Miracle-dz/UniFAR-FTUs huggingface dataset:
Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum

Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis.
Remote Sensing Image Matching using Sift And Affine Transformation

paper presents remote sensing image matching using sift algorithm and affine transformation. The novelty in our approach is to find the features in the reference image and then match the input image with that of reference image using Affine Transformation. Both synthetic and real data have been considered in this work for the evaluation of the proposed methodology. After registering the image, the outliers are removed. A speeded up affine invariant detector is proposed in this paper for local feature extraction. The experimental results show that the proposed algorithm decreases the redundancy of key points and speeds up the implementation. It is able to account for differences in spectral content, rotation, scale, translation, different viewpoint, and change in illumination. The proposed technique improves the computational efficiency and decrease the storage requirement.
A New Giant Branch Clump Structure in the Large Magellanic Cloud

We present Washington C and T1 CCD photometry of 21 fields located in the northern part of the Large Magellanic Cloud (LMC), and spread over a region of more than 2.5 deg2 approximately 6° from the bar. The surveyed areas were chosen on the basis of their proximity to SL 388 and SL 509, whose fields showed the presence of a secondary giant clump, observationally detected by Bica et al. We also observed NGC 2209, located ∼14° away from SL 509. From the collected data, we found that most of the observed field CMDs do not show a separate secondary clump, but rather reveal a continuous vertical structure (VS), which is clearly seen for the first time. The VS also appears in the field of NGC 2209. Its position and size are nearly the same throughout the surveyed regions: it lies below the red giant clump (RGC) and extends from the bottom of the RGC to ∼0.45 mag fainter, spanning the bluest color range of the RGC. In two fields in addition to the NGC 2209 field the RGC is slightly tilted, following approximately the reddening vector, while the VS maintains its verticality. We found that the number of stars in the VS box defined by Δ(C - T1) = 1.45–1.55 mag and ΔT1 = 18.75–19.15 mag has a strong spatial variation, reaching the highest VS star density just northeast of SL 509. Moreover, the more numerous the VS stars in a field, the larger the number of LMC giants in the same zone. We also found that, in addition to SL 509, two relatively massive star clusters, SL 515 and NGC 2209, separated by more than 10° from each other, develop giant clumps with a considerable number of VS stars. This result demonstrates that VS stars belong to the LMC and are most likely the result of some kind of evolutionary process in the LMC, particularly in those LMC regions with a noticeable large giant population. Our results are successfully predicted by the models of Girardi in the sense that a large proportion of 1–2 Gyr old stars mixed with older stars and with metallicities higher than [Fe/H] ≃ -0.7 should result in a fainter and bluer secondary clump near the mass at which degenerate core He burning takes place. However, our results apparently suggest that in order to trigger the formation of VS stars, there should be other conditions in addition to the appropriate age, metallicity, and the necessary red giant star density. Indeed, stars satisfying the requisites mentioned above are commonly found throughout the LMC, but the VS phenomenon is only clearly seen in some isolated regions. Finally, the fact that clump stars have an intrinsic luminosity dispersion further constrains the use of the clump magnitude as a reliable distance indicator.
Estimating Transfer Function from Air to bone conduction using singing voice

Singers often notice a disparity between how they perceive their own voice while they are singing and how they perceive their voice when hearing a recorded playback. This research aims to produce a digital filter which will take a sound sung by a singer and render it to a processed sound which is a close match to that heard by the singer during performance. One reason for the disparity arises from the fact that the skull conveys sound to ears when people speak or sing, and then the sound that is delivered blends with the air-conducted ones at the cochlea. In this paper, we investigate the spectral difference between the air-conducted sound and the boneconducted sound, and estimate the transfer function from air conduction to bone conduction by signal processing methods. Then we transform the original recording by air transmission using the filter coefficients of the transfer function and compare the filtered sound to the original recording by bone transmission.
The effect of seasonal birth pulses on pathogen persistence in wild mammal populations

