Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-analysis on the efficacy and tolerability of the augmentation of antidepressants with atypical antipsychotics in patients with major depressive disorder

We assessed the efficacy and tolerability of the augmentation of antidepressants (ATDs) with atypical antipsychotics (AAPs) to treat patients with major depressive disorder. A retrograde study to identify relevant patient data included databases of PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and Database of Abstracts of Reviews of Effects. Data from 17 trials, involving 3807 participants, were identified. The remission rate (RR) and overall response rate (ORR) of adjunctive treatment with AAPs were significantly higher than placebo treatment: RR=1.90 (95%CI=1.61-2.23, z=7.74, P<0.00001) and ORR=1.68 (95%CI=1.45-1.94, z=7.07, P<0.00001). We found that the short-term (4 weeks) treatment [ORR=1.70 (95%CI=0.98-2.95, Z=1.89, P=0.06)] was significantly different from the long-term (6-12 weeks) treatment [ORR=1.68 (95%CI=1.45-1.94, z=7.07, P<0.00001)]. No significant difference in ORR was observed between groups with or without sedative drugs. The discontinuation rate due to adverse effects was higher for adjunctive treatment with AAPs: ORR=3.32 (95%CI=2.35-4.70, z=6.78, P<0.00001). These results demonstrate that the augmentation of ATDs with AAPs (olanzapine, quetiapine, aripiprazole, and risperidone) was more effective than a placebo in improving response and remission rates, although associated with a higher discontinuation rate due to adverse effects.
Exploiting Explicit Annotations and Semantic Types for Implicit Argument Resolution

Following the frame semantics paradigm, we present a novel strategy for solving null-instantiated arguments. Our method learns probability distributions of semantic types for each Frame Element from explicit corpus annotations. These distributions are used to select the most probable missing implicit arguments together with its most probable fillers. We empirically demonstrate that our method outperforms the systems evaluated on the Sem Eval 2010 task 10 dataset.
The Dependence of Galaxy Colors on Luminosity and Environment at z ~ 0.4

We analyze the B - RC colors of galaxies as functions of luminosity and local galaxy density using a large photometric redshift catalog based on the Red-Sequence Cluster Survey. We select two samples of galaxies with a magnitude limit of M < -18.5 and redshift ranges of 0.2 ≤ z < 0.4 and 0.4 ≤ z < 0.6 containing ~105 galaxies each. We model the color distributions of subsamples of galaxies and derive the red galaxy fraction and peak colors of red and blue galaxies as functions of galaxy luminosity and environment. The evolution of these relationships over the redshift range of z ~ 0.5-0.05 is analyzed in combination with published results from the Sloan Digital Sky Survey. We find that there is a strong evolution in the rest-frame peak color of bright blue galaxies in that they become redder with decreasing redshift, while the colors of faint blue galaxies remain approximately constant. This effect supports the "downsizing" scenario of star formation in galaxies. While the general dependence of the galaxy color distributions on the environment is small, we find that the change of red galaxy fraction with epoch is a function of the local galaxy density, suggesting that the downsizing effect may operate with different timescales in regions of different galaxy densities.
A voting-based working set assessment scheme for dynamic cache resizing mechanisms

Considering the trade-off between performance and power consumption has become significantly important in multi-core processor design. Under this situation, one promising approach is to employ a power-aware dynamic cache partitioning mechanism. This mechanism individually manages activation of each cache way, and exclusively allocates the minimum number of required ways to each thread. In the mechanism, an appropriate number of ways for a thread is decided based on locality assessment. However, sampling results of cache accesses that are used for locality assessment are disturbed by exceptional behaviors of cache accesses, which happen in a very short period. Such sampling results may change locality assessment results to ones that are not along with the overall trend in a long access-sampling period. These assessment results will excessively adapt the cache to exceptional behaviors, and deteriorate energy efficiency. To avoid such excessive adaptation by the exceptional behaviors, this paper proposes a voting-based working set assessment scheme, in which the number of activated ways is adjusted based on majority voting of locality assessment of several short sampling periods. By using the majority voting, the proposed scheme can identify the periods including exceptional behaviors, and ignore the assessment results of these periods. As a result, the proposed scheme makes the cache resizing mechanism more stable and robust. The experimental results indicate that the proposed scheme can reduce energy consumption by up to 24%, and 10% on an average without significant performance degradation in multi-thread execution on a 2-core CMP.
Information Variables for Monetary Policy in a Small Structural Model of the Euro Area

