Miracle-dz/UniFAR-FTUs huggingface dataset:
Weighing Risk and Uncertainty

Decision theory distinguishes between risky prospects, where the probabilities associated with the possible outcomes are assumed to be known, and uncertain prospects, where these probabilities are not assumed to be known. Studies of choice between risky prospects have suggested a nonlinear transformation of the probability scale that overweights low probabilities and underweights moderate and high probabilities. The present article extends this notion from risk to uncertainty by invoking the principle of bounded subadditivity: An event has greater impact when it turns impossibility into possibility, or possibility into certainty, than when it merely makes a possibility more or less likely. A series of studies provides support for this principle in decision under both risk and uncertainty and shows that people are less sensitive to uncertainty than to risk. Finally, the article discusses the relationship between probability judgments and decision weights and distinguishes relative sensitivity from ambiguity aversion. Decisions are generally made without definite knowledge of their consequences. The decisions to invest in the stock market, to undergo a medical operation, or to go to court are generally made without knowing in advance whether the market will go up, the operation will be successful, or the court will decide in one's favor. Decision under uncertainty, therefore, calls for an evaluation of two attributes: the desirability of possible outcomes and their likelihood of occurrence. Indeed, much of the study of decision making is concerned with the assessment of these values and the manner in which they are—or should be— combined. In the classical theory of decision under risk, the utility of each outcome is weighted by its probability of occurrence. Consider a simple prospect of the form (x, p) that offers a probability p to win $jc and a probability 1 — p to win nothing. The expected utility of this prospect is given by pu(x) + (1 — p)w(O), where u is the utility function for money. Expected utility theory has been developed to explain attitudes toward risk, namely, risk aversion and risk seeking. Risk aversion is denned as a preference for a sure outcome over a prospect with an equal or greater expected value. Thus, choosing a sure $100 over an even chance to win $200 or nothing is an expression of risk aversion. Risk seeking is exhibited if a prospect is preferred to a sure outcome with equal or greater expected value. It is commonly assumed that people are risk averse, which is explained in expected utility theory by a concave utility function. The experimental study of decision under risk has shown that people often violate both the expected utility model and the
Modeling network traffic in mobile networks implementing offloading

The increasing demand of mobile data traffic is starting to stress the networks of mobile network operators (MNOs). Techniques for offloading traffic (partially or totally) from the network of the MNO are currently being designed and deployed at various points of the network, which depend on the goal of each MNO. Such techniques divert traffic to offloading networks, such as Wi-Fi access networks, femtocells, etc., or directly to the Internet. This paper presents a generic analytical approach for studying the impact that offloading techniques might have on the networks of MNOs. The model is generic in the sense that it is independent of the specific offloading technology used and may be of use to provide bounds on network dimensioning. Based on previous measurements found in the literature, our model assumes that user activity periods and periods characterizing offloading are heavy-tailed. We model them as strictly alternating independent ON/OFF processes. Therefore, the non-offloaded traffic (i.e., that traffic still being served by the MNO on a regular basis) is modeled as the product of these two processes. We prove that the resulting process is long-range dependent, with heavy-tailed ON/OFF-period durations, and its characteristic parameters can be derived from those of the initial processes. We also evaluate the network resources required to serve the traffic resulting from the aggregation of many such sources. We conclude that offloading does not always mean reduction of resource consumption, and that the distribution of offloading periods turns out to be the main design parameter to deploy effective offloading strategies in the networks of MNOs. Extensive simulations, in which the Hill's estimator was used to obtain the main parameters of the resulting process, confirm the results of our analytical study.
Completion and Recidivism Rates of High-Risk Youth on Probation: Do Home Visits Make a Difference?

Probation supervision with and without home visits is an underresearched area for adjudicated higher risk youth. This study compared 287 juvenile probationers receiving police/probation home visits with similar youth (n = 437) who were supervised on regular probation without home visits. Youth performance was measured during supervision and up to 24 months following probation. The most notable finding was that the rearrest rate for youth who had home visits during supervision was 3 times lower after probation supervision ended than for youth who did not have home visits.
Development and Initial Testing of the Stroke Rapid-Treatment Readiness Tool

ABSTRACT No instruments are currently available to help health systems identify target areas for reducing door-to-needle times for the administration of intravenous tissue plasminogen activator to eligible patients with ischemic stroke. A 67-item Likert-scale survey was administered by telephone to stroke personnel at 252 U.S. hospitals participating in the “Get With The Guidelines-Stroke” quality improvement program. Factor analysis was used to refine the instrument to a four-factor 29-item instrument that can be used by hospitals to assess their readiness to administer intravenous tissue plasminogen activator within 60 minutes of patient hospital arrival.
Lack of confidence in ABC model choice

