Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimensionality Reduction using Clustering Technique

Clustering is a method of finding homogeneous classes of the known objects. Clustering plays a major role in various applications in data mining such as, computational biology, medical diagnosis, information recovery, CRM, scientific data investigation, selling, and web analysis. Most of the researchers have a major interest in designing clustering algorithms. &quot;Big data&quot; involves terabytes and petabytes of data. Big data is challenging because of its five important characteristics such as volume, velocity, variety, variability and complexity. Therefore big data is difficult to handle using conventional tools and techniques. There are so many issues in clustering techniques, so some of the issues is how to process the data and big data is clustered in more compact format, Clustering algorithm suffer from stability problem, ensemble of single and multi level clustering. An important issue in clustering is that we do not have earlier knowledge regarding data. Also selection of input parameters such as number of
NEAR INFRARED SPECTRA OF THE ORION BAR

We have used the LONGSP spectrometer on the 1.5- m TIRGO telescope to obtain long slit spectra in the J, H, and K wavelength bands towards two positions along the Orion bar. These data have been supplemented with images made using the ARNICA camera mounted on TIRGO as well as with an ESO NTT observation carried out by Dr A. Moorwood. We detect a variety of transitions of hydrogen, helium, OI, FeII, FeIII, and H2. From our molecular hydrogen data, we conclude that densities are moderate (3 6 10 4 cm 3 ) in the layer responsible for the molecular hydrogen emission and give no evidence for the presence of dense neutral clumps. We also nd that the molecular hydrogen bar is likely to be tilted by 10 degreesrelativetothelineofsight.Wediscusstherelativemerits of several models of the structure of the bar and conclude that it may be split into two structures separated by 0.2-0.3 parsec along the line of sight. It also seems likely to us that in both structures, density increases along a line perpendicular to the ionization front which penetrates into the neutral gas. We have used the 1.317m OI line to estimate the FUV radiation eld incident at the ionization front and nd values of 1 310 4 greaterthantheaverageinterstellareld.From(FeII) line measurements, we conclude that the electron density in the ionized layer associated with the ionization front is of order 10 4 cm 3 . Finally, our analysis of the helium and hydrogen recombination lines implies essential coincidence of the helium and hydrogen Strspheres.
THE EFFECTS OF MINDFULNESS BASED STRESS REDUCTION ON BREAST CANCER SURVIVORS by RUOHONG YAO

Breast cancer is the most common type of cancer among women in the United States. Cancer diagnosis and treatment usually induce significant amount of psychological stress on patients, and breast cancer patients are especially susceptible to cancer-related distress. Chronic stress activates the hypothalamicpituitary-adrenal (HPA) and the sympathetic-adrenomedullary (SAM) axis, whose prolonged activation initiates physiological events harmful to the immune system and negatively influence cancer progression and recurrence. Therefore, it is important to identify and introduce effective cancer-related stress management programs and incorporate them into the standard cancer care routine besides conventional therapy. Mindfulness-based stress reduction (MBSR) is an 8-week stress reduction program that has deep roots in ancient Buddhist practice and is used widely in clinics around the world nowadays. Is has been demonstrated to be effective in relieving stress and promoting well-being in a variety of populations, both clinical and nonclinical. And now it has started to be adapted into a complementary breast cancer therapy. However, much of MBSR’s mechanism is still unknown,
[Intradural anterior clinoidectomy. Anatmoclinical study and its usefulness in the treatment of trans-segmentary C5-C6 trans-segmentary paraclinoid aneurysms].

OBJECTIVE To present an anatomoclinical study of the intradural anterior clinoidectomy and to evaluate the usefulness of this procedure in the microsurgical management of paraclinoid aneurysms. To describe two cases of a subtype of paraclinoid aneurysms arising from and with their fundus growing both in the clinoidal and subarachnoidal segments of the internal carotid artery (paraclinoid trans-segmentary C5-C6 aneurysms). MATERIAL AND METHODS The microanatomy of the clinodal region has been studied in dried and fixed specimens. The steps of the intradural anterior clinoidectomy are showed. The imaging and microsurgical findings in two cases of trans-segmentary C5-C6 aneurysms are also described. RESULTS The C5 clinoid segment of the internal carotid artery is exposed intradurally after anterior intradural clinoidectomy. The transtion between the C5 clinoid and C6 ophthalmic is also exposed and it is movilized only after the section of the carotid distal ring. These manoeuvres allows the microsurgical management and dipping of the trans-segmentary C5-05 aneurysms. CONCLUSIONS The nomenclature of the internal carotid artery segments and paraclinoid aneurysms remains confuse. Therefore, each lesion should be idetified by the location of the neck (extradural: C4 and C5 segments; intradural: C6 segment), fundus projection and location (intradural / extradural). The microsurgical clipping of the paraclinoid aneurysms is made easier after intradural anterior clinoidectomy, but this manoeuvre is mandatory for trans-segmentary C5-C6 lesions.
Knowledge Engineering with Big Data

