Semantic conflict resolution ontology (SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts

Establishing semantic interoperability among heterogeneous information sources has been a critical issue in the database community for the past two decades. Despite the critical importance, current approaches to semantic interoperability of heterogeneous databases have not been sufficiently effective. We propose a common ontology called semantic conflict resolution ontology (SCROL) that addresses the inherent difficulties in the conventional approaches, i.e., federated schema and domain ontology approaches. SCROL provides a systematic method for automatically detecting and resolving various semantic conflicts in heterogeneous databases. SCROL provides a dynamic mechanism of comparing and manipulating contextual knowledge of each information source, which is useful in achieving semantic interoperability among heterogeneous databases. We show how SCROL is used for detecting and resolving semantic conflicts between semantically equivalent schema and data elements. In addition, we present evaluation results to show that SCROL can be successfully used to automate the process of identifying and resolving semantic conflicts.     

Detection and Classification of Diabetic Retinopathy Using DCNN and BSN Models

Diabetes is associated with many complications that could lead to death. Diabetic retinopathy, a complication of diabetes, is difficult to diagnose and may lead to vision loss. Visual identification of micro features in fundus images for the diagnosis of DR is a complex and challenging task for clinicians. Because clinical testing involves complex procedures and is time-consuming, an automated system would help ophthalmologists to detect DR and administer treatment in a timely manner so that blindness can be avoided. Previous research works have focused on image processing algorithms, or neural networks, or signal processing techniques alone to detect diabetic retinopathy. Therefore, we aimed to develop a novel integrated approach to increase the accuracy of detection. This approach utilized both convolutional neural networks and signal processing techniques. In this proposed method, the biological electro retinogram (ERG) sensor network (BSN) and deep convolution neural network (DCNN) were developed to detect and classify DR. In the BSN system, electrodes were used to record ERG signal, which was pre-processed to be noise-free. Processing was performed in the frequency domain by the application of fast Fourier transform (FFT) and mel frequency cepstral coefficients (MFCCs) were extracted. Artificial neural network (ANN) classifier was used to classify the signals of eyes with DR and normal eye. Additionally, fundus images were captured using a fundus camera, and these were used as the input for DCNN-based analysis. The DCNN consisted of many layers to facilitate the extraction of features and classification of fundus images into normal images, non-proliferative DR (NPDR) or early-stage DR images, and proliferative DR (PDR) or advanced-stage DR images. Furthermore, it classified NPDR according to microaneurysms, hemorrhages, cotton wool spots, and exudates, and the presence of new blood vessels indicated PDR. The accuracy, sensitivity, and specificity of the ANN classifier were found to be 94%, 95%, and 93%, respectively. Both the accuracy rate and sensitivity rate of the DCNN classifier was 96.5% for the images acquired from various hospitals as well as databases. A comparison between the accuracy rates of BSN and DCNN approaches showed that DCNN with fundus images decreased the error rate to 4%.     

Evaluation of concentration dependant diffusion coefficients of carbon in a dissimilar joint of ferritic steels

When dissimilar weldments between 9Cr-1Mo and 2¼Cr-1Mo ferritic steels are exposed to high temperature, microstructural and microchemical modifications are observed near the weld interface. Diffusion of carbon driven by the activity gradient from low Cr to high Cr steel leads to the formation of carbon enriched ‘hard’ zone and carbon depleted ‘soft’ zone near the fusion joint. The present paper deals with the measurement of carbon diffusion profiles and the evaluation of concentration dependent diffusion coefficients of carbon across the interface at a temperature of 1023 K. Accurate carbon concentration profiles are generated using carbon calibration graph. The profiles are smoothened to reduce the experimental scatter and the concentration dependant diffusion coefficients are determined using Den Broeder’s method. In the base materials, where the concentration gradient is extremely small, D(c) values are determined using Hall’s method. Variation in D(c) across the weld interface is understood based on the microstructural and microchemical changes that take place during heat treatment.     

Factors influencing arsenic and nitrate removal from drinking water in a continuous flow electrocoagulation (EC) process

An experimental study was conducted under continuous flow conditions to evaluate some of the factors influencing contaminant removal by electrocoagulation (EC). A bench-scale simulation of drinking water treatment was done by adding a filtration column after a rectangular EC reactor. Contaminant removal efficiency was determined for voltages ranging from 10 to 25 V and a comparative study was done with distilled water and tap water for two contaminants: nitrate and arsenic(V). Maximum removal efficiency was 84% for nitrate at 25 V and 75% for arsenic(V) at 20 V. No significant difference in contaminant removal was observed in tap water versus distilled water. Increase in initial As(V) concentration from 1 ppm to 2 ppm resulted in a 10% increase in removal efficiency. Turbidity in the EC reactor effluent was 52 NTU and had to be filtered to achieve acceptable levels of final turbidity (5 NTU) at steady-state. The flow regime in the continuous flow reactor was also evaluated in a tracer study to determine whether it is a plug flow reactor (PFR) or constantly stirred tank reactor (CSTR) and the results show that this reactor was close to an ideal CSTR, i.e., it was fairly well-mixed.     

