Miracle-dz/UniFAR-FTUs huggingface dataset:
The Investment-Cash Flow Sensitivity Puzzle: Can Negative Cash Flow Observations Explain It?

In a television receiver, a north-south pincushion correction circuit includes a switching transistor having a variable on-time controlled by a variable DC bias to phase shift a horizontal sawtooth coupled to a differential amplifier. A pair of diodes, coupled to the outputs of the differential amplifier, are maintained in the conduction region under control of a vertical sawtooth signal to generate a pincushion correction signal which is superimposed on the vertical sawtooth. The resultant is amplified by a vertical amplifier and drives vertical yoke coils to a sub-multiple of the horizontal sawtooth frequency.
The Research on Simulation Method of PHS Network Capacity Enlargement

High traffic always leads to descending quality of communication, higher lost call rate and increased complaints with the expansion of regional customer scale. Therefore, it is necessary to improve communication quality by enlarging the capacity of base station with the consideration of utilization efficiency of network resources. The difficulty of decision on PHS network capacity enlargement increases for the stochastic characteristic of traffic. The traffic and the base station capacity in a region are simulated by modeling and simulation experiment in this paper. Considering the economy in network resources, a reasonable enlargement plan is given after the effect comparison of different ones. The conclusion shows that multi-objective optimization plan, which also takes the stochastic characteristic of traffic into account, can be obtained by Monte Carlo simulation in the decision on PHS network capacity enlargement.
Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change

Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout across the interior western United States (1.01 million km2), based on empirical statistical models built from fish surveys at 9,890 sites. Projections under the 2080s A1B emissions scenario forecast a mean 47% decline in total suitable habitat for all trout, a group of fishes of major socioeconomic and ecological significance. We project that native cutthroat trout Oncorhynchus clarkii, already excluded from much of its potential range by nonnative species, will lose a further 58% of habitat due to an increase in temperatures beyond the species’ physiological optima and continued negative biotic interactions. Habitat for nonnative brook trout Salvelinus fontinalis and brown trout Salmo trutta is predicted to decline by 77% and 48%, respectively, driven by increases in temperature and winter flood frequency caused by warmer, rainier winters. Habitat for rainbow trout, Oncorhynchus mykiss, is projected to decline the least (35%) because negative temperature effects are partly offset by flow regime shifts that benefit the species. These results illustrate how drivers other than temperature influence species response to climate change. Despite some uncertainty, large declines in trout habitat are likely, but our findings point to opportunities for strategic targeting of mitigation efforts to appropriate stressors and locations.
Multicomponent Signal Processing for Rayleigh Wave Ellipticity Estimation: Application to Seismic Hazard Assessment

Dispersion curves of surface waves, i.e., the wave velocity as a function of frequency, are largely used in seismology to invert for the soil structure, i.e., the shear (and pressure) wave velocity profile as a function of depth. In addition to the dispersion curve, Rayleigh waves (one of the two most important types of seismic surface waves) exhibit a second property that is directly linked to the soil structure: ellipticity. This parameter indicates the ratio between the horizontal and vertical axes of the elliptical wave motion of Rayleigh waves and is also a function of frequency. Although some early applications of ellipticity measurements date back to the 1960s, it is only recently that this parameter has gained more attention, leading to the development of new methods allowing its estimation. These methods include single sensor and array vector-sensor processing techniques. The ellipticity can be inverted for the soil structure, an important property for the estimation of the seismic hazard at a given site. In this article, we will give an overview of the newly developed methods and compare their respective performances by analyzing simulated seismic signals.
Study on Music Emotion Cognition Model Based on Applying the Improved Gene Expression Programming

This paper proposes a music emotion cognition model by applying the improved genetic algorithm with dynamic mutation operator. Firstly, a Hevner emotion ring representing the music emotion space is presented by utilizing psychological fuzzy measure on words in music psychology. Secondly, the music emotion vector is introduced based on semantic similarity relation in computing with words. Then the mapping from high dimensional feature space of music to emotion space is built by using the genetic algorithm which can mine the emotion expressions. Finally the comparisons with some famous learning algorithms such as BP neural network, regression method with least square, show that the proposed method is effective for music emotion cognition.
Automated epileptic seizure detection using relevant features in support vector machines

Automatic seizure detection is very essential for monitoring and rehabilitation of epilepsy patients and will open up new treatment possibilities for saving the lives of epileptic patients. In recent years, many algorithms for the automatic seizure detection have been proposed and applied, in which Support vector machines proved to be a robust machine learning algorithm. The purpose of this study is to compute relevant EEG features and apply a feature selection algorithm to select an optimum set of features for use in a classification scheme for epileptic seizure detection. Thus S VM will thereby yield a better accuracy compared to other algorithms. Effective features such as energy, relative amplitude, standard deviation, coefficient of variation, fluctuation index etc are selected and then these features are fed into the support vector machine for training and classification. This algorithm makes use of Radial Basis Function Kernels for training data and thus obtains more accurate results.
A statistical algorithm for multi-objective handover optimization under uncertainties

