Miracle-dz/UniFAR-FTUs huggingface dataset:
Students’ engagement in social media in Cambodia O envolvimento dos alunos no Camboja com as mídias sociais

Conhecimento & Diversidade, Niterói, v. 11, n. 23, p. 145–165, jan/abr. 2019 According to Choudhury (2014), Web 1.0 lasted from 1989 to 2005, Web 2.0 was defined by Dale Dougherty in 2004 and Web 3.0 was first coined by John Markoff of the New York Times. To describe and characterize the social dynamics and information processes that are part of the Internet, Fuchs et al. (2010) identified three qualities of the Web, namely Web 1.0 as a Web of cognition, Web 2.0 as a Web of human communication, and Web 3.0 as a Web of co-operation.
Anti-oxidative metabolite comparison between two phenotypes of Celastrus hindsii Benth

Celastrus hindsii Benth. is an evergreen twining shrub that has been used for generations in Northern Vietnam for diseased treatment relating to ulcers, tumors, and inflammation due to its bioactive compounds. The narrow leaf and broad leaf phenotypes have raised concerns about their comparatively biochemical quality, which is the determinant of their uses for medicinal purposes. The study aimed to investigate the concentration of important anti-oxidative metabolites between narrow leaf and broad leaf phenotypes using spectrophotometric method. The results showed that BL had a significantly higher level of -tocopherol, flavonoid, phospholipid, and possibly glutathione (based on an air-dry weight and protein basis). Stress biomarkers such as proline and malondialdehyde were elevated in NL, indicating their roles in response to stress. In contrast, the enzyme and metabolite increase in NL may be associated with tissue degradation. BL of C. hindsii, which contains more diverse and superior concentrations of essential phytochemicals and pharmaceutically related proteins, should be positioned as an important commercial source for natural drug development.
Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy

Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value < 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.
MECHANICAL PROPERTIES OF WOVEN NATURAL FIBER REINFORCED COMPOSITES

Epoxy matrix composites reinforced with woven natural fiber were studied. Composites having fiber volume fraction greater than 55% were prepared by hand lay-up technique. For reinforcement, three different natural fibers were used, jute, flax and silk. The tensile and flexural properties were investigated and the influence of the orientation of fibers on the stiffness were analyzed. It was observed that the tensile and flexural strength of silk composites is almost equal to that of flax composite and 1.98 times that of jute composite. Moreover the stiffness of the silk composites isn’t influenced by orientation of fibers. Morphological examinations were carried out using scanning electron microscopy (SEM). All specimens were coated with a thin layer gold alloy prior to SEM observations. A high voltage of 20 kV was used for making the micrographs. The SEM investigation was used to study the fracture surface of the tensile specimens of the composites samples. The results of this study indicate that using silk fiber as reinforcement could successfully develop a composite material in terms of high strength and stiffness to produce a bio-composites for light applications compared to conventional composites.
Salty Matters Saline Dolomites : Saline marine-margin analogs-Coorong Lakes

Most authors agree that precipitating dolomite (cf calcite) is a kinetic problem that must overcome an energy barrier imposed by Mg2+ hydration and that ordered placement of cations as alternating Mg and Ca layers separated by a carbonate layer requires high levels of kinetic energy (Lippmann, 1973; Land, 1998; Warren, 2000). Mechanisms proposed to overcome this kinetic prohibition include; increased Mg/Ca, removal of sulphate, microbial catalysis, carboxyl group facilitation and abiogenically from solutions containing polysaccharides such as carboxymethyl cellulose or agar (Figure 1). This multiplicity of causes ties to what is known as the dolomite problem via a simple twofold statement: 1) there is a sharp contrast between the scarce poorly-ordered thin-bedded modern dolomite occurrences and the abundant stoichiometric thick-layered platform-wide units of ancient dolomite; 2) there is significant chemical variation in environments where dolomites Introduction More than two hundred years ago, the mineral dolomite was first described in the French Alps by the French geologist Dolomieu, and the mineral was later named after him (Dolomieu, 1791). Since then, a variety of mechanisms and processes have been used to explain the formation of dolomite, including Holocene dolomites identified in contemporary Coorong-style lacustrine dolomite, sabkha-style arid peritidal dolomite, and normal seawater dolomite settings. These modern dolomites are variously described as penecontemporaneous, syndepositional or eogenetic. Lattice structure in Holocene dolomites is always highly disordered with mineral compositions that are calcian or magnesian-rich and never truly stoichiometric (Mg: Ca = 1). Then there are the early burial diagenetic (eogenetic to early mesogenetic) forms of dolomite (brine reflux dolomite, mixing-zone dolomite, and organogenic dolomite), as well as later mesogenetic or burial forms of dolomite. Ancient (pre-Holocene) dolomites tend to more ordered lattice structures, with chemistries approaching stoichiometric (Land, 1985; Warren, 2000).
A Human-Robot Interface based on Surface Electroencephalographic Sensors

