Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceiving question intonation : the delayed focal

This paper presents the results of a perception experiment designed to investigate the contribution of a pre-focal hesitation pause, delayed focal peak and a raised F0 range for signaling interrogative mode in Swedish. The results are consistent with a previous study which demonstrated that a delayed peak combined with a raised F0 range can effectively signal interrogative mode in Swedish echo questions. In addition, the present study supports the hypothesis that the presence of a pre-focal hesitation pause strengthens the interpretation of a focal peak delay as signaling question intonation. The results are discussed in terms of a framework of biological codes for universal meanings of intonation proposed by Gussenhoven. An additional biological code is proposed on a behavioral level where cognitive loading results in a hesitation pause or dysfluency which is perceived as non-assertiveness.
Shape Recovery from Multiple Views: A Parallax Based Approach

Given two arbitrary views of a scene under central projection, if the motion of points on a parametric surface is compensated, the residual parallax displacement eld on the reference image is an epipolar eld. The parallax magnitude at a point, after suitable scaling, is an a ne invariant; if the surface aligned is a plane, it is directly proportional to the height of the point from the plane and inversely proportional to its depth from the camera. We exploit the above result to infer 3D height information from oblique aerial 2D images. We use direct methods to register the aerial images, develop methods to infer height information under the following three conditions: (i) focal length and image center are both known, (ii) only the focal length is known, and (iii) both are unknown. We use the invariance property of the scaled parallax magnitudes to combine multiple frame information to obtain accurate heights, and to extrapolate new views from a given set of views (i.e., in photogrammetric terms, to achieve \transfer"). We use the view extrapolation process to construct a panoramic mosaic image by combining multiple views that is accurate in terms of 3D positions of surfaces.
Lagrangian dynamic SGS model for stochastic coherent adaptive large eddy simulation

Stochastic coherent adaptive large eddy simulation (SCALES) is an extension of large eddy simulation that uses a wavelet filter-based dynamic grid adaptation strategy to solve for the most energetic coherent structures in a turbulent flow field, while modeling the effect of the less energetic ones. A localized dynamic subgrid scale model is needed to fully exploit the ability of the method to track coherent structures. In this paper, new local Lagrangian models based on a modified Germano dynamic procedure, redefined in terms of wavelet thresholding filters, are proposed. These models extend the original path-line formulation of Meneveau et al. [J. Fluid Mech. 319 (1996)] in two ways: as Lagrangian path-line diffusive and Lagrangian path-tube averaging procedures. The proposed models are tested for freely decaying homogeneous turbulence with initial Re λ = 72. It is shown that the SCALES results, obtained with less than 0.4% of the total non-adaptive nodes required for a DNS with the same wavelet solver, closely match reference DNS data. In contrast to classical LES, this agreement holds not only for large scale global statistical quantities, but also for energy and, more importantly, enstrophy spectra up to the dissipative wavenumber range.
Mögliche Persönlichkeitsveränderungen bei Parkinson-Patienten

Ethische Fragen zur tiefen Hirnstimulation (THS) werden seit einigen Jahren von Medizinethikern diskutiert; allerdings steht dabei deren Anwendung für psychiatrische Erkrankungen im Fokus (1, 2), nicht jene für Morbus Parkinson oder essenzielle Dystonie. Der Grund dafür ist möglicherweise, dass die Möglichkeit einer direkten Veränderung psychischer Funktionen durch einen physischen Eingriff in das Gehirn als ethisch brisanter angesehen wird, als wenn solche Veränderungen als Nebenwirkung resultieren. Tatsächlich lässt sich die Anwendung der THS für psychiatrische Erkrankungen als konsequente Weiterentwicklung ihrer Anwendung bei Morbus Parkinson verstehen. Denn zum einen betrifft diese Erkrankung nicht nur die Motorik, sondern auch kognitive, affektive und behaviorale Funktionen, deren therapeutische Verbesserung ebenfalls angestrebt wird. Zum anderen legen psychische Veränderungen, die nach THS bei ParkinsonPatienten beobachtet werden können, die Hypothese nahe, dass THS auch bei psychiatrischen Erkrankungen anderer Genese wirksam sein könnte. Im Folgenden untersuchen wir ethische Fragen der THS des Nucleus subthalamicus (STN, das heutzutage bevorzugte target des Eingriffs) bei Parkinson-Patienten, die aus THS-induzierten psychischen Veränderungen entstehen. Dabei fokussieren wir vor allem auf die Schwierigkeiten, emotionale, verhaltensmäßige und soziale Folgen der Therapie zu identifizieren und zwischen krankheitsund therapiebedingten Folgen zu unterscheiden.
PSYCHOLOGICAL WELL-BEING OF VOLUNTEER TEACHER TRAINERS IN THE REMOTE AREA IN INDONESIA

