Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in the Employment Contract? Evidence from a Quasi-Experiment

provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. Abstract: Many authors have discussed an apparent shift to a new employment contract characterized by less commitment between employer and employee coupled with closer ties between wages within the enterprise and those in the external labor market. We study the issue of when people in the U.S. and Canada feel pay cuts are fair, comparing our results with those of Kahneman, Knetsch, and Thaler (1986). In contrast to much previous discussion, we find no evidence of increasing acceptance of pay cuts--a measure of whether external, not internal, labor markets are considered fair. These results suggest that new organizational forms might do well to preserve some of the features of the "old" employment contract. Abstract The recent reform of the federal welfare system is meant to encourage recipients to leave welfare and enter the workforce. If the reform is successful there are likely to be e(cid:11)ects felt throughout the low{skilled end of the labor market. As former welfare recipients enter the labor market, they may exert downward pressure on wages or displace employment of others already in the labor market. Since there has been limited changes in eligibility for federal welfare programs from which to draw inferences, the magnitude of these labor market e(cid:11)ects are open to debate. This study considers these issues in general and evaluates how labor markets in Michigan were a(cid:11)ected when the General Assistance program in that state was eliminated in 1991. General Assistance was a large{scale, state{administered program that provided bene(cid:12)ts to people who fell through the cracks in federal anti{poverty programs. In all, about eighty to one{hundred thousand able{bodied adults lost bene(cid:12)ts. Increased labor force participation among these people resulted in a decline in weekly hours among high school drop{outs of 1.2 to 2.4 percent. There is little evidence of declines in hourly earnings, except in the Detroit area, where wages fell by about (cid:12)ve percent.
CAMTA 1 Immunostaining is not Useful in Differentiating Epithelioid Hemangioendothelioma from its Potential Mimickers CAMTA

Objective: Epithelioid hemangioendothelioma is a rare member of vascular tumors of intermediate malignancy. Recently, presence of t(1;3) translocation and WWTR1/CAMTA1 gene fusion, which enhances CAMTA1 expression, are found to be specific to this tumor. We investigated the CAMTA1 immune expression profile of epithelioid hemangioendothelioma and its potential mimickers using a commercially available CAMTA1 antibody.
COWLES FOUNDATION FOR RESEARCH IN ECONOMICS

The efficient markets theory reached the height of its dominance in academic circles around the 1970s. Faith in this theory was eroded by a succession of discoveries of anomalies, many in the 1980s, and of evidence of excess volatility of returns. Finance literature in this decade and after suggests a more nuanced view of the value of the efficient markets theory, and, starting in the 1990s, a blossoming of research on behavioral finance. Some important developments in the 1990s and recently include feedback theories, models of the interaction of smart money with ordinary investors, and evidence on obstacles to smart money.
Interventionelle Therapie der Varikosis mit hocherhitztem Dampf

Seit November 2009 ist ein weiteres endovenöses Verfahren zur Behandlung der Varikosis in Deutschland erhältlich, das Heißdampf-Verfahren, kurz SVS (Steam vein sclerosis) genannt. Bisher gibt es wenige Daten zur Effektivität dieser neuen Methode. Eine „Proofof-Principle-Studie“ zeigte bei 13 von 20 behandelten Stammvenen (Magna oder Parva) einen vollkommenen Verschluss, bei 7 Venen eine kurzstreckige Rekanalisation nach 6 Monaten (1). Auch ich kann noch keine weiteren Daten diesbezüglich vorweisen, deshalb werde ich nur meine bisherigen Erfahrungen mit dem Heißdampf-Gerät erläutern. Der SVS-Generator ( Abb.1) ist von der Größe ähnlich den Generatoren anderer endovaskulärer Verfahren (VNUS closure fast, RFITT (Celon), Radiallaser 1470 nm). Der Unterschied ist jedoch, dass das Gerät an einen Druckluftausgang im OP angeschlossen oder aber mit seperater CO2-Flasche ausgestattet werden muß.
Theory and application of weather index-based insurance in agriculture

