Studies on clustering of chilli (Capsicum annum L.) genotypes based on genetic distance

Mahalanobis' D2 statistics was used to analyse forty-five chilli (Capsicum annum L.) genotypes based on eighteen characters in order to pick out supreme potential parents for hybridization. Based on D2 values, the genotypes were divided into eleven groups with extreme divergence. Cluster I had the majority of genotypes (sixteen), whereas the fewest genotypes were identified in clusters VII, VIII, X and XI (one). Cluster XI had the greatest distance within the cluster. Clusters V and XI had the maximum generalized distance between them, followed by clusters VII and XI, clusters IV and VII, clusters IV and V and clusters II and XI. This suggests that the genotypes in these groups had more genetic variation. Following cluster VII and VIII, cluster V showed the highest cluster mean for green, dry fruit yield (846g and 95.50g) and several yield-related features. At clusters I, II and VI, no observation for high cluster means but had fair trait performance. It may be suggested to directly advance the genotypes from clusters V, VII, VII in hybridization to obtain unique recombinants

Automated object detection of mechanical fasteners using faster region based convolutional neural networks

Mechanical fasteners are widely used in manufacturing of hardware and mechanical components such as automobiles, turbine & power generation and industries. Object detection method play a vital role to make a smart system for the society. Internet of things (IoT) leads to automation based on sensors and actuators not enough to build the systems due to limitations of sensors. Computer vision is the one which makes IoT too much smarter using deep learning techniques. Object detection is used to detect, recognize and localize the object in an image or a real time video. In industry revolution, robot arm is used to fit the fasteners to the automobile components. This system will helps the robot to detect the object of fasteners such as screw and nails accordingly to fit to the vehicle moved in the assembly line. Faster R-CNN deep learning algorithm is used to train the custom dataset and object detection is used to detect the fasteners. Region based convolutional neural networks (Faster R-CNN) uses a region proposed network (RPN) network to train the model efficiently and also with the help of Region of Interest able to localize the screw and nails objects with a mean average precision of 0.72 percent leads to accuracy of 95 percent object detectio

Multi-Objective Optimization in Friction Welding Process Parameters on EN353 Alloy Steel using Taguchi based GRA

Joining of similar materials by varying the input factors on a continuous drive friction welding process is done in this study. The intention is to find the optimal solution in friction welding input process parameters. Among several types of welding processes, friction welding forms good metal joints. The process factors considered for this material joining practice are Upset Time (UT), Heating Time (HT), Heating Pressure (HP), Upset Pressure (UP), chemical composition and measurements of the materials. Frictional joints provide better mechanical properties, hence it is attracted by researchers. Here, EN353 is used as the specimen, for its extensive usage in the automobile and manufacturing sectors. Axial shortening, hardness testing and the temperature during welding are evaluated, compared and optimized using Taguchi Design of Experiments (DoE) scheme using L27 orthogonal array and Grey Relational Analysis (GRA)

Diaqua­dichloridobis(pyridine-κN)manganese(II)

The molecular title compound, [MnCl2(C5H5N)2(H2O)2], lies about an inversion centre. The MnII atom is in an all-trans octa­hedral environment defined by two water mol­ecules, two chloride anions and two pyridine ligands. An inter­molecular hydrogen-bonding inter­action between a water mol­ecule and a chloride anion bonded to an adjacent MnII atom generates an eight-membered ring. The crystal packing exhibits two inter­molecular π–π stacking inter­actions between the aromatic rings, with centroid–centroid distances of 3.485 (12) and 3.532 (12) Å

Potentiation of general anaesthetic activity of ketamine by memantine

Background: The study was done with the objective to evaluate synergistic activity of ketamine induced general anesthesia by memantine in wistar albino rats.Methods: The wistar albino rats of either sex were divided into four groups of five animals. Group 1 received ketamine 40 mg/kg, group 2 received ketamine 80 mg/kg, group 3 received ketamine 40 mg/kg along with memantine 10 mg/kg and group 4 received 80 mg of ketamine along with memantine 10 mg/kg to evaluate the synergistic activity of ketamine induced general anesthesia by memantine. The sleep latency time and duration of sleep were measured in all the groups.Results: The sleep latency time of group 4 is significantly decreased (p<0.001) compared to all other groups. The duration of sleep of group 4 is significantly increased (p<0.001) compared to group 1 and group 3, but less than that of group 1.Conclusions: Memantine possess synergistic activity of ketamine induced general anaesthesia

