Miracle-dz/UniFAR-FTUs huggingface dataset:
Maintenance Use of Antidepressants in Dutch General Practice: Non-Guideline Concordant

Background There is hardly evidence on maintenance treatment with antidepressants in primary care. Nevertheless, depression guidelines recommend maintenance treatment i.e. treatment to prevent recurrences, in patients with high risk of recurrence, and many patients use maintenance treatment with antidepressants. This study explores the characteristics of patients on maintenance treatment with antidepressants in general practice, and compares these characteristics with guideline recommendations for maintenance treatment. Methods We used data (baseline, two-year and four-year follow-up) of primary care respondents with remitted depressive disorder (≥6 months) from the Netherlands Study of Depression and Anxiety (n = 776). Maintenance treatment was defined as the use of an antidepressant for ≥12 months. Multilevel logistic regression was used to describe the association between sociodemographic, clinical and care characteristics and use of maintenance treatment with antidepressants. Results Older patients, patients with a lower education, those using benzodiazepines or receiving psychological/psychiatric care and patients with a concurrent history of a dysthymic or anxiety disorder more often received maintenance treatment with antidepressants. Limitations Measurements were not made at the start of an episode, but at predetermined points in time. Diagnoses were based on interview (CIDI) data and could therefore in some cases have been different from the GP diagnosis. Conclusions Since patients with chronic or recurrent depression do not use maintenance treatment with antidepressants more often, characteristics of patients on maintenance treatment do not fully correspond with guideline recommendations. However, patients on maintenance treatment appear to be those with more severe disorder and/or more comorbidity.
Skyline Query Processing System for Taiwan Maps

With the fast advance of GPS technology and mobile devices, Location-Based Services (LBS for short) are useful in many real-life applications. In this paper, we develop a location-based system which processes the skyline queries for the Taiwan maps. We dedicate to improve the usability, design the user-friendly interface, and provide a consistent user experience for all cross-devices. We try to implement a general and useful system for the skyline queries.
Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation

We study the least square regression with data dependent hypothesis and coefficient regularization algorithms based on general kernel. An explicit expression of the solution of this kernel scheme is derived. Then we provide a sample error with a decay of
Energy-Efficient Communication-Based Train Control Systems With Packet Delay and Loss

Designing a train control system over wireless train-wayside communications is a challenging task due to the packet delay and loss caused by unreliable wireless communications. In this paper, we study the performance optimization issues in communication-based train control (CBTC) systems with both packet delay and loss introduced by random transmission errors and frequent handoffs in train-wayside communications. A networked control system (NCS) model is formulated for multitrain CBTC systems with packet delay and loss. Then, we propose a novel train control scheme to enhance the quality of service (QoS) of CBTC systems. In the proposed scheme, medium-access control layer retry limit adaption is used to minimize the energy consumption, and guidance trajectory update is used to mitigate the trip time tracking errors. Extensive simulation results show that the QoS of CBTC systems can be substantially improved in the proposed scheme. The energy consumption and trip time error can be reduced in both static and time-varying wireless environments.
The Gap Phenomena During Retrograde Conduction in Man

Ventricular refractory period studies were performed in 12 consecutive and unselected patients using the ventricular extrastimulus method (V2) at basic ventricular cycle lengths (V1 V1). In six of 12 patients two types of retrograde gaps occurred. At relatively long V1 V2 intervals, ventriculo-atrial (V-A) conduction failed and then resumed at shorter V1 V2 intervals. The initial sites of retrograde block were the A-V node in two patients and the His-Purkinje system in four patients. In both groups, resumption of V-A conduction at shorter V1 V2 intervals occurred because of retrograde delay within the His-Purkinje system. Retrograde gaps differ from previously described antegrade gaps in A-V conduction: The site of initial block in A-V gaps is the His-Purkinje system and resumption of A-V conduction occurs at shorter A1 A2 intervals because of proximal delay in the A-V node (type I) or delay in the proximal His-Purkinje system (type II). In V-A gaps the site of initial block may be either the A-V node or the His-Purkinje system and resumption of V-A conduction always occurs due to delay within the distal His-Purkinje system. A common feature of both A-V and V-A gaps is the fact that delay of the more premature impulses allows time for previously refractory areas to recover excitability and both can be functional in nature. Only one of the 12 patients had both A-V and V-A gaps in conduction. Retrograde gaps in V-A conduction are more commonly observed than A-V gaps.
Cyclical prudence - credit cycles in Australia

