Miracle-dz/UniFAR-FTUs huggingface dataset:
COMMENTS ON HAMILTONIAN FORMALISM OF AdS/CFT CORRESPONDENCE

As a toy model to search for Hamiltonian formalism of the AdS/CFT correspondence, we examine a Hamiltonian formulation of the AdS2/CFT1 correspondence emphasizing unitary representation theory of the symmetry. In the course of a canonical quantization of the bulk scalars, a particular isomorphism between the unitary irreducible representations in the bulk and boundary theories is found. This isomorphism defines the correspondence of field operators. It states that field operators of the bulk theory are field operators of the boundary theory by taking their boundary values in a specific way. The Euclidean continuation provides an operator formulation on the hyperbolic coordinates system. The associated Fock vacuum of the bulk theory is located at the boundary, thereby identified with the boundary CFT vacuum. The correspondence is interpreted as a simple mapping of the field operators acting on this unique vacuum. Generalization to higher dimensions is speculated.
TVG-OSN: A Time Varying Graph Model for Online Social Network Dynamics Analysis

Online social networks like Facebook, Twitter, Linked In and YouTube have become major platforms for sharing content, socialization, e-commerce, security monitoring, etc. Numerous researchers are devoted to studying these platforms that are modeled from a variety of perspectives. Hence, depending on the research, online social networks are modeled using different annotations that often refer to the same concepts. Many of these models ignore or discretize the temporal dimension of social networks leading to a loss of temporal information. Other models consider communications on these platforms to be instantaneous overlooking the delay between its initiation and processing, or omit the representation of identity maps between nodes at different times. Also, most models do not allow for the representation of the states of social network actors at different times. We provide in this paper a simple temporal graph model for online social networks (TVG-OSN) that fully accounts for their dynamics in addition to a new definition of the latency function between users.
Probabilistic Decoding of Low-Density Cayley

Adam L. Berger John D. La erty Computer Science Department Carnegie Mellon University Abstract | We report on some investigations into the behavior of a class of low-density codes constructed using algebraic techniques. Recent work shows expansion to be an essential property of the graphs underlying the low-density parity-check codes rst introduced by Gallager. In addition, it has recently been shown that certain spectral techniques similar to those based on Fourier analysis for classical cyclic codes can be applied to codes constructed from Cayley graphs. This motivates us to compare the behavior of algebraically constructed expanders and randomly generated bipartite graphs using a probabilistic decoding algorithm. Preliminary results indicate that the performance of the explicit, algebraic expanders is comparable to that of random graphs in the case where each variable is associated with only two parity checks, while such codes are inferior to randomly generated codes with three or more constraints for each variable.
On the Optimal Topology of Bluetooth Piconets : Roles Swapping Algorithms

In this paper we investigate the impact of the master choice on the performance of a Bluetooth piconet. Starting from the knowledge of the end–to–end traffic matrix, we address stability issues and, then, propose an optimal and a suboptimal criterion for the choice of the master unit. The performance improvement achievable with respect to a random choice is evaluated via numerical simulations. Finally, we describe some possible scenarios where the analysis provided in this paper may be applied.
Do inhaled corticosteroids affect perception of dyspnea during bronchoconstriction in asthma?

BACKGROUND Some of the disagreements on the perception of dyspnea (PD) during bronchoconstriction in asthma patients could depend on the interrelationships among the following: (1) the influence of baseline airflow obstruction on the patient's ability to detect any further increase in airway resistance; (2) the effect of eosinophilic inflammation on the airway; (3) bronchial hyperresponsiveness (BHR); and (4) the effect of inhaled corticosteroids (ICSs). OBJECTIVE We hypothesized that if the inflammation of the airway wall influences to some extent and in some way the PD in asthma patients, ICSs reverse the effect of airway inflammation on the PD. METHODS We studied 100 asthma patients who were divided into the following four groups: patients with obstruction who were either ICS-naive (group I) or were treated with ICSs (group II); and nonobstructed patients who were either ICS-naive (group III) or were treated with ICSs (group IV). PD on the visual analog scale (VAS) was assessed during a methacholine-induced FEV(1) decrease and specifically was quantified as the VAS slope and score at an FEV(1) decrease of 5 to 20%. BHR was assessed in terms of the provocative concentration of methacholine causing a 20% fall in FEV(1) (PC(20)). Eosinophil counts in induced sputum samples also were performed. Regression analysis, univariate analysis of variance, and factor analysis were applied for statistical evaluation. RESULTS For a 5 to 20% fall in FEV(1) from the lowest point after saline solution induction, VAS score was lowest in group II, slightly higher in group I, slightly higher still in group IV, and the highest in group III. In the patients as a whole, BHR related to PD, but age, clinical score, duration of the disease, and presence of baseline airway obstruction did not. In patients with obstruction who were treated with ICSs, eosinophil counts related to PD negatively. Factor analysis yielded the following four factors that accounted for 70% of the variance in the data: ICS; eosinophil counts; FEV(1); and PC(20) loaded on separated factors with PD loading on the same factors as PC(20). The post hoc analysis carried out dividing the patients into ICS-treated and ICS-naive, showed that in the former group eosinophil counts and BHR proved to be factors negatively associated with PD, while in the latter group eosinophil counts were positively associated with PD. CONCLUSIONS We have shown that eosinophilic inflammation of the airway wall may increase PD and that the association of eosinophil counts with ICSs may result in lessening the PD.
A pilot study on biological nitrogen removal in a frequent anoxic-aerobic alternation sequencing batch reactor

