Miracle-dz/UniFAR-FTUs huggingface dataset:
Euoplocephalus tutus and the Diversity of Ankylosaurid Dinosaurs in the Late Cretaceous of Alberta, Canada, and Montana, USA

Few ankylosaurs are known from more than a single specimen, but the ankylosaurid Euoplocephalus tutus (from the Late Cretaceous of Alberta, Canada and Montana, USA) is represented by dozens of skulls and partial skeletons, and is therefore an important taxon for understanding intraspecific variation in ankylosaurs. Euoplocephalus is unusual compared to other dinosaurs from the Late Cretaceous of Alberta because it is recognized from the Dinosaur Park, Horseshoe Canyon, and Two Medicine formations. A comprehensive review of material attributed to Euoplocephalus finds support for the resurrection of its purported synonyms Anodontosaurus lambei and Scolosaurus cutleri, and the previously resurrected Dyoplosaurus acutosquameus. Anodontosaurus is found primarily in the Horseshoe Canyon Formation of Alberta and is characterized by ornamentation posterior to the orbits and on the first cervical half ring, and wide, triangular knob osteoderms. Euoplocephalus is primarily found in Megaherbivore Assemblage Zone 1 in the Dinosaur Park Formation of Alberta and is characterized by the absence of ornamentation posterior to the orbits and on the first cervical half ring, and keeled medial osteoderms on the first cervical half ring. Scolosaurus is found primarily in the Two Medicine Formation of Montana (although the holotype is from Dinosaur Provincial Park), and is characterized by long, back-swept squamosal horns, ornamentation posterior to the orbit, and low medial osteoderms on the first cervical half ring; Oohkotokia horneri is morphologically indistinguishable from Scolosaurus cutleri. Dyoplosaurus was previously differentiated from Euoplocephalus sensu lato by the morphology of the pelvis and pes, and these features also differentiate Dyoplosaurus from Anodontosaurus and Scolosaurus; a narrow tail club knob is probably also characteristic for Dyoplosaurus.
Exploring DSM-5 ADHD criteria beyond young adulthood: phenomenology, psychometric properties and prevalence in a large three-decade birth cohort

Background There are still uncertainties on the psychometric validity of the DSM-5 attention deficit hyperactivity disorder (ADHD) criteria for its use in the adult population. We aim to describe the adult ADHD phenotype, to test the psychometric properties of the DSM-5 ADHD criteria, and to calculate the resulting prevalence in a population-based sample in their thirties. Method A cross-sectional evaluation using the DSM-5 ADHD criteria was carried out in 3574 individuals from the 1982 Pelotas Birth Cohort. Through receiver operator curve, latent and regression analyses, we obtained parameters on construct and discriminant validity. Still, prevalence rates were calculated for different sets of criteria. Results The latent analysis suggested that the adult ADHD phenotype is constituted mainly by inattentive symptoms. Also, inattention symptoms were the symptoms most associated with impairment. The best cut-off for diagnosis was four symptoms, but sensitivity and specificity for this cut-off was low. ADHD prevalence rates were 2.1% for DSM-5 ADHD criteria and 5.8% for ADHD disregarding age-of-onset criterion. Conclusions The bi-dimensional ADHD structure proposed by the DSM demonstrated both construct and discriminant validity problems when used in the adult population, since inattention is a much more relevant feature in the adult phenotype. The use of the DSM-5 criteria results in a higher prevalence of ADHD when compared to those obtained by DSM-IV, and prevalence would increase almost threefold when considering current ADHD syndrome. These findings suggest a need for further refinement of the criteria for its use in the adult population.
A new interpretation of scattered light measurements at Titan's limb

Images of Titan, taken by Voyager 2 at phase angles Φ=140° and Φ=155° have provided radial intensity profiles at the bright and dark limbs, which provide information on the vertical and latitudinal distribution of organic hazes. In previous work, the deduced extinction coefficient, using ad hoc particle sizes, was obtained without help of microphysics, and it appeared difficult to compare it with coefficients computed from theoretical models. We use here our fractal approach of microphysical modeling and optics of agregates to compute intensity profiles of the main haze at the bright limb, and compare to the Voyager observations. Fractal aerosol distributions are obtained using different production altitudes and rates. Scattering and absorption of light are described by an improved model, based on the use of fractal aggregates made of spherical (Mie) particles. We show that the fractal dimension of aggregates has to be Df≈2, as predicted by microphysical arguments. Only a production altitude z0≈385±60 km, corresponding to a monomer radius rm≈0.066 μm, is fully consistent with both phase angle data. We also point out that the production rate of the aerosols decreases by a factor ≈2 between 30°S and the midnorthern latitude and further, increases up to 80°N. The average value of the production rate is Q≈1.4×10−13 kg/m2/s; we give arguments in favor of dynamical processes rather than of a purely microphysical mechanisms to explain such latitudinal variations.
Selective uplink training for massive MIMO systems