Indonesia is a wide country and it consists of thousands of islands. This condition makes many regions in Indonesia do not get the proper educational facilities. In addition, the quality of teachers in the remote areas is still poor. People who concern with the condition of education in the remote areas are still rare because of the limited access and high cost to get there. However, there is one group of volunteers who care about the condition of education in the remote areas of Indonesia called RUBI (Ruang Berbagi Ilmu). RUBI is a voluntary movement of professionals that focus on improving teachers' competence in the remote areas. The purpose of this study was to explore the motivation of the volunteer and to understand how the dynamics of the volunteers in achieving psychological well-being. The research was conducted by a qualitative method using phenomenology approach. The respondents in this study were professionals who had already traveled to remote areas to become a volunteer teacher trainer. The results of this study indicated that becoming volunteer requires a lot of sacrifices, such as material and time. In addition, being a volunteer also has great challenges because they have to adapt to a new environment. However, despite these sacrifices and inconveniences, many volunteers feel addicted to get involved in this activity. There are many benefits perceived as volunteers such as 1) increasing insight and knowledge from any source and any region, 2) developing their competence, 3) gaining inner satisfaction and meaningful life, 4) becoming more widespread the social relations, and 5) becoming more positive and more grateful. In general, being volunteers in the remote area has affected the six dimensions of psychological well-being, that is self-acceptance, positive relationships with others, autonomy, environmental mastery, purpose in life, and personal growth. The dynamics of psychological well-being of the volunteer trainers are discussed further in this paper.
Performance boundaries of massive Floating Car Data offloading

Floating Car Data (FCD) consist of information generated by moving vehicles and uploaded to Internet-based control centers for processing and analysis. As upcoming mobile services based on or built for networked vehicles largely rely on uplink transfers of small-sized but high-frequency messages, FCD traffic is expected to become increasingly common in the next few years. Presently, FCD are managed through a traditional cellular network paradigm: however, the scalability of such a model is unclear in the face of massive FCD upload, involving large fractions of the vehicles over short time intervals. In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to partially relieve the cellular infrastructure from FCD traffic. Specifically, we study the performance boundaries of such a FCD offloading approach in presence of best- and worst-case data aggregation possibilities at vehicles. We show the gain that can be obtained by offloading FCD via vehicular communication, and propose a simple distributed heuristic that has nearly optimal performance under any FCD aggregation model.
A hybrid pose / wrench control framework for quadrotor helicopters

This paper presents a hybrid pose / wrench control framework for quadrotor helicopters, allowing direct contact of the quadrotor with its environment and stable motion while in contact. The presented work explicitly takes into account the quadrotor's underactuation and utilizes a wrench estimator, able to estimate the wrench generated by the quadrotor using only quadrotor inputs and pose measurements. Experimental results of the quadrotor in pose and hybrid pose-wrench control mode are presented, showing stable behaviour while moving in contact. Whereas a lot of research nowadays is focused mainly on free-flight applications, stable and robust wrench control of quadrotors in direct contact with their environment, opens up new application areas for this class of flying robots.
A ROBUST MODEL FOR GENE ANLYSIS AND CLASSIFICATION

