Miracle-dz/UniFAR-FTUs huggingface dataset:
LDA-based dimensionality reduction and domain adaptation with application to DNA sequence classification

Several computational biology and bioinformatics problems involve DNA sequence classification using supervised machine learning algorithms. The performance of these algorithms is largely dependent on the availability of labeled data and the approach used to represent DNA sequences as feature vectors. For many organisms, the labeled DNA data is scarce, while the unlabeled data is easily available. However, for a small number of well-studied model organisms, large amounts of labeled data are available. This calls for domain adaptation approaches, which can transfer knowledge from a source domain, for which labeled data is available, to a target domain, for which large amounts of unlabeled data are available. Intuitively, one approach to domain adaptation can be obtained by extracting and representing the features that the source domain and the target domain sequences share. Latent Dirichlet Allocation (LDA) is an unsupervised dimensionality reduction technique that has been successfully used to generate features for sequence data such as text. In this work, we explore the use of LDA for generating predictive DNA sequence features, that can be used in both supervised and domain adaptation frameworks. More precisely, we propose two dimensionality reduction approaches, LDA Words (LDAW) and LDA Distribution (LDAD) for DNA sequences. LDA is a probabilistic model, which is generative in nature, and is used to model collections of discrete data such as document collections. For our problem, a sequence is considered to be a “document” and k-mers obtained from a sequence are “document words”. We use LDA to model our sequence collection. Given the LDA model, each document can be represented as a distribution over topics (where a topic can be seen as a distribution over k-mers). In the LDAW method, we use the top k-mers in each topic as our features (i.e., k-mers with the highest probability); while in the LDAD method, we use the topic distribution to represent a document as a feature vector. We study LDA-based dimensionality reduction approaches for both supervised DNA sequence classification, as well as domain adaptation approaches. We apply the proposed approaches on the splice site predication problem, which is an important DNA sequence classification problem in the context of genome annotation. In the supervised learning framework, we study the effectiveness of LDAW and LDAD methods by comparing them with a traditional dimensionality reduction technique based on the information gain criterion. In the domain adaptation framework, we study the effect of increasing the evolutionary distances between the source and target organisms, and the effect of using different weights when combining labeled data from the source domain and with labeled data from the target domain. Experimental results show that LDA-based features can be successfully used to perform dimensionality reduction and domain adaptation for DNA sequence classification problems.
Effect of Various Physical Parameters and Statistical Medium Optimization on Production of Hyaluronic Acid Using S. Equi Subsp. Zooepidemicus ATCC 39920

It has been shown that initial conditions for bacterial cultivation are extremely important for the successful production of hyaluronic acid (HA) by fermentation. We investigated several physical parameters that affect productivity of HA under shake flask. i.e. transfer criteria of seed, agitation and aeration of fermentation flasks. Among the various physical parameters studied, inoculum age of 8-10 h, pH 6.4, optical density (600 nm) 2.0 and 3% level inoculum transfer found to be optimum. After inoculating with Streptococcus equi subsp . zooepidemicus ATCC 39920, the temperature 37 0 C and 90 rpm found optimum during growth as well as for the HA production. The fractional factorial design of six factors with two levels showed yeast extract, potassium dihydrogen phosphate and sodium bicarbonate as significant model terms. The factor potassium dihydrogen phosphate was relatively more significant than yeast extract.
Devolatilization of Organo-sulfur Compounds in Coal Gasification

