Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonveridical visual perception in human amblyopia.

PURPOSE Amblyopia is a developmental disorder of spatial vision. There is evidence to suggest that some amblyopes misperceive spatial structure when viewing with the affected eye. However, there are few examples of these perceptual errors in the literature. This study was an investigation of the prevalence and nature of misperceptions in human amblyopia. METHODS Thirty amblyopes with strabismus and/or anisometropia participated in the study. Subjects viewed sinusoidal gratings of various spatial frequencies, orientations, and contrasts. After interocular comparison, subjects sketched the subjective appearance of those stimuli that had nonveridical appearances. RESULTS Nonveridical visual perception was revealed in 20 amblyopes ( approximately 67%). In some subjects, misperceptions were present despite the absence of a deficit in contrast sensitivity. The presence of distortions was not simply linked to the depth of amblyopia, and anisometropes were affected as well as those with strabismus. In most cases, these spatial distortions arose at spatial frequencies far below the contrast detection acuity cutoff. Errors in perception became more severe at higher spatial frequencies, with low spatial frequencies being mostly perceived veridically. The prevalence and severity of misperceptions were frequently found to depend on the orientation of the grating used in the test, with horizontal orientations typically less affected than other orientations. Contrast had a much smaller effect on misperceptions, although there were cases in which severity was greater at higher contrasts. CONCLUSIONS Many types of misperceptions documented in the present study have appeared in previous investigations. This suggests that the wide range of distortions previously reported reflect genuine intersubject differences. It is proposed that nonveridical perception in human amblyopia has its origins in errors in the neural coding of orientation in primary visual cortex.
Society of the Pacific Planetary Companions Around Two Solar Type Stars: HD

We have enlarged the sample of stars in the planet search at Lick Observatory. Doppler measurements of 82 new stars observed at Lick Observatory, with additional velocities from Keck Observatory, have revealed two new planet candidates. The G3 V/IV star, HD 195019, exhibits Keplerian velocity variations with a period of 18.27 d, an orbital eccentricity of 0.03±0.03, and M sin i = 3.51 MJUP. Based on a measurement of Ca II H&K emission, this star is chromospherically inactive. We estimate the metallicity of HD 195019 to be approximately solar from ubvy photometry. The second planet candidate was detected around HD 217107, a G7V star. This star exhibits a 7.12 d Keplerian period with eccentricity 0.14 ± 0.05 and M sin i = 1.27 MJUP. HD 217107 is also chromospherically inactive. The photometric metallicity is found to be [Fe/H]= +0.29 ± 0.1 dex. Given the relatively short orbital period, the absence of tidal spin up in HD 217107 provides a theoretical constraint on the upper limit of the companion mass of < 11 MJUP. Subject headings: planetary systems – stars: individual (HD 195019, HD 217107) Based on observations obtained at Lick Observatory, which is operated by the University of California, and on observations obtained at the W.M. Keck Observatory, which is operated jointly by the University of California and the California Institute of Technology. Department of Physics and Astronomy, San Francisco State University, San Francisco, CA, USA 94132 and at Department of Astronomy, University of California, Berkeley, CA USA 94720, fischer@stars.sfsu. edu Anglo–Australian Observatory, PO Box 296, NSW 1710 Epping, Australia UCO/Lick Observatory, University of California at Santa Cruz, Santa Cruz, CA, 95064 Physics and Astronomy, Universityof Sussex, Falmer, Brighton, BN1, 9QJ, UK
Mass segmentation in mammograms for computer-aided diagnosis of breast cancer