The development of microarray gene technology has provided a large volume of data to many fields. Microarray data analysis and classification has demonstrated an effective methodology for the effective diagnosis of diseases and cancers. Although much research has been performed on applying machine learning techniques for microarray data classification during the past years, it has been shown that conventional machine learning techniques have intrinsic drawbacks in achieving accurate and robust classifications. So it is more desirable to make a decision by combining the results of various expert classifiers rather than by depending on the result of only one classifier. We address the microarray dataset based cancer classification using a newly proposed ensemble classifier generation technique referred to as RotBoost, which is constructed by combining Rotation Forest and AdaBoost. The experiments conducted with 8 microarray datasets, among which a classification tree is adopted as the base learning algorithm, demonstrate that RotBoost can generate ensemble classifiers with significantly lower prediction error than either Rotation Forest or AdaBoost more often than the reverse.
Neuropsychological sequelae of obstructive sleep apnea-hypopnea syndrome: A critical review

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a well-recognized clinical sleep disorder that results in chronically fragmented sleep and recurrent hypoxemia. The primary daytime sequelae of the disorder include patient reports of excessive daytime sleepiness, depression, and attention and concentration problems. It has been well established that OSAHS negatively impacts certain aspects of cognitive functioning. The primary goals of this article are to (1) clarify the pattern of cognitive deficits that are specific to OSAHS; (2) identify the specific cognitive domains that improve with treatment; and (3) elucidate the possible mechanisms of cognitive dysfunction in OSAHS. At the conclusion of the paper, we propose a potential neurofunctional theory to account for the etiology of cognitive deficits in OSAHS. Thirty-seven peer-reviewed articles were selected for this review. In general, findings were equivocal for most cognitive domains. Treatment, however, was noted to improve attention/vigilance in most studies and consistently did not improve constructional abilities or psychomotor functioning. The results are discussed in the context of a neurofunctional theory for the effects of OSAHS on the brain. (JINS, 2004, 10, 772–785.)
ASYMPTOTIC FIRST EXIT TIMES OF THE CHAFEE-INFANTE EQUA- TION WITH SMALL HEAVY-TAILED LÉVY NOISE

Abstract This article studies the behavior of stochastic reaction-diffusion equations driven by additive regularly varying pure jump Lévy noise in the limit of small noise intensity. It is shown that the law of the suitably renormalized first exit times from the domain of attraction of a stable state converges to an exponential law of parameter 1 in a strong sense of Laplace transforms, including exponential moments. As a consequence, the expected exit times increase polynomially in the inverse intensity, in contrast to Gaussian perturbations, where this growth is known to be of exponential rate.
Bacteroides fragilis Lipopolysaccharide and Inflammatory Signaling in Alzheimer’s Disease

The human microbiome consists of ~3.8 × 1013 symbiotic microorganisms that form a highly complex and dynamic ecosystem: the gastrointestinal (GI) tract constitutes the largest repository of the human microbiome by far, and its impact on human neurological health and disease is becoming increasingly appreciated. Bacteroidetes, the largest phylum of Gram-negative bacteria in the GI tract microbiome, while generally beneficial to the host when confined to the GI tract, have potential to secrete a remarkably complex array of pro-inflammatory neurotoxins that include surface lipopolysaccharides (LPSs) and toxic proteolytic peptides. The deleterious effects of these bacterial exudates appear to become more important as GI tract and blood-brain barriers alter or increase their permeability with aging and disease. For example, presence of the unique LPSs of the abundant Bacteroidetes species Bacteroides fragilis (BF-LPS) in the serum represents a major contributing factor to systemic inflammation. BF-LPS is further recognized by TLR2, TLR4, and/or CD14 microglial cell receptors as are the pro-inflammatory 42 amino acid amyloid-beta (Aβ42) peptides that characterize Alzheimer’s disease (AD) brain. Here we provide the first evidence that BF-LPS exposure to human primary brain cells is an exceptionally potent inducer of the pro-inflammatory transcription factor NF-kB (p50/p65) complex, a known trigger in the expression of pathogenic pathways involved in inflammatory neurodegeneration. This ‘Perspectives communication’ will in addition highlight work from recent studies that advance novel and emerging concepts on the potential contribution of microbiome-generated factors, such as BF-LPS, in driving pro-inflammatory degenerative neuropathology in the AD brain.
A simple extraction procedure for determining the electrical parameters in Silicon Photomultipliers