We propose a human-robot interface based on potentials recorded through surface Electroencephalographic sensors, aiming to decode human visual attention into motion in three-dimensional space. Low-frequency components are extracted and processed in real time, and subspace system identification methods are used to derive the optimal, in mean squared sense, linear dynamics generating the position vectors. This results in a human-robot interface that can be used directly in robot teleoperation or as part of a shared-control robotic manipulation scheme, feels natural to the user, and is appropriate for upper extremity amputees, since it requires no limb movement. We validate our methodology by teleoperating a redundant, anthropomorphic robotic arm in real time. The system's performance outruns similar EMG-based systems, and shows low long-term model drift, indicating no need for frequent model re-training.
A comparison of pain registration by Visual Analog Scale and Numeric Rating Scale, a cross-sectional study of primary triage registration

Background Pain is a subjective sensation; self-reporting is important for quantifying pain intensity. There are several different validated tools for this, such as Visual Analog Scale and Numeric Rating Scale. In the clinic, these terms are often used as equivalent. The objective of this study was to examine correlation and agreement between the pain registration tools in triage in an emergency department. Materials and Methods The study was performed in the Department of Emergency Medicine at Haukeland University Hospital in the period June-August 2019. We registered the pain score with two tools in 200 unselected patients in emergency admission with pain. In addition, we registrered gender, age, triage and general department affiliation. Results We found a strong correlation between the pain registration tools by Spearmans correlation test (rho=0,930, p<0,001). There were no significant difference between the pain registration tools within the subgroups. Bland-Altman analysis show agreement between the two pain registration tools. Conclusions In an Emergency Department triage is it acceptable to use Visual Analog Scale and Numeric Rating Scale as equivalent, as long as the correct terminology is used.
Phenotypic Response Of Marine Cryptophytes To Varying Spectral Irradiance

v LIST OF TABLES . viii LIST OF FIGURES . ix LIST OF ABBREVIATIONS . x CHAPTER 1: INTRODUCTION . 1 CHAPTER 2: MATERIALS AND METHODS . 5 2.1 STUDY SPECIES AND STOCK CULTURES . 5 2.2 EXPERIMENTAL CULTURES . 5 2.3 GROWTH EXPERIMENTS . 6 2.4 CR-PBP ANALYSIS . 7 2.5 ABSORPTION SPECTRUM ANALYSIS . 8 2.6 HPLC PIGMENT ANALYSIS . 9 2.7 CELL VOLUME ANALYSIS . 10 2.8 STATISICAL ANALYSES . 10 CHAPTER 3: RESULTS . 14 3.1 GROWTH RATES . 14
Determination of trace elements: neutron-activation analysis in geochemistry and cosmochemistry

Geochemistry, like cosmochemistry, {open_quotes}studies chemical elements {hor_ellipsis} of the crust and {hor_ellipsis} the Earth {hor_ellipsis} their history, their distribution {hor_ellipsis} their genetic {hor_ellipsis} connections{close_quotes} and is based on data on the abundance and distribution of elements obtained by various analytical methods. Neutron-activation analysis (NAA) plays a particular role in this respect. This is due to its high sensitivity (detection limit as small as 10{sup -14} g), which makes possible the use of samples of arbitrary mass, and also due to the possibility of obtaining information about composition without destruction of the object, conserving, if required, the unique material under investigation. Of the most interest are the data on the contents for a number of trace elements (at a level of 10{sup -7} - 10{sup -4}%), among which are rare-earth elements (REE), U, Th, Zr, Hf, Ta, W, Ga, Ni, Rb, Cs, platinum-group metals, Ag, Au, etc. These elements are considered as indicators of geochemical processes associated with the genesis and evolution of solar system bodies in early and more recent stages of evolution; they are also used to study processes and phenomena at zone boundaries: river-sea, ocean-atmosphere, and so on. The aim of this work is to show the capabilitiesmore » of NAA in the determination of trace elements. « less
The Ximalaya TTS System for Blizzard Challenge 2020

