Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces

The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizontal position of targets in aerial images. Images were presented by means of the rapid serial visual presentation technique at rates of 5, 6 and 10 Hz. We created three different cBCIs and tested a participant selection method in which groups are formed according to the similarity of participants’ performance. The N2pc that is elicited in our experiments contains information about the position of the target along the horizontal axis. Moreover, combining information from multiple participants provides absolute median improvements in the area under the receiver operating characteristic curve of up to 21% (for groups of size 3) with respect to single-user BCIs. These improvements are bigger when groups are formed by participants with similar individual performance, and much of this effect can be explained using simple theoretical models. Our results suggest that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets.
The Relationship of Orthorexic Tendencies with Eating Disorder Tendencies and Gender in a Group of University Students

Orthorexia Nervosa is described as a psychopathological preoccupation about healthy food (Bratman & Knight, 2001). Investigation of the relationship of orthorexic tendencies with other eating disorder tendencies and gender among a group of university students was aimed as purpose of the presented study. Participants are 100 university students (57 females, 43 male) who volunteered to answer the scales when study explained to them. Orthorexic tendencies were measured by ORTO-11 scale and eating attitudes were measured by YTT-40 and REZZY scales. Intercorrelations among variables revealed that orthorexic tendencies and eating attitudes are all tended to rise together. On the other hand no significant correlation was found between YTT-40 and ORTO-11 scores. It was thought that lack of any significant correlation between YTT-40 and ORTO-11 scores can be interpreted as another indication of the differences in terms of characteristic symptoms between Anorexia Nervosa and Orthorexia Nervosa. Results points out that REZZY scale seems more related than YTT-40 in terms of covering orthorexic symptoms. According to findings, females’ orthorexic tendencies (which measured by ORTO-11) and eating disorder tendencies (which measured by REZZY and YTT-40) are higher than males’. Overweight group showed lower orthorexic tendencies than participants who has normal weight, which is parallel with the results that reveals when orthorexic tendencies decline body mass index scores of participants’ rise as a result of not being pathologically preoccupied with 'healthy' eating. It is hoped that the findings of the present study by combining with other related studies will be helpful regarding building a model for this disorder and to debates about classification of orthorexia nervosa. Besides findings are also important in terms of treatment plans regarding this disorder. As mentioned in literature too, more future investigations are needed about orthorexia nervosa. More research with various participants and perhaps with various measurement tools can be suggested for clarification of existing unanswered questions in this relatively young area of investigation.
Trends of Mobile Learning in Computing Education from 2006 to 2014: A Systematic Review of Research Publications

The majority of the existing research regarding mobile learning in computing education has primarily focused on studying the effectiveness of, and in some cases reporting about, implemented mobile learning solutions. However, it is equally important to explore development and application perspectives on the integration of mobile learning into computing education and identify practical implications for learning and teaching practices. In this study, the authors performed a systematic review of scientific publications related to mobile learning in computing education. After identifying relevant publications, they analysed them from three main aspects: technology and development, design of mobile learning solutions and applications, and implications for learning. The authors' study reveals that mobile learning in computing education has the potential to increase several affective traits of learners. In addition, mobile learning in computing education has matured enough to be mainly concerned with the mainstreaming of the computing curriculum rather than basic research.
Time Parameterization of Humanoid-Robot Paths

This paper proposes a unified optimization framework to solve the time-parameterization problem of humanoid-robot paths. Even though the time-parameterization problem is well known in robotics, the application to humanoid robots has not been addressed. This is because of the complexity of the kinematical structure as well as the dynamical motion equation. The main contribution of this paper is to show that the time parameterization of a statically stable path to be transformed into a dynamically stable trajectory within the humanoid-robot capacities can be expressed as an optimization problem. Furthermore, we propose an efficient method to solve the obtained optimization problem. The proposed method has been successfully validated on the humanoid robot HRP-2 by conducting several experiments. These results have revealed the effectiveness and the robustness of the proposed method.
Does Gene Tree Discordance Explain the Mismatch between Macroevolutionary Models and Empirical Patterns of Tree Shape and Branching Times?

Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth–death and multispecies coalescent model can explain the difference in empirical trees and birth–death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion.
Effect of dietary lactose on cecal morphology, pH, organic acids, and Salmonella enteritidis organ invasion in Leghorn chicks.

The effect of 14 or 19 days of 10% dietary lactose administration on Salmonella enteritidis (SE) colonization and histological, morphometric, and organic acid changes of the ceca were investigated. At Day 13 or 18, chicks were challenged with 10(8) cfu of SE. Chicks were killed and cultured 24 h later. A reduction in the total number of positive SE organ invasions was observed following 14 days (P < .001) or 19 days (P < .005) of treatment in chicks fed with lactose. Histological examination revealed a marked reduction in lamina propria thickness of ceca, as well as subjective epithelial cell proliferation from chicks following either 14 or 19 days of lactose administration. Using morphometric analysis, a reduction in the mean lamina propria thickness in chickens fed with lactose during 14 or 19 days was observed as compared with controls (P < .05). Yet, an increase (P < .05) in the mean epithelial cell length in both lactose-treated groups was observed as compared with controls. Lactose decreased luminal pH (P < .05) and increased the concentration of acetic, propionic, butyric, and lactic acid (P < .05). These data indicate that lactose-induced resistance to SE organ invasion is associated not only with an increase in organic acid concentration but also with measurable morphological changes of the cecal mucosa.
A survey of frequent subgraph mining algorithms

Abstract Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets. The research goals are directed at: (i) effective mechanisms for generating candidate subgraphs (without generating duplicates) and (ii) how best to process the generated candidate subgraphs so as to identify the desired frequent subgraphs in a way that is computationally efficient and procedurally effective. This paper presents a survey of current research in the field of frequent subgraph mining and proposes solutions to address the main research issues.
The influence of dietary tryptophan on broiler chick growth and lipid metabolism as mediated by dietary protein levels.

Three experiments were conducted to determine how dietary protein and tryptophan influence the lipid metabolism of growing broiler chicks. A diet-dilution method (corn-corn gluten meal-gelatin summit/corn starch basal) was used in three factorial experiments. Various levels of protein and tryptophan were fed in each experiment: protein from 16 to 28% and tryptophan from . 34 to 2.74% of protein. Gain was maximized when the dietary levels of tryptophan were . 83 +/- . 03, 77 +/- . 04, 77 +/- . 05, and . 78 +/- . 05% of the protein for 16, 20, 24, and 28% dietary protein, respectively. The requirement estimates for feed efficiency and gain were similar. Liver lipids significantly decreased as the level of dietary tryptophan increased at each protein level (P less than .0001). Dietary tryptophan did not significantly alter the concentration of total plasma lipid in the chicks or in the carcass lipid content (P greater than .2399). Tryptophan supplementation significantly increased the concentration of plasma linoleic acid and plasma free tryptophan. The requirement of the chicks for tryptophan was estimated to be . 80 +/- . 01% of the dietary protein for the growing chick. Increased liver lipid and decreased plasma tryptophan are diagnostic lesions suggesting a tryptophan deficiency.
Trends and disparities in antiretroviral therapy initiation and virologic suppression among newly treatment-eligible HIV-infected individuals in North America, 2001-2009.