This Paper estimates a small New-Keynesian model with imperfect information and optimal discretionary policy using data for the euro area. The model is used to assess the usefulness of monetary aggregates and unit labour costs as information variables for monetary policy. The estimates reveal that the information content of the M3 monetary aggregate is limited. A more useful role emerges for the unit labour costs indicator, which contains information that helps to reduce the volatility of the output gap. Finally, the estimated weights for the objectives of monetary policy indicate that considerable importance is attributed to interest-rate smoothing, greater than the importance attributed to the output gap stabilization. This finding indicates that the welfare gains of commitment may be smaller than is suggested by typical parameterizations of New-Keynesian models.
Recounting the Courts? Applying Automated Content Analysis to Enhance Empirical Legal Research

Political scientists in general and public law specialists in particular have only recently begun to exploit text classification using machine learning techniques to enable the reliable and detailed content analysis of political/legal documents on a large scale. This paper provides an overview and assessment of this methodology. We describe the basics of text classification, suggest applications of this technique to enhance empirical legal research (and political science more broadly), and report results of experiments designed to test the strengths and weaknesses of alternative text classification models for classifying the positions and interpreting the content of briefs submitted to the U.S. Supreme Court. We find that the Wordscores method (introduced by Laver, Benoit, et. al. 2003), and various models using a Naive Bayes classifier, perform well at accurately classifying the ideological direction of amicus curiae briefs submitted in the Bakke (1978) and Bollinger (2003) affirmative action cases. We also find that automated feature selection techniques can enable the detection of disparate issue conceptualizations by opposing sides in a single case, and facilitate analysis of relative linguistic "reliance" and "dominance" over time. We conclude by discussing the implications of our results and pointing to areas where technical and infrastructural improvement are most needed.
Shared Packages Through

This paper describes a method to implement the functionality of shared passive packages on top of a logical distributed memory — Linda. From a shared passive package a compiler can construct a new normal package that replaces the shared passive package. The new package contains the same subprograms and is extended with abstract data structures mapping Ada objects onto the storage units of Linda. A short program example is included to illustrate the construction process.
Robust gust load alleviation for a flexible aircraft

An ∞ controller design is presented to establish a nominal performance baseline for the vertical acceleration control of a B-52 aircraft model with flexibility. μ-synthesis and analysis is used to study the robust performance of the aircraft taking into account specific input and output multiplicative uncertainty models. The aircraft is assumed to be subjected to severe wind gusts causing undesirable vertical motion. We use the Dryden gust power spectral density model to guide the performance specifications and control designs, as well as for time-domain simulations. Motivation for the use of an ∞ ominal performance baseline specification is given in terms of a new interpretation of the Dryden model. The ∞ optimal controller is shown to reduce dramatically the effect of wind gust on the aircraft vertical acceleration. Robust performance is achieved with a μ-synthesis controller design using a D-K iteration procedure.
A framework for modelling spatially dependent interactions of biological systems in CCP

