Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.
Presentations of the Roger–Yang generalized
skein algebra

We describe presentations of the Roger-Yang generalized skein algebras for punctured spheres with an arbitrary number of punctures. This skein algebra is a quantization of the decorated Teichmuller space and generalizes the construction of the Kauffman bracket skein algebra. In this paper, we also obtain a new interpretation of the homogeneous coordinate ring of the Grassmannian of planes in terms of skein theory.
Ácido indolbutírico e ortotropismo na miniestaquia de Araucaria angustifolia

Considering the limitations of vegetative propagation of Araucaria angustifolia and the total absence of information regarding the minicuttings technique in this species, this study aimed to evaluate the influence of concentrations of indolbutyric acid (IBA) in minicuttings technique of Araucaria angustifolia, as well as the characterization of growth habit (orthotropic or plagiotropic) of the minicuttings produced. The Minigarden comprised ministumps propagated by seeds. The basal region of minicuttings was exposed during 10s in solutions containing concentrations 0, 1.5, 3.0 and 4.0 gL-1 IBA after what they were transferred to a greenhouse for 120 days. The design was completely randomized with five replications of 15 minicuttings. Increasing IBA concentrations favored a little increase in survival (up to 3.0 gL-1), number of roots of minicuttings (estimate up to 2.3 gL-1) and rooting (up to 1.5 gL-1), causing inhibition at the highest concentration, however the low 32% best rooting result obtained. According to the results there is a need to develop more studies on the specie, especially when considering the nutritional and environmental propagation. The growing habit of all rooted minicuttings was orthotropic, showing the potential of the technique in cloning selected families of the species.
Examining the drivers of business cycle divergence between Euro Area and Romania.

This research aims to provide an explanatory analyses of the business cycles divergence between Euro Area and Romania, respectively its drivers, since the synchronisation of output-gaps is one of the most important topic in the context of a potential EMU accession. According to the estimates, output-gaps synchronisation entered on a downward path in the subperiod 2010-2017, compared to 2002-2009. The paper demonstrates there is a negative relationship between business cycles divergence and three factors (economic structure convergence, wage structure convergence and economic openness), but also a positive relationship between it and its autoregressive term, respectively the GDP per capita convergence.
Feature based Sequential Classifier with Attention Mechanism

Cervical cancer is one of the deadliest cancers affecting women globally. Cervical intraepithelial neoplasia (CIN) assessment using histopathological examination of cervical biopsy slides is subject to interobserver variability. Automated processing of digitized histopathology slides has the potential for more accurate classification for CIN grades from normal to increasing grades of pre-malignancy: CIN1, CIN2 and CIN3. Cervix disease is generally understood to progress from the bottom (basement membrane) to the top of the epithelium. To model this relationship of disease severity to spatial distribution of abnormalities, we propose a network pipeline, DeepCIN, to analyze high-resolution epithelium images (manually extracted from whole-slide images) hierarchically by focusing on localized vertical regions and fusing this local information for determining Normal/CIN classification. The pipeline contains two classifier networks: 1) a cross-sectional, vertical segment-level sequence generator (two-stage encoder model) is trained using weak supervision to generate feature sequences from the vertical segments to preserve the bottom-to-top feature relationships in the epithelium image data; 2) an attention-based fusion network image-level classifier predicting the final CIN grade by merging vertical segment sequences. The model produces the CIN classification results and also determines the vertical segment contributions to CIN grade prediction. Experiments show that DeepCIN achieves pathologist-level CIN classification accuracy.
Primes of the form $X^{3} + NY^{3}$ and a family of non-singular plane curves which violate the local-global principle