Over the past 150 years, Australia has experienced four major cycles in credit in the 1890s, 1930s, 1970s and 1990s. Each of these episodes combined cycles in the real economy with varying degrees of financial system instability. This association reflects the fact that the health of the financial system and the economy are inextricably linked. While the strength of economic activity influences the demand for credit, at the same time the health of the financial system affects the supply of credit, which in turn influences economic activity. However, of particular concern for policymakers is the potential for the behaviour of financial institutions and financial markets to amplify cycles in the real economy.
Assistive Teleoperation : A New Domain for Interactive Learning – Extended Abstract –

Assistive Teleoperation as Policy Blending In assistive teleoperation, the robot attempts to predict the user’s intent and augments his or her input based on this prediction, in order to simplify the task. Our recent work on policy blending (Dragan and Srinivasa 2012) formalizes assistance as an arbitration of the user’s input and the robot’s prediction. At any instant, the robot combines the input, U , and the prediction, P , using a state-dependent arbitration function α ∈ [0, 1] (Fig.1(bottom)). Policy blending can have a strong corrective effect on the actual input provided by the user, but burdens the robot to predict accurately and arbitrate appropriately.
Anagnorisis and narrative incorporation: How significant incidents affect language-learning behavior

This paper examines how fleeting experiences exert a disproportionately powerful effect on the language learning motivation and behavior of university students. A thematic analysis of interview data is used to show how significant incidents have two principal consequences. The first, anagnorisis, is an immediate, revelatory change in beliefs about language learning. The second, narrative incorporation, is a process through which the memory of the incident and/or its anagnorisis becomes a constituent of self-narratives. It is argued that the significant incident is best understood not as an external influence on motivation, but as a component of the learner’s worldview.
The Effect of the Number of Features to Supervised Chinese Word Sense Disambiguation

Although feature selection is very important during either supervised or unsupervised word sense disambiguation processing, there is no systematic study on investigating the relationship between the number of features and the performance as we know yet. This paper investigates the effect of the number of features to supervised Chinese word sense disambiguation through thousands of experiments on Semeval 2007 Multilingual Chinese-English Lexical Sample task dataset. It shows that local basic feature provides adequate information to do disambiguation and the influence of data sparseness is not as important on the performance as we think before from the number of features point of view.
FPGA Implementation of Low Power, High Speed, Area Efficient Invisible Image Watermarking Algorithm for Images

In recent years, the applications about multimedia have been developed rapidly. Due to rapid development in the network and communication field, it has become necessary to protect the data during transmission. Digital watermarking is a solution to the copyright protection and authentication of data in the network. Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. So there has been growing interest in developing effective techniques to discourage the unauthorized duplication of digital data In this technique, based Image robust watermarking technique for color and gray scale images was performed. The RGB image is converted to HSV and watermarked by using discrete wavelet transform. Watermarking embedded stage and extraction stage is designed using invisible watermarking algorithm. Here the host signal is an image and after embedding the secret data a watermarked image is obtained and then extracts secret image and original image separately. Checking the watermark insertion and quality analysis various parameters like PSNR, Cross correlation etc FPGA implementation of invisible watermarking algorithm using the proposed design can operate at a maximum frequency of 344 MHz . An improvement of 28% in speed has been achieved by consuming considerably less number of resources of Vertex 6 6vsx315tff1156-2 FPGA device to provide cost effective solutions for real time image processing applications.
PET imaging of the dopamine transporter in progressive supranuclear palsy and Parkinson’s disease

Objective: To differentiate the patterns of dopamine transporter loss between idiopathic PD and progressive supranuclear palsy (PSP). Methods: We used the radiotracer [11C]-WIN 35,428 and PET. Regional striatal dopamine transporter binding was measured in the caudate, anterior putamen, and posterior putamen of six patients with L-dopa–responsive stage 2 PD, six patients with PSP, and six age-comparable healthy controls. Results: In patients with idiopathic PD, the most marked abnormality was observed in the posterior putamen (77% reduction), whereas transporter density in the anterior putamen (60% reduction) and the caudate (44% reduction) was less affected. Unlike the patients with PD, the PSP group showed a relatively uniform degree of involvement in the caudate (40% reduction), anterior putamen (47% reduction), and posterior putamen (51% reduction). When posterior putamen/caudate ratios were calculated, these values were significantly lower in patients with PD than they were in patients with PSP (p = 0.0008) and the control group (p < 0.0001). Conclusions: Patients with PD have a more pronounced loss of dopamine transporters in the posterior putamen due to a subdivisional involvement of nigrostriatal dopaminergic projections in idiopathic PD. This technique is useful in the determination of neurochemical changes underlying PD and PSP, thus differentiating between them.
One-loop divergences in simple supergravity: Boundary effects.