The present study focused on investigation of biological nitrogen removal efficiency and the superiority of continuous feeding sequencing batch reactor system with a frequent anoxic-aerobic alternation strategy. The result indicated that continuous feeding SBR achieved an excellent efficiency for pollutants removal. The removal efficiency of COD and NH4+-N reached above 90% and 91.4% respectively which was not significantly affected by A/O alternating frequency. Removal efficiency of TN was positively related to A/O alternating frequency, the average TN removal efficiencies reached 71.5%, 82.4% and 87.2% respectively with the alternating frequency changed from 5 to 15 and 30, the 5–5min agitation — aeration mode was the best one for nitrogen removal. Moreover, continuous feeding SBR was proved to be better in domestic wastewater treatment compared with instantaneous feeding SBR, and this superiority was more significant with a 5–5min agitation/ aeration operation strategy.
Altered profile of seminal plasma microRNAs in the molecular diagnosis of male infertility.

BACKGROUND Although microRNAs (miRNAs) play essential roles in spermatogenesis, little is known about seminal plasma miRNAs in infertile men. We investigated the profile of seminal plasma miRNAs in infertile men to identify miRNAs that are altered in infertility; we then evaluated their diagnostic value. METHODS Seminal plasma samples were obtained from 289 infertile men and 168 age-matched fertile control individuals. The stability of the miRNAs was first assessed by time-course and freeze-thaw cycle analyses. The Solexa sequencing technology was used for an initial screen of the miRNAs in samples pooled from 45 patients with nonobstructive azoospermia, 58 patients with asthenozoospermia, and 100 fertile controls. A stem-loop quantitative reverse-transcription PCR (RT-qPCR) assay was conducted in the training and verification sets to confirm the concentrations of the altered miRNAs in 73 patients with nonobstructive azoospermia, 79 patients with asthenozoospermia, 34 patients with oligospermia, and 68 fertile controls. RESULTS The miRNAs in seminal plasma were stable. The Solexa sequencing analysis demonstrated 19 markedly altered miRNAs in the patient groups, compared with the control group. RT-qPCR analysis identified 7 miRNAs (miR-34c-5p, miR-122, miR-146b-5p, miR-181a, miR-374b, miR-509-5p, and miR-513a-5p) as markedly decreased in azoospermia but increased in asthenozoospermia. The area under the ROC curve for these miRNAs ranged from 0.733 to 0.921, markedly higher than for routine biochemical parameters (0.510-0.622). Moreover, the concentrations of some selected miRNAs were also increased in the semen sperm of the asthenozoospermia patients. CONCLUSIONS The measurement of miRNAs in seminal plasma provides a novel, noninvasive approach for diagnosing male infertility.
A Low Power V-Band CMOS Frequency Divider With Wide Locking Range and Accurate Quadrature Output Phases

A new injection-locked frequency divider (ILFD) circuit topology, by combining the strengths of LC type ILFD (LC_ILFD) and ring oscillator type ILFD (RO_ILFD), is proposed to achieve high speed, low power, wide locking range and accurate quadrature output phases. The frequency-division criterion is analyzed and agrees well with simulation results. The phase-locking mechanism is also investigated with emphasis on its resilience to device and circuit mismatches. A prototype is implemented in TSMC 90 nm CMOS to validate the effective locking range of 7.4 GHz (53.4 to 60.8 GHz) with 0 dBm input signal and 5 mW DC power dissipation. The circuit attains the highest figure-of-merit (dividing frequency/power) to date for V-band frequency dividers implemented in deep-scaled CMOS technologies.
A-Brain: the multiple problems solver

Intelligence is strongly related to the ability of solving different problems by a single system. General problems solvers such as Artificial Neural Networks, Evolutionary Algorithms, Particle Swarm etc, have traditionally been tested against one problem at one time. The purpose of this research is to build a complex and adaptive system able to solve multiple (and different) problems. The proposed system, called A-Brain, consists of several connected components (a Decision Maker, a Trainer and several Problem Solvers) which provide a base for building complex problem solvers. The A-Brain system is applied for solving some well-known problems in the field of symbolic regression. Numerical experiments show that A-Brain system is able to perform very well on the considered test problems.
Medical text categorization using SEBLA and Kernel Discriminant Analysis