As a promising technique to meet the drastically growing demand for both high throughput and uniform coverage in the fifth generation (5G) wireless networks, massive multiple-input multiple-output (MIMO) systems have attracted significant attention in recent years. However, in massive MIMO systems, as the density of mobile users (MUs) increases, conventional uplink training methods will incur prohibitively high training overhead, which is proportional to the number of MUs. In this paper, we propose a selective uplink training method for massive MIMO systems, where in each channel block only part of the MUs will send uplink pilots for channel training, and the channel states of the remaining MUs are predicted from the estimates in previous blocks, taking advantage of the channels' temporal correlation. We propose an efficient algorithm to dynamically select the MUs to be trained within each block and determine the optimal uplink training length. Simulation results show that the proposed training method provides significant throughput gains compared to the existing methods, while much lower estimation complexity is achieved. It is observed that the throughput gain becomes higher as the MU density increases.
Analysis and architecture design of block matching in BM3D image denoising

In this paper, a low-cost VLSI implementation for Block Matching (BM) in BM3D image denoising with novel architectures of the slip window and SSD tree are presented. The experimental results show that the proposed technique preserves the BM3D denoising performance and obtains excellent performances in terms of less logic gate count and better visual quality. The design requires only low computational complexity and less SRAM for slip window. Its hardware cost is quite low, about 350k gates. Synthesis results show that the proposed design at a throughput about 177MB/s by using UMC 0.18um technology.
First‐order error propagation formulae for the Gassmann relations

The Gassmann relations of poroelasticity provide a connection between the dry and the saturated elastic moduli of porous rock and are useful in a variety of petroleum geoscience applications. Because some uncertainty is usually associated with the input parameters, the propagation of error in the inputs into the final moduli estimates is immediately of interest. Two common approaches to error propagation include: a first‐order Taylor series expansion and Monte‐Carlo methods. The Taylor series approach requires derivatives, which are obtained either analytically or numerically and is usually limited to a first‐order analysis. The formulae for analytical derivatives were often prohibitively complicated before modern symbolic computation packages became prevalent but they are now more accessible. We apply this method and present formulae for uncertainty in the predicted bulk and shear moduli for two forms of the Gassmann relations. Numerical results obtained with these uncertainty formulae are compared with Monte‐Carlo calculations as a form of validation and to illustrate the relative characteristics of the two approaches. Particular emphasis is given to the problem of correlated variables, which are often ignored in naïve approaches to error analysis. Going out to the error level that the two methods were compared, the means agree and the variance of the Monte Carlo method for bulk modulus grows with input error.
Distributional semantics with eyes: using image analysis to improve computational representations of word meaning

The current trend in image analysis and multimedia is to use information extracted from text and text processing techniques to help vision-related tasks, such as automated image annotation and generating semantically rich descriptions of images. In this work, we claim that image analysis techniques can "return the favor" to the text processing community and be successfully used for a general-purpose representation of word meaning. We provide evidence that simple low-level visual features can enrich the semantic representation of word meaning with information that cannot be extracted from text alone, leading to improvement in the core task of estimating degrees of semantic relatedness between words, as well as providing a new, perceptually-enhanced angle on word semantics. Additionally, we show how distinguishing between a concept and its context in images can improve the quality of the word meaning representations extracted from images.
A study of low bit-rate linear prediction based speech coders for Indian dialects

Speech coders based on the linear prediction model are widely in use today. This paper describes the algorithms of low bit-rate vocoders, viz. Code-Excited Linear Prediction (CELP) and Mixed Excitation Linear Prediction (MELP) and their performance for Indian dialects. A Linux platform has been used for execution of the vocoders. Mean Opinion Score testing has been performed with speech samples of Indian dialects and Indian-accented English. Waveform analysis has been done using Praat software. Results show that CELP which operates at a higher bit rate of 4.8 kb/s gives better quality output. MELP speech output is intelligible and suited for very low bit-rate (2.4 kb/s) applications. The results also highlight the need for better codebook tuning in Indian dialects.
Numerical modeling of sorption kinetics of organic compounds to soil and sediment particles

