Miracle-dz/UniFAR-FTUs huggingface dataset:
Tag-Based Integrated Semantic Ontology Construction and Evolution

In this research, we propose a methodology for ontology construction and evolution using tags from tag-cloud to improve availability of analysis and utilization of large scale of data. It is possible to construct semantic relationships among tags. To do this, one way of building of relationships among tags is use of a popularized tag as a thing of ontology. However, it is not easy to select the popularized tag from tag cloud and to build a complete ontology with all of tags in the tag-cloud because tags are timely and dynamically updated added with tremendous numbers of tags. Therefore, we construct Primitive Ontologies (POs). A general tag is used to as a thing of a PO. The general tag is matched into one of requested keywords by users. In addition, we propose a methodology to evolve ontology using tags. To construct and evolve a PO, it defines classes and relationships between given tags by a user. Finally, the constructed several POs are integrated into a Tag-Based integrated Semantic ontology (TBiSont) by building relationships between classes that are included in each different PO. The construction of relationships among tags depends on linked resources into tags. The properties of tags are usually characterized by linked resources. It causes to extract semantic relationships among tags, because tags are comprised of meta-information that represents properties of resources. Thereby, the proposed PO is constructed by a general tag as a best-referring tag and relationships among tags including the general tag. The TBiSont as an integration of POs was applied into data analysis and a search process to verify efficiency of as in application systems. When we applied TBiSont into searching, it shows that TBiSont is more efficient than the other statistical-based search systems to increase accuracy or diversity of search results.
Correlation Distance based Information Extraction System at FIRE 2016 Microblog Track

The FIRE 2016 Microblog track provided a set of tweets posted during the Nepal earthquake on April 2015, and a set of seven topics. The challenge was to extract all tweets relevant to each topic. In this method, separate word bags are constructed for each topic describing a generic information need during a disaster situation using topic seed words, stemmers, dictionary and other NLP tools. The topic word bags have been populated with scrambled words that generally appear as noise words in tweet texts. The correlation distance between the topic word bag vectors and each tweet text vector is computed. The correlation distance measure is used to compute the relevance score of each tweet to each topic. Special consideration is taken for the topics that are conditioned on the presence of organization names, location names and Geo locations. Organization names and location names are identified on the crawled tweet texts. The presence of geo locations in the crawled tweets is also identified by the tweet parser. The system response is generated by ordering tweet ids in descending order of their relevance score with respect to each topic. The evaluation scores of the submitted system in terms of Precision@20, Recall@1000, Map@1000 and Overall Map have been reported as 0.4357, 0.3420, 0.0869 and 0.1125 respectively. The evaluation scores of the system without the scrambled noisy words in the word bag vectors in terms of Precision@20, Recall@1000, Map@1000 and Overall Map have been reported as 0.4000, 0.3401, 0.0860 and 0.1119 respectively. The results indicate that the precision of the information extraction system depends on considering the presence of scrambled noisy words in the tweet texts.
On the optimal boolean function for prediction under quadratic loss

Suppose Y n is obtained by observing a uniform Bernoulli random vector Xn through a binary symmetric channel. Courtade and Kumar asked how large the mutual information between Y n and a Boolean function b(Xn) could be, and conjectured that the maximum is attained by the dictator function. An equivalent formulation of this conjecture is that dictator minimizes the prediction cost in sequentially predicting Y n under logarithmic loss, given b(Xn). In this paper, we study the question of minimizing the sequential prediction cost under a different (proper) loss function - the quadratic loss. In the noiseless case, we show that majority asymptotically minimizes this prediction cost among all Boolean functions. We further show that for weak noise, majority is better than dictator, and that for strong noise dictator outperforms majority. We conjecture that for quadratic loss, there is no single Boolean function that is simultaneously optimal at all noise levels.
Author ' s personal copy Comparison of digestive proteinases in three penaeids

