Miracle-dz/UniFAR-FTUs huggingface dataset:
Leading Indicators and the Evaluation of the Performance of Alerts for Influenza Epidemics

Background Most evaluations of epidemic thresholds for influenza have been limited to internal criteria of the indicator variable. We aimed to initiate discussion on appropriate methods for evaluation and the value of cross-validation in assessing the performance of a candidate indicator for influenza activity. Methods Hospital records of in-patients with a diagnosis of confirmed influenza were extracted from the Canadian Discharge Abstract Database from 2003 to 2011 and aggregated to weekly and regional levels, yielding 7 seasons and 4 regions for evaluation (excluding the 2009 pandemic period). An alert created from the weekly time-series of influenza positive laboratory tests (FluWatch, Public Health Agency of Canada) was evaluated against influenza-confirmed hospitalizations on 5 criteria: lead/lag timing; proportion of influenza hospitalizations covered by the alert period; average length of the influenza alert period; continuity of the alert period and length of the pre-peak alert period. Results Influenza hospitalizations led laboratory positive tests an average of only 1.6 (95% CI: -1.5, 4.7) days. However, the difference in timing exceeded 1 week and was statistically significant at the significance level of 0.01 in 5 out of 28 regional seasons. An alert based primarily on 5% positivity and 15 positive tests produced an average alert period of 16.6 weeks. After allowing for a reporting delay of 2 weeks, the alert period included 80% of all influenza-confirmed hospitalizations. For 20 out of the 28 (71%) seasons, the first alert would have been signalled at least 3 weeks (in real time) prior to the week with maximum number of influenza hospitalizations. Conclusions Virological data collected from laboratories was a good indicator of influenza activity with the resulting alert covering most influenza hospitalizations and providing a reasonable pre-peak warning at the regional level. Though differences in timing were statistically significant, neither time-series consistently led the other.
Individualized 3 D Face Model Reconstruction using Two Orthogonal Face Images

In this paper, there are two main topics to generate a 3D facial model from 2D face images. The first topic is to extract facial components such as eyebrows, eyes, nose, ear, mouth and face contour on the face images, and the second is to create 3D individualized face model using extracted facial components information at previous step. The generated final face model has an individualized shape, realistic skin texture and deformable structure for facial animation. In this paper, we propose novel approach to detect facial components automatically using a active contour extraction algorithm(Active Contour Model, Snake) for facial information. And how to generate adaptive individualized 3D face model from detected facial components are explained and result of 3D face models are discussed.
Differential potencies of effector genes in adult Drosophila

The GAL4/UAS gene expression system in Drosophila has been crucial in revealing the behavioral significance of neural circuits. Transgene products that block neurotransmitter release and induce cell death have been proved to inhibit neural function powerfully. Here we compare the action of the five effector genes shibirets1, Tetanus toxin light chain (TNT), reaper, Diphtheria toxin A‐chain (DTA), and inwardly rectifying potassium channel (Kir2.1) and show differences in their efficiency depending on the target cells and the timing of induction. Specifically, effectors blocking neuronal transmission or excitability led to adult‐induced paralysis more efficiently than those causing cell ablation. We contrasted these differential potencies in adult to their actions during development. Furthermore, we induced TNT expression in the adult mushroom bodies. In contrast to the successful impairment in short‐term olfactory memory by shibirets1, adult TNT expression in the same set of cells did not lead to any obvious impairment. Altogether, the efficiency of effector genes depends on properties of the targeted neurons. Thus, we conclude that the selection of the appropriate effector gene is critical for evaluating the function of neural circuits. J. Comp. Neurol. 498:194–203, 2006. © 2006 Wiley‐Liss, Inc.
Towards Integration of End-User Tags with Professional Annotations

The goal of the paper is assessing the quality of end-user tags from a video labeling game as a first step in the process of integrating them with the annotations made by professionals. Tags lack precise meaning, whereas the terms and concepts the professionals are used to have a clearly defined semantics given by structured vocabularies. Hence, we explore the possibility of mapping user tags to their semantic counterparts from domain and lexical vocabularies. Furthermore, we report on an analysis performed by a senior cataloguer regarding the general usefulness of the user tags in terms of video and fragment retrieval. Finally, we investigate the distribution of tags with respect to audio and visual portion of the video content.
Koszul Duality for Dioperads

