Miracle-dz/UniFAR-FTUs huggingface dataset:
Incomplete information and the idiosyncratic foundations of aggregate volatility

This thesis considers two interrelated themes: the emergence of aggregate volatility from idiosyncratic shocks and optimisation under incomplete information when, for reasons of strategic complementarity, agents are interested in both simple and weighted averages of their competitors' actions. I first develop a model of Bayesian social learning over a network. Unlike earlier literature that abandons one of the assumptions that agents (a) act repeatedly; (b) are rational; and (c) face strategic complementarities, I obtain tractability for arbitrarily large networks by also assuming that agents do not know the full structure of the network, but do know its link distribution. An AR(1) process for the underlying state induces an ARMA(1,1) process for the hierarchy of expectations, with current and lagged weighted averages of agents' idiosyncratic shocks entering at an aggregate level. For sufficiently irregular networks, these shocks do not wash out, thus causing persistent aggregate effects. I next apply this to firms' price-setting problem, demonstrating that even when firms possess complete price exibility, network learning induces considerable persistence in aggregate variables following monetary and real shocks and that network shocks plausibly represent a source of aggregate economic volatility. Finally, I explore price setting under monopolistic competition when facing TransLog preferences. I solve explicitly for a firm's best-response pricing rule under full information and show that in partial equilibrium under incomplete information, larer firms will focus on their marginal costs while smaller firms will place more weight on changes in consumer preferences and competitors' prices. In general equilibrium, I estimate the effect of two distinct sources of real rigidity that emerge from TransLog preferences: the well-known curvature in demand and the dramatic increase in complexity of firms' signal-extraction problems. With non-uniform preferences, the model represents another channel through which idiosyncratic shocks can cause aggregate volatility.
Face-tree: A compact discrete 3D face shape representation

Recently, there has been an increasing interest in using 3D facial images as biometric modality. To that end, a proper representation of the 3D facial shape that would allow effective face matching is a major requirement. In this paper, we propose a novel 3D facial representation, dubbed, the face-tree. We describe the extraction process of this representation from 3D triangular mesh face model, then we showcase its distinguished properties which include, ordered structure, compactness, richness, efficiency, and capacity for partial deployment. We discuss the potential of the face-tree representation for 3D face recognition, through experiments made with two different database sets.
Efficient RAS support for 3 D Die-Stacked DRAM

Die-stacked DRAM is one of the most promising memory architectures to satisfy high bandwidth and low latency needs of many computing systems. But, with technology scaling, all memory devices are expected to experience significant increase in single and multi-bit errors. 3D die-stacked DRAM will have the added burden of protecting against single through-siliconvia (TSV) failures, which translate into multiple bit errors in a single cache line, as well multiple TSV failures that may lead to an entire channel failure. To exploit wide I/O capability of 3D DRAM, large chunks of data are laid out contiguously in a single channel and an entire cache line is sourced from a single channel. Conventional approaches such as ECC DIMM and chipkill-correct are inefficient since they spread data across multiple DRAM layers to protect against failures and also place restrictions on the number of memory layers that must be protected together. This paper adapts several well known error detection and correction techniques while taking into account 3D DRAM’s unique organization. First, we decouple error correction from detection and perform error detection using a novel two level 8-bit interleaved parity to handle diestacked DRAM-specific failure modes such as TSV failures. We then adapt RAID5-like parity, a technique developed for hard disks which also layout large chunks of data contiguously, for recovering from a wide range of errors from single-bit errors to channel-level failures without the need to splice data across multiple layers. As further optimizations, a two-step decoupled error correction code update process is used to improve write speed, and an error detection code cache is used for improving read/write performance without compromising reliability. The proposed approaches effectively reduce the FIT rate with 15.7% area and almost negligible performance overhead.
IBEX — A tele-operation and training device for walking excavators

This paper describes a novel tele-operation and training device for walking excavators based on a compact 3DOF motion platform. Thanks to an innovative setup optimized for high mobility, with two lever arms for differential roll and pitch actuation as well as a continuous rotation mechanism for yaw, the movement of the remote walking excavator can be accurately replicated in any situation. For realistic yet comfortable visual feedback, three foldable screens provide a view around the unmanned excavator. With this augmented feedback, an operator can work as if he was sitting in the actual machine. The platform is successfully tested by experienced and unexperienced users. To this end, a realistic simulation using CM Labs vortex environment is implemented and a series of scenarios are tested. As such, ibex additionally serves as ideal training device for walking excavator pilots.
Human and cultural capital complementarities and externalities in economic growth

