Окружење за анализу и оцену квалитета великих и повезаних података

Linking and publishing data in the Linked Open Data format increases the interoperability and discoverability of resources over the Web. To accomplish this, the process comprises several design decisions, based on the Linked Data principles that, on one hand, recommend to use standards for the representation and the access to data on the Web, and on the other hand to set hyperlinks between data from different sources. Despite the efforts of the World Wide Web Consortium (W3C), being the main international standards organization for the World Wide Web, there is no one tailored formula for publishing data as Linked Data. In addition, the quality of the published Linked Open Data (LOD) is a fundamental issue, and it is yet to be thoroughly managed and considered. In this doctoral thesis, the main objective is to design and implement a novel framework for selecting, analyzing, converting, interlinking, and publishing data from diverse sources, simultaneously paying great attention to quality assessment throughout all steps and modules of the framework. The goal is to examine whether and to what extent are the Semantic Web technologies applicable for merging data from different sources and enabling end-users to obtain additional information that was not available in individual datasets, in addition to the integration into the Semantic Web community space. Additionally, the Ph.D. thesis intends to validate the applicability of the process in the specific and demanding use case, i.e. for creating and publishing an Arabic Linked Drug Dataset, based on open drug datasets from selected Arabic countries and to discuss the quality issues observed in the linked data life-cycle. To that end, in this doctoral thesis, a Semantic Data Lake was established in the pharmaceutical domain that allows further integration and developing different business services on top of the integrated data sources. Through data representation in an open machine-readable format, the approach offers an optimum solution for information and data dissemination for building domain-specific applications, and to enrich and gain value from the original dataset. This thesis showcases how the pharmaceutical domain benefits from the evolving research trends for building competitive advantages. However, as it is elaborated in this thesis, a better understanding of the specifics of the Arabic language is required to extend linked data technologies utilization in targeted Arabic organizations.Повезивање и објављивање података у формату "Повезани отворени подаци" (енг. Linked Open Data) повећава интероперабилност и могућности за претраживање ресурса преко Web-а. Процес је заснован на Linked Data принципима (W3C, 2006) који са једне стране елаборира стандарде за представљање и приступ подацима на Wебу (RDF, OWL, SPARQL), а са друге стране, принципи сугеришу коришћење хипервеза између података из различитих извора. Упркос напорима W3C конзорцијума (W3C је главна међународна организација за стандарде за Web-у), не постоји јединствена формула за имплементацију процеса објављивање података у Linked Data формату. Узимајући у обзир да је квалитет објављених повезаних отворених података одлучујући за будући развој Web-а, у овој докторској дисертацији, главни циљ је (1) дизајн и имплементација иновативног оквира за избор, анализу, конверзију, међусобно повезивање и објављивање података из различитих извора и (2) анализа примена овог приступа у фармацeутском домену. Предложена докторска дисертација детаљно истражује питање квалитета великих и повезаних екосистема података (енг. Linked Data Ecosystems), узимајући у обзир могућност поновног коришћења отворених података. Рад је мотивисан потребом да се омогући истраживачима из арапских земаља да употребом семантичких веб технологија повежу своје податке са отвореним подацима, као нпр. DBpedia-јом. Циљ је да се испита да ли отворени подаци из Арапских земаља омогућавају крајњим корисницима да добију додатне информације које нису доступне у појединачним скуповима података, поред интеграције у семантички Wеб простор. Докторска дисертација предлаже методологију за развој апликације за рад са повезаним (Linked) подацима и имплементира софтверско решење које омогућује претраживање консолидованог скупа података о лековима из изабраних арапских земаља. Консолидовани скуп података је имплементиран у облику Семантичког језера података (енг. Semantic Data Lake). Ова теза показује како фармацеутска индустрија има користи од примене иновативних технологија и истраживачких трендова из области семантичких технологија. Међутим, како је елаборирано у овој тези, потребно је боље разумевање специфичности арапског језика за имплементацију Linked Data алата и њухову примену са подацима из Арапских земаља

Mercury Toxicity in Public Health

Mercury was the name of the Roman messenger of god who can move really fast. It is also called as quicksilver due to its fast movement and silvery tinge. Liquid metal state mercury (Hg) has little to no solubility and is not poisonous. But the liquid mercury can vaporize, and gaseous mercury becomes poisonous due to its nature of being absorbed into the blood. Mercury in +2 state is more poisonous due to high solubility. Mercury is the only metal that exists in liquid state at normal temperature and pressure. Mercury poisoning occurs by exposure to mercury, i.e., acute and chronic exposures. Symptoms of mercury poisoning depend on the type, dose, method, and duration of exposure. Mercury poisoning effects on the human body are not limited to reddishness of hands and feet; renal failures; cardiovascular, liver, brain, and hormonal issues; and intestinal ulceration. The present chapter describes the mercury sources, types of exposures, types of poisoning, treatments, and preventive measures of mercury poisoning

Genetic diversity analysis and DNA fingerprinting of tomato breeding lines using SSR markers

