Miracle-dz/UniFAR-FTUs huggingface dataset:
24andmore: Using genome-wide SNPS to investigate the genetic diversity of Iowa walleye (Sander vitreous) broodstock

The stocking of Sander vitreus in Iowa waterbodies is one of the primary tools used by the Iowa Department of Natural Resources (DNR) to ensure healthy populations for enjoyable fishing experiences. A substantial amount of time and money goes into this effort, so stocking efficiency is vital. Knowledge of genetic diversity contained in the broodstock increases this efficiency by having a better understanding of which strain will survive and contribute to the fishery in certain environments. The objective of this study is to investigate the genetic diversity of Iowa S. vitreus broodstock to identify genetic ancestry and quantify the genetic diversity of each strain contained in the broodstock. From this information, the creation of a strain-specific identification marker was explored. Rathbun Fish Hatchery’s captive walleye broodstock contains two genetic strains: the lake-strain and the river-strain. Sampling of the 2019 captive broodstock at the Rathbun Fish Hatchery in Moravia, IA was conducted to genotype individuals and generate genome-wide single nucleotide polymorphism (SNP) datasets. Three datasets were generated; one to infer genetic variation between strain, the combined LR dataset, and two to infer genetic variation within strain, lake-only and river-only datasets. In total, 69 individuals were sampled and 11,764 SNPs were analyzed for the combined LR dataset. The datasets demonstrated the ability to detect fine-scale structure both between and within strains. The results of the analyses support a genetic differentiation between the two Iowa walleye strains; however, this variation is complex and subtle. Multiple genetic markers significantly associated with both lakeand river-strain were identified. The variation identified when the loci were compared between strains was not enough to differentiate the strains and, therefore, create a stock identification tool. Based on these results, a simple strain-identification tool is not recommended. Instead, genotyping and generating more SNP datasets would not only allow for the unknown samples to be evaluated alongside the known individuals of this study, revealing genetic strain, but also would give further insight into the ancestry of Iowa walleye by revealing admixture and wild types that were not included in the present broodstock individuals. 24ANDMORE: USING GENOME-WIDE SNPS TO INVESTIGATE THE GENETIC DIVERSITY OF IOWA WALLEYE (SANDER VITREUS) BROODSTOCK A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree
Half-integer Bessel beams

In this work we introduce an angular spectrum of plane waves representation for the paraxial wave equation (PWE) in circular cylindrical coordinates. We show that a family of exact solutions to the PWE depends on half-integer Bessel functions. We also show how such optical beams can be generated simply by diffraction. Numerical and experimental results are presented.
Meta-Learning 3D Shape Segmentation Functions

Learning robust 3D shape segmentation functions with deep neural networks has emerged as a powerful paradigm, offering promising performance in producing a consistent part segmentation of each 3D shape. Generalizing across 3D shape segmentation functions requires robust learning of priors over the respective function space and enables consistent part segmentation of shapes in presence of signiﬁcant 3D structure variations. Existing generalization methods rely on extensive training of 3D shape segmentation functions on large-scale labeled datasets. In this paper, we proposed to formalize the learning of a 3D shape segmentation function space as a meta-learning problem, aiming to predict a 3D segmentation model that can be quickly adapted to new shapes with no or limited training data. More speciﬁcally, we deﬁne each task as unsupervised learning of shape-conditioned 3D segmentation function which takes as input points in 3D space and predicts the part-segment labels. The 3D segmentation function is trained by a self-supervised 3D shape reconstruction loss without the need for part labels. Also, we introduce an auxiliary deep neural network as a meta-learner which takes as input a 3D shape and predicts the prior over the respective 3D segmentation function space. We show in experiments that our meta-learning approach, denoted as Meta-3DSeg, leads to improvements on unsupervised 3D shape segmentation over the conventional designs of deep neural networks for 3D shape segmentation functions.
The Task Force for the Diagnosis and Management of Acute Pulmonary Embolism of the European Society of Cardiology (ESC) Endorsed by the European Respiratory Society (ERS)