In this paper we show how to model biochemical reactions in Concurrent Constraint Programming (CCP) taking into account space and locality. In fact, in many cases, the distribution of the reactants in the cellular space is critical for the correct dynamics of the reactions. Thus, we propose a modelling framework which allows us to take into account space domains. Resorting on our approach, it is possible to de- scribe accurately biochemical processes without abstracting away from features related to the spatial localisation. In order to describe locality in CCP, we add subexponentials, a concept coming from linear logic, to the constraint system and then, we can model declaratively when a certain reaction occurs within one location of the space domain. Clearly we can also express interactions between agents, taking place either in dierent spaces or in the same space. Metabolic pathways and, in par- ticular, signalling pathways tend to be arranged in a physical space such that the product of one reaction is in the right place to become the re- actant for the subsequent reaction in the pathway. Following this idea, we show through a simple case study how we can model a signalling cascade. Then, we exploit our framework to model a more complex sig- nalling pathway, namely the TWEAK (TNF related Weak inducer of apoptosis), whose misfunctioning has implications in several important diseases.
Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization

This article describes a simulation model in which a multi-objective approach is utilized for evolving an artificial neural networks (ANNs) controller for an autonomous mobile robot. A mobile robot is simulated in a 3D, physics-based environment for the RF-localization behavior. The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. The generated controllers are evaluated on its performances based on Pareto analysis. Furthermore, the generated controllers are tested with four different environments particularly for robustness assessment. The testing environments are different from the environment in which evolution was conducted. Interestingly however, the testing results showed some of the mobile robots are still robust to the testing environments. The controllers allowed the robots to home in towards the signal source with different movements’ behaviors. This study has thus revealed that the PDE-EMO algorithm can be practically used to automatically generate robust controllers for RFlocalization behavior in autonomous mobile robots.
High-Quality Draft Genome Sequences of Pantoea agglomerans Isolates Exhibiting Antagonistic Interactions with Wheat Seed-Associated Fungi

ABSTRACT Pantoea agglomerans isolates 3 and 4 were retrieved from the bacterial community associated with wheat seeds. These isolates differ in their pattern of growth antagonism toward Alternaria species. A comparison of the genome sequences of these two isolates revealed a high sequence identity with previously sequenced strains of P. agglomerans.
Litigation in Spain 2001-2010: Exploring the Market for Legal Services

There is empirical evidence of a cross-country positive association between the number of lawyers per capita and the extent of litigation. For instance, Spain has more litigation and more lawyers per capita than most OECD countries. How should this association be interpreted? In this paper we analyse the variation in both variables across Spanish provinces during the period 2001-2010, by means of an instrumental variable approach, to shed some light on the sources of the statistical association between them. Finally, implications of the results are discussed.
Collagen VI deficiency reduces muscle pathology, but does not improve muscle function, in the γ-sarcoglycan-null mouse

Muscular dystrophy is characterized by progressive skeletal muscle weakness and dystrophic muscle exhibits degeneration and regeneration of muscle cells, inflammation and fibrosis. Skeletal muscle fibrosis is an excessive deposition of components of the extracellular matrix including an accumulation of Collagen VI. We hypothesized that a reduction of Collagen VI in a muscular dystrophy model that presents with fibrosis would result in reduced muscle pathology and improved muscle function. To test this hypothesis, we crossed γ-sarcoglycan-null mice, a model of limb-girdle muscular dystrophy type 2C, with a Col6a2-deficient mouse model. We found that the resulting γ-sarcoglycan-null/Col6a2Δex5 mice indeed exhibit reduced muscle pathology compared with γ-sarcoglycan-null mice. Specifically, fewer muscle fibers are degenerating, fiber size varies less, Evans blue dye uptake is reduced and serum creatine kinase levels are lower. Surprisingly, in spite of this reduction in muscle pathology, muscle function is not significantly improved. In fact, grip strength and maximum isometric tetanic force are even lower in γ-sarcoglycan-null/Col6a2Δex5 mice than in γ-sarcoglycan-null mice. In conclusion, our results reveal that Collagen VI-mediated fibrosis contributes to skeletal muscle pathology in γ-sarcoglycan-null mice. Importantly, however, our data also demonstrate that a reduction in skeletal muscle pathology does not necessarily lead to an improvement of skeletal muscle function, and this should be considered in future translational studies.
Searching for the in-plane Galactic bar and ring in DENIS

