Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Learning Control Using Adaptive Critic Designs With Sparse Kernel Machines

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.
The Role of BKCa Channels in Electrical Signal Encoding in the Mammalian Auditory Periphery

Large-conductance voltage- and Ca2+-activated K+ channels (BKCa) are involved in shaping spiking patterns in many neurons. Less is known about their role in mammalian inner hair cells (IHCs), mechanosensory cells with unusually large BKCa currents. These currents may be involved in shaping the receptor potential, implying crucial importance for the properties of afferent auditory signals. We addressed the function of BKCa by recording sound-induced responses of afferent auditory nerve (AN) fibers from mice with a targeted deletion of the pore-forming α-subunit of BKCa (BKα−/−) and comparing these with voltage responses of current-clamped IHCs. BKCa-mediated currents in IHCs were selectively abolished in BKα−/−, whereas cochlear physiology was essentially normal with respect to cochlear sensitivity and frequency tuning. BKα−/− AN fibers showed deteriorated precision of spike timing, measured as an increased variance of first spike latency in response to tone bursts. This impairment could be explained by a slowed voltage response in the presynaptic IHC resulting from the reduced K+ conductance in the absence of BKCa. Maximum spike rates of AN fibers were reduced nearly twofold in BKα−/−, contrasting with increased voltage responses of IHCs. In addition to presynaptic changes, which may be secondary to a modest depolarization of BKα−/− IHCs, this reduction in AN rates suggests a role of BKCa in postsynaptic AN neurons, which was supported by increased refractory periods. In summary, our results indicate an essential role of IHC BKCa channels for precise timing of high-frequency cochlear signaling as well as a function of BKCa in the primary afferent neuron.
Clique-aware mobile social clouds

The important role played by cliques in identifying cohesive subgroups of people has been theorized and explored by sociologists years ago, but only recently investigated in large-scale social networks. In this paper we focus on the interplay between cliques established by on-phone communications and the urban locations their members share each other. The results about co-located cliques has been achieved through the extensive analysis of a large anonymized dataset of Call Detail Records (CDR) relying on the phone activities of nearly 1 million people in the city of Milan. Taking the cue from the observation of cliques, the paper envisions and designs a novel clique-support service for mobile users by fully exploiting the current virtualization process that is radically transforming the core network of mobile operators. The approach we propose brings together a few important contributions: first, it concretely shows that the current NFV-enabled trend of placing cloud services at the edge of the operator's network is viable and may have a payoff in terms of traffic offloading and improved user's experience; secondly, it demonstrates for the first time that a few typical cloud-based services can effectively be directly performed inside the mobile network by simply leveraging the rich amount of data about users' location and mobility behavior.
Automatic Road Crack Detection Using Random Structured Forests

Cracks are a growing threat to road conditions and have drawn much attention to the construction of intelligent transportation systems. However, as the key part of an intelligent transportation system, automatic road crack detection has been challenged because of the intense inhomogeneity along the cracks, the topology complexity of cracks, the inference of noises with similar texture to the cracks, and so on. In this paper, we propose CrackForest, a novel road crack detection framework based on random structured forests, to address these issues. Our contributions are shown as follows: 1) apply the integral channel features to redefine the tokens that constitute a crack and get better representation of the cracks with intensity inhomogeneity; 2) introduce random structured forests to generate a high-performance crack detector, which can identify arbitrarily complex cracks; and 3) propose a new crack descriptor to characterize cracks and discern them from noises effectively. In addition, our method is faster and easier to parallel. Experimental results prove the state-of-the-art detection precision of CrackForest compared with competing methods.
Extrapolative Capability of Two Models That Estimating Soil Water Retention Curve between Saturation and Oven Dryness

Accurate estimation of soil water retention curve (SWRC) at the dry region is required to describe the relation between soil water content and matric suction from saturation to oven dryness. In this study, the extrapolative capability of two models for predicting the complete SWRC from limited ranges of soil water retention data was evaluated. When the model parameters were obtained from SWRC data in the 0–1500 kPa range, the FX model (Fredlund and Xing, 1994) estimations agreed well with measurements from saturation to oven dryness with RMSEs less than 0.01. The GG model (Groenevelt and Grant, 2004) produced larger errors at the dry region, with significantly larger RMSEs and MEs than the FX model. Further evaluations indicated that when SWRC measurements in the 0–100 kPa suction range was applied for model establishment, the FX model was capable of producing acceptable SWRCs across the entire water content range. For a higher accuracy, the FX model requires soil water retention data at least in the 0- to 300-kPa range to extend the SWRC to oven dryness. Comparing with the Khlosi et al. (2006) model, which requires measurements in the 0–500 kPa range to reproduce the complete SWRCs, the FX model has the advantage of requiring less SWRC measurements. Thus the FX modeling approach has the potential to eliminate the processes for measuring soil water retention in the dry range.
Natural Killer Cell Inhibitory Receptors Block Actin Cytoskeleton-dependent Recruitment of 2B4 (CD244) to Lipid Rafts