Saabunud / Received 01.04.2021 ; Aktsepteeritud / Accepted 04.06.2021 ; Avaldatud veebis / Published online 04.06.2021 ; Vastutav autor / Corresponding author: Ghassan Jaafar Hamd [email protected] is a need to expand the information on genetic relationships between tomato (Solanum lycopersicum L.) lines to improve hybridization breeding. The genetic diversity and relationships among 24 tomato lines were evaluated by simple sequence repeat (SSR) markers. A total of 65 bands were generated with 15 SSR primers, of which 64 bands were polymorphic. The mean polymorphic information content was 0.356. There was a high degree of polymorphism between tomato cultivars. The mean marker index and heterozygosity were 0.045 and 0.454, respectively. Cluster analysis grouped cultivars into 6 main clusters. The cvs. Mo. H. P, 'C. C. Orange', and 'Marb' had the greatest genetic distance from other cultivars and is suitable for hybridization to achieve maximum variability for selection in segregating populations. The data can be used to select appropriate parents in tomato hybridization breeding

Bioactivity of pyocyanin of Pseudomonas aeruginosa clinical isolates against a variety of human pathogenic bacteria and fungi species

Pyocyanin is blue pigment redox active, secondary metabolites produced by P. aeruginosa. The present study investigated the bioactivity of pyocyanin against certain types of bacteria and fungi causing human infections Objectives: Pyocyanin is blue pigment redox active, secondary metabolites produced by P. aeruginosa. The current study deals with biosynthesis, purification and bioactivity of pyocyanin produced by P. aeruginosa. Design: Pyocyanin extraction was done by chloroform method and concentration was determined by multiplying the optical density at 520 nm by 17.072 expressed as µg/ml. Biological activity of pyocyanin was determined by well diffusion procedure. Results: According to the source of infection, results showed that P. aeruginosa were most common in ear infection (30%) followed by wounds (22%), burns (17%), urine (13%) and each in stool and diabetes (9%). In this study the high resistance of  P. aeruginosa  isolates to antibiotics were 19 (82.6 %) to piperacillin followed by 10(43.5%) to aztreonem, 8(34.8%) to meropenem, 6(26.1%) to amikacin, 5(21.7%) to ciprofloxacin then 2(8.7%) to cefotaxime. the urine isolate produced the largest amount of pyocyanin (15.894 µg/ml). pyaocyanin have antimicrobial activity against Pathogenic bacteria: Shigella,  Staphyllococcus aureus and  Staphyllococcus epidermedis. and pathogenic fungi and yeast: Aspergillus niger, Penicillium spp., Rhizopus spp, Trichophyton  mentagrophyte, Rhodotorula spp., Alternaria alternate , Trichophyton rubrum and Candida spp Conclusions: cefotaxime is the best antibiotic for P. aeruginosa. Antimicrobial activity of pyocyanin against gram positive more than gram negative bacteria but less than that observed against fungi (molds and yeast)

Comparison of California Mastitis Test and somatic cell counts for detection of subclinical mastitis in crossbred cattle

Mastitis is a major constraint that severely affects milk production in dairy animals. The California Mastitis Test (CMT) is a reliable and rapid field test for the diagnosis of subclinical mastitis (SCM) which gives an indirect estimate of somatic cell count (SCC). Based on the results of CMT screening and SCC of the milk of 105 crossbred animals located in different farms in Wayanad and Calicut districts of Kerala state, the present study attempts to find the estimates of sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV), false discovery rate (FDR) and false omission rate (FOR) of CMT relative to SCC as the reference standard. The correlation and agreement between CMT and SCC were also analysed. The estimated Spearman and Kendall Tau b correlation coefficients were 0.88 and 0.76, respectively, which indicated a strong positive relationship between CMT and SCC. The sensitivity and specificity values of CMT were 1.000±0.000 and 0.510±0.071, respectively. These values indicate that the probability for an animal with mastitis to be identified using CMT is 100 per cent and the probability of correctly identifying an animal without mastitis animal is 51 per cent. The high sensitivity value of CMT in this study indicated that CMT could be used to find out the true prevalence of SCM in crossbred animals. Analysis of the data also revealed that CMT had a PPV of 0.700±0.051 and an NPV of 1.000±0.000. The calculated accuracy of CMT was 0.771±0.041. The estimated FDR and FOR were 0.300±0.051 and 0.000±0.000, respectively. Kappa statistic was used to determine the level of agreement between CMT and SCC and the kappa coefficient value was 0.53±0.07 which indicated moderate agreement