New evidence for a long thin Galactic bar (in contradistinction to the bulge), as well as for the existence of the ring and the truncation of the inner disc, are sought in the DENIS survey. First, we examine DENIS and Two Micron Galactic Survey star counts for the characteristic signatures of an in-plane bar and ring. The star counts in the plane for $30^\circ> l> -30^\circ$ are shown to be highly asymmetric with considerably more sources at positive than at negative longitudes. At $|b|\approx 1.5^\circ$, however, the counts are nearly symmetric. Therefore, the asymmetry is not due to the disc, which is shown to have an inner truncation, or to the bulge, so there has to be another major component in the inner Galaxy that is causing the asymmetries. This component provides up to 50% of the detected sources in the plane between the bulge and $l=27^\circ$ or $l=-14^\circ$. This component is shown to be consistent with an in-plane bar with a position angle of $40^\circ$ and half-length of 3.9 kpc. However, there is also a major peak in the counts at $l=-22^\circ$, which coincides with the tangential point of the so-called 3 kpc arm. This is shown to be most probably a ring or a pseudo-ring. The extinction in the plane is also shown to be asymmetric with more extinction at negative than at positive longitudes. For $l< 8^\circ$ the extinction is shown to be slightly tilted with respect to $b=0^\circ$ in the same manner as the HI disc. We conclude that the Galaxy is a fairly typical ringed barred spiral galaxy.
Logical winnowing methods from multiple identification candidates using corresponding appearance identification results in time-series

This paper describes logical winnowing methods from multiple identification candidates using corresponding appearance identification results with chronological pedestrian tracking results. It is difficult to identify individual using appearance identification, because appearance identification has some properties. This research proposes two methods that logically winnow out the identification candidates as methods that effectively fuse different directional identification results without the directional information. Experiments were made to verify the validity of the proposed methods. A mobile robot equipped with a laser scanner and a camera was used in the experiments. A pedestrian tracking method uses the laser scanner. The appearance identification uses the camera. The experimental results verified the validity of the logical winnowing method taking the logical product of identification candidates determined by each round of identification. In this paper, the appearance identification properties, the proposed methods and the experiments are described.
Efficient Moment Computation over Polygonal Domains with an Application to Rapid Wedgelet Approximation

Many algorithms in image processing rely on the computation of sums of pixel values over a large variety of subsets of the image domain. This includes the computation of image moments for pattern recognition purposes, or adaptive smoothing and regression methods, such as wedgelets. In the first part of the paper, we present a general method which allows the fast computation of sums over a large class of polygonal domains. The approach relies on the idea of considering polygonal domains with a fixed angular resolution, combined with an efficient implementation of a discrete version of Green’s theorem. The second part deals with the application of the new methodology to a particular computational problem, namely wedgelet approximation. Our technique results in a speedup of $O(10^3)$ by comparison to preexisting implementations. A further attractive feature of our implementation is the instantaneous access to the full scale of wedgelet minimizers. We introduce a new scheme that replaces the locally constant regression underlying wedgelets by basically arbitrary local regression models. Due to the speedup obtained by the techniques explained in the first part, this scheme is computationally efficient and at the same time much more flexible than previously suggested methods such as wedgelets or platelets. In the final section we present numerical experiments showing the increase in speed and flexibility.
Comparison of buspirone with diazepam and fluvoxamine on aversive classical conditioning in humans