Coal gasification is a thermo-chemical process aiming at the production of high heating value syngas. The coal charges present, typically, a low quantity of sulfur compounds for prevent the formation of a large amount of sulfuric acid (H2S), that is a pollutant and a poison for catalysts, in syngas stream. However, in the world there are a lot of coals that cannot be used for gasification because of their high sulfur content (e.g. Sulcis Italian coal or Inner Mongolia Chinese coal). The interest on these types of coal is increasing due to a novel technology that allows to convert H2S and CO2 into syngas (AG2S TM ). The aim of this work is to propose a predictive kinetic model of the release of sulfur compounds (e.g H2S) from coal. This kinetic scheme is implement into GASDS, a package that includes a gasifier mathematical model, which accurately describes the inter-phase mass and heat transfer. The first complexity relies in the characterization of the coal, in particular the relative amount of the different forms of sulfur components (e.g. inorganic such as pyritic and sulfates, and organic sulfur such as aliphatic, aromatic and thiophenic) and their pyrolysis and devolatilization process. The kinetic model, with the related rate parameters, is validated through comparison with experimental data from the literature and obtained during several experimental campaigns at the Sotacarbo S.p.A. pilot platform. Finally, different operating conditions of gasification are analyzed in order to obtain the best yield in the downstream process, with special reference to the novel Acid Gas to Syngas (AG2S TM ) process.
DEGRADATION OF ALKANES IN CONTAMINATED SITES

Petroleum hydrocarbons are important energy resources used by industry and in our daily life, whose production contributes highly to environmental pollution. To control such risk, bioremediation constitutes an environmentally friendly alternative technology that has been established and applied. It constitutes the primary mechanism for the elimination of hydrocarbons from contaminated sites by natural existing populations of microorganisms. Petroleum (or crude oil) is a complex mixture of hydrocarbons. Annually, millions of tons of crude petroleum oil enter the marine environment from either natural or anthropogenic sources. Hydrocarbon-degrading bacteria (HDB) are able to assimilate and metabolize hydrocarbons present in petroleum. Crude oil pollution constitutes a temporary condition of carbon excess coupled to a limited availability of nitrogen that prompts marine oil-degrading bacteria to accumulate storage compounds. This review focuses on the role and distribution in the environment of degradation bacteria and their (potential) applications in bioremediation and biocatalysis. Bacteria play an important role in the microbial degradation of oil, chlorinated hydrocarbons, fuel additives, and many other compounds. Environmental studies demonstrate the abundance of alkane degraders and have lead to the identification of many new species, including some that are (near) obligate alkanotrophs. Bioremediation is being increasingly seen as an affective, environmentally friendly treatment for contaminated shorelines from marine oil spills. Oil bioremediation is limited by the availability of nitrogen and phosphorous which are needed by the bacteria and are not present in sufficient amounts for the biodegradation of the spilled hydrocarbons.
Classification of Genotype and Age of Eyes Using RPE Cell Size and Shape

Retinal pigment epithelium (RPE) is a principal site of pathogenesis in age-related macular degeneration (AMD). AMD is a main source of vision loss even blindness in the elderly and there is no effective treatment right now. Our aim is to describe the relationship between the morphology of RPE cells and the age and genotype of the eyes. We use principal component analysis (PCA) or functional principal component method (FPCA), support vector machine (SVM), and random forest (RF) methods to analyze the morphological data of RPE cells in mouse eyes to classify their age and genotype. Our analyses show that amongst all morphometric measures of RPE cells, cell shape measurements (eccentricity and solidity) are good for classification. But combination of cell shape and size (perimeter) provide best classification. INDEX WORDS: Principal component analysis, Functional principal component analysis, Support vector machine, Random forest, Retinal pigment epithelium CLASSIFICATION OF GENOTYPE AND AGE OF EYES USING RPE CELL SIZE AND SHAPE
IMPROVING Q/A USING ARABIC WORDNET

With the expansion of the content available on the web, Question/Answering (Q/A) systems have become, among other searching tools, a focus of researchers and users as well. For the Arabic language very few works have been done in this field. In this paper, we focus on the improvement of Q/A through a Query Expansion (QE) process. Our approach is based on the ontology that we have built using Arabic WordNet. Indeed, we designed a QE process from the semantic relations existing among the concepts of our ontology. The preliminary experiments that we have conducted show that the accuracy of getting the answer expected was improved by our QE approach.
A Dual Ultra Wide Band Slotted Antenna for C and X Bands Application

