Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of analytical and experimental results of ductility factor in reinforced concrete structures

In seismic areas, ductility is an important factor in design of concrete members under flexure; it is due to the increase in capacity of plastic displacement. As a result, the inertial forces imposed on the structures can be decreased. The effective factors on ductility are; concrete compression strength f′c, the percentage of tension and compression steel, ρ and ρ′, the amount of stirrups confinement for concrete ρc , the stirrups spacing, brittle effect of concrete strength, yield stress of longitudinal bars fy and the effect of width to the depth of the section b/h. Perhaps the most simple and general definition for section ductility of members is defined, as the ratio of curvatures at ultimate load to curvatures at yield load (μ=φu/φy). In this paper, a proposed method was considered to calculate the flexural curvature ductility ratio of reinforced concrete (RC) sections. Based on the proposed method, computer software was produced to calculate the curvature ductility in confined RC beams. The method is based on actual characteristics of a concrete flexural section by considering almost all effective ductility parameters such as available experimental concrete compression diagrams. By the developed software, the ductility factor of 250 beams under efficient circumstances were investigated completely. The nonlinear multiple regression analyses were also performed for these 250 beams and a direct equation is introduced to determine the ductility factor. Based on the obtained experimental results a comparison was made between the proposed direct method and experimental results, and it was shown that a good agreement is available. [Hamid Reza Ashrafi, Hossein Behsan and Neda esmaeili. Comparison of analytical and experimental results of ductility factor in reinforced concrete structures. Life Sci J 2012;9(4):2721-2734]. (ISSN: 1097-8135). http://www.lifesciencesite. com. 401
Granitoid rocks in the Lynn Lake region, northwestern Manitoba: preliminary results of reconnaissance mapping and sampling

Manitoba Geological Survey Summary In 2015, the Manitoba Geological Survey continued its project to investigate the petrogenesis and metallogeny of granitoid rocks throughout Manitoba. Initiated the spring of 2014, the main objectives of this project are to identify the various petrogenetic types of granitoid rocks in Manitoba and to investigate their geodynamic settings and mineralization potential. This report presents the preliminary results of fieldwork conducted in the Lynn Lake region. Granitoid rocks were examined and sampled to document field relationships, textures (fabrics), mineral assemblages, magnetic susceptibilities (MS), and presence of mineralization and/or alteration. This study indicates that muscoviteand/or garnetbearing granitic rocks characterized by low MS values (<0.1 × 10-3 SI units; i.e., strongly peraluminous S type, or ilmenite series) were intruded mainly into domain boundaries, which may thus serve as a useful criterion for recognizing major tectonic or domain boundaries. These peraluminous granitic rocks may have formed in crust thickened as a result of terrane assembly and/or continental collision, and may have potential to host rare-metal and (or) Sn-W mineralization. In contrast, plutons consisting of quartz diorite, tonalite, granodiorite and granite are characterized by higher MS values (>0.1 × 10-3 SI units) and mineral assemblages typical of I-type granitoid rocks (e.g., amphibole±biotite or biotite±amphibole). Such plutons are abundant across the region, suggesting that this magmatism contributed significantly to crustal growth in the Trans-Hudson orogen, and may have been related to subduction tectonics. It is worth noting that I-type or magnetite-series granitoid intrusions may have potential to host porphyry Cu, Au and Mo mineralization. In addition, subordinate A-type granitoid plutons in the region, characterized by relatively oxidized features (e.g., MS >0.5 × 10-3 SI units) and by the presence of sodic amphibole (±sodic pyroxene), likely emplaced in extensional settings, have potential for rare-metal (e.g., Nb, Ta) mineralization.
Feedback Medicine: Working Notes on Control Systems Concepts in Personalised, Predictive Medicine and Combinatorial Intervention

In its broadest definition, systems biology is the application of a ‘systems’ way of thinking about and doing cell biology [1]. By implication, this also invites us to consider a systems approach in the context of medicine and the treatment of disease. In particular, the idea that systems biology can form the basis of a personalised, predictive medicine [2, 3] will require that much closer attention is paid to the analytic properties of the feedback loops which will be set up by a personalised approach to healthcare. To emphasize the role that feedback theory will play in understanding personalised medicine, we use the term feedback medicine to describe the issues outlined in these working notes. More generally and beyond the personalised medicine debate, we advocate this ‘systems’ approach be extended to medicine as an important ingredient in future bio-medical research. In this context, and in our interpretation, the systems approach pays close attention to:
Does selection bias cause us to overestimate gender differences in competitiveness?