Education data mining (EDM) is an emerging field which take advantage of natural language processing, data mining, statistics and machine learning algorithms for different types of educational data especially related to medical e-learning. Medical text categorization is the one of the major component to help students more easily and effectively search medical text for e-Learning. In this paper, spectral based Kernel Discriminant Analysis has been introduced for medical text categorization. We evaluated the proposed approach on 10 most frequent categories of cardiovascular diseases group from Ohsumed data sets. When compared with existing approaches, the results have indicated significant increase in performance. In order to further refine the search, Semantic Engine that uses Brain-Like approach (SEBLA) is also introduced in this paper.
Noncanonical Wnt signaling promotes apoptosis in thymocyte development

The Wnt–β-catenin signaling pathway has been shown to govern T cell development by regulating the growth and survival of progenitor T cells and immature thymocytes. We explore the role of noncanonical, Wnt–Ca2+ signaling in fetal T cell development by analyzing mice deficient for Wnt5a. Our findings reveal that Wnt5a produced in the thymic stromal epithelium does not alter the development of progenitor thymocytes, but regulates the survival of αβ lineage thymocytes. Loss of Wnt5a down-regulates Bax expression, promotes Bcl-2 expression, and inhibits apoptosis of CD4+CD8+ thymocytes, whereas exogenous Wnt5a increases apoptosis of fetal thymocytes in culture. Furthermore, Wnt5a overexpression increases apoptosis in T cells in vitro and increases protein kinase C (PKC) and calmodulin-dependent kinase II (CamKII) activity while inhibiting β-catenin expression and activity. Conversely, Wnt5a deficiency results in the inhibition of PKC activation, decreased CamKII activity, and elevation of β-catenin amounts in thymocytes. These results indicate that Wnt5a induction of the noncanonical Wnt–Ca2+ pathway alters canonical Wnt signaling and is critical for normal T cell development.
Mathematica implementation of chasing method for linear boundary value problems

The chasing method proposed by Gelfand and Lokutzievskii and implemented in Mathematica package ”Numerical Solution of Linear Boundary Value Problems” is described. This package served as a base for a linear boundary value problem solver built in Mathematica 5.0 function NDSolve. Examples of the package usage are presented.
Efficient zerotree-based image compression with directionlets

Directionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments (DVMs) imposed along different directions. Here, we combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.
Randomized sibling-oocyte study using recombinant human hyaluronidase versus bovine-derived Sigma hyaluronidase in ICSI patients.

BACKGROUND The enzyme hyaluronidase from bovine origin is commonly used for oocyte-cumulus cell removal in ICSI. A recombinant human hyaluronidase (rHuPH20) has been introduced as a quality-controlled and safe alternative. METHODS In order to validate its effectiveness, a non-inferiority trial was started on sibling cumulus-oocyte complexes (135 ICSI patients). Oocyte denudation involved enzyme incubation under Pasteur pipetting, followed by further mechanical stripping. Primary end-points were oocyte intactness after ICSI and fertilization rate. Secondary end-points were embryo development and positive hCG. RESULTS Oocyte intactness after ICSI was 89.6% and 92.9% with rHuPH20 and bovine hyaluronidase, respectively [absolute difference -3.3% (-7.4 to 10.7)]. The fertilization rate was 73.9% after rHuPH20 and 77.1% after bovine hyaluronidase treatment [absolute difference -3.2% (-8.3 to 1.8)]. Embryo development was similar in both treatment groups up till Day 5. Positive hCGs were equally distributed over mixed transfers 21/45 (46.7%) and transfers of only embryos from rHuPH20 treatment 17/35 (48.6%) or transfers of only embryos from bovine hyaluronidase treatment 22/48 (45.8%). CONCLUSIONS Our results indicate that rHuPH20 is not inferior to bovine hyaluronidase for oocyte denudation, with regard to oocyte survival and fertilization. rHuPH20 treatment of human oocytes is compatible with good embryo development, with positive hCG results and with live birth.
Effects of Basketball Activity on Self-Esteem and Mental Health Among Male College Students

Objective To probe the effects of basketball sport of low and moderate intensity on self-esteem and mental health and to provide evidence for their physical education and mental health education.Methods Intervention was conducted in experimental subjects for 10 weeks by basketball exercise of low and moderate intensity.Both PSPP and SCL-90 were used to investigate the students' self-esteem and mental health before and after the interventions.Results As to PSPP,there was an improving trend to the level among the students in experimental group after the intervention,of which,there was obvious variation to the total score of PSPP of moderate intensity group(P=0.052). No difference of self-esteem was found in the control group before and after the intervention.Basketball activity of low intensity had effects on mental health among the students in experimental group.After the intervention,students in moderate intensity group had lower scores in obsessive-compulsive,interpersonal sensitivity,depression,phobic-anxiety,psychoticism and general score.Conclusion Basketball activity of moderate or low intensity is benefit to male students' self-esteem and mental health,and moderate intensity group is better than low intensity group.
Effect of hough forests parameters on face detection performance: An empirical analysis

