Miracle-dz/UniFAR-FTUs huggingface dataset:
Parent-Child Resemblance in Weight Status and Its Correlates in the United States

Background Few studies have examined parent-child resemblance in body weight status using nationally representative data for the US. Design We analyzed Body Mass Index (BMI), weight status, and related correlates for 4,846 boys, 4,725 girls, and their parents based on US nationally representative data from the 2006 and 2007 Medical Expenditure Panel Survey (MEPS). Pearson partial correlation coefficients, percent agreement, weighted kappa coefficients, and binary and multinomial logistic regression were used to examine parent-child resemblance, adjusted for complex sampling design. Results Pearson partial correlation coefficients between parent and child’s BMI measures were 0.15 for father-son pairs, 0.17 for father-daughter pairs, 0.20 for mother-son pairs, and 0.23 for mother-daughter pairs. The weighted kappa coefficients between BMI quintiles of parent and child ranged from −0.02 to 0.25. Odds ratio analyses found children were 2.1 (95% confidence interval (CI): 1.6, 2.8) times more likely to be obese if only their father was obese, 1.9 (95% CI: 1.5, 2.4) times more likely if only their mother was obese, and 3.2 (95% CI: 2.5, 4.2) times more likely if both parents were obese. Conclusions Parent-child resemblance in BMI appears weak and may vary across parent-child dyad types in the US population. However, parental obesity status is associated with children’s obesity status. Use of different measures of parent-child resemblance in body weight status can lead to different conclusions.
A Practical Query Language for Graph DBs

Query languages for current graph DB systems lack clear syntax and semantics, which difficults the understanding of its expressiveness and complexity. In particular, many of them suffer from poor performance due to the inherently high complexity of the queries they can express. We propose propositional dynamic logic (PDL) as a yardstick query language for graph database engines, based on the fact that it can express many relevant properties with very low computational cost. We present an implementation of the language that shows its potential applicability for querying massive graph databases by building on existing graph database support.
Building Up a Class Hierarchy with Properties from Japanese Wikipedia

Japanese Wikipedia Ontology, which we have constructed semi-automatically from Japanese Wikipedia, has problems of lacking upper classes and appropriate definition of properties. The purpose of our research is to complement the upper classes in Japanese Wikipedia Ontology and build up a class hierarchy with properties by integrating Japanese Wikipedia Ontology and Japanese Word Net. In this paper, we propose a method to build up the class hierarchy with properties by lifting up common properties that are defined in sibling classes to more upper classes in Japanese Wikipedia Ontology. We also introduce an attempt to integrate Japanese Wikipedia Ontology and Japanese Word Net.
Star Formation Triggering Mechanisms in Dwarf Galaxies: The Far-Ultraviolet, Hα, and H I Morphology of Holmberg II

Far-ultraviolet (FUV), Hα, and H I observations of dwarf galaxy Holmberg II are used to investigate the means by which star formation propagates in galaxies lacking global internal triggering mechanisms such as spiral density waves. The observations trace the interaction between sites of massive star formation and the neutral and ionized components of the surrounding ISM in this intrinsically simple system. Both local and large-scale triggering mechanisms related to massive star formation are seen, suggesting that feedback from massive stars is a microscopic process operating in all galaxies to a certain degree. The data emphasize the importance of local conditions in regulating star formation from evidence such as massive stars inside ionized shells, compact H II regions surrounding aging clusters, and stars formed in chains of progressing age. Surface brightness profiles show that current activity correlates with the time-averaged level of past star formation at a given radius demonstrating a reliance on local conditions. Large-scale triggering by H I shells is supported by observations of progenitor populations as well as secondary sites of star formation associated with their dense rims. Analysis of the energy available from massive stars inside H I shells indicates that energy deposited into the ISM from supernovae and stellar winds is sufficient to account for the H I morphology. Ages of individual star-forming regions are derived using B, Hα, and FUV photometry and show both older, diffuse FUV regions and younger, compact H II regions. The distribution of ages is reconciled with the H I morphology, showing a clear preference of young regions for areas of dense H I and old regions for H I voids. Global kinematical properties may also play a role in the star formation process since differences in the rotation characteristics of the neutral gas disk correlate with differences in triggering mechanisms. Large-scale feedback from massive stars is shown to operate in regions that lack differential shear in the gas disk.
Amitriptyline protects against TNF‐α‐induced atrophy and reduction in synaptic markers via a Trk‐dependent mechanism