The notion of a critical community size (CCS), or population size that is likely to result in long-term persistence of a communicable disease, has been developed based on the empirical observations of acute immunizing infections in human populations, and extended for use in wildlife populations. Seasonal birth pulses are frequently observed in wildlife and are expected to impact infection dynamics, yet their effect on pathogen persistence and CCS have not been considered. To investigate this issue theoretically, we use stochastic epidemiological models to ask how host life-history traits and infection parameters interact to determine pathogen persistence within a closed population. We fit seasonal birth pulse models to data from diverse mammalian species in order to identify realistic parameter ranges. When varying the synchrony of the birth pulse with all other parameters being constant, our model predicted that the CCS can vary by more than two orders of magnitude. Tighter birth pulses tended to drive pathogen extinction by creating large amplitude oscillations in prevalence, especially with high demographic turnover and short infectious periods. Parameters affecting the relative timing of the epidemic and birth pulse peaks determined the intensity and direction of the effect of pre-existing immunity in the population on the pathogen's ability to persist beyond the initial epidemic following its introduction.
On Semantic Underspecification 1. Underspecification Phenomena

Scope, especially quantiier scope, is the rst and best investigated phenomenon in the eld of underspeciication research. The use of logic representation languages in natural language semantics often requires a choice between alternative scopings in the interpretation process, where this choice seems to be premature or unnecessarily ne-grained. An example is (1a), which can be assigned either (1b) or (1c) as logical representation, although in many cases the relative scope of universal and existential operator may be unclear, or irrelevant, or both. (1) a. Two foreign languages are spoken by every linguist. b. 9 2 x(foreign language(x)^8y(linguist(y) ! spoken by(x; y))) c. 8y(linguist(y) ! 9 2 x(foreign language(x)^spoken by(x; y))) The basic idea behind the technique of underspeciication is to represent the semantic information connected with a semantically underdeter-mined utterance A by a partial description of logical structure, rather than enumerating the possible completely speciied interpretation alternatives for A. Pioneering research on structural underspeciication has been performed at SRI Cambridge. The QLF formalism described in (Alshawi and Crouch, 1992) provides an underspeciied treatment of scope as well as certain aspects of referential ambiguity, ellipsis, and focus-background structure. 1 Another important source for the interest in underspeciication is lexical semantics. Example (2) is a representative for a large eld of ambiguity phenomena, which are conventionally classiied as lexical ambiguities, but diier from trivial cases like the homonyms bank or pen in several important ways.
Cloud Resource Allocation Algorithms for Elastic Media Collaboration Flows

Real-time Audio/Video (A/V) collaboration is an application domain for which Cloud adoption is being investigated. However, the professional market generally prefers reliability over elasticity / scalability, in terms of managed delay and quality, and hence usually relies on dedicated specialized hardware and network setups, which are costly and hard to scale. This paper proposes cloud-enabled A/V resource allocation algorithms that combine elasticity and scalability with a focus on solving professional SLA requirements. The proposed algorithms attempt to minimize cloud cost and network usage by intelligently provisioning service endpoints along distributed data centers and splitting A/V streaming content in selected endpoints, while striving for the measurable and controlled reliability offered by dedicated solutions. An extended version of the CloudSim simulator, developed to generate and simulate A/V collaboration patterns while collecting statistics about resource usage and cost, network congestion and delay, among others, was used for evaluation purposes. When comparing results between the most efficient proposed approach and the second one, bandwidth usage and virtual machine costs are reduced by 60% and 65%, respectively, while maintaining industry-accepted SLA compliance levels.
Decoupling session variability modelling and speaker characterisation

The Factor Analysis framework demonstrated its high power to model session variability during the past years. However, training the FA parameters implies to have a large amount of training data. When the size of the available database is limited, the number of components of the core statistical model, the UBM, is also limited as the UBM drives the dimension of the FA main matrix. As the size of the UBM gives directly the size of the speaker supervector (concatenation of the GMM mean parameters), it limits also the intrinsic capacity of the recognition system , reducing the performance expectation. This paper aims to withdraw this limitation by breaking the intrinsic link between the FA dimensionality and the UBM dimensionality. The session variability modelling is done on a smaller dimension compared to the UBM, which drives the discriminative power of the system. The first experimental results proposed in this paper, done using the NIST-SRE 2008 framework, are encouraging with a relative EER improvement of about 18% when a 512 components UBM is associated to a 32 components session variability modelling compared with a 32 components UBM associated with the same variability modelling.
Chest X-ray retrieval based on modified Homogeneous Texture Descriptor and local feature fusion

