Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular phylogeny of the highly disjunct cliff water beetles from South Africa and China (Coleoptera: Aspidytidae)

The superfamily Dytiscoidea contains six families with an aquatic lifestyle, with most of its extant diversity in two families: the burrowing water beetles (Noteridae) and the diving beetles (Dytiscidae). The other families have few species (up to six) and generally highly disjunct extant distributions. Aspidytidae currently contains one genus with two species, one in China and one in South Africa. Here we provide the first molecular data for the Chinese species, allowing us to explore the phylogenetic relationships and position of both species of this small family for the first time. Based on a matrix of 11 genes we inferred a phylogenetic hypothesis for Dytiscoidea including all extant families. Unexpectedly, Aspidytidae were consistently recovered as paraphyletic relative to Amphizoidae, despite being well characterized by apparently synapomorphic adult features. A re-examination of larval characters in the two aspidytid species revealed that the larva of the Chinese species is strikingly similar to that of Amphizoidae. Both share a series of plesiomorphic features but also some potential synapomorphies, including a dense vestiture of short setae on the head capsule, anteriorly shifted posterior tentorial grooves and widely separated labial palps. Arguably these features may belong to the groundplan of the clade Aspidytidae+Amphizoidae, with far-reaching secondary modifications (including reversals) in the South African Aspidytes niobe. At present we retain the family Aspidytidae, however, due to the strong adult morphological synapomorphies of the two extant species, and the fact that the molecular paraphyly of the family may result from the highly divergent nature of the two extant species. This long evolutionary separation and strong divergence, in terms of gene sequences and larval features, is undeniable, substantial levels of saturation in third codon positions of protein-coding genes being present between the two taxa. We address this issue taxonomically by introducing the new genus Sinaspidytes gen. nov. for the Chinese Aspidytes wrasei. The continued contentious relationships amongst Dytiscidae, Hygrobiidae, Aspidytidae and Amphizoidae highlight the need for more data to address dytiscoid phylogenetics, possibly involving a genomic approach. (c) 2016 The Linnean Society of London
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model

The inverse temperature parameter of the Potts model governs the strength of spatial cohesion and therefore has a major influence over the resulting model fit. A difficulty arises from the dependence of an intractable normalising constant on the value of this parameter and thus there is no closed-form solution for sampling from the posterior distribution directly. There are a variety of computational approaches for sampling from the posterior without evaluating the normalising constant, including the exchange algorithm and approximate Bayesian computation (ABC). A serious drawback of these algorithms is that they do not scale well for models with a large state space, such as images with a million or more pixels. We introduce a parametric surrogate model, which approximates the score function using an integral curve. Our surrogate model incorporates known properties of the likelihood, such as heteroskedasticity and critical temperature. We demonstrate this method using synthetic data as well as remotely-sensed imagery from the Landsat-8 satellite. We achieve up to a hundredfold improvement in the elapsed runtime, compared to the exchange algorithm or ABC. An open source implementation of our algorithm is available in the R package "bayesImageS. "
Persistence differences between the Three Mile Island residents and a control group. Doctoral thesis

Abstract : A nuclear accident occurred at Three Mile Island (TMI) on March 28, 1979. The aftermath of this incident remains unresolved. The cleanup activities have been progressing for the last 5 years and have been a source of stress for TMI residents, exacerbated by conflicting reports regarding how and when the damage nuclear material would be removed. The purpose of this study was to compare TMI residents to a demographically similar control group to determine (1) if thechronic stress experience by TMI residents would influence persistence on two experimental tasks, and (2) whether effects on task persistence would vary depending upon individual coping style and degree of behavioral involvement with the tasks. All subjects resided within sight of the damaged nuclear power plant at TMI. The control group subjects were from Frederick, Maryland located over eighty miles away. The specific variables investigated were level of involvement(i.e., high or low) and coping style (i.e., High-Control-Oriented or Low-Control-Oriented). On two chance tasks (i.e., a dice task and a calculator task) subjects predicted the next 2-digit number that would appear when either a pair of dice was rolled or when a calculator randomly generated the numbers. Each subject performed both tasks and was highly involved in one task and in the low involvement condition in the other task. In the high involvement condition, subjects physically rolled the dice or started the calculator whereas, in the low involvement condition the experimenter, not the subject, performed the physical portion of the task. The total number of trials completed was the measure of persistence. The order of both the tasks and the involvement conditions was randomized for all subjects. Furthermore, whether a subject chose to roll the dice by hand or use a dice cup was recorded by the experimenter and compared for both groups (i.e., TMI vs control).
Unravelling the origins of S0 galaxies using maximum likelihood analysis of planetary nebulae kinematics

