Miracle-dz/UniFAR-FTUs huggingface dataset:
Price Discovery without Trading: Evidence from the Nasdaq Preopening

This paper studies Nasdaq market makers' activities during the one-and-half hour pre-opening period. Price discovery during the pre-opening is conducted via price signaling as opposed to the auction used to open the NYSE or the continuous market used during trading. In the absence of trades, Nasdaq dealers use crossed and locked inside quotes to signal to other market makers which direction the price should move. Furthermore, we find evidence of price leadership among market makers that bears little resemblance to their IPO/SEO lead underwriter participation.
Positive, Neutral, and Negative Connotations Associated with Social Representation of 'Hearing Loss' and 'Hearing Aids'

Background and Objectives In our previous studies we explored the social representation of hearing loss and hearing aids. In this study we aimed at exploring if the positive, neutral and negative connotations associated with the social representation of 'hearing loss' and 'hearing aids' for the same categories vary across countries. In addition, we also looked at if there is an association between connotations and demographic variables. Subjects and Methods A total of 404 individuals from four countries were asked to indicate the words and phrases that comes to mind when they think about 'hearing loss' and 'hearing aids'. They also indicated if the words and phrases they reported had positive, neutral or negative association, which were analyzed and reported in this paper. Results There are considerable differences among the countries in terms of positive, neutral and negative associations report for each category in relation to hearing loss and hearing aids. However, there is limited connection between demographic variables and connotations reported in different countries. Conclusions These results suggesting that the social representation about the phenomenon hearing loss and hearing aids are relatively stable within respondents of each country.
Proposed cloud infrastructure of wearable and ubiquitous medical services

A Wearable Health Monitoring system is described that uses low-cost off the shelf sensors and computing components, along with custom made software, to provide an economical solution to personalized health care monitoring problems, while retaining all the functionality and flexibility of more expensive systems. Cloud technology is used to store sensor measurements which are categorized based on the criticality of bio-signals. Furthermore, a new session protocol for medical sensor data transmission is proposed. In a prototype system, tests based on different transmission architectures have so far yielded useful and favorable results in comparison with existing protocols and usually more expensive systems.
Respiratory Muscle Strength During and After Hospitalization for COPD Exacerbation

BACKGROUND: A more profound investigation of respiratory muscle strength during COPD exacerbation was needed, so we investigated respiratory muscle strength and related factors in patients with COPD during and after hospitalization for COPD exacerbation. METHODS: In 19 subjects hospitalized for COPD exacerbation (12 males, mean age 67 ± 11 y, median percent-of-predicted FEV1 26% [IQR 19–32%]) we measured lung function and respiratory and quadriceps muscle strength at admission (day 1), at discharge, and 1 month after discharge. RESULTS: At admission, 68% of the subjects had inspiratory muscle dysfunction (maximum inspiratory pressure < 70% of predicted). Inspiratory muscle strength increased between day 1 (56 cm H2O [IQR 45–64 cm H2O]) and 1 month after discharge (65 cm H2O [IQR 51–74 cm H2O], P = .007). Expiratory muscle strength increased between day 1 (99 cm H2O [65–117 cm H2O]) and discharge (109 cm H2O [77–136 cm H2O], P = .005), and between day 1 and 1 month after discharge (114 cm H2O [90–139 cm H2O], P = .001). Inspiratory capacity increased between discharge (1.59 ± 0.44 L) and 1 month after discharge (1.99 ± 0.54 L, P = .02). There was no significant change in other lung function variables or quadriceps strength. At admission the inspiratory muscle dysfunction and reduction in inspiratory capacity (< 80% of predicted) correlated linearly (phi coefficient 0.62, P = .03), whereas the expiratory muscle strength correlated inversely with FEV1 (Spearman rho −0.61, P = .005) and inspiratory capacity (Spearman rho −0.54, P = .02). CONCLUSIONS: There was a high prevalence of inspiratory muscle dysfunction in patients hospitalized for COPD exacerbation. Inspiratory and expiratory muscle strength increased markedly during and after hospitalization. The degree of air-flow obstruction and hyperinflation were related to inspiratory and expiratory muscle strength.
Learning eye movements strategies on tiled Large High-Resolution Displays using inverse reinforcement learning

In this paper, we modeled eye movements on tiled Large High-Resolution Displays (LHRD) as a Markov decision process(MDP). We collected eye movements of users participated with free viewing task experiments on LHRD. We have examined two different inverse reinforcement learning algorithms. The presented approach used information about the possible eye movement positions. We showed that it is possible to automatically extract reward function based on effective features from user eye movement behaviors using IRL. We found that, the Itti and HoG features shows highest positive reward weights for both algorithms. Most interestingly, we found that the reward function was able to extract expert behavior information that fulfill to predict eye movements. This is valuable information for estimating the internal states of users such as in, for example, intention recognition, to adapt visual interfaces, or to place important information.
EXISTENCE OF POSITIVE SOLUTIONS FOR SOME PROBLEMS WITH NONLINEAR DIFFUSION

