Miracle-dz/UniFAR-FTUs huggingface dataset:
RDF and OWL Ontology Building of Web Applications

The goal of semantic web is to understand human language with meaning. Semantic web include metadata that is called annotation. RDF and OWL both languages have standard formats for the sharing and understanding of knowledge on the web. Ontologies also originate from Semantic Web. These RDF and OWL Ontology for web application like Library System of CIIT (Comsats Institute of Information Technology) of Lahore campus can be built. With the help of this ontology we can search the data, understand and customize the data, efficient reasoning support. These OWL ontologies include classes, properties, individuals and their instances. How these classes relate with each other. All the properties related to the Book Information System have set into the data type properties, object properties and annotations. In this research study we proposed the work related to RDF and OWL Ontologies comparison between RDF and OWL ontology and XML schema relationship between the cases of this ontologies, how this ontology was helpful in our web applications. We provide the best way of building of ontology for any web application and any other organization. When the ontology is build, result is obtained by the SPARQL queries with efficient reasoning support. This ontology is developed for CLS (Comsats Library System) in Lahore campus. Manipulation of different properties and then binding of protege with eclipse to give support for user interface is important task. The results are best correctly gained through SPARQL query.
Independent pseudogenization of CYP2J19 in penguins, owls and kiwis implicates gene in red carotenoid synthesis

Carotenoids have important roles in bird behavior, including pigmentation for sexual signaling and improving color vision via retinal oil droplets. Yellow carotenoids are diet-derived, but red carotenoids (ketocarotenoids) are typically synthesized from yellow precursors via a carotenoid ketolase. Recent research on passerines has provided evidence that a cytochrome p450 enzyme, CYP2J19, is responsible for this reaction, though it is unclear if this function is phylogenetically restricted. Here I provide evidence that CYP2J19 is the carotenoid ketolase common to Aves using the genomes of 65 birds and the retinal transcriptomes of 15 avian taxa. CYP2J19 is functionally intact and robustly transcribed in all taxa except for several species adapted to foraging in dim light conditions. Two penguins, an owl and a kiwi show evidence of genetic lesions and relaxed selection in their genomic copy of CYP2J19, and six owls show evidence of marked reduction in CYP2J19 retinal transcription compared to nine diurnal avian taxa. Notably, none of these taxa are known to use red carotenoids for sexual signaling and several species of owls and penguins represent the only birds known to completely lack red retinal oil droplets. The remaining avian taxa belong to groups known to possess red oil droplets, known or expected to deposit red carotenoids in skin and/or plumage, and/or frequently forage in bright light. The loss and reduced expression of CYP2J19 is likely an adaptation to maximize retinal sensitivity, given that oil droplets reduce the amount of light available to the retina.
THE ACCESSIBILITY AND SCALABILITY OF GENE FAMILY ANALYSIS

THE ACCESSIBILITY AND SCALABILITY OF GENE FAMILY ANALYSIS by James Jackson University of New Hampshire, August, 2012 Gene family detection allows us to gain a better understanding of how different genomes are related. At UNH, we have a pipeline that computes these families using a variety of methods. However, the pipeline is inefficient, and performs poorly on large numbers of genomes. The pipeline is comprised of many Perl scripts, which are complex to use, and require specific organization of the data at each step. This means that all users of the pipeline must undergo training to understand each step of the pipeline and the intricacies of each script. The goal of my thesis is two-fold. First, I have optimized the scripts used in determining the gene families. This allows users to run gene family analysis on any number of genomes, without using excessive amounts of memory. My second step was to create a web interface for the pipeline. Each user is given an account that they can use to create pipeline projects. Within a project, users can simply upload their data, create the jobs they wish to run, and the web interface takes care of all the details. The server structures their data in the correct form, and the pipeline scripts are run automatically. The results are produced in an easy to understand format, and can be downloaded by the users. We have taken this interface, and have created a machine image containing all the tools needed to run the pipeline, and have made it available publicly on the Amazon Elastic Compute Cloud.
INTRODUCING PRESSURE FOR EXPRESSIVITY INTO LANGUAGE EVOLUTION EXPERIMENTS