This paper describes the proposed Himalaya text-to-speech synthesis system built for the Blizzard Challenge 2020. The two tasks are to build expressive speech synthesizers based on the released 9.5-hour Mandarin corpus from a male native speaker and 3-hour Shanghainese corpus from a female native speaker respectively. Our architecture is Tacotron2-based acoustic model with WaveRNN vocoder. Several methods for preprocessing and checking the raw BC transcript are imple-mented. Firstly, the multi-task TTS front-end module trans-forms the text sequences into phoneme-level sequences with prosody label after implement the polyphonic disambiguation and prosody prediction module. Then, we train the released corpus on a Seq2seq multi-speaker acoustic model for Mel spec-trograms modeling. Besides, the neural vocoder WaveRNN[1] with minor improvements generate high-quality audio for the submitted results. The identiﬁer for our system is M, and the experimental evaluation results in listening tests show that the system we submitted performed well in most of the criterion.
Characterizing the implicit bias via a primal-dual analysis

This paper shows that the implicit bias of gradient descent on linearly separable data is exactly characterized by the optimal solution of a dual optimization problem given by a smoothed margin, even for general losses. This is in contrast to prior results, which are often tailored to exponentially-tailed losses. For the exponential loss specifically, with $n$ training examples and $t$ gradient descent steps, our dual analysis further allows us to prove an $O(\ln(n)/\ln(t))$ convergence rate to the $\ell_2$ maximum margin direction, when a constant step size is used. This rate is tight in both $n$ and $t$, which has not been presented by prior work. On the other hand, with a properly chosen but aggressive step size schedule, we prove $O(1/t)$ rates for both $\ell_2$ margin maximization and implicit bias, whereas prior work (including all first-order methods for the general hard-margin linear SVM problem) proved $\widetilde{O}(1/\sqrt{t})$ margin rates, or $O(1/t)$ margin rates to a suboptimal margin, with an implied (slower) bias rate. Our key observations include that gradient descent on the primal variable naturally induces a mirror descent update on the dual variable, and that the dual objective in this setting is smooth enough to give a faster rate.
Deep Efficient End-to-End Reconstruction (DEER) Network for Few-View Breast CT Image Reconstruction

Breast CT provides image volumes with isotropic resolution in high contrast, enabling detection of small calcification (down to a few hundred microns in size) and subtle density differences. Since breast is sensitive to x-ray radiation, dose reduction of breast CT is an important topic, and for this purpose, few-view scanning is a main approach. In this article, we propose a Deep Efficient End-to-end Reconstruction (DEER) network for few-view breast CT image reconstruction. The major merits of our network include high dose efficiency, excellent image quality, and low model complexity. By the design, the proposed network can learn the reconstruction process with as few as <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(N)$ </tex-math></inline-formula> parameters, where <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> is the side length of an image to be reconstructed, which represents orders of magnitude improvements relative to the state-of-the-art deep-learning-based reconstruction methods that map raw data to tomographic images directly. Also, validated on a cone-beam breast CT dataset prepared by Koning Corporation on a commercial scanner, our method demonstrates a competitive performance over the state-of-the-art reconstruction networks in terms of image quality. The source code of this paper is available at: <uri>https://github.com/HuidongXie/DEER</uri>.
Improving Graduation Rate Estimates Using Regularly Updating Multi-Level Absorbing Markov Chains

American universities use a procedure based on a rolling six-year graduation rate to calculate statistics regarding their students’ final educational outcomes (graduating or not graduating). As an alternative to the six-year graduation rate method, many studies have applied absorbing Markov chains for estimating graduation rates. In both cases, a frequentist approach is used. For the standard six-year graduation rate method, the frequentist approach corresponds to counting the number of students who finished their program within six years and dividing by the number of students who entered that year. In the case of absorbing Markov chains, the frequentist approach is used to compute the underlying transition matrix, which is then used to estimate the graduation rate. In this paper, we apply a sensitivity analysis to compare the performance of the standard six-year graduation rate method with that of absorbing Markov chains. Through the analysis, we highlight significant limitations with regards to the estimation accuracy of both approaches when applied to small sample sizes or cohorts at a university. Additionally, we note that the Absorbing Markov chain method introduces a significant bias, which leads to an underestimation of the true graduation rate. To overcome both these challenges, we propose and evaluate the use of a regularly updating multi-level absorbing Markov chain (RUML-AMC) in which the transition matrix is updated year to year. We empirically demonstrate that the proposed RUML-AMC approach nearly eliminates estimation bias while reducing the estimation variation by more than 40%, especially for populations with small sample sizes.
Dynamical structure of highly eccentric discs with applications to tidal disruption events