Authors/Task Force Members: Stavros V. Konstantinides* (Chairperson) (Germany/ Greece), Adam Torbicki* (Co-chairperson) (Poland), Giancarlo Agnelli (Italy), Nicolas Danchin (France), David Fitzmaurice (UK), Nazzareno Galiè (Italy), J. Simon R. Gibbs (UK), Menno V. Huisman (The Netherlands), Marc Humbert† (France), Nils Kucher (Switzerland), Irene Lang (Austria), MareikeLankeit (Germany), John Lekakis (Greece), Christoph Maack (Germany), Eckhard Mayer (Germany), Nicolas Meneveau (France), Arnaud Perrier (Switzerland), Piotr Pruszczyk (Poland), Lars H. Rasmussen (Denmark), Thomas H. Schindler (USA), Pavel Svitil (Czech Republic), Anton Vonk Noordegraaf (The Netherlands), Jose Luis Zamorano (Spain), Maurizio Zompatori (Italy)
Link based small sample learning for web spam detection

Robust statistical learning based web spam detection system often requires large amounts of labeled training data. However, labeled samples are more difficult, expensive and time consuming to obtain than unlabeled ones. This paper proposed link based semi-supervised learning algorithms to boost the performance of a classifier, which integrates the traditional Self-training with the topological dependency based link learning. The experiments with a few labeled samples on standard WEBSPAM-UK2006 benchmark showed that the algorithms are effective.
Fitting Statistical Models with Multiphase Mean Structures for Longitudinal Data

When measuring individuals over time, change is frequently curvilinear and residual errors are typically correlated. Two population-average and two subject-specific models with multiphase mean structures are proposed to model change over time and account for error correlations. In the Frequentist tradition, such models fall under the category of nonlinear and nonlinear mixed-effects models, respectively. The latter class becomes increasingly difficult to estimate with full information maximum likelihood (FIML) as the number of random effects increases. However, Bayesian multilevel models care little for the number of individually modeled parameters, as the mechanics of MCMC escape the numerical integration problems encountered by FIML. This thesis illustrates the differences between population-average and subject-specific models, highlights the advantages of multiphase mean structures, comments on issues regarding the estimation of such models, and presents general Bayesian formulations for population-average and subject-specific models with mutliphase mean structures for a real dataset.
Compared to placebo , long-term antibiotics resolve otitis media with effusion ( OME ) and prevent acute otitis media with perforation ( AOMwiP ) in a high-risk population : A randomized controlled trial

Background: For children at high risk of chronic suppurative otitis media (CSOM), strategies to prevent acute otitis media with perforation (AOMwiP) may reduce progression to CSOM. Methods: In a double blind study in northern Australia, 103 Aboriginal infants with first detection of OME were randomised to receive either amoxicillin (50 mg/kg/d BD) or placebo for 24 weeks, or until bilateral aerated middle ears were diagnosed at two successive monthly examinations (success). Standardised clinical assessments and international standards for microbiology were used. Results: Five of 52 infants in the amoxicillin group and none of 51 infants in the placebo group achieved success at the end of therapy (Risk Difference = 9.6% [95% confidence interval 1.6,17.6]). Amoxicillin significantly reduced the proportion of children with i) perforation at the end of therapy (27% to 12% RD = -16% [-31,-1]), ii) recurrent perforation during therapy (18% to 4% RD = -14% [-25,-2]), and iii) reduced the proportion of examinations with a diagnosis of perforation during therapy (20% to 8% adjusted risk ratio 0.36 [0.15,0.83] p = 0.017). During therapy, the proportion of examinations with penicillin non-susceptible (MIC > 0.1 microg/ml) pneumococci was not significantly different between the amoxicillin group (34%) and the placebo group (40%). Betalactamase positive non-capsular H. influenzae (NCHi) were uncommon during therapy but more frequent in the amoxicillin group (10%) than placebo (5%). Conclusion: Aboriginal infants receiving continuous amoxicillin had more normal ears, fewer perforations, and less pneumococcal carriage. There was no statistically significant increase in resistant pneumococci or NCHi in amoxicillin children compared to placebo children who received regular paediatric care and antibiotic treatment for symptomatic illnesses. Published: 2 June 2008 BMC Pediatrics 2008, 8:23 doi:10.1186/1471-2431-8-23 Received: 14 December 2007 Accepted: 2 June 2008 This article is available from: http://www.biomedcentral. com/1471-2431/8/23 © 2008 Leach et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Constrained robust model predictive control embedded with a new data‐driven technique

