Miracle-dz/UniFAR-FTUs huggingface dataset:
No difference in flanker effects for sad and happy schematic faces: A parametric study of temporal parameters

Flanker effects with schematic faces have been reported to be larger for happy than for sad faces, allegedly because sad faces restrict the focus of spatial attention. We report a parametric study that fails to replicate this effect. Participants performed speeded identifications of happy or sad faces accompanied by compatible or incompatible flanker faces. We varied the temporal interval between presentation of central target and flanker faces because differential attentional effects of happy and sad faces should critically depend on this variable. In contradiction to the literature, we found large compatibility effects that were modulated by temporal parameters, but not by the emotional valence of the faces, and not in the way consistent with differential attentional modulation. We conclude that previously reported asymmetries in flanker tasks with schematic faces are not due to changes in attentional scope (mediated by emotion or otherwise), but rather to perceptual low-level differences.
Visualization of species pairwise associations: a case study of surrogacy in bird assemblages

Quantifying and visualizing species associations are important to many areas of ecology and conservation biology. Species networks are one way to analyze species associations, with a growing number of applications such as food webs, nesting webs, plant–animal mutualisms, and interlinked extinctions. We present a new method for assessing and visualizing patterns of co-occurrence of species. The method depicts interactions and associations in an analogous way with existing network diagrams for studying pollination and trophic interactions, but adds the assessment of sign, strength, and direction of the associations. This provides a distinct advantage over existing methods of quantifying and visualizing co-occurrence. We demonstrate the utility of our new approach by showing differences in associations among woodland bird species found in different habitats and by illustrating the way these can be interpreted in terms of underlying ecological mechanisms. Our new method is computationally feasible for large assemblages and provides readily interpretable effects with standard errors. It has wide applications for quantifying species associations within ecological communities, examining questions about particular species that occur with others, and how their associations can determine the structure and composition of communities.
Molecular Basis of the Dominant Negative Effect of a Glycine Transporter 2 Mutation Associated with Hyperekplexia*

Background: Hyperekplexia is caused by defective glycinergic neurotransmission. Results: A dominant negative glycine transporter-2 mutant is trapped in a calnexin-bound state and retains wild type GlyT2 in the endoplasmic reticulum. Conclusion: Chemical chaperones rescue the folding defect of the mutant and overcome its dominant negative effect. Significance: This opens the way to revert the dominant negative effect exerted by the mutant associated with hyperekplexia in neurons. Hyperekplexia or startle disease is a rare clinical syndrome characterized by an exaggerated startle in response to trivial tactile or acoustic stimuli. This neurological disorder can have serious consequences in neonates, provoking brain damage and/or sudden death due to apnea episodes and cardiorespiratory failure. Hyperekplexia is caused by defective inhibitory glycinergic neurotransmission. Mutations in the human SLC6A5 gene encoding the neuronal GlyT2 glycine transporter are responsible for the presynaptic form of the disease. GlyT2 mediates synaptic glycine recycling, which constitutes the main source of releasable transmitter at glycinergic synapses. Although the majority of GlyT2 mutations detected so far are recessive, a dominant negative mutant that affects GlyT2 trafficking does exist. In this study, we explore the properties and structural alterations of the S512R mutation in GlyT2. We analyze its dominant negative effect that retains wild-type GlyT2 in the endoplasmic reticulum (ER), preventing surface expression. We show that the presence of an arginine rather than serine 512 provoked transporter misfolding, enhanced association to the ER-chaperone calnexin, altered association with the coat-protein complex II component Sec24D, and thereby impeded ER exit. The S512R mutant formed oligomers with wild-type GlyT2 causing its retention in the ER. Overexpression of calnexin rescued wild-type GlyT2 from the dominant negative effect of the mutant, increasing the amount of transporter that reached the plasma membrane and dampening the interaction between the wild-type and mutant GlyT2. The ability of chemical chaperones to overcome the dominant negative effect of the disease mutation on the wild-type transporter was demonstrated in heterologous cells and primary neurons.
Cultural Variations in the Reasons People Provide Avoidance Support

This study explores variations in the reasons people engage in avoidance as a support strategy across the two cultures of the United States and China. An avoidance-support belief scale was developed. Exploratory factor analysis of responses from 231 Americans and 219 Chinese identified three dimensions of the scale: (1) protecting the support seeker from harm by avoiding, (2) maintaining a positive mood by avoiding, and (3) spiritual/philosophical reasons for avoiding. Follow-up analyses revealed that Chinese scored significantly and substantially higher than Americans for all three avoidance support dimensions. Implications and future research directions are discussed.
Phenotypic variation in California populations of valley oak (Quercus lobata Née) sampled along elevational gradients