Окружење за анализу и оцену квалитета великих и повезаних података

Linking and publishing data in the Linked Open Data format increases the interoperability and discoverability of resources over the Web. To accomplish this, the process comprises several design decisions, based on the Linked Data principles that, on one hand, recommend to use standards for the representation and the access to data on the Web, and on the other hand to set hyperlinks between data from different sources. Despite the efforts of the World Wide Web Consortium (W3C), being the main international standards organization for the World Wide Web, there is no one tailored formula for publishing data as Linked Data. In addition, the quality of the published Linked Open Data (LOD) is a fundamental issue, and it is yet to be thoroughly managed and considered. In this doctoral thesis, the main objective is to design and implement a novel framework for selecting, analyzing, converting, interlinking, and publishing data from diverse sources, simultaneously paying great attention to quality assessment throughout all steps and modules of the framework. The goal is to examine whether and to what extent are the Semantic Web technologies applicable for merging data from different sources and enabling end-users to obtain additional information that was not available in individual datasets, in addition to the integration into the Semantic Web community space. Additionally, the Ph.D. thesis intends to validate the applicability of the process in the specific and demanding use case, i.e. for creating and publishing an Arabic Linked Drug Dataset, based on open drug datasets from selected Arabic countries and to discuss the quality issues observed in the linked data life-cycle. To that end, in this doctoral thesis, a Semantic Data Lake was established in the pharmaceutical domain that allows further integration and developing different business services on top of the integrated data sources. Through data representation in an open machine-readable format, the approach offers an optimum solution for information and data dissemination for building domain-specific applications, and to enrich and gain value from the original dataset. This thesis showcases how the pharmaceutical domain benefits from the evolving research trends for building competitive advantages. However, as it is elaborated in this thesis, a better understanding of the specifics of the Arabic language is required to extend linked data technologies utilization in targeted Arabic organizations.Повезивање и објављивање података у формату "Повезани отворени подаци" (енг. Linked Open Data) повећава интероперабилност и могућности за претраживање ресурса преко Web-а. Процес је заснован на Linked Data принципима (W3C, 2006) који са једне стране елаборира стандарде за представљање и приступ подацима на Wебу (RDF, OWL, SPARQL), а са друге стране, принципи сугеришу коришћење хипервеза између података из различитих извора. Упркос напорима W3C конзорцијума (W3C је главна међународна организација за стандарде за Web-у), не постоји јединствена формула за имплементацију процеса објављивање података у Linked Data формату. Узимајући у обзир да је квалитет објављених повезаних отворених података одлучујући за будући развој Web-а, у овој докторској дисертацији, главни циљ је (1) дизајн и имплементација иновативног оквира за избор, анализу, конверзију, међусобно повезивање и објављивање података из различитих извора и (2) анализа примена овог приступа у фармацeутском домену. Предложена докторска дисертација детаљно истражује питање квалитета великих и повезаних екосистема података (енг. Linked Data Ecosystems), узимајући у обзир могућност поновног коришћења отворених података. Рад је мотивисан потребом да се омогући истраживачима из арапских земаља да употребом семантичких веб технологија повежу своје податке са отвореним подацима, као нпр. DBpedia-јом. Циљ је да се испита да ли отворени подаци из Арапских земаља омогућавају крајњим корисницима да добију додатне информације које нису доступне у појединачним скуповима података, поред интеграције у семантички Wеб простор. Докторска дисертација предлаже методологију за развој апликације за рад са повезаним (Linked) подацима и имплементира софтверско решење које омогућује претраживање консолидованог скупа података о лековима из изабраних арапских земаља. Консолидовани скуп података је имплементиран у облику Семантичког језера података (енг. Semantic Data Lake). Ова теза показује како фармацеутска индустрија има користи од примене иновативних технологија и истраживачких трендова из области семантичких технологија. Међутим, како је елаборирано у овој тези, потребно је боље разумевање специфичности арапског језика за имплементацију Linked Data алата и њухову примену са подацима из Арапских земаља

Feature Based Sentiment Analysis for Service Reviews

Sentiment Analysis deals with the analysis of emotions, opinions and facts in the sentences which are expressed by the people. It allows us to track attitudes and feelings of the people by analyzing blogs, comments, reviews and tweets about all the aspects. The development of Internet has strong influence in all types of industries like tourism, healthcare and any business. The availability of Internet has changed the way of accessing the information and sharing their experience among users. Social media provide this information and these comments are trusted by other users. This paper recognizes the use and impact of social media on healthcare industry by analyzing the users' feelings expressed in the form of free text, thereby gives the quality indicators of services or features related with them. In this paper, a sentiment classifier model using improved Term Frequency Inverse Document Frequency (TF-IDF) method and linear regression model has been proposed to classify online reviews, tweets or customer feedback for various features. The model involves the process of gathering online user reviews about hospitals and 'analyzes' those reviews in terms of sentiments expressed. Information Extraction process filters irrelevant reviews, extracts sentimental words of features identified and quantifies the sentiment of features using sentiment dictionary. Emotionally expressed positive or negative words are assigned weights using the classification prescribed in the dictionary. The sentiment analysis on tweets/reviews is done for various features using Natural Language Processing (NLP) and Information Retrieval (IR) techniques. The proposed linear regression model using the senti-score predicts the star rating of the feature of service. The statistical results show that improved TF-IDF method gives better accuracy when compared with TF and TF-IDF methods, used for representing the text. The senti-score obtained as a result of text analysis (user feedback) on features gives not only the opinion summarization but also the comparative results on various features of different competitors. This information can be used by business to focus on the low scored features so as to improve their business and ensure a very high level of user satisfaction