In the era of big data, knowledge engineering faces fundamental challenges induced by fragmented knowledge from heterogeneous, autonomous sources with complex and evolving relationships. The knowledge representation, acquisition, and inference techniques developed in the 1970s and 1980s, driven by research and development of expert systems, must be updated to cope with both fragmented knowledge from multiple sources in the big data revolution and in-depth knowledge from domain experts. This article presents BigKE, a knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation.
MOSAIC FLORAL ORGANS1, an AGL6-Like MADS Box Gene, Regulates Floral Organ Identity and Meristem Fate in Rice[W]

Floral organ identity and meristem determinacy in plants are controlled by combinations of activities mediated by MADS box genes. AGAMOUS-LIKE6 (AGL6)-like genes are MADS box genes expressed in floral tissues, but their biological functions are mostly unknown. Here, we describe an AGL6-like gene in rice (Oryza sativa), MOSAIC FLORAL ORGANS1 (MFO1/MADS6), that regulates floral organ identity and floral meristem determinacy. In the flower of mfo1 mutants, the identities of palea and lodicule are disturbed, and mosaic organs were observed. Furthermore, the determinacy of the floral meristem was lost, and extra carpels or spikelets developed in mfo1 florets. The expression patterns of floral MADS box genes were disturbed in the mutant florets. Suppression of another rice AGL6-like gene, MADS17, caused no morphological abnormalities in the wild-type background, but it enhanced the phenotype in the mfo1 background, indicating that MADS17 has a minor but redundant function with that of MFO1. Whereas single mutants in either MFO1 or the SEPALLATA-like gene LHS1 showed moderate phenotypes, the mfo1 lhs1 double mutant showed a severe phenotype, including the loss of spikelet meristem determinacy. We propose that rice AGL6-like genes help to control floral organ identity and the establishment and determinacy of the floral meristem redundantly with LHS1.
Ideal Kernel-Based Multiple Kernel Learning for Spectral-Spatial Classification of Hyperspectral Image

Using multiple types of features can effectively improve the classification accuracy of hyperspectral image (HSI). Multiple kernel learning (MKL) provides a flexible framework to fuse different features in a very natural way. In this letter, a novel MKL algorithm is proposed to integrate multiple types of features [i.e., principal components of original spectrum, multistructure morphological profiles (MPs), and multiattribute MPs] for HSI classification. The basic kernels are constructed with each feature subset separately, and the weights of basic kernels are determined by solving an optimization problem with the objective of the ideal kernel. Then, linear programming (LP) and signal sparse representation are adopted to solve the optimization problem, thus leading to two variants of the proposed algorithm, ideal kernel MKL (IKMKL)-LP and IKMKL-sparse, respectively. Experiments carried out on real hyperspectral data show that the proposed algorithms outperform several state-of-the-art MKL algorithms and reveal the capability of ranking the relevant features.
Data strip mining for the virtual design of pharmaceuticals with neural networks

A novel neural network based technique, called "data strip mining" extracts predictive models from data sets which have a large number of potential inputs and comparatively few data points. This methodology uses neural network sensitivity analysis to determine which predictors are most significant in the problem. Neural network sensitivity analysis holds all but one input to a trained neural network constant while varying each input over its entire range to determine its effect on the output. The least sensitive variables are iteratively removed from the input set. For each iteration, model cross-validation uses multiple splits of training and validation data to determine an estimate of the model's ability to predict the output for data points not used during training. Elimination of variables through neural network sensitivity analysis and predicting performance through model cross-validation allows the analyst to reduce the number of inputs and improve the model's predictive ability at the same time. This paper illustrates this technique using a cartoon problem from classical physics. It then demonstrates its effectiveness on a pair of challenging problems from combinatorial chemistry with over 400 potential inputs each. For these data sets, model selection by neural sensitivity analysis outperformed other variable selection methods including forward selection and a genetic algorithm.
A web-based IT Asset Management application using Fuzzy Logic in vendor selection process

Managing and tracking thousands of IT assets across a company manually is costly, time-consuming, and prone to errors. In order to reduce costs in budget planning, maintaining control of IT assets, increasing accountability to ensure compliance, and supporting strategic decision making, companies require a solution to manage hardware, software, and information throughout the IT asset lifecycle. The main objective of this study is to develop an IT Asset Management application that helps companies maintain information regarding hardware assets, locations, owners, and incurred costs via a web interface. A secondary objective is to introduce the application of Fuzzy Logic using Tsukamoto method to solve vendor selection problem in the procurement process. Fuzzy Logic can provide definitive solutions for vague, imprecise, and ambiguous issues by transforming linguistic-form information provided by experts in the procurement field into a mathematical decision making model. Vendor selection is a critical activity to increase competitive value of company in today's business environment. The two criteria used in this study to measure vendor performance are price and delivery delay. Result from this study is a web-based IT Asset Management application, using fuzzy logic to provide rank and score of recommended vendors in the asset procurement process.
Motivational factors , entrepreneurship and education : Study with reference to women in SMEs