BACKGROUND Since the mid-1990s, effective antiretroviral therapy (ART) regimens have improved in potency, tolerability, ease of use, and class diversity. We sought to examine trends in treatment initiation and resulting human immunodeficiency virus (HIV) virologic suppression in North America between 2001 and 2009, and demographic and geographic disparities in these outcomes. METHODS We analyzed data on HIV-infected individuals newly clinically eligible for ART (ie, first reported CD4+ count<350 cells/µL or AIDS-defining illness, based on treatment guidelines during the study period) from 17 North American AIDS Cohort Collaboration on Research and Design cohorts. Outcomes included timely ART initiation (within 6 months of eligibility) and virologic suppression (≤500 copies/mL, within 1 year). We examined time trends and considered differences by geographic location, age, sex, transmission risk, race/ethnicity, CD4+ count, and viral load, and documented psychosocial barriers to ART initiation, including non-injection drug abuse, alcohol abuse, and mental illness. RESULTS Among 10,692 HIV-infected individuals, the cumulative incidence of 6-month ART initiation increased from 51% in 2001 to 72% in 2009 (Ptrend<.001). The cumulative incidence of 1-year virologic suppression increased from 55% to 81%, and among ART initiators, from 84% to 93% (both Ptrend<.001). A greater number of psychosocial barriers were associated with decreased ART initiation, but not virologic suppression once ART was initiated. We found significant heterogeneity by state or province of residence (P<.001). CONCLUSIONS In the last decade, timely ART initiation and virologic suppression have greatly improved in North America concurrent with the development of better-tolerated and more potent regimens, but significant barriers to treatment uptake remain, both at the individual level and systemwide.
Software-Defined Microgrid Control for Resilience Against Cyber Attacks

Microgrids (MGs) rely on networked control supported by off-the-shelf wireless communications. This makes them vulnerable to cyber-attacks, such as denial-of-service (DoS). In this paper, we mitigate those attacks by applying the concepts of (i) separation of data plane from network control plane, inspired by the software defined networking (SDN) paradigm, and (ii) agile reconfiguration of the data plane connections. In our architecture, all generators operate as either voltage regulators (active agents), or current sources (passive agents), with their operating mode being locally determined, according the global information on the MG state. The software-defined MG control utilizes the fact that, besides the data exchange on the wireless channel, the power-grid bus can be used to create side communication channels that carry control plane information about the state of the MG. For this purpose, we adopt power talk, a modem-less, low-rate, power-line communication designed for direct current (DC) MGs. The results show that the proposed software-defined MG offers superior performance compared to the static MG, as well as resilience against cyber attacks.
Development and implementation of a low cost image correlation system to obtain full-field in-plane displacement and strain data

When using multi-axial testing, obtaining in-plane strain and displacement data can be difficult and costly. Montana State University’s In Plane Loader (IPL) can apply any number of loads in the X and Y axes and as rotation but can only provide the displacement data at the grips. This project uses a Canon consumer-model digital single lens reflex camera and a series of matlab codes to provide in-plane displacement and strain data at as many points on the surface of the loaded specimen as required using Digital Image Correlation. The system has been successfully used to measure surface and boundary displacements on composite and aluminum samples, as well as on glued aluminum joints. The software system has been shown to estimate strains with a strain error of less then 0.0002 m/m or ±0.5% placing it within ASTM-B2 classification. It also has been shown to measure displacements to within 0.02 pixels accuracy, which for tests on the IPL translates to 0.007mm. The hardware/software system has also been used with the IPL to estimate Young’s modulus of aluminum with less then 5% error and yield strength with just over 10% error.
Enhance word representation for out-of-vocabulary on Ubuntu dialogue corpus

Ubuntu dialogue corpus is the largest public available dialogue corpus to make it feasible to build end-to-end deep neural network models directly from the conversation data. One challenge of Ubuntu dialogue corpus is the large number of out-of-vocabulary words. In this paper we proposed an algorithm which combines the general pre-trained word embedding vectors with those generated on the task-specific training set to address this issue. We integrated character embedding into Chen et al's Enhanced LSTM method (ESIM) and used it to evaluate the effectiveness of our proposed method. For the task of next utterance selection, the proposed method has demonstrated a significant performance improvement against original ESIM and the new model has achieved state-of-the-art results on both Ubuntu dialogue corpus and Douban conversation corpus. In addition, we investigated the performance impact of end-of-utterance and end-of-turn token tags.
Gene Expression Meta-Analysis of Seven Candidate Gene Sets for Diabetes Traits Following a GWAS Pathway Study