The aim of this paper is to investigate the role of culture, viewed according to Throsby’s definition of cultural capital (that is, an asset of tangible and intangible cultural expressions), in fostering economic growth. Recent literature in the field of cultural economics highlights a possible inversion of the usual causality relation, and culture can be seen as one of the engine of economic wealth. In this article we analyze one possible channel through which it may occur: human capital investment. Using a two-sectors endogenous growth model, the relation between cultural and human capital is deeply investigated.
The Role of Inflation Differentials in Regional Adjustment: Evidence from the United States

Within a monetary union, regional inflation differentials lead to a competition between the real interest rate and wealth channels on the one hand and the real exchange rate channel on the other hand in the transmission of regional shocks. This may have implications for the length and vehemence of regional business cycles. This paper tries to quantify how these forces work against each other using regional data for the United States. Our estimates indicate that, following an increase in the regional inflation rate, in the short run the pro-cyclical effect through the real interest rate and wealth channels is strongest. After a period of about 3-4 years the cumulative worsening of the competitive position asserts its influence. Regional cycles in the housing market have a clear pro-cyclical effect and are, on their part, affected by regional real interest rates and real growth.
Building Vietnamese Topic Modeling Based on Core Terms and Applying in Text Classification

In the languages, the occur of words are indicated about meaning of contents in text. Generative models for text, such as the topic model, have the potential to make important contributions to the statistical analysis of large document collections, and the development of a deeper understanding of human language learning and processing. In this paper, we proposed a novel method for building Vietnamese topic model based on core terms and conditional probability. With this approach, we reduced cost of time for building corpus. After that, we perform with Vietnamese text classification and the experimental show that, this corpus will help text classification system really effectively than traditional methods, higher accuracy and reduced complex data processing.
Converted Lattice-Based Chinese Spontaneous Speech Retrieval Based on Mutual Information Confidence Measure

Nowadays rapid and accurate speech retrieval techniques based on semantics are desired for the overwhelming amounts of speech data. In this paper we mainly study a converted lattice-based approach for Chinese spontaneous speech retrieval. A new confidence measure method is proposed based on context mutual information. In our knowledge, it is firstly used in a lattice construction for speech indexing. The method can take full advantage of the mutual information between words in order to describe the language model more exactly. Our experiment results show that the proposed method in this paper outperforms both posterior probability based method and N-best based method. And our best system achieves a FOM of 81.2% on a task of spontaneous Chinese speech retrieval.
Surgical versus low-dose progestin treatment for endometriosis-associated severe deep dyspareunia II: effect on sexual functioning, psychological status and health-related quality of life.

STUDY QUESTION Does surgical and low-dose progestin treatment differentially affect endometriosis-associated severe deep dyspareunia in terms of sexual functioning, psychological status and health-related quality of life? SUMMARY ANSWER Surgery and progestin treatment achieved essentially similar benefits at 12-month follow-up, but with different temporal trends. WHAT IS ALREADY KNOWN Conservative surgery and hormonal therapies have been used independently for endometriosis-associated deep dyspareunia with inconsistent results. STUDY DESIGN, SIZE, DURATION Patient preference, parallel cohort study with 12-month follow-up. The effect of conservative surgery at laparoscopy versus treatment with a low dose of norethisterone acetate per os (2.5 mg/day) in women with persistent/recurrent severe deep dyspareunia after first-line surgery was compared. PARTICIPANTS/MATERIALS AND SETTING, METHODS A total of 51 patients chose repeat surgery and 103 progestin treatment. Variations in sexual function, psychological well-being and quality of life were measured by means of the Female Sexual Function Index (FSFI), the Hospital Anxiety and Depression Scale (HADS) and the Endometriosis Health Profile-30 (EHP-30). MAIN RESULTS AND THE ROLE OF CHANCE Four women in the surgery group and 21 women in the progestin group withdrew from the study for various reasons. Total FSFI scores, anxiety and depression scores and EHP-30 scores improved immediately after surgery, but worsened with time, whereas the effect during progestin use increased more gradually, but progressively, without overall significant between-group differences at 12-month follow-up. A tendency was observed towards a slightly better total FSFI score after surgery at the end of the study period. LIMITATIONS, REASONS FOR CAUTION Treatments were not randomly allocated, and distribution of participants as well as of dropouts between study arms was unbalanced. However, the possibility of choosing the treatment allowed assessment of the maximum potential effect size of the interventions. WIDER IMPLICATIONS OF THE FINDINGS Both surgery and medical treatment with progestins are valuable options for improving the detrimental impact of endometriosis-associated dyspareunia on sexual functioning and quality of life. Women should be aware of the pros and cons of both options to decide which one best suits their needs. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by a research grant from the University of Milan School of Medicine (PUR number 2009-ATE-0570). None of the authors have a conflict of interest.
The effects of service recovery on consumer satisfaction: a comparison between complainants and non‐complainants

