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.     

CuInS2/SiNWs/Si composite material for application as potential photoelectrode for photoelectrochemical hydrogen generation

This work aims at developing a new composite material based on nanosized semiconducting CuInS₂ (CIS) particles combined with silicon nanowires grown on a silicon substrate (SiNWs/Si) for photoelectrochemical (PEC)-splitting of water. The CIS particles were prepared via a colloidal method using N-methylimidazole (NMI) as the solvent and an annealing treatment. The SiNWs were obtained by chemical etching of silicon (100) substrates assisted by a metal. The CIS/SiNWs/Si composite material was obtained by deposition of an aliquot of a suspension of CIS particles onto the SiNWs/Si substrate, using spin coating followed by a drying step. The XRD pattern demonstrated that CuInS₂ grows in the tetragonal/chalcopyrite phase, while SiNWs/Si presents a cubic structure. The SEM images show semi-spherical particles (～10 nm) distributed on the surface of silicon nanowires (～10 μm). The EIS measurements reveal n-type conductivity for CIS, SiNWs/Si and CIS/SiNWs/Si materials, which could favour the oxidation reaction of water molecules.     

Migration of Point Defects in the Field of a Temperature Gradient

The influence of the temperature gradient over the thickness of the cladding of a fuel element of a fast-neutron reactor on the migration of point defects formed in the cladding material due to neutron irradiation has been studied. It has been shown that, under the action of the temperature gradient, the flux of vacancies onto the inner surface of the cladding is higher than the flux of interstitial atoms, which leads to the formation of a specific concentration profile in the cladding with a vacancy-depleted zone near the inner surface. The experimental results on the spatial distribution of pores over the cladding thickness have been presented with which the data on the concentration profiles and vacancy fluxes have been compared.     

A Giant Frequency Shift in the Raman Spectrum of Water Adsorbed on a Metallic Silver Surface

The Raman spectrum of water adsorbed on a metallic silver surface reveals an anomalously large shift of the vibrational frequency as compared to that in the bulk. The results are compared to data reported by other researchers, and possible interpretations of the observed phenomenon are discussed.