Seasonal changes in the biochemical composition of liver in Garra mullya (Sykes)

Seasonal changes taking place in the biochemical constituents of liver of G. mullya are reported. An inverse relationship was noticed in the variation of fat and water. Maximum fat contents were observed during june-july. Reserve fat was utilized through gluconeogenesis during the spawning months. Protein and glycogen percentages were comparatively higher in liver than in the muscles and gonads. Decline in the glycogen content was associated with spawning during July to November. Nutritive values have shown more energy contents in the liver during pre-spawning months

भारत में उत्तरदायित्वपूर्ण सामुद्री मात्स्यिकी विकास

कृपया पूरा लेख पढे

Assessment of executive functions in type II diabetes patients with focus on duration of diabetes: preliminary findings of an analytical cross-sectional study

Background: Executive functions have been defined as one’s ability to plan, initiate, sequence, monitor, and inhibit complex behaviour. Executive functions are purportedly affected significantly in diabetes population; duration of diabetes having particularly negative impact. Present study was undertaken to determine whether executive functions are affected more in diabetic patients as compared to non-diabetics and to further assess the role duration of diabetes. Methods: In this analytical, cross-sectional study being conducted over 18 months period at a tertiary-care private teaching hospital in Central India, 148 participants (74 in diabetic & 74 in non-diabetic group) between the age of 30-60 years are enrolled. Preliminary data of 50 patients is presented here. The executive functions were assessed by using Delis-Kaplan Executive function system and participants was subjected to Trail making test, Design fluency test, Tower test and DKEF sorting test and the scores were compared between the two groups. Results: Statistically significant differences were observed for Trail making test (median value diabetic-7 vs. non-diabetic-10), Design fluency test (median value diabetic-10 vs. non-diabetic-10, the range varied significantly), Tower test (median value diabetic-5 vs. non-diabetic-9), DKEF sorting test (median value diabetic-7 vs. non-diabetic-8) and Sort recognition test (median value- diabetic-6 vs. non-diabetic-8). The duration of diabetes exhibited strong, statistically significant negative correlation with the four studied parameters and had weak, insignificant positive correlation with sort recognition DS. Conclusions: Executive functions are significantly affected in adult diabetes patients as compared to non-diabetic population and duration of diabetes has major contributory role in this affection

A Detailed Dominant Data Mining Approach for Predictive Modeling of Social Networking Data using WEKA

Social network has gained popularity manifold in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. In this Paper, we present the first comprehensive review of social and computer science literature on trust in social networks. We first review the existing definitions of trust and define social trust in the context of social networks. Web-based social networks have become popular as a medium for disseminating information and connecting like-minded people. The public accessibility of such networks with the ability to share opinions, thoughts, information, and experience offers great promise to enterprises and governments. As the popularity increases and they became widely used as one of the important sources of news, people become more cautious about determining the trustworthiness of the information which is disseminating through social media for various reasons. For this reason, knowing the factors that influence the trust in social media content became very important. In this research paper, we use a survey as a mechanism to study trust in social networks. First, we prepared a questionnaire which focuses on measuring the ways in which social network users determine whether content is true or not and then we analyzed the response of individuals who participated in the survey and discuss the results in a focus group session. Then, the responses, we get from the survey and the focus group was used as a dataset for modeling trust, which incorporates factors that alter trust determination. The dataset preprocessing a total of 56 records were used for building the models. This Paper applies the Decision Tree, Bayesian Classifiers and Neural Network predictive data mining techniques in significant social media factors for predicting trust. To accomplish this goal: The WEKA data mining tool is used to evaluate the J48, Na�ve Bayes and Multilayer Perception algorithms with different experiments were made by performing adjustments of the attributes and using various numbers of attributes in order to come up with a purposeful output

Istraživanje patologije i dokaz koinfekcije goveđim papiloma virusima na koži i bradavicama sisa goveda