A dynamic balance of positive and negative signals regulates target cell lysis by natural killer (NK) cells upon engagement of a variety of different activation receptors and of inhibitory receptors that recruit the tyrosine phosphatase SHP-1. However, the step at which activation signals are blocked by SHP-1 is not known. We have been using activation receptor 2B4 (CD244) to study the influence of inhibitory receptors on NK cell activation. Engagement of inhibitory receptors by HLA class I on target cells blocks phosphorylation of 2B4, placing the inhibitory step at the level, or upstream of 2B4 phosphorylation. Here we show that phosphorylated 2B4, after engagement with either antibodies or target cells that express the 2B4 ligand, is found exclusively in a detergent-resistant membrane fraction that contains lipid rafts. Integrity of lipid rafts was essential for phosphorylation and activating function of 2B4. Coengagement of inhibitory receptors blocked 2B4 phosphorylation and 2B4 association with detergent-resistant membranes, indicating that inhibitory receptors function upstream of raft-dependent signals. Recruitment of 2B4 into detergent-resistant membrane fractions and 2B4 phosphorylation were dependent on actin polymerization. Blocking actin cytoskeleton-dependent raft recruitment of different receptors may be a general mechanism by which inhibitory receptors control NK cell activation.
Minty Fresh! Absolving Dieters of their Consumption Sins

This research contributes to the emerging interest in food morality by exploring the preference for and the effects of a particular food flavor (mint) on consumption behavior. More specifically, we examine how the refreshing oronasal properties of a specific food flavor (i.e., mint) systematically influence consumer preferences and food choice behavior. Across a pilot and two studies, we show that the refreshing properties of mint that can help dieters wash away the guilt associated with the consumption of “taboo” foods. We found that dieters tended to prefer “taboo” foods such as chocolate cookies (study 1) when they were mint-flavored. Further, after having consumed taboo food such as chocolate, dieters were more likely to prefer a mint- (vs. berry- or cinnamon-) flavored oral freshener (study 2). We also provide food marketers and public policy makers with new insights into how certain consumers (i.e., dieters) evaluate mint-flavored food products.
Position-based contextualization for passage retrieval

We present a novel contextualization approach for passage retrieval. The core principle is to let any occurrence of a query term in a document affect the passage retrieval score, whether the occurrence is in the passage or not. This effect is controlled by the distance between the term occurrence and the passage. Empirical evaluation demonstrates the merits of our approach; the resultant retrieval performance substantially transcends that of previously proposed passage retrieval methods, including those that use various contextualization approaches.
BATTING AND BUTTON-PRESS REACTION TIME IN PRIMARY, JUNIOR HIGH AND HIGH SCHOOL BASEBALL PLAYERS

The focus of this study was how baseball players acquire rapid visuo-motor processing during developmental stages. We compared simple and Go/Nogo reaction times in a button-press task and a swing-a-bat task between different age groups of teenage baseball players. Though reaction time, swing time and total reaction time were shorter in the older group, baseball-specific visuo-motor skills could not be investigated by our experiment. These results indicate that the general neural foundations underlying baseball performance develop over the school years.
Sequence variation data of F8 and F9 genes in functionally validated control individuals: implications on the molecular diagnosis of hemophilia

Background The F8 and F9 genes encode for coagulation factor VIII (FVIII) and FIX, respectively, and mutations in these genes are the genetic basis of hemophilia A/B. To determine whether a sequence variation in F8/F9 is a disease-causing mutation, frequency data from a control population is needed. This study aimed to obtain data on sequence variation in F8/F9 in a set of functionally validated control chromosomes of Korean descent. Methods We re-sequenced F8 and F9 from DNA samples of 100 Korean male control individuals with normal PT, aPTT, and FVIII activity. PCR and direct sequencing analyses were performed using primer pairs to cover all coding regions and the flanking intronic sequences. Results Thirteen individuals (13%) were hemizygous for sequence variations in the coding region of F8. Six (6%) had c.3780C>G (p.Asp1260Glu), five (5%) had c.3864A>C (p.Ser1288=). One each individual (1%) had c.4794G>T (p.Glu1598Asp) and c.5069 A>G (p.Glu1690Gly). Asp1260Glu and Ser1288= were known SNPs (rs1800291 and rs1800292, respectively). Glu1598Asp was assigned as a missense mutation in public databases (HGMD and HAMSTeRS), and Glu1690Gly was a novel variation. Based on the normal FVIII activities in control individuals carrying these variations (109% and 148%, respectively), they were considered to be rare SNPs. No variation was observed in F9 of control individuals. Conclusion A significant proportion of control individuals carried sequence variations in F8, but not in F9. These results can be used as a reference dataset for molecular diagnosis of hemophilia A and B, particularly in Korea.
The effective resolution of correlation filters applied to natural scenes

