Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Models for Clinical Psychology

The network approach to clinical psychology is a relatively new approach and diverges on various aspects from existing models and theories. The hallmark of the theory is that there is no common cause that underlies a set of symptoms. Instead, the network approach starts out by assuming that symptoms causally interact with each other. In this chapter, we first explain the conceptualization of psychological phenomena as a network in the introduction. Second, we provide an overview of the methods that are used to construct network models from data; both Gaussian and binary data, as well as cross‐sectional and longitudinal data are covered. Third, we describe how a given network can be analyzed to uncover important symptoms in the network, to predict behavior of the network, and to compare network structures. Fourth, we discuss current state‐of‐the‐art research in clinical psychology and psychiatry, to see what these networks taught us about psychopathology. Finally, we discuss the promising prospects for clinical psychology research that the network approach has to offer and some of the challenges a researcher might face in applying this approach to clinical psychology data.
On the Boundedness of Penalty Parameters in an Augmented Lagrangian Method with Constrained Subproblems ∗

Augmented Lagrangian methods are eﬀective tools for solving large-scale nonlinear programming problems. At each outer iteration a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When the penalty parameter becomes very large the sub-problem is diﬃcult, therefore the eﬀectiveness of this approach is associated with boundedness of penalty parameters. In this paper it is proved that, under more natural assumptions than the ones up to now employed, penalty parameters are bounded. For proving the new bound-edness result, the original algorithm has been slightly modiﬁed. Numerical consequences of the modiﬁcations are discussed and computational experiments are presented.
hRUL138, a novel human RNA-binding RING-H2 ubiquitin-protein ligase

Cellular as well as viral RNAs are usually found complexed with proteins. In an attempt to identify proteins that interact with transcripts of hepatitis B virus (HBV), a DNA virus that replicates through reverse transcription, a partial cDNA was isolated from a human cDNA expression library whose gene product bound to an HBV-derived RNA. Using an overlapping clone from a molecular hybridization screen a full-length cDNA was assembled. It contained a large open reading frame for a 1208 amino-acid protein of 138 kDa identical to the hypothetical product of the KIAA0675 clone. Closely related sequences are present in mouse cDNA libraries but not in the genomes of lower organisms. The protein sequence contained no known RNA-binding domain and, apart from a probable coiled-coil domain, the only significant homology involved a complete RING-H2 motif. This suggested that the protein might be a novel RNA-binding RING-dependent ubiquitin-protein ligase or E3 enzyme. A motif critical for RNA binding was experimentally mapped to a central Lys-rich region. Binding specificity is either broad or the protein has as yet unknown physiological targets; hence, at present, a potential importance for HBV biology remains open. The RING-H2 domain was functional in and essential for self- and trans-ubiquitylation in vitro and for proteasome-mediated turnover of the protein in vivo. We therefore termed it hRUL138 for human RNA-binding ubiquitin ligase of 138 kDa. hRUL138 mRNAs are expressed at low levels in most tissues. GFP-tagged hRUL138 derivatives were found associated with cytoplasmic structures, possibly the ER, but excluded from the nucleus. The combined presence of RNA binding and E3 activity in hRUL138 raises the possibility that both are mechanistically linked.
Using 3-D projection to bring a statue to life

contrast, our interest is in using the technology to support engaged communication. Beyond such explorations of 3-D projection, which primarily focus on the technical aspects of the technology, the most prominent examples of 3-D projection are, arguably, the works of Pablo Valbuena. His series of installations, entitled Augmented Sculptures, has been displayed at Ars Electronica and has attracted many online visitors to Youtube [4]. Valbuena’s installations are typically composed of camera-tracked, angular, and clear-cut geometric shapes in conjunction with 3-D technology, which is used to create the illusion of light sources moving across elements of the faces of the installations. Also, there is a growing number of installations that employ 3-D projection to mimic the third dimension on a 2-D surface. 555 Kubik is one example of such an installation [5]. Projected onto the facade of Hamburg’s Kunsthalle, the instalIn the dungeons of Kronborg, a nearly 400-year-old Renaissance castle known from Shakespeare’s Hamlet, there is a statue of Holger the Dane. Holger the Dane is a mythical figure who, according to one myth, will awaken and defend the country when an enemy from beyond the borders threatens the kingdom of Denmark. Annually, more than 90,000 people visit the castle, and while most of them visit the dungeons, they usually visit the statue only briefly. How does a Danish myth relate to HCI? Well thanks to 3-D technology, we have been able to bring Holger the Dane “to life. ” In order to create an engaging experience that communicates some of the many legends about Holger the Dane, most of which are unknown to the public, we looked to 3-D projection. Three-dimensional projection on physical objects is a particular kind of spatially augmented reality (AR), which augments a physical object by projecting digital content directly onto it, rather than by using a device such as a mobile phone or a head-mounted display. During the past two decades, several research teams have been investigating 3-D projection on physical objects from Using 3-D Projection to Bring a Statue to Life
Speech enhancement using transfer function ratio beamformer and matched filter array