The appearance of masses in in X-ray mammograms is one of the early signs of women breast cancer. Currently, mammography is the single most effective and reliable technique in the investigation of breast abnormalities detection such as masses. However, their detection is still a challenging problem due, to the diversity in shape, size, ambiguous margins and to the poor contrast between the cancerous areas and surrounding bright structures. This paper presents an effective approach based on mathematical morphology for detection of masses in digitized mammograms. The developed approach performs an initial step in order to remove and delete unwanted signs and radiopaque artifacts present in the background of the mammogram, and to extract the breast area. Then an enhancement process is applied to improve appearance and increase the contrast of images and to eliminate noise. Once the breast region has been found, a segmentation phase through morphological watersheds is performed for localization /detection of various types of masses in mammograms. The main advantage and motivation of this paper is the ability to detect hard masses cases in very dense mammograms. The algorithms have been evaluated on a set of 38 mammograms from MIAS dataset, shows the presence of masses, previously selected by expert radiologists. In addition, it has been compared to the manual detection marked by radiologists. The obtained results show promising performances of the proposed algorithm. Indeed, the watershed transform has demonstrated a great efficiency in the masses detection. Consequently, the developed algorithm provides “a visual aid” to radiologists in their interpreting mammograms.
Risk and Regret of Hierarchical Bayesian Learners

Common statistical practice has shown that the full power of Bayesian methods is not realized until hierarchical priors are used, as these allow for greater "robustness" and the ability to "share statistical strength. " Yet it is an ongoing challenge to provide a learning-theoretically sound formalism of such notions that: offers practical guidance concerning when and how best to utilize hierarchical models; provides insights into what makes for a good hierarchical prior; and, when the form of the prior has been chosen, can guide the choice of hyperparameter settings. We present a set of analytical tools for understanding hierarchical priors in both the online and batch learning settings. We provide regret bounds under log-loss, which show how certain hierarchical models compare, in retrospect, to the best single model in the model class. We also show how to convert a Bayesian log-loss regret bound into a Bayesian risk bound for any bounded loss, a result which may be of independent interest. Risk and regret bounds for Student's t and hierarchical Gaussian priors allow us to formalize the concepts of "robustness" and "sharing statistical strength. " Priors for feature selection are investigated as well. Our results suggest that the learning-theoretic benefits of using hierarchical priors can often come at little cost on practical problems.
The Choquet-Deny theorem and distal properties of totally disconnected locally compact groups of polynomial growth

We obtain sufficient and necessary conditions for the Choquet- Deny theorem to hold in the class of compactly generated totally disconnected locally compact groups of polynomial growth, and in a larger class of totally disconnected generalized FC -groups. The following conditions turn out to be equivalent when G is a metrizable compactly generated totally disconnected locally compact group of polynomial growth: (1) The Choquet-Deny theorem holds for G. (2) The group of inner automorphisms of G acts distally on G. (3) Every inner automorphism of G is distal. (4) The contraction subgroup of every inner automorphism of G is trivial. (5) G is a SIN group. We also show that for every probability measure μ on a totally disconnected compactly generated locally compact second countable group of polynomial growth, the Poisson boundary is a homogeneous space of G, and that it is a compact homogeneous space when the support of μ generates G.
Prospective Science Teachers' Self-Assessments about the Use of Slowmation Approach in Teaching

In the concept of this study, science teacher candidates prepared some animations regarding biology topics by using slow-motion technique. Following this process of animation making, how teacher candidates see extend of contribution of the process on education is examined. This study is carried out with 49 teacher candidates, who were taking general biology course in the spring semester of 2013-2014 academic years. The data of the research is collected by 8-item five point Likert-type slow-motion survey forms and semi-structured interview questions, developed by the researchers. As a result of the study, the teacher candidates reported that the slow-motion technique is an informative technique, which is instructive, useful, developing their creativity, enjoyable and stimulating to the course. As a result of the interviews made with teacher candidates, it is revealed that they are quite willing to use this technique in their professional lives as a teaching approach, which contribute to their learning skills, thus they want to implement this technique to their students as well.
Extending generalized hough transform to detect 3D objects in laser range data