In this paper, we measure the responses of image patches, used as filters, on different image ensembles and examine how the responses are affected by reducing the resolution of the image ensembles. By comparing the set of responses obtained at high and reduced resolutions, we find that for the ensembles of natural and object images (cars), there is a limit resolution of about 15times15 and 10times10 pixels, respectively, beyond which the filter responses are significantly affected by resolution reduction. We support the result by a simple theoretical analysis based on image ensemble statistics. There are two consequences to this result. First, it provides a natural working resolution, determined solely from the image ensemble statistics, to which higher resolution templates can be reduced without losing a significant amount of information. This can be used, in particular, to reduce the search space for useful visual features in many applications. Secondly, in contrast to many studies, it suggests that features that are more complex than Gabor patches can be effectively used as first layer filters and combined in order to represent more complex shapes and appearances.
A frozen feast: thawing permafrost increases plant‐available nitrogen in subarctic peatlands

Many of the world's northern peatlands are underlain by rapidly thawing permafrost. Because plant production in these peatlands is often nitrogen (N)‐limited, a release of N stored in permafrost may stimulate net primary production or change species composition if it is plant‐available. In this study, we aimed to quantify plant‐available N in thawing permafrost soils of subarctic peatlands. We compared plant‐available N‐pools and ‐fluxes in near‐surface permafrost (0–10 cm below the thawfront) to those taken from a current rooting zone layer (5–15 cm depth) across five representative peatlands in subarctic Sweden. A range of complementary methods was used: extractions of inorganic and organic N, inorganic and organic N‐release measurements at 0.5 and 11 °C (over 120 days, relevant to different thaw‐development scenarios) and a bioassay with Poa alpina test plants. All extraction methods, across all peatlands, consistently showed up to seven times more plant‐available N in near‐surface permafrost soil compared to the current rooting zone layer. These results were supported by the bioassay experiment, with an eightfold larger plant N‐uptake from permafrost soil than from other N‐sources such as current rooting zone soil or fresh litter substrates. Moreover, net mineralization rates were much higher in permafrost soils compared to soils from the current rooting zone layer (273 mg N m−2 and 1348 mg N m−2 per growing season for near‐surface permafrost at 0.5 °C and 11 °C respectively, compared to −30 mg N m−2 for current rooting zone soil at 11 °C). Hence, our results demonstrate that near‐surface permafrost soil of subarctic peatlands can release a biologically relevant amount of plant available nitrogen, both directly upon thawing as well as over the course of a growing season through continued microbial mineralization of organically bound N. Given the nitrogen‐limited nature of northern peatlands, this release may have impacts on both plant productivity and species composition.
Multimodel Ensemble for Freeway Traffic State Estimations

Freeway traffic state estimation is a vital component of traffic management and information systems. Macroscopic-model-based traffic state estimation methods are widely used in this field and have gained significant achievements. However, tests show that the inherent randomness of traffic flow and uncertainties in the initial conditions of models, model parameters, and model structures all influence traffic state estimations. To improve the estimation accuracy, this paper presents an ensemble learning framework to appropriately combine estimation results from multiple macroscopic traffic flow models. This framework first assumes that any models existing are imperfect and have their own strengths/weaknesses. It then estimates the online traffic states in a rolling horizon scheme. This framework automatically ensembles the information from each individual estimation model based on their performance during the selected regression horizon. In particular, we discuss three weighting algorithms, namely, least square regression, ridge regression, and lasso, which represent different presumptions of model capabilities. A field test based on real freeway measurements indicates that lasso ensemble best handles various uncertainties and improves estimation accuracy significantly. It should be also pointed out that the proposed framework is a flexible tool to assemble nonmodel-based traffic estimation algorithms. This framework can be also extended for many other applications, including traffic flow prediction and travel-time prediction.
A Parallel Functional Topography between Medial and Lateral Prefrontal Cortex: Evidence and Implications for Cognitive Control