For the past couple of years entrepreneurship development is considered as the priority area in the development policy in many countries, especially in India. The young entrepreneurs are engaged in varied form of small and medium scale enterprises ranging from paper to electronics, engineering to electrical, textile to metal and pipe industry, construction to food processing, education to handicrafts. The interesting fact is that the entrepreneurial ventures are making provision of more business options not only for men, but also for women, especially in rural and semi urban areas. Considering this trend, a study is conducted to analyze, what exactly motivate women entrepreneurs to get into small and medium scale entrepreneurial ventures. Relating entrepreneurship with educational institutions, it is hypothesized in this study that the identification of motivational factors among women may support educational institutions to tailor made their entrepreneurial program in tune with appropriate pedagogy and approach. In order to conduct the study SIDCO Industrial Estates in Madurai Region region is selected since it is populated with several small and medium scale enterprises. The respondents were the entrepreneurs who run small-scale industrial units of SIDCO Industrial Estate. Out of total population of 432, 144 small scale entrepreneurs have been taken as sample size. The data collected were analyzed on the basis of Descriptive Statistics, Correlation, Regression and Kruskal Wallis Test. The findings of this paper show the major factors which influence the motivation of women entrepreneurs in small and medium scale enterprises and its close relationship with the entrepreneurial factors. The study also suggests some measure for the educational institutions in order to make its pedagogue support their entrepreneurial development efforts of the country.
Structural and Functional Characterization of an Orphan ATP-Binding Cassette ATPase Involved in Manganese Utilization and Tolerance in Leptospira spp

ABSTRACT Pathogenic Leptospira species are the etiological agents of the widespread zoonotic disease leptospirosis. Most organisms, including Leptospira, require divalent cations for proper growth, but because of their high reactivity, these metals are toxic at high concentrations. Therefore, bacteria have acquired strategies to maintain metal homeostasis, such as metal import and efflux. By screening Leptospira biflexa transposon mutants for their ability to use Mn2+, we have identified a gene encoding a putative orphan ATP-binding cassette (ABC) ATPase of unknown function. Inactivation of this gene in both L. biflexa and L. interrogans strains led to mutants unable to grow in medium in which iron was replaced by Mn2+, suggesting an involvement of this ABC ATPase in divalent cation uptake. A mutation in this ATPase-coding gene increased susceptibility to Mn2+ toxicity. Recombinant ABC ATPase of the pathogen L. interrogans exhibited Mg2+-dependent ATPase activity involving a P-loop motif. The structure of this ATPase was solved from a crystal containing two monomers in the asymmetric unit. Each monomer adopted a canonical two-subdomain organization of the ABC ATPase fold with an α/β subdomain containing the Walker motifs and an α subdomain containing the ABC signature motif (LSSGE). The two monomers were arranged in a head-to-tail orientation, forming a V-shaped particle with all the conserved ABC motifs at the dimer interface, similar to functional ABC ATPases. These results provide the first structural and functional characterization of a leptospiral ABC ATPase.
Evolution of Specialized Department for Service Innovation: A Case Study of Ctrip

In recent years, some developed service enterprises in China has established specialized R&D or management departments for service innovation, effectively managed service innovation activities. This article summaries the evolution of Ctrip's specialized department of service innovation, by reviewing its evolution process, discussing its responsibilities in mode innovation, process innovation and service product innovation, finally exploring its promotion approach. The experience of Ctrip's specialized department of service innovation is of great value for other service enterprises. This article provides some theoretical and practical methods for enterprises about how to promote service innovation effectively.
Serological correlate of protection against norovirus-induced gastroenteritis.

BACKGROUND Norovirus infection is the leading cause of acute nonbacterial gastroenteritis. Histoblood group antigens (HBGAs) are host susceptibility determinants for Norwalk virus (NV) infection. We hypothesized that antibodies that block NV-HBGA binding are associated with protection from clinical illness following NV exposure. METHODS We developed an HBGA blocking assay to examine the ability of human serum to block the interaction of NV viruslike particles with H type 1 and H type 3 glycans. Serum samples from persons who were experimentally challenged with NV were evaluated. RESULTS There was a high correlation between the H type 1 and H type 3 synthetic glycan assays (r = 0.977; P < .001); the H type 1 assay had higher quantitative sensitivity (P < .001). Among 18 infected secretor-positive individuals, blocking titers peaked by day 28 after challenge and were higher for individuals who did not develop gastroenteritis than for those who developed gastroenteritis on days 0, 14, 28, and 180 (P < .05 for each). In addition, 6 of 6 subjects without gastroenteritis had measurable prechallenge blocking titers (>25), compared with 2 of 12 subjects with gastroenteritis (P = .002). CONCLUSIONS Blocking antibodies correlate with protection against clinical NV gastroenteritis. This knowledge will help guide the evaluation of new vaccine strategies and the elucidation of the nature of immunity to the virus. Trial registration. ClinicalTrials.gov identifier: NCT00138476.
[POSTER] The Augmented Library: An Approach for Improving Users Awareness in a Campus Library