The Silicon Photomultiplier (SiPM) is a promising kind of device able to handle single photons thus permitting the measurement of weak optical signals. The design of a highperformance front-end electronics for the read-out, requires an accurate electrical model of the SiPM. A reliable model was developed in the past but the parameter extraction procedure is rather cumbersome and requires several measurement steps. In this communication we present a simple extraction procedure that can be performed with two simple measurement steps. The extraction procedure is applied to a 10×10 SiPM and is validated by comparing the equivalent spice model to measurement results.
Atmospheric Analysis of the M/L- and M/T-Dwarf Binary Systems LHS 102 and Gliese 229

We present 0.9–2.5 μm spectroscopy with R∼800 and 1.12–1.22 μm spectroscopy with R∼5800 for the M dwarfs Gl 229A and LHS 102A, and for the L dwarf LHS 102B. We also report IZJHKL′ photometry for both components of the LHS 102 system, and L′ photometry for Gl 229A. The data are combined with previously published spectroscopy and photometry to produce flux distributions for each component of the kinematically old disc M/L dwarf binary system LHS 102 and the kinematically young disc M/T dwarf binary system Gliese 229. The data are analysed using synthetic spectra generated by the latest ‘AMES-dusty’ and ‘AMES-cond’ models by Allard & Hauschildt. Although the models are not able to reproduce the overall slope of the infrared flux distribution of the L dwarf, most likely because of the treatment of dust in the photosphere, the data for the M dwarfs and the T dwarf are well matched. We find that the Gl 229 system is metal-poor despite having kinematics of the young disc, and that the LHS 102 system has solar metallicity. The observed luminosities and derived temperatures and gravities are consistent with evolutionary model predictions if the Gl 229 system is very young (age∼30 Myr) with masses (A,B) of (0.38,≳0.007) M⊙, and the LHS 102 system is older, aged 1–10 Gyr with masses (A,B) of (0.19,0.07) M⊙.
Drosophila song as a species-specific mating signal and the behavioural importance of Kyriacou & Hall cycles in D.melanogaster song

'Species-specific' mating signals may not make a significant contribution to sexual isolation if differences between species are not matched by narrowly tuned differences in female preferences. The courtship song of the melanogaster species group of Drosophila has been studied by several researchers as a potential factor in sexual isolation, but there are few clear demonstrations that species differences are behaviourally significant. We played synthetic song with typical pulse interval parameters for D. melanogaster, D. simulans or D. sechellia to D. melanogaster or D. simulans females in the presence of mute males. Females mated most quickly when stimulated by song typical of their own species, confirming that song can influence sexual isolation between these species. This effect was greater in D. melanogaster than D. simulans, which correlates with reduced variability in mean interpulse interval within D. melanogaster. We also examined the role of 'Kyriacou & Hall cycles' (periodic cycling of mean interpulse intervals) in D. melanogaster. Contrary to some predictions, the presence of the Kyriacou & Hall cycle was more important in increasing mating speed than the increased variability of interpulse intervals that is inevitably present in song containing a cycle. The large stimulatory effect of cycles on mating speed is curious, given that the periodicity of cycles would probably be difficult for females to detect during courtship in field conditions. Copyright 1999 The Association for the Study of Animal Behaviour.
Variational Belief Networks forApproximate

