Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-sided Learning in New Keynesian Models : Dynamics , Convergence and the Value of Information

This paper investigates the role of two-sided learning in a New Keynesian framework populated by private agents and a central bank that have asymmetric imperfect knowledge about the true data generating process. We assume that all agents employ the data they observe (which can be di¤erent for di¤erent sets of agents) to form beliefs about the aspects of the true model of the economy that they dont know, use these beliefs to decide on actions, and revise them through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of the model and the optimal policy recommendations along this pattern. We nd that two-sided learning can generate large departures of beliefs and policy decisions from their rational expectations equilibrium values, and can alter the behavior of the variables in the model in a signi cant way.
Modelling Worker Residence Distribution in the Los Angeles Region Shun ~

is one of ten regional units mandated by Congress and established in Pail 1988 to support research, education, and training in surface transportation. The UC Center serves federal Region IX and is supported by matching grants from the U.S. Department of Transportation, the California Department of Transportation (Caltrans), and the University. Based on the Berkeley Campus, UCTC draws upon existing capabilities and resources of the Institutes of Transportation Studies at Berkeley, Davis, Irvine, and Los Angeles; the Institute of Urban and Regional Development at Berkeley; and sever~ academic departments at the Berkeley, Davis, Irvine, and Los Angeles campuses. Faculty and students on other University of California campuses may participate in Center activities. Researchers at other universities within the region also have opportunities to collaborate with UC faculty on selected studies° UCTC's educational and research programs are focused on strategic planning for improving metropolitan accessibility, with emphasis on the special conditions in Region IX. Particular attention is directed to strategies for using transportation as an instrument of economic development, while also accommodating to the region's persistent expansion and while maintaining and enhanco ing the quality of life there. The Center distributes reports on its research in work/ng papers, monographs, and in reprints of published articles. It also publishes Access, a magazine presenting summaries of selected studies. For a list of publications in print, write to the address below. The contents of this report reflect the views of the author who is responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the of-tidal views or policies of the State of California or the U.S. Department of Transportation. This report does not constitute a standard, specification, or regulation. Summary This paper examines the spatial pattern of worker residences with three different density functions: monocentric, polycentric, and dispersive. Analysis of the 1980 journey-to-work census data for the Los Angeles region reveals that the polycentric density function statistically explains the actual distribution better than the monocentric density function, but the dispersive density function fits best. These findings confirm a polycentfic spatial pattern, and also imply that overall accessibility to employment opportunities is the primary determinant of residential location choices. and two anonymous referees for their valuable suggestions and comments. Remaining errors and omissions are the responsibility of the author.
An advanced contrast enhancement using partially overlapped sub-block histogram equalization

In this paper, an advanced histogram equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global histogram equalization is simple and fast, but its contrast enhancement power is relatively low. Local histogram equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block histogram equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of local histogram equalization while still achieving high contrast.
Distributed hybrid agent-based discrete event emergency medical services simulation

This paper presents the development of a distributed hybrid agent-based (ABS) discrete event simulation (DES) model within the context of emergency medical services (EMS). The existing simulation models of EMS either are considered as a single model or several standalone models that represent different system elements in isolation. The aim of this research is to demonstrate the feasibility of using distributed simulation technology to implement hybrid EMS simulation. This would provide opportunities to study holistically integrated improvement scenarios for emergency medical services and crisis management systems. The case study is based on the London EMS and consists of an ambulance service ABS model and several accident and emergency departments DES models. Both the ABS and the DES models were developed in Repast Simphony toolkit using poRTIco RTI software to achieve communication between them. The results prove that we can use distributed simulation to successfully represent the real system.
Design and evaluation of a multi-touch interaction language for approach controllers

Since smartphones and tablets were introduced into consumer electronics, multi-touch technology has been increasingly used for professional purposes. The aim of our research was to determine whether approach controllers could also use gesture-based natural user interfaces for their work. We built a prototype that was evaluated against a comparable mouse interaction concept. In our preliminary study, five test persons were asked to guide air traffic in a realistic scenario with both the multi-touch and mouse mock-up. Usability and workload were assessed. The results revealed higher usability scores for the multi-touch mock-up, whereas the workload evaluation showed no clear trend for either interaction concept.
Data Compression Using Adaptive Coding and Partial String Matching