Let $n$ be an integer such that $n = 5$ or $n \geq 7$. In this article, we introduce a recipe for a certain infinite family of non-singular plane curves of degree $n$ which violate the local-global principle. Moreover, each family contains infinitely many members which are not geometrically isomorphic to each other. Our construction is based on two arithmetic objects; that is, prime numbers of the form $X^{3}+NY^{3}$ due to Heath-Brown and Moroz and the Fermat type equation of the form $x^{3}+Ny^{3} = Lz^{n}$, where $N$ and $L$ are suitably chosen integers. In this sense, our construction is an extension of the family of odd degree $n$ which was previously found by Shimizu and the author. The previous construction works only if the given degree $n$ has a prime divisor which satisfies a certain indivisibility conjecture of Ankeny-Artin-Chowla-Mordell type. In this time, we focus on the complementary cases, namely the cases of even degrees and exceptional odd degrees. Consequently, our recipe works well as a whole. This means that we can unconditionally obtain infinitely many non-singular plane curves of every degree $n = 5$ or $n \geq 7$ which violate the local-global principle. This gives a conclusion of the classical story of searching explicit ternary forms violating the local-global principle, which was originated by Selmer (1951) and extended by Fujiwara (1972) and others.
The different flavors of extragalactic jets: The role of relativistic flow deceleration

We perform three-dimensional numerical simulations of relativistic (with a Lorentz factor of 10), non-magnetized jets propagating in a uniform density environment in order to study the effect of the entrainment and the consequent deceleration. Our simulations investigate the jet propagation inside the galaxy core, where the deceleration most likely occurs more efficiently. We compare cases with different density and pressure ratios with respect to the ambient medium and find that low density jets are efficiently decelerated and reach a quasi-steady state in which, over a length of 600 jet radii, they slow down from highly relativistic to sub-relativistic velocities. Conversely, denser jets keep highly relativistic velocities over the same length. We discuss these results in relation to the Faranoff Riley (FR) radio source classification. We infer that lower density jets can give rise to FR 0 and FR I radio sources, while higher density jets may be connected to FR II radio sources.
Rethinking CNN Models for Audio Classification

In this paper, we show that ImageNet-Pretrained standard deep CNN models can be used as strong baseline networks for audio classification. Even though there is a significant difference between audio Spectrogram and standard ImageNet image samples, transfer learning assumptions still hold firmly. To understand what enables the ImageNet pretrained models to learn useful audio representations, we systematically study how much of pretrained weights is useful for learning spectrograms. We show (1) that for a given standard model using pretrained weights is better than using randomly initialized weights (2) qualitative results of what the CNNs learn from the spectrograms by visualizing the gradients. Besides, we show that even though we use the pretrained model weights for initialization, there is variance in performance in various output runs of the same model. This variance in performance is due to the random initialization of linear classification layer and random mini-batch orderings in multiple runs. This brings significant diversity to build stronger ensemble models with an overall improvement in accuracy. An ensemble of ImageNet pretrained DenseNet achieves 92.89% validation accuracy on the ESC-50 dataset and 87.42% validation accuracy on the UrbanSound8K dataset which is the current state-of-the-art on both of these datasets.
Effect of particle inertia on the alignment of small ice crystals in turbulent clouds

Small non-spherical particles settling in a quiescent fluid tend to orient so that their broad side faces down, because this is a stable fixed point of their angular dynamics at small particle Reynolds number. Turbulence randomises the orientations to some extent, and this affects the reflection patterns of polarised light from turbulent clouds containing ice crystals. An overdamped theory predicts that turbulence-induced fluctuations of the orientation are very small when the settling number Sv (a dimensionless measure of the settling speed) is large. At small Sv, by contrast, the overdamped theory predicts that turbulence randomises the orientations. This overdamped theory neglects the effect of particle inertia. Therefore we consider here how particle inertia affects the orientation of small crystals settling in turbulent air. We find that it can significantly increase the orientation variance, even when the Stokes number St (a dimensionless measure of particle inertia) is quite small. We identify different asymptotic parameter regimes where the tilt-angle variance is proportional to different inverse powers of Sv. Parameter values for ice crystals in turbulent clouds lie near the boundaries between these regions; ice crystal-alignment in such clouds is thus unlikely to follow a simple power law. The theory predicts how the degree of alignment depends on particle size, shape, and turbulence intensity.
Maximum Likelihood Estimation of a Likelihood Ratio Ordered Family of Distributions