The mobility robustness optimization (MRO) problem in LTE self-organizing networks (SON) is a multi-objective optimization problem; it involves a set of non-convex contradicting objective functions that depend on multiple variables such as handover (HO) parameters and user mobility classes. This paper exploits the framework of stochastic processes to develop a novel method of successively choosing a sequence of multi-variate training points for multi-objective optimization. Combined with the collected statistics and a priori knowledge, the proposed method is used in the design of an efficient MRO algorithm. The performance of the algorithm is evaluated by simulations to illustrate significant improvements with respect to both HO-related ratio link failures (RLFs) and unnecessary HOs.
Managerial Effectiveness in a Global Context.

In the past decade an increasing number of international managers from multinational organizations have participated in development programs at the Center for Creative Leadership. These managers work across the borders of multiple countries simultaneously. Working with these managers led us to ask fundamental questions about our current understanding of managerial effectiveness and whether or not it applied to managers who work in an increasingly complex global world. We asked ourselves: What do these managers do? Is it different from the work they did when they managed in their own countries, and if it is different, how so? What does it take for them to be effective when they manage across so many countries simultaneously? What do these managers need to know in order to be effective? What do organizations need to know and do in order to select and develop people who will manage and lead effectively in the global economy? Research designed to answer those questions provides insight into the work of global managers.
Non-Invasive Detection of Coronary Endothelial Response to Sequential Handgrip Exercise in Coronary Artery Disease Patients and Healthy Adults

Objectives Our objective is to test the hypothesis that coronary endothelial function (CorEndoFx) does not change with repeated isometric handgrip (IHG) stress in CAD patients or healthy subjects. Background Coronary responses to endothelial-dependent stressors are important measures of vascular risk that can change in response to environmental stimuli or pharmacologic interventions. The evaluation of the effect of an acute intervention on endothelial response is only valid if the measurement does not change significantly in the short term under normal conditions. Using 3.0 Tesla (T) MRI, we non-invasively compared two coronary artery endothelial function measurements separated by a ten minute interval in healthy subjects and patients with coronary artery disease (CAD). Methods Twenty healthy adult subjects and 12 CAD patients were studied on a commercial 3.0 T whole-body MR imaging system. Coronary cross-sectional area (CSA), peak diastolic coronary flow velocity (PDFV) and blood-flow were quantified before and during continuous IHG stress, an endothelial-dependent stressor. The IHG exercise with imaging was repeated after a 10 minute recovery period. Results In healthy adults, coronary artery CSA changes and blood-flow increases did not differ between the first and second stresses (mean % change ±SEM, first vs. second stress CSA: 14.8%±3.3% vs. 17.8%±3.6%, p = 0.24; PDFV: 27.5%±4.9% vs. 24.2%±4.5%, p = 0.54; blood-flow: 44.3%±8.3 vs. 44.8%±8.1, p = 0.84). The coronary vasoreactive responses in the CAD patients also did not differ between the first and second stresses (mean % change ±SEM, first stress vs. second stress: CSA: −6.4%±2.0% vs. −5.0%±2.4%, p = 0.22; PDFV: −4.0%±4.6% vs. −4.2%±5.3%, p = 0.83; blood-flow: −9.7%±5.1% vs. −8.7%±6.3%, p = 0.38). Conclusion MRI measures of CorEndoFx are unchanged during repeated isometric handgrip exercise tests in CAD patients and healthy adults. These findings demonstrate the repeatability of noninvasive 3T MRI assessment of CorEndoFx and support its use in future studies designed to determine the effects of acute interventions on coronary vasoreactivity.
ViSMA: extendible, mobile-agent based services for the materialization and maintenance of personalized and shareable Web views

ViSMA (Views Supported by Mobile Agents) is a prototype set of extendible mobile-agent based services that allow the definition, materialization, maintenance and sharing of views created over remote Web-accessible databases. The system's primary goal is to support mobile clients carrying lightweight devices of various connectivity and resources such as portable computers and PDAs by being completely deployed over mobile agent technology. In this paper we propose a multi-tier architecture on which the system is built and we present the system's features, which include view mobility, shareable and personalized view creation and customizable, automated view monitoring and updating. The system has been fully implemented and tested using three alternative client types.
SNR-dependent mixture of PLDA for noise robust speaker verification