Purpose – Since the 1990s, there has been a discussion about the use of weather indexbased insurance, also called weather derivatives, as a new instrument to hedge against volumetric risks in agriculture. It particularly differs from other insurance schemes by pay-offs being related to objectively measurable weather variables. Due to the absence of individual farm yield time series, the hedging effectiveness of weather index-based insurance is often estimated on the basis of aggregated farm data. We expect that there are differences in the hedging effectiveness of insurance on the aggregated level and on the individual farm-level. The purpose of this paper is to estimate the magnitude of bias which occurs if the hedging effectiveness of weather index-based insurance is estimated on aggregated yield data. Design/methodology/approach – The study is based on yield time series from individual farms in central Germany and weather data provided by the German Meteorological Service. Insurance is structured as put-option on a cumulated precipitation index. The analysis includes the estimation of the hedging effectiveness of insurance on aggregated level and on individual farm-level. The hedging effectiveness is measured nonparametrically regarding the relative reduction of the standard deviation and the value at risk of wheat revenues. Findings – Findings indicate that the hedging effectiveness of a weather index-based insurance estimated on aggregated level is considerably higher than the realizable hedging effectiveness on the individual farm-level. This refers to (i) hedging effectiveness estimated on the aggregated level is higher than the mean of realized hedging effectiveness on the individual farm-level and (ii) almost every evaluated individual farm in our analysis realizes a lower hedging effectiveness than estimated on I. Hedging weather risk on aggregated and individual farm-level 21 the aggregated level of the study area. Nevertheless, weather index-based insurance designed on the aggregated level can lead to a notable risk reduction for individual farms. Research limitations/implications – We focused on farms in central Germany and found a pronounced bias when the hedging effectiveness of weather index-based insurance is estimated on aggregated data and assigned to individual farms. To confirm that the indicated magnitude of this bias is also applicable to other geographic regions, further research is required. Practical implications – The results reconfirm that weather index-based insurance can be attractive for farmers. The fact that the hedging effectiveness estimated on aggregated level is higher than that estimated on individual farm-level reveals that (potential) suppliers of insurance may overestimate the market potential if their analysis is only based on aggregated data. Originality/value – To our knowledge, this paper is the first that analyzes the influence of crop yield aggregation with regard to the hedging effectiveness of weather indexbased insurance.
Clinical outcomes in clinical trials of anti-HIV treatment

Since the introduction of combination antiretroviral therapy, there has been a decrease in both AIDS-defining illnesses and deaths. This decrease meant that performing clinical trials with clinical outcomes in HIV infection became more time consuming and hence costly. Improved understanding and knowledge of HIV led to short-term trials using surrogate outcomes such as viral load and CD4 count. This established a faster drug approval process that complimented the rapid need to evaluate and provide access to drugs based on short-term trials. However, no treatment has yet been found that eradicates the infection, so when treatment is started it is currently a lifelong commitment. Is it reasonable then that guidelines are based almost completely on short-term randomized trials and observational studies of surrogate markers, or is there still a need for trials with clinical outcomes?
Ja n 20 14 POSTECH-MLG-2014-001 Convex Optimization for Binary Classifier Aggregation in Multiclass Problems a

Multiclass problems are often decomposed into multiple binary problems that are solved by individual binary classifiers whose results are integrated into a final answer. Various methods, including all-pairs (APs), one-versus-all (OVA), and error correcting output code (ECOC), have been studied, to decompose multiclass problems into binary problems. However, little study has been made to optimally aggregate binary problems to determine a final answer to the multiclass problem. In this paper we present a convex optimization method for an optimal aggregation of binary classifiers to estimate class membership probabilities in multiclass problems. We model the class membership probability as a softmax function which takes a conic combination of discrepancies induced by individual binary classifiers, as an input. With this model, we formulate the regularized maximum likelihood estimation as a convex optimization problem, which is solved by the primal-dual interior point method. Connections of our method to large margin classifiers are presented, showing that the large margin formulation can be considered as a limiting case of our convex formulation. Numerical experiments on synthetic and real-world data sets demonstrate that our method outperforms existing aggregation methods as well as direct methods, in terms of the classification accuracy and the quality of class membership probability estimates. aAppeared in Proceedings of the 2014 SIAM International Conference on Data Mining (SDM 2014). 2 S. Park et al. CONTENTS
N ov 2 00 7 Models for dependent extremes using stable mixtures Running / short title : Models for dependent extremes

Abstract: This paper unifies and extends results on a class of multivariate Extreme Value (EV) models studied by Hougaard, Crowder, and Tawn. In these models both unconditional and conditional distributions are EV, and all lower-dimensional marginals and maxima belong to the class. This leads to substantial economies of understanding, analysis and prediction. One interpretation of the models is as size mixtures of EV distributions, where the mixing is by positive stable distributions. A second interpretation is as exponential-stable location mixtures (for Gumbel) or as power-stable scale mixtures (for non-Gumbel EV distributions). A third interpretation is through a Peaks over Thresholds model with a positive stable intensity. The mixing variables are used as a modeling tool and for better understanding and model checking. We study extreme value analogues of components of variance models, and new time series, spatial, and continuous parameter models for extreme values. The results are applied to data from a pitting corrosion investigation.
A Completeness Result for the ∀ + Types of System

