Computer is a part and parcel in our day to day life and used in various fields. The interaction of human and computer is accomplished by traditional input devices like mouse, keyboard etc. Hand gestures can be a useful medium of human-computer interaction and can make the interaction easier. Gestures vary in orientation and shape from person to person. So, non-linearity exists in this problem. Recent research has proved the supremacy of Convolutional Neural Network (CNN) for image representation and classification. Since, CNN can learn complex and non-linear relationships among images, in this paper, a static hand gesture recognition method using CNN was proposed. Data augmentation like re-scaling, zooming, shearing, rotation, width and height shifting was applied to the dataset. The model was trained on 8000 images and tested on 1600 images which were divided into 10 classes. The model with augmented data achieved accuracy 97.12% which is nearly 4% higher than the model without augmentation (92.87%).

Like synthetic fiber reinforced composites, natural fiber reinforced composites possess a good potential to be used in high performance applications due to their good balance of mechanical and damping properties. Composite materials used in sporting goods equipment and automotive applications are subjected to repeating, regular loads. Therefore a clear understanding about the reliability of composite materials under fatigue/cyclic loading is important for their design in high performance applications. Currently, the fatigue performance of natural fiber reinforced composites are not well understood or characterized. The fatigue damage of flax fiber reinforced polymer matrix composites can be divided into two components: thermal damage due to self-heating in the sample and micro-mechanical damage due to damage creation (i.e. crack initiation, crack propagation, delamination, etc.). In this study, fatigue tests were conducted at four different loading frequencies and the two energy components defined were separated experimentally. The fatigue life of flax fiber reinforced composites was found to decrease with increasing loading frequency. Thermal damage due to the high self-heating temperature of the sample was found to be the main responsible form of energy which decreases fatigue life with increasing loading frequency. Micro-mechanical damage due to cyclic loading was not found to change significantly with increasing loading frequency.

Background. Worldwide, Neisseria gonorrhoeae-related sexually transmitted infections (STIs) continue to be of significant public health concern. This obligate-human pathogen has developed a number of defenses against both innate and adaptive immune responses during infection, some of which are mediated by the pathogen’s proteins. Hence, the uncharacterized proteins of N. gonorrhoeae can be annotated to get insight into the unique functions of this organism related to its pathogenicity and to find a more efficient therapeutic target. Methods. In this study, a hypothetical protein (HP) of N. gonorrhoeae was chosen for analysis and an in-silico approach was used to explore various properties such as physicochemical characteristics, subcellular localization, secondary structure, 3D structures, and functional annotation of that HP. Finally, a molecular docking analysis was performed to design an epitope-based vaccine against that HP. Results. This study has identified the potential role of the chosen HP of N. gonorrhoeae in plasmid transfer, cell cycle control, cell division, and chromosome partitioning. Acidic nature, thermal stability, cytoplasmic localization of the protein, and some of its other physicochemical properties have also been identified through this study. Molecular docking analysis has demonstrated that one of the T cell epitopes of the protein has a significant binding affinity with the human leukocyte antigen HLA-B ∗ 15 : 01. Conclusions. The in-silico characterization of this protein will help us understand molecular mechanism of action of N. gonorrhoeae and get an insight into novel therapeutic identification processes. This research will, therefore, enhance our knowledge to find new medications to tackle this potential threat to humankind.

Development of a controlled atmosphere (CA) plant and shelf-life of fresh tomatoes at different storage conditions were studied in this research. The controlled chamber (4.5' × 4.5' × 4.5') with supplement of 1% L-ascorbic acid as antioxidant source was constructed using locally available materials. Fresh tomatoes were kept with wrapping by low density polyethylene under refrigerated and CA storage conditions. The maximum shelf-life of fresh tomato was 42 days under CA condition and followed by 35 days in refrigeration condition. Though initial cost of controlled atmosphere was high but it resulted in maximum shelf life of tomato. However, CA condition retained the physiological changes namely, color change, TSS, and weight loss of fresh tomatoes than that of stored in refrigerated condition. From nutritional point of view, it was concluded that developed CA plant could be used to extend the shelf-life of fresh tomatoes with minimum physicochemical changes throughout the storage period.