Neuritic degeneration and synaptic loss are features of both neuroinflammation and neurodegenerative disease. The tricyclic antidepressant amitriptyline has neurotrophic and anti‐inflammatory properties and acts as a novel agonist of the neurotrophin Trk receptors. Primary cortical neurons were treated with amitriptyline, nortriptyline and NGF and tested for neuronal complexity by Sholl analysis, protein expression by Western immunoblotting, and synapse number by colocalization of pre and postsynaptic makers. Amitriptyline (500 nmol/L) and its active metabolite nortriptyline (50 nmol/L) are found to induce neurite outgrowth in rat primary cortical neurons. Amitriptyline‐induced neurite outgrowth is blocked by inhibition of Trk signaling using Trk antagonist K252a (200 nmol/L) but not by the neurotrophin inhibitor Y1036 (40 μmol/L), indicating that amitriptyline binds directly to the Trk receptor to initiate neurite outgrowth. MEK inhibitor PD98059 (10 μmol/L) also blocks amitriptyline‐induced neurite outgrowth, implicating activation of the MAPK signaling pathway downstream of Trk receptor activation. Furthermore, pretreatment of primary cortical neurons with amitriptyline and nortriptyline prevents the effects of the proinflammatory cytokine TNF‐α (10 ng/mL) on neurite outgrowth and colocalization of synaptic proteins. These findings suggest that amitriptyline and nortriptyline can exert neurotrophic effects in primary cortical neurons via activation of a Trk/MAPK signaling pathway. These compounds therefore have significant potential to be used in the treatment of neurodegenerative conditions where atrophy and loss of synaptic connections contribute to progression of disease.
Non-Uniform Hierarchical Geo-consistency for Multi-baseline Stereo

We propose a new and flexible hierarchical multibaseline stereo algorithm that features a non-uniform spatial decomposition of the disparity map. The visibility computation and refinement of the disparity map are integrated into a single iterative framework that does not add extra constraints to the cost function. This makes it possible to use a standard efficient stereo matcher during each iteration. The level of refinement is increased automatically where it is needed in order to preserve a good localization of boundaries. While two graph-theoretic stereo matchers are used in our experiments, our framework is general enough to be applied to many others. The validity of our framework is demonstrated using real imagery with ground truth.
Frequency and Time Domain Crosstalk Signal Analysis for Integrated High-Density Circuits

Crosstalk is one of the greatest concerns in the design of integrated high-density circuits, especially in high frequency range, due to that it seriously leads to a wireless communication system deviating from its designed performance. In this paper, we analyze the frequency and time domain crosstalk effects between two traces as a function of their spacing and orientation. It is found that two vertical traces result in a smallest crosstalk and that the crosstalk signals are insensitive to the spacing increment between two parallel traces in the range investigated.
Dissecting Play - Investigating the Cognitive and Emotional Motivations and Affects of Computer Gameplay 1

All games are cognitive learning environments. A cognitive approach to understanding games and gameplay emphasises the analysis and understanding of these learning functions and how game design features facilitate them. The experience of gameplay is one of interacting with a game design in the performance of cognitive tasks, with a variety of emotions arising from or associated with different elements of motivation, task performance and completion. Psychophysiological techniques provide empirical methods for investigating play that provide a foundation for developing plausible models of what those cognitive decision processes are, how they relate to design features and how emotions integrated with task performance lead to rewards of play, creating an experience of 'fun'.
Binarizing Syntax Trees to Improve Syntax-Based Machine Translation Accuracy