In this paper, a novel compact dual-band microstrip antenna operating at two difierent bands, namely, C-band and X-band is presented and analyzed. The dual ultra wide band is realized by cutting two triangular slots on the right and on the left sides of the patch and a rectangular slot on the top side of the patch. The antenna structure is optimized and simulated using commercial software. The excitation is launched through a 50Ohms microstrip-line. According to simulation and measured results the proposed antenna can provide two separated impedance bandwidths of 500MHz centered at 7GHz and 2GHz centered at 10.7GHz and stable radiation patterns.
An Analytical Model of Mountain Wave Drag for Wind Profiles withShear and Curvature

Abstract An analytical model is developed to predict the surface drag exerted by internal gravity waves on an isolated axisymmetric mountain over which there is a stratified flow with a velocity profile that varies relatively slowly with height. The model is linear with respect to the perturbations induced by the mountain, and solves the Taylor–Goldstein equation with variable coefficients using a Wentzel–Kramers–Brillouin (WKB) approximation, formally valid for high Richardson numbers, Ri. The WKB solution is extended to a higher order than in previous studies, enabling a rigorous treatment of the effects of shear and curvature of the wind profile on the surface drag. In the hydrostatic approximation, closed formulas for the drag are derived for generic wind profiles, where the relative magnitude of the corrections to the leading-order drag (valid for a constant wind profile) does not depend on the detailed shape of the orography. The drag is found to vary proportionally to Ri−1, decreasing as Ri decreas.
Biochemical studies of a membrane protein: The KtrAB ion transporter

KtrAB is a potassium transporter, present widely among prokaryotes, which is essential for the adaptation to osmotic stress and resistance to high salinity, among other properties. This transporter is composed of two polypeptides: a membrane protein, KtrB, which facilitates ion passage, and a cytosolic protein, KtrA, that has regulatory functions and is an RCK domain (regulates conductance of potassium). Unlike the very well known potassium channels, the mechanisms by which this transporter regulates and enables ion passage are not well established and so, it is critical to obtain high resolution structures that can help understand these aspects. The aim of this project was to obtain a KtrA mutant that makes it more stable and that can help improve the diffraction quality of protein crystals resulting in higher resolution structures. In order to do so, several residues in the C-terminal domain of KtrA were mutated, both in the core and at the surface of the domain, introducing amino acids that could potentially stabilize the protein. The mutants that were tolerated were purified and tested in a thermal shift assay, which evaluated the melting temperature of each mutant. All mutants tested resulted in a stabilization of the protein structure and were combined to further improve stability. Some of the properties of final combination mutant, named KtrA CysLHDN, were evaluated. In particular, it was verified that the mutant assembles with the KtrB membrane protein and that it forms protein crystals that diffract better than the wild-type protein. As a result, a crystal structure of KtrA CysLHDN bound to ATP was obtained at 2.8 Å. The recent discovery of a new ligand that binds to the C-terminal domain of KtrA, c-di-AMP, led to a new aim in the project. This ligand was tested with the native KtrA and some mutants in thermal shift and ITC assays. It was possible to show that the ligand not only binds to KtrA, but also stabilizes the protein. This stabilization occurs when KtrA is bound to ADP but not when KtrA is bound to ATP. The ITC allowed the determination of a dissociation constant of 12 μM and a stoichiometry of 1 c-di-AMP molecule per KtrA dimer. ITC measurements confirmed the thermal shift results and c-di-AMP appears to not bind to the KtrA-ATP complex. Key-words: K transporter; KtrAB; KtrA; c-di-AMP; crystal structures; RCK domain; protein stability. FCUP Biochemical studies of a membrane protein: The KtrAB ion transporter iii
Latitudinal- and local-scale variations in a rocky intertidal interaction web