We consider bivariate observations $(X_1,Y_1), \ldots, (X_n,Y_n)\subset \mathfrak{X}\times\mathbb{R}$ with a real set $\mathfrak{X}$ such that, conditional on the $X_i$, the $Y_i$ are independent random variables with distribution $P_{X_i}$, where $(P_x)_{x\in\mathfrak{X}}$ is unknown. Using an empirical likelihood approach, we devise an algorithm to estimate the unknown family of distributions $(P_x)_{x\in\mathfrak{X}}$ under the sole assumption that this family is increasing with respect to likelihood ratio order. We review the latter concept and realize that no further assumption such as all distributions $P_x$ having densities or having a common countable support is needed. The benefit of the stronger regularization imposed by likelihood ratio ordering over the usual stochastic ordering is evaluated in terms of estimation and predictive performances on simulated as well as real data.
Active and resting metabolism in birds: allometry, phylogeny and ecology

Variation in resting metabolic rate is strongly correlated with differences in body weight among birds. The lowest taxonomic level at which most of the variance in resting metabolic rate and body weight is evident for the sample is among families within orders. The allometric exponent across family points is 0.67. This exponent accords with the surface area interpretation of metabolic scaling based on considerations of heat loss. Deviations of family points from this allometric line are used to examine how resting metabolic rates differ among taxa, and whether variation in resting metabolic rate is correlated with broad differences in ecology and behaviour. Despite the strong correlation between resting metabolic rate and body weight, there is evidence for adaptive departures from the allometric line, and possible selective forces are discussed. The allometric scaling of active metabolic rate is compared with that of resting metabolic rate. The allometric exponents for the two levels of energy expenditure differ, demonstrating that active small-bodied birds require proportionately more energy per unit time above resting levels than do active large-bodied birds. No consistent evidence was found to indicate that the different methods used to estimate active metabolic rate result in systematic bias. Birds require more energy relative to body size when undertaking breeding activities than at other stages of the annual cycle.
DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration

This work addresses the problem of point cloud registration using deep neural networks. We propose an approach to predict the alignment between two point clouds with overlapping data content, but displaced origins. Such point clouds originate, for example, from consecutive measurements of a LiDAR mounted on a moving platform. The main difficulty in deep registration of raw point clouds is the fusion of template and source point cloud. Our proposed architecture applies flow embedding to tackle this problem, which generates features that describe the motion of each template point. These features are then used to predict the alignment in an end-to-end fashion without extracting explicit point correspondences between both input clouds. We rely on the KITTI odometry and ModelNet40 datasets for evaluating our method on various point distributions. Our approach achieves state-of-the-art accuracy and the lowest run-time of the compared methods.
Regulatory Properties of Phosphoenolpyruvate Carboxylase in Crassulacean Acid Metabolism Plants: Diurnal Changes in Phosphorylation State and Regulation of Gene Expression

