Understanding diversity is important in our inclusive society to hedge against ignorance and accommodate plural perspectives. Diversity nowadays can be observed in online social spaces. People from different backgrounds (e.g. gender, age, culture, expertise) are interacting every day around online digital objects (e.g. videos, images and web articles) leaving their social content in different format, commonly as textual comments and profiles. The social clouds around digital objects (i.e. user comments, user profiles and other metadata of digital objects) offer rich source of information about the users and their perspectives on different domains. Although, researchers from disparate disciplines have been working on understanding and measuring diversity from different perspectives, little has been done to automatically measure diversity in social clouds. This is the main objective of this research. This research proposes a semantic driven computational model to systematically represent and automatically measure diversity in a social cloud. Definitions from a prominent diversity framework and Semantic Web techniques underpin the proposed model. Diversity is measured based on four diversity indices - variety, balance, coverage and (within and across) disparity with regards to two perspectives – (a) domain, which is captured in user comments and represented by domain ontologies, and (b) user, which is captured in profiles of users who made the comments and represented by a proposed User Diversity Ontology. The proposed model is operationalised resulting in a Semantic Driven Diversity Analytics Tool (SeDDAT), which is responsible for diversity profiling based on the diversity indices. The proposed approach of applying the model is illustrated on social clouds from two social spaces - open (YouTube) and closed (Active Video Watching (AVW-Space)). The open social cloud shows the applicability of the model to generate diversity profiles of a large pool of videos (600) with thousands of users and comments. Closed social clouds of two user groups around same set of videos illustrate transferability and further utility of the model. A list of possible diversity patterns within social clouds is provided, which in turn deepen the understanding of diversity and open doors for further utilities of the diversity profiles. The proposed model is applicable in similar scenarios, such as in the social clouds around MOOCs and news articles.

 Human milk contains an abundant supply and diverse array of oligosaccharides that are known to impart significant health benefits to the nursing infant including establishment and maintenance of a healthy gut microflora, immune development and protection against gastro intestinal infections. When breastfeeding is not possible or insufficient, infant formulas are commonly used as an alternative. However, limited information is available about the presence of naturally occurring oligosaccharides in these infant formulas and their likely health benefits. The present study examined the presence of naturally occurring oligosaccharides in commercial goats’ milk-based stage 1 and stage 2 infant formulas and their prebiotic and anti-infection properties. LC/MS was used to detect and quantify oligosaccharides and their prebiotic potential was assessed by their ability, at concentrations present in reconstituted ready-to-use infant formula, to promote the growth of Bifidobacterium animalis subsp. lactis BB12, B. longum BB536, Lactobacillus acidophilus 4461 and L. casei 2607 in vitro. For anti-infection properties, the ability of goat milk oligosaccharides to prevent the adhesion of Escherichia coli NCTC 10418 and a Salmonella typhimurium isolate to Caco-2 cells was investigated. The results showed the presence off ourteen quantifiable oligosaccharides instage1andstage2goats’milk-basedinfantformula.Thiswassimilartothenumberofoligosaccharidesdetectedinthefreshgoats’milk.Of these, five were structurally similar to those foundinhumanmilk.Theseoligosaccharideswereshowntosignificantlyenhancethegrowthof bifidobacteria and lactobacilli and reduce the adhesion of E. coli NCTC 10418 and S. typhimurium to Caco-2 cells. Together, these results suggest that oligosaccharides naturally present in goats’ milk-based infant formula exhibit strong prebiotic and anti-pathogen adhesion properties and may confer gut health benefits to infants.

Age prediction is an active study field that can substantially affect many computer vision problems like object recognition. In this paper, an accurate system with extensive experiments is proposed to provide an efficient and accurate approach for age range prediction of people from their facial images. Histogram Equalization technique is used to reduce the illumination effects on all facial images taken from FG-NET and UTD aging databases, and image resizing is used to unify all image sizes. Moreover, Histogram of Oriented Gradient (HOG) and Local Binary Pattern (LBP) are used to extract the features of these images. Then, Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) are used for the classification processes. To evaluate the performance of the proposed system, both Leave-One-Out (LOO) and Confusion Matrix (CM) are used. The extensive and intensified experiments improved the age range predicting performance up to 98.6%.

