SU(3)-Flavor-Analysis of Nonfactorizable Contributions to D→PpD \to Pp Decays

We study charm D - meson decays to two pseudoscalar mesons in Cabibbo favored mode employing SU(3)-flavor for the nonfactorizable matrix elements. Using $D\rightarrow \bar K \pi$ and $D_{s} \rightarrow \bar K K$ to fix the reduced matrix elements, we obtain a consistent fit for $\eta$ and $\eta'$ emitting decays of $D$ and $D_{s}$ mesons.Comment: Latex, 13 page

Fixed Points for Ciric-G-Contractions in Uniform Spaces Endowed with a Graph

In this paper, we generalize the notion of $\lambda$-generalized contractions introduced by \'Ciri\'c from metric to uniform spaces endowed with a graph and discuss on the existence and uniqueness of fixed points for this type of contractions using the basic entourages.Comment: 12 page

Deep Multi-Model Fusion for Human Activity Recognition Using Evolutionary Algorithms

Machine recognition of the human activities is an active research area in computer vision. In previous study, either one or two types of modalities have been used to handle this task. However, the grouping of maximum information improves the recognition accuracy of human activities. Therefore, this paper proposes an automatic human activity recognition system through deep fusion of multi-streams along with decision-level score optimization using evolutionary algorithms on RGB, depth maps and 3d skeleton joint information. Our proposed approach works in three phases, 1) space-time activity learning using two 3D Convolutional Neural Network (3DCNN) and a Long Sort Term Memory (LSTM) network from RGB, Depth and skeleton joint positions 2) Training of SVM using the activities learned from previous phase for each model and score generation using trained SVM 3) Score fusion and optimization using two Evolutionary algorithm such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The proposed approach is validated on two 3D challenging datasets, MSRDailyActivity3D and UTKinectAction3D. Experiments on these two datasets achieved 85.94% and 96.5% accuracies, respectively. The experimental results show the usefulness of the proposed representation. Furthermore, the fusion of different modalities improves recognition accuracies rather than using one or two types of information and obtains the state-of-art results

Preliminary study on diminution level of RNA/DNA ratio in tissue of Labeo rohita by exposure to some endocrine disrupting compounds (EDCs)

Effects of EDCs particularly on RNA/DNA ratio are yet to be investigated to manage the effluents in natural waters. We investigated exposure effects of endocrine disrupting compounds (EDCs) phthalic acid ester (PAE) and hexachlorocyclohexane (HCH) on the RNA/DNA ratio in tissue of an Indian major carp Labeo rohita. Fish were exposed to pre-determined sublethal concentrations of phthalic acid ester (Di-methyl phthalate (DMP), di-butyl phthalate (DBP), and di-(2- ethylhexyl) phthalate (DEHP) and also HCH for determining the tissue RNA/DNA ratio after 30, 60 and 90 days of exposure in the doses of 0.2 mg L-1, 0.3 mg L-1, and 0.5 mg L-1 respectively. All these tested chemicals significantly (P0.05) inhibited RNA/DNA ratio. The ratio gradually significantly (P0.05) decreased after DEHP where it was 1.9±0.51 F1, 18=15.8 P=0.014 n=19; in case of DBP it was 1.92±0.62 F1, 20=6.5 P=0.012 n=19 and for HCH it was 0.94±0.21 F1, 18=18.08 P=0.0012 n=19 at treatments concentrations of 0.3 mg L-1 and 0.5 mg L-1, compared to control (2.9±0.2) after 90 days. However, there was no statistical significance (P0.05) in RNA/DNA ratio after the DMP (F1, 20=2.4 P=0.15n=21) treatment

Deep Learning Approach to Recognize COVID-19, SARS and Streptococcus Diseases from Chest X-ray Images

Corona Virus Disease (COVID-19) became pandemic for the world in the year 2020. A large numbers of people are infected worldwide due to the rapid widespread infectious virus which is threatening many lives and economic damages. Controlling of this virus becomes challenging for the world due to non-preparedness and less availability of testing kits, necessary medical equipment, and vaccine. Pathological laboratory testing of a large number of suspects becomes challenging. Some existing pathological testing is producing false-negative results. Therefore, this paper aims to develop a method of automatic detection of transmissible diseases through medical image analysis techniques which are based on the radiological changes in the X-ray images. In this paper, a Deep Learning approach is proposed for the fast detection of COVID-19, Streptococcus, and Severe Acute Respiratory Syndrome (SARS) positive cases. In Deep Learning, 2-D Convolution Neural Network (2DCNN) is used to classify graphical features of X-ray image’s dataset of COVID-19 positive, Streptococcus and Severe Acute Respiratory Syndrome (SARS) patients. The proposed approach is implemented on the COVID-chest X-Ray dataset. Experiments produced individual accuracy of COVID-19, Streptococcus, SARS disease and normal person is 100%, 90.9%, 91.3%, and 94.7% respectively. This approach achieved an overall accuracy of 95.73% over four classes. Validation of the proposed approach results has been done using Precision, Recall, and F1-score matrices. From the experimental results, it is proved that the performance of the proposed deep learning approach is quite better as compared to the mentioned state-of-art methods to detect COVID-19, SARS, and Streptococcus disease using X-ray medical imaging

Nonfactorization in Hadronic Two-body Cabibbo-favored decays of D^0 and D^+

With the inclusion of nonfactorized amplitudes in a scheme with $N_c=3$, we have studied Cabibbo-favored decays of $D^0$ and $D^+$ into two-body hadronic states involving two isospins in the final state. We have shown that it is possible to understand the measured branching ratios and determined the sizes and signs of nonfactorized amplitudes required.Comment: 15 pages, Late

Weak Radiative Hyperon Decays and Vector Meson Dominance

We study the question whether the phenomenologically successful VMD approach to weak radiative hyperon decays can be made consistent with Hara's theorem and still yield the pattern of asymmetries exhibited by experimental data. It appears that an essential ingredient which governs the pattern of asymmetries is the off-shell behaviour of the input electromagnetic 1/2^- 1/2^+ \gamma couplings. Although this behaviour can be chosen in such a way that the experimentally observed pattern is obtained, and yet Hara's theorem satisfied, at the same time the approach yields a definite prediction for the size of weak meson-nucleon coupling constants. Comparison with experiment reveals then another conflict.Comment: Talk given at 3rd International Conference on Hyperons, Charm and Beauty Hadrons, Genoa, Italy, 30 Jun - 3 Jul 1998; To appear in Nuclear Physics B, Proceedings Supplements; 4 pages, LaTeX, uses espcrc2.sty (can be obtained from http://www.nucphys.nl