A numerical model is developed to simulate hydrophobic organic compound sorption kinetics, based on a retarded intraaggregate diffusion conceptualization of this solid-water exchange process. This model was used to ascertain the sensitivity of the sorption process for various sorbates to nonsteady solution concentrations and to polydisperse soil or sediment aggregate particle size distributions. Common approaches to modeling sorption kinetics amount to simplifications of our model and appear justified only when (1) the concentration fluctuations occur on a time scale which matches the sorption timescale of interest and (2) the particle size distribution is relatively narrow. Finally, a means is provided to estimate the extent of approach of a sorbing system to equilibrium as a function of aggregate size, chemical diffusivity and hydrophobicity, and system solids concentrations.
Activation of vascular endothelial growth factor gene transcription by hypoxia-inducible factor 1

Expression of vascular endothelial growth factor (VEGF) is induced in cells exposed to hypoxia or ischemia. Neovascularization stimulated by VEGF occurs in several important clinical contexts, including myocardial ischemia, retinal disease, and tumor growth. Hypoxia-inducible factor 1 (HIF-1) is a heterodimeric basic helix-loop-helix protein that activates transcription of the human erythropoietin gene in hypoxic cells. Here we demonstrate the involvement of HIF-1 in the activation of VEGF transcription. VEGF 5'-flanking sequences mediated transcriptional activation of reporter gene expression in hypoxic Hep3B cells. A 47-bp sequence located 985 to 939 bp 5' to the VEGF transcription initiation site mediated hypoxia-inducible reporter gene expression directed by a simian virus 40 promoter element that was otherwise minimally responsive to hypoxia. When reporters containing VEGF sequences, in the context of the native VEGF or heterologous simian virus 40 promoter, were cotransfected with expression vectors encoding HIF-1alpha and HIF-1beta (ARNT [aryl hydrocarbon receptor nuclear translocator]), reporter gene transcription was much greater in both hypoxic and nonhypoxic cells than in cells transfected with the reporter alone. A HIF-1 binding site was demonstrated in the 47-bp hypoxia response element, and a 3-bp substitution eliminated the ability of the element to bind HIF-1 and to activate transcription in response to hypoxia and/or recombinant HIF-1. Cotransfection of cells with an expression vector encoding a dominant negative form of HIF-1alpha inhibited the activation of reporter transcription in hypoxic cells in a dose-dependent manner. VEGF mRNA was not induced by hypoxia in mutant cells that do not express the HIF-1beta (ARNT) subunit. These findings implicate HIF-1 in the activation of VEGF transcription in hypoxic cells.
Degrees of Freedom of Time Correlated MISO Broadcast Channel With Delayed CSIT

We consider the time correlated multiple-input single-output (MISO) broadcast channel where the transmitter has imperfect knowledge of the current channel state, in addition to delayed channel state information. By representing the quality of the current channel state information as P-α for the signal-to-noise ratio P and some constant α ≥ 0, we characterize the optimal degrees of freedom region for this more general two-user MISO broadcast correlated channel. The essential ingredients of the proposed scheme lie in the quantization and multicast of the overheard interferences, while broadcasting new private messages. Our proposed scheme smoothly bridges between the scheme recently proposed by Maddah-Ali and Tse with no current state information and a simple zero-forcing beamforming with perfect current state information.
A magnetotelluric image at subduction zone: Taiwan

As part of an integrated project to map the 3-D structures beneath Taiwan, which is a typical example of arccontinental collision, broadband magnetotelluric (MT) data have been collected and analyzed at 20 sites uniformly covering the entire Taiwan. The determinant response of impedance tensor was calculated for inversion and the Occam’s inversion which could generate smooth model was used for interpreting MT data at each site. A north dipping conductor, at a depth of approximately 10-20 km with resistivities lower than 100 ohm-m beneath the Island of Taiwan is undoubtedly the most significant feature obtained in this study. The depth are correlated well with the inferred depth of dehydration reactions from Suppe (1981) and the top of the aseismic lower crust observed by Wang (1994). We infer that this dipping conductor is associated with the upper surface of the subducting Philippine Sea plate. This finding also provides one more example to support the argument that conductivity anomalies are commonly associated with plate subduction.
The Role of Leadership Practices on Job Stress among Malay Academic Staff: a Structural Equation Modeling Analysis