I present a language evolution experiment that integrates two evolutionary pressures (for learnability and for expressivity) and two directions of language transmission (vertical and horizontal). Members of each generation of a diffusion chain are given a communication task. The experiment shows that the compositionality of their languages increases over generations, but the reproduction fidelity does not. Moreover, the compositionality of the input language is a good predictor for the compositionality of the output language, but not for the reproduction fidelity. These results, together with the analysis of intragenerational alignment, allow to estimate the contribution of each kind of pressure and each transmission way.
A Bayesian Foundation for Active Stereo Vision1

Sensing three-dimensional shape is a central problem in the development of robot systems for autonomous navigation and manipulation. Stereo vision is an attractive approach to this problem in several applications; however, stereo algorithms still lack reliability and generality. We address these problems by modelling the stereo depth map as a discrete random field, by formulating the matching problem in terms of Bayesian estimation, and by using this framework to develop a "bootstrap" procedure that employs fine camera motion to initialize stereo fusion. First, one camera is translated parallel to the stereo baseline to acquire a narrow-baseline image pair; then, the depth map obtained from the narrow-baseline image pair is used to constrain matching in a "wide-baseline" image pair consisting of one image from each camera. The result of our procedure is an estimate of depth and depth uncertainty at each pixel in the image. This approach produces accurate depth maps reliably and efficiently, applies to indoor and outdoor domains, and extends naturally to multi-sensor systems. We demonstrate the potential of this approach by showing results c lined with scale models of difficult, outdoor scenes.
Different Machine Learning Algorithms for Breast Cancer Diagnosis

Breast cancer affects many people at the present time. The factors that cause this disease are many and cannot be easily determined. Additionally, the diagnosis process which determines whether the cancer is benign or malignant also requires a great deal of effort from a doctors and physicians . When several tests are involved in the diagnosis of breast cancer, such as clump thickness, uniformity of cell size, uniformity of cell shape,. etc, the ultimate result may be difficult to obtain, even for medical experts. This has given a rise in the last few years to the use of machine learning and Artificial Intelligence in general as diagnostic tools. We aimed from this study to compare different classification learning algorithms significantly to predict a benign from malignant cancer in Wisconsin breast cancer dataset. We used the Wisconsin breast cancer dataset to compare five different learning algorithms , Bayesian Network, Naive Bayes, Decision trees J4.8 , ADTree, and Multi-layer Neural Network along with t-test for the best algorithm in terms of prediction accuracy. The experiment, has shown that Bayesian Network is significantly better than the other algorithms.
Sperm DNA Fragmentation Assays Correlate with Sperm Abnormal Morphology and the Pregnancy Outcome

Purpose: A retrospective study of 89 hypo-fertile male patients attending for in vitro fertilization was undertaken in order to evaluate possible correlations among sperm DNA damage, sperm analysis parameters and pregnancies. Methods: Sperm parameters (concentration, normal morphology and multiple anomalies) were evaluated according to the World Health Organization guidelines. DNA damages were simultaneously evaluated on each sperm sample by i) sperm chromatin decondensation test; ii) sperm DNA fragmentation evaluated by Sperm Chromatin Dispersion and Halo sperm Kit; iii) sperm DNA fragmentation evaluated by the Terminal Uridine Nick-End Labelling procedure. Results: Statistical analysis was performed by using analysis of variance and least squares regression. The sperm chromatin dispersion and fragmentation assays showed a statistically significant positive correlation (P=0.0017) in all the samples confirming the good efficacy of either of the two tests in detecting sperm DNA damage. Both the two test negatively correlated with normal sperm morphology (P=0.008), however only by using Halo sperm test we obtained a significant correlation with multiple sperm pathological morphologies (P=0.029) and an inverse correlation with pregnancies outcome (P=0.013). No correlation was detected among DNA damages, sperm concentration and chromatin decondensation. Conclusions: These data suggest a similar efficacy of sperm chromatin dispersion and Terminal Uridine Nick-End Labelling in detecting sperm DNA integrity. Due to the higher sensitivity of Halo test, its prognostic role in the diagnosis of fertilizing ability of a semen sample and possible pregnancy rate is discussed
Vegetally localized Vrtn functions as a novel repressor to modulate bmp2b transcription during dorsoventral patterning in zebrafish

