α-Glucosidase, α-amylase inhibition kinetics,in vitro gastro-intestinal digestion,and apoptosis inducing abilities of Ficus microcarpa L. f. and Ficus racemosa L. fruit polysaccharides

Food Science and Biotechnology - A rich source of nutrients, figs have a number of clinically validated benefits. This study aimed to evaluate the in vitro simulated gastrointestinal digestion, and...     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Fabrication of Functional Nanofibrous Ammonia Sensor

A nanofibrous sensor for ammonia gas is fabricated by electrospinning the composite of poly(diphenylamine) (PDPA) with poly(methyl methacrylate) (PMMA) onto the patterned interdigit electrode. The composite electrospun membrane shows interconnected fibrous morphology. Functional groups in PDPA and the high active surface area of the fibrous membrane make the device detect a lower concentration of ammonia with a good reproducibility. The sensing capability of the device is studied by monitoring the changes in resistance of the membrane with different concentrations of ammonia. The changes in resistance of the membrane shows linearity with the concentration of ammonia in the limit of 10 and 300 ppm. UV-visible spectroscopy reveals the mechanism of sensing ammonia by the membrane.     

Microwave-Assisted Synthesis of Fine Particle Oxides Employing Wet Redox Mixtures

Interaction of electromagnetic radiation with a physical mixture of metal nitrates and amides/hydrazides is observed to initiate high-temperature reactions, useful for realizing several high-temperature ceramic materials. A judicious choice of such redox mixtures undergoes exothermic reactions when they couple with microwave radiation. The coupling of electromagnetic radiation with metal salts and amides/hydrazides depends on the dielectric properties of the individual components in the reaction mixture. The approach has been used to prepare γ-Fe₂O₃, Fe₃O₄, MgCr₂O₄, α-CaCr₂O₄, and La_0.7Ba_0.3MnO₃.     

Normality and Finite-State Dimension of Liouville Numbers

Liouville numbers were the first class of real numbers which were proven to be transcendental. It is easy to construct non-normal Liouville numbers. Kano (1993) and Bugeaud (2002) have proved, using analytic techniques, that there are normal Liouville numbers. Here, for a given base k ≥ 2, we give a new construction of a Liouville number which is normal to the base k. This construction is combinatorial, and is based on de Bruijn sequences.     

Compressive strength of coated rigid-rod polymer fibres

One limitation to the use of high-strength/high-modulus rigid-rod polymer fibres like poly-(p-phenylene benzobisthiazole) (PBZT) and poly-(p-phenylene benzobisoxazole) (PBZO) in composite structures is their low compressive strength. Various theories have been developed to predict compressive strength of rigid-rod fibres. In this study the critical buckling stress for rigid-rod fibres with stiff external coatings has been theoretically modelled assuming that the failure mode in compression is the microbuckling of the fibrils in shear. Our model predicts that significant improvement in fibre compressive strength will occur only when relatively thick coatings, with thickness to diameter (t/D) ratios in excess of > 0.05, are used. Experimentally measured compressive strength of aluminium coated PBZT fibres shows values in good agreement to the theory at t/D ratios of 0.006 and below. Factors related to the selection of suitable coating materials and problems associated with establishing coating performance are identified.Nomenclature P axial compressive load - P _f axial compressive load on the fibre - P _c axial compressive load on the coating - P _cr ⁱ critical buckling load in the ith case - _cr critical buckling stress - _co compressive strength of the uncoated fibre - _c compressive strength of the coated fibre - v(x) lateral deflection of a buckled fibril or coating - V _m amplitude of the lateral deflection in the mth mode - m number of half-sine waves in the deflection mode - x coordinate distance along axial direction - y coordinate distance along radial direction - coordinate distance along circumferential direction - l length of the buckling unit - N number of fibrils in the fibre - D fibre diameter - d fibril diameter - t coating thickness - I _f moment of inertia of the fibril - A _f cross-sectional area of the fibril - E _f tensile modulus of the fibre - E _c tensile modulus of the coating material - E tensile modulus of the coated fibre - G torsional shear modulus of the fibre - v_c Poisson's ratio of the coating material - _f density of the fibre - _c density of the coating material - density of the coated fibre - U _f strain-energy change in the fibre - U _c strain-energy change in the coating - T _f external work done on the fibre - T _c external work done on the coating - d/D - t/D     

Trusted consensus protocol for blockchain networks based on fuzzy inference system

The Journal of Supercomputing - Blockchain technology with its inherent security features revolutionizes the field of distributed networks and has become one of the significant areas of research....     

Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated as initial reconfigurable technologies have emerged. Hence, in this paper, it is proposed that the DWT method can be implemented on a field-programmable gate array in a digital architecture (FPGA-DA). We examined the effects of quantization on DWT performance in classification problems to demonstrate its reliability concerning fixed-point math implementations. The Advanced Encryption Standard (AES) algorithm for DWT learning used in this architecture is less responsive to resampling errors than the previously proposed solution in the literature using the artificial neural networks (ANN) method. By reducing hardware area by 57%, the proposed system has a higher throughput rate of 88.72%, reliability analysis of 95.5% compared to the other standard methods.