The effects of buspirone, fluvoxamine and diazepam were investigated, using healthy volunteers, in an aversive conditioning paradigm, a putative model for conditioned anxiety. The main prediction was that buspirone, an anxiolytic agent which reduces activity in serotonin (5-hydroxytryptophan, 5-HT) neurones, would attenuate aversively conditioned skin conductance responses. Skin conductance responses were recorded to 10 neutral tones (habituation phase). Tone 11 was immediately followed by a 1-s 90-dB aversive white noise (unconditioned stimulus). The conditioning trial reinstated responding to a second presentation of the tones (extinction phase). Skin conductance response amplitude, inter-response level and spontaneous fluctuations were recorded. There were five treatment groups comprising five men and five women. One control group took placebo, another control group received nothing; there was no effect of placebo on any measure. Diazepam (2 mg, p.o.), a positive comparator, markedly reduced the amplitude of skin conductance responses at all phases of the experiment, but only in women. Buspirone (5 mg, p.o.) had the predicted effect of accelerating extinction but also of unexpectedly accelerated habituation of skin conductance responses. There was a trend to reduce spontaneous fluctuations and no effect on skin conductance level. The effects of buspirone were thus specific to responses to stimuli. Fluvoxamine (25 mg, p.o.) had similar effects to buspirone and diazepam in women. An action common to buspirone, fluvoxamine and diazepam, which may account for their shared effect on conditioned autonomic responses, is the suppression of neural activity in the dorsal raphe nucleus. It is argued that enhanced habituation must involve a different mechanism, such as enhanced 5-HTIA function in the terminal fields of the median raphe nucleus.
Internationalising the university: the Chinese context

Preface Acknowledgements Notes on Contributors Introduction: Cooperation with Chinese Universities - Issues and Trends P.Rastall Conceptions of Internationalisation and their Implications for Academic Engagement and Institutional Action: A Preliminary Case Study Y.Turner & S.Robson Chinese Universities' Motivations in Transnational Higher Education and their Implications for Higher Education Marketization L.Zheng The Internationalisation of Higher Education in China: The Case of One University J.Wang Global Connections - Local Impacts: Trends and Developments for Internationalism and Cross Border Higher Education D.Olcott Jr. Using Policy Initiatives to Support Both Learning Enhancement and Language Enhancement at a Hong Kong University C.Mcnaught & A.Curtis Cultivators, Cows and Computers:Chinese Learners' Metaphors of Teachers M.Cortazzi , L.Jin ,& W.Zhiru The Dissonance Between Insider and Outsider Perspectives of the 'Chinese Problem': Implications for one of the UK's Largest Undergraduate Programmes P.V. Smith & X.Zhou Decoding Students Value Orientations in Contemporary China S.Yang Overcoming Linguistic and Cultural Barriers to Integration: An Investigation of Two Models S.Devlin & N.Peacock Building on Experience: Meeting the Needs of Chinese Students in British Higher Education V.Edwards & A.Ran Chinese Learners and Interactive Learning W.Littlewood Afterword: Responses to Internationalisation in the UK and the International Context and a Survey on Responses to Intercultural Communication Teaching T.Coverdale-Jones Index
Discriminative Learning for Minimum Error Classification

Recently, due to the advent of artificial neural networks and learning vector quantizers, there is a resurgent interest in reexamining the classical techniques of discriminant analysis to suit the new classifier structures. One of the particular problems of interest is minimum error classification in which the misclassification probability is to be minimized based on a given set of training samples. In this paper, we propose a new formulation for the minimum error classification problem, together with a fundamental technique for designing a classifier that approaches the objective of minimum classification error in a more direct manner than traditional methods. We contrast the new method to several traditional classifier designs in typical experiments to demonstrate the superiority of the new learning formulation. The method can be applied to other classifier structures as well. Experimental results pertaining to a speech recognition task are also provided to show the effectiveness of the new technique.
Radial Velocity Jitter in Stars from the California and Carnegie Planet Search at Keck Observatory

I present an empirical model for predicting a star’s radial velocity jitter from its B - V color, activity level, and absolute magnitude. This model is based on observations of ∼450 well‐observed stars from Keck Observatory for the California and Carnegie Planet Search Program. The model includes noise from both astrophysical sources and systematic errors, and describes jitter as generally increasing with a star’s activity and height above the main sequence.