The vegetal pole cytoplasm represents a critical source of maternal signals for patterning the primary dorsoventral axis of the early embryo. Vegetally localized dorsal determinants are essential for the formation of the Spemann organizer, which expresses both bone morphogenetic proteins and their antagonists. The extracellular regulation of BMP signalling activity has been well characterized, however, transcriptional regulation of bmp genes along the dorsoventral axis remains largely unknown. Here, we report a novel mode of maternal regulation of BMP signalling in the lateral and ventral regions by analyzing the unexpected dorsalizing effect following vegetal yolk ablation experiment. We identified Vrtn as a novel vegetally localized maternal factor displaying dorsalizing activity. It functions as a novel transcriptional repressor to regulate bmp2b expression in the marginal region. Mechanistically, Vrtn binds bmp2b upstream sequence and inhibits its transcription independently of maternal Wnt/ß-catenin signalling. By creating vrtn loss-of-function mutation and analyzing maternal-zygotic mutant embryos, we further showed that Vrtn is required for the formation of dorsoventral axis. Our work thus unveils a novel maternal mechanism regulating BMP gradient during dorsoventral specification.
Heterogeneity of normal human breast stem and progenitor cells as revealed by transcriptional profiling

During development and pregnancy, the human mammary gland undergoes extensive remodeling in processes driven by populations of stem and progenitor cells. We recently reported that breast cancers are also hierarchically organized and driven by distinct populations of cancer stem cells characterized as CD44+CD24low/− or by expression of Aldehyde dehydrogenase (ALDH). These sets of markers identify largely non-overlapping mesenchymal and epithelial populations, each of which is capable of tumor initiation when transplanted into immunosuppressed mice. Less is known about these two populations, individually or their overlap, in the normal human mammary gland. The goal of this study was to understand the biology of the ALDH+ and CD44+CD24− populations in the normal human breast, using flow cytometry based sorting paired with functional ex vivo analyses, RNA-sequencing, and single cell RNA expression profiling. ALDH+ cells and ALDH−CD44+CD24− cells, generally, have epithelial-like and mesenchymal-like characteristics, respectively. Despite this, there are substantial similarities in the biological pathways activated in both populations when compared to differentiated cells. Additionally, we found a substantial proportion of cells that simultaneously express ALDH+ and CD44+CD24− whose abundance varies between individuals. At the single cell level, these cells have the greatest mammosphere forming capacity and express high levels of stemness and EMT-associated genes including ID1, SOX2, TWIST1, and ZEB2. Through unbiased analysis of individual ALDH+ cells, we find cells with either epithelial or mesenchymal expression phenotypes. We also identify a subpopulation of cells with a hybrid epithelial/mesenchymal expression phenotype that overexpress genes associated with aggressive triple negative breast cancers. These results highlight the utility of single cell analyses to characterize tissue heterogeneity, even in marker enriched cell populations, and further identifies the genes and pathways that define this heterogeneity.
Genetic Architecture and Molecular Networks Underlying Leaf Thickness in Desert-Adapted Tomato Solanum pennellii