Most existing libraries use floor plans and call numbers in order to locate books rather than providing truly user's awareness of the extensive collections and services for students in the library context. With a collection of more than 48,568 volumes at the Engineering and Exact Sciences library of the Universidad Autónoma de Yucatán (UADY), the task of looking for a book can be really a time-consuming and frustrating task, specially for newcomers. This paper proposes an Augmented Reality (AR) based application which aims to solve users spatial unawareness at library by providing an AR shelf searching system, and to assist students and newcomers by providing a mobile guide with library information services into library. In this work, the results of a pilot study are presented demonstrating that user's experiences and performance at library were enhanced through the use of augmented reality technology.
ACTA UNIVERSITATIS APULENSIS Special Issue LINEAR BOUNDARY ELEMENTS FOR SOLVING THE NONSINGULAR BOUNDARY INTEGRAL EQUATION OF THE FLUID FLOW AROUND OBSTACLES

The aim of the paper is to present a numerical solution for the problem of the 2D fluid flow around an obstacle, a solution obtained by applying the boundary element method. It is focused on the second step in applying the mentioned method. In order to satisfy the conditions required by the unknown of the problem, the solution is obtained by using linear boundary elements for solving the boundary integral equation of the problem. The boundary integral equation considered is a nonsingular one, and so the numerical solution is expected to be better than the numerical solution of the same problem solved when a singular boundary integral equation is considered. A computer code in MathCAD, based on the method described, is also made in order to get the numerical solution. This solution is compared with the exact one for some particular cases, and with the one obtained in case when a singular integral equation, equivalent with the same problem, is considered. The graphics show a high agreement between the numerical solution and the exact one. It is also pointed out the biggest advantage of the present solution: it is obtained without considering singular integrals, and special methods to treat them, and so all coefficients that appear are easier to evaluate with a computer code.
Numerical Modeling of Nonlinear SurfaceWaves Caused By Surface Effect Ships Dynamics And Kinematics

We model fully nonlinear free surface waves caused by a translating disturbance made of a pressure patch and/or a surface-piercing body (ship), within the framework of potential flow theory. The three-dimensional higher-order Boundary Element Model by Grilli et al. (2001) and Fochesato et al. (2004) is utilized with some recent extensions. In addition to the regular Eulerian-Lagrangian updating of the free surface geometry and potential, based on higher-order explicit Taylor series expansions, a pseudo-Lagrangian updating algorithm is developed to express and solve the problem in a coordinate system traveling at the instantaneous speed of the moving disturbance. This paper presents theoretical developments and applications illustrating both the accuracy and efficiency of the present method for a traveling pressure patch and an advancing Wigley hull. Based on numerical results, it is concluded that the present numerical approach, with a pseudo-Lagrangian updating and a higher-order BEM provides accurate and efficient results.
Cord blood lipoprotein profile in term, preterm, and late preterm newborns

Background: High concentrations of triglyceride-rich lipoproteins, and apolipoprotein B in newborns with low gestational age may increase the risk of cardiovascular diseases in the future. We investigated the lipid profile in term, late preterm and preterm Iranian infants. Materials and Methods: A total number of 99 term (gestational age ≥37 weeks), preterm (gestational age <34 weeks), and late preterm (34≤ gestational age <37 weeks) newborns were studied. Total cholesterol, low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), and triglycerides, as well as apolipoproteins A and B were analyzed using auto analyzer. Results: Significant differences existed between cord blood concentrations of triglycerides, total cholesterol, and LDL-C in the term, late preterm and preterm infants (P < 0.05). The highest (61.69 mg/dl) and lowest (47.03 mg/dl) concentrations of triglycerides were documented in term and preterm newborns, respectively. Late preterm infants had the highest concentration of cord blood cholesterol. The lowest amount of cholesterol was found in term newborns (72.51 mg/dl). No significant difference existed in the mean of HDL-C and apolipoproteins in the studied groups (P > 0.05). Conclusion: In this study, the cord blood concentrations of cholesterol, triglycerides, and LDL-C were lower in term than in preterm and late preterm infants. This finding should be considered in infant nutrition and preventive measures.