We presente in this note a completeness result for the types with positive quantifiers of the J.-Y. Girard type system F . This result generalizes a theorem of R. Labib-Sami (see [3]). Abridged English Version. The F type system have been introduced by J.-Y. Girard (see [1]). This system is based on the second order intuitionistic propositional calculus, and thus it gives the possibility to quantify on types. In addition to strong normalisation theorem which certifies the termination of programs, the system F has two more properties : It allows to write programs for all the fonctions whose termination can be proved in the Peano’s second order arithmetics. It allows to define all the usual data types : booleans, integers, lists, etc. The semantics of the system F proposed by J.-Y. Girard and J.-L. Krivine (see [1] and [2]) consists in associating to each type A a set of λ-terms |A|, in order to obtain the following result: if a λ-term t is of type A, then it belongs to the set |A|. This result is known as the adequation lemma, and it allows to prove the strong normalisation of system F and the unicity of data representation. The converse of the adequation lemma (a completeness result) is not true. The difficulty comes from the interpretation of second order quantifier. R. LabibSami proved a completeness result for the types with positive quantifiers and for a semantic based on the sets stable by the βη-equivalence (see [3]). In this
SC ] 1 2 A pr 2 01 3 Kinetic vs . energetic discrimination in biological copying

We study stochastic copying schemes in which discrimination between a right and a wrong match is achieved via different kinetic barriers or different binding energies of the two matches. We demonstrate that, in single-step reactions, the two discrimination mechanisms are strictly alternative and can not be mixed to further reduce the error fraction. Close to the lowest error limit, kinetic discrimination results in a diverging copying velocity and dissipation per copied bit. On the opposite, energetic discrimination reaches its lowest error limit in an adiabatic regime where dissipation and velocity vanish. By analyzing experimentally measured kinetic rates of two DNA polymerases, T7 and Polγ, we argue that one of them operates in the kinetic and the other in the energetic regime. Finally, we show how the two mechanisms can be combined in copying schemes implementing error correction through a proofreading pathway.
Class : Class 0 : Normal Person . Class 1 : first stroke Class 2 : second stroke Class 3 : end of life Attribute Description

One of the important techniques of Data mining is Classification. Many real world problems in various fields such as business, science, industry and medicine can be solved by using classification approach. Neural Networks have emerged as an important tool for classification. The advantages of Neural Networks helps for efficient classification of given data. In this study a Heart diseases dataset is analyzed using Neural Network approach. To increase the efficiency of the classification process parallel approach is also adopted in the training phase.
OF BOOTSTRAP : THE GRENANDER ESTIMATOR By

In this paper, we investigate the (in)-consistency of different bootstrap methods for constructing confidence intervals in the class of estimators that converge at rate n. The Grenander estimator, the nonparametric maximum likelihood estimator of an unknown nonincreasing density function f on [0,∞), is a prototypical example. We focus on this example and explore different approaches to constructing bootstrap confidence intervals for f(t0), where t0 ∈ (0,∞) is an interior point. We find that the bootstrap estimate, when generating bootstrap samples from the empirical distribution function Fn or its least concave majorant F̃n, does not have any weak limit in probability. We provide a set of sufficient conditions for the consistency of any bootstrap method in this example and show that bootstrapping from a smoothed version of F̃n leads to strongly consistent estimators. The m out of n bootstrap method is also shown to be consistent while generating samples from Fn and F̃n.
IJASCSE Volume 2, Theme based issue 3, 2013

The wireless sensor networks combines sensing, computation, and communication into a single small device. These devices depend on battery power and may be placed in hostile environments replacing them becomes a tedious task. Thus improving the energy of these networks becomes important. Clustering in wireless sensor network looks several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we study a protocol supporting an energy efficient clustering, cluster head selection and data routing method to extend the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection and data routing. The results of simulation show that at the end of some certain part of running the EECS and Fuzzy based clustering algorithm increases the number of alive nodes comparing with the LEACH and HEED methods and this can lead to an increase in sensor network lifetime. By using the EECS method the total number of messages received at base station is increased when compared with LEACH and HEED methods. The Fuzzy based clustering method compared with the K-Means Clustering by means of iteration count and time taken to die first node in wireless sensor network, as the result shows that the fuzzy based clustering method perform well than kmeans clustering methods.
N ov 2 00 9 QUANTIFYING SLOW EVOLUTIONARY DYNAMICS IN RNA FITNESS

We re-examine the evolutionary dynamics of RNA secondary structures under directional selection towards an optimum RNA structure. We find that the punctuated equilibria lead to a very slow approach to the optimum, following on average an inverse power of the evolutionary time. In addition, our study of the trajectories shows that the out-of-equilibrium effects due to the evolutionary process are very weak. In particular, the distribution of genotypes is close to that arising during equilibrium stabilizing selection. As a consequence, the evolutionary dynamics leave almost no measurable out-of-equilibrium trace, only the transition genotypes (close to the border between different periods of stasis) have atypical mutational properties.
44 55 v 1 [ cs . D S ] 18 F eb 2 01 4 Symbiosis of Search and Heuristics for Random 3SAT