Natural assemblages are structured by a complex combination of positive and nega- tive interactions, and the relative importance of each interaction can vary across spatial scales. By using a simple interaction web (barnaclesgrazersmicrophytobenthos) in a rocky intertidal sys- tem, we tested the hypothesis that the relative strength of positive and negative interactions would vary as a function of different environmental stress between 2 latitudinal levels and local environmental conditions. We manipulated the cover of barnacles and the presence of limpets at 2 sites in northern and southern Italy and non-destructively examined the response of microphyto - benthos (MPB) (photosynthetic biomass, F0, and maximum efficiency, Fv/Fm) and of its small-sized grazers (littorinids). At northern sites, a density-dependent facilitative effect of barnacles on F0 was detected. The effect was likely due to the addition of favourable secondary habitat (i.e. bar- nacle shells) and amelioration of abiotic conditions to nearby rock. At southern sites, a positive effect of increasing barnacle cover was observed on littorinid density. The subsequent indirect trophic effect on F0, in addition to local nutrient input from anthropogenic activities, likely masked the positive effects of increasing cover of barnacles on F0 at this latitude. No factors influenced Fv/Fm, suggesting a lack of changes in the relative abundance of MPB species. There was no effect of excluding herbivores at either latitude. Results suggest that species interactions supported by foundation species might be undermined by the concomitant action of temperature-related changes and local anthropogenic stressors, whose interactive effects are likely to become more severe with global climate change.
STUDIES ON ANTIOXIDANT , ANTIHYPERGLYCEMIC AND ANTIMICROBIAL EFFECTS OF EDIBLE MUSHROOMS BOLETUS EDULIS AND CANTHARELLUS CIBARIUS

The study evaluated the antioxidant, antihyperglycemic and antimicrobial effects of both ethanolic and hydromethanolic extracts of the fruiting bodies of wild edible mushrooms Boletus edulis (penny bun) and Cantharellus cibarius (golden chanterelle) sampled in Poiana Stampei (Suceava county, Romania). The total phenolic contents of extracts were also determined. Boletus edulis hydromethanolic extract showed the highest total phenolic content (72.78±0.29 mg/g). This extract was also the most active as scavenger of DPPH and ABTS radicals (EC50=151.44±0.85 and 65.4±0.4 μg/mL, respectively) and reducing agent (EC50=46.77±0.34 μg/mL). Cantharellus cibarius ethanolic extract showed high ferrous ion chelating (EC50=82.9±0.6 μg/mL), 15-lipoxygenase (EC50=236.7±1.5 μg/mL) and αglucosidase (EC50=9.77±0.06 μg/mL) inhibitory activities. For both mushrooms, the ethanolic extracts were more active against Staphylococcus aureus ATCC 25923 than the hydromethanolic ones. The antioxidant and antihyperglycemic effects revealed in this study support further investigations for a possible valorization of both mushrooms in the dietary supplement and pharmaceutical industries.
Understanding participant loyalty intentions in virtual communities

This study proposes a conceptual model based on expectation confirmation theory with extended antecedent variables (human assets, technical assets, and complementary assets) to examine the impact of virtual communities' assets on member satisfaction and perception of usefulness. The members of JavaWorld@TW, a representative professional community in Taiwan, were chosen to participate in the survey, and 235 usable responses were collected in three months. Partial Least Square(PLS) regression were used to test the model, the findings show that satisfaction is the strongest predictor of revisiting, following perceived usefulness. Furthermore, higher confirmation of human assets, technical assets, and complementary assets are accompanied with higher positive satisfaction and perceived usefulness which influence the intention to revisit. We also advanced to explore the difference within groups, weak-tie members and strong-tie members were separated for further examination. The difference in the behavioral models of weak-tie and strong-tie, particularly in the revisit context, shed light on the importance of development related theories that can be applied to shape the post-use behavior of specific groups. Implications are proposed in the final section.
Recovering a Basic Space from Issue Scales in R

basicspace is an R package that conducts Aldrich-McKelvey and Blackbox scaling to recover estimates of the underlying latent dimensions of issue scale data. We illustrate several applications of the package to survey data commonly used in the social sciences. Monte Carlo tests demonstrate that the procedure can recover latent dimensions and reproduce the matrix of responses at moderate levels of error and missing data.
Using the Spatial Population Abundance Dynamics Engine for conservation management