California oaks exhibit tremendous phenotypic variation throughout their range. This variation reflects phenotypic plasticity in tree response to local environmental conditions as well as genetic differences underlying those phenotypes. In this study, we analyze phenotypic variation in leaf traits for valley oak adults sampled along three elevational transects and in young seedlings grown from their acorns in greenhouse conditions. This project represents the early phase of a long-term provenance study of valley oak (see Delfino Mix and others, Establishing a range-wide provenance test in valley oak (Quercus lobata Nee) at two California sites, these proceedings) where we subsample the maternal families sampled along elevation gradients to assess the extent to which selection may be shaping geographical variation in leaf phenotypes of valley oak. We find that leaf thickness is the trait that shows correlations in adult populations in the field and significant variation in the greenhouse. For this trait, we also found significant differentiation across maternal families, providing preliminary evidence that this trait experiences differential selection across natural populations with different environments. This study, part of a large-scale provenance/genomic study of the genetic basis of phenotypic variation, provides an early analysis of leaf traits that may play an important role in local adaptation to climate environments and provide background for management and restoration of California oak forests.
A Comparison of Teacher-Directed versus Peer-Assisted Instruction to Struggling First-Grade Readers

The purpose of this research was to provide more definitive answers about best instructional delivery arrangements for accelerating the reading growth of struggling readers. 2 instructional methods-peer-assisted instruction using carefully prescribed materials and routines and small-group teacher-directed instruction-were compared both to typical undifferentiated instruction and to each other. 22 general education first-grade teachers of 89 economically and ethnically diverse students who were low performers in reading participated in this research. 7 teachers conducted first-grade PALS, 7 teachers conducted teacher-directed small-group lessons, and 8 teachers served as the contrast group. To ensure that effects of the instructional delivery arrangement were truly being examined, both small-group teachers and peers taught from parallel materials and followed parallel routines that had been validated previously. Multiple measures of reading were collected, including pre- and postmeasures of timed and untimed word identification and phonetic decoding, and comprehension. Likewise, measures of phonemic segmentation and oral reading fluency were collected every 2 weeks. Results suggested that both peer-assisted instruction and small-group teacher-directed instruction, on average, enhanced reading performance of struggling readers more than typical, undifferentiated instruction both in terms of statistical significance and in terms of educational relevance. Results also implied that receiving instruction from a teacher in a small group was somewhat more powerful than similar instruction delivered by a classroom peer.
Learning to Extract Text-Based Information from the World Wide Web

There is a wealth of information to be mined from narrative text on the World Wide Web. Unfortunately, standard natural language processing (NLP) extraction techniques expect full, grammatical sentences, and perform poorly on the choppy sentence fragments that are often found on web pages. This paper1 introduces Webfoot, a preprocessor that parses web pages into logically coherent segments based on page layout cues. Output from Webfoot is then passed on to CRYSTAL, an NLP system that learns text extraction rules from example. Webfoot and CRYSTAL transform the text into a formal representation that is equivalent to relational database entries. This is a necessary first step for knowledge discovery and other automated analysis of free text.
Sibling incest: A literature review and a clinical study

Abstract Few previous studies have explored the characteristics and dynamics of adolescent sibling incest. The objectives of this paper were twofold: first, to conduct a literature review that accounts for earlier research in the area, and secondly, to conduct a clinical study to explore differences regarding the characteristics of a group of adolescent sibling incest offenders (n=21) compared to a group of adolescent non-sibling offenders (n=24). Comparisons were made regarding variables such as family dysfunction, the offenders' prior victimization and offending behaviour. The data were derived from intake assessment files and semi-structured interviews with 45 adolescents who had sexually offended. The sibling incest offender group had grown up more often in dysfunctional families. Moreover, the results indicated that the offending behaviour in the sibling incest group was more severe. The study gives some empirical support for the possibility that sibling incest can be one sign, among others, of maltreatment during childhood.
Declarative analysis of noisy information networks

There is a growing interest in methods for analyzing data describing networks of all types, including information, biological, physical, and social networks. Typically the data describing these networks is observational, and thus noisy and incomplete; it is often at the wrong level of fidelity and abstraction for meaningful data analysis. This has resulted in a growing body of work on extracting, cleaning, and annotating network data. Unfortunately, much of this work is ad hoc and domain-specific. In this paper, we present the architecture of a data management system that enables efficient, declarative analysis of large-scale information networks. We identify a set of primitives to support the extraction and inference of a network from observational data, and describe a framework that enables a network analyst to easily implement and combine new extraction and analysis techniques, and efficiently apply them to large observation networks. The key insight behind our approach is to decouple, to the extent possible, (a) the operations that require traversing the graph structure (typically the computationally expensive step), from (b) the operations that do the modification and update of the extracted network. We present an analysis language based on Datalog, and show how to use it to cleanly achieve such decoupling. We briefly describe our prototype system that supports these abstractions. We include a preliminary performance evaluation of the system and show that our approach scales well and can efficiently handle a wide spectrum of data cleaning operations on network data.
MIMS: A Minimally Invasive Monitoring Sensor Platform