Approximate Bayesian computation (ABC) have become a essential tool for the analysis of complex stochastic models. Earlier, Grelaud et al. (2009) advocated the use of ABC for Bayesian model choice in the specific case of Gibbs random fields, relying on a inter-model sufficiency property to show that the approximation was legitimate. Having implemented ABC-based model choice in a wide range of phylogenetic models in the DIY-ABC software (Cornuet et al., 2008), we now present theoretical background as to why a generic use of ABC for model choice is ungrounded, since it depends on an unknown amount of information loss induced by the use of insufficient summary statistics. The approximation error of the posterior probabilities of the models under comparison may thus be unrelated with the computational effort spent in running an ABC algorithm. We then conclude that additional empirical verifications of the performances of the ABC procedure as those available in DIYABC are necessary to conduct model choice.
From informal resource usage to incidental language acquisition: language uptake from online television viewing in English

La recherche dans le domaine de l’apprentissage informel de l’anglais en ligne a mis en evidence le fait que ce phenomene est courant chez les apprenants d’anglais du secteur Lansad dans les universites francaises. La langue a laquelle ces apprenants sont exposes lors de visionnages de series televisees en version originale par le biais du streaming ou du telechargement a aussi ete caracterisee et quantifiee. Dans la presente etude, des apprenants ont d’abord repondu a un questionnaire pour determiner la frequence a laquelle ils visionnent de tels contenus. Ils ont ensuite participe a un test dans lequel ils se sont servis d’une echelle de connaissance de vocabulaire pour indiquer leur degre de connaissance d’une serie de phrases incorporant les blocs de quatre mots les plus frequents dans les dialogues de ces series. Les resultats indiquent un ecart significatif dans les scores a ce test entre ceux qui visionnent frequemment ces series, et ceux qui ne les visionnent qu’occasionnellement.
Membrane properties specialize mammalian inner hair cells for frequency or intensity encoding

The auditory pathway faithfully encodes and relays auditory information to the brain with remarkable speed and precision. The inner hair cells (IHCs) are the primary sensory receptors adapted for rapid auditory signaling, but they are not thought to be intrinsically tuned to encode particular sound frequencies. Here I found that under experimental conditions mimicking those in vivo, mammalian IHCs are intrinsically specialized. Low-frequency gerbil IHCs (~0.3 kHz) have significantly more depolarized resting membrane potentials, faster kinetics, and shorter membrane time constants than high-frequency cells (~30 kHz). The faster kinetics of low-frequency IHCs allow them to follow the phasic component of sound (frequency-following), which is not required for high-frequency cells that are instead optimally configured to encode sustained, graded responses (intensity-following). The intrinsic membrane filtering of IHCs ensures accurate encoding of the phasic or sustained components of the cell’s in vivo receptor potential, crucial for sound localization and ultimately survival. DOI: http://dx.doi. org/10.7554/eLife.08177. 001
A Hybrid Model of Wavelet and Neural Network for Short Term Load Forecasting

Electric load forecasting is a key to the efficient management of power supply system. Load forecasting, which involves estimation of future load according to the previous load data. This paper presents a pragmatic methodology for short term load forecasting (STLF) using proposed hybrid method of wavelet transform (WT) and artificial neural network (ANN). It is a two stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with other input is trained using separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Australia electricity market.
.0 Introduction 2.0 Test Chip Design

Quiescent Signal Analysis (QSA) is an I DDQ method for detecting defects that is based on the analysis of multiple simultaneous measurements of supply port I DDQ s. The nature of the information in the multiple I DDQ s measurements also allows for the localization of the defect to physical coordinates in the chip. In previous work, we derived a hyperbola-based method from simulation experiments that is able to " triangulate " the position of the defect in the layout. In this paper, we evaluate the accuracy of this method using data collected from 12 chips fabricated in a 65 nm process. Diagnosis is a process designed to identify the location of the fault in chips that have failed in the field or at production test. It is a key component to failure analysis. The information gleamed from failure analysis is used to tune the fabrication process for the purpose of improving reliability and yield. Hardware-based fault localization is challenged by increases in chip complexity as well as additional intercon-nection levels and the limitations on the spatial resolution of imaging technology [1]. The increase in difficulty and cost of performing hardware physical failure analysis is likely to move it into a sampling/verification role. These trends continue to increase the importance of developing alternative software-based fault localization procedures. Several " software-based " diagnostic methods have been proposed based on I DDQ measurements [2-9]. These methods can be classified as static, quasi-static and dynamic diagnostic test paradigms. For static, the diagnostic test set and test response are precomputed and stored in a fault dictionary. The quasi-static paradigm, the test set is pre-computed but the fault dictionary is eliminated. Instead, the test response is computed dynamically. Under the dynamic paradigm, both the diagnostic test set and response are computed dynamically during response analysis. The method that we propose in this work is a new approach to diagnosis and cannot be classified under these paradigms. It is complementary to these strategies and can be used in combination with them as a means of further improving diagnostic resolution. Moreover, QSA is more robust to the detrimental effects of increasing background leakage currents than these methods. This is true because the total (chip-wide) leakage current distributes across the multiple supply ports of the chip, and is reduced in magnitude in each of the supply port measurements. In previous works, we developed statistical defect detection and localization …
Social factors of depression among Cuban and Indochinese American adolescents

