Miracle-dz/UniFAR-FTUs huggingface dataset:
Partially segregated neural networks for spatial and contextual memory in virtual navigation

Finding our way in a previously learned, ecologically valid environment concurrently involves spatial and contextual cognitive operations. The former process accesses a cognitive map representing the spatial interactions between all paths in the environment. The latter accesses stored associations between landmark objects and their milieu. Here, we aimed at dissociating their neural basis in the context of memory‐based virtual navigation. To do so, subjects freely explored a virtual town for 1 h, then were scanned using fMRI while retrieving their way between two locations, under four navigation conditions designed to probe separately or jointly the spatial and contextual memory components. Besides prominent commonalities found in a large hippocampo‐neocortical network classically involved in topographical navigation, results yield evidence for a partial dissociation between the brain areas supporting spatial and contextual components of memory‐based navigation. Performance‐related analyses indicate that hippocampal activity mostly supports the spatial component, whereas parahippocampal activity primarily supports the contextual component. Additionally, the recruitment of contextual memory during navigation was associated with higher frontal, posterior parietal and lateral temporal activity. These results provide evidence for a partial segregation of the neural substrates of two crucial memory components in human navigation, whose combined involvement eventually leads to efficient navigation behavior within a learned environment. © 2008 Wiley‐Liss, Inc.
A Phenotypic Recessive, Post‐Entry Block in Rabbit Cells that Results in Aberrant Trafficking of HIV‐1

Rabbit cells are poorly permissive to HIV‐1 infection, but little is known about the nature of this block. Here, we show that the block to infection is mainly at the level of reverse transcription (RT), is independent of the cell receptor used by the virus for entry, cannot be effectively saturated with high doses of virus or virus‐like particles, and has a recessive phenotype in human–rabbit heterokaryons. RT complexes (RTCs) extracted from human and rabbit cells have different densities but are both competent for RT in an in vitro endogenous assay. Cell fractionation showed that HIV‐1 is trafficked in a different way in human and rabbit cells and that correct intracellular trafficking is linked to efficient RT and high infectivity in vivo. Viral DNA accumulated in rabbit cell nuclei only at a later stage and failed to associate with chromatin, suggesting a further block prior to integration. Our data point to the existence of cellular factors regulating the early stages of intracytoplasmic and possibly intranuclear HIV‐1 trafficking.
Localizing Facial Keypoints with Global Descriptor Search, Neighbour Alignment and Locally Linear Models

We present our technique for facial key point localization in the wild submitted to the 300-W challenge. Our approach begins with a nearest neighbour search using global descriptors. We then employ an alignment of local neighbours and dynamically fit a locally linear model to the global key point configurations of the returned neighbours. Neighbours are also used to define restricted areas of the input image in which we apply local discriminative classifiers. We then employ an energy function based minimization approach to combine local classifier predictions with the dynamically estimated joint key point configuration model. % Our method is able place 68 key points on in the wild facial imagery with an average localization error of less than 10% of the inter-ocular distance for almost 50% of the challenge test examples. Our model therein increased the yield of low error images over the baseline AAM result provided by the challenge organizers by a factor of 2.2 for the 68 key point challenge. Our method improves the 51 key point baseline result by a factor of 1.95, yielding key points for more than 50% of the test examples with error of less than 10% of inter-ocular distance.
A new method to reduce truncation errors in partial spherical near-field measurements

A new and effective method for reduction of truncation errors in partial spherical near-field (SNF) measurements is proposed. The method is useful when measuring electrically large antennas, where the measurement time with the classical SNF technique is prohibitively long and an acquisition over the whole spherical surface is not practical. Therefore, to reduce the data acquisition time, partial sphere measurement is usually made, taking samples over a portion of the spherical surface in the direction of the main beam. But in this case, the radiation pattern is not known outside the measured angular sector as well as a truncation error is present in the calculated far-field pattern within this sector. The method is based on the Gerchberg-Papoulis algorithm used to extrapolate functions and it is able to extend the valid region of the calculated far-field pattern up to the whole forward hemisphere. To verify the effectiveness of the method, several examples are presented using both simulated and measured truncated near-field data.
Distributed Geometric Query Monitoring Using Prediction Models