The recently developed technique of arithmetic coding, in conjunction with a Markov model of the source, is a powerful method of data compression in situations where a linear treatment is inappropriate. Adaptive coding allows the model to be constructed dynamically by both encoder and decoder during the course of the transmission, and has been shown to incur a smaller coding overhead than explicit transmission of the model's statistics. But there is a basic conflict between the desire to use high-order Markov models and the need to have them formed quickly as the initial part of the message is sent. This paper describes how the conflict can be resolved with partial string matching, and reports experimental results which show that mixed-case English text can be coded in as little as 2.2 bits/ character with no prior knowledge of the source.
Love in the Time of HIV: Testing as a Signal of Risk

The HIV epidemic in southern Africa has important consequences for economic development. The epidemic could be stopped by a universal test and treat policy, as antiretroviral drugs block the spread of the virus. However, demand for HIV testing and treatment are surprisingly low. This paper develops a model in which the decision to seek an HIV test is a signal of infection, and those who seek a test are subject to statistical discrimination from potential sexual partners. We evaluate an information experiment designed to test the theory, and find evidence that this form of discrimination is a significant barrier to HIV testing. In particular, we provide information at the community level on the public benefit of antiretroviral therapy: because the drugs prevent HIV transmission, a person who is tested and treated for HIV is a relatively safe sexual partner. This information reduces discrimination and increases HIV testing, with the strongest effects in communities where the new information becomes common knowledge. The results demonstrate that discrimination towards HIV positive individuals can be due to rational behavior by a misinformed public, and that providing new information can be an effective way to mitigate its effects. JEL Codes: C70, D82, D83, I12, I15, I18 ∗laura.derksen@utoronto.ca Laura Derksen is grateful to her supervisor, Oriana Bandiera and her advisor, Greg Fischer, for their continued guidance and encouragement. This paper also benefited from discussions with Marcella Alsan, Nava Ashraf, Victoria Baranov, Tim Besley, Patrick Blanchenay, Gharad Bryan, Jon De Quidt, Erika Deserranno, Kate Dovel, Thiemo Fetzer, Maitreesh Ghatak, Markus Goldstein, Willa Friedman, Marcos Vera Hernandez, Jason Kerwin, Alan Manning, Sam Marden, Steve Pischke, Munir Squires, Balazs Szentes, Susan Watkins, and Kelly Zhang, as well as seminar and conference participants at CSAE 2016, Dartmouth, IAS 2015, LSE, Mathematica, Melbourne, Ottawa, Oxford, PacDev 2016, PAA 2016, RES 2016, Sussex,
A Seamless Handoff With Multiple Radios in IEEE 802.11 WLANs

It is obvious that a seamless handoff should be pursued for better service. For this reason, we design a novel and feasible 802.11 handoff scheme for 802.11 wireless local area networks (WLANs). In the proposed handoff scheme, the 802.11 access points (APs) have multiple radios. One of the multiple radios is exclusively reserved for scanning purposes. It certainly helps the 802.11 mobile stations (STAs) to easily search neighboring APs. Moreover, the reserved exclusive channel is available for data frame exchanges. Consequently, STAs can be serviced with minimized data frame losses while they are performing the proposed handoff. For practical observations, we implement the proposed handoff scheme. Then, we evaluate handoff performances by comparing the packet losses between the proposed handoff scheme and the existing handoff schemes. Based on the evaluation, we have built analytical models to estimate overall packet losses while an STA moves from an AP to another AP in an indoor environment. The analytical results show that the proposed handoff significantly reduces packet losses compared with existing 802.11 handoff schemes.
The Glypican 3-Hosted Murine Mir717 Gene: Sequence Conservation, Seed Region Polymorphisms and Putative Targets

Mir717 (mmu-mir-717) was first reported in mouse and resides in the intron 3 of glypican 3 (Gpc3) gene. Our present study revealed that this microRNA (miRNA) gene is conserved among 26 mammalian species and harbors polymorphic sites within the mature seed region in mice. Our finding represents a rare four layer genomic overlap consisting of growth associated quantitative trait locus (QTL), body mass associated Gpc3 gene, highly conserved miRNA gene and mature miRNA seed single nucleotide polymorphism (SNP) identified in the lean mouse strain 129/Sv. Additionally, genes potentially targeted by Mir717 include 91 genes associated with obesity and related phenotypes in mammals. Our analysis provides a basis for further experiments to causally connect the identified SNP and Mir717 gene itself to obesity regulation. Furthermore, our bioinformatics analysis now enables functional annotation of Mir717 orthologs in other species, thus determining the effect of its target genes on fat-related traits.
Crowdsourcing Based Mobile Location Recognition with Richer Fingerprints from Smartphone Sensors

