Gluten-free cakes with walnut flour: a technological,sensory, and microstructural approach

Walnut flour (WF), a by-product of walnut oil production, is characterised by high polyunsaturated fatty acids, proteins, and fibre contents and presents suitability for bakery products. However, when using non-traditional ingredients, it is essential to evaluate the effect on the quality properties of the final product. So, this work aimed to assess the impact of WF on the technological, physicochemical, and sensory properties of gluten-free (GF) cakes. WF was added at a flour blend (cassava (CS) and maize (MS) starches and rice flour) at 0, 10%, 15%, and 20%. The results showed that WF modified starch gelatinisation, increased amylose–lipid complex (ALC) content, and made crumbs easier to chew. Besides, the total dietary fibre (TDF) and protein content significantly increased. Cakes with 15% WF presented the highest specific volume (SV) and no differences in overall acceptability with respect to control. Hence, WF is a suitable ingredient for gluten-free bakery products.     

Influence of the silicon surface treatment by plasma etching and scratching on the nucleation of diamond grown in HFCVD - a comparative study

A comparative study for the nucleation of diamond was carried out using surface treatment like (i) surface scratching with 1 μm diamond paste and (ii) surface etching using chlorine plasma at different RF powers (50, 100 and 150 W). Atomic force microscopic study shows variation in roughness from 31 nm to 110 nm. Scratching results in random scratches, whereas plasma etches a surface uniformly. Scanning electron microscopic observations show well faceted crystallites with a predominance of angular shaped grains corresponding to 〈100〉 and 〈110〉 crystallite surfaces for the scratched as well as plasma etched substrate. Surface etching at 150 W plasma power results in a better growth in comparison with 50 and 100 W plasma powers. Chlorine-radical is found responsible for the changes in the growth morphology. Raman spectroscopy shows a sharp peak at 1,332 cm⁻¹ and a peak at ∼1,580 cm⁻¹ for both samples.     

Kidney Injury Caused by Preeclamptic Pregnancy Recovers Postpartum in a Transgenic Rat Model

Preeclampsia (PE) is characterized by the onset of hypertension (≥140/90 mmHg) and presence of proteinuria (>300 mg/L/24 h urine) or other maternal organ dysfunctions. During human PE, renal injuries have been observed. Some studies suggest that women with PE diagnosis have an increased risk to develop renal diseases later in life. However, in human studies PE as a single cause of this development cannot be investigated. Here, we aimed to investigate the effect of PE on postpartum renal damage in an established transgenic PE rat model. Female rats harboring the human-angiotensinogen gene develop a preeclamptic phenotype after mating with male rats harboring the human-renin gene, but are normotensive before and after pregnancy. During pregnancy PE rats developed mild tubular and glomerular changes assessed by histologic analysis, increased gene expression of renal damage markers such as kidney injury marker 1 and connective-tissue growth factor, and albuminuria compared to female wild-type rats (WT). However, four weeks postpartum, most PE-related renal pathologies were absent, including albuminuria and elevated biomarker expression. Only mild enlargement of the glomerular tuft could be detected. Overall, the glomerular and tubular function were affected during pregnancy in the transgenic PE rat. However, almost all these pathologies observed during PE recovered postpartum.     

Estimation in Random Coefficient Autoregressive Models

Abstract. We propose the quasi‐maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.     

Magnesium interlayered diamond coating on silicon

Diamond thin films have been deposited using hot filament chemical vapour deposition technique on manually scratched p-Si(1 0 0) substrate, with and without magnesium interlayer. In spite of magnesium melting point being lower (T_m = 649 °C) than the growth temperature of the substrate (T_s  750 °C) used in these experiments, it was found that high quality diamond films could be grown on Mg covered substrate. A liquid substrate is probably generated during the diamond film growth. Raman spectroscopy analysis exhibited only the triply degenerate, zone centre optical phonon peak at 1333 cm⁻¹ indicating that nearly stress free crystallites were present. Broadening of the Raman peak (11.76 cm⁻¹) indicates that some small crystallites also are present. Scanning electron and atomic force microscopy accompanied by X-ray diffraction analysis where used to compare the details of diamond film growth directly on scratched Si(1 0 0) and Mg interlayered scratched Si(1 0 0) substrates.     