Human machine interface for speech processing often suffers from interferences which contain nonstationary signal, stationary signal and reverberation. In this paper, we consider two speech sources in the reverberant and noisy environment and we develop a speech enhancement approach to extract desired speech signal from the corrupt observations. The proposed method uses transfer function ratio beamformer, H∞ adaptive filter algorithm and matched filter array to perform speech enhancement as well as dereverberation at two stages. The desired speech is extracted at the first stage and the extracted speech which contains reverberation is dereverberated at the second stage.
Algorithm 963

We describe the implementation of a parameter estimation method suitable for models commonly used in quantitative finance. The Continuum-Generalized Method of Moments (CGMM) is a Generalized Method of Moments (GMM) type of methodology that applies a continuum of moment conditions to achieve the efficiency of a Maximum Likelihood method. Instead of the transition density, the more commonly available conditional characteristic function is used for estimation. We test the CGMM and a simpler version, called the CMM, on simulated time series to check the recovery of the parameters. We also applied CMM to two stochastic covariance models, the Wishart Affine Stochastic Correlation (WASC) model and the Principal Components Stochastic Volatility (PCSV) model. This illustrates the power of CGMM, as stochastic covariance models are generally hard to estimate. The estimation method is fully implemented in MATLAB.
Error-Correcting Code Aware Memory Subsystem

An error-correcting code (ECC) immune to bit errors has been widely used in reliable computer systems. However, ECC techniques can make memory performance severely degraded since incomplete-word write requests lead to inefficient read-to-write (RTW) and write-to-read operations of synchronous dynamic random access memory. In this paper, we propose a memory subsystem efficient for ECC operations. Our key idea is that the RTW operations causing incomplete-word write requests are split and grouped into independent read and write operations, and then the grouped read and write operations are individually scheduled for the optimal memory performance under application constraints. Experimental results show that the proposed ECC-aware memory subsystem achieves 17% shorter memory latency, and 12% higher memory utilization, on average, than the latest conventional memory subsystems on industrial multimedia applications. Moreover, the ECC-aware memory subsystem improves up to 2.5 times higher memory performance on synthetic benchmarks.
Cross-Supervised Synthesis of Web-Crawlers

A web-crawler is a program that automatically and systematically tracks the links of a website and extracts information from its pages. Due to the different formats of websites, the crawling scheme for different sites can differ dramatically. Manually customizing a crawler for each specific site is time consuming and error-prone. Furthermore, because sites periodically change their format and presentation, crawling schemes have to be manually updated and adjusted. In this paper, we present a technique for automatic synthesis of web-crawlers from examples. The main idea is to use hand-crafted (possibly partial) crawlers for some websites as the basis for crawling other sites that contain the same kind of information. Technically, we use the data on one site to identify data on another site. We then use the identified data to learn the website structure and synthesize an appropriate extraction scheme. We iterate this process, as synthesized extraction schemes result in additional data to be used for re-learning the website structure. We implemented our approach and automatically synthesized 30 crawlers for websites from nine different categories: books, TVs, conferences, universities, cameras, phones, movies, songs, and hotels.
A High Dietary Glycemic Index Increases Total Mortality in a Mediterranean Population at High Cardiovascular Risk

Objective Different types of carbohydrates have diverse glycemic response, thus glycemic index (GI) and glycemic load (GL) are used to assess this variation. The impact of dietary GI and GL in all-cause mortality is unknown. The objective of this study was to estimate the association between dietary GI and GL and risk of all-cause mortality in the PREDIMED study. Material and Methods The PREDIMED study is a randomized nutritional intervention trial for primary cardiovascular prevention based on community-dwelling men and women at high risk of cardiovascular disease. Dietary information was collected at baseline and yearly using a validated 137-item food frequency questionnaire (FFQ). We assigned GI values of each item by a 5-step methodology, using the International Tables of GI and GL Values. Deaths were ascertained through contact with families and general practitioners, review of medical records and consultation of the National Death Index. Cox regression models were used to estimate multivariable-adjusted hazard ratios (HR) and their 95% CI for mortality, according to quartiles of energy-adjusted dietary GI/GL. To assess repeated measures of exposure, we updated GI and GL intakes from the yearly FFQs and used Cox models with time-dependent exposures. Results We followed 3,583 non-diabetic subjects (4.7 years of follow-up, 123 deaths). As compared to participants in the lowest quartile of baseline dietary GI, those in the highest quartile showed an increased risk of all-cause mortality [HR = 2.15 (95% CI: 1.15–4.04); P for trend = 0.012]. In the repeated-measures analyses using as exposure the yearly updated information on GI, we observed a similar association. Dietary GL was associated with all-cause mortality only when subjects were younger than 75 years. Conclusions High dietary GI was positively associated with all-cause mortality in elderly population at high cardiovascular risk.
Agent Design Considerations within Distributed Information Retrieval Systems