Automated detection and 3D modelling of objects in laser range data is of great importance in many applications. Existing approaches to object detection in range data are limited to either 2.5D data (e.g. range images) or simple objects with a parametric form (e.g. spheres). This paper describes a new approach to the detection of 3D objects with arbitrary shapes in a point cloud. We present an extension of the generalized Hough transform to 3D data, which can be used to detect instances of an object model in laser range data, independent of the scale and orientation of the object. We also discuss the computational complexity of the method and provide cost-reduction strategies that can be employed to improve the efficiency of the method.
Genetic effects on alcohol dependence risk: re-evaluating the importance of psychiatric and other heritable risk factors

Background. Genetic influences have been shown to play a major role in determining the risk of alcohol dependence (AD) in both women and men; however, little attention has been directed to identifying the major sources of genetic variation in AD risk. Method. Diagnostic telephone interview data from young adult Australian twin pairs born between 1964 and 1971 were analyzed. Cox regression models were fitted to interview data from a total of 2708 complete twin pairs (690 MZ female, 485 MZ male, 500 DZ female, 384 DZ male, and 649 DZ female/male pairs). Structural equation models were fitted to determine the extent of residual genetic and environmental influences on AD risk while controlling for effects of sociodemographic and psychiatric predictors on risk. Results. Risk of AD was increased in males, in Roman Catholics, in those reporting a history of major depression, social anxiety problems, and conduct disorder, or (in females only) a history of suicide attempt and childhood sexual abuse; but was decreased in those reporting Baptist, Methodist, or Orthodox religion, in those who reported weekly church attendance, and in university-educated males. After allowing for the effects of sociodemographic and psychiatric predictors, 47% (95% CI 28–55) of the residual variance in alcoholism risk was attributable to additive genetic effects, 0% (95% CI 0–14) to shared environmental factors, and 53% (95% CI 45–63) to non-shared environmental influences. Conclusions. Controlling for other risk factors, substantial residual heritability of AD was observed, suggesting that psychiatric and other risk factors play a minor role in the inheritance of AD.
A Finite Element Model for Estimating Young-s Modulus of Carbon Nanotube Reinforced Composites Incorporating Elastic Cross-Links

The presence of chemical bonding between functionalized carbon nanotubes and matrix in carbon nanotube reinforced composites is modeled by elastic beam elements representing covalent bonding characteristics. Neglecting other reinforcing mechanisms in the composite such as relatively weak interatomic Van der Waals forces, this model shows close results to the Rule of Mixtures model's prediction for effective Young's modulus of a Representative Volume Element of composite for small volume fractions (~1%) and high aspect ratios (L/D>200) of CNTs. Keywords—Beam Element, Carbon Nanotube Reinforced Composite, Cross-link, Young's modulus. I. INTRODUCTION ARBON Nanotubes (CNTs) have attracted researchers' great attention due to their outstanding mechanical, electrical, thermal, chemical, and even biological properties. Young's modulus, strength, strain before failure, and aspect ratio in CNTs are significantly high which bring about application of CNTs as composites reinforcement, and thus providing versatile characteristics for composites. The small size of nanostructure of such composites brings sever limitations in conducting experimental studies, thus encouraging scientists to develop theoretical models in order to explore their mechanical behavior. CNT reinforced composites have been investigated by multiscale modeling bridging the length scales from nano- through the mesoscale (1-3). Description of the interaction between the CNT (reinforcement) and the matrix is of great importance in analysis of CNT reinforced composites, as several models
Hybrid type-II ARQ schemes with adaptive modulation systems for wireless channels

In this paper, we propose and analyze a scheme for wireless channels which is a combination of a hybrid type-II automatic repeat request (ARQ) scheme and an adaptive modulation system (AMS). In hybrid type-II ARQ schemes, the transmission of redundancy bits for error correction is adapted to the channel variations. Additionally, in the proposed AMS, the modulation is gradually changed from a large constellation to small constellations when the channel bit error probability is high. This is done without any knowledge of the channels at the transmitter. The proposed scheme provides a significant gain in the throughput performance as compared to traditional hybrid type-II ARQ schemes, as verified by simulations.
Mitotic Phosphorylation of Histone H3: Spatio-Temporal Regulation by Mammalian Aurora Kinases