ABSTRACT This study used data from the first wave of the Children of Immigrants Longitudinal Study (CILS) [Portes, A. , & Rumbaut, R. G. (2008). Children of immigrants longitudinal study (CILS). Ann Arbor, MI: Inter-university Consortium for Political and Social Research] to examine cross-cultural differences and similarities in risk and protective factors of depression in a sample of 1827 Cuban and Indochinese adolescents aged from 13 to 16 years old: 1197 Cubans and 630 Indochinese. The results revealed that discrimination, poor family economic situation, sex, and age were risk factors of depression. English language speaking, parental love, parental attention, and living with both parents were protective factors against depression. There was a significant interaction association between sex and ethnic groups with depression and a significant interaction association between age and ethnic groups with depression. The results relating to cross-cultural differences and similarities in risk and protective factors of depression between ethnic immigrant adolescents are discussed, and recommendations for school counsellors, social workers, and mental health service providers are highlighted.
Practical Aspects of Imperative Program Verification in Theorema Presented at 5 th International Workshop on Symbolic and Numeric Algorithms for Scientific Computing

Approaching the problem of imperative program verification from a practical point of view has certain implications concerning: the style of specifications, the programming language which is used, the help provided to the user for finding appropriate loop invariants, the theoretical frame used for formal verification, the language used for expressing generated verification theorems as well as the database of necessary mathematical knowledge, and finally the proving power, style and language. The Theorema system (www. theorema.org) has certain capabilities which make it appropriate for such a practical approach. Our approach to imperative program verification in Theorema is based on Hoare– Logic and the Weakest Precondition Strategy. In this paper we present some practical aspect of our work, as well as a novel method for verification of programs that contain loops, namely a method based on recurrence equation solvers for generating the necessary loop invariants and termination terms automatically. We have tested our system with numerous examples, some of these example are presented at the end of the paper.
Visualizing and Animating Search Operations on Quadtrees on the Worldwide Web

A set of spatial index JAVATM applets is described that enable users on the worldwide web to experiment with a number of variants of the quadtree spatial data structure for different spatial data types, and, most importantly, enable them to see in an animated manner how a number of basic search operations are executed for them. The spatial data types are points, line segments, and rectangles. The search operations are finding nearest neighbors from an object of arbitrary type and shape, and retrieving all objects that overlap an object of arbitrary type and shape or are within a given distance of an object of arbitrary type and shape. The nearest neighbor and within queries retrieve their results in the order of their distance from the given query object. The representations and algorithms are visualized and animated in a consistent manner using the same primitives so that the differences between the effects of the representations can be easily understood. The applets can be found at http://www.cs. umd.edu/~hjs/quadtree/index.html.
Gauging of Flat Groups in Four Dimensional Supergravity

We show that N = 8 spontaneously broken supergravity in four dimensions obtained by Scherk-Schwarz generalized dimensional reduction can be obtained from a pure four dimensional perspective by gauging a suitable electric subgroup of E7,7. Owing to the fact that there are non isomorphic choices of maximal electric subgroups of the U-duality group their gaugings give rise to inequivalent theories. This in particular shows that the Scherk-Schwarz gaugings do not fall in previous classifications of possible gauged N = 8 supergravities. Gauging of flat groups appear in many examples of string compactifications in presence of brane fluxes.
Distributed Dense Numerical Linear Algebra Algorithms on Massively Parallel Architectures: DPLASMA

We present DPLASMA, a new project related to PLASMA, that operates in the distributed memory regime. It uses a new generic distributed Direct Acyclic Graph engine for high performance computing (DAGuE). Our work also takes advantage of some of the features of DAGuE, such as DAG representation that is independent of problem-size, overlapping of communication and computation, task prioritization, architecture-aware scheduling and management of micro-tasks on distributed architectures that feature heterogeneous many-core nodes. The originality of this engine is that it is capable of translating a sequential nested-loop code into a concise and synthetic format which it can be interpret and then execute in a distributed environment. We consider three common dense linear algebra algorithms, namely: Cholesky, LU and QR factorizations, to investigate their data driven expression and execution in a distributed system. We demonstrate from our preliminary results that our DAG-based approach has the potential to bridge the gap between the peak and the achieved performance that is characteristic in the stateof-the-art distributed numerical softwares on current and emerging architectures.
Asymptotic tail properties of the distributions in the class of dispersion models

