Miracle-dz/UniFAR-FTUs huggingface dataset:
Active Network Management and Kolmogorov Complexity

This paper seeks to describe new and better ways to represent network health and thus attempts to explore concepts other than those based on network topology-based representations of network management. It examines the manner in which active network management can benefit from Algorithmic Information Theory. Due to the new paradigm and enhanced capabilities of active networks, this work proceeds along the lines that a new perspective that incorporates Algorithmic Information Theory can provide superior, innovative solutions for network management.
Complex Plane Transformations for Manipulation and Visualization of Panoramas

We present a method for manipulation and visualization of wide-angle images using transformations defined on the complex plane C. We map the unit sphere S2 to C using the stereographic projection, multiply the complex plane by a given complex number, and map the result back to the sphere using the inverse of the stereographic projection. Since all these transformations preserve angle, we obtain a result containing only distortions due to the latitude/longitude representation of the sphere, which were already present in the input image. We then explore the possibility given by our technique of mapping wide fields of view to narrower ones. This makes possible to apply perspective projection to wider fields of view, leading to a natural generalization of the perspective projection in the context of panoramic images. Our results are generated in real-time and compare competitively with state-of-the-art methods used to project the viewing sphere to the image plane.
Inside the Syntactic Box: The Neural Correlates of the Functional and Positional Level in Covert Sentence Production

The aim of the present fMRI study was to investigate the neural circuits of two stages of grammatical encoding in sentence production. Participants covertly produced sentences on the basis of three words (one verb and two nouns). In the functional level condition both nouns were animate and so were potential competitors for the grammatical function of subject. In the positional level condition the first noun was animate whereas the second was inanimate. We found activation of Broca's and adjacent areas, previously indicated as responsible for syntactic processing. Additionally, a later onset of the activation in three brain areas in the functional level condition suggests that there is indeed a competition for assignment of subjecthood. The results constrain theories of grammatical encoding, which differ in whether they assume two separate processing levels or only one.
A Study on Analysis of Various Datamining Classification Techniques on Healthcare Data

The health care industry is one of the world's largest and fastest growing industries having huge amount of healthcare data. This health care data includes relevant information about patient data, their treatment data and resource management data. The information is rich and massive. Hidden relationships and trends in healthcare data can be discovered from the application of data mining techniques. Data mining techniques are more effective that has used in healthcare research. In this paper we aimed to do the analysis of several data mining classification techniques using WEKA machine learning tools over the healthcare datasets. In this study, we use different data mining classification techniques that have been tested on two heart disease datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The technique which is suitable for a particular dataset is chosen based on highest classification accuracy rate and least error rate.
phloat : Integrated Writing Environment for ESL learners

present (贈る;okuru) send (送る;okuru) live (送る;okuru) After the user chooses one of the candidate phrases, the system subsequently suggests candidates to fill in the slots of the phrase. These slot candidates are generated from the context of the suggested English phrase and its Japanese translation. This enables users to complete a long expression just by choosing a phrase and filling out the blanks in it. Phrase Suggestion
Summarizing Evolving Data Streams using Dynamic Prefix Trees

In stream data mining it is important to use the most recent data to cope with the evolving nature of the underlying patterns. Simply keeping the most recent records offers no flexibility about which data is kept, and does not exploit even minimal redundancies in the data (a first step towards pattern discovery). This paper focuses in how to construct and maintain efficiently (in one pass) a compact summary for data such as web logs and text streams. The resulting structure is a prefix tree, with ordering criterion that changes with time, such as an activity time stamp or attribute frequency. A detailed analysis of the factors that affect its performance is carried out, including empirical evaluations using the well known 20 Newsgroups data set. Guidelines for forgetting and tree pruning are also provided. Finally, we use this data structure to discover evolving topics from the 20 Newsgroups.
Automatically Suggesting Example Sentences of Near-Synonyms for Language Learners

In this paper, we propose GiveMeExample that ranks example sentences according to their capacity of demonstrating the differences among English and Chinese near-synonyms for language learners. The difficulty of the example sentences is automatically detected. Furthermore, the usage models of the near-synonyms are built by the GMM and Bi-LSTM models to suggest the best elaborative sentences. Experiments show the good performance both in the fill-in-the-blank test and on the manually labeled gold data, that is, the built models can select the appropriate words for the given context and vice versa.
Preliminary studies of 12S-8P and 12S-14P Hybrid-Excited Flux Switching Machine with FEC in radial direction by using JMAG-designer software