Abstract Regulatory properties of Phosphoenolpyruvate carboxylase (PEPC, EC 4.1.1.31) in three CAM species, Kalanchoë pinnata, K. daigremontiana and Ananas comosus (pineapple) were examined. PEPC activity in the leaves of the three CAM species exhibited diurnal changes peaking during the first 2-h of darkness in Kalanchoë species and at midnight in pineapple, and then decreasing drastically until dawn. The oscillations of PEPC activity were far greater in Kalanchoë species than in pineapple. In the presence of 2 mM malate, the activity of PEPC decreased in all three CAM species, but the sensitivity of PEPC to malate was markedly different between pineapple and the Kalanchoë species. The malate sensitivity was 2- to 3-times higher in pineapple than in the Kalanchoë species during the dark period, but it was almost the same during the light period. PEPC in the three CAM species was phosphorylated only during the dark period. PEPC proteins were highly phosphorylated during the first 2-h of darkness in Kalanchoë species and at midnight in pineapple, and then they decreased drastically during the latter part of darkness. CAM-specific isoforms of PEPC in the leaves of the three CAM species contained a highly conserved phosphorylation site of Ser-11 at the N-terminus. These PEPC isoforms displayed diurnal changes in transcript abundance, with the peak of transcripts occurring during the dark period. The day/night changes in PEPC transcript abundance were mirrored by changes in the PEPC protein and corresponding enzyme activity over the diurnal cycle. These findings suggest that the diurnal regulation in PEPC activity is determined by the amount of PEPC protein as well as the posttranslational control in these CAM species.
The Interplay between Star Formation and Black Hole Accretion in Nearby Active Galaxies

Black hole accretion is widely thought to influence star formation in galaxies, but the empirical evidence for a physical correlation between star formation rate (SFR) and the properties of active galactic nuclei (AGNs) remain highly controversial. We take advantage of a recently developed SFR estimator based on the [O ii] λ3727 and [O iii] λ5007 emission lines to investigate the SFRs of the host galaxies of more than 5800 type-1 and 7600 type-2 AGNs with z < 0.35. After matching in luminosity and redshift, we find that type-1 and type-2 AGNs have a similar distribution of internal reddening, which is significant and corresponds to ∼109 M⊙ of cold molecular gas. In spite of their comparable gas content, type-2 AGNs, independent of stellar mass, Eddington ratio, redshift or molecular gas mass, exhibit intrinsically stronger star formation activity than type-1 AGNs, in apparent disagreement with the conventional AGN unified model. We observe a tight, linear relation between AGN luminosity (accretion rate) and SFR, one that becomes more significant toward smaller physical scales, suggesting that the link between the AGN and star formation occurs in the central kpc-scale region. This, along with a correlation between SFR and Eddington ratio in the regime of super-Eddington accretion, can be interpreted as evidence that star formation is impacted by positive feedback from the AGN.
The inner gas mass–temperature profile in the core of nearby galaxy clusters

We present a mass–temperature profile of gas within the central 10 kpc of a small sample of cool core clusters. The mass of the hottest gas phases, at 1.5 and 0.7 keV, is determined from X-ray spectra from the XMM Reflection Grating Spectrometers. The masses of the partially ionized atomic and the molecular phases are obtained from published H α and CO measurements. We find that the mass of gas at 0.7 keV in a cluster is remarkably similar to that of the molecular gas. Assuming pressure equilibrium between the phases, this means that they occupy volumes differing by 105. The molecular gas is located within the H α nebula which is often filamentary and coincides radially and in position angle with the soft X-ray emitting gas.
Transforming growth factor- 1 downregulation of Smad1 gene expression in rat hepatic stellate cells

Shen, Hong, Guojiang Huang, Mohammed Hadi, Patrick Choy, Manna Zhang, Gerald Y. Minuk, Yongping Chen, and Yuewen Gong. Transforming growth factor1 downregulation of Smad1 gene expression in rat hepatic stellate cells. Am J Physiol Gastrointest Liver Physiol 285: G539–G546, 2003. First published June 4, 2003; 10.1152/ajpgi.00436. 2002. —Smads are intracellular signaling molecules of the transforming growth factor(TGF) superfamily that play an important role in the activation of hepatic stellate cells (HSCs) and hepatic fibrosis. Excepting the regulation of Smad7, receptor-regulated Smad gene expression is still unclear. We employed rat HSCs to investigate the expression and regulation of the Smad1 gene, which is a bone morphogenetic protein (BMP) receptor-regulated Smad. We found that the expression and phosphorylation of Smad1 are increased during the activation of HSCs. Moreover, TGFsignificantly inhibits Smad1 gene expression in HSCs in a timeand dose-dependent manner. Furthermore, although both TGF1 and BMP2 stimulate the activation of HSCs, they have different effects on HSC proliferation. In conclusion, Smad1 expression and phosphorylation are increased during the activation of HSCs and TGF1 significantly inhibits the expression of the Smad1 gene.
Correlation of ultrasound placental diameter & thickness with gestational age