We show that phrase structures in Penn Treebank style parses are not optimal for syntaxbased machine translation. We exploit a series of binarization methods to restructure the Penn Treebank style trees such that syntactified phrases smaller than Penn Treebank constituents can be acquired and exploited in translation. We find that by employing the EM algorithm for determining the binarization of a parse tree among a set of alternative binarizations gives us the best translation result.
The Impact of Task and Corpus on Event Extraction Systems

The term event extraction covers a wide range of information extraction tasks, and methods developed and evaluated for one task may prove quite unsuitable for another. Understanding these task differences is essential to making broad progress in event extraction. We look back at the MUC and ACE tasks in terms of one characteristic, the breadth of the scenario ― how wide a range of information is subsumed in a single extraction task. We examine how this affects strategies for collecting information and methods for semi-supervised training of new extractors. We also consider the heterogeneity of corpora ― how varied the topics of documents in a corpus are. Extraction systems may be intended in principle for general news but are typically evaluated on topic-focused corpora, and this evaluation context may affect system design. As one case study, we examine the task of identifying physical attack events in news corpora, observing the effect on system performance of shifting from an attack-event-rich corpus to a more varied corpus and considering how the impact of this shift may be mitigated.
Case Study : Ubiquitin

Without a doubt, the most organized and coordinated machine known is the biological cell. Inside its micrometer-scale diameter, a wide variety of macromolecules (DNA, proteins, sugars, lipids, etc.) work together in a cooperative way, balancing energy and matter to keep the cell alive. Within the cell, proteins are the overachievers. They allow the movement of water and ions through the cell membrane, help ATP to store energy, assist DNA during replication, recognize foreign infections, and more. However, all of these functions don’t work independently of each other. To maintain harmony and efficiency between various functions, most processes have to be turned on or off according to different cellular stages and changes within the environment. To this end, together with the mechanisms to assemble functional proteins and to turn on their functions, there should be counterparts to suppress and disassemble proteins when they are no longer needed. The cellular machine depends on assembly and disassembly to regulate the effective concentration of proteins and their corresponding activities [1]. Furthermore, defective
A Single Residue in a Novel ADP-ribosyl Cyclase Controls Production of the Calcium-mobilizing Messengers Cyclic ADP-ribose and Nicotinic Acid Adenine Dinucleotide Phosphate*

Cyclic ADP-ribose and nicotinic acid adenine dinucleotide phosphate are ubiquitous calcium-mobilizing messengers produced by the same family of multifunctional enzymes, the ADP-ribosyl cyclases. Not all ADP-ribosyl cyclases have been identified, and how production of different messengers is achieved is incompletely understood. Here, we report the cloning and characterization of a novel ADP-ribosyl cyclase (SpARC4) from the sea urchin, a key model organism for the study of calcium-signaling pathways. Like several other members of the ADP-ribosyl cyclase superfamily, SpARC4 is a glycoprotein targeted to the plasma membrane via a glycosylphosphatidylinositol anchor. However, unlike most other members, SpARC4 shows a remarkable preference for producing cyclic ADP-ribose over nicotinic acid adenine dinucleotide phosphate. Mutation of a single residue (tyrosine 142) within a noncanonical active site reversed this striking preference. Our data highlight further diversification of this unusual enzyme family, provide mechanistic insight into multifunctionality, and suggest that different ADP-ribosyl cyclases are fine-tuned to produce specific calcium-mobilizing messengers.
Southeast Europe Journal of Soft Computing Diagnosis of Parkinson's Disease Using Principal Component Analysis and Boosting Committee Machines