To investigate the origins of S0 galaxies, we present a new method of analysing their stellar kinematics from discrete tracers such as planetary nebulae. This method involves binning the data in the radial direction so as to extract the most general possible non-parametric kinematic profiles, and using a maximum-likelihood fit within each bin in order to make full use of the information in the discrete kinematic tracers. Both disc and spheroid kinematic components are fitted, with a two-dimensional decomposition of imaging data used to attribute to each tracer a probability of membership in the separate components. Likelihood clipping also allows us to identify objects whose properties are not consistent with the adopted model, rendering the technique robust against contaminants and able to identify additional kinematic features. The method is first tested on an N-body simulated galaxy to assess possible sources of systematic error associated with the structural and kinematic decomposition, which are found to be small. It is then applied to the S0 system NGC 1023, for which a planetary nebula catalogue has already been released and analysed by Noordermer et al. The correct inclusion of the spheroidal component allows us to show that, contrary to previous claims, the stellar kinematics of this galaxy are indistinguishable from those of a normal spiral galaxy, indicating that it may have evolved directly from such a system via gas stripping or secular evolution. The method also successfully identifies a population of outliers whose kinematics are different from those of the main galaxy; these objects can be identified with a stellar stream associated with the companion galaxy NGC 1023A.
rxKinFu: Moving Volume KinectFusion for 3D Perception and Robotics

KinectFusion is an impressive algorithm that was introduced in 2011 to simultaneously track the movement of a depth camera in the 3D space and densely reconstruct the environment as a Truncated Signed Distance Formula (TSDF) volume, in real-time. In 2012, we introduced the Moving Volume KinectFusion method that allows the volume/camera move freely in the space. In this work, we further develop the Moving Volume KinectFusion method (as rxKinFu) to fit better to robotic and perception applications, especially for locomotion and manipulation tasks. We describe methods to ray cast point clouds from the volume using virtual cameras, and use the point clouds for heightmaps generation (e.g., useful for locomotion) or object dense point cloud extraction (e.g., useful for manipulation). Moreover, we present different methods for keeping the camera fixed with respect to the moving volume, fusing also IMU data and the camera heading/velocity estimation. Last, we integrate and show some demonstrations of rxKinFu on the mini-bipedal robot RPBP, our wheeled quadrupedal robot CENTAURO, and the newly developed full-size humanoid robot COMAN+. We release the code as an open-source package, using the Robotic Operating System (ROS) and the Point Cloud Library (PCL).
Foreign Capital and Garment Export from Myanmar: Implications for the Labour Process

This paper examines the impact of foreign capital inflows on employment, wages and skills, in the export-oriented garment manufacturing sector of Myanmar. The paper argues that global developments driven by the World Trade Organisation have stimulated foreign capital inflows into Myanmar in export-oriented labour-intensive industries such as garment manufacturing. Despite a rise in exports to countries such as Japan, the paper provides evidence to show that international economic and political isolation and poor infrastructure have left Myanmar’s workers vulnerable to the vicissitudes of capitalist exploitation. Women particularly face a highly uncertain future as the poor working conditions include very low wages, little exposure to training and transient work. It is clear that the host-government is the critical agent here to ensure cohesive integration in the global economy as well as to provide the basic infrastructure and the bargaining power required to leverage improvements in working conditions of garment workers in Myanmar.
A Novel Denoising Algorithm Based on Superpixel Clustering and Dictionary Learning Approach