The class of dispersion models introduced by J{\o}rgensen (1997b) covers many known distributions such as the normal, Student t, gamma, inverse Gaussian, hyperbola, von-Mises, among others. We study the small dispersion asymptotic (J{\o}rgensen, 1987b) behavior of the probability density functions of dispersion models which satisfy the uniformly convergent saddlepoint approximation. Our results extend those obtained by Finner et al. (2008).
Causally ordering broadcast protocol

The distributed applications require group communications among multiple entities. In the group communication, it is important to discuss in what order each entity in the group can receive data units. In order to realize fault-tolerant systems, the same events have to occur in the same order in each entity. The ordering among the events is known as a causal order. This paper presents a reliable causally ordering broadcast (CO) protocol which provides the same causal ordering of data units for all the entities in the group. In the CO protocol, the data units received are causally ordered by using the sequence numbers of the data units. The CO protocol is based on the fully distributed control scheme, i.e. no master controller, and uses high-speed networks where each entity may fail to receive data units due to the buffer overrun. Furthermore, the CO protocol provides asynchronous data transmission for multiple entities in the group. <<ETX>>
The Nature and Psychological Impact of Child/Adolescent Attachment to Dogs Compared with Other Companion Animals

Building on a study examining children’s knowledge and care of companion animals, this paper examines emotional attachment to dogs. It uses a large-scale dataset on children’s health and well-being (n = 6,700) to explore the connection between attachment to dogs, compared with other companion animals, and a range of well-being indicators. Findings reveal stronger attachments to dogs that are linked with well-being. Some associations are also evident for children reporting a strong bond with small mammals. A mixed pattern of results is evident for cats, and no associations were apparent for those with fish, reptiles, or amphibians. Relationships with dogs appear distinctive; children’s sense of emotional reciprocity and shared enjoyment of play act as possible mechanisms by which attachment translates into benefits. Emotional connections to all types of animals investigated in this study weaken with age. This may be due to the changing nature of attachment as children move through adolescence.
Integrating Communication Skills and Planning Techniques

Practitioners have long stressed the need to teach professional commumcations skills to planning students. This paper describes ten years of experience in teaching a course in which communications skills and techniques of gathering and analyzing information are taught concurrently while investigating a problem of importance in the community. The course involves an ongoing collaboration, a "marriage of convenience," between an academic and a planner, casting city/county planning staff as clients for students This has proven useful for pedagogy and has had some positive impact on the community.
Deep Habits, Price Rigidities and the Consumption Response to Government Spending

This paper presents the novel implications of introducing price rigidities into a model of good-specific habit formation, for the response of private consumption following a positive government spending shock. With 'deep' habits in demand, the price elasticity of demand rises after the fiscal expansion and it is optimal for the firm to lower the mark-up while increasing production. This in turn raises the demand for labour and the real wage rises. Consequently, agents raise consumption at the expense of leisure and overcome the negative wealth effect of the fiscal shock. We show that increasing price stickiness in a model with deep habits hinders the crowding-in of consumption. If the degree of price stickiness is high enough, consumption is crowded out by government spending. These dynamics are in stark contrast to those in traditional models where price rigidities are known to weaken the crowding-out of consumption.
How Do Engineering Students' Achievement Goals Relate to their Reflection Behaviors and Learning Outcomes?

This research study investigated the relationship between achievement goals, reflection behaviors, and learning outcomes of industrial engineering students. The study used Achievement Goal Questionnaire-Revised (AGQ-R) scale to measure engineering students’ achievement goals. Six response variables for each student were included: the reflection quality score, total number of reflections, two exam scores, final exam score, and the total learning outcome based on course grading policy criteria. Both parametric bivariate regression analysis and regression analysis after transformation based on beta distribution were conducted. The results indicated that mastery approach had a significant effect on the total number of reflections, final exam, and the total learning outcome. Performance approach showed significances on the final exam and the total learning outcome. Mastery avoidance showed significances on the total number of reflections, exam2, and the total learning outcome. Performance avoidance had a significant effect on exam 2, final exam, and the total learning outcome. The findings of this study confirm previous research findings in other domains, which suggest that there is a positive relation between performance approach and learning outcome, and between mastery approach and students’ learning style and strategies.