Parkinson's disease (PD) has become one of the most common degenerative disorder of the central nervous system. In this study, our main goal was to discriminate between healthy people and people with Parkinson's disease. In order to achieve this we used artificial neural networks, and dataset taken from University of California, Irvine machine learning database, having 48 normal and 147 PD cases. We examine the performance of neural network systems with back propagation together with a majority voting scheme. In order to train examples we used boosting by filtering technique with seven committee machines, and principal component analysis is used for data reduction. The experimental results have demonstrated that the combination of these proposed methods has obtained very good results with correct positive value of 92% on the classification of PD.
Adaptive Path Planning for Randomly Deployed Wireless Sensor Networks

In this paper, we propose an adaptive path planning scheme considering the length of movement path and number of beacon messages of a mobile beacon for its energy efficiency, where the sensor nodes are randomly deployed. Contrary to the previous studies that utilize mobile beacons (nodes sending beacon messages) only on the basis of a random movement method or predefined static movement paths, the proposed scheme provides energy-efficient and adaptive movement path construction with low computational complexity. The movement path also includes beacon positions in which the mobile beacon broadcasts beacon messages containing the information of its current position. The random movement methods are not concerned about the energy of the mobile beacon. In randomly deployed environments, it is not easy to obtain precise field information for static movement path decisions. Thus, we propose the adaptive path planning scheme which can operate without this information in randomly deployed wireless sensor networks, and improve the energy efficiency of the mobile beacon. The candidate areas that limit the search space are devised so as to provide low complexity. The performance evaluation shows that the proposed scheme reduces the movement distance and number of beacon messages of the mobile beacon by comparison with other methods.
Electrophysiological correlates of visual search in the autism spectrum

The thesis examines the neural basis of selective attention in those with high and low levels of self-reported autistic traits. Existing literature suggests that those with an autism spectrum condition (ASC) show atypical selective attention (e.g. Burack 1994), and this has been extended to those with high levels of autistic traits (Bayliss & Kritikos, 2011). The research presented in the thesis has, for the first time, examined the neural basis of spatial attention in those with high and low levels of autistic traits by measuring the ERP deflections associated with covert attention, target selection and distracter suppression (The N2pc, NT and PD). The results provide evidence of neural differences in spatial attention in those with high levels of autistic traits. Specifically, a larger N2pc suggests greater allocation of attentional resources, and a reduced PD indicates reduced distracter suppression in those with high levels of autistic traits. No group differences were found in the NT component, indicating that the neural mechanisms underpinning target selection do not differ between those with high and low levels of autistic traits. The findings support Remington’s suggestion of an enhanced perceptual capacity in ASC (Remington et al., 2009); which would result in the processing of normally irrelevant information. Recent work has extended the possibility of an enhanced perceptual capacity to those with high levels of autistic traits (Bayliss & Kritikos, 2011; Milne et al., 2013), and this is supported by the ERP findings reported in the thesis. The findings may be an important factor in explaining the overwhelming perceptual experience often reported by those on the autism spectrum.
A major root protein of carrots with high homology to intracellular pathogenesis-related (PR) proteins and pollen allergens.

We isolated the cDNA clone coding for a major root specific protein (CR16) of carrots. The CR16 protein (154a.a.) has a high homology to intracellular pathogenesis-related (PR) proteins, stress-induced proteins and also the major allergen protein of celery (Api g1). The CR16 protein gene formed a super gene family and transcripts of this CR16 protein gene are predominant in root tissue, not in leaves or flowers.
The weak INTEGRAL bursts GRB 040223 and GRB 040624: an emerging population of dark afterglows

