Study of planar structure applying reciprocity technique combined with MGEC and analysis of discontinuity

The 3D structure electromagnetic computation presents several difficulties related to the volume mesh. In fact, the entire volume space must be taken into account even the smallest details. In this article, we propose a formulation based on the reciprocity theorem combined with the generalized equivalent circuit method to model a planar 3D structure with both coaxial and planar excitation. The major advantage of this formulation is the fact to reduce the computational volume into 2D ones in the discontinuity plane. In addition, we focused on the calculation of the discontinuity between the excitation source and the planar structure to determine the exact behavior of the electric coaxial excitation model. The obtained current density, electric field distributions, and the input impedance are presented and discussed in the following sections. An approximately good agreement of input impedance with those obtained by the simulator and measurement is shown.     

User activities and the heterogeneity of urban space:The case of Dahiyat Al Hussein park

Urban researchers have maintained a constant interest in the complexity and continuity of urban space usage. Some have applied actor–network theory (ANT) to investigate the heterogeneity of spaces and present them through the networks of their users’ activities. However, these accounts are predominantly limited in examining the extent to which these spaces may be heterogeneous when exploring such networks. This paper draws on recent ANT scholarship, which employs an ethnographic research conducted in a main park in a housing project at Dahiyat Al Hussein in Amman, Jordan. The findings describe the complex and unpredictable negotiations that occur within spaces by documenting the varieties and interrelations among user activity networks within this common and shared urban space. This research reveals the extent to which spaces, parks in this case, may be heterogeneous by unpacking their usage. The conclusions and insights assert the necessity of paying attention to design detail and creating designs that are responsive to evolving user activities.     

Haemolytic activity of Aeromonas species isolated in Libya

Twenty seven Aeromonas strains (5A. hydrophila, 8A. sobria and 14A. caviae) isolated from children with diarrhoea and 34 Aeromonas strains (9A. hydrophila, 7A. sobria an 18A. caviae) isolated from children without diarrhoea were tested from haemolysin production. The results obtained showed that haemolysin production using human, horse or sheep erythrocytes was significantly associated with A.hydrophila and A sobria but not with A.caviae, regardless of whether these strains were isolated from children with or without diarrhoea. Human or horse rather than sheep erythrocytes are recommended for use in the haemolysin assay.     

The equilibrium partitioning of titanium between Ti3+ and Ti4+ valency states in CaO-SiO2-TiO x slags

The redox behavior of titanium in CaO-SiO₂-TiO _x melts was investigated using a slag-gas equilibrium technique. Titanium partitioning between Ti³⁺ and Ti⁴⁺ valency states and the ratio of activity coefficients of TiO_1.5 and TiO₂ were determined as functions of oxygen partial pressure, temperature, and slag composition. The equilibrium experiments were carried out at temperatures between 1783 and 1903 K under CO-CO₂-Ar gas atmosphere with oxygen partial pressure ranging from 10⁻¹² to 10⁻⁷ atm (1.01×10⁻¹⁰ kPa to 1.01×10⁻⁵ kPa). The slags had CaO/SiO₂ ratios between 0.55 and 1.35 and total titanium oxide concentrations from 7 to 50 mass pct. Experimental results showed that the Ti³⁺/Ti⁴⁺ ratio in CaO-SiO₂-TiO _x slags, containing up to 50 mass pct TiO _x , increased with decreasing oxygen partial pressure and decreased with increasing CaO/SiO₂ ratio and decreasing temperature. Measured variation of the redox ratio Ti³⁺/Ti⁴⁺ with oxygen partial pressure closely followed the ideal behavior. Increasing the CaO/SiO₂ ratio increased the ratio of activity coefficients of TiO_1.5 and TiO₂. The effect of total titania content on this ratio was more complex and in accord with Raman spectroscopy data.     

Ambient‐cured polyesteramide‐based anticorrosive coatings from linseed oil—A sustainable resource

Ambient‐cured polyesteramide (APEA) coating resin synthesized from dihydroxy fatty amide obtained from linseed oil, a sustainable resource, and poly(styrene‐co‐maleic anhydride), a bifunctional acid component, was found to exhibit improved physicomechanical and anticorrosive properties. The structural elucidation of APEA resin has been carried out by FTIR, ¹H‐NMR, and ¹³C‐NMR spectroscopies. The physicomechanical and chemical resistance properties were investigated by standard methods. The corrosion resistance performance was evaluated in acid, alkali, and organic solvent. The thermal behavior was studied by TGA technique. A comparative study of these properties of APEA with reported baked polyesteramide (PEA) coatings was carried out. A remarkable improvement in the drying property of APEA was observed. The APEA coatings also showed improved physicomechanical and anticorrosive properties as compared to the baked PEA coatings. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1818–1824, 2005     

Miscibility behavior of blend of polyesteramides of linseed oil and dehydrated castor oil with poly(methacrylic acid)