Many modern streaming applications, such as online analysis of financial, network, sensor, and other forms of data, are inherently distributed in nature. An important query type that is the focal point in such application scenarios regards actuation queries, where proper action is dictated based on a trigger condition placed upon the current value that a monitored function receives. Recent work [Sharfman et al. 2006, 2007b, 2008] studies the problem of (nonlinear) sophisticated function tracking in a distributive manner. The main concept behind the geometric monitoring approach proposed there is for each distributed site to perform the function monitoring over an appropriate subset of the input domain. In the current work, we examine whether the distributed monitoring mechanism can become more efficient, in terms of the number of communicated messages, by extending the geometric monitoring framework to utilize prediction models. We initially describe a number of local estimators (predictors) that are useful for the applications that we consider and which have already been shown particularly useful in past work. We then demonstrate the feasibility of incorporating predictors in the geometric monitoring framework and show that prediction-based geometric monitoring in fact generalizes the original geometric monitoring framework. We propose a large variety of different prediction-based monitoring models for the distributed threshold monitoring of complex functions. Our extensive experimentation with a variety of real datasets, functions, and parameter settings indicates that our approaches can provide significant communication savings ranging between two times and up to three orders of magnitude, compared to the transmission cost of the original monitoring framework.
BOLD-based Techniques for Quantifying Brain Hemodynamic and Metabolic Properties – Theoretical Models and Experimental Approaches

Quantitative evaluation of brain hemodynamics and metabolism, particularly the relationship between brain function and oxygen utilization, is important for understanding normal human brain operation as well as pathophysiology of neurological disorders. It can also be of great importance for evaluation of hypoxia within tumors of the brain and other organs. A fundamental discovery by Ogawa and co-workers of the BOLD (Blood Oxygenation Level Dependent) contrast opened a possibility to use this effect to study brain hemodynamic and metabolic properties by means of MRI measurements. Such measurements require developing theoretical models connecting MRI signal to brain structure and functioning and designing experimental techniques allowing MR measurements of salient features of theoretical models. In our review we discuss several such theoretical models and experimental methods for quantification brain hemodynamic and metabolic properties. Our review aims mostly at methods for measuring oxygen extraction fraction, OEF, based on measuring blood oxygenation level. Combining measurement of OEF with measurement of CBF allows evaluation of oxygen consumption, CMRO2. We first consider in detail magnetic properties of blood – magnetic susceptibility, MR relaxation and theoretical models of intravascular contribution to MR signal under different experimental conditions. Then, we describe a “through-space” effect – the influence of inhomogeneous magnetic fields, created in the extravascular space by intravascular deoxygenated blood, on the MR signal formation. Further we describe several experimental techniques taking advantage of these theoretical models. Some of these techniques MR susceptometry, and T2-based quantification of oxygen OEF – utilize intravascular MR signal. Another technique – qBOLD – evaluates OEF by making use of throughspace effects. In this review we targeted both scientists just entering the MR field and more experienced MR researchers interested in applying advanced BOLD-based techniques to study brain in health and disease.
Technology sourcing by UK manufacturing fi rms : an empirical analysis using fi rm-level patent data

This paper examines whether UK firms that locate their R&D activity in the USA benefit more than other UK firms from knowledge spillovers originating from US R&D. Patent data provides a firm-level measure of the location of innovative activity, which enables the identification of knowledge spillovers associated with "technology sourcing". We find evidence for such spillovers, although the data do not currently allow a clear differentiation between technology sourcing and an absorptive capacity effect. Future research may be able to clarify these issues by using an enlarged dataset and exploiting more of the information provided by the patent data. In particular the use of citations data to create a more precise measure of the spillover pool available to each firm provides a potentially fruitful avenue of research. ∗Acknowledgement: The authors would like to thank . Financial support for this project was provided by the ESRC Centre for the Microeconomic Analysis of Fiscal Policy at the IFS. The data was developed with funding from the Leverhulme Trust. †Institute for Fiscal Studies and University College London (rgriffith@ifs.org.uk, rharrison@ifs.org.uk) ‡University College London and Centre for Economic Performance
Cooperative Navigation for Low-bandwidth Mobile Acoustic Networks