This paper presents the design and implementation of an agent society within the con nes of IBM s Aglet advanced programming interface speci cation The society exists with the sole purpose of nd ing MP s throughout a given network A sociohistorical context of the problem of nding MP s is provided The core design issues of agent tracking agent messaging social structure agent mobility methods and agent security are addressed and resolved An end user interface is es tablished along with a detailed discussion of design strategy
Identification of NTF2, a cytosolic factor for nuclear import that interacts with nuclear pore complex protein p62

Protein import into the nucleus is a multistep process that requires the activities of several cytosolic factors. In this study we have purified a cytosolic factor that interacts with the nuclear pore complex glycoprotein p62. Isolation involved biochemical complementation of cytosol depleted of this activity by preadsorption with recombinant p62 and the use of a novel flow cytometry-based assay for quantitation of nuclear import. The purified activity (NTF2) is an apparent dimer of approximately 14-kD subunits and is present at approximately 10(6) copies per cell. We obtained a cDNA encoding NTF2 and showed that the recombinant protein restores transport activity to p62-pretreated cytosol. Our data suggest that NTF2 acts at a relatively late stage of nuclear protein import, subsequent to the initial docking of nuclear import ligand at the nuclear envelope. NTF2 interacts with at least one additional cytosolic transport activity, indicating that it could be part of a multicomponent system of cytosolic factors that assemble at the pore complex during nuclear import.
Investigations on a Pedagogical Calculus of Constructions

In the last few years appeared pedagogical propositional natural deduction systems. In these systems, one must satisfy the pedagogical constraint: the user must give an example of any introduced notion. First we expose the reasons of such a constraint and properties of these "pedagogical" calculi: the absence of negation at logical side, and the "usefulness" feature of terms at computational side (through the Curry-Howard correspondence). Then we construct a simple pedagogical restriction of the calculus of constructions (CC) called CCr. We establish logical limitations of this system, and compare its computational expressiveness to Godel system T. Finally, guided by the logical limitations of CCr, we propose a formal and general definition of what a pedagogical calculus of constructions should be.
Playability in Action Videogames: A Qualitative Design Model

In the 1990s, the videogame industry has managed to become the fastest growing segment of the entertainment industry in America. However, only a very low number of videogame products manage to cover the costs of production and generate earnings. According to traditional marketing wisdom, players' preferences are a core issue in creating successful products, and the game design process is crucial for guaranteeing players' satisfaction. Then, an important question arises: What do players want in videogames? The purpose of this work is to propose a game design reference that directly mirrors players' preference, shaped as a qualitative model based on empirical data gathered during playing sessions. The model describes the main elements that, according to players' opinions, determine the playability of action videogames; the model proposes design guidelines that are the conceptualization of players' preferences. Therefore, the model helps game designers to understand the elements that must be dealt with to make better games. Besides the operational relevance of the model, the research methodology described in this work is an example of how a qualitative approach such as the grounded theory paradigm can be applied to solve a software specification problem directly focusing on end-users.
Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling

The idea of using common Poisson shock processes to model dependent event frequencies is well known in the reliability literature. In this paper we examine these models in the context of insurance loss modelling and credit risk modelling. To do this we set up a very general common shock framework for losses of a number of different types that allows for both dependence in loss frequencies across types and dependence in loss severities. Our aims are threefold: to demonstrate that the common shock model is a very natural way of approaching the modelling of dependent losses in an insurance or risk management context; to provide a summary of some analytical results concerning the nature of the dependence implied by the common shock specification; to examine the aggregate loss distribution that results from the model and its sensitivity to the specification of the model parameters.
Dynamic learning algorithm of multi-layer perceptrons for letter recognition

The classical back-propagation learning algorithms of neural networks suffer from a major disadvantage that of excessive computational burden encountered by processing all the data. Relatively speaking, the samples near the separating boundary have a more important influent on the final weights than those far. This paper presents a dynamic back-propagation algorithm which is just based on those decision boundary samples. The dynamic back-propagation algorithm using those boundary samples to update weights can not only greatly improve the learning speed, but also can improve the classification correction. The experimental results for the Letter data set verified that the proposed method is effective. It is far faster than classical learning algorithm and gets 91.1% classification correction.
Kernel Uncorrelated Local Fisher Discriminant Analysis and Its Application to Face Recognition