An effective image retrieval system applied to chest X-ray image database is presented in this paper. In this system, image features are represented and matched by a modified MPEG-7 Homogeneous Texture Descriptor, whose Gabor filter bank is redesigned to be more suitable for chest X-ray images, and the similarity metric strategy is replaced by a boosting distance metric learning method. A local feature fusion technique, which contains an automatic subdivision method and a self-adaptive local feature weighing algorithm, is proposed to detect and analyze lesions in small areas. The system is tested on a database with 120 chest radiographs and the average retrieval accuracy of this system reaches 83.67%. The experimental results indicate that the modified Homogeneous Texture Descriptor improves the retrieval effectiveness compared with the standard version, and the local feature fusion enhances the retrieval accuracy significantly.
Learning Strategies at Work Scale: a Confirmatory Factor Analysis

Abstract The aim of this study was to gather new evidences of validity for the Learning Strategies at Work Scale (LSW). Especially, we intended to verify the initially proposed factor structure and to reduce items as to obtain a higher level of parsimony. We further addressed testing the LSW’s invariance across occupations, with potentially discrepant work design characteristics (core activities vs. non-core activities). 955 Brazilian professionals that worked in a wide range of occupations participated in this study. Results of a confirmatory factor analysis support the structure of five factors, namely (1) intrinsic and extrinsic reflection, (2) mental repetition, (3) interpersonal help seeking, (4) help seeking in written material and (5) trial and error learning. In order to obtain higher parsimony, based upon psychometric criteria, five items were eliminated, resulting in better fit-indices. A multigroup analysis of this reduced scale showed invariance across the above-mentioned occupations. The study adds validity evidences for the LSW in Brazil.
Dietary n-3 Fatty Acids Inhibit Fever Induced by Inflammation in the Rat

Modification of endogenous eicosanoid synthesis by dietary n-3 fatty acid supplementation reduces febrile responses, but the mechanisms underlying these effects in vivo have not been determined. In the present study, local inflammation was induced by intramuscular injection ofturpentine in rats fed control or n-3 supplemented diets for 8-9 weeks. In animals fed the control diet, turpentine induced fever, hypermetabolism, marked local inflammation (oedema), increased plasma IL-6 concentrations and raised cerebrospinal fluid (CSF) concentrations of PGE2. N-3 fatty acid supplementation significantly inhibited the rise in CSF PGE2, fever and hypermetaboHsm induced by turpentine. Local inflammation and increased plasma IL-6 concentrations were not affected by n-3 supplementation. These findings suggest that modification of dietary fat intake inhibits fever via reduced release of prostaglandins, probably within the brain, but does not affect the local or afferent signals involved in fever generation.
The Distant-l Chromatic Number of Random Geometric Graphs

A random geometric graph $G_n$ is given by picking $n$ vertices in $\mathbb{R}^d$ independently under a common bounded probability distribution, with two vertices adjacent if and only if their $l^p$-distance is at most $r_n$. We investigate the distant-$l$ chromatic number $\chi_l(G_n)$ of $G_n$ for $l\ge1$. Complete picture of the ratios of $\chi_l(G_n)$ to the chromatic number $\chi(G_n)$ are given in the sense of almost sure convergence.
A distributed joint power control and mode selection scheme for D2D communication underlaying LTE-A networks

In addition to providing high data rate, Device-to-Device (D2D) communication reduces the transmit power of users and improve spatial spectrum reuse significantly. In this paper, we formulate the joint power control and mode selection problem for D2D communications underlaying LTE-A network for minimizing the aggregate transmit power of users subject to a minimum target throughput for each cellular and D2D user, and propose a distributed joint mode selection and power control scheme for addressing it. In our proposed distributed scheme, each D2D user selects its mode on each of its assigned resource blocks (RBs), based on the effective interference on that RB, and each cellular and D2D user adjusts its transmit power level on its assigned RBs so that its target throughput is achieved. The mode selection by D2D users and the power control by cellular and D2D users in our proposed scheme are performed in an iterative manner. The simulation results demonstrate the effectiveness and superiority of our proposed method over two extreme methods (i.e., force D2D and force cellular methods), in terms of power consumption.
Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types