Abstract : This thesis reports on the design and validation of estimation and planning algorithms for underwater vehicle cooperative localization. While attitude and depth are easily instrumented with bounded-error, autonomous underwater vehicles (AUVs) have no internal sensor that directly observes XY position. The global positioning system (GPS )and other radio-based navigation techniques are not available because of the strong attenuation of electromagnetic signals in seawater. The navigation algorithms presented herein fuse local body-frame rate and attitude measurements with range observations between vehicles within a decentralized architecture. The acoustic communication channel is both unreliable and low bandwidth, precluding many state-of-the-art terrestrial cooperative navigation algorithms. We exploit the underlying structure of a post-process centralized estimator in order to derive two real-time decentralized estimation frameworks. First, the origin state method enables a client vehicle to exactly reproduce the corresponding centralized estimate within a server-to-client vehicle network. Second, a graph-based navigation framework produces an approximate reconstruction of the centralized estimate onboard each vehicle. Finally, we present a method to plan a locally optimal server path to localize a client vehicle along a desired nominal trajectory. The planning algorithm introduces a probabilistic channel model into prior Gaussian belief space planning frameworks. In summary, cooperative localization reduces XY position error growth within underwater vehicle networks. Moreover, these methods remove the reliance on static beacon networks, which do not scale to large vehicle networks and limit the range of operations. Each proposed localization algorithm was validated in full-scale AUV field trials. The planning framework was evaluated through numerical simulation.
'Sentiments,' Conduct, and Trust in the Laboratory

In this article we provide a brief account and interpretation of The Theory of Moral Sentiments showing that it departs fundamentally from contemporary patterns of thought in economics that are believed to govern individual behavior in small groups, and contains strong testable propositions governing the expression of that behavior. We also state a formal representation of the model for individual choice of action, apply the propositions to the prediction of actions in trust games, report two experiments testing these predictions, and interpret the results in terms directly related to the model. In short, we argue that the system of sociability developed by Adam Smith provides a coherent non-utilitarian model that is consistent with the pattern of results in trust games, and leads to testable new predictions, some of which we test.
HIV Prevalence in a Gold Mining Camp in the Amazon Region, Guyana

The prevalence of HIV infection among men in a gold mining camp in the Amazon region of Guyana was 6.5%. This high percentage of HIV infection provides a reservoir for the virus in this region, warranting immediate public health intervention to curb its spread. As malaria is endemic in the Amazon Basin (>30,000 cases/year), the impact of coinfection may be substantial.
A Nimble Video Editor That Puts Audio First

Video editing software tends to be feature-laden, to respond sluggishly to user input—and to be focused on the visuals rather than on auditory aspects. All of this is a burden when the task is to edit material in which audio plays the leading role, such as a talk show, a video podcast, or a lecture recording. This work presents a highly visual, no-frills video editor that is tailored to these tasks. It combines a range of techniques that speed up the process of searching and reviewing. They range from an overview-and-detail display to speech recognition to constant-pitch variable-speed playback . The implementation is heavily multithreaded and fully leverages the computer’s main memory to ensure a highly fluid interaction.
Combining forward and backward processing for Korean baseNP identification

BaseNP identification is an important NLP task. We propose a Korean baseNP identification method that uses a state-based model focusing on directionality of the state transition. In Korean baseNP identification, the degree of difficulty in identifying a start position is different from that of identifying an end position. This fact implies that the property of the model can be changed if the state transition is processed in a right-to-left manner. We propose the backward processing model that processes the state transition in a right-to-left manner. In addition, we combine it with the forward processing model that processes the state transition in a left-to-right manner. The results of both models are better than those of the previous ones in Korean baseNP identification. We can achieve further improvement by combining the two models.
Forecasting electricity consumption in South Africa: ARMA, neural networks and neuro-fuzzy systems

This paper presents an experiment that consists of constructing auto-regressive moving average (ARMA), neural networks and neuro-fuzzy models with historical electricity consumption time series data to create models that can be used to forecast consumption in the future. The data was sampled on a monthly basis from January 1985 to December 2011. An ARMA, multilayer perceptron neural network with back propagation and neuro-fuzzy modelling technique which combines Takagi-Sugeno fuzzy models and neural networks were used to create the models for one step ahead forecasting. The results of the three techniques were compared and the results show that neuro-fuzzy models outperformed the neural network and ARMA models in terms of accuracy.
What’s missing in longitudinal studies conducted in the U.S. with implications for mathematics education?