We report here γ -ray, X-ray and near-infrared observations of GRB 040223 along with γ -ray and optical observations of GRB 040624. GRB 040223 was detected by INTEGRAL close to the Galactic plane and GRB 040624 at high Galactic latitude. Analyses of the prompt emission detected by the IBIS instrument on INTEGRAL are presented for both bursts. The two GRBs have long durations, slow pulses and are weak. The γ -ray spectra of both bursts are best fit with steep power-laws, implying they are X-ray rich. GRB 040223 is among the weakest and longest of INTEGRAL GRBs. The X-ray afterglow of this burst was detected 10 h after the prompt event by XMM-Newton . The measured spectral properties are consistent with a column density much higher than that expected from the Galaxy, indicating strong intrinsic absorption. We carried out near-infrared observations 17 h after the burst with the NTT of ESO, which yielded upper limits. Given the intrinsic absorption, we find that these limits are compatible with a simple extrapolation of the X-ray afterglow properties. For GRB 040624, we carried out optical observations 13 h after the burst with FORS 1 and 2 at the VLT, and DOLoRes at the TNG, again obtaining upper limits. We compare these limits with the magnitudes of a compilation of promptly observed counterparts of previous GRBs and show that they lie at the very faint end of the distribution. These two bursts are good examples of a population of bursts with dark or faint afterglows that are being unveiled through the increasing usage of large diameter telescopes engaged in comprehensive observational programmes.
Searching for a compromise between satisfaction and diversity in database fuzzy querying

This paper deals with fuzzy queries and describes an approach that aims at providing users with a set of answers which satisfies a diversity criterion on one or several attributes. Different cases are considered and two types of algorithms are described. The first one, which has a linear complexity in terms of the number of tuples in the result, is suited to the case where the notion of similarity underlying the definition of diversity is crisp. The second one, based on a trial and error strategy, makes it possible to deal with fuzzy similarity, but its high complexity means that it can be employed only when a relatively small sets of tuples is used to increase diversity.
Expectation-based sentence comprehension in Korean: evidence from behavioral and neurological studies

The goal of this study was to provide meaningful insights in the algorithms of statistical and computational modeling in natural language processing, by emphasizing the role of expectation in human language comprehension. To obtain the evidence for expectation-based sentence comprehension in Korean, we revisited Lee's study [1, 2] in which the processing of Korean relative-clause sentences was tested. In Study 1, using Lee's materials, we conducted gated cloze tasks by which the conditional probability of a target constituent was computed at each point in a way that a word was incrementally added to a sentence fragment. Then, the patterns of the computed conditional probabilities of target constituents were compared to those of the reading times of target constituents that Lee had observed. In Study 2, we examined whether the patterns of the expectation-based sentence processing that we observed in Study 1 was modulated by readers' working memory capacity. Finally, in Study 3, an fMRI study was conducted to explore the locus of expectation-based sentence processing in brain. We found that the patterns of conditional probabilities were mapped to those of behavioral reading times, but we did not observe individual differences in expectation-based comprehension. We also obtained neurological results suggesting that the Broca area is the locus for the processing of the expected syntactic information. Taken together, our behavioral and neurological findings provided evidence supporting expectation-based sentence comprehension in Korean.
Barriers in Implementing E-Learning in Hormozgan University of Medical Sciences

Background: E-learning provides an alternative way for higher educational institutes to deliver knowledge to learners at a distance, rather than the traditional way. The aim of this study is to identify the barrier factors of e-learning programs in Hormozgan University of Medical Sciences (HUMS) in respect of the students and lecturers’ point of view. Methods: A cross-sectional study based on a questionnaire was conducted among 286 of students and lecturers in the nursing, midwifery and paramedic schools of HUMS. Two hundred and eighty-six participants filled in the questionnaire: 256 students, and 30 lecturers. Results: Results of the study showed a lack of proper training in e-learning courses of the university 182 (69.1%), limited communication with the instructor 174 (68%) and the learners dominance of English language 174 (68%) showed the greatest importance for the students. The awareness about e-learning program was 80% and 43% among lecturers and students respectively. The dominance of English language 26 (86.7%) and lack of research grants for e-learning 23 (76.6%) and lack of proper training on e-learning courses from the university 20 (66.7 %) were the most important barrier factors of implementing e-learning for lecturers. E-learning courses to supplement classroom teaching was a solution that mentioned by the majority of students 240 (93.8%) and lecturers 29 (96.7%) in this study. Conclusions: The positive perception of e-learning is an important consequence effect in the future, educational development of nursing, midwifery and paramedic schools.