An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent based, and thus best suited to small spatial or temporal scales. These approaches also often ignore financial decisions crucial to choosing management approaches on the basis of cost‐effectiveness. We created a user‐friendly and flexible modelling framework for simulating these population issues at large spatial scales – the Spatial Population Abundance Dynamics Engine (SPADE). SPADE is based on the Spatio‐Temporal Animal Reduction (STAR) model (McMahon et al. 2010) and uses a reaction–diffusion approach to model population trajectories and a cost‐benefit analysis technique to calculate optimal management strategies over long periods and across broad spatial scales. It expands on STAR by incorporating species interactions and multiple concurrent management strategies, and by allowing full user control of functional forms and parameters. We used SPADE to simulate the eradication of feral domestic cats Felis catus on sub‐Antarctic Marion Island (Bester et al., South African Journal of Wildlife Research, 32, 2002, 65) and compared modelled outputs to observed data. The parameters of the best‐fitting model reflected the conditions of the management programme, and the model successfully simulated the observed movement of the cat population to the southern and eastern portion of the island under hunting pressure. We further demonstrated that none of the management strategies would likely have been successful within a reasonable time frame if performed in isolation. Spatial Population Abundance Dynamics Engine is applicable to a wide range of population management problems and allows easy generation, modification and analysis of management scenarios. It is a useful tool for the planning, evaluation and optimisation of the management of wild populations and can be used without specialised training.
The Innovation and Productivity Effect of Foreign Take-Over of National Assets

Over the past decades, there has been a dramatic increase in the foreign-ownership of firms in the four Nordic countries Denmark, Finland, Norway and Sweden. This increase has generated interest in the welfare effect of foreign take-over of national assets. In this paper we ask: how would a firm’s behaviour and performance have been if a foreign owner had not acquired the firm? The analysis is based on a sample of 5 186 firm-level observations in four Nordic countries, of which close to 30 percent are owned by foreign companies. Using an empirical approach that accounts for both selection bias and simultaneity bias, we establish some new findings regarding foreign ownership. First, no robust difference in the propensity to be innovative can be established. Second, among the group of innovative firms, foreign-owned multinationals are generally outperformed by domestic multinationals in R&D and innovation engagement. Third, despite the fact that domestic multinationals are considerably more involved in national innovation systems than other firms, they are not producing more innovation per R&D-dollar, controlling for firm size, human capital and industry. Finally, we find that foreign take-over of firms is neutral with respect to labour productivity, and hence that no evidence of welfare gain or welfare drain of foreign ownership can be established.
The Effects of Core Stability Exercise on the Dynamic Balance of Volleyball Players

Dynamic balance is a key component of injury prevention and rehabilitation in sports. Training the core muscles has been hypothesized as an intervention for improving balance. However, there is a lack of current scientific evidence to support this claim. The purpose of this study was to evaluate the effects of a core stability program on dynamic balance of volleyball players as measured with the Star Excursion Balance Test (SEBT). Thirty healthy participants were divided into 2 groups: control and exercise groups. All participants performed the SEBT before and after 8-week exercise time. During the 8-week time, the exercise group performed a core stability program, whereas the control group abstained from any new exercise. These results also illustrated there was significant differences in the scores for pre-test and post-test of all direction according SEBT in the experimental group. An independent sample t-test was conducted to compare experimental and control group (F=43.573, Sig=0.000). These results were a significant difference in the scores for control and experimental groups. Maximum excursion distances improved for the exercise group, compared with the control group. This result justifies the hypothesis that core strengthening can improve dynamic postural control during landing of volleyball players significantly.Keywords: Core stabilization; volleyball player; dynamic balance; SEBT