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Produce is increasingly recognized as a reservoir of human pathogens and transferable antibiotic resistance genes. This study aimed to explore methods to characterize the transferable resistome of bacteria associated with produce. Mixed salad, arugula, and cilantro purchased from supermarkets in Germany were analyzed by means of cultivation- and DNA-based methods. Before and after a nonselective enrichment step, tetracycline (TET)-resistant Escherichia coli were isolated and plasmids conferring TET resistance were captured by exogenous plasmid isolation. TET-resistant E. coli isolates, transconjugants, and total community DNA (TC-DNA) from the microbial fraction detached from leaves or after enrichment were analyzed for the presence of resistance genes, class 1 integrons, and various plasmids by real-time PCR and PCR-Southern blot hybridization. Real-time PCR primers were developed for IncI and IncF plasmids. TET-resistant E. coli isolated from arugula and cilantro carried IncF, IncI1, IncN, IncHI1, IncU, and IncX1 plasmids. Three isolates from cilantro were positive for IncN plasmids and bla_CTX-M-1 From mixed salad and cilantro, IncF, IncI1, and IncP-1β plasmids were captured exogenously. Importantly, whereas direct detection of IncI and IncF plasmids in TC-DNA failed, these plasmids became detectable in DNA extracted from enrichment cultures. This confirms that cultivation-independent DNA-based methods are not always sufficiently sensitive to detect the transferable resistome in the rare microbiome. In summary, this study showed that an impressive diversity of self-transmissible multiple resistance plasmids was detected in bacteria associated with produce that is consumed raw, and exogenous capturing into E. coli suggests that they could transfer to gut bacteria as well.

ABSTRACT To our knowledge all the previous researches and studies for extracting the likely cause of emotion spikes was for comments and reviews with non-Arabic languages. Although, According to a study performed by Semiocast , Arabic was the fastest growing language on Twitter in 2011, and was the 6th most used language on Twitter in 2012. While a wide range of Arabic opinionated posts are broadcasted, research in the area of Arabic sentiment analysis remain sparse and show a very slow progress compared to that being carried out in other languages, mainly in English . For that, our work will be to identifying the likely causes of strong and sudden change of emotions within the temporal dimension of influential users’ emotion flow in Arabic Twitter we chose twitter because Twitter as a microblogging platform, receives over 500 million tweets worldwide every day as per 2016.These emotion spikes are the reaction of users toward certain events. Hence, our system will try to extracts keyphrases, which associated with each identified emotion spike, and passes them to an analyze step. Then the system will detect the named-entities and events or topics identification since the extracted keyphrases indicate a change on user’s emotions, and represent the causes of a particular emotion spike. 

Modelling diversity is especially valuable in soft skills learning, where contextual awareness and understanding of different perspectives are crucial. This paper presents an application of a diversity analytics pipeline to generate domain diversity profiles for learners as captured in their comments while watching videos for learning a soft skill. The datasets for analysis were collected from a series of studies on learning presentation skills with Active Video Watching system (AVW-Space). Two user studies (with 37 postgraduates and 140 undergraduates, respectively) were compared. The learners’ diversity and personal profiles are used to further understand and highlight any notable patterns about their domain coverage on presentation skills.

Colour image watermarking has become one of the most important algorithms for copyright protection. The following paper will present an innovative scheme for watermarking blind colour images using the discrete wavelet transform (DWT), fast Walsh Hadamard transform (FWHT) and the Hessenberg decomposition as its basis. First, two-level DWT followed by FWHT are used to decompose the host image’s red channel. Next, the FWHT coefficients are split into 4× 4 non-overlapping blocks. Then, each selected block is decomposed using Hessenberg decomposition, where the first row, first column element of the upper Hessenberg matrix H is quantified to embed the watermark information. Peak signalto-noise ratio, normalized cross-correlation and structural similarity index measure are used to evaluate the feasibility and the robustness. The experimental results have demonstrated that the proposed watermarking scheme is highly invisible with PSNR> 40 dB, for several watermarked colour images, with a capacity of 4096 bits and execution time of 0.7415 s. The proposed watermarking scheme is also highly resistant to both common image processing and geometrical attacks such as filtering, JPEG2000, noise adding, cropping, scaling, blurring and sharpening, and others

Plants are colonized by diverse microorganisms, which may positively or negatively influence the plant fitness. The positive impact includes nutrient acquisition, enhancement of resistance to biotic and abiotic stresses, both important factors for plant growth and survival, while plant pathogenic bacteria can cause diseases. Plant pathogens are adapted to negate or evade plant defense mechanisms, e.g. by the injection of effector proteins into the host cells or by avoiding the recognition by the host. Plasmids play an important role in the rapid bacterial adaptation to stresses and changing environmental conditions. In the plant environment, plasmids can further provide a selective advantage for the host bacteria, e.g. by carrying genes encoding metabolic pathways, metal and antibiotic resistances, or pathogenicity-related genes. However, we are only beginning to understand the role of mobile genetic elements and horizontal gene transfer for plant-associated bacteria. In this review, we aim to provide a short update on what is known about plasmids and horizontal gene transfer of plant associated bacteria and their role in plant-bacteria interactions. Furthermore, we discuss tools available to study the plant-associated mobilome, its transferability, and its bacterial hosts.