In this paper we study the existence of positive solutions for problems of the type −∆pu(x) = u(x)q−1h(x, u(x)), x ∈ Ω, u(x) = 0, x ∈ ∂Ω, where ∆p is the p-Laplace operator and p, q > 1. If p = 2, such problems arise in population dynamics. Making use of different methods (suband supersolutions and a variational approach), we treat the cases p = q, p q, respectively. Also, some systems of equations are considered.
Migration and Interregional Employment Redistribution in the United States

During the 1970's the South and West census regions accounted for 89.9 percent of incremental U.S. population and 72.5 percent of incremental nonagricultural employment. These figures are sharply higher than corresponding figures for any other decade in U.S. history. For example, during the 1930's the South and West gained 65.4 percent of incremental national population, which was the highest share previously recorded. The immediate cause of the interregional population shifts is fairly heavy net out-migration from the Northeast and North Central regions to the South and West, combined with birth rates that are near historical low levels. Interactive relationships that cause employment growth and migration to reinforce one another are probably operating, but these relationships are not well understood. They are the focus of this paper. Using a new and unique set of time-series data on migration and employment, we develop and estimate a time-series model of migration and employment growth for each of 171 U.S. regions. Our primary emphasis in this paper is on the 57 major metropolitan
Aberrant Expression of Connexin Isoforms in the Corpus Epididymis of the Adult Rat by Exposure to Estradiol Benzoate or Flutamide at the Weaning Age

A proper development of the epididymis during the early postnatal development is required for successful fertility in the adult male. Direct cell-cell communication via connexin (Cx) molecules is a common way of cellular interactions to achieve normal development of a given tissue consisting of different cell types. The present research was attempted to determine the effect of exogenous exposure to estrogenic agonist or antiandrogen at the weaning age on expression of Cx isoforms in the adult corpus epididymis. Male rats were subcutaneously administrated with estradiol benzoate (EB) or flutamide (Flu) at the weaning age. The tissue was collected at 4 months of age. Expressional levels of Cx isoforms were determined by a quantitative real-time PCR. Statistical comparison showed significant increases of Cxs31, 32, 37, 40, and 43 transcript amounts by a treatment of 0.015 mg of EB /kg body weight (BW). A treatment of 1.5 μg of EB /kg BW caused a significant decrease of Cx43 gene expression but increases of Cxs26, 31, 32, 37, and 40 transcript levels. Exposure to 500 mg of Flu/kg BW induced an increase of Cx37 expression but significant decreases of Cxs43 and 45 mRNA levels. Expression of Cx37 was increased by a treatment of 5 mg of Flu/kg BW, while transcript levels of Cxs26, 30.3, 31, 31.1, 32, and 43 were significantly decreased by same treatment. These results demonstrate that exposure to steroidal compounds at the early developmental age alters expression of Cx isoforms in the adult corpus epididymis.
A Polarimetric Thermal Database for Face Recognition Research

We present a polarimetric thermal face database, the first of its kind, for face recognition research. This database was acquired using a polarimetric longwave infrared imager, specifically a division-of-time spinning achromatic retarder system. A corresponding set of visible spectrum imagery was also collected, to facilitate crossspectrum (also referred to as heterogeneous) face recognition research. The database consists of imagery acquired at three distances under two experimental conditions: neutral/baseline condition, and expressions condition. Annotations (spatial coordinates of key fiducial points) are provided for all images. Cross-spectrum face recognition performance on the database is benchmarked using three techniques: partial least squares, deep perceptual mapping, and coupled neural networks.
“ My Roomba is Rambo ” : Intimate Home Appliances

Robots have entered our domestic lives as pets, caretakers and vacuum cleaners. Yet, little is known about their impact on the home. This paper takes first steps towards addressing this omission, by reporting on results from an empirical study of iRobot’s Roomba –a vacuuming robot—that examined adoption and use. Our findings suggest that, by developing intimacy to the robot, our participants were able to derive increased pleasure from cleaning, and expended effort to fit Roomba into their homes and share with others. These findings lead us to propose four design implications that we argue could increase people’s enthusiasm for smart home technologies.
Corporate Responsibility Reporting and its Determinants in Comparative Perspective – a Review of the Empirical Literature and a Meta‐analysis