With the rapid advancements of mobile computing, mobile location recognition is becoming an important and useful service, which recognizes the logical locations of places/scenes that users are interested in, instead of physical coordinates. Most of the existing mobile location recognition systems utilize the image as visual fingerprint of a place, and need to construct a large-scale visual fingerprint database in advance. However, collecting visual fingerprints is a labor-intensive and time-consuming procedure. In order to address this problem, we propose a novel crowdsourcing-based framework, and leverage a variety of sensors embedded in smartphones to collect richer location fingerprints for exploring their positive effects. To achieve higher recognition accuracy, we propose an object-centric fingerprint searching which can sufficiently take advantage of smartphone sensors and determine more accurate searching space than the traditional user-centric method. We build a crowdsourcing-based database with richer fingerprints and implement a location recognition system, called CrowdLR. Extensive experiments verify that our object-centric method can achieve promising results maintaining around 10% precision higher than the user-centric method.
Running Speed Alters the Frequency of Hippocampal Gamma Oscillations

Successful spatial navigation is thought to employ a combination of at least two strategies: the following of landmark cues and path integration. Path integration requires that the brain use the speed and direction of movement in a meaningful way to continuously compute the position of the animal. Indeed, the running speed of rats modulates both the firing rate of neurons and the spectral properties of low frequency, theta oscillations seen in the local field potential (LFP) of the hippocampus, a region important for spatial memory formation. Higher frequency, gamma-band LFP oscillations are usually associated with decision-making, increased attention, and improved reaction times. Here, we show that increased running speed is accompanied by large, systematic increases in the frequency of hippocampal CA1 network oscillations spanning the entire gamma range (30–120 Hz) and beyond. These speed-dependent changes in frequency are seen on both linear tracks and two-dimensional platforms, and are thus independent of the behavioral task. Synchrony between anatomically distant CA1 regions also shifts to higher gamma frequencies as running speed increases. The changes in frequency are strongly correlated with changes in the firing rates of individual interneurons, consistent with models of gamma generation. Our results suggest that as a rat runs faster, there are faster gamma frequency transitions between sequential place cell-assemblies. This may help to preserve the spatial specificity of place cells and spatial memories at vastly different running speeds.
Maximum likelihood estimation of signal amplitude and noise variance from MR data

In MRI, the raw data, which are acquired in spatial frequency space, are intrinsically complex valued and corrupted by Gaussian‐distributed noise. After applying an inverse Fourier transform, the data remain complex valued and Gaussian distributed. If the signal amplitude is to be estimated, one has two options. It can be estimated directly from the complex valued data set, or one can first perform a magnitude operation on this data set, which changes the distribution of the data from Gaussian to Rician, and estimate the signal amplitude from the obtained magnitude image. Similarly, the noise variance can be estimated from both the complex and magnitude data sets. This article addresses the question whether it is better to use complex valued data or magnitude data for the estimation of these parameters using the maximum likelihood method. As a performance criterion, the mean‐squared error (MSE) is used. Magn Reson Med 51:586–594, 2004. © 2004 Wiley‐Liss, Inc.
A high performance parallel computing system for imaging and graphics

UWGSP4 (University of Washington Graphics System Processor) consists of four parts: a parallel vector processor, a shared-memory system, an interconnection network, and a graphics subsystem. The parallel vector processor was provided mainly for imaging and general-purpose computing, whereas the main functions of the graphics subsystem are to generate realistic three-dimensional images and to draw the display screen. Among the four parts, the shared memory and the interconnection network were designed to fully support the parallel vector processor and graphics subsystem so as to yield high sustained performance. A discussion is presented of the architecture of UWGSP4, simulated performance figures for several imaging and graphics algorithms, and applications areas. <<ETX>>
Hybrid model for information filtering in location based social networks using text mining

The research aims to create an application that uses techniques from Machine Learning to extract and collate data geolocated - collected a Social Network, aiming to promote the Social Recommendation users. Existing research in the field of social recommendation deficiencies remain regarding the effectiveness of the filtered data. This paper presents a study and implementation using Text Mining techniques as a proposal for resolution of problems found in social recommendation and more effective results.
Understanding Deep Representations through Random Weights