Exact inference in large, densely connected probabilistic networks is computationally intractable, and approximate schemes are therefore of great importance. One approach is to use mean eld theory, in which the exact log-likelihood is bounded from below using a simpler approximating distribution. In the standard mean eld theory, the approximating distribution is factorial. We propose instead to use a (tractable) belief network as an approximating distribution. The resulting compact framework is analogous to standard mean eld theory and no additional bounds are required, in contrast to other recently proposed extensions. We derive mean eld equations which provide an ecient iterative algorithm to optimize the parameters of the approximating belief network. Simulation results indicate a considerable improvement on previously reported methods.
Estimating out-of-sample pointwise predictive accuracy using posterior simulations

The Watanabe-Akaike information criterion (WAIC) and cross-validation are methods for estimating pointwise out-of-sample prediction accuracy from a fitted Bayesian model. WAIC is based on the series expansion of leave-one-out cross-validation (LOO), and asymptotically they are equal. With finite data, WAIC and cross-validation address different predictive questions and thus it is useful to be able to compute both. WAIC and an importance-sampling approximated LOO can be estimated directly using the log-likelihood evaluated at the posterior simulations of the parameter values. We show how to compute WAIC, IS-LOO, K-fold cross-validation, and related diagnostic quantities in the Bayesian inference package Stan as called from R.
Channel estimation in MIMO-OFDM systems based on comparative methods by LMS algorithm

In mobile telecommunication systems, a channel estimating method which is able to follow its changes at any moment, quickly, precisely and with less calculating operations, is a mater of high significance. The aim of this paper is to investigate and propose a channel estimation method for MIMO-OFDM systems based on comparative methods. According to this, with investigating the channel estimation method, we can design optimum training courses for these systems and introduce related comparative methods based on LMS algorithm. The efficiency of suggested LMS algorithm can be investigated by simulation and the results of estimation will come to a comparison.
A Credit-Based Incentive Mechanism for Recommendation Acquisition in Multihop Mobile Ad Hoc Networks

Trust and reputation systems play an important role in collaborative operations in mobile ad hoc networks. However, the security of trust and reputation system itself is threatened by the existence of selfish nodes. Selfish nodes can make passive attacks on the foundational process of trust and reputation system, the recommendation acquisition, through non cooperation of packet forwarding and recommendation rendering. Existing trust and reputation systems commonly suffer from vulnerability caused by the failure of recommendation acquisition which refers to the unsuccessful recommendation information obtaining from one node to another node. A credit-based mechanism is proposed to address this problem by offering credits as incentives to both intermediate nodes and recommendation render nodes. Furthermore, competition between selfish nodes is explored to prevent selfish nodes being paid excessive credits. Simulation results show that the proposed mechanism can effectively improve the success rate of recommendation acquisition and lower the total paid payoffs.
Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations

Anticancer agents often have a narrow therapeutic index (TI), requiring precise dosing to ensure sufficient exposure for clinical activity while minimizing toxicity. These agents frequently have complex pharmacology, and combination therapy may cause schedule‐specific effects and interactions. We review anticancer drug development, showing how integration of modeling and simulation throughout development can inform anticancer dose selection, potentially improving the late‐phase success rate. This article has a companion article in Clinical Pharmacology & Therapeutics with practical examples.
Brain processes in emotional perception: Motivated attention

Brain potentials and blink reflexes were recorded while participants viewed emotional pictures organised into content categories that varied in motivational significance. Event‐related potentials at picture onset showed the largest late positive potentials to erotic scenes and to scenes of threat and mutilation, suggesting heightened attention to contents that are presumed to strongly activate appetitive and defensive motivational systems. Erotic content also showed the greatest sustained attention over the viewing interval as measured by the inhibition of the P3 component of the event‐related potential to the late interval startle probe. Among pleasant contents, probe P3 amplitude was inversely related to reported arousal; however, P3 was similarly inhibited across all unpleasant contents. Replicating previous findings, greatest modulation of the startle reflex occurred when participants viewed pictures depicting threat, violent death, and erotica. Overall, the data were seen as consistent with a motivated attention model of emotional perception.