ABSTRACT ‘What works’ policies are the latest incarnation of best practices in educational research. Instituted by various organisations internationally, they define what kind of research counts as ‘evidence’ for reform-oriented decision-making. While some countries rely on systematic analyses and meta-analyses, the U.S. favours primary quantitative longitudinal research designs as evidence. Critics claim that institutionalising methods will distort educational research. This commentary discusses these two concerns about the research designs favoured in the American ‘what works’ milieu: missing research and missing data. To explore whether those concerns are warranted, we focus on mathematics education, a national priority in the U.S. After establishing enduring questions in mathematics education, we provide primers on quantitative longitudinal research designs and the analysis of missing data due to attrition. Then, we address these questions about the state of research: As a research community, are we missing research with implications for mathematics education? Are we missing data with implications for the inferences that can be made? This review of research questions and analyses in recent studies suggests missing data poses a greater threat than missing research. Finally, we make recommendations for minimising the risk of missing evidence that will be of interest to international educational researchers in any discipline.
Boosting kernel density estimates: A bias reduction technique?

This paper proposes an algorithm for boosting kernel density estimates. We show that boosting is closely linked to a previously proposed method of bias reduction and indicate how it should enjoy similar properties. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research. Copyright Biometrika Trust 2004, Oxford University Press.
Positive Affect and Cognitive Restoration: Investigating the Role of Valence and Arousal

Positive moods are thought to restore self-control resources following depletion. However, it is not well understood whether this effect is due to affective valence (pleasantness), arousal (activation), or a combination of both. Across four studies, we set out to investigate the role of positive moods on cognitive and behavioral measures of self-regulation in an ego-depletion paradigm. In studies 1 and 2, we independently manipulated affective valence and arousal and assessed self-regulation with a Stroop task. Results did not suggest a restorative effect of either on cognitive resources. In study 3, we employed both behavioral (the ‘handgrip task’) and cognitive (Stroop) assessments of self-regulation. Again, no significant effect of mood was observed on the Stroop task. Additionally, participants did not persist significantly longer on the handgrip task following a positive mood induction. Finally, in study 4, high vs. low states of arousal were manipulated and self-regulation was assessed via pre- and post-manipulation Stroop performance. In study 4, Stroop performance improved slightly more across time points for those in the high arousal condition than for those in the low arousal condition. Therefore, across four studies, we failed to find a consistent pattern of results suggesting that positive moods restore cognitive resources.
An authorization model for temporal data

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State-Space Synthesis of Current-Mode First-Order Log-Domain Filters

This paper proposes current-mode first-order log-domain filters, which are systematically derived using the state-space synthesis procedure. First-order low-pass, high-pass, and all-pass responses are obtained with different circuit types. The filter circuits have very simple structures, since they use only bipolar junction transistors (BJTs) and a grounded capacitor. They can be electronically tuned by changing an external current. The filters have a greater bandwidth due to inherently current-mode and log-domain operation. PSPICE simulations are given to confirm the theoretical analysis.
The Return of the King

This study examined the experiences of Northeast Ohio residents when LeBron James announced he was leaving the Cleveland Cavaliers in 2010 and then returned in 2014, through the lens of parasocial relationships (PSRs). One hundred thirty-seven people who either grew up in or currently resided in Northeast Ohio reported about their experiences when LeBron James announced he was leaving Cleveland to play in Miami in 2010, as well as their experiences when he announced his return to Cleveland in 2014. Results indicated the more intense a PSR with James was, the more invested in him individuals were. Additionally, experiencing a parasocial breakup was positively related to having feelings of grief after James left. The results of this study extend previous research on PSRs to a new realm and help explain why some sports fans might react negatively when finding out their favorite player is no longer playing with their favorite team.
Development of the language proficiency of five- to seven-year-olds in rural areas

ABSTRACT Rural children are a largely understudied population in language and literacy research, despite the fact that these children often enter school with delays in their language development. Since most rural areas suffered from so-called selective rural outmigration, many parents in rural areas are lower or middle educated. The home literacy climate, however, depends not only on the educational level of parents, but also on their lifestyle. In this study, we examined whether parental educational level and literacy use – as a feature of parental lifestyle – predict the language skills of children in Grade 1 in Northeast Netherlands. Structural equation modelling analyses revealed that the effect of parental literacy use on code-related skills is only significant in K-1 and K-2. In Grade 1, however, literacy use had a modest effect on oral language skills. The findings stress the importance of parents’ literacy use for informational purposes.