This paper proposes a mixture of SNR-dependent PLDA models to provide a wider coverage on the i-vector spaces so that the resulting i-vector/PLDA system can handle test utterances with a wide range of SNR. To maximise the coordination among the PLDA models, they are trained simultaneously via an EM algorithm using utterances contaminated with noise at various levels. The contribution of a training i-vector to individual PLDA models is determined by the posterior probability of the ut-terance’s SNR. Given a test i-vector, the marginal likelihoods from individual PLDA models are linear combined based on the the posterior probabilities of the test utterance and the target-speaker’s utterance. Veriﬁcation scores are the ratio of the marginal likelihoods. Results based on NIST 2012 SRE sug-gest that this soft-decision scheme is particularly suitable for the situations where the test utterances exhibit a wide range of SNR.
An Efficient Boosting Algorithm for Combining Preferences

We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences arises in several applications, such as that of combining the results of different search engines, or the “collaborative-ﬁltering” problem of ranking movies for a user based on the movie rankings provided by other users. In this work, we begin by presenting a formal framework for this general problem. We then describe and analyze an efﬁcient algorithm called RankBoost for combining preferences based on the boosting approach to machine learning. We give theoretical results describing the algorithm’s behavior both on the training data, and on new test data not seen during training. We also describe an efﬁcient implementation of the algorithm for a particular restricted but common case. We next discuss two experiments we carried out to assess the performance of RankBoost. In the ﬁrst exper-iment, we used the algorithm to combine different web search strategies, each of which is a query expansion for a given domain. The second experiment is a collaborative-ﬁltering task for making movie recommendations.
Feature preserving holes filling of scattered point cloud based on tensor voting

This paper presented a novel holes filling method for the scattered point cloud, particularly for recovering the missing points at featured curves or corners. Firstly, hole-boundary point and feature point were extracted to determine the incomplete feature curves. According to these two point sets, the holes were categorized into two types, featured holes and non-featured holes. Secondly, tensor voting was used to restore the missing feature points of the incomplete feature curves. Accordingly, original holes were divided into sub-holes without missing feature. Finally, all the non-featured holes were filled by the tensor voting. Experimental results show that the proposed method could accurately and effectively restore the original shape of the hole including the sharp features.
Modeling Vocal Interaction for Text-Independent Classification of Conversation Type

We describe a system for conversation type classification which relies exclusively on multi-participant vocal activity patterns. Using a variation on a well-studied model from stochastic dynamics, we extract features which represent the transition probabilities that characterize the evolution of participant interaction. We also show how vocal interaction can be modeled between specific participant pairs. We apply the proposed system to the task of classifying meeting types in a large multi-party meeting corpus, and achieve a three-way classification accuracy of 84%. This represents a relative error reduction of more than 50% over a baseline which uses only individual speaker times (i.e. no interaction dynamics). Random guessing on this data yields an accuracy of 43%.
Reengineering the Systems Development Process for User Centred Design

Have you ever been frustrated with that IT system at work that does not behave the way you expect it to? Or had problems with using the features on your new mobile phone? When systems and appliances do not support us in what we are doing, and do not behave the way we expect them to, then usability is neglected. Poor usability may be frustrating and irritating when trying out your mobile phone, but in a critical work situation poor usability may be disastrous.In this thesis, user-centred systems design (UCSD) is advocated as an approach for facilitating the development of usable interactive systems. Systems that suit their intended use and users do not just “emerge”. They are the result of a UCSD process and a user-centred attitude during the development. This means in short that the real users and their needs, goals, context of use, abilities and limitations, drive the development – in contrast to technology-driven development. We define UCSD as: a process focusing on usability throughout the entire development process and further throughout the system life cycle. I argue that this definition along with a set of key principles do help organisations and individual projects in the process of developing usable interactive systems. The key principles include the necessity of having an explicit focus on users and making sure that users are actively involved in the process.The thesis provides knowledge and insights gained from real-life situations about what UCSD is and how it can be put into practice. The most significant results are: the proposal of a clear definition of UCSD and a set of key principles encompassing UCSD; a process for usability design and the usability designer role. Furthermore, design cases from different domains are provided as examples and illustrations.
Bartonella and intraocular inflammation: a series of cases and review of literature