a r t i c l e i n f o Recently, several groups of researchers reported that besides serine proteinases, other classes of proteinases may be involved in crustacean's food protein digestion, including cysteine and aspartic proteinases. In this paper, a comparative study of the class and type of digestive proteinases of whiteleg shrimp Penaeus vannamei, blue shrimp Penaeus stylirostris, and yellowleg shrimp Penaeus californiensis is addressed, along with some operational characteristics. The substrate-SDS-PAGE zymogram of the three species showed varieties of different proteinases that were species-specific and proteinase composition that may be used for species identification or population studies. In the three species, trypsin and chymotrypsin were present as isoenzymes. Some active bands were active at acid pH and were partially inhibited by pepstatin A and based on bibliography information they are digestive enzymes. The involvement of these enzymes in food protein digestion is discussed and compared with digestive enzymes present in other decapod species. This and additional information expand the knowledge about enzyme food protein digestion in crustaceans, making clear that digestion process is more complex than previously alleged and if common patrons exist, there are some individualities. This information opens a line of research trying to fully understand the mechanism of protein digestion. With the advent of genomic era, nutrition and food sciences are moving to individualize or personalize food and nutrition, and ultimately health by tailoring the food to the individual or population genotype, this merged science is called Nutrigenomics. Into doing so, it is necessary to identify what genome derived molecules are involved in processing food. In this study we describe proteinases of digestive system of three commercial shrimp species, including operational parameters. This information, with others to come, will help to understand if proteinases, as it happens for Penaeus vannamei, are present as isoenzymes, enzymes with same specificity for the substrate and reaction but coming from different genes, and can be used as population markers for feeding trials while aquafarming. The research is supported by the knowledge that shrimp nutritional, functional and organoleptic properties are influenced by what is fed and how food or feed is processed by the digestive system. Other important potential contribution is that the precise knowledge of enzymes present in the digestive gland of penaeids may help to design strategies to extend the shelf life of the seafood product. Hydrolyzing of exogenous protein by the digestive system and endogenous …
The Number of Cultural Traits Is Correlated with Female Group Size but Not with Male Group Size in Chimpanzee Communities

What determines the number of cultural traits present in chimpanzee (Pan troglodytes) communities is poorly understood. In humans, theoretical models suggest that the frequency of cultural traits can be predicted by population size. In chimpanzees, however, females seem to have a particularly important role as cultural carriers. Female chimpanzees use tools more frequently than males. They also spend more time with their young, skewing the infants' potential for social learning towards their mothers. In Gombe, termite fishing has been shown to be transmitted from mother to offspring. Lastly, it is female chimpanzees that transfer between communities and thus have the possibility of bringing in novel cultural traits from other communities. From these observations we predicted that females are more important cultural carriers than males. Here we show that the reported number of cultural traits in chimpanzee communities correlates with the number of females in chimpanzee communities, but not with the number of males. Hence, our results suggest that females are the carriers of chimpanzee culture.
A New Scheme for Nucleotide Sequence Signature Extraction

In this paper, we have proposed a new method that extracts a set of signatures from different nucleotide groups via measuring the distances between the groups. The proposed method not only extracts automatically the signatures of different sizes via constraint relaxation, but also provides the locations of signatures in a sequence while it measures the relative distance between the groups, which provides a convenience for understanding the information on nucleotide. The performance of the proposed method is demonstrated through simulations and analysis
On the semantic security of cellular automata based pseudo-random permutation using results from the Luby-Rackoff construction

This paper proposes a semantically secure construction of pseudo-random permutations using second-order reversible cellular automata. We show that the proposed construction is equivalent to the Luby-Rackoff model if it is built using non-uniform transition rules, and we prove that the construction is strongly secure if an adequate number of iterations is performed. Moreover, a corresponding symmetric block cipher is constructed and analysed experimentally in comparison with popular ciphers. Obtained results approve robustness and efficacy of the construction, while achieved performances overcome those of some existing block ciphers.
The landmark variation improvement on the different modalities for the facial sketch features detection

Facial feature detection studies on the same modality have been conducted by many researchers, but the research results cannot be implemented on the different modality, only a few studies that can be used to detect the facial features on the different modality. In this research, we proposed method to detect the facial features on the different modality. The deviation standard on the landmark variations improvement has been considered as parameters to improve the moving direction toward the corresponding features. The experimental results show that the detection accuracy of our proposed method is 91.944% for the 1st model and 91.46% for the 2nd model. Our proposed method has been shown outperformed the mixture model method.
Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63–0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited.
The structure of the KlcA and ArdB proteins reveals a novel fold and antirestriction activity against Type I DNA restriction systems in vivo but not in vitro