Experimental evidence suggests there is a substantial difference in the willingness of men and women to compete that could help explain the gender gap in labor market outcomes. The use of volunteer samples, however, raises a question about whether self-selection into experiments biases the estimated difference in competitiveness. To address it, we first measure the willingness of 1,145 individuals to compete in a classroom experiment. We then identify among them the subset of ‘lab volunteers’ by observing who accepts an invitation to participate in lab experiments. To test for the existence of selection bias, we compare the gender gap among lab volunteers to that in the population from which they were recruited. We find that selection causes us to overestimate the gender gap in competitiveness by 16 percentage points in absolute terms and, in relative terms, by a factor of 2 to 3 depending on the econometric model. We also show that selection causes us to significantly overestimate the gender gap in risk attitudes and the tendency of lowperforming men to select into competition. We present evidence men and women select differently into the lab, and discuss the implications of our findings for future research.
EFFECT OF ASCORBIC ACID AND/OR ALPHA-TOCOPHEROL FORTIFICATION ON SEMEN QUALITY, METABOLIC PROFILE, ANTIOXIDANTS STATUS, AND DNA OF ROOSTERS EXPOSED TO HEAT STRESS

This study investigates the influence of heat stress (HS) and vitamin C (VC) and/or vitamin E (VE) on semen quality, biochemical constituents of seminal and blood plasma, antioxidant status and jejunum and ilium deoxyribonucleic acid (DNA) of roosters. Forty-five, 32-week-old roosters were divided into five groups of nine replicates. One group was kept under a thermoneutral environment, whereas the other four were kept under HS. One of the four groups served as an unsupplemented HS group and was fed the basal diet only. The other three HS groups were supplemented with VC (200 mg/kg ascorbic acid and/or VE 150 mg/kg α-tocopherol acetate). Vitamins fortification completely restored sperm liveability , semen pH, fertility, seminal plasma total protein and globulin to the control level. Vitamins fortification completely recovered seminal plasma and blood plasma total antioxidant capacity (TAC) and malondialdehyde (MDA), red blood cell (RBCs), haemoglobin (Hgb), packed cell volume (PCV), white blood cells (WBCs), blood plasma glucose, lipid profiles, liver enzymes, and renal function. Heterophil/lymphocyte (H/L) ratio was totally restored following VE fortification. Vitamins fortification significantly increased jejunum and ileum DNA compared with the HS group, with VC inducing a complete recovery. In conclusion, either 200 mg /kg VC or 150 mg/kg VE improved semen quality, fertility, seminal plasma and blood biochemistry and haematology of HS roosters, with the VE group yielding
FREDERIK LELIAERT* and ERIC COPPEJANS

Two rare and ill-known subtidal species of stalked, net-forming green algae, Struvea gardineri A.Gepp & E.Gepp and Phyllodictyon orientale (A.Gepp & E.Gepp) Kraft & M.J.Wynne, are re-described on the basis of the examination of type material and recent collections from the Maldives, Seychelles, and Socotra Island in the tropical Indian Ocean. The taxonomic position of both species is re-appraised on the basis of morphological data (cell division, branching pattern, tenacular cells, crystalline cell inclusions, cell shape, and cell dimensions) and molecular phylogenetic evidence (partial large subunit nuclear ribosomal DNA sequences). On the basis of the occurrence of segregative cell division in young plants of S. gardineri , this species is returned to its original genus, Struvea . Cell division in P. orientale takes place exclusively by centripetal wall ingrowths, confirming its placement in the genus Phyllodictyon as currently defined. However, morphological observations and molecular phylogenetic studies indicate that the delineation of genera on the basis of modes of cell division is problematic, and that the genera Struvea and Phyllodictyon , as presently conceived, almost certainly do not represent natural groups. © 2007 The Linnean Society of London, Botanical Journal of the Linnean Society , 2007, 153 , 115–132.
The Influence of Transformational Leadership, Organizational Culture, and Organizational Citizenship Behavior on Job Performance