ABSTRACT Phosphorylation at a highly conserved serine residue (Ser-10) in the histone H3 tail is considered to be a crucial event for the onset of mitosis. This modification appears early in the G2 phase within pericentromeric heterochromatin and spreads in an ordered fashion coincident with mitotic chromosome condensation. Mutation of Ser-10 is essential in Tetrahymena, since it results in abnormal chromosome segregation and extensive chromosome loss during mitosis and meiosis, establishing a strong link between signaling and chromosome dynamics. Although mitotic H3 phosphorylation has been long recognized, the transduction routes and the identity of the protein kinases involved have been elusive. Here we show that the expression of Aurora-A and Aurora-B, two kinases of the Aurora/AIK family, is tightly coordinated with H3 phosphorylation during the G2/M transition. During the G2 phase, the Aurora-A kinase is coexpressed while the Aurora-B kinase colocalizes with phosphorylated histone H3. At prophase and metaphase, Aurora-A is highly localized in the centrosomic region and in the spindle poles while Aurora-B is present in the centromeric region concurrent with H3 phosphorylation, to then translocate by cytokinesis to the midbody region. Both Aurora-A and Aurora-B proteins physically interact with the H3 tail and efficiently phosphorylate Ser10 both in vitro and in vivo, even if Aurora-A appears to be a better H3 kinase than Aurora-B. Since Aurora-A and Aurora-B are known to be overexpressed in a variety of human cancers, our findings provide an attractive link between cell transformation, chromatin modifications and a specific kinase system.
Neural networks with periodic and monotonicactivation functions : a comparative study inclassi cation problemsJosep

This article discusses a number of reasons why the use of non-monotonic functions as activation functions can lead to a marked improvement in the performance of a neural network. Using a wide range of benchmarks we show that a multilayer feed-forward network using sine activation functions (and an appropriate choice of initial parameters) learns much faster than one incorporating sigmoid functions-as much as 150-500 times faster-when both types are trained with backpropagation. Learning speed also compares favorably with speeds reported using modiied versions of the backpropagation algorithm. In addition, computational and generalization capacity increases.
Solving Aircraft-Sequencing Problem Based on Bee Evolutionary Genetic Algorithm and Clustering Method

Aircraft-sequencing problem (ASP) is a major issue in air traffic control operations and it is also an NP-hard problem with large-scale and multi-constraint, thus it is hard to find optimal solution efficiently. This paper proposes a hybrid algorithm by means of integrating Bee Evolutionary Genetic algorithm with modified clustering method (named BEGA-CM) for solving ASP. In details, clustering method is suitable to deal with distribution of arrival time window, moreover, we newly define the relative and absolute position in aircraft permutation according to its distribution of cluster, which can help us to construct new crossover and mutation operator and efficiently reduce infeasible permutation and improve convergence speed. Experiments show the hybrid algorithm is able to obtain an optimal landing sequence and landing time rapidly and effectively
A 4-layer flexible virtual hand model for haptic interaction

Virtual hand interactions play key roles in virtual environments. The recent addition of force feedback to virtual reality simulations has enhanced their realism, especially when dexterous manipulation of virtual objects is concerned. In the past decades, much effort has been made on virtual hand modeling from the perspectives of computer animation and human computer interaction. However, much less attention is paid on haptic modeling of flexible virtual hand. In this paper, we propose a 4-layer flexible virtual hand model for virtual hand haptic interaction. The skin layer, kinematics layer, collision detection layer and haptic layer are integrated into a sophisticated virtual hand to simulate the human hands natural anatomy in its appearance and motion, and to reflect the area contact feature of force feedback datagloves. The infrastructure and details of the flexible virtual hand model are discussed. Experimental results show that the proposed flexible virtual hand demonstrates good performance in virtual hand haptic applications.
How to use the world's scarce selenium resources efficiently to increase the selenium concentration in food