Plasmids, conjugative transposons and phage frequently encode anti-restriction proteins to enhance their chances of entering a new bacterial host that is highly likely to contain a Type I DNA restriction and modification (RM) system. The RM system usually destroys the invading DNA. Some of the anti-restriction proteins are DNA mimics and bind to the RM enzyme to prevent it binding to DNA. In this article, we characterize ArdB anti-restriction proteins and their close homologues, the KlcA proteins from a range of mobile genetic elements; including an ArdB encoded on a pathogenicity island from uropathogenic Escherichia coli and a KlcA from an IncP-1b plasmid, pBP136 isolated from Bordetella pertussis. We show that all the ArdB and KlcA act as anti-restriction proteins and inhibit the four main families of Type I RM systems in vivo, but fail to block the restriction endonuclease activity of the archetypal Type I RM enzyme, EcoKI, in vitro indicating that the action of ArdB is indirect and very different from that of the DNA mimics. We also present the structure determined by NMR spectroscopy of the pBP136 KlcA protein. The structure shows a novel protein fold and it is clearly not a DNA structural mimic.
Computational Difficulty of Computing the Density of States

We study the computational difficulty of computing the ground state degeneracy and the density of states for local Hamiltonians. We show that the difficulty of both problems is exactly captured by a class which we call #BQP, which is the counting version of the quantum complexity class quantum Merlin Arthur. We show that #BQP is not harder than its classical counting counterpart #P, which in turn implies that computing the ground state degeneracy or the density of states for classical Hamiltonians is just as hard as it is for quantum Hamiltonians.
Much Ado About Nothing: the Mixed Models Controversy Revisited

We consider a well‐known controversy that stems from the use of two mixed models for the analysis of balanced experimental data with a fixed and a random factor. It essentially originates in the different statistics developed from such models for testing that the variance parameter associated to the random factor is null. The corresponding hypotheses are interpreted as that of null random factor main effects in the presence of interaction. The controversy is further complicated by different opinions regarding the appropriateness of such hypothesis. Assuming that this is a sensible option, we show that the standard test statistics obtained under both models are really directed at different hypotheses and conclude that the problem lies in the definition of the main effects and interactions. We use expected values as in the fixed effects case to resolve the controversy showing that under the most commonly used model, the test usually associated to the inexistence of the random factor main effects addresses a different hypothesis. We discuss the choice of models, and some further problems that occur in the presence of unbalanced data.
A Physical Model for the Coevolution of QSOs and Their Spheroidal Hosts

We present a physically motivated model for the early coevolution of massive spheroidal galaxies and active nuclei at their centers. Within dark matter halos, forming at the rate predicted by the canonical hierarchical clustering scenario, the gas evolution is controlled by gravity, radiative cooling, and heating by feedback from supernovae and from the growing active nucleus. Supernova heating is increasingly effective with decreasing binding energy in slowing down the star formation and in driving gas outflows. The more massive protogalaxies virializing at earlier times are thus the sites of the faster star formation. The correspondingly higher radiation drag fastens the angular momentum loss by the gas, resulting in a larger accretion rate onto the central black hole. In turn, the kinetic energy carried by outflows driven by active nuclei can unbind the residual gas, thus halting both the star formation and the black hole growth, in a time again shorter for larger halos. For the most massive galaxies the gas unbinding time is short enough for the bulk of the star formation to be completed before Type Ia supernovae can substantially increase the Fe abundance of the interstellar medium, thus accounting for the α-enhancement seen in the largest galaxies. The feedback from supernovae and from the active nucleus also determines the relationship between the black hole mass and the mass, or the velocity dispersion, of the host galaxy, as well as the black hole mass function. In both cases the model predictions are in excellent agreement with the observational data. Coupling the model with GRASIL (Silva et al. 1998), the code computing in a self-consistent way the chemical and spectrophotometric evolution of galaxies over a very wide wavelength interval, we have obtained predictions in excellent agreement with observations for a number of observables that proved to be extremely challenging for all the current semianalytic models, including the submillimeter counts and the corresponding redshift distributions, and the epoch-dependent K-band luminosity function of spheroidal galaxies.
SV40 Utilizes ATM Kinase Activity to Prevent Non-homologous End Joining of Broken Viral DNA Replication Products