Local Fisher Discriminant Analysis (LFDA) achieves high performance for face recognition. However, LFDA is still a linear technique and usually deteriorates because the basis vectors of LFDA are statistically correlated. In this paper, we propose a Kernel Uncorrelated Local Fisher Discriminant Analysis (KULFDA), which can exploit the nonlinear and statistically uncorrelated features. A major advantage of the proposed method is that every column of the kernel matrix is regarded as a corresponding sample. Then nonlinear features can be extracted by performing ULFDA the in kernel matrix. Experimental results on ORL and YALE databases demonstrate the effectiveness of the proposed algorithm.
Implementation of configurable and multipurpose spiking neural networks on GPUs

In recent years, scientists and researchers have paid special attention to the implementation of Spiking Neural Networks (SNN), for approaching simulations of the human brain mechanisms, or to solve practical problems, such as epilepsy and seizure detection [1]. Nevertheless, large-scale SNN simulations are expensive from the computational point of view. These models quite often require the usage of parallel computing implementations on several devices[2], such as FPGAs [3], supercomputers [4], and recently on GPUs. Particularly on these last class of devices, a variety of techniques have been posed, like OpenGL pixel shade rendering [5], as well OpenCL and CUDA C/C++ [1], [6]. In this paper, we introduce a configurable large-scale fully parallel implementation that could well model a wide range of SNN using NVIDIA's GPU Common unified device architecture. Because of the achieved scalability, and flexibility in the definition of synaptic connections and neuron population, we show that our implementation shall be easily adapted as a back-end system for a wide variety of purposes. To examine some advantages of this implementation, we pose a comparative between Izhikevich's serialized program and our implementation using a large amount of neurons and synaptic connections. Also, as an additional experimental data, we report execution times, generated spikes and firing rates in a huge amount of neurons and a comparative between different neuron-synapse relations. We also achieved the simulation of 3.8×106 synaptic connections in real time (which is 1,000 time steps, one millisecond each, executed in one second). Finally, we demonstrated the increased performance on different hardware environments.
The 1997 American Diabetes Association and 1999 World Health Organization criteria for hyperglycemia in the diagnosis and prediction of diabetes.

OBJECTIVE The 1997 American Diabetes Association (ADA) and the 1985 and 1999 World Health Organization (WHO) criteria for diabetes and hyperglycemia differ. The appropriateness of these diagnostic criteria in terms of individuals identified as abnormal and their prognosis has been debated. The purpose of this study is to compare the classifications of people by these criteria and to compare fasting and postload plasma glucose concentrations in the prediction of diabetes. RESEARCH DESIGN AND METHODS The frequencies of diabetes by the 3 sets of criteria were compared in 5,023 adult Pima Indians not taking hypoglycemic drugs. Among nondiabetic subjects, fasting plasma glucose (FPG) and 2-h postload plasma glucose (2-h PG) concentrations and categories of impaired glucose regulation or diabetes were evaluated as predictors of diabetes defined by 1999 WHO criteria. RESULTS The frequency of diabetes was 12.5% by 1997 ADA criteria, 14.6% by 1985 WHO criteria, and 15.3% by 1999 WHO criteria. The incidence of diabetes was strongly related to higher FPG and 2-h PG, each of which had very similar predictive powers. Impaired glucose tolerance (IGT) was more common than impaired fasting glucose (IFG) (15 vs. 5%), but the 5-year incidence of diabetes was higher in IFG than IGT (37 vs. 24%). CONCLUSIONS The prevalence and incidence of diabetes are somewhat lower with the ADA criteria than with the 1985 or 1999 WHO criteria. The intermediate categories of glycemia differ substantially IFG defines a smaller number of people who are at higher risk of developing diabetes than those with IGT. More people at high risk of diabetes could be identified by using either IFG or IGT, as recommended by the 1999 WHO criteria, or by using the FPG concentration alone, but with a lower cutoff value.
Warm absorbers in active galactic nuclei

Recent {\it ASCA} observations confirm the presence of X-ray absorption due to partially ionized gas in many Seyfert 1 galaxies; the so-called warm absorber. Constraints on the location of the warm material are presented with the conclusion that this material lies at radii coincident with, or just outside, the broad-line region. The stability of this warm material to isobaric perturbations under the assumptions of thermal and photoionization equilibrium is also studied. It is shown that there is a remarkably small range of ionization parameter, $\xi$, for which the warm absorber state is stable. The robustness of this result to changes in the shape of the primary continuum, the assumed density and optical depth is investigated. Given the constraints on the location and the stability properties of the material, several models for the environments of Seyfert nuclei are discussed. These attempt to explain the presence of significant amounts of partially ionized material. In particular, various models of the broad-line region are discussed. The simple two-phase model of the broad-line region proves to be unsatisfactory. A model of the broad-line region is presented in which a turbulent, hot intercloud medium is mechanically heated. Turbulent mixing layers could then give rise to warm absorption features. Finally, a model is discussed in which the warm absorber is due to a steady state, radiatively driven outflow.