For four decades, reporting on corporate responsibility by businesses has been the subject of empirical research. In the 1970s and 1980s, studies mostly originated from Anglo-Saxon and Western European countries. During the last two decades research on responsibility reporting was increasingly undertaken in emerging and developing countries as well – always following the reporting practices of the respective businesses. Consequentially, a very large number of studies exist today. Many of these have empirically investigated the determinants of responsibility reporting and examined whether internal factors like size and industry or external factors like stakeholder pressures have an impact on disclosure. Thus, the purpose of the following paper is twofold. First, it seeks to provide an overview of the existing literature in order to facilitate further research. Overall, 186 studies have been examined for the determinants which they considered and have been grouped according to their geographical origin. This provides for an analysis of whether academics from different regions have taken different approaches to the empirical examination of responsibility reporting and if their results differed. The findings show that scholars across regions have taken different paths in empirical research, but indications for a variation in the impact of specific determinants on reporting are weak. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.
The implications of the new ISO 9000:2000 standards for certified organizations: A review of anticipated benefits and implementation pitfalls

Purpose – To exploit the main implications of the revised series of quality assurance standards ISO 9000:2000 for the certified organisations. The paper aims to identify the anticipated benefits of the changes in the series, as well as the main barriers and pitfalls that may deprive organisations of these benefits.Design/methodology/approach – The paper combines the ideas and views of different authors and studies in this subject and organises them accordingly, based on the author's previous experience and empirical studies on ISO 9000 implementation, in order to fully describe the subject for the reader.Findings – The paper finds that although the revised series of standards may offer important benefits to the certified organisations in areas which were previously considered to be the weak areas of the standards, there are still important dilemmas regarding the degree to which companies will be able to overcome a number of barriers and implementation pitfalls.Research limitations/implications – The paper.
Influence of Exchange Variation and Demand Conditions in the Determination of IPCA in Brazil

Abstract The objective of this paper is to analyze the exchange rate pass-through in Braziland the importance of demand pressures on prices in the period after the implementation of the inflation-targeting regime. The methodology used was the Vector Error Correction Model (VECM), between three periods January 1999 to May 2011. The results show a high degree of inertia in all periods. Furthermore, they show that when neglecting the inertia, the exchange was the main determinant of price variation in the first period, while in the second period the main causes of inflationary pressures were demand pressures. The results also show that, in the Brazilian case, a significant devaluation in a short period of time can be dangerous to the stability of prices.
Dynamic Investment Models and the Firm's Financial Policy

In this paper we investigate the sensitivity of investment to the availability of internal funds using the hierarchy of finance approach to corporate finance. We characterize the empirical implications of this approach for dynamic investment models and test these implications using firm-level data. The model we estimate is based on the Euler equation for optimal capital accumulation in the presence of convex adjustment costs. The theoretical model explicitly allows for debt finance and financial assets. The empirical investigation uses U.K. company panel data to estimate dynamic investment models using GMM and tests the derived implications.
Local Permutations in the Glomerular Array of the Mouse Olfactory Bulb

Olfactory sensory neurons expressing a given odorant receptor gene project their axons with great precision to a few specific glomeruli in the olfactory bulb. It is not clear to which extent the positions of these glomeruli are fixed. We sought to evaluate the constancy of the glomerular array in the mouse by determining the relative positions of glomeruli for various odorant receptors, using a method that affords single-axon resolution, and in a large number of bulbs. We used a genetic strategy to visualize neuronal populations that express one of three members of the mOR37 subfamily. We generated by gene targeting five strains of mice in which expression of a givenmOR37 gene is linked to expression of an axonal maker, which is either taulacZ or tauGFP. The patterns of marker expression faithfully mimic those of the cognate receptors. Axons of neurons expressing a given mOR37 gene converge onto one or two glomeruli per bulb. Each mOR37 gene has its own glomeruli, and the mOR37 glomeruli are grouped within a restricted domain of the bulb. Serial sectioning of 214 bulbs reveals that the relative positions of the three types of glomeruli are not fixed but display local permutations. Importantly, this is also the case among the two bulbs from one individual, ruling out the genetic manipulation itself and differences in genetic background or olfactory experience as causes for the observed variability. These local permutations may reflect the developmental history of the glomeruli and are relevant for the construction of spatial odor maps.
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning

Principal Component Analysis (PCA) is a fundamental method for estimating a linear subspace approximation to high-dimensional data. Many algorithms exist in literature to achieve a statistically robust version of PCA called RPCA. In this paper, we present a geometric framework for computing the principal linear subspaces in both situations that amounts to computing the intrinsic average on the space of all subspaces (the Grassmann manifold). Points on this manifold are defined as the subspaces spanned by K-tuples of observations. We show that the intrinsic Grassmann average of these subspaces coincide with the principal components of the observations when they are drawn from a Gaussian distribution. Similar results are also shown to hold for the RPCA. Further, we propose an efficient online algorithm to do subspace averaging which is of linear complexity in terms of number of samples and has a linear convergence rate. When the data has outliers, our proposed online robust subspace averaging algorithm shows significant performance (accuracy and computation time) gain over a recently published RPCA methods with publicly accessible code. We have demonstrated competitive performance of our proposed online subspace algorithm method on one synthetic and two real data sets. Experimental results depicting stability of our proposed method are also presented. Furthermore, on two real outlier corrupted datasets, we present comparison experiments showing lower reconstruction error using our online RPCA algorithm. In terms of reconstruction error and time required, both our algorithms outperform the competition.
Efficient estimation of accurate maximum likelihood maps in 3D