Thicker leaves allow plants to grow in water-limited conditions. However, our understanding of the genetic underpinnings of this highly functional leaf shape trait is poor. We used a custom-built confocal profilometer to directly measure leaf thickness in a set of introgression lines (ILs) derived from the desert tomato species Solanum pennellii, and identified quantitative trait loci (QTL). We report evidence of a complex genetic architecture of this trait and roles for both genetic and environmental factors. Several ILs with thick leaves have dramatically elongated palisade mesophyll cells and, in some cases, increased leaf ploidy. We characterized thick ILs 2-5 and 4-3 in detail and found increased mesophyll cell size and leaf ploidy levels, suggesting that endoreduplication underpins leaf thickness in tomato. Next, we queried the transcriptomes and inferred Dynamic Bayesian Networks of gene expression across early leaf ontogeny in these lines to compare the molecular networks that pattern leaf thickness. We show that thick ILs share S. pennellii-like expression profiles for putative regulators of cell shape and meristem determinacy, as well as a general signature of cell cycle related gene expression. However, our network data suggest that leaf thickness in these two lines is patterned by at least partially distinct mechanisms. Consistent with this hypothesis, double homozygote lines combining introgression segments from these two ILs show additive phenotypes including thick leaves, higher ploidy levels and larger palisade mesophyll cells. Collectively, these data establish a framework of genetic, anatomical, and molecular mechanisms that pattern leaf thickness in desert-adapted tomato.
Development of Psychophysical Methods for Estimating Human Odour Detection Thresholds

III DEDICATION . IV ACKNOWLEDGEMENTS . V TABLE OF CONTENTS . VII LIST OF FIGURES . IX LIST OF TABLES . XIII CHAPTER I – GENERAL INTRODUCTION . 1 1.1 Psychophysics . 2 1.2 Theories about Sensory Thresholds . 8 1.3 Odour Detection Thresholds . 26 1.4 Investigation of Psychophysical Methods for Odour Threshold Measurement . 34 1.5 Review of Current Methods for Estimating Odour Thresholds . 38 1.6 Objectives of this Thesis . 48 CHAPTER II – THE EFFECT OF STOPPING RULES ON THRESHOLDS ESTIMATED WITH ASTM E679 . 53 2.
Whole Genome Sequencing of Drought Stress Tolerance Endophytic Bacterium Enterobacter sp.Mr1

Bacteria which live inside the plant and not affected to plant are called Endophytic bacteria. Endophytes help plant to the growth, health and development of their host plant. The present studies on isolation of endophytic bacteria from drought tolerance plant Butea monosperma. Genome sequencing was performed in Ion-torrent (Personal Genome Machine). A total of 82.10 Mb data with 505,210 reads was obtained. GC content of the genome is 52.8%. A total of 80 RNA sequence were identified, of which 8 genes were responsible for 5S rRNA synthesis, 1 gene for 16S rRNA synthesis and 1 gene for 23S rRNA synthesis [1]. The genome size of Enterobacter sp. MR1 was found to be 4.58 Mb and its closest neighbors were Enterobactersp. 638 (Genome ID: 399742.10) and Enterobacter cloacaesubsp. cloacae ATCC 13047 (Genome ID: 716441.4).
Popularity Prediction for Entities on SNS Using Semantic Relations

In social networking service (SNS), popularity of an entity (e.g., person, company and place) roles an important criterion for people and organizations, and several studies pose to predict the popularity. Although recent papers which addressing the problem of predicting popularity use the attributes of entity itself, typically, the popularity of entities depends on the attributes of other semantically related entities. Hence, we take an approach exploiting the background semantic structure of the entities. Usually, many factors affect a person’s popularity: the occupation, the parents, the birthplace, etc. All affect popularity. Predicting the popularity with the semantic structure is almost equivalent to solving the question: What type of relation most affects user preferences for an entity on a social medium? Our proposed method for popularity prediction is presented herein for predicting popularity, on a social medium of a given entity as a function of information of semantically related entities using DBpedia as a data source. DBpedia is a large semantic network produced by the semantic web community. The method has two techniques: (1) integrating accounts on SNS and DBpedia and (2) feature generation based on relations among entities. This is the first paper to propose an analysis method for SNS using semantic network.
Sequence Length Variation and Transmembrane Analysis of Contagious Bovine Pleuropneumonia (CBPP) and Contagious Caprine Pleuropneumonia (CCPP) Proteins