In the control field, the adaptive model predictive control (AMPC) has the capability of taking effective control actions on unknown-but-bounded time-independent or slowly time-varying systems coupling with constraints. In essence, AMPC estimates the uncertain parameters or uncertainty set online by utilising historian data to extract model information. The model estimation procedure imposes some specific conditions on data and these extra conditions have restricted its practical use. To overcome these problems, a new data-driven control methodology is presented that integrates the data-driven concept into robust model predictive control (RMPC) architecture for unknown-but-bounded time-independent or slowly time-varying plant. The key novelty is to employ historian data to derive control policy and make a prediction in replacement with the complicated procedure of utilising data to estimate model parameters. A data-driven RMPC algorithm is developed within the robust model predictive control framework with the fulfilment of recursive feasibility and stability. The authors display the highlights of the data-driven model predictive control controller through two simulation examples. The resulting controller is verified to reduce conservativeness and increase the closed-loop performance of the system.
Gap plasmonic effects of gold nanoparticles on metallic film

The effective confinement of light in a deep-subwavelength volume can be achieved in metallic nanostructures through the electronic resonance, surface plasmons (SPs). There are few ways to enhance the localization of the field such as adopting metallic nanopost or nanowire structures on the precious metallic film. The achieved highly enhanced field localization through SPs can be exploited for surface-enhanced spectroscopy, biosensor, enhancing energy emitter, and enhanced energy generator. Also, many researches have been tried with few-nanometer gap between the metals for achieving large field enhancements. In this paper, by comparing the scattering of gold nanoparticles, the effects of metallic film of substrates were investigated through simulation. In addition, as changing of the gap between gold nanoparticle and metallic surface, different resonance wavelengths were observed in scattering spectra from simulation and practical experiments. We confirmed that the gold film with gold nanoparticles shows the most distinctive scattering spectra. The numerical demonstration was matched with our experimental demonstration, also with the previously introduced papers as well.
Electron scattering channels in GaAs: A fully first-principles study of electron transport

We present a parameter-free first-principles framework for studying the electron transport in GaAs through the effect of electron-phonon interaction (EPI). Both the long-range and shortrange EPI are well addressed and found to have remarkable impacts on the electron transport properties. Our calculation results reveal significant differences from existing semi-empirical model in terms of scattering mechanisms and their energy dependence. Using iterative solution of the electron Boltzmann transport equation, we achieved excellent agreements with experimental data on mobility and identified that the electrons with mean free paths in the range of 130 to 160 nm contribute dominantly to the electron transport.
The Extremal Graphs of Some Topological Indices with Given Vertex k-Partiteness

The vertex k-partiteness of graph G is defined as the fewest number of vertices whose deletion from G yields a k-partite graph. In this paper, we characterize the extremal value of the reformulated first Zagreb index, the multiplicative-sum Zagreb index, the general Laplacian-energy-like invariant, the general zeroth-order Randić index, and the modified-Wiener index among graphs of order n with vertex k-partiteness not more than m .
Using External Galactic Forces as an Alternative to Dark Matter