Purpose: To present various forms of uveitis and/or retinal vasculitis attributed to Bartonella infection and review the impact of this microorganism in patients with uveitis. Methods: Retrospective case series study. Review of clinical records of patients diagnosed with Bartonella henselae and Bartonella quintana intraocular inflammation from 2001 to 2010 in the Ocular Inflammation Department of the University Eye Clinic, Ioannina, Greece. Presentation of epidemiological and clinical data concerning Bartonella infection was provided by the international literature. Results: Eight patients with the diagnosis of Bartonella henselae and two patients with B. quintana intraocular inflammation were identified. Since four patients experienced bilateral involvement, the affected eyes totaled 14. The mean age was 36.6 years (range 12–62). Uveitic clinical entities that we found included intermediate uveitis in seven eyes (50%), vitritis in two eyes (14.2%), neuroretinitis in one eye (7.1%), focal retinochoroiditis in one eye (7.1%), branch retinal vein occlusion (BRVO) due to vasculitis in one eye (7.1%), disc edema with peripapillary serous retinal detachment in one eye (7.1%), and iridocyclitis in one eye (7.1%). Most of the patients (70%) did not experience systemic symptoms preceding the intraocular inflammation. Antimicrobial treatment was efficient in all cases with the exception of the case with neuroretinitis complicated by anterior ischemic optic neuropathy and tubulointerstitial nephritis. Conclusion: Intraocular involvement caused not only by B. henselae but also by B. quintana is being diagnosed with increasing frequency. A high index of suspicion is needed because the spectrum of Bartonella intraocular inflammation is very large. In our study the most common clinical entity was intermediate uveitis.
Evaporation of Compact Young Clusters near the Galactic Center

We investigate the dynamical evolution of compact young clusters (CYCs) near the Galactic center (GC) using Fokker-Planck models. CYCs are very young (<5 Myr), compact (<1 pc), and only a few tens of parsecs away from the GC, while they appear to be as massive as the smallest Galactic globular clusters (~104 M☉). A survey of cluster lifetimes for various initial mass functions, cluster masses, and Galactocentric radii is presented. Short relaxation times due to the compactness of CYCs and the strong tidal fields near the GC make clusters evaporate fairly quickly. Depending on cluster parameters, mass segregation may occur on a timescale shorter than the lifetimes of most massive stars, which accelerates the cluster's dynamical evolution even more. When the difference between the upper and lower mass boundaries of the initial mass function is large enough, strongly selective ejection of lighter stars makes massive stars dominate even in the outer regions of the cluster, so the dynamical evolution of those clusters is weakly dependent on the lower mass boundary. The mass bins for Fokker-Planck simulations were carefully chosen to properly account for a relatively small number of the most massive stars. We find that clusters with a mass ≲2 × 104 M☉ evaporate in ≲10 Myr. Two CYCs observed near the GC—the "Arches cluster" (G0.121+0.17) and the "Quintuplet cluster" (AFGL 2004)—are interpreted in terms of the models; their central densities and apparent ages are consistent with the hypothesis that they represent successive stages of cluster evolution along a common track, with both undergoing rapid evaporation. A simple calculation based on the total masses in observed CYCs and the lifetimes obtained here indicates that the massive CYCs make up only a fraction of the star formation rate (SFR) in the inner bulge estimated from Lyman continuum photons and far-IR observations. This is consistent with the observation that many stars in the inner bulge form outside the large clusters.
Exploring information theory for vision-based volumetric mapping

This article presents an innovative probabilistic approach for building volumetric maps of unknown environments with autonomous mobile robots, which is based on information theory. Each mobile robot uses an entropy gradient-based exploration strategy, with the aim of maximizing information gain when building and improving a 3D map upon measurements yielded by an on-board stereo-vision sensor. The proposed framework was validated through experiments with a real mobile robot equipped with stereo-vision, in order to be further used on cooperative volumetric mapping with teams of mobile robots.
Reciprocal effects of health and economic well-being among older adults in Taiwan and Beijing.

The objectives of this study are threefold: 1) to examine whether socioeconomic status disparities in health are found in non-Western settings; 2) to assess whether socioeconomic status gradients in health endure into older ages; and 3) to evaluate the direction of causality between health and socioeconomic status. Using data from multiple waves of two longitudinal panel studies of older adults: the Survey of Health and Living Status of the Elderly in Taiwan (1993 1996 1999) and the Beijing Multidimensional Longitudinal Study of Aging (1992 1994 1997) the paper employs structural equation models to test hypotheses concerning cross-lagged and reciprocal influences between economic well-being and health. Findings provide evidence for reciprocal effects of economic well-being and health among older adults in both Taiwan and Beijing. Those with higher levels of economic well-being have lower levels of functional limitation over time and those with higher levels of functional limitation have lower levels of economic well-being over time. Consistent with studies based in the United States and Europe findings from Asia indicate economic differentials in functional health among older adults highlighting the wider applicability of these associations across settings with very different systems of health care and stratification. Results underscore the importance of considering reciprocal influences in studies of socioeconomic status and health. (authors)