Globalization brings change in all aspect of human life, including in how job and organizations operate. These changes create strain and stress not only among employee at business organization, but also among academic staff. The dean of faculty or department at university has important role in prevent the effects of job stress among the academic staff by giving support, motivation, and redesign how a task should be finished to reduce job stress. This study aims to examine the role of leadership practices with job stress among Malay academic staff. Design of this study is survey research with quantitative approach. A total of 124 academic staff participate or answered the questionnaires. The data was analyzed with structural equation model method using Amos 18 program. The result of structural equation modeling suggests that four dimensions of leadership practices show unique relationship pattern with four dimensions of job stress. The significant relationship between exogenous and endogenous was tested using structural equation modeling (SEM). The result of SEM analysis just confirms three exogenous variables that significantly have relationship with endogenous variables. Those are dimension of challenging the process with behavioral, emotional, physiologic and cognitive stress responses. Enabling others to act with emotional stress response, and the last, encouraging the heart with behavioral stress response. While inspiring a shared vision is not have significant relationship with all dimension of job stress. Overall, the proposed model had a fit model with empirical data. The mechanism of relationship among exogenous and endogenous variables will be discussed in a paper below.
Person Identification by Using AR Model for EEG Signals

A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960’s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.
Revista Española De Cirugía Ortopédica Y Traumatología Study of the Role of Mirna in Mesenchymal Stem Cells Isolated from Osteoarthritis Patients

Objective: miRNAs act as gene silencers that are involved in the regulation of essential cell functions. miR-335 is involved in regulating cell differentiation processes in progenitor cells. Mesenchymal stem cells (MSCs) are progenitor cells of chondrocytes and osteoblasts responsible for homeostatic maintenance of cartilage and bone. The aim of this study was to determine a possible relationship between the expression of miR-335 and osteoarthritis. Methods: MSCs obtained from the bone marrow of 3 osteoarthritic patients and 3 controls with no clinical signs of osteoarthritis or osteoporosis were cultured and phenotypically and functionally characterized in a 3-step culture. Expression levels of miR-335 and the mesoderm-specific transcript gene-MEST-that controls its expression were determined by quantitative PCR. Results: Differences in the expression levels of miR-335 and MEST (median [interquartile range]: 1.69 [0.85-1.74], and 3.85 [3.20-5.67] were detected between MSCs isolated from patients with osteoarthritis and controls. Although the differences detected did not reach statistical significance (P = .1), a clear trend toward lower expression of miR-335 in osteoarthritis MSCs was observed. Conclusions: Given that miR-335 has the different genes involved in the Wnt signaling pathway as potential targets, the observed trend may help to ascertain, at least partially, some of the alterations which determine the onset or progression of osteoarthritis, and can therefore serve for the design of future therapeutic targets for the treatment of this disease. Aunque las diferencias detectadas no alcanzaron una signifi-cación estadística (p = 0,1), sí se apreció una clara tendencia a una menor expresión de miR-335 en las MSC de pacientes artrósicos.
Combinatorial Abstractions of Dynamical Systems

Formal verification has been successfully developed in computer science for verifying combinatorial classes of models and specifications. In like manner, formal verification methods have been developed for dynamical systems. However, the verification of system properties, such as safety, is based on reachability calculations, which are the sources of insurmountable complexity. This talk addresses indirect verification methods, which are based on abstracting the dynamical systems by models of reduced complexity and preserving central properties of the original systems.
Using a Data-Constrained Model of Home Range Establishment to Predict Abundance in Spatially Heterogeneous Habitats

Mechanistic modelling approaches that explicitly translate from individual-scale resource selection to the distribution and abundance of a larger population may be better suited to predicting responses to spatially heterogeneous habitat alteration than commonly-used regression models. We developed an individual-based model of home range establishment that, given a mapped distribution of local habitat values, estimates species abundance by simulating the number and position of viable home ranges that can be maintained across a spatially heterogeneous area. We estimated parameters for this model from data on red-backed vole (Myodes gapperi) abundances in 31 boreal forest sites in Ontario, Canada. The home range model had considerably more support from these data than both non-spatial regression models based on the same original habitat variables and a mean-abundance null model. It had nearly equivalent support to a non-spatial regression model that, like the home range model, scaled an aggregate measure of habitat value from local associations with habitat resources. The home range and habitat-value regression models gave similar predictions for vole abundance under simulations of light- and moderate-intensity partial forest harvesting, but the home range model predicted lower abundances than the regression model under high-intensity disturbance. Empirical regression-based approaches for predicting species abundance may overlook processes that affect habitat use by individuals, and often extrapolate poorly to novel habitat conditions. Mechanistic home range models that can be parameterized against abundance data from different habitats permit appropriate scaling from individual- to population-level habitat relationships, and can potentially provide better insights into responses to disturbance.