Nowadays, the exploitation of images is inevitable in all the domains. However, the major issue being faced by the images is ‘noise’, which seriously affects the image quality. In order to address this issue, this article presents a novel denoising algorithm that is based on superpixel clustering and dictionary learning process. The superpixel clustering groups the similar pixels together to form a superpixel. As soon as the superpixels are computed, the sparse coefficients are computed by the steepest descent orthogonal matching pursuit algorithm. The process of dictionary updation is achieved by Discriminative KSingular Value Decomposition (DK-SVD). The dictionary is trained by DK-SVD algorithm, as the discriminative capability of the algorithm is greater. The proposed approach shows promising results, which when compared to the existing techniques. Additionally, the time consumption of the proposed approach is very minimal than the comparative techniques.
Molecular Simulation of Hydrogen Adsorption onto Single-Walled Carbon and Boron-Nitride Nano-Cones

In this paper, we have studied the hydrogen adsorption onto CNCs and BNNCs nano-cones using GCMC simulations. The effects of length and cone apex angle on adsorption property have been investigated. Our results show that with increasing the pressure and decreasing the cone length and cone apex angle except for CNC-300˚, the hydrogen adsorption onto the BNNCs and CNCs was increased. It was also found that BNNCs can uptake more hydrogen in comparison with CNCs at the same thermodynamically conditions. Further, more hydrogen adsorption can be achieved in both CNCs and BNNCs with 240˚apex angle. This finding attributed to high surface area as well as strong interactions between hydrogen molecules and respected nano-cones. Also, results of hydrogen adsorption with unit of mol/m3 are corresponded of the energy of hydrogen adsorption.
Redes Neurais Artificiais Aplicadas A Problemas De Classificação Hierárquica Multirrótulo

Resumo – Em problemas de classificação hierárquica multirrótulo, cada exemplo pode ser classificado em duas ou mais classes simultaneamente, diferentemente de problemas de classificação convencionais. Adicionalmente, as classes envolvidas nesses problemas são estruturadas em uma hierarquia, que pode ser uma árvore ou um grafo acı́clico direcionado (DAG). Dessa forma, um exemplo pode ser atribuı́do a dois ou mais caminhos de uma estrutura hierárquica formada por centenas e até milhares de classes, dificultando muito o problema de classificação. Muitos métodos têm sido propostos para solucionar tais problemas, alguns deles utilizando um único classificador para lidar com todas as classes simultaneamente (métodos globais), e outros utilizando vários classificadores para decompor o problema original em vários subproblemas (métodos locais). Este trabalho propõe um método local para classificação hierárquica multirrótulo utilizando redes neurais artificiais. O método é chamado HMCLMLP (Hierarchical Multi-label Classification with Local Multi-Layer Perceptron), e utiliza uma rede Multi-Layer Perceptron (MLP) associada a cada nı́vel da hierarquia. As predições feitas em um nı́vel são então utilizadas como entrada para outra MLP responsável pelas predições no próximo nı́vel. São utilizados dois algoritmos para o treinamento das MLPs, o algoritmo Backpropagation e o algoritmo Resilient back-propagation. Adicionalmente, além da medida de erro convencional, uma medida de erro especı́fica para problemas multirrótulo é utilizada para o treinamento das redes. O método é comparado com outros dois métodos locais considerados estado da arte para problemas de classificação hierárquica multirrótulo, utilizando conjuntos de dados relacionados à predição de funções de proteı́nas. De acordo com os resultados experimentais, o método proposto obteve resultados preditivos competitivos, o que sugere as redes neurais artificiais como alternativas promissoras para tratar problemas de classificação hierárquica multirrótulo.
Math self-concept and mathematics achievement: Examining gender variation and reciprocal relations among junior high school students in Taiwan