Seven gene sets were significantly enriched for SNP associations with diabetes, and considered as potential diabetes pathways in a previous meta-analysis of diabetes GWAS. This study aims to examine if these gene sets also have expression associations with diabetes. The analysis was conducted using pooled data from 23 diabetes gene expression studies. Gene associations were examined using linear modeling with an empirical Bayes approach, and pathway associations were investigated by testing enrichment for significant genes. Meta-analyses were performed to investigate gene and pathway associations in all studies and tissue types. The analysis showed that six gene sets and three member genes of ACADSB, RASSF2, and KLF12 had significant associations with diabetes traits. The findings suggest that these gene sets are related to diabetes regulation, and their functions tend to be tissue non-specific.
Tramadol state-dependent memory: involvement of dorsal hippocampal muscarinic acetylcholine receptors

The effects on tramadol state-dependent memory of bilateral intradorsal hippocampal (intra-CA1) injections of physostigmine, an acetylcholinesterase inhibitor, and atropine, a muscarinic acetylcholine receptor antagonist, were examined in adult male NMRI mice. A single-trial step-down passive avoidance task was used for the assessment of memory retention. Post-training intra-CA1 administration of an atypical &mgr;-opioid receptor agonist, tramadol (0.5 and 1 &mgr;g/mouse), dose dependently impaired memory retention. Pretest injection of tramadol (0.5 and 1 &mgr;g/mouse, intra-CA1) induced state-dependent retrieval of the memory acquired under the influence of post-training tramadol (1 &mgr;g/mouse, intra-CA1). A pretest intra-CA1 injection of physostigmine (1 &mgr;g/mouse) reversed the memory impairment induced by post-training administration of tramadol (1 &mgr;g/mouse, intra-CA1). Moreover, pretest administration of physostigmine (0.5 and 1 &mgr;g/mouse, intra-CA1) with an ineffective dose of tramadol (0.25 &mgr;g/mouse, intra-CA1) also significantly restored retrieval. Pretest administration of physostigmine (0.25, 0.5, and 1 &mgr;g/mouse, intra-CA1) by itself did not affect memory retention. A pretest intra-CA1 injection of the atropine (1 and 2 &mgr;g/mouse) 5 min before the administration of tramadol (1 &mgr;g/mouse, intra-CA1) dose dependently inhibited tramadol state-dependent memory. Pretest administration of atropine (0.5, 1, and 2 &mgr;g/mouse, intra-CA1) by itself did not affect memory retention. It can be concluded that dorsal hippocampal muscarinic acetylcholine receptor mechanisms play an important role in the modulation of tramadol state-dependent memory.
MPC-Inspired Neural Network Policies for Sequential Decision Making

In this paper we investigate the use of MPC-inspired neural network policies for sequential decision making. We introduce an extension to the DAgger algorithm for training such policies and show how they have improved training performance and generalization capabilities. We take advantage of this extension to show scalable and efficient training of complex planning policy architectures in continuous state and action spaces. We provide an extensive comparison of neural network policies by considering feed forward policies, recurrent policies, and recurrent policies with planning structure inspired by the Path Integral control framework. Our results suggest that MPC-type recurrent policies have better robustness to disturbances and modeling error.
Joint Learning of Binocularly Driven Saccades and Vergence by Active Efficient Coding

This paper investigates two types of eye movements: vergence and saccades. Vergence eye movements are responsible for bringing the images of the two eyes into correspondence, whereas saccades drive gaze to interesting regions in the scene. Control of both vergence and saccades develops during early infancy. To date, these two types of eye movements have been studied separately. Here, we propose a computational model of an active vision system that integrates these two types of eye movements. We hypothesize that incorporating a saccade strategy driven by bottom-up attention will benefit the development of vergence control. The integrated system is based on the active efficient coding framework, which describes the joint development of sensory-processing and eye movement control to jointly optimize the coding efficiency of the sensory system. In the integrated system, we propose a binocular saliency model to drive saccades based on learned binocular feature extractors, which simultaneously encode both depth and texture information. Saliency in our model also depends on the current fixation point. This extends prior work, which focused on monocular images and saliency measures that are independent of the current fixation. Our results show that the proposed saliency-driven saccades lead to better vergence performance and faster learning in the overall system than random saccades. Faster learning is significant because it indicates that the system actively selects inputs for the most effective learning. This work suggests that saliency-driven saccades provide a scaffold for the development of vergence control during infancy.