This study aimed to study: 1) the influence of transformational leadership, organizational culture, and organizational citizenship behavior on job performance and 2) develop the model and test by using structural equation modelling. The samples were 560 staffs of seven higher education institutions in the North-Eastern. The instrument was questionnaire. Data were analyzed by descriptive statistics and structural equation modelling (SEM). The result indicated a high average mean in each component, were inspirational leadership, adaptation culture, sportsmanship and quality. Organizational culture had mostly direct effect organizational citizenship behavior and job performance respectively. While transformational leadership had direct effect organizational citizenship behavior. Meanwhile organizational culture had mostly total effect job performance through organizational citizenship behavior, and transformational leadership had total effect job performance through organizational citizenship behavior. Furthermore job performance had relationship among transformational leadership, organizational culture and organizational citizenship
Network Embeddedness and Content Sharing on Social Media Platforms

We study the impact of network embeddedness – the overlap in network neighbors between two users – on content sharing in directed social media platforms. We propose a hazard model that flexibly captures the impact of three different measures of embeddedness on content sharing and apply it individual-level data from Digg. Our results indicate that all three measures of embeddedness have an impact on the amount of content sharing. Specifically, a receiver is more likely to share content from a sender if they share more common followees, common followers or common mutual followers after accounting for the other measures. Additionally, the effect of common followers and common mutual followers is positive when the content is novel but decreases and may become negative when many others in the network have already adopted it. Our findings are managerially relevant for targeting customers for content propagation in social networks.
Chaotic-Like Transfers of Energy in Hamiltonian PDEs

We consider the nonlinear cubic Wave, the Hartree and the nonlinear cubic Beam equations on T2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathbb {T}}^2$$\end{document} and we prove the existence of different types of solutions which exchange energy between Fourier modes in certain time scales. This exchange can be considered “chaotic-like” since either the choice of activated modes or the time spent in each transfer can be chosen randomly. The key point of the construction of those orbits is the existence of heteroclinic connections between invariant objects and the construction of symbolic dynamics (a Smale horseshoe) for the Birkhoff Normal Form truncation of those equations.
Directional Pruning of Deep Neural Networks

In the light of the fact that the stochastic gradient descent (SGD) often finds a flat minimum valley in the training loss, we propose a novel directional pruning method which searches for a sparse minimizer in that flat region. The proposed pruning method is automatic in the sense that neither retraining nor expert knowledge is required. To overcome the computational formidability of estimating the flat directions, we propose to use a carefully tuned $\ell_1$ proximal gradient algorithm which can provably achieve the directional pruning with a small learning rate after sufficient training. The empirical results show that our algorithm performs competitively in highly sparse regime (92\% sparsity) among many existing automatic pruning methods on the ResNet50 with the ImageNet, while using only a slightly higher wall time and memory footprint than the SGD. Using the VGG16 and the wide ResNet 28x10 on the CIFAR-10 and CIFAR-100, we demonstrate that our algorithm reaches the same minima valley as the SGD, and the minima found by our algorithm and the SGD do not deviate in directions that impact the training loss.
Global Feature Aggregation for Accident Anticipation

Anticipation of accidents ahead of time in autonomous and non -autonomous vehicles aids in accident avoidance. In order to recognize abnormal events such as traffic accidents in a video sequence, it is important that the network takes into account interactions of objects in a given frame. We propose a novel Feature Aggregation (FA) block that refines each object's features by computing a weighted sum of the features of all objects in a frame. We use FA block along with Long Short Term Memory (LSTM) network to anticipate accidents in the video sequences. We report mean Average Precision (mAP) and Average Time-to-Accident (ATTA) on Street Accident (SA) dataset. Our proposed method achieves the highest score for risk anticipation by predicting accidents 0.32 sec and 0.75 sec earlier compared to the best results with Adaptive Loss and dynamic parameter prediction based methods respectively.
Density of States Estimation for Out-of-Distribution Detection