Blending of two polymers in solution is a simple and cost‐effective technique to improve upon the physical and mechanical properties of the component polymers through synergism. To obtain maximum synergy in their properties, the component polymers should be miscible with each other on molecular scale. Polymer blends of complex physicomechanical properties are being actively investigated. Poly(methacrylic acid) (PMAA), a commercial polymer, yields transparent, hard, brittle, and water‐sensitive films. It has been blended with natural polymers like dextran, collagen, and gelatin to obtain films with improved physical and mechanical characteristics. Polyesteramides, which are easily synthesized from vegetable seeds oil, a sustainable resource, have found application in surface coatings. These oligomeric products do not make free standing films in the ambient condition. The polyesteramides from vegetable seeds oil can be used to obtain blend with PMMA of improved mechanical and water absorption properties. In this study, linseed oil polyesteramide (LOPEA) and dehydrated castor oil polyesteramide (DCPEA), the source oils with different unsaturation in their fatty acid chains, were blended with PMAA through mixing in solution in the ratio DCPEA/LOPEA: PMAA as 80/20, 70/30, 60/40, 50/50, 40/60, 30/70, and 20/80. In the first instance, the miscibility of the two components was investigated in solution by viscosity and ultrasonic measurements and in solid phase through differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Moisture absorption by the blend was also studied. DCPEA and LOPEA show immiscibility with PMAA in solution phase while LOPEA with more unsaturation in the fatty acid chain of the oil was found more immiscible than DCPEA. DCPEA shows a narrow miscibility window in the solid phase while LOPEA was found immiscible with PMAA in the solid phase too. Uptake of moisture was found to be markedly reduced in the blends of DCPEA/LOPEA with PMAA. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1367–1374, 2007:     

Super-Resolution image Reconstruction Based on Iteration and Wavelet Transform

In this paper, we provide a super-resolution image reconstruction algorithm based on wavelet transform. Wavelet transform can separate high frequency and low frequency information of image. The more high frequency information can be obtained by using wavelet transform and the technique of image fusion. Meanwhile, reconstructed super-resolution image is produced by the iterative method. In iteration process, noise of image can be suppressed by applying method of wavelet threshold de-noising. The experiment results show that the algorithm can overcome the disadvantage of the classical interpolation method and effectively improve the resolution and PSNR of the image.     

基围虾冻藏过程中的品质变化

通过测定基围虾不同冻藏时间点(0、1、3、5、7周)质构、多酚氧化酶(PPO)活性、脂肪氧化、脂肪酸组成、风味及鲜度的变化,探究了对虾冻藏过程中品质变化的机理。结果表明,随着冻藏时间的延长,基围虾的黏附性逐渐增加,弹性、硬度、咀嚼性显著下降。PPO活性呈现先升后降的趋势。基围虾冻藏过程中脂肪氧化水平(TBARS)不断增加,饱和脂肪酸显著增加,多不饱和脂肪酸(PUFA)显著降低。基围虾冻藏过程中共检测出50多种挥发性风味物质,其中醇类和芳香族化合物含量降低,醛、酮及含氮化合物的含量增加。由ATP、ADP、AMP和HxR及Hx等鲜度指标的测定结果可知,基围虾冻藏7周后仍比较新鲜。虽然基围虾在冻藏过程中品质和营养价值降低,但仍较新鲜。     

Thermal antioxidative kinetics of sesamol in triacylglycerols and fatty acid methyl esters of sesame,olive, and canola oils

Oxidation kinetics of the triacylglycerols (TAGs) and fatty acid methyl esters (FAMEs) of sesame, olive, and canola oils were studied in the presence of the different concentrations of sesamol (0.1%–0.16%) at 60, 80, and 100°C. Sesamol increased the temperature coefficient, T_C, and Q₁₀ number of the TAGs more significantly compared to the FAMEs. All the sesamol-added TAG and FAME systems, respectively, of the olive, canola, and sesame oils, respectively, exerted increased values of the Arrhenius (activation energy, E_a, and frequency factor, A) and Eyring (enthalpy, ΔH⁺⁺, and entropy, ΔS⁺⁺) equation parameters. Sesamol improved the Gibbs free energy (ΔG⁺⁺) of the activated complex formation in the canola, sesame, and olive systems, respectively, and the effect was greater in the FAMEs.     

A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work proposed a deep learning-based (DL) solution for the early detection of this deadly disease from histopathology images. To evaluate the robustness of the proposed method a large publically available breast histopathology image database containing a total of 277524 histopathology images is utilized. The proposed automatic diagnosis of BC detection and classification mainly involves three steps. Initially, a DL model is proposed for feature extraction. Secondly, the extracted feature vector (FV) is passed to the proposed novel feature selection (FS) framework for the best FS. Finally, for the classification of BC into invasive ductal carcinoma (IDC) and normal class different machine learning (ML) algorithms are used. Experimental outcomes of the proposed methodology achieved the highest accuracy of 92.7% which shows that the proposed technique can successfully be implemented for BC detection to aid the pathologists in the early and accurate diagnosis of BC.