Face detection as one of the most challenging tasks in computer vision has received a lot of attention in recent decades due to its wide range of use in face based image analysis. In this paper, we propose an efficient approach for face detection that efficiently combines generalized Hough transform within random decision forests framework. In this approach, we train random decision forests that directly maps the image patch appearance to the probabilistic vote about the possible location of the face centroid; the detection hypotheses then correspond to the maxima of the Hough image. The random decision forests construction and prediction abilities depend on setting some parameters, which in turns affects the performance of the method. Therefore, the impact of these parameters that most influence the behavior of the forest for detecting faces is studied through experiments on the widely used CMU+MIT database. Moreover, a comparison with some published methods is presented.
The Anatomy of Public Prcblems, Building a Methodology of Policy Analysis

Public policy analysis is rich in methods and poor in methodology. As the number and sophistication of methods continue to increase, the failure to build an integral mode of analysis becomes the more apparent. A wealth of technique does not yield a systematic way of proceeding with the analysis of a problem-a theory of how to proceed and why. The missing ingredient is methodological: a logic-of-doing policy analysis. Wildavsky (1979: 2, 15), certainly a leading practitioner and teacher in the field, concludes that he can neither say what policy analysis is nor how it is possible to do it. While embracing a variety of methods as useful , he seems to reject the possibility of methodological development (1979: 3): What tools does the policy analyst use? Qualitative political theory, for refining our picture of where we want to go; quantitative modeling, for systematizing guesswork on how to get there; microeconomics, for disciplining desire with limited resources, and macro-organization theory, for instilling the will to correct errors: each has its place. Policy analysis, however, is one activity for which there can be no fixed program, for policy analysis is synonymous with creativity, which may be stimulated by theory and sharpened by practice, which can be learned but not taught. [Emphasis supplied] Doing policy analysis, he argues, is akin to "discovery" and exhibits little structure or pattern. Rather than a logic of inquiry, Wildavsky proposes a logic of appraisal or "justification" (1979: 387-88). He recommends giving attention to the development of systematic criteria for evaluating the work of policy analysts (1979: 397-98), but not an attempt to give more 1 2 structure to the process of doing policy analysis, which must remain a "private affair" (1979: 15). If, as Wildavsky says, policy analysis can be viewed as both art and craft, the "material" of policy analysis consists of public problems. The relevance of methodology depends upon the nature of the material. If the salient features of public problems are characterized more by uniqueness than by similarity or congruency, then an integral mode of analysis cannot be developed. When one focuses on "solutions," or at least "recommended courses of action," as the product of policy analysis, this view of public problems as basically idiosyncratic may appear to be valid. A successful course of action may often depend on details that are unique to a situation. Policy prescriptions, however, also depend upon an understanding …
' s personal copy Automated text classification using a dynamic artificial neural network model

Widespread digitization of information in today’s internet age has intensified the need for effective textual document classification algorithms. Most real life classification problems, including text classification, genetic classification, medical classification, and others, are complex in nature and are characterized by high dimensionality. Current solution strategies include Naïve Bayes (NB), Neural Network (NN), Linear Least Squares Fit (LLSF), k-Nearest-Neighbor (kNN), and Support Vector Machines (SVM); with SVMs showing better results in most cases. In this paper we introduce a new approach called dynamic architecture for artificial neural networks (DAN2) as an alternative for solving textual document classification problems. DAN2 is a scalable algorithm that does not require parameter settings or network architecture configuration. To show DAN2 as an effective and scalable alternative for text classification, we present comparative results for the Reuters-21578 benchmark dataset. Our results show DAN2 to perform very well against the current leading solutions (kNN and SVM) using established classification
Classification of Clinical Conditions: A Case Study on Prediction of Obesity and Its Co-morbidities

We investigate a multiclass, multilabel classification problem in medical domain in the context of prediction of obesity and its co-morbidities. Challenges of the problem not only lie in the issues of statistical learning such as high dimensionality, interdependence between multiple classes but also in the characteristics of the data itself. In particular, narrative medical reports are predominantly written in free text natural language which confronts the problem of predominant synonymy, hyponymy, negation and temporality. Our work explores the comparative evaluation of both traditional statistical learning based approach and information extraction based approach for the development of predictive computational models. In addition, we propose a scalable framework which combines both the statistical and extraction based methods with appropriate feature representation/selection strategy. The framework leads to reliable results in making correct classification. The framework was designed to participate in the second i2b2 Obesity Challenge.