Preliminary Screening of Antimicrobial Properties of Few Medicinal Plants

Crude extracts were prepared from the leaves of ten medicinal plants viz., Alpinia galanga, Artabotrys uncinatus, Commelina benghalensis, Costus igneus, Euphorbia cyathopora, Justicia gendarussa, Kalanchoe pinnata, Panicum antidotale, Sauropus androgynous and Hibiscus using methanol as solvent and screened for their antibacterial activity against ten bacterial pathogens. The tested gram positive bacterial strains were Bacillus cerus, Bacillus megaterium, Micrococcus leuteus, Staphylococcus aureus, Streptococcus lactis, and gram negative strains were Pseudomonas aeruginosa, Escherichia coli, Enterobacter aerogenes, Klebsiella pneumoniae and Salmonella typhimurium. Among the ten plants tested, the methanol extracts of Alpinia galanga, Artabotrys uncinatus, Costus igneus and Yellow Hibiscus exhibited higher antibacterial activity when compared to the other plant extracts. These four plant extracts were further used for the phytochemical analysis. Results of the phytochemical analysis indicated the presence of alkaloids, phenolic compounds and flavanoids. The antibacterial activities of the leaves were due to the presence of various secondary metabolite

Improving knowledge of street food vendors through an educational intervention in Kandy district, Sri Lanka

Background: Street food sector plays an important role in urban areas of many developing countries in catering to the needs of the urban population. Contamination of ready to eat food and beverages sold by street food vendors rendering them unacceptable for human consumption has become a global problem. The aim of this study was to evaluate the effectiveness of providing a health educational programme in improving knowledge related to food safety on street food vendors.Methods: Study used a quasi-experimental pre-test, post-test design. Evaluation instruments consisted of a questionnaire and a checklist. A total number of 427 street food vendors were included. A visual educational intervention was developed to provide training to all vendors in the intervention area. The study areas covered were method of food contamination, personal hygiene, safe food handling of potentially hazardous street vended food and time temperature control.Results: The results of the pre intervention survey showed that the baseline knowledge was poor. Vendors had unfavorable views particularly towards available facilities and support services. It was revealed that over 50% of the study population had received information on safe food handling though public health inspectors. Post intervention showed knowledge had improved significantly in the intervention group in all subject areas, when compared to control group (p<0.001).Conclusions: Health education intervention was effective in improving knowledge of the street food vendors in safe food handling practices and food borne disease prevention

Comparison of α-glucosyl hesperidin of citrus fruits and epigallocatechin gallate of green tea on the Loss of Rotavirus Infectivity in Cell Culture

A number of secondary plant metabolites (e.g., flavonoids) possess antiviral/antimicrobial activity. Most flavonoids, however, are difficult to study, as they are immiscible in water-based systems. The relatively new semisynthetic α-glucosyl hesperitin (GH), and the natural plant product epigallocatechin gallate (EGCG) are unique among most flavonoids, as these flavonoids are highly soluble. The antiviral activity of these plant metabolites were investigated using the rotavirus as a model enteric virus system. Direct loss of virus structural integrity in cell-free suspension and titration of amplified RTV in host cell cultures was measured by a quantitative enzyme-linked immunosorbent assay (qEIA). After 30 min. 100 × 103 μg/ml GH reduced RTV antigen levels by ca. 90%. The same compound reduced infectivity (replication in cell culture) by a similar order of magnitude 3 to 4 days post inoculation. After 3 days in culture, EGCG concentrations of 80, 160, and 320 μg/ml reduced RTV infectivity titer levels to ca. 50, 20, and 15% of the control, respectively. Loss of RTV infectivity titers occurred following viral treatment by parallel testing of both GH and EGCG, with the latter, markedly more effective. Cytotoxicity testing showed no adverse effects by the phenolic concentrations used in this study. The unique chemical structure of each flavonoid rather than each phenolic’s inherent solubility may be ascribed to those marked differences between each molecule’s antiviral (anti-RTV) effects. The solubility of EGCG and GH obviated our need to use potentially confounding or obfuscating carrier molecules (e.g., methanol, ethanol, DMSO) denoting our use of a pure system environ. Our work further denotes the need to address the unique chemical nature of secondary plant metabolites before any broad generalizations in flavonoid (antiviral) activity may be proposed