Simian virus 40 (SV40) and cellular DNA replication rely on host ATM and ATR DNA damage signaling kinases to facilitate DNA repair and elicit cell cycle arrest following DNA damage. During SV40 DNA replication, ATM kinase activity prevents concatemerization of the viral genome whereas ATR activity prevents accumulation of aberrant genomes resulting from breakage of a moving replication fork as it converges with a stalled fork. However, the repair pathways that ATM and ATR orchestrate to prevent these aberrant SV40 DNA replication products are unclear. Using two-dimensional gel electrophoresis and Southern blotting, we show that ATR kinase activity, but not DNA-PKcs kinase activity, facilitates some aspects of double strand break (DSB) repair when ATM is inhibited during SV40 infection. To clarify which repair factors associate with viral DNA replication centers, we examined the localization of DSB repair proteins in response to SV40 infection. Under normal conditions, viral replication centers exclusively associate with homology-directed repair (HDR) and do not colocalize with non-homologous end joining (NHEJ) factors. Following ATM inhibition, but not ATR inhibition, activated DNA-PKcs and KU70/80 accumulate at the viral replication centers while CtIP and BLM, proteins that initiate 5′ to 3′ end resection during HDR, become undetectable. Similar to what has been observed during cellular DSB repair in S phase, these data suggest that ATM kinase influences DSB repair pathway choice by preventing the recruitment of NHEJ factors to replicating viral DNA. These data may explain how ATM prevents concatemerization of the viral genome and promotes viral propagation. We suggest that inhibitors of DNA damage signaling and DNA repair could be used during infection to disrupt productive viral DNA replication.
Mechanism of regulation of glucose transport in Rhizobium leguminosarum

Multiple glucose transport systems were distinguished in Rhizobium leguminosarum. We found nonlinear Lineweaver-Burk plots for the uptake of glucose, 2-deoxy-D-glucose, and alpha-methyl-D-glucoside, and this implied the existence of at least two uptake mechanisms. Different patterns of inhibition of 2-deoxy-D-glucose uptake and alpha-methyl-D-glucoside uptake at 0.1 mM by various carbohydrates revealed differences in the stereospecificities of the transport systems. Osmotic shock treatment abolished transport activities, and two independent glucose-binding activities were detected in the supernatants. Induction of glucose transport was repressed strongly by L-malate, even in the presence of excess D-glucose. Rhizobium bacteroids showed no significant glucose uptake activity at different oxygen concentrations. These results suggested that glucose transport is repressed by dicarboxylic acids during R. leguminosarum symbiosis.
Order Formation in Learning Nonlinear Robust Control Systems by Use of Neural Networks

In designing controllers, robustness against uncertainties is very important property, therefore we proposed design methods of nonlinear robust control system by use of neural networks. Competition between a neural network, which acts as a robust controller and uncertainties of the plant, plays a very important role to be robust, and simple order formation, such as power law scaling, can be found in a set of trained robust controllers. Such simple order is widely found in nature and complex systems, but learning methods without considering uncertainties has never formed such relations. Therefore competitive learning will have important relationship to order formation in various systems.
Simulating Language Learning in Community of Agents Using Self-Organizing Maps

In this article, we present a model of a cognitive system, or an agent, with the following properties: it can perceive its environment, it can move in its environment, it can perform some simple actions, and it can send and receive messages. The main components of its internal structure include a working memory, a semantic memory, and a decision making mechanism. In our implemented simulation model, the agent associates linguistic expressions and vis ual perceptions. The main motivation for communication is to exchange information. The linguistic expressions are not symbolic but pattern-like. With the current framework and simulation tool, we wish to provide a useful model for language emergence based on the unsupervised learning paradigm among a community of communicating autonomous agents. In the future, we plan to include other aspects of cognitive modeling including more realistic multimodal information processing, anticipatory decision making, language evolution, and emotional modeling.
The meaning of natural environment occupations: Exploring the experiences of Sierra Club members

Poets and writers have long lauded the beauty and necessity of nature. More recent literature and research has provided support for the healthful benefits of the natural environment. This literature spans the breadth of many disciplines. Yet, very little occupational therapy literature focuses on the natural environment. This is somewhat surprising given occupational therapy’s focus on space and place. This thesis explores the experience of participation in natural environment occupations by adult members of the Sierra Club. Five Sierra Club members were interviewed and two local Sierra Club outings were observed. Qualitative data analysis revealed two major themes: childhood beginnings and adult values, and positive health benefits. This research adds to the paucity of occupational therapy literature on the natural environment and sheds light on the various benefits of natural environment occupations.