Learning maps is one of the fundamental tasks of mobile robots. In the past, numerous efficient approaches to map learning have been proposed. Most of them, however, assume that the robot lives on a plane. In this paper, we consider the problem of learning maps with mobile robots that operate in non-flat environments and apply maximum likelihood techniques to solve the graph-based SLAM problem. Due to the non-commutativity of the rotational angles in 3D, major problems arise when applying approaches designed for the two-dimensional world. The non-commutativity introduces serious difficulties when distributing a rotational error over a sequence of poses. In this paper, we present an efficient solution to the SLAM problem that is able to distribute a rotational error over a sequence of nodes. Our approach applies a variant of gradient descent to solve the error minimization problem. We implemented our technique and tested it on large simulated and real world datasets. We furthermore compared our approach to solving the problem by LU-decomposition. As the experiments illustrate, our technique converges significantly faster to an accurate map with low error and is able to correct maps with bigger noise than existing methods.
A Comparative Study of Bag-of-Words and Bag-of-Topics Models of EO Image Patches

The large volume of detailed land cover features, provided by high resolution Earth observation (EO) images, has attracted considerable interest in the discovery of these features by learning systems. In this letter, we perform latent Dirichlet allocation on the bag of words (BoW) representation of collections of EO image patches to discover their semantic-level features, the so-called topics. To assess the discovered topics, the images are represented based on the occurrence of different topics, called bag of topics (BoT). The value added by BoT to the BoW model of image patches is then measured based on existing human annotations of the data. In our experiments, we compare the classification accuracy results of BoT and BoW representations of two different remote sensing image data sets, a multispectral optical data set and a synthetic-aperture-radar data set. Experimental results demonstrate that BoT can provide a compact and semantically meaningful representation of data; it either causes no significant reduction in the classification accuracy or increases the accuracy by a sufficient number of topics.
Association rules mining on forest fires data using FP-Growth and ECLAT algorithm

Forest fires and land are a serious problem that must be solved by the Indonesian government including Riau Province. One of forest fires prevention effort is discovering relationship patterns of hotspot occurrences as fire indicators with characteristics of geographic objects where the hotspots occur. The objective of this research is to apply the multidimensional association rule mining method with Frequent Pattern Growth algorithm (FP-Growth) and Equivalence Class Transformation algorithm (ECLAT) to determine association patterns between hotspot occurrences and its supporting factors. The factors that influence hotspot occurrences were discovered on minimum support of 30% and minimum confidence of 80% with hotspot occurrence as the target attribute. The result of this research shows that strong relationships between hotspot occurrences and its influence factor were found with the the highest support of 44.49%, confidence of 100%, and lift of 1.02, where hotspot are mostly occurred in areas which has precipitation greater than or equal to 3 mm/day.
On the Use of XMDD in Software Development Education

Process modeling can play a central role in problem-based software development education with regard to qualifying students for the design and implementation of software applications for their specific needs without putting the focus on the technical part of coding. eXtreme Model Driven Design (XMDD) is a paradigm that focuses on the What (solving problems), rather than on the How (the technical skills of writing code). In this way it renders application design and implementation less daunting, thus accessible and more appealing to people that are either less technically skilled, or simply not interested at all in learning usual programming. In this paper we report on our experiences with the use of the jABC process modeling framework for teaching service-based software development in an XMDD fashion to students of different fields and on different levels of education.
Dual and opposing roles of presynaptic Ca2+ influx for spontaneous GABA release from rat medial preoptic nerve terminals

Calcium influx into the presynaptic nerve terminal is well established as a trigger signal for transmitter release by exocytosis. By studying dissociated preoptic neurons with functional adhering nerve terminals, we here show that presynaptic Ca2+ influx plays dual and opposing roles in the control of spontaneous transmitter release. Thus, application of various Ca2+ channel blockers paradoxically increased the frequency of spontaneous (miniature) inhibitory GABA‐mediated postsynaptic currents (mIPSCs). Similar effects on mIPSC frequency were recorded upon washout of Cd2+ or EGTA from the external solution. The results are explained by a model with parallel Ca2+ influx through channels coupled to the exocytotic machinery and through channels coupled to Ca2+‐activated K+ channels at a distance from the release site.