This paper describes a minimally invasive sensor platform for active and passive monitoring of human movements and physiological signals. Such a system is needed in cases where 24 × 7 monitoring is required, as in older adults with cognitive impairment, dementia and Alzheimer's disease. The passive monitoring systems used today are useful only in detecting events after they happen; the accuracy and speed of detection is questionable. The noninvasive nature of such systems does not bring trade off benefits to early detection and prevention of emergency incidents. We compare some existing sensor platforms and present our monitoring approach using minimally invasive wearable sensor device(s). With a Minimally Invasive Monitoring Sensor (MIMS), using advanced intelligent systems, we analyze the physiological signal data preceding potential emergency events in order to predict them quickly. The Virtual Hub is the core component of MIMS, which acts as a gateway between a monitored person and her/his caregivers, as well as a shared access point between active and passive sensing devices. Some preliminary results are presented here from our sleep-related fall study using two heterogeneous sensor systems.
Faster Projection-free Convex Optimization over the Spectrahedron

Minimizing a convex function over the spectrahedron, i.e., the set of all positive semidefinite matrices with unit trace, is an important optimization task with many applications in optimization, machine learning, and signal processing. It is also notoriously difficult to solve in large-scale since standard techniques require expensive matrix decompositions. An alternative, is the conditional gradient method (aka Frank-Wolfe algorithm) that regained much interest in recent years, mostly due to its application to this specific setting. The key benefit of the CG method is that it avoids expensive matrix decompositions all together, and simply requires a single eigenvector computation per iteration, which is much more efficient. On the downside, the CG method, in general, converges with an inferior rate. The error for minimizing a $\beta$-smooth function after $t$ iterations scales like $\beta/t$. This convergence rate does not improve even if the function is also strongly convex. In this work we present a modification of the CG method tailored for convex optimization over the spectrahedron. The per-iteration complexity of the method is essentially identical to that of the standard CG method: only a single eigenvecor computation is required. For minimizing an $\alpha$-strongly convex and $\beta$-smooth function, the expected approximation error of the method after $t$ iterations is: $$O\left({\min\{\frac{\beta{}}{t} ,\left({\frac{\beta\sqrt{\textrm{rank}(\textbf{X}^*)}}{\alpha^{1/4}t}}\right)^{4/3}, \left({\frac{\beta}{\sqrt{\alpha}\lambda_{\min}(\textbf{X}^*)t}}\right)^{2}\}}\right) ,$$ where $\textbf{X}^*$ is the optimal solution. To the best of our knowledge, this is the first result that attains provably faster convergence rates for a CG variant for optimization over the spectrahedron. We also present encouraging preliminary empirical results.
CLASIC VERSUS NOVEL IN REDUCTION OF ACUTE ANTERIOR DISLOCATION OF THE SHOULDER: A COMPARISON OF FOUR REDUCTION TECHNIQUES.

AIM The purpose of our study is to compare four different techniques for reduction shoulder dislocation in term of efficacy, duration until reduction and pain felt by patient during the procedure. MATERIAL AND METHODS During 2015 year, we conducted a study on 50 chronological patients with anterior shoulder dislocation. After exclusion of four patients, the remaining 46 (74% males, mean age 44.6 +/- 20.03 years, range 18 to 89) were randomly assigned in four groups and reduced by Cunningham (C), Kocher (K), Mothes (M) and Hipocrat (H) techniques. All the patients were sedated using Midazolam (2 mg) and Fentanyl (1 microg/kgbw) except patients who underwent Cunningham technique. RESULTS The success rate was 76.9% in C group, 98.4% in K group, 90.2% in M group and 87.96% in H group (p>0.05). The level of pain in C group was similar to the other groups in the absence of pain medication (p<0.05). CONCLUSIONS Cunningham technique is a simple, single person technique, drug free, less painful and safer, comparable with other "classical" methods.
Uncriticality-Directed Low-Power Instruction Scheduling

Intelligent mobile information devices require low-power and high-performance processors. In order to reduce energy consumption with maintaining computing performance, we proposed to utilize information regarding instruction criticality. Every functional unit in our processor has different latency and energy consumption. Only critical instructions are executed in power-hungry units, and the total energy consumption can be reduced. While we have studied several techniques to identify critical instructions for years, we have not found any technique that achieves both simplicity and high accuracy to identify. In this paper, we propose to exploit uncriticality rather than criticality. Only uncritical instructions are executed in power-efficient units, and energy consumption can be reduced. Our simulation results show approximately 10% energy reduction.
Hardiness Profiles: Defining Clusters of the Dispositional Resilience Scale and Their Relation to Soldiers’ Health