A total of forty (40) contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) proteins comprising 20 each of cattle and goats were retrieved from the GenBank (www.ncbi.nlm.nih.gov). The Genbank accession numbers of the sequences and sequence variations of the proteins were used to investigate the molecular identity of various CBPP and CCPP proteins. The protein molecules of the CBPP and CCPP proteins had varied amino acid sequences. This indicated that the genome that coded for the building of their protein molecule exhibited high level of polymorphism. The CBPP and CCPP protein’s amino acid sequences were subjected to transmembrane domain identification using TMbase. The Transmembrane of CBPP revealed that the inside to outside and outside to inside are significant while that of CCPP inside to outside only sequence position from 354-370 is significant and outside to inside only sequence position from 353-370 is significant. Phylogenetic trees analysis by Neighbor-Joining (NJ) trees were constructed using CBPP and CCPP protein sequences. The evolutionary distances were computed using the Poisson correction method. The reliability of the trees was calculated by bootstrap confidence values with 1000 bootstrap iterations using MEGA 5.1 software. Similar CBPP and CCPP proteins tend to cluster together compared to proteins that are distantly related in both species. This could be seen among others in the closeness of protein P62415-Phosphoglycerate kinase-bovine and KEY84661-Phosphoglycerate kinase-caprine. The study concluded that new typing tool may help improve the surveillance and control of the disease, as well as to trace new epidemics.
Focused Crawler Based on Domain Ontology and FCA

Focused crawler is a web crawler that aims to selectively seeking out web pages which are relevant to a predefined set of crawling topics, instead of searching the whole Web exhaustively. In this paper, we propose an effective focused web crawling method which based on domain ontology and Formal Concept Analysis (FCA). The method construct a core similarity graph based on WordNet and concept relatedness firstly, and then combining with concept lattice knowledge, a Similarity Concept Context Graph (SCCG) is built. On the basis of SCCG, a focused web crawling method which can measure a page’s expected relevancy to a given topic and determine which URL should be crawled firstly is proposed. Experimental result shows our approach has higher recall rates than the standard breadth-first approach, the approach with Context Graph (CG) and the approach with Relevancy Context Graph (RCG). In conclusion, the result demonstrates the effectiveness and significance of our approach.
WISKI - A Software Package For Acquisition, Analysis And Administration Of Time Series Data

This paper describes the WISKI Hydrological, Meteorological, and Environmental data management software package. In this paper are primarily concerned with hydrological data management. WISKI is a Microsoft WindowsTM based client/server system that uses relational databases, and was designed in cooperation with water agency authorities, engineers and hydrologists. It combines the modem standards of data management with advanced tools to collect, edit, store, and present time series data to intranet, intemet and GIS users. WISKI consists of three parts, a remote data acquisition server, a central database server for storage and management, and a WindowsTM based hydrological workbench. The system allows automatic and effortless flow of time series data from the measuring site to the database. Data are reviewed using powerfid graphical and tabular interface tools. Accepted data are then ready for further analysis using either internal or external statistical and modeling packages. The WISKI package is a complete solution for decision support and management of resources or events.
Molecular Mechanisms of Antisense Oligonucleotides.

In 1987, when I became interested in the notion of antisense technology, I returned to my roots in RNA biochemistry and began work to understand how oligonucleotides behave in biological systems. Since 1989, my research has focused primarily on this topic, although I have been involved in most areas of research in antisense technology. I believe that the art of excellent science is to frame large important questions that are perhaps not immediately answerable with existing knowledge and methods, and then conceive a long-term (multiyear) research strategy that begins by answering the most pressing answerable questions on the path to the long-term goals. Then, a step-by-step research pathway that will address the strategic questions posed must be implemented, adjusting the plan as new things are learned. This is the approach we have taken at Ionis. Obviously, to create antisense technology, we have had to address a wide array of strategic questions, for example, the medicinal chemistry of oligonucleotides, .