This paper studies the semiclassical approximation of simple supergravity in Riemannian four-manifolds with boundary, within the framework of $\zeta$-function regularization. The massless nature of gravitinos, jointly with the presence of a boundary and a local description in terms of potentials for spin ${3\over 2}$, force the background to be totally flat. First, nonlocal boundary conditions of the spectral type are imposed on spin-${3\over 2}$ potentials, jointly with boundary conditions on metric perturbations which are completely invariant under infinitesimal diffeomorphisms. The axial gauge-averaging functional is used, which is then sufficient to ensure self-adjointness. One thus finds that the contributions of ghost and gauge modes vanish separately. Hence the contributions to the one-loop wave function of the universe reduce to those $\zeta(0)$ values resulting from physical modes only. Another set of mixed boundary conditions, motivated instead by local supersymmetry and first proposed by Luckock, Moss and Poletti, is also analyzed. In this case the contributions of gauge and ghost modes do not cancel each other. Both sets of boundary conditions lead to a nonvanishing $\zeta(0)$ value, and spectral boundary conditions are also studied when two concentric three-sphere boundaries occur. These results seem to point out that simple supergravity is not even one-loop finite in the presence of boundaries.
The interoperability of Wi-Fi hotspots and packet cellular networks and the impact of user behaviour

The rapid emergence of Wi-Fi hotspots (access points), that are aimed at providing broadband wireless access to users in and around places of commercial interest, presents the unique problem of integrating existing cellular networks with these. We present a novel architecture that explores the interoperability issues between Wi-Fi hotspots and packet cellular networks. In the presence of multiple wireless networks with different access costs, different areas of coverage and bandwidth, the user's choice to select a particular network can significantly impact user benefits and resource usage. We identify three major user profiles - bandwidth conscious, cost conscious and glitch conscious - and study their impact on resource utilization. Contrary to intuition, simulation experiments have shown that bandwidth conscious users may get fewer bandwidth resources compared to glitch conscious users at high mobility. Similarly, it was found that bandwidth conscious users achieve high packet delivery ratios, even while incurring lower costs than cost conscious users, in certain situations. Although increasing the number of access points (APs) leads to higher packet delivery ratios, system performance degrades when the number of APs becomes very large.
Minimizing register usage penalty at procedure calls

Inter-procedural register allocation can minimize the register usage penalty at procedure calls by reducing the saving and restoring of registers at procedure boundaries. A one-pass inter-procedural register allocation scheme based on processing the procedures in a depth-first traversal of the call graph is presented. This scheme can be overlaid on top of intra-procedural register allocation via a simple extension to the priority-based coloring algorithm. Using two different usage conventions for the registers, the scheme can distribute register saves/restores throughout the call graph even in the presence of recursion, indirect calls or separate compilation. A natural and efficient way to pass parameters emerges from this scheme. A separate technique uses data flow analysis to optimize the placement of the save/restore code for registers within individual procedures. The techniques described have been implemented in a production compiler suite. Measurements of the effects of these techniques on a set of practical programs are presented and the results analysed.
Evaluation of the modified group delay feature for isolatedword recognition

The results of our recent human perception experiments indicate that the short-time phase spectrum can significantly contribute to speech intelligibility over small window durations (i.e., 20-40 ms). This motivates us to investigate the use of the short-time phase spectrum to derive features for automatic speech recognition, which generally uses small window durations of 20-40 ms for spectral analysis. In this paper, we specifically investigate the frequency-derivative of the short-time phase spectrum (i.e., group delay function, GDF) from which to extract features. We demonstrate, with some simple examples, the volatility of the GDF to noise, pitch epochs and windowing effects. We summarise the work by Yegnanarayana and Murthy on the modified GDF (MGDF), which serves to remedy the problems of the GDF. We then implement Murthy and Gadde's MGDF-based features (MODGDF) to determine if they provide an improvement over the popular MFCC representation either by themselves or in combination with MFCCs on an isolated word recognition task.
REGULARIZATION , BOOSTING AND MIRROR AVERAGING