Background & Objectives: Estimation of fetal maturity is common in obstetric practice especially when the women do not keep accurate menstrual records. An accurate establishment of expected date of delivery is fundamental to the management of both high risk and normal pregnancies. The objective of this study was to determine the placental diameter (PD), placental thickness (PT) and to establish a correlation between PD, PT and gestational age. Methods: This is an observational cross-sectional study that examines by means of ultrasonography the correlation between placental diameter and thickness with gestational age in Enugu, South East, Nigeria. Results: A total of 400 healthy subjects were recruited in 3rd trimester of pregnancy having fulfilled the inclusion criteria. PD and PT in this study did not correlate with parity. There is a linear increase of gestational age and placental thickness and diameter. These increases heighten between 38th week gestation and 40 weeks’ gestation. 205.0±1.4, 43.00±0.0 to 215.0±1.4, 46.00±2.8 respectively. Conclusion: Placental thickness and Placental diameter can be used to predict gestational age. It is therefore advised to use PT & PD in ultrasound obstetric assessment especially when Last menstrual period (LMP) is not clear.
Geodesic motion of S2 and G2 as a test of the fermionic dark matter nature of our Galactic core

The motion of S-stars around the Galactic center implies that the central gravitational potential is dominated by a compact source, Sagittarius A* (Sgr A*), which has a mass of about 4 × 106 M⊙ and is traditionally assumed to be a massive black hole (BH). The explanation of the multiyear accurate astrometric data of the S2 star around Sgr A*, including the relativistic redshift that has recently been verified, is particularly important for this hypothesis and for any alternative model. Another relevant object is G2, whose most recent observational data challenge the scenario of a massive BH: its post-pericenter radial velocity is lower than expected from a Keplerian orbit around the putative massive BH. This scenario has traditionally been reconciled by introducing a drag force on G2 by an accretion flow. As an alternative to the central BH scenario, we here demonstrate that the observed motion of both S2 and G2 is explained in terms of the dense core – diluted halo fermionic dark matter (DM) profile, obtained from the fully relativistic Ruffini-Argüelles-Rueda (RAR) model. It has previously been shown that for fermion masses 48−345 keV, the RAR-DM profile accurately fits the rotation curves of the Milky Way halo. We here show that the solely gravitational potential of such a DM profile for a fermion mass of 56 keV explains (1) all the available time-dependent data of the position (orbit) and line-of-sight radial velocity (redshift function z) of S2, (2) the combination of the special and general relativistic redshift measured for S2, (3) the currently available data on the orbit and z of G2, and (4) its post-pericenter passage deceleration without introducing a drag force. For both objects, we find that the RAR model fits the data better than the BH scenario: the mean of reduced chi-squares of the time-dependent orbit and z data are ⟨χ̄2⟩S2,RAR ≈ 3.1 and ⟨χ̄2⟩S2,BH ≈ 3.3 for S2 and ⟨χ̄2⟩G2,RAR ≈ 20 and ⟨χ̄2⟩G2,BH ≈ 41 for G2. The fit of the corresponding z data shows that while for S2 we find comparable fits, that is, χ̄2z,RAR ≈ 1.28 and χ̄2z,BH ≈ 1.04, for G2 the RAR model alone can produce an excellent fit of the data, that is, χ̄2z,RAR ≈ 1.0 and χ̄2z,BH ≈ 26. In addition, the critical mass for gravitational collapse of a degenerate 56 keV-fermion DM core into a BH is ∼ 108 M⊙. This result may provide the initial seed for the formation of the observed central supermassive BH in active galaxies, such as M 87.