We introduce the notion of a dioperad to describe certain operations with multiple inputs and multiple outputs. The framework of Koszul duality for operads is generalized to dioperads. We show that the Lie bialgebra dioperad is Koszul. The current interests in the understanding of various algebraic structures using operads is partly due to the theory of Koszul duality for operads; see eg. [K] or [L] for surveys. However, algebraic structures such as bialgebras and Lie bialgebras, which involve both multiplication and comultiplication, or bracket and cobracket, are defined using PROP's (cf. [Ad]) rather than operads. Inspired by the theory of string topology of Chas-Sullivan ([ChS], [Ch], [Tr]), Victor Ginzburg suggested to the author that there should be a theory of Koszul duality for PROP's. The present paper results from the observation that when the defining relations between the generators of a PROP are spanned over trees, then the " tree-part " of the PROP has the structure of a dioperad. We show that one can set up a theory of Koszul duality for dioperads. In §1, we give the definition of a dioperad and other generalities. In §2, we define the notion of a quadratic dioperad, its quadratic dual, and introduce our main example of Lie bialgebra dioperad. In §3, we define the cobar dual of a dioperad. A quadratic dioperad is Koszul if its cobar dual is quasi-isomorphic to its quadratic dual. The formalism in §2 and §3, in the case of operads, is due to Ginzburg-Kapranov [GiK]. In §4, we prove a proposition to be used later in §5. This proposition is a generalization of a result of Shnider-Van Osdol [SVO]. In §5, we prove that Koszulity of a quadratic dioperad is equivalent to exactness of certain Koszul complexes. In the case of operads, this is again due to Ginzburg-Kapranov, with a different proof by Shnider-Van Osdol. The Koszulity of the Lie bialgebra dioperad follows from this and an adaptation of results of Markl [M2]. 1. Dioperads 1.1. Let C be the category of finite dimensional differential Z-graded super vector spaces over a field k of characteristic 0, and let Hom be the internal hom functor of C.
Tunable bandpass frequency selective surface with embedded biasing

This article presents a tunable bandpass frequency selective surface (FSS) based on varactor diodes. The FSS is made of three metallic layers that are separated from each other by two thin dielectric spacers. Tunability is achieved by loading varactor diodes on the front and back layers. The varactors are connected to the middle layer wire grid and are tuned by applying a bias voltage between the middle and front/back layers wire grids. The proposed tuning concept is validated by fabricating an FSS prototype and testing it in a parallel plate waveguide setup.
An Empirical Analysis of a Large-scale Mobile Cloud Storage Service

Cloud storage services are serving a rapidly increasing number of mobile users. However, little is known about the differences between mobile and traditional cloud storage services at scale. In order to understand mobile user access behavior, we analyzed a dataset of 350 million HTTP request logs from a large-scale mobile cloud storage service. This paper presents our results and discusses the implications for system design and network performance. Our key observation is that the examined mobile cloud storage service is dominated by uploads, and the vast majority of users rarely retrieve their uploads during the one-week observation period. In other words, mobile users lean towards the usage of cloud storage for backup. This suggests that delta encoding and chunk-level deduplication found in traditional cloud storage services can be reasonably omitted in mobile scenarios. We also observed that the long idle time between chunk transmissions by Android clients should be shortened since they cause significant performance degradation due to the restart of TCP slow-start. Other observations related to session characteristics, load distribution, user behavior and engagement, and network performance.
Generation of ATM Video Traffic Using Neural Networks

A new model to generate Asynchronous Transfer Mode (ATM) video traffic is presented. The model, implemented on neural networks, is capable of accurately adjusting the autocorrelation and probability distribution functions of a given video traffic. This adjustment is performed by capturing the projected conditioned histogram of the real traffic, so that the neural model will be able to yield a simulated as a function of an input white noise. Using neural networks we benefit from their inherent capacities for working in real time, because of their parallelism, and interpolating unknown functions. Results are presented for a real MPEG video source.
Applying Experiential Learning in College Teaching and Assessment: A Process Model.

This manual presents a process model in which university teaching and assessment processes are embedded within a broader view of the human learning experience and the outcomes that are required for professional student growth. The model conceptualizes the university's role in the lives of life-long learners and provides a framework for rethinking traditional university teaching practices and future research into teaching and learning. The model's components include: (1) adult learner characteristics; (2) the conceptual foundations of experiential learning; (3) methods and techniques for engaging learners in experiential learning activities; (4) assessment processes and outcomes, involving building a folio with artifacts and reproductions; and (5) building a portfolio from the folio. Implications of the model for college and university courses and programs are discussed. Chapters have the following titles and authors: "Overview of the Model of the Teaching/Learning Process" (Lewis Jackson and Doug Maclsaac); "Characteristics of Adult Learners and Foundations of Experiential Learning" (Rosemary Caffarella and Bruce Barnett); "Methods and Techniques for Engaging Learners in Experiential Learning Activities" (Patty Lee and Rosemary Caffarella); "Assessment Processes and Outcomes: Building a Folio with Artifacts and Reproductions" (Bruce Barnett and Patty Lee); and "Assessment Processes and Outcomes: Building a Portfolio from the Folio" (Doug MacIsaac and Lewis Jackson). (References accompany each chapter.) (JDD) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** 6 ' . Experiential Learning Model 1
Subtyping object and recursive types logically ⋆ (Extended Abstract)

