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.     

Thermal stability of NO 2 ⋅ and NO⋅ radicals formed in an Al23 catalyst during its preparation from a nitrate precursor

During the preparation of alumina as a catalyst support from aluminium nitrates by precipitation with a NH₄OH base, NO ₂ ^⋅ radicals have been formed in the catalyst after calcination under air in the solid at different temperatures. These radicals remained stable until a calcination temperature of 800°C. When the calcined catalyst was degassed under vacuum above 300 °C, the NO ₂ ^⋅ was reduced to give NO^⋅ and O^- species which were both tightly trapped in the solid. These latter species remained stable until vacuum treatment at 800 °C. This revised version was published online in July 2006 with corrections to the Cover Date.     

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     

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.     

Polypyrrole functionalized with FePcTSA for NO2 sensor application

The nitrogen dioxide (NO₂) sensing capability of polypyrrole (PPy) was enhanced dramatically after functionalized with iron(III)phthalocyanine-4,4′,4″,4-tetrasulfonic acid monosodium salt (FePcTSA). The incorporated phthalocyanine was confirmed by different characterization techniques such as UV–vis spectroscopy, FTIR, GFAAS, EDAX, etc. The resistance of the functionalized PPy decreased spontaneously during exposure to NO₂ gas at room temperature. This material exhibited excellent stability, reversibility, and reproducibility. The lowest response time (t₅₀) thus obtained is 47 s with a highest response factor (ΔR/R₀ × 100) of 50.25.     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

Evidence of the vital role of the pore network on various catalytic conversions of N2O over Fe-silicalite and Fe-SBA-15 with the same iron constitution

Fe-silicalite and Fe-SBA-15 with similar iron content have been characterized by N₂ adsorption, small angle X-ray scattering (SAXS), wide-angle X-ray scattering (WAXS), scanning electron microscopy (SEM), high-resolution transmission electron micrographs (HRTEM), UV–vis–DRS and EPR, and tested in direct N₂O decomposition, N₂O reduction by CO and N₂O-mediated propane oxidative dehydrogenation. Both catalysts contain almost exclusively isolated Fe³⁺ sites of similar concentration and structure, which are, however, stabilized in markedly different pore geometries (intersecting channels of ca. 0.55 nm diameter in Fe-silicalite versus parallel linear pores of ca. 7.5 nm diameter in Fe-SBA-15). This aspect is of vital importance in order to exclusively ascribe different catalytic performances to the environment where the iron species are stabilized. Fe-silicalite revealed to be much more active than Fe-SBA-15 in all reactions studied. This clearly illustrates that the confinement of the iron species in pores of suitable geometry (structure and size) is essential to originate their remarkable catalytic properties. The large pores in ordered mesoporous materials apparently do not generate the required intimate contact between potentially active Fe sites and reactant molecules.