When combined properly, search techniques can reveal the fu ll potential of sophisticated branching heuristics. We demonstrat e this observation on the well-known class of random 3-SAT formulae. First, a new bran chi g heuristic is presented, which generalizes existing work on this class. M uch smaller search trees can be constructed by using this heuristic. Second, we introduce a variant of discrepancy search, called ALDS. Theoretical and practi c l evidence support that ALDS traverses the search tree in a near-optimal order w h n combined with the new heuristic. Both techniques, search and heuristic, h ave been implemented in the look-ahead solver march. The SAT 2009 competition results show that march is by far the strongest complete solver on random k-SAT formulae.
Learning styles: Literature versus machine learning

Every teacher understands that different students benefit from different activities. Recent advances in data processing allow us to detect and use behavioral variability for adapting to a student. This approach allows us to optimize learning process but does not focus on understanding it. Conversely, classical findings in educational sciences allow us to understand the learner but are hard to embed in a large scale adaptive system. In this study we design and build a framework to investigate when the two approaches coincide.
Improving TCP/IP Performance over Wireless IEEE 802.11 Link

Cellular phones, wireless laptops, personal portable devices that supports both voice and data access are all examples of communicating devices that uses wireless communication. Sine TCP/IP (and UDP) is the dominant technology in use in the internet, it is expected that they will be used (and they are currently) over wireless connections. In this paper, we investigate the performance of the TCP (and UDP) over IEEE802.11 wireless MAC protocol. We investigate the performance of the TCP and UDP assuming three different traffic patterns. First bulk transmission where the main concern is the throughput. Second real-time audio (using UDP) in the existence of bulk TCP transmission where the main concern is the packet loss for audio traffic. Finally web traffic where the main concern is the response time. We also investigate the effect of using forward Error Correction (FEC) technique and the MAC sublayer parameters on the throughput and response time.
Deep Bayesian Neural Netowrk Performance Measurement

Deep Bayesian neural network has aroused a great attention in recent years since it combines the benefits of deep neural network and probability theory. Because of this, the network can make predictions and quantify the uncertainty of the predictions at the same time, which is important in many life-threatening areas. However, most of the recent researches are mainly focusing on making the Bayesian neural network easier to train, and proposing methods to estimate the uncertainty. I notice there are very few works that properly discuss the ways to measure the performance of the Bayesian neural network. Although accuracy and average uncertainty are commonly used for now, they are too general to provide any insight information about the model. In this paper, we would like to introduce more specific criteria and propose several metrics to measure the model performance from different perspectives, which include model calibration measurement, data rejection ability and uncertainty divergence for samples from the same and different distributions.
N ov 2 01 0 Trace-Driven Performance Evaluation of Distributed File Systems under Enterprise Application Workload

We evaluate the performance of distributed file systems (DFS) under the IO load produced by enterprise applications. The evaluation is carried out using a trace-bas ed approach that allows for recording file system accesses of an application and re-playing the trace on an arbitrary file systems under test. This method avoids the overhead that is associat ed with installing and maintaining complex multi-tier enterp rise applications. Our trace-based assessment suggests that DF S, and specifically XtreemFS have a good potential to support trans actional IO load in distributed environments: they demonstrate good performance of read operations and scalability in gene ral, while at the same time opening the way for significant TCO reduction. We found, however, that more work should be done to improve the performance of write operations, which is crucial in transactional enterprise applications.
An Affine-Transformation Invariant Bayesian Cluster Process with Split-Merge Gibbs Sampler

In order to identify clusters of objects with features transformed by unknown affine transformations, we develop a Bayesian cluster process which is invariant with respect to certain linear transformations of the feature space and able to cluster data without knowing the number of clusters in advance. Specifically, our proposed method can identify clusters invariant to orthogonal transformations under model I, invariant to scaling-coordinate orthogonal transformations under model II, or invariant to arbitrary non-singular linear transformations under model III. The proposed split-merge algorithm leads to an irreducible and aperiodic Markov chain, which is also efficient at identifying clusters reasonably well for various applications. We illustrate the applications of our approach to both synthetic and real data such as leukemia gene expression data for model I; wine data and two half-moons benchmark data for model II; three-dimensional Denmark road geographic coordinate system data and an arbitrary non-singular transformed two half-moons data for model III. These examples show that the proposed method could be widely applied in many fields, especially for finding the number of clusters and identifying clusters of samples of interest in aerial photography and genomic data.