Perhaps surprisingly, recent studies have shown probabilistic model likelihoods have poor specificity for out-of-distribution (OOD) detection and often assign higher likelihoods to OOD data than in-distribution data. To ameliorate this issue we propose DoSE, the density of states estimator. Drawing on the statistical physics notion of ``density of states,'' the DoSE decision rule avoids direct comparison of model probabilities, and instead utilizes the ``probability of the model probability,'' or indeed the frequency of any reasonable statistic. The frequency is calculated using nonparametric density estimators (e.g., KDE and one-class SVM) which measure the typicality of various model statistics given the training data and from which we can flag test points with low typicality as anomalous. Unlike many other methods, DoSE requires neither labeled data nor OOD examples. DoSE is modular and can be trivially applied to any existing, trained model. We demonstrate DoSE's state-of-the-art performance against other unsupervised OOD detectors on previously established ``hard'' benchmarks.
The Milky Way Cepheid Leavitt law based on Gaia DR2 parallaxes of companion stars and host open cluster populations

Aims. Classical Cepheids provide the foundation for the empirical extragalactic distance ladder. Milky Way Cepheids are the only stars in this class accessible to trigonometric parallax measurements. However, the parallaxes of Cepheids from the second Gaia data release (GDR2) are affected by systematics because of the absence of chromaticity correction, and occasionally by saturation. Methods. As a proxy for the parallaxes of 36 Galactic Cepheids, we adopt either the GDR2 parallaxes of their spatially resolved companions or the GDR2 parallax of their host open cluster. This novel approach allows us to bypass the systematics on the GDR2 Cepheids parallaxes that is induced by saturation and variability. We adopt a GDR2 parallax zero-point (ZP) of −0.046 mas with an uncertainty of 0.015 mas that covers most of the recent estimates. Results. We present new Galactic calibrations of the Leavitt law in the V, J, H, KS, and Wesenheit WH bands. We compare our results with previous calibrations based on non-Gaia measurements and compute a revised value for the Hubble constant anchored to Milky Way Cepheids. Conclusions. From an initial Hubble constant of 76.18 ± 2.37 km s−1 Mpc−1 based on parallax measurements without Gaia, we derive a revised value by adopting companion and average cluster parallaxes in place of direct Cepheid parallaxes, and we find H0 = 72.8 ± 1.9 (statistical + systematics) ±1.9 (ZP) km s−1 Mpc−1 when all Cepheids are considered and H0 = 73.0 ± 1.9 (statistical + systematics) ±1.9 (ZP) km s−1 Mpc−1 for fundamental mode pulsators only.
Arp 220: New Observational Insights into the Structure and Kinematics of the Nuclear Molecular Disks and Surrounding Gas

ALMA cycle 3 observations of 12CO J = 3 → 2, 13CO J = 4 → 3, SiO J = 8 → 7, and HCN J = 5 → 4 are presented. Significant extended emission is detected in 12CO J = 3 → 2 with a morphology that is indicative of m = 2 tidal features, suggesting gas inflow. In addition, outflows for both nuclei are found in 12CO J = 3 → 2. Significant SiO absorption is detected in the western nucleus. HCN that is morphologically distinct from CO is detected in both nuclei. These observations are compared to non-LTE radiative transfer models created using the Line Modeling Engine for simple gas dynamics to gain insight into how physical parameters, such as rotational velocity, turbulent velocity, gas temperature, dust temperature, and gas mass, can reproduce the observed kinematic and spatial features. The eastern nucleus is found to be best modeled with an inclusion of a temperature asymmetry from one side of the disk to the other. It is also found that the western nucleus is optically thick even in the less abundant species of 13CO, absorbing significant amounts of continuum radiation.
The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks

Generative Adversarial Networks (GANs) are performant generative methods yielding high-quality samples. However, under certain circumstances, the training of GANs can lead to mode collapse or mode dropping, i.e. the generative models not being able to sample from the entire probability distribution. To address this problem, we use the last layer of the discriminator as a feature map to study the distribution of the real and the fake data. During training, we propose to match the real batch diversity to the fake batch diversity by using the Bures distance between covariance matrices in feature space. The computation of the Bures distance can be conveniently done in either feature space or kernel space in terms of the covariance and kernel matrix respectively. We observe that diversity matching reduces mode collapse substantially and has a positive effect on the sample quality. On the practical side, a very simple training procedure, that does not require additional hyperparameter tuning, is proposed and assessed on several datasets.
A New Perspective on Uncertainty Quantification of Deep Ensembles

We present a novel perspective on uncertainty quantification in deep learning, based on the bias-variance decomposition of ensembles. We argue that the existing uncertainty estimation methods are suboptimal in estimating the prediction error of an ensemble, and propose a new two-stage procedure instead, where in the first stage we estimate the unknown function using an ensemble, and in the second stage we fit a separate neural net to the errors of the first model. We argue that this has several advantages, among which better control over regularization such as early stopping, and a more accurate approximation to the aleatoric uncertainty. We extensively test our method on both synthetic as well as real world MRI data, and find that our method significantly improves uncertainty estimates compared to various alternatives such as dropout and deep ensemble based methods.
The Mass–Size Relation and the Constancy of GMC Surface Densities in the Milky Way

We use two existing molecular cloud catalogs derived from the same CO survey and two catalogs derived from local dust extinction surveys to investigate the nature of the giant molecular cloud (GMC) mass–size relation in the Galaxy. We find that the four surveys are well described by MGMC ∼ R2, implying a constant mean surface density, , for the cataloged clouds. However, the scaling coefficients and scatter differ significantly between the CO- and extinction-derived relations. We find that the additional scatter seen in the CO relations is due to a systematic variation in with Galactic radius that is unobservable in the local extinction data. We decompose this radial variation of into two components, a linear negative gradient with Galactic radius and a broad peak coincident with the molecular ring and superposed on the linear gradient. We show that the former may be due to a radial dependence of XCO on metallicity, while the latter likely results from a combination of increased surface densities of individual GMCs and a systematic upward bias in the measurements of due to cloud blending in the molecular ring. We attribute the difference in scaling coefficients between the CO and extinction data to an underestimate of XCO. We recalibrate the CO observations of nearby GMCs using extinction measurements to find that locally XCO = 3.6 ± 0.3 × 1020 cm−2 (K km s−1)−1. We conclude that outside the molecular ring, the GMC population of the Galaxy can be described to relatively good precision by a constant of 35 pc−2.
Measuring the surface mass density ellipticity of redMaPPer galaxy clusters using weak lensing

In this work we study the shape of the projected surface mass density distribution of galaxy clusters using weak-lensing stacking techniques. In particular, we constrain the average aligned component of the projected ellipticity, $\epsilon$, for a sample of redMaPPer clusters ($0.1 \leq z < 0.4$). We consider six different proxies for the cluster orientation and measure $\epsilon$ for three ranges of projected distances from the cluster centres. The mass distribution in the inner region (up to $700\,$kpc) is better traced by the cluster galaxies with a higher membership probability, while the outer region (from $700\,$kpc up to $5\,$Mpc) is better traced by the inclusion of less probable galaxy cluster members. The fitted ellipticity in the inner region is $\epsilon = 0.21 \pm 0.04$, in agreement with previous estimates. We also study the relation between $\epsilon$ and the cluster mean redshift and richness. By splitting the sample in two redshift ranges according to the median redshift, we obtain larger $\epsilon$ values for clusters at higher redshifts, consistent with the expectation from simulations. In addition, we obtain higher ellipticity values in the outer region of clusters at low redshifts. We discuss several systematic effects that might affect the measured lensing ellipticities and their relation to the derived ellipticity of the mass distribution.