A Unified Approach to the Sizing and Control of Energy Storage Systems

Grid operation and planning challenges arising out of large-scale integration of renewable power can to a large extent be solved by the use of energy storage systems (ESSs). The type and size of storage to be used may be decided by the amount of fluctuating power the storage charges or discharges to attain its objective. Storage systems can be used as single devices or as hybrid systems where two or more devices complement the working of each other. The objective of this paper is to find an accurate power and energy sizing methodology for storage devices working in a single or hybrid arrangement such that the power fed to the grid from a wind turbine generator is regulated to a constant value. A strategy for sizing of a hybrid ESS is proposed by choosing the long-term storage to be a battery energy system and the short-term device to be a flywheel and using frequency analysis techniques. In the case of flywheel energy storage system, the inertia and the gain of an integral controller applied to an induction-machine-based flywheel are obtained. The simulations are done in MATLAB.     

Green Nanosilver as Reinforcing Eco-Friendly Additive to Epoxy Coating for Augmented Anticorrosive and Antimicrobial Behavior

Epoxy resin GY250 representing diglycidyl ethers of bisphenol-A (DGEBA) was reinforced with 1, 3 and 5wt % of surface functionalized silver nanoparticles (F-AgNPs) which were synthesized using Couroupita guianensis leaves extract with a view of augmenting the corrosion control property of the epoxy resin and also imparting antimicrobial activity to epoxy coatings on mild steel. Corrosion resistance of the coatings was evaluated by EIS, potentiodynamic polarization studies and cross scratch tests. AFM, SEM, HRTEM and EDX were utilized to investigate the surface topography, morphology and elemental composition of the coatings on MS specimens. Results showed that the corrosion resistance, hardness and T_g of the DGEBA/F-AgNPs coatings increased at 1wt % of F- AgNPs. The DGEBA/F-AgNPs coatings also offered manifold antimicrobial protection to the MS surfaces by inhibiting the growth of biofilm forming bacteria like P. aeruginosa, B. subtilis, the most common human pathogen E. coli and the most virulent human pathogenic yeast C. albicans.     

Nitroarenes as Antitubercular Agents: Stereoelectronic Modulation to Mitigate Mutagenicity

Nitroarenes are less preferred in drug discovery due to their potential to be mutagenic. However, several nitroarenes were shown to be promising antitubercular agents with specific modes of action, namely, nitroimidazoles and benzothiazinones. The nitro group in these compounds is activated through different mechanisms, both enzymatic and non‐enzymatic, in mycobacteria prior to binding to the target of interest. From a whole‐cell screening program, we identified a novel lead nitrobenzothiazole (BT) series that acts by inhibition of decaprenylphosphoryl‐β‐d ‐ribose 2′‐epimerase (DprE1) of Mycobacterium tuberculosis (Mtb). The lead was found to be mutagenic to start with. Our efforts to mitigate mutagenicity resulted in the identification of 6‐methyl‐7‐nitro‐5‐(trifluoromethyl)‐1,3‐benzothiazoles (cBTs), a novel class of antitubercular agents that are non‐mutagenic and exhibit an improved safety profile. The methyl group ortho to the nitro group decreases the electron affinity of the series, and is hence responsible for the non‐mutagenic nature of these compounds. Additionally, the co‐crystal structure of cBT in complex with Mtb DprE1 established the mode of binding. This investigation led to a new non‐mutagenic antitubercular agent and demonstrates that the mutagenic nature of nitroarenes can be solved by modulation of stereoelectronic properties.     

PHYSIOLOGICAL AND MORPHOLOGICAL CHANGES IN IMMOBILIZED L. PLANTARUM NCIM 2084 CELLS DURING REPEATED BATCH FERMENTATION FOR PRODUCTION OF LACTIC ACID

L. Plantarum NCIM 2084 cells are homofermentative, essentially producing lactic acid as the main end product of glucose fermentation. Prolonged use through repeated batch fermentation with the cells of L. plantarum immobilized on chitosan treated polypropylene matrix showed a shift in the metabolic pathway from the homofermentative to heterofermentative, accompanied by morphological changes in immobilized cells from the normal rod shape to the coccoid shape. These changes appear to be related to a shift in the bacterial cell metabolism, resulting in a decrease in lactic acid yields.     

Spectral distribution of photocurrent in poly(6-tert-butyl-3-methyl-3,4-dihydro-2H-1,3-benzoxazine)

The spectral distribution of photoconductivity in poly(6-tert-butyl-3-methyl-3,4-dihydro-2H-1,3-benzoxazine) was studied in the sandwich configuration with indium tin oxide and silver electrodes. The photocurrent was found to originate mainly from the bulk dissociation of excitons with lesser contribution from electrode-mediated exciton dissociation. The molecule was fluorescent, but in the presence of the electron acceptor molecule 2,4,6-trinitrophenol (TNP), the intensity was reduced. The reduction in fluorescence intensity corresponded to an increase in photocurrent. The molecule showed photoconductivity in the visible without any sensitizers, which makes it suitable for stable photorefractive composites.