This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (τ), droplet effective radius (re), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for τ between 5 and 60 and re less than approximately 20 μm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of from 5 to 10 and re < 10 μm, with maximum sensitivity obtained for an overhead sun.
Auditory letter-name processing elicits crossmodal representations in blind listeners

As incoming stimuli travel through our sensory pipelines, they are processed in multiple formats, spanning levels of abstraction as well as sensory domains. The spatiotemporal and representational dynamics of this processing cascade remain especially unclear in nonvisual modalities and nontypical populations; in particular, a stimulus representation may either facilitate or suppress its multisensory analogue. Here, we presented auditory alphabetic letter names to blind listeners with no visual letter experience, as well as sighted listeners with no braille (tactile) reading experience. Blind and sighted groups’ brain responses distinguished letter identity along similar time courses and accuracies. However, only blind listeners’ brain signals correlated with a low-level model of braille characters, while no such correlation was found between sighted listeners’ brain signals and a neural network model of low-level visual letter features. The results illustrate that visual experience modulates both the extent and nature of multisensory processing and object representation generally.
A Statistical Model to Analyze Clinician Expert Consensus on Glaucoma Progression using Spatially Correlated Visual Field Data

Purpose We developed a statistical model to improve the detection of glaucomatous visual field (VF) progression as defined by the consensus of expert clinicians. Methods We developed new methodology in the Bayesian setting to properly model the progression status of a patient (as determined by a group of expert clinicians) as a function of changes in spatially correlated sensitivities at each VF location jointly. We used a spatial probit regression model that jointly incorporates all highly correlated VF changes in a single framework while accounting for structural similarities between neighboring VF regions. Results Our method had improved model fit and predictive ability compared to competing models as indicated by the deviance information criterion (198.15 vs. 201.29–213.38), a posterior predictive model selection metric (130.08 vs. 142.08–155.59), area under the receiver operating characteristic curve (0.80 vs. 0.59–0.72; all P values < 0.018), and optimal sensitivity (0.92 vs. 0.28–0.82). Simulation study results suggest that estimation (reduction of mean squared errors) and inference (correct coverage of 95% credible intervals) for the model parameters are improved when spatial modeling is incorporated. Conclusions We developed a statistical model for the detection of VF progression defined by clinician expert consensus that accounts for spatially correlated changes in visual sensitivity over time, and showed that it outperformed competing models in a number of areas. Translational Relevance This model may easily be incorporated into routine clinical practice and be useful for detecting glaucomatous VF progression defined by clinician expert consensus.
Research on Fuzzy-PID control strategy for AC arc furnace electrode regulator system

This paper studied the Fuzzy-PID control strategy for AC arc furnace electrode regulator system. Based on the classical PID control, this paper used the basic theories and methods of Fuzzy Mathematics to adjust the PID parameters, realized the Fuzzy-PID control strategy, applied it in electrode regulator system and then made the simulation. The simulation results showed that the control strategy of the electrode regulator discussed in this paper adjusted the position of the electrode accurately, regulated the arc length of the electrode to an expectable value. Therefore, this discussed control strategy could suppress the power grid fluctuations, reduce power consumption and save energy.
Low-Noise Sigma-Delta Capacitance-to-Digital Converter for Sub-pF Capacitive Sensors with Integrated Dielectric Loss Measurement

A sigma-delta capacitance-to-digital converter (CDC) with a resolution down to 19.3 aF at a bandwidth of 10 kHz, corresponding to a noise level of 0.2 aF/radicHz, is presented. An integrated dielectric loss measurement circuit by means of two parallel channels with different integration times offers a complex permittivity measurement in a single-chip solution. The achieved dielectric loss angle resolution is as low as 0.3deg for a material density ratio of 0.55 %. A test chip with two converter blocks including two 2nd order and two 4th order modulators has been produced in the austriamicrosystems AG C35B3C0 0.35 mum DPTM CMOS process, operating at a single 3.3 V supply. Applications of this circuit include mass measurement and analysis of material compositions.