Bovine papillomas are benign tumors of the cutaneous and mucosal epithelia and are commonly found in cattle. The productivity loss and economic impact depends on the location and degree of infection. The present study was undertaken to investigate the pathology and association of different bovine papilloma virus (BPV) types in cattle cutaneous and teat warts. Grossly, the warts were of variable size and shape (rice grain, cauliflower and finger- like horny growths or irregular). Histopathologically, the warts were diagnosed as fibropapilloma, papilloma, fibrosarcoma and hyperplasia. Fibropapilloma was the most frequent histological type observed and was characterized by hyperkeratosis, parakeratosis and acanthosis. PCR revealed the presence of either BPV-1, -2 and -5 DNA or their co-infections. Transmission electron microscopy on negative staining showed BPV-like particles. Varied copy numbers of viral DNA of BPV-1, -2 and -5 were detected by real-time PCR. Immunohistochemistry revealed the expression of Ki-67 mainly in the proliferating cells of stratum spinosum and a few basal cells in papilloma and fibropapilloma. Cyclooxygenase-2 immunostaining was observed in the cytoplasm and cell membrane of suprabasal cells. In conclusion, cutaneous and teat warts in cattle in India are more frequently associated with BPV-1/ -2 and their mixed infections, with the rare presence of BPV-5. The DNA of BPV-5 was detected for the first time in warts in India. Co-infection with two or three different viral types demonstrated the diversity of BPV types involved in warts. The frequent expression of Ki-67 in suprabasal layers may be indicative of its association with viral replication and that they are as proliferation sites.Papilomi su benigni tumori kožnog i sluzničnog epitela koji se u goveda često nalaze. Proizvodni gubici i utjecaj na ekonomičnost uzgoja ovise o lokaciji i stupnju infekcije. Ovo je istraživanje provedeno kako bi se ustanovila patologija i povezanost različitih tipova goveđih papilomavirusa (BPV) na koži i bradavicama sisa goveda. Bradavice su većinom bile različite veličine i oblika (oblika zrna riže, cvjetače i rožnate izrasline nalik na prste ili nepravilna oblika). Histopatološki su bradavice dijagnosticirane kao fibropapilomi, papilomi, fibrosarkomi i hiperplazije. Fibropapilomi su bili najčešći histološki tip, obilježeni hiperkeratozom, parakeratozom i akantozom. PCR-om je dokazan DNA virusa BPV-1, BPV-2 i BPV-5 DNA ili koinfekcije tim virusima. Negativno bojenje elektronskom transmisijskom mikroskopijom pokazalo je čestice nalik na BPV. PCR-om u stvarnom vremenu otkriveni su različiti brojevi kopija virusne DNA virusa BPV-1, BPV-2 i BPV-5. Imunohistokemijskim je pretragama pronađena ekspresija Ki-67, većinom u proliferativnim stanicama stratum spinosum i nekoliko bazalnih stanica u papilomima i fibropapilomima. Provedeno je imunobojenje ciklooksigenazom 2 u citoplazmi i staničnoj membrani suprabazalnih stanica. Zaključeno je da su u Indiji bradavice na koži i sisama u goveda mnogo češće povezane s BPV-1 i BPV-2 i mješovitim infekcijama tim virusima, dok je prisutnost virusa BPV-5 rijetka. DNA virusa BPV-5 prvi je put pronađena u bradavicama u Indiji. Koinfekcije dvama ili trima različitim virusnim tipovima pokazuje raznolikost tipova BPV-a koji se nalaze u bradavicama. Učestala ekspresija Ki-67 u suprabazalnim slojevima može upućivati na njegovu povezanost s virusnom replikacijom i mjestima proliferacije

A Detailed Dominant Data Mining Approach for Predictive Modeling of Social Networking Data using WEKA

Social network has gained popularity manifold in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. In this Paper, we present the first comprehensive review of social and computer science literature on trust in social networks. We first review the existing definitions of trust and define social trust in the context of social networks. Web-based social networks have become popular as a medium for disseminating information and connecting like-minded people. The public accessibility of such networks with the ability to share opinions, thoughts, information, and experience offers great promise to enterprises and governments. As the popularity increases and they became widely used as one of the important sources of news, people become more cautious about determining the trustworthiness of the information which is disseminating through social media for various reasons. For this reason, knowing the factors that influence the trust in social media content became very important. In this research paper, we use a survey as a mechanism to study trust in social networks. First, we prepared a questionnaire which focuses on measuring the ways in which social network users determine whether content is true or not and then we analyzed the response of individuals who participated in the survey and discuss the results in a focus group session. Then, the responses, we get from the survey and the focus group was used as a dataset for modeling trust, which incorporates factors that alter trust determination. The dataset preprocessing a total of 56 records were used for building the models. This Paper applies the Decision Tree, Bayesian Classifiers and Neural Network predictive data mining techniques in significant social media factors for predicting trust. To accomplish this goal: The WEKA data mining tool is used to evaluate the J48, Naïve Bayes and Multilayer Perception algorithms with different experiments were made by performing adjustments of the attributes and using various numbers of attributes in order to come up with a purposeful output