Purpose – The primary objective of this study is to investigate the effects of service recovery on customer satisfaction. Specifically, it examines the perception of “justice” in service recovery and how it affects the level of satisfaction and behavioral outcomes. In addition, the study also explores whether the “recovery paradox” exists.Design/methodology/approach – Data were collected through a survey using a structured questionnaire. The 428 respondents were analyzed according to whether they did or did not make a complaint to the service providers.Findings – The findings showed that the complainants' level of satisfaction with service recovery was significantly affected by perceived justice. The behavioral outcomes of the complainants in terms of trust, word‐of‐mouth (WOM) and loyalty were also found to be affected by their satisfaction with the service recovery. T‐tests confirmed that the levels of trust, WOM and loyalty were significantly higher for those respondents who were satisfied with the ser.
Human activity recognition from accelerometer data using Convolutional Neural Network

We propose a one-dimensional (1D) Convolutional Neural Network (CNN)-based method for recognizing human activity using triaxial accelerometer data collected from users' smartphones. The three human activity data, walking, running, and staying still, are gathered using smartphone accelerometer sensor. The x, y, and z acceleration data are transformed into a vector magnitude data and used as the input for learning the 1D CNN. The ternary activity recognition performance of our 1D CNN-based method which showed 92.71% accuracy outperformed the baseline random forest approach of 89.10%.
Method for Collecting Air-Water Interface Microbes Suitable for Subsequent Microscopy and Molecular Analysis in both Research and Teaching Laboratories

ABSTRACT A method has been developed for collecting air-water interface (AWI) microbes and biofilms that enables analysis of the same sample with various combinations of bright-field and fluorescence light microscopy optics, scanning and transmission electron microscopy (TEM), and atomic force microscopy. The identical sample is then subjected to molecular analysis. The sampling tool consists of a microscope slide supporting appropriate substrates, TEM grids, for example, that are removable for the desired protocols. The slide with its substrates is then coated with a collodion polymer membrane to which in situ AWI organisms adhere upon contact. This sampling device effectively separates the captured AWI bacterial community from the bulk water community immediately subtending. Preliminary data indicate that the AWI community differs significantly from the water column community from the same sample site when both are evaluated with microscopy and with 16S ribosomal DNA sequence-based culture-independent comparisons. This microbe collection method can be used at many levels in research and teaching.
Extracting Time Expressions from Clinical Text

Temporal information extraction is important to understanding text in clinical documents. Temporal expression extraction provides explicit grounding of events in a narrative. In this work we provide a direct comparison of various ways of extracting temporal expressions, using similar features as much as possible to explore the advantages of the methods themselves. We evaluate these systems on both the THYME (Temporal History of Your Medical Events) and i2b2 Challenge corpora. Our main findings are that simple sequence taggers outperform conditional random fields on the new data, and higher-level syntactic features do not seem to improve performance.
The Spectacle of U.S. Senate Campaigns

List of Figures ix List of Tables xi Acknowledgments xiii PART ONE: UNDERSTANDING AND MEASURING CAMPAIGNS 1 One The Nature of Political Campaigns 3 Two Measuring the Content and Consequences of Political Campaigns 30 PART TWO: THE CAMPAIGN STRATEGIES OF CANDIDATES 41 Three In Order to Win: An Examination of Campaign Strategies 43 Four Attack Politics: Understanding the Determinants of Negative Campaigning 74 PART THREE: THE NEWS MEDIA'S COVERAGE OF CAMPAIGNS 99 Five Deciding What Is News: The Media's Coverage of Senate Campaigns 101 Six The Struggle for Control over the News Media's Agenda: How Candidates Influence the Content and Tone of News Coverage 133 PART FOUR: CITIZENS' REACTIONS TO CAMPAIGNS 161 Seven The Dynamics of Competition: The Impact of the Candidates and the News Media 163 Eight Citizens' Knowledge about U.S. Senate Campaigns 174 Nine How Voters Make Decisions in U.S. Senate Campaigns 206 PART FIVE: CONCLUSIONS 233 Ten Conclusions and Implications 235 Appendixes 245 A. Interview Schedule for Successful Incumbents 247 B. Political Advertising Code Sheet 251 C. Sample of Newspapers 255 D. Newspaper Content Analysis Code Sheet 257 References 263 Index 275
Feature Ranking in Dynamic Texture Clustering