It has been over 30 years since the first Cold Dark Matter (CDM) model was proposed as a way of describing Dark Matter, but as yet, there have been no experimental results that support CDM. CDM depends on the discovery of new non-baryonic particles not defined in the Standard Model as the source of the needed mass. Recently, final results from the Large Underground Xenon (LUX) dark matter experiment, have failed to find any traces of these non-baryonic particles, and the Large Hadron Collider (LHC) has not detected any strong evidence of supersymmetry particles. With the lack of supporting experimental results for CDM or supersymmetry, it is time to examine other solutions that might explain Dark Matter without requiring any new particles to be detected. The current concept of Dark Matter assumes the undiscovered particles add an additional gravitational mass to the galaxy. Another solution to the galaxy rotation problem would be to assume there is some external force pressing in on the galaxies holding them together. This research shows how external gravitational forces on the galaxies can duplicate the galaxy rotation curves that have been observed, without any Dark Matter. It also offers an explanation for the acceleration constant a0, that results from the modified Newtonian dynamics (MOND) theory of galaxy dynamics. The results show that a model using an external galactic force is a valid approach to explain the effect known as Dark Matter.
Multithreaded and Reconvergent Aware Algorithms for Accurate Digital Circuits Reliability Estimation

Until recently, reliability was not considered to be a major design concern for circuit designers, except in the case of space and mission critical applications. However, the aggressive scaling of CMOS devices has significantly affected their reliable operation. Several schemes have been used for mitigating the scaling effects and maintaining the reliability above a certain threshold. Many of these schemes rely on incorporating different types of redundancy at the device, gate, and system level, which inevitably affect the area, power, and delay parameters. To optimize the tradeoff between these conflicting parameters, an accurate and efficient reliability EDA tool is needed. Such a tool would help circuit designers compare different reliability schemes and select the one that achieves the target reliability margins while having minimum impact on the other design parameters. However, the enormous size and the complexity of today's logic circuits make accurate calculation of the circuit's reliability a very challenging and time-consuming process. This paper introduces a novel, accurate, and efficient algorithm for circuit reliability estimation. The algorithm improves accuracy by taking the effect of reconvergent fan-out nodes into consideration, while improving efficiency by implementing a multithreaded approach for node evaluation. Simulation results show that the proposed algorithm is efficient and more accurate than other reliability estimation algorithms currently proposed in the literature.
Relativistic simulations of compact object mergers for nucleonic matter and strange quark matter

Under the assumption that the energy of the ground state of 3-flavor quark matter is lower than the one of nucleonic matter, the compact stellar remnants of supernova explosions are composed of this quark matter. Because of the appearence of strange quarks, such objects are called strange stars. Considering their observational features, strange stars are very similar to neutron stars made of nucleonic matter, and therefore observations cannot exclude the existence of strange stars. This thesis introduces a new method for simulating mergers of compact stars and black holes within a general relativistic framework. The main goal of the present work is the investigation of the question, whether the coalescence of two strange stars in a binary system yields observational signatures that allow one to distinguish them from colliding neutron stars. In this context the gravitational-wave signals are analyzed. It is found that in general the characteristic frequencies in the gravitational-wave spectra are higher for strange stars. Moreover, the amount of matter that becomes gravitationally unbound during the merging is determined. The detection of ejecta of strange star mergers as potential component of cosmic ray flux could serve as a proof of the existence of strange quark matter.
On Multi-dominance in Restrictive Relative Structures*

This paper argues, based on the DP-internal multi-dominance analysis of restrictive relative structures presented in Inada (2016), that the restrictive relatives in English involve sharing of NumP, a nominal functional layer in between DP and NP. The proposed analysis accounts for the adjunction property of restrictive relative clauses and the reconstruction effects of the Head Nouns. The multi-dominance structure with a shared element is shown to be obtained by simultaneous applications of External Merge, which are operative for the computation of Narrow Syntax, which must be equipped with the formation of the two intersecting sets as a complex set.
Reynolds stress anisotropy in shock-containing jets

The anisotropy of the Reynolds stress tensor is assessed from numerical and experimental data for an underexpanded supersonic jet. Shock structures are shown both to directly influence anisotropy within the jet core, as well as to modulate anisotropy within the shear layer. The jet shear layer is mostly characterized by three-component turbulence, with complex variation within