In this paper, design analysis of Hybrid- Excited Flux Switching Machine (H-EFSM) with 12Slot-8Pole (12S-8P) and 12Slot-14Pole (12S-14P) topologies are presented. H-EFSM has been introduced in which the advantage of Permanent Magnet (PM) machines and DC Field Excitation Coil (FEC) synchronous machines is combined. H-EFSM design proposed less permanent magnet consumption, high to torque/power density and high efficiency. In recent, most of H-EFSM having FEC arranged in theta direction that affect in flux production which cause less flux generation and machines performances. Therefore, a design of 12S-8P and 12S-14P H-EFSM with FEC arranged in radial direction is proposed to prevent flux cancellation and produce high flux linkage. Performance analysis of 12S-8P and 12S-14 H-EFSM such as PM flux, induced voltage, cogging torque and flux distribution are investigated by 2-D Finite Element Analysis (2D-FEA). A design with 12S-14P configuration has achieved the higher torque and power with 220.15Nm and 92.45kW, respectively at maximum field and armature current density
The Telephone Interviewer's Handbook: How to Conduct Standardized Conversations

DESCRIPTION "Survey organizations should make this handbook an integral part of their training of telephone interviewers. It covers in a clear and direct manner all aspects of the interviewing process and incorporates the latest knowledge about what makes effective interviewers in today’s challenging survey environment. " — David R. Johnson, professor of sociology, human development and family studies, and demography and former director of the Survey Research Center, Penn State University and the Bureau of Sociological Research, University of Nebraska-Lincoln
Accelerated DNA methylation age and the use of antihypertensive medication among older adults

The discrepancy of DNA methylation age (DNAmAge) with chronological age (termed as age acceleration, AA) has been identified to be associated with many aging-related health outcomes including hypertension. Since taking antihypertensive medication (AHM) could prevent aging-related diseases caused by hypertension, we hypothesized that using AHM could also reduce the AA. We examined this hypothesis among 546 males aged 55–85 years by exploring the associations of AHM use with AA and its change rate (ΔAA) in two visits with a median follow-up of 3.86 years. Horvath DNAmAge was derived from DNA methylation profiles measured by Illumina HumanMethylation450 BeadChip and information on AHM use was collected by physician interview. A general decreasing pattern of AA was observed between the two visits. After the fully adjusting for potential covariates including hypertension, any AHM use showed a cross-sectional significant association with higher AA at each visit, as well as a longitudinal association with increased ΔAA between visits. Particularly, relative to participants who never took any AHM, individuals with continuous AHM use had a higher ΔAA of 0.6 year/chronological year. This finding underlines that DNAmAge and AA may not be able to capture the preventive effects of AHMs that reduce cardiovascular risks and mortality.
The Joint Determination of Union Status and Union Wage Effects: Some Tests of Alternative Models

The problems of estimation and interpretation of union wage differentials are examined. The properties of cross-section and longitudinal estimators are compared. Estimates are presented and those in the literature summarized. Conflicting results are obtained. Longitudinal estimators typically produce results smaller than those of OLS, while cross-section methods (instrumental variables or inverse Mills ratio) raise the estimate. The paper offers a reconciliation of these results. It supports a more optimistic conclusion than that reached in reviews by Freeman and Lewis, who argued that little has been learned from attempts to deal with the endogeneity issue. Comparisons between estimators are used to throw light on the process governing union status and to suggest interpretations of "union differentials" consistent with the current evidence.
Solving Strategic Control Problems using Temporal Difference Methods with Artificial Neural Networks

The possibilities of using temporal difference learning techniques in combination with artificial neural networks to solve strategic control problems, as seen in arcade-like games, are in this thesis investigated. Earlier studies have often concentrated on simple control problems and board games. The main application used was the classic arcade game Pong, a simple 2D-tennis played by two players. Two versions of the game were implemented and studied: one discrete and one with continuous state variables but discrete actions. Firstly the discrete version was studied using the SARSA(λ)-algorithm together with Artificial Neural Networks approximating the value function and a tabular version using a matrix for storing the value function. The tabular version performed very well and converged to a near-perfect solution with λ set to 0. Another implementation of the discrete version had λ set to 0.95 using a sigmoidal artificial neural network to approximate the value function, and this converged to a perfect solution. These two versions were then compared and studied in detail. Secondly the continuous version was briefly examined, using the SARSA(λ)-algorithm together with a sigmoidal artificial neural network. The results of this were promising but not satisfactory. No stable conversion to an acceptable solution was ever observed. However, altogether the results clearly show the potential of temporal difference learning methods together with function approximation in this domain. The influence that the design of the Artificial Neural Networks had on the convergence of the value function was also investigated using a simple 2-dimensional maze. It was found that the output neuron used had to be linear in a 2-weight layered sigmoidal network in order to achieve a stable convergence. The parameter’s influence on the appearance of the value function was also found to be of a significant importance.
Reionization Revisited: Secondary Cosmic Microwave Background Anisotropies and Polarization