The study explored Taiwanese students’ mathematics learning at the junior high school level. Utilizing structural equation modeling, it examined the relationships between math self-concept and mathematics achievement with longitudinal data. Participants included 1,256 Taiwanese seventh graders in the first wave and declined slightly to 1,211 eighth graders in the second wave. Findings indicated the following. First, the longitudinal effects were all significant: (a) prior mathematics achievement significantly predicted subsequent math self-concept (skill development model), (b) prior math self-concept significantly predicted subsequent mathematics achievement (self-enhancement model), and (c) the reciprocal effects model was supported, and the effects of achievement tended to become stronger and more systematic. Second, results showed significant gender variation with respect to math self-concept and mathematics achievement. Boys had significantly higher math self-concept than girls, whereas girls exhibited higher mathematics achievement than boys. The implications of these findings for cultivating students’ interest in mathematics learning were discussed.
Contribution of the buffer layer to the Raman spectrum of epitaxial graphene on SiC(0001)

We report a Raman study of the so-called buffer layer with periodicity which forms the intrinsic interface structure between epitaxial graphene and SiC(0001). We show that this interface structure leads to a non-vanishing signal in the Raman spectrum at frequencies in the range of the D- and G-band of graphene and discuss its shape and intensity. Ab initio phonon calculations reveal that these features can be attributed to the vibrational density of states of the buffer layer.
Pool Boiling on Modified Surfaces Using R-123

Saturated pool boiling of R-123 was investigated for five horizontal copper surfaces modified by different treatments, namely, an emery-polished surface, a fine sandblasted surface, a rough sandblasted surface, an electron beam-enhanced surface, and a sintered surface. Each 40-mm-diameter heating surface formed the upper face of an oxygen-free copper block, electrically heated by embedded cartridge heaters. The experiments were performed from the natural convection regime through nucleate boiling up to the critical heat flux, with both increasing and decreasing heat flux, at 1.01 bar, and additionally at 2 bar and 4 bar for the emery-polished surface. Significant enhancement of heat transfer with increasing surface modification was demonstrated, particularly for the electron beam-enhanced and sintered surfaces. The emery-polished and sandblasted surface results are compared with nucleate boiling correlations and other published data.
The contents of free amino acids and elements in As-hyperaccumulator Pteris cretica and non-hyperaccumulator Pteris straminea during reversible senescence

Pavlíková D. , Zemanová V. , Pavlík M. (2017): The contents of free amino acids and elements in As-hyperaccumulator Pteris cretica and non-hyperaccumulator Pteris straminea during reversible senescence. Plant Soil Environ. , 63: 455–460. The objectives of this study were to analyse the relationship between the contents of elements and free amino acids (AAs) in fronds of As-hyperaccumulator Pteris cretica cv. Albo-lineata (PC) and non-hyperaccumulator Pteris straminea (PS) during reversible senescence. The time-course effect on senescence was also investigated. The two ferns were grown in a pot experiment with soil containing 16 mg Astotal/kg soil for 160 days. The contents of elements and AAs in both ferns and in individual sampling periods differed. The highest accumulation of elements and AAs was measured in PS fronds after 83 days; however, the accumulation of As, Ca, Cu, Fe, Mg, P and asparagin in PC fronds was highest after 160 days. The results of principal component analysis showed more rapid senescence of PS compared to PC. This was caused by changes in the relationship between the contents of elements (cofactors of metalloenzymes, stress metabolites) and AAs (transport of NH2 group and stress metabolites). The hyperaccumulator plant (PC) was more resistant than the bioindicator plant (PS) to the conversion from reversible to irreversible senescence.
Long-term and millennial-scale climate variability in northwestern France during the last 8850 years