We study subtyping in first-order object calculi with respec t to the logical semantics obtained by identifying terms that satis fy the same set of pre- dicates, as formalized through an assignment system. It is shown that equality in the full first-order ς-calculus is modeled by this notion, which is included in a Morris-style contextual equivalence.
Parallelize Bubble Sort Algorithm Using OpenMP

Sorting has been a profound area for the algorithmic researchers and many resources are invested to suggest more works for sorting algorithms. For this purpose, many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. In this paper we implemented the bubble sort algorithm using multithreading (OpenMP). The proposed work tested on two standard datasets (text file) with different size . The main idea of the proposed algorithm is distributing the elements of the input datasets into many additional temporary sub- arrays according to a number of characters in each word. The sizes of each of these sub-arrays are decided depending on a number of elements with the same number of characters in the input array. We implemented OpenMP using Intel core i7-3610QM ,(8 CPUs),using two approaches (vectores of string and array 3D) . Finally, we get the data structure effects on the performance of the algorithm for that we choice the second approach.
The structure and evolution of lower stratospheric frontal zones. Part II: The influence of tropospheric ascent on lower stratospheric frontal development

The intensification of frontal characteristics in the region above the mid‐latitude jet core within the lower stratospheric portion of an upper‐level jet front system (ULJF) is known as lower stratospheric frontogenesis. Four recent cases of lower stratospheric frontogenesis in southwesterly flow are examined in order to elucidate the interaction between lower stratospheric dynamical processes and tropospheric ascent that characterizes such developments. In all of the cases examined the lower stratospheric front was (1) characterized by lower stratospheric quasi‐geostrophic forcing for ascent on its cold side, and (2) parallel to a surface cold front.
Ouroboros: Objectivity of the subjective process of interpretation

Behoudens de in of krachtens de Auteurswet van 1912 gestelde uitzonderingen mag niets uit deze uitgave worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand, of openbaar gemaakt, in enige vorm of op enige wijze, hetzij elektronisch, mechanisch door fotokopieën, opnamen of enig andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. Voor zover het maken van kopieën uit deze uitgave is toegestaan op grond van artikelen 16h t/m 16m Auteurswet 1912 jo. Besluit van 27 november 2002, Stb 575, dient men de daarvoor wettelijk verschuldigde vergoeding te voldoen aan de Stichting Reprorecht te Hoofddorp (postbus 3060, 2130 KB, www.reprorecht.nl) of contact op te nemen met de uitgever voor het treffen van een rechtstreekse regeling in de zin van art. 16l, vijfde lid, Auteurswet 1912. Voor het overnemen van gedeelte(n) uit deze uitgave in bloemlezingen, readers en andere compilatiewerken (artikel 16, Auteurswet 1912) kan men zich wenden tot de Stichting PRO (Stichting Publicatieen Reproductierechten, postbus 3060, 2130 KB Hoofddorp, www.cedar.nl/pro).
A general approach to the joint asymptotic analysis of statistics from sub-samples

In time series analysis, statistics based on collections of estimators computed from sub-samples play a crucial role in an increasing variety of important applications. Proving results about the joint asymptotic distribution of such statistics is challenging since it typically involves a nontrivial verification of technical conditions and tedious case-by-case asymptotic analysis. In this paper, we provide a novel technique that allows to circumvent those problems in a general setting. Our approach consists of two major steps: a probabilistic part which is mainly concerned with weak convergence of sequential empirical processes, and an analytic part providing general ways to extend this weak convergence to functionals of the sequential empirical process. Our theory provides a unified treatment of asymptotic distributions for a large class of statistics, including recently proposed self-normalized statistics and sub-sampling based p-values. In addition, we comment on the consistency of bootstrap procedures and obtain general results on compact differentiability of certain mappings that seem to be of independent interest.
Order Estimation of Multivariate ARMA Models