Secondary cosmic microwave background (CMB) anisotropies and polarization provide a laboratory for studying structure formation in the reionized epoch. We consider the kinetic Sunyaev-Zeldovich effect from mildly nonlinear large-scale structure and show that it is a natural extension of the perturbative Vishniac effect. If the gas traces the dark matter to overdensities of order 10, as expected from simulations, this effect is at least comparable to the Vishniac effect at arcminute scales. On smaller scales, it can be used to study the thermal history-dependent clustering of the gas. Polarization is generated through Thomson scattering of primordial quadrupole anisotropies, kinetic (second-order Doppler) quadrupole anisotropies, and intrinsic-scattering quadrupole anisotropies. Small-scale polarization results from the density and ionization modulation of these sources. These effects generically produce comparable E- and B-parity polarization, but of negligible amplitude (10-3-10-2 μK) in adiabatic cold dark matter (CDM) models. However, the primordial and kinetic quadrupoles are observationally comparable at present, so that a null detection of B-polarization would set constraints on the evolution and coherence of the velocity field. Conversely, the detection of a cosmological B-polarization even at large angles does not necessarily imply the presence of gravity waves or vorticity. For these calculations, we develop an all-sky generalization of the Limber equation that allows for an arbitrary local angular dependence of the source for both scalar and symmetric trace-free tensor fields on the sky.
Molecular Cloning and Characterization of a Novel ATP P2X Receptor Subtype from Embryonic Chick Skeletal Muscle*

We have cloned a new P2X ligand-gated ion channel receptor from embryonic chick skeletal muscle, which is tentatively named as chick P2X8 (cP2X8) receptor. The cloned cDNA encodes a protein with 402 amino acids. Electrophysiological study of the recombinant cP2X8receptor expressed in Xenopus oocytes showed that 10 μm ATP induced a fast inward current followed by rapid and long lasting desensitization in medium containing 1.8 mm Ca2+. In medium with 0.3 mmCa2+ ATP induced a bi-phasic response as follows: a slower inward current succeeded the initial fast one. 2-Methylthio-ATP, α,β-methylene-ATP, and adenosine 5′-O-(thio)triphosphate were potent agonists, whereas ADP was a very weak agonist. ATP-induced currents were blocked by 100 μm suramin and pyridoxal phosphate 6-azophenyl-2′,4′-disulfonic acid. Northern blot analysis and reverse transcription-polymerase chain reaction showed that cP2X8RNA transcripts were mainly expressed in skeletal muscle, brain, and heart of Day 10 chick embryos. A moderate level of expression was also detected in gizzard and retina. Whole mount in situhybridization showed that cP2X8 RNA transcripts were expressed mainly in neurotube, notochord, and stomach in Day 3 embryos. In Day 4 and Day 6 embryos, the cP2X8 RNA transcripts were highly expressed in the myotome and premuscle mass. The physiological role of this receptor in the establishment of the skeletal muscle innervation will be studied.
WSD Team's Approaches for Textual Entailment Recognition at the NTCIR10 (RITE2)

In this paper, we describe the WSD team’s approaches to textual entailment recognition task (RITE) at NTCIR-10[1], a conference held in June 18-21, 2013, at NII in Tokyo, Japan, and present experimental results for three Japanese subtasks, called “Binary Class” (BC), “Multi Class” (MC) and “Entrance Exam BC” (ExamBC). Our approach employs two supervised learning techniques: support vector machine (SVM) and logistic regression (LR). For the binary classification subtasks (BC and ExamBC), we propose hand-coded rules to classify text into entailment or non-entailment categories, while for the multi-classification subtask (MC), we used the bidirectional features for the texts. The best performance in three runs achieved precision of 80.66% in BC subtask, 69.53% in MC subtask and 67.86% in ExamBC subtask. We won second place for BC and MC, and third place for ExamBC.
Learning Not to Diversify: The Transformation of Graduate Business Education and the Decline of Diversifying Acquisitions

Once a preferred strategy, corporate diversification into disparate lines of business has gradually declined in the U.S. over the past several decades. We argue that changes that occurred in a closely related domain—graduate business education—are important in understanding variation in de-diversification across firms. Building on a historical account of the transformation of business education, we explain how the rise of financial economics and agency-theoretic logic in business education changed students’ views about diversification. Nearly 20 years later, these MBA graduates rose to top decision-making positions and put the brakes on diversification. Using data on CEOs who ran 640 large U.S. corporations from 1985 to 2015, we show that CEOs who earned an MBA before the 1970s actively pursued diversification, whereas the next cohort of CEOs, who had been exposed to agency-theoretic logic in financial economics, refrained from it. We also demonstrate that the degree of managerial discretion moderated the effect of the CEO’s MBA education. Our study shows that institutional change in one domain (i.e., business education) contributed to change in another domain (i.e., corporate diversification), albeit with a considerable time lag.
Network Topology Algorithm Based on Energy-consumption Optimization of Multi-hop Wireless Networks