Whether tidal disruption events circularise or accrete directly as highly eccentric discs is the subject of current research and appears to depend sensitively on the disc thermodynamics. One aspect of this problem that has not received much attention is that a highly eccentric disc must have a strong, non-hydrostatic variation of the disc scale height around each orbit. As a complement to numerical simulations carried out by other groups, we investigate the dynamical structure of TDE discs using the nonlinear theory of eccentric accretion discs. In particular, we study the variation of physical quantities around each elliptical orbit, taking into account the dynamical vertical structure, as well as viscous dissipation and radiative cooling. The solutions include a structure similar to the nozzle-like structure seen in simulations. We find evidence for the existence of the thermal instability in highly eccentric discs dominated by radiation pressure. For thermally stable solutions many of our models indicate a failure of the $\alpha-$prescription for turbulent stresses. We discuss the consequences of our results for the structure of eccentric TDE discs.
SimulMT to SimulST: Adapting Simultaneous Text Translation to End-to-End Simultaneous Speech Translation

We investigate how to adapt simultaneous text translation methods such as wait-k and monotonic multihead attention to end-to-end simultaneous speech translation by introducing a pre-decision module. A detailed analysis is provided on the latency-quality trade-offs of combining fixed and flexible pre-decision with fixed and flexible policies. We also design a novel computation-aware latency metric, adapted from Average Lagging.
On Ordered Fuzzy Numbers Generated By Time Series.

This paper proposes a new trapezoidal ordered fuzzy number representation of windowed time series based on the idea of a Japanese candlestick to those previously proposed in the literature. We define and illustrate several descriptive statistics based on the information contained in the ordered fuzzy numbers. We utilize financial trading data from three automotive companies as a case study. Further expansion can be applied to any other forms of time series data to offer further insight into many other data driven situations.
Bayesian Variational Optimization for Combinatorial Spaces

This paper focuses on Bayesian Optimization in combinatorial spaces. In many applications in the natural science. Broad applications include the study of molecules, proteins, DNA, device structures and quantum circuit designs, a on optimization over combinatorial categorical spaces is needed to find optimal or pareto-optimal solutions. However, only a limited amount of methods have been proposed to tackle this problem. Many of them depend on employing Gaussian Process for combinatorial Bayesian Optimizations. Gaussian Processes suffer from scalability issues for large data sizes as their scaling is cubic with respect to the number of data points. This is often impractical for optimizing large search spaces. Here, we introduce a variational Bayesian optimization method that combines variational optimization and continuous relaxations to the optimization of the acquisition function for Bayesian optimization. Critically, this method allows for gradient-based optimization and has the capability of optimizing problems with large data size and data dimensions. We have shown the performance of our method is comparable to state-of-the-art methods while maintaining its scalability advantages. We also applied our method in molecular optimization.
Electronic Structure Correspondence of Singlet-Triplet Scale Separation in Strained Sr2RuO4

At a temperature of roughly 1 K, Sr2RuO4 undergoes a transition from a normal Fermi liquid to a superconducting phase. Even while the former is relatively simple and well understood, the superconducting state has not even been understood after 25 years of study. More recently, it has been found that critical temperatures can be enhanced by the application of uniaxial strain, up to a critical strain, after which it falls off. In this work, we take an “instability” approach and seek divergences in susceptibilities. This provides an unbiased way to distinguish tendencies to competing ground states. We show that in the unstrained compound, the singlet and triplet instabilities of the normal Fermi liquid phase are closely spaced. Under uniaxial strain, electrons residing on all orbitals contributing to the Fermiology become more coherent, while the electrons of the Ru-dxy character become heavier, and the electrons of the Ru-dxz,yz characters become lighter. In the process, Im χ(q,ω) increases rapidly around q = (0.3,0.3,0)2π/a and q = (0.5,0.25,0)2π/a, while it gets suppressed at all other commensurate vectors, in particular at q = 0, which is essential for spin-triplet superconductivity. We observe that the magnetic anisotropy under strain drops smoothly, which is concomitant with the increment in singlet instability. Thus, the triplet superconducting instability remains the lagging instability of the system, and the singlet instability enhances under strain, leading to a large energy-scale separation between these competing instabilities. However, since this happens even without spin-orbit coupling, we believe it is primarily the enhancement in the spin fluctuation glue around quasi-anti-ferromagnetic vectors that drives the Cooper pairing instead of the magnetic anisotropy. At large strain, an instability to a spin density wave overtakes the superconducting one. The analysis relies on a high-fidelity, ab initio description of the one-particle properties and two-particle susceptibilities, based on the quasiparticle self-consistent GW approximation augmented by dynamical mean field theory. This approach is described and its high fidelity confirmed by comparing to observed one- and two-particle properties.