The dynamic texture clustering over space and time, which considers a video as a sample from a linear dynamical system, has recently received great attention. While there exist many algorithms for time-varying characteristics and phenomena clustering, an important and challenging issue arising from these studies concerns is that how to compare the importance of each feature, and which features of the data should be used for time-varying clustering. In view of the aforementioned observations, a new unsupervised feature ranking for dynamic texture clustering is proposed in this paper. Different from previous works, where the selection criteria are often used to identify relevant features, our method has an ability to score relevant features, and allow us to evaluate the importance of each feature. Also, it is intuitively appealing, avoiding any combinatorial search. Numerical experiments on various time-varying characteristics and phenomena demonstrate the accuracy and effectiveness of the proposed method.
Improving our understanding of the in vivo modelling of psychotic disorders: A protocol for a systematic review and meta‐analysis

Psychosis represents a set of symptoms against which current available treatments are not universally effective and are often accompanied by adverse side effects. Clinical management could potentially be improved with a greater understanding of the underlying biology and subsequently with the introduction of novel treatments. Since many clinical drug candidates are identified through in vivo modelling, a deeper understanding of the pre‐clinical field, might help us understand why translation of results from animal models to inform mental health clinical practice has so far been weak. We set out to give a shallow, but broad unbiased overview of experiments looking at the in vivo modelling of psychotic disorders using a systematic review and meta‐analysis. This protocol describes the exact methodology we propose to follow in order to quantitatively review both studies characterizing a model and those experiments that investigate the effects of novel therapeutic options. We are interested in assessing the prevalence of the reporting of measures to reduce risk of bias, and the internal and external validity of the animal models and outcome measures used to validate these models. This generation of strong empirical evidence has the potential to identify areas for improvement, make suggestions for future research avenues, and ultimately inform what we think we know to improve the current attrition rate between bench and bedside in psychosis research. A review like this will also support the reduction of animal numbers used in research and the refinement of experiments to maximize their value in informing the field.
Regulatory Mode Profiles and the Organization of the Flow of Time

Background: Individuals strive after goals through regulatory modes of assessment and locomotion. The independent inter-relationship between these two modes implies four profiles: assessor (i.e. high in assessment/low in locomotion), low regulator (i.e. low assessment/low locomotion), high regulator (i.e. high assessment/high locomotion), and locomotor (i.e. low assessment/high locomotion). We investigated the way individuals with different profiles organize the flow of time (i.e. past, present, and future) in order to explore how the outlook on time might be associated to changes in regulatory mode. Method: High school pupils and university Students (N=522) answered to the Self-regulatory Mode Questionnaire and Zimbardo Time Perspective Inventory. Results: The regulatory mode profiles had a significant effect on the five time perspective dimensions (F(15, 1548)=14.66, p<0.001, Pillias´Trace=0.37). Comparisons between individuals who differed in one regulatory mode but where similar in the other suggested that high levels of past positive and low levels of past negative were associated to low assessment when locomotion was high and to high locomotion when assessment was low. High levels in the future time perspective dimension were related to high levels of locomotion when assessment was high, while low levels of past negative were related to low assessment when locomotion was low. Conclusion: The results illustrate the complexity of a dynamic system of regulation in which the same antecedents can lead to different outcomes (i.e. multi-finality) and different antecedents can lead to the same outcome (i.e. equifinality). Although only theoretical, this gives an idea of how some leaps might be abrupt as a quantum leap (i.e. extremely different profiles), while others might be serial (i.e. from one profile to another profile that shares the same level in one regulatory mode but that differs in the other).
Influence of Assessment for Learning Professional Development in Rural Georgia Public Schools.

Marianne W. Cole. INFLUENCE OF ASSESSMENT FOR LEARNING PROFESSIONAL DEVELOPMENT IN RURAL GEORGIA PUBLIC SCHOOLS. (Under the direction of Dr. Jeffery Crawford) School of Education, August, 2010. This study investigated the effect of two models of professional development concerning Assessment for Learning on teacher perception of the effectiveness of Assessment for Learning strategies and student achievement as measured by standardized Georgia End of Course Tests. The study hypothesized that a positive relationship exists between teacher perception of the benefit of Assessment for Learning strategies and increased student achievement as measured by student performance on standardized Georgia End of Course Tests. The study hypothesized that a positive relationship exists between teacher participation in Assessment for Learning professional development and teacher positive perception of the benefit of Assessment for Learning strategies. The sample consisted of 174 teachers and 2,787 students in core content courses in grades 9-12 in rural Georgia schools. Teacher participants received training on Assessment for Learning in either a theory-based or application-based professional development class or were part of the control group not participating in Assessment for Learning professional development. Teacher participants completed a detailed survey to gather assessment perception data. Students participated in instruction and completed Georgia End of Course Tests (EOCT), standardized achievement assessments, to gather performance data. Multiple ANOVA were used to statistically analyze the data and a relationship was found between teacher participation in formative-assessment professional development and student performance on standardized Georgia End of Course Tests.