We systematically study the deep representation of random weight CNN (convolutional neural network) using the DeCNN (deconvolutional neural network) architecture. We first fix the weights of an untrained CNN, and for each layer of its feature representation, we train a corresponding DeCNN to reconstruct the input image. As compared with the pre-trained CNN, the DeCNN trained on a random weight CNN can reconstruct images more quickly and accurately, no matter which type of random distribution for the CNN's weights. It reveals that every layer of the random CNN can retain photographically accurate information about the image. We then let the DeCNN be untrained, i.e. the overall CNN-DeCNN architecture uses only random weights. Strikingly, we can reconstruct all position information of the image for low layer representations but the colors change. For high layer representations, we can still capture the rough contours of the image. We also change the number of feature maps and the shape of the feature maps and gain more insight on the random function of the CNN-DeCNN structure. Our work reveals that the purely random CNN-DeCNN architecture substantially contributes to the geometric and photometric invariance due to the intrinsic symmetry and invertible structure, but it discards the colormetric information due to the random projection.
Characterization of Fibrin and Collagen Gels for Engineering Wound Healing Models

Hydrogels are used for 3D in vitro assays and tissue engineering and regeneration purposes. For a thorough interpretation of this technology, an integral biomechanical characterization of the materials is required. In this work, we characterize the mechanical and functional behavior of two specific hydrogels that play critical roles in wound healing, collagen and fibrin. A coherent and complementary characterization was performed using a generalized and standard composition of each hydrogel and a combination of techniques. Microstructural analysis was performed by scanning electron microscopy and confocal reflection imaging. Permeability was measured using a microfluidic-based experimental set-up, and mechanical responses were analyzed by rheology. We measured a pore size of 2.84 and 1.69 μm for collagen and fibrin, respectively. Correspondingly, the permeability of the gels was 1.00·10−12 and 5.73·10−13 m2. The shear modulus in the linear viscoelastic regime was 15 Pa for collagen and 300 Pa for fibrin. The gels exhibited strain-hardening behavior at ca. 10% and 50% strain for fibrin and collagen, respectively. This consistent biomechanical characterization provides a detailed and robust starting point for different 3D in vitro bioapplications, such as collagen and/or fibrin gels. These features may have major implications for 3D cellular behavior by inducing divergent microenvironmental cues.
Toward Unified Organization Theory : Perspectives on the State of Computational Modeling

Scholars engaged in the study of work group and organizational behavior are increasingly calling for the use of integrated methods in conducting research, including the wider adoption of computational models for generating and testing new theory. Our review of the state of modern computational modeling incorporating social structures reveals steady increases in the incorporation of dynamic, adaptive, and realistic behaviors of agents in network settings, yet exposes gaps that must be addressed in the next generation of organizational simulation systems. We compare 29 models according to more than two hundred evaluation criteria, ranging from simple representations of agent demographic and performance characteristics, to more richly defined instantiations of behavioral attributes, interaction with non-agent entities, model flexibility, communication channels, simulation types, knowledge, transactive memory, task complexity, and resource networks. Our survey assesses trends across the wide set of criteria, discusses practical applications, and proposes a research and development agenda that motivates advancement of computational science toward unification of organization theory.
Learning To Use Statistical Tests In Psychology

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Weight change and sickness absence--a prospective study among middle-aged employees.

BACKGROUND Obesity is associated with an increased risk of work disability, but studies concerning weight change are few. We examined the associations of weight change with subsequent sickness absence. METHODS Weight status data of 4164 (83% women) employees of the City of Helsinki were gathered from the Helsinki Health Study baseline survey in 2000-2002 and follow-up survey in 2007. Data were linked prospectively with the employer's sickness absence registers. Employees were categorized according to their baseline Body Mass Index (normal weight, overweight, obese) as well as weight change (weight gainer, weight loser, weight maintainer) between the two surveys. The association of weight change with sickness absence spells was analysed with Poisson regression. RESULTS Among women, those who maintained normal weight had the lowest risk for sickness absence. Weight loss, weight gain and stable obesity increased the risk for sickness absence spells of all lengths. Adjustments for covariates attenuated the association only slightly. Among men, the achieved results were mostly not statistically significant. CONCLUSIONS Preventing obesity and weight gain is important for employee well-being and work ability. Early support measures in occupational health care could benefit obese employees and those with weight gain to maintain work ability. The association between weight loss and sickness absence should be corroborated in further studies.