlag, Berlin, 2001, pp. 39-49] to apply to 6 rounds of the AES. In this paper, we extend on previous results to present an attack on the AES up to 7 rounds. This is the best-known impossible differential attack on the AES, and works by exploiting weaknesses in the AES key schedule.