Bioconversion of eugenol into food flavouring agent vanillin

Microorganisms have the ability to chemically modify a wide variety of organic compounds by a process referred to as biological or microbial transformation, or in general, bioconversion. The microbial cells and their catalytic machinery (enzymes) accept a wide array of complex molecules as substrates, yielding products with unparallel chiral (enantio-), positional (region-) and chemical (chemo-) selectivity through various biochemical reactions. The present study was formulated on the objective of the conversion of abundantly available phytomolecules eugenol into vanillin, a compound of industrial importance, using microorganisms Aspergillus flavus, Aspergillus niger and Pseudomonas aeruginosa. These microbes were found to be capable of converting eugenol to industrially important cost-effective products, vanillin (used as flavouring agent). The results were analyzed using thin layer and gas chromatographic techniques. Our results demonstrated that A. flavus, A. niger and P. aerouginosa were able to transform eugenol to vanillin. Our findings may provide a novel approach for the production of cost-effective vanillin using microorganisms

Boosting Principal Component Analysis by Genetic Algorithm

This paper presents a new method of feature extraction by combining principal component analysis and genetic algorithm. Use of multiple pre-processors in combination with principal component analysis generates alternate feature spaces for data representation. The present method works out the fusion of these multiple spaces to create higher dimensionality feature vectors. The fused feature vectors are given chromosome representation by taking feature components to be genes. Then these feature vectors are allowed to undergo genetic evolution individually. For genetic algorithm, initial population is created by calculating probability distance matrix, and by applying a probability distance metric such that all the genes which lie farther than a defined threshold are tripped to zero. The genetic evolution of fused feature vector brings out most significant feature components (genes) as survivours. A measure of significance is adapted on the basis of frequency of occurrence of the surviving genes in the current population. Finally, the feature vector is obtained by weighting the original feature components in proportion to their significance. The present algorithm is validated in combination with a neural network classifier based on error backpropagation algorithm, and by analysing a number of benchmark datasets available in the open sources.Defence Science Journal, 2010, 60(4), pp.392-398, DOI:http://dx.doi.org/10.14429/dsj.60.49

Facial Recognition Attendance System

In this digital era, face recognition system plays a very important role in nearly every sector. Face recognition is one of the mostly used natural science. it'll used for security, authentication, identification, and has got a lot of blessings. Despite of obtaining low accuracy once compared to iris recognition and fingerprint recognition, it is being wide used due to its contactless and non-invasive technique. what's a lot of, face recognition system can even be used for attending marking in colleges, colleges, offices, etc. This system aims to make a class attending system that uses the thought of face recognition as existing manual attending system is time overwhelming and cumbersome to stay up. And there's conjointly prospects of proxy attending. Thus, the requirement for this technique can increase. this technique consists of four phases- data creation, face detection, face recognition, attending updating. Data is created by the pictures of the students in class. Face detection and recognition is performed exploitation Haar-Cascade classifier and native Binary Pattern chart algorithmic program severally. Faces unit detected and recognized from live streaming video of the room. attending are armored to the individual faculty at the tip of the session. it's standard that marking attending of the scholars is associate degree obligatory half in academe. standard technique of marking the attending is being followed by numerous establishments and Universities with several manual interventions. to scale back time consumption and human effort, the employment of associate degree automatic method of marking attending supported image process may be implemented. Authors have projected a sensible attending observance system through face detection and recognition techniques supported their face expression. a group of pictures of the scholars are antecedently fed to the system against that the live pictures of the scholars are compared and attending would be recorded supported facial characteristics. The projected approach uses CNN rule for coaching the pictures and LBPH visual descriptor for image classification. This models are going to be capable of providing higher degree of accuracy compared to already existing literature work. Authors have compared their experimental results with the present approaches and located satisfactory &nbsp