Model order estimation is fundamental in the system identification process. In this paper, we generalize a previous multivariate autoregressive (AR) model order estimation method (J. Lardies and N. Larbi, ¿A new method for model order selection and model parameter estimation in time domain,¿ J. Sound Vibr., vol. 245, no. 2, 2001) to include multivariate autoregressive moving average (ARMA) models and propose a modified model order selection criterion. We discuss the performance analysis of the proposed criterion and show that it has a lower error probability for model order selection when compared to the criterion of G. Liang ¿ARMA model order estimation based on the eigenvalues of the covariance matrix,¿IEEE Trans. Signal Process. , vol. 41, no. 10, pp. 3009-03009, Oct. 1993). A Monte-Carlo (MC) analysis of the model order selection performance under different noise variations and randomized model parameters is performed, allowing the MC results to be generalized across model parameter values and various noise levels. Finally we validate the model for both simulated data and real electroencephalographic (EEG) data by spectral fitting, using the model order selected by the proposed technique as compared to that selected by Akaike's Information Criterion (AIC). We demonstrate that with the proposed technique a better fit is obtained.
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Testing for Bubbles in Housing Markets: New Results Using a New Method Testing for Bubbles in Housing Markets: New Results Using a New Method

In the context of financial crises influenced by the development and burst of housing price bubbles, the detection of exuberant behaviors in the financial market and the implementation of early warning diagnosis tests are of vital importance. This paper applies the new method developed by Phillips et al (2012) for detecting bubbles in the Colombian residential property market. The empirical results suggest that currently the country could be experiencing a price bubble, when the CPI and the housing rent index are used as deflators. We do not check the robustness of these results to alternative deflators, such as a household income index and a land price index, due to the lack of monthly data on these indicators. The views in this paper are those of the authors and do not necessarily reflect the views of the Banco de la República, its Board of Directros, the Federal Reserve Bank of Dallas or the Federal Reserve System. ABSTRACT In the context of financial crises influenced by the development and burst of housing price bubbles, the detection of exuberant behaviors in the financial market and the implementation of early warning diagnosis tests are of vital importance. This paper applies the new method developed by Phillips et al (2012) for detecting bubbles in the Colombian residential property market. The empirical results suggest that currently the country could be experiencing a price bubble, when the CPI and the housing rent index are used as deflators. We do not check the robustness of these results to alternative deflators, such as a household income index and a land price index, due to the lack of monthly data on these indicators. 1 Disclaimer: The findings, recommendations, interpretations and conclusions expressed in this paper are those of the authors and do not necessarily reflect the view of the Banco de la República or its Board of Directors. We gratefully acknowledge Peter C.B. Phillips, Jun Yu, Hernando Vargas and Andrés Murcia for valuable comments. All remaining errors are our own.
An adaptive e-learning framework: crowdsourcing approach

E-learning is an attractive learning opportunity that eliminates time and space restrictions imposed by traditional learning activities. Many learners have greatly benefited from the availability of learning material and the flexibility of the e-learning process. Still, other issues in the e-learning process need to be addressed. Adaptive e-learning is the new trend towards more flexible and personalized learning material instead of a one-size-fits-all approach. It is a learner-centered approach that provides learners with an individualized, engaging and responsive learning environment. Adaptive e-learning aims to improve the e-learning experience through the automatic adaptation of the lesson content and presentation to fit users' preferences and needs. This study proposes a framework for adapting learning content and lesson delivery through crowdsourcing and recommender systems to achieve a better-personalized and adaptive e-learning experience.
The Extracytoplasmic Domain of the Mycobacterium tuberculosis Ser/Thr Kinase PknB Binds Specific Muropeptides and Is Required for PknB Localization

The Mycobacterium tuberculosis Ser/Thr kinase PknB has been implicated in the regulation of cell growth and morphology in this organism. The extracytoplasmic domain of this membrane protein comprises four penicillin binding protein and Ser/Thr kinase associated (PASTA) domains, which are predicted to bind stem peptides of peptidoglycan. Using a comprehensive library of synthetic muropeptides, we demonstrate that the extracytoplasmic domain of PknB binds muropeptides in a manner dependent on the presence of specific amino acids at the second and third positions of the stem peptide, and on the presence of the sugar moiety N-acetylmuramic acid linked to the peptide. We further show that PknB localizes strongly to the mid-cell and also to the cell poles, and that the extracytoplasmic domain is required for PknB localization. In contrast to strong growth stimulation by conditioned medium, we observe no growth stimulation of M. tuberculosis by a synthetic muropeptide with high affinity for the PknB PASTAs. We do find a moderate effect of a high affinity peptide on resuscitation of dormant cells. While the PASTA domains of PknB may play a role in stimulating growth by binding exogenous peptidoglycan fragments, our data indicate that a major function of these domains is for proper PknB localization, likely through binding of peptidoglycan fragments produced locally at the mid-cell and the cell poles. These data suggest a model in which PknB is targeted to the sites of peptidoglycan turnover to regulate cell growth and cell division.