The world's rare selenium resources need to be managed carefully. Selenium is extracted as a by-product of copper mining and there are no deposits that can be mined for selenium alone. Selenium has unique properties as a semi-conductor, making it of special value to industry, but it is also an essential nutrient for humans and animals and may promote plant growth and quality. Selenium deficiency is regarded as a major health problem for 0.5 to 1 billion people worldwide, while an even larger number may consume less selenium than required for optimal protection against cancer, cardiovascular diseases and severe infectious diseases including HIV disease. Efficient recycling of selenium is difficult. Selenium is added in some commercial fertilizers, but only a small proportion is taken up by plants and much of the remainder is lost for future utilization. Large biofortification programmes with selenium added to commercial fertilizers may therefore be a fortification method that is too wasteful to be applied to large areas of our planet. Direct addition of selenium compounds to food (process fortification) can be undertaken by the food industry. If selenomethionine is added directly to food, however, oxidation due to heat processing needs to be avoided. New ways to biofortify food products are needed, and it is generally observed that there is less wastage if selenium is added late in the production chain rather than early. On these bases we have proposed adding selenium-enriched, sprouted cereal grain during food processing as an efficient way to introduce this nutrient into deficient diets. Selenium is a non-renewable resource. There is now an enormous wastage of selenium associated with large-scale mining and industrial processing. We recommend that this must be changed and that much of the selenium that is extracted should be stockpiled for use as a nutrient by future generations.
Conceptual Classiication from Imprecise Data

In this paper, we propose a model to represent not completely deened data. These data are structured in rooted trees that take into account unknown and impossible values. We make a Galois connexion between entities described with imprecise data and their associated predicates. We propose an algorithm to nd concepts deened by a Galois connexion.
Functionalized glass coating for PDMS microfluidic devices

Microfluidic devices can perform multiple laboratory functions on a single, compact, and fully integrated chip. However, fabrication of microfluidic devices is difficult, and current methods, such as glass-etching or soft-lithography in PDMS, are either expensive or yield devices with poor chemical robustness. We introduce a simple method that combines the simple fabrication of PDMS with superior robustness and control of glass. We coat PDMS channels with a functionalized glass layer. The glass coating greatly increases the chemical robustness of the PDMS devices. As a demonstration, we produce emulsions in coated channels using organic solvents. The glass coating also enables surface properties to be spatially controlled. As a demonstration of this control, we spatially pattern the wettability of coated PDMS channels and use the devices to produce double emulsions with fluorocarbon oil.
An improved AP algorithm for identifying overlapping functional modules in protein-protein interaction networks

Identifying modules in protein-protein interaction (PPI) networks is important to understand the organization of the cellular processes. In this paper, an improved algorithm based on affinity propagation (AP) is proposed. We embed AP in our algorithm by utilizing AP to find the candidate overlapping vertices and keep those satisfying our filter condition. We apply our algorithm to S. cerevisiae PPI networks. The experimental results show that compared with AP, MCL, MCODE and CPM, our algorithm can discover more functional modules with high matching rate. Our proposed method is validated as an effective algorithm in identifying overlapping functional modules and can provide more insights for future biological study.
The role of activity level for memory in the elderly

iii ACKNOWLEDGMENTS . y LIST OF TABLES . ix LIST OF FIGURES . , . x INTRODUCTION . 1 Physiological Activity and Cognitive Performance . 4 Leisure Activity and Life Satisfaction . 9 Prospective,Memory . 15 Implicit Memory . 19 Source Monitoring . , . 25 Overview of the Current Study . 31 METHOD . 35 Subjects . 35 Materials . 36 General Questionnaire . 36 General Health Questionnaire . 36 Activity Scale . 37 Implicit Memory . 38 Source Monitoring . 39 Procedure . 41 Level of Activity . , . 45 RESULTS . 48 Memory Tasks . 48