In their paper, Peter Bickel and Bo Li give an interesting unified view of regularization methods in statistics. The literature on this subject is immense, so they outline a general conceptual approach, and then focus on some selected problems where regularization is used, such as regression and classification, or more generally, prediction. In this context, they discuss in detail a number of recently emerging techniques, in particular, boosting, estimation of large covariance matrices, estimation in the models where the dimension is larger than the sample size. It is difficult to overestimate the importance of regularization in statistics, especially in nonparametrics. Most of nonparametric estimation problems are ill-posed, and common estimators (kernel, histogram, spline, orthogonal series etc.) are nothing but regularized methods of solving them. The corresponding regularization parameters are just smoothing parameters of the estimators. The main ideas of statistical regularization can be very transparently explained for prediction problems. Assume that X1, . , Xn are i.i. d. observations taking values in a space X , and assume that the unknown underlying function f ? that we want to estimate belongs to a space F . Consider a loss function Q : X × F → IR and the associated prediction risk R(f) = EQ(X, f) where X has the same distribution as Xi. Assume that f ? is a minimizer of the risk R(f) over F . Then a classical, but not always reasonable, estimator of f ? is a minimizer over f ∈ F of the corresponding empirical risk
The Gamma-Ray Burst Luminosity Function in the Light of the Swift 2 Year Data

We compute the luminosity function (LF) and the formation rate of long gamma-ray bursts (GRBs) by fitting the observed differential peak flux distribution obtained by BATSE in three different scenarios: (1) GRBs follow the cosmic star formation, and their LF is constant in time; (2) GRBs follow the cosmic star formation, but the LF varies with redshift; and (3) GRBs form preferentially in low-metallicity environments. We find that the differential peak flux number counts obtained by BATSE and by Swift can be reproduced using the same LF and GRB formation rate, indicating that the two satellites are observing the same GRB population. We then check the resulting redshift distributions in light of Swift 2 year data, focusing in particular on the relatively large sample of GRBs detected at z > 2.5. We show that models in which GRBs trace the cosmic star formation and are described by a constant LF are ruled out by the number of high-z Swift detections. This conclusion does not depend on the redshift distribution of bursts that lack optical identification, nor on the existence of a decline in star formation rate at z > 2, nor on the adopted faint end of the GRB LF. Swift observations can be explained by assuming that the LF varies with redshift and/or that GRB formation is limited to low-metallicity environments.
The Decision-Making Context Influences the Role of the Enterprise Architect

Enterprise architecture (EA) offers ways to steer and guide the design and evolution of the enterprise, including its information technology (IT). One of the objectives of EA is to support IT decision-making. This study aims to provide EA researchers and practitioners with insight into the factors that influence the role of EA in IT decision- making. For this purpose, we conducted a multiple case study at three different organizations in which we analyzed how EA influences IT decisions regarding specific issues. EA's support was found to deliver a valuable contribution in all three cases, which however varied considerably from case to case. We have identified four different factors that determine the role of EA in IT decision-making processes: the formalization of the decision-making process, the mindset of decision-makers, the magnitude of impact and the time pressure of the issue. These factors determine how the enterprise architect will be involved in IT decision-making, the type of deliverables and the breadth and depth of the architecture analysis.
A Catalog of Absorption Lines in Eight HST/STIS E230M 1.0 < z < 1.7 Quasar Spectra

We have produced a catalog of line identifications and equivalent width measurements for all absorption features in eight ultraviolet echelle quasar spectra. These spectra were selected as having the highest signal-to-noise among the HST/STIS spectra obtained with the E230M grating. We identify 56 metal-line systems toward the eight quasars, and present plots of detected transitions, aligned in velocity-space. We found that about 1/4 - 1/3 of the features in the Lya forest region, redward of the incidence of the Lyb forest, are metal lines. High ionization transitions are common. We see both O VI and C IV in 88 - 90% of the metal-line systems for which the spectra cover the expected wavelength. Si III is seen in 58%, while low ionization absorption in C II, Si II, and/or Al II is detected in 50% of the systems for which they are covered. This catalog will facilitate future studies of the Lya forest and of metal-line systems of various types.
Comparing CRF and template-matching in phrasing tasks within a Hybrid MT system

The present article focuses on improving the performance of a hybrid Machine Translation (MT) system, namely PRESEMT. The PRESEMT methodology is readily portable to new language pairs, and allows the creation of MT systems with minimal reliance on expensive resources. PRESEMT is phrase-based and uses a small parallel corpus from which to extract structural transformations from the source language (SL) to the target language (TL). On the other hand, the TL language model is extracted from large monolingual corpora. This article examines the task of maximising the amount of information extracted from a very limited parallel corpus. Hence, emphasis is placed on the module that learns to segment into phrases arbitrary input text in SL, by extrapolating information from a limited-size parsed TL text, alleviating the need for an SL parser. An established method based on Conditional Random Fields (CRF) is compared here to a much simpler template-matching algorithm to determine the most suitable approach for extracting an accurate model. Experimental results indicate that for a limited-size training set, template-matching generates a superior model leading to higher quality translations.