The dorsomedial and dorsolateral prefrontal cortices (dmPFC and dlPFC) together support cognitive control, with dmPFC responsible for monitoring performance and dlPFC responsible for adjusting behavior. The dlPFC contains a topographic organization that reflects complexity of control demands, with more anterior regions guiding increasingly abstract processing. Recent evidence for a similar gradient within dmPFC suggests the possibility of parallel, hierarchical organization. Here, we measured connectivity between functional nodes of dmPFC and dlPFC using resting-state functional magnetic resonance imaging in humans. We found a posterior-to-anterior connectivity gradient; posterior dmPFC maximally connected to posterior dlPFC and anterior dmPFC maximally connected to anterior dlPFC. This parallel topographic pattern replicated across three independent datasets collected on different scanners, within individual participants, and through both point-to-point and voxelwise analyses. We posit a model of cognitive control characterized by hierarchical interactions—whose level depends on current environmental demands—between functional subdivisions of medial and lateral PFC.
A Methodology for Dialogue Act Modeling from Part-of-Speech Annotations of Practical Dialogues in Mexican Spanish

This article proposes a methodology to model dialogue acts (DA) from part-of-speech (POS) annotations in practical dialogues in Mexican Spanish. An example using empirical data is presented to illustrate this methodology. DA and POS annotations were obtained from DIME, a spoken dialogue corpus in which speakers perform tasks in a virtual environment on a collaborative basis. POS structure is a key notion in this methodology. It is the POS tagging sequence for particular instances of utterances. The models are produced as probability tables of pairs of DA annotations and POS structures. Results show that a number of POS structures are more frequently used by speakers to communicate particular DA types. These patterns can be exploited to enhance systems for automatic recognition of DA.
International Journal of Behavioral Development Volume 30, 2006, List of Reviewers

Children's sense and reasoning about territory and land ownership may develop differently in contexts of poverty and where narratives of dispossession are a part of daily life and are of political and historical significance, as is the case in the Palestinian refugee context in Lebanon. In this study we looked at how 3-and 5-year-old refugee Palestinian and American children distribute land among neighbors disputing over an unoccupied piece of land separating their properties. Children were required to make distributive justice decisions about 4 scripted scenarios that involved a pretend conflict between different types of neighbors (rich/poor; ingroup vs. outgroup; neighbors of the same material wealth and neighbors that were either poor or rich as well as ingroup members). Both 5-year-old Palestinian and American children showed inequality aversion, favoring the poor neighbor over the rich in their distributive justice decisions. This first finding suggests that being born into poverty does not make young children more sensitive to material inequity, even if the object of dispute is of particular cultural relevance. However, a second main finding suggests that extreme circumstances potentially translate into enhanced ingroup partialities, above and beyond the universal normative trend toward inequity aversion.
‘It's the way that you look at it’—a cognitive neuropsychological account of SSRI action in depression

The fact that selective serotonin reuptake inhibitors (SSRIs) have antidepressant effects in some patients supports the notion that serotonin plays a role in the mode of action of antidepressant drugs. However, neither the way in which serotonin may alleviate depressed mood nor the reason why several weeks needs to elapse before the full antidepressant effect of treatment is expressed is known. Here, we propose a neuropsychological theory of SSRI antidepressant action based on the ability of SSRIs to produce positive biases in the processing of emotional information. Both behavioural and neuroimaging studies show that SSRI administration produces positive biases in attention, appraisal and memory from the earliest stages of treatment, well before the time that clinical improvement in mood becomes apparent. We suggest that the delay in the clinical effect of SSRIs can be explained by the time needed for this positive bias in implicit emotional processing to become apparent at a subjective, conscious level. This process is likely to involve the re-learning of emotional associations in a new, more positive emotional environment. This suggests intriguing links between the effect of SSRIs to promote synaptic plasticity and neurogenesis, and their ability to remediate negative emotional biases in depressed patients.
Multimodal meeting analysis by segmentation and classification of meeting events based on a higher level semantic approach

This paper encompasses the analysis of meetings for segmentation into sub-genres. Therefore, an approach on a higher semantic level has been chosen. The algorithms make use of the results of specialized recognizers like a speaker turn detector and a gesture recognizer. Basically, the goal of this investigation was to answer the question, how well meeting analysis is possible if only the results of these recognizers are available. After introducing briefly the basics of these recognizers, two slightly different methods for the segmentation are presented. The results show the potential of the used methods to find the segment boundaries and to categorize the detected segments into sub-genres (also called meeting events or group actions). Based on this segmentation, further analysis regarding topic detection and content extraction can be accomplished.