K-means cluster analysis was performed on a Norwegian infantry battalion deployed in Kosovo. A four-cluster solution was obtained. The High Hardy cluster showed high scores on all three facets of hardiness. The Low Hardy cluster showed low scores on all facets. The Sensation Seeking cluster was described as low on control and commitment but high on challenge. The Rigid Control cluster was characterized by low on challenge but medium to high on control and commitment. An analysis of variance (ANOVA) showed higher General Health Questionnaire (GHQ-30) scores in the Rigid Controls compared to both the High Hardy and the Sensation Seekers, and the Low Hardy cluster scoring higher than the Sensation Seekers.
Fine permafrost deformation features observed using TerraSAR-X ST mode InSAR in Beiluhe of the Qinghai-Tibet Plateau, West China

Generally speaking the permafrost in the Tibet region is influenced by the global climate change. The synthetic aperture radar interferometry (InSAR) could detect the surface uplift/subsidence in millimeter-level resolutions, which is powerful for the permafrost monitoring. In recent years, high-resolution synthetic aperture radar (SAR) with centimeter-level resolution makes it possible to explore the permafrost change not only in regional scales but also in the local scales. In this paper, TerraSAR-X Staring Spotlight (ST) mode data in the Beiluhe of the Qinghai-Tibet Plateau (QTP) from Jun. 2004 to Dec. 2004 was used to explore the fine features of permafrost during the thawing/freezing seasons, and the coupling between the permafrost and the infrastructures in local scales. It is shown that the main displacement of permafrost is related to the landcover types, ground materials and soil moisture. The drainage system has impact on the settlement and heave in the permafrost area. The asymmetric deformation patterns of the thermalkarst lakes are determined by the permafrost configurations of lakes. The anthropogenic activities and infrastructures are the other factor influencing the permafrost thermal regime and displacement distribution.
Added Redundancy Explicit Authentication at the Block Level for Parallelized Encryption and Integrity Checking on Processor-Memory Buses

The bus between the System on Chip (SoC) and the external memory is one of the weakest points of computing systems because an adversary can easily probe this bus in order to read private data, to retrieve software code (data confidentiality concern) or to inject data (data integrity concern). The conventional way to provide data confidentiality and integrity is to implement a dedicated hardware engine for each security service. Being secured, this approach prevents parallelizability of the underlying computations. In this paper, we introduce the concept of Added Redundancy Explicit Authentication (AREA) at the block level and we describe a Parallelized Encryption and Integrity Checking Engine (PE-ICE) based on this concept. PE-ICE has been designed to provide an effective solution to ensure both security services while allowing for full parallelization on processor read and write operations and optimizing the hardware resources. Compared to standard encryption which provides only confidentiality, we show that PE-ICE additionally guarantees code and data integrity for less than 4% of run-time performance overhead and at no additional hardware cost.
A Hierarchical Computational Model of Selective Visual Attention

Computational model of visual attention has got more and more attention in machine vision and image processing. A hierarchical computational model for selective visual attention is proposed in this paper. This model simulates the attention mechanism from far (coarse) to near (fine) of human visual system. Firstly, the input image is analyzed at the coarsest resolution and visual saliency of each part is computed at this level. Regions of attention are selected according to the saliency. Then the sub-regions of the selected region compete for attention at a finer resolution. This process is done iteratively until every salient region and its sub-regions have been processed at different levels respectively. The proposed model has been tested on many natural images. Experiment results show that the proposed model is valid and the attention results are consistent with human visual system.
Middle years students’ experience with new media

This study draws on a survey of 800 upper primary school students concerning their knowledge of certain ‘new media’ applications. The findings concur with other studies in suggesting that students’ relationship with technology is more complex and nuanced than is conveyed by a simple branding of ‘digital native’. Some differential experiences between classes and genders are identified, along with an important minority of students who have much more out-of-school experience with new media than others. The role of the school and teacher in inducting students to new media is presented as central, with important implications for curriculum leadership and teacher professional development.
Considering power variations of DVS processing elements for energy minimisation in distributed systems

Dynamic voltage scaling (DVS) is a powerful technique to reduce power dissipation in embedded systems. In this paper we investigate the problem of considering DVS-processing element (DVS-PE) power variations dependent on the executed tasks, during the synthesis of distributed embedded systems, and its impact on the energy savings. Unlike previous approaches, which minimise the energy consumption by exploiting the available slack time without considering the PE power profiles, a new and fast heuristic for the voltage scaling problem is proposed, which improves the voltage selection for each task dependent on the individual power dissipation caused by that task. Experimental results show that energy reductions with up to 80.7% were achieved by integrating the proposed DVS algorithm, which considers the PE power profiles, into the co-synthesis of distributed systems.