Abstract— Dentistry is a major branch of medicine. It deals with the study and the diagnosis, treatment and prevention of diseases of the oral cavity, adjacent structures and tissues . Biomedical engineering is an interdisciplinary branch of engineering science that deals with the application of engineering principles in the field of biology and medicine for the betterment of health . Being an ancient branch of medicine, dentistry largely needs a lot of technical instruments for its purpose to serve its patients .
Abstract— Modern communication systems are increasingly adopting new Morden technologies like OFDM and LDPC for achieving high performance, low Bit Error Rate (BER) and high capacity. The OFDM communication is very much inspired from the channel frequencies over the network. In such a network some kind of orthogonal distortion occurs over the channel called Inter Carrier Interference.
Abstract— The Ebola virus is one of the most dangerous viruses in Filoviridae family. It causes fatal hemorrhagic fever in both non-human and human primates. The fatality rate is up to ninety percent. There is no effective treatment against EBOV infection so far. By using host microRNAs, we have explored for potential anti-viral therapeutics against EBOV infection, which may down-regulate viral gene expression in order to suppress viral replication. We have identified eight human miRNAs from eight potential hairpin sequences of EBOV genome. Our study provided an interesting hypothesis that those miRNAs are hsa-miR-3915, hsa-miR-6750-5p, hsa-miR-4452, hsa-miR-4796-5p, hsa-miR-671-3p, hsa-miR-5096, hsa-miR-302c-3p and hsa-miR-2054. We suggested that these hairpin sequences could be use as anti-viral therapeutics to quell the replication of EBOV infection in human.
Performance evaluation of different bedding media in aquaponic system for growth and production of okra and tilapia
Abstract— Aquaponics is the marriage of aquaculture and hydroponic technologies. Present research was accomplished to evaluate the relative performance of only gravels (T1), only coconut husk (T2) and mixture of gravels and coconut husk (1:1 in volume) (T3) as media in aquaponic system to grow okra (Abelmoschus esculentus) and tilapia (Oreochromis niloticus). Each treatment had three replications of similar bedding media. Nine food grade plastic containers filled with media and a 180 liter plastic water tank were used to construct the aquaponic system for growing okra and tilapia, respectively. In each bedding container, 4 okra seeds were sown and tilapia with initial length of 13.65 ± 1.88 cm and weight of 46.04 ± 20.93 g were stocked at the rate of 144 fish/m3 in the fish tank. Tilapia were fed twice a day at the rate of 3% for premier month, 2% for next month and 1.5% of body weight for the remaining time. Fish and plants were sampled biweekly during the whole study period. Data analysis revealed that the treatment T3 performed best followed by T1 and T2, respectively in terms of okra plant growth performances with respect to duration of plant growth in different growth stages, plant height, leaf number per plant, leaf area and branch number per plant. Okra production was shown significantly greater (P ≤ 0.05) in the treatment T3 (9.08 ± 1.25 kg/m2/157 days) pursued by T1 (7.5 ± 1.83 kg/m2/157 days) and T2 (3.83 ± 2.33 kg/m2/157 days), respectively. At the termination of the study, the length gain and weight gain of tilapia were 6.64 ± 0.1 cm and 104.76 ± 20.78 g, respectively. Total tilapia yield was recorded 138.80 tons/ha/157 days with 92.3% survival and FCR of 1.96. The water quality parameters and the nutrient concentrations in influent and effluent water remained within suitable ranges for tilapia production as well as the growth of okra. Therefore, the mixture of gravels and coconut husk media showed incentive performance in plant growth and production of okra compared to the individual media and at the same time the tilapia production was also satisfactory.
Abstract— The anomaly or outlier detection is one of the applications of data mining. The major use of anomaly or outlier detection is fraud detection. Health care fraud leads to substantial losses of money each year in many countries. Effective fraud detection is important for reducing the cost of Health care system. This paper reviews the various approaches used for detecting the fraudulent activities in Health insurance claim data. The approaches reviewed in this paper are Hierarchical Hidden Markov Models and Non Negative Matrix Factorization. The data mining goals achieved and functions performed in these approaches have given in this paper.