Vegetation and quantitative climate reconstructions from a northwestern France shelf core (VK03-58Bis) show orbital and suborbital climate variability for the last 8850 years in this region. A long-term cooling trend in summer temperatures, marked by gradual temperate and humid forest decline, parallels cooling in Greenland and the decrease of mid-latitude summer insolation reduction until at least 2000 cal. yr BP. At the long-term scale, the lowering in seasonal contrast revealed by vegetation changes follows the increase of precession. Corylus woodlands spread at the expense of deciduous Quercus forest, between 8740 and 8390 cal. yr BP, linked with the high seasonality conditions that, counterbalancing the long-term astronomical forcing trend, were amplified by the north Atlantic high-latitudes winter sea-ice expansion. High seasonality conditions resulted from the Agassiz and Ojibway final outburst episodes and consequent gradual reduction of the Meridional Overturning Circulation (MOC). Between 8390—8060 cal. yr BP, a sudden Corylus woodland decline marks the 8.2 kyr cold event in northwestern France probably triggered by the severe MOC reduction leading to the additional drop in winter temperature over Europe and Greenland. Nonetheless, seasonality remains high during this interval. The high seasonality conditions detected in `VK03-58Bis' between 8740 and 8060 cal. yr BP reflects the multicentennial-scale climate cooling 8.6—8.0 kyr episode of the North Atlantic. Following the Agassiz and Ojibway final outburst episodes, climate became more stable. However, millennial-scale climate cooling episodes are recorded in `VK03-Bis' and are characterized by weak winter cooling and increases in precipitation. Furthermore, dinocyst analysis and benthic gastropod Turritella communis occurrences indicate regional changes such as the southward migration of the Boreal biogeographical zone between 8740 and 8480 cal. yr BP and the subsequent opening of the English Channel at around 8480—8390 cal. yr BP.
Green-eyed monsters: a corpus-based study of the concepts of ENVY and JEALOUSY in modern English

In this paper, I apply metaphorical pattern analysis suggested in Stefanowitsch (2006) to a British National Corpus-based study of the emotion concepts of JEALOUSY and ENVY. On identification of central conceptual metaphors of these emotion concepts, I show that although both manifest significant similarity in the source domains via which they are construed in English, their specificity in relation to each other and other emotion concepts can nevertheless be assessed with the help of a quantitative distributional analysis of the frequencies of occurrence of metaphoric expressions associated with each of the concepts under study. Furthermore, I question whether folk metaphoric conceptualizations of the English concepts of JEALOUSY and ENVY, together with three other “prototypical” social emotion concepts of SHAME, GUILT and PRIDE, are consistent with the criteria posited for differentiating them as “secondary” against the set of “basic”, or “primary” emotion concepts in English-speaking psychological literature (Ekman 1992, Ortony/Turner 1990, Parrot 2001) and discuss the implications of this consistency in the context of the role of metaphoric language in forming cultural models of emotions and influencing the English language speakers' conjectures about emotional experiences in scientific research.
Epilepsy diagnosis using artificial neural network learned by PSO

Electroencephalogram (EEG) is used routinely for diagnosis of diseases occurring in the brain. It is a very useful clinical tool in the classification of epileptic seizures and the diagnosis of epilepsy. In this study, epilepsy diagnosis has been investigated using EEG records. For this purpose, an artificial neural network (ANN), widely used and known as an active classification technique, is applied. The particle swarm optimization (PSO) method, which does not need gradient calculation, derivative information, or any solution of differential equations, is preferred as the training algorithm for the ANN. A PSO-based neural network (PSONN) model is diversified according to PSO versions, and 7 PSO-based neural network models are described. Among these models, PSONN3 and PSONN4 are determined to be appropriate models for epilepsy diagnosis due to having better classification accuracy. The training methods-based PSO versions are compared with the backpropagation algorithm, which is a traditional method. In addition, different numbers of neurons, iterations/generations, and swarm sizes have been considered and tried. Results obtained from the models are evaluated, interpreted, and compared with the results of earlier works done with the same dataset in the literature.