Using multiple endmember spectral mixture analysis to retrieve subpixel fire properties from MODIS

The Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on NASA's Terra and Aqua satellites image most of the Earth multiple times each day, providing useful data on fires that cannot be practically acquired using other means. Unfortunately, current fire products from MODIS and other sensors leave large uncertainties in measurements of fire sizes and temperatures, which strongly influence how fires spread, the amount and chemistry of their gas and aerosol emissions, and their impacts on ecosystems. In this study, we use multiple endmember spectral mixture analysis (MESMA) to retrieve subpixel fire sizes and temperatures from MODIS, possibly overcoming some limitations of existing methods for characterizing fire intensities such as estimating the fire radiative power (FRP). MESMA is evaluated using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to assess the performance of FRP and MESMA retrievals of fire properties from a simultaneously acquired MODIS image, for a complex of fires in Ukraine from August 21, 2002. The MESMA retrievals of fire size described in this paper show a slightly stronger correlation than FRP does to fire pixel counts from the coincident ASTER image. Prior to this work, few studies, if any, had used MESMA for retrieving fire properties from a broad-band sensor like MODIS, or compared MESMA to higher-resolution fire data or other measures of fire properties like FRP. In the future, MESMA retrievals could be useful for fire spread modeling and forecasting, reducing hazards that fires pose to property and health, and enhancing scientific understanding of fires and their effects on ecosystems and atmospheric composition.     

Self-developing fuzzy expert system: a novel learning approach,fitting for manufacturing domain

The foremost challenge faced by expert systems, for their applicability to real world problems, is their inherent deficiency of dynamism. For an expert system to be more pragmatic and applicable, the whole structure of an expert system—including rule-base, fuzzy sets, and even user-interface—needs to be upgraded continuously. This continuous up gradation demands full-time, repetitive, and cumbersome involvement of knowledge engineers. Machine learning is an answer to this problem, but unfortunately, the solutions that have been provided are limited in scope. For example, most of the researchers put forward techniques of either generating just rules from data, or self-expanding and self-correcting knowledge-base only. The innovative approach presented in this paper is broader in scope. It enhances the efficacy and viability of expert systems to be more capable of coping with dynamic and ever-changing industrial environments. The objective is facilitated by rendering, concurrently, the self-learning, self-correcting, and self-expanding abilities to the expert system, without requiring knowledge engineering skills of the developers. This means that the user needs just to feed data in form of the values of input/output variables and the complete development of expert system is done automatically. The superiority of the proposed expert system, regarding its continuous self-development, has been explained with the help of three examples related to prediction and optimization of milling and welding processes.     

The influence of epiphylls on remote sensing of humid forests

Epiphylls - lichens, fungi, liverworts, etc. infesting leaf surfaces - are found throughout humid forests of the world. It is well understood that epiphylls inhibit light interception by host plants, but their effect on remote sensing of colonized forests has not been examined. Incorporating leaf-level spectra from Terra Firme (primary forest) and Amazonian Caatinga (woodlands/forest growing on nutrient-deficient sandy soils), we used the GeoSAIL model to propagate leaf-level measurements to the canopy level and determine their effect on commonly used vegetation indices. In Caatinga, moderate infestations (50% leaf area epiphyll cover), lowered simulated Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) values by 6.1% and 20.4%, respectively, largely due to near infrared dampening. Heavy infestation (100% cover) simulations exhibited decreases 1.5-2 times greater than those of moderate infestations. For Terra Firme, which are generally less affected by epiphylls, moderate (20% leaf area) and heavy infestations (40%) lowered EVI by 4.4% (S.D. 0.8%) and 8.1% (S.D. 1.5%), respectively. Near infrared and green reflectance were most affected at the canopy level, showing mean decreases of 10.6% (S.D. 2.25%) and 9.5% (S.D. 3.49%), respectively, in heavy Terra Firme infestations. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and the EVI and NDVI. These results suggest that, without explicit consideration of the presence of epiphylls, remote sensing-based methodologies may underestimate leaf area index, biomass and productivity in humid forests.     

Second-Order Stiffness Matrix and Loading Vector of a Beam-Column with Semirigid Connections on an Elastic Foundation

The second-order stiffness matrix and corresponding loading vector of a prismatic beam–column subjected to a constant axial load and supported on a uniformly distributed elastic foundation (Winkler type) along its span with its ends connected to elastic supports are derived in a classical manner. The stiffness coefficients are expressed in terms of the ballast coefficient of the elastic foundation, applied axial load, support conditions, bending, and shear deformations. These individual parameters may be dropped when the appropriate effect is not considered; therefore, the proposed model captures all the different models of beams and beam–columns including those based on the theories of Bernoulli–Euler, Timoshenko, Rayleigh, and bending and shear.The expressions developed for the load vector are also general for any type or combinations of transverse loads including concentrated and partially nonuniform distributed loads. In addition, the transfer equations necessary to determine the transverse deflections, rotations, shear, and bending moments along the member are also developed and presented.