A balanced topology intervention algorithm based on energy-consumption optimization is presented in this paper. Multilayer sequence planning algorithm is firstly adopted to convert the nonlinear optimization problem into edge-stirring mechanism and node-stirring mechanism so as to independently optimize these sub-problems, and then the solutions of these problems are adopted to analyze the potential balanced performance between energy consumption and average path-length in the networks. Through simulation under different network scale and operational requirement, the validity and applicability of the algorithm are verified. In addition, we have found the balance point between edge-stirring mechanism and node-stirring mechanism in the network with energy and throughput constraints
Preference and Lysosomal Localization Acid Oxidase with an Unusual Acidic pH IL-4-Induced Gene-1 Is a Leukocyte l-Amino

Porti, Sangeeta S. Chavan and Charles C. ChuJames M. Mason, Mamta D. Naidu, Michele Barcia, Debrahttp://www.jimmunol.org/content/173/7/4561J Immunol€2004; 173:4561-4567; ;Referenceshttp://www.jimmunol.org/content/173/7/4561.full#ref-list-1This article cites 47 articles, 22 of which you can access for free at: Subscriptionshttp://jimmunol.org/subscriptionsInformation about subscribing to The Journal of Immunology is online at: Permissionshttp://www.aai. org/ji/copyright.htmlSubmit copyright permission requests at: Email Alertshttp://jimmunol.org/cgi/alerts/etocReceive free email-alerts when new articles cite this article. Sign up at:
Inspecting Sample Reusability for Active Learning

Active Learning (AL) exploits a learning algorithm to selectively sample examples which are expected to be highly useful for model learning. The resulting sample is governed by a sampling selection bias. While a bias towards useful examples is desirable, there is also a bias towards the learner applied during AL selection. This paper addresses sample reusability, i.e., the question whether and under which conditions samples selected by AL using one learning algorithm are well-suited as training data for another learning algorithm. Our empirical investigation on general classication problems as well as the natural language processing subtask of Named Entity Recognition shows that many intuitive assumptions on reusability characteristics do not hold. For example, using the same algorithm during AL selection (called selector) and for inducing the nal model (called consumer) is not always the optimal choice. We investigate several putatively explanatory factors for sample reusability. One nding is that the suitability of certain selector-consumer pairings cannot be estimated independently of the actual learning problem.
Assessing metacognitive abilities of postgraduate medical students

Background: Metacognition is essential to successful learning, especially in the field of medicine because it enables individuals to better manage their cognitive skills and determine weaknesses that can be corrected by constructing new cognitive skills. This study was undertaken to study the difference in the metacognitive abilities toward learning in the clinical and nonclinical disciplines of medicine. Methods: Four hundred and sixty-eight residents were contacted, 442 consented, 373 completely filled pro formas were received, and two groups, namely, clinical (n = 275) and nonclinical (n = 128) were formed. Data were collected with the help of a semi-structured questionnaire and the metacognitive assessment inventory. It has two broad domains-knowledge about cognition and regulation of cognition with each having 3 and 5 subdomains, respectively. Results: The two broad domains of MAI revealed a highly significant difference with the students of nonclinical disciplines having higher knowledge about cognition (t = 1.46, P < 0.014) and regulation of cognition (t = 3.13, P < 0.0019) as compared to their clinical peers. All subdomains of knowledge about cognition showed highly significant differences. Planning and evaluation subdomains of regulation of cognition were significant in the nonclinical group. The other subdomains of information management, debugging strategies, and comprehension monitoring were not significant. Discussion: The nonclinical disciplines showed better ability for factual knowledge, use of critical thinking, knowledge about how to implement and when, and why to use learning procedures as compared to their clinical counterparts. Planning, goal setting, with an analysis of performance was also much better in the students of nonclinical disciplines. Conclusion: This study highlights the need to inculcate in medical postgraduates self-learning using their metacognitive abilities so that learning would become more focused and improvement in skills would take place.
Family Background, Secondary School and University Prestige: Contributors to Income Inequality in Chile.

There is strong evidence that expansion of university enrolment contributes to economic growth. Less clear, however, is whether that expansion will reduce income inequality. Human capital theory argues that education provides graduates with the knowledge and skills to be more productive. As more students from disadvantaged families graduate from universities, the theory states, the effect will be greater income equality. If, however, salaries depend on characteristics linked to graduates’ social origin, expansion can perpetuate inequality. This study examines the relationship between salary on graduation from university, and mother’s education, prestige of secondary school and university attended, and graduates’ perceptions of the quality of the university program completed. Data were collected from a sample of students in two degree programs in three universities in Chile. Salaries for graduates in psychology were unrelated to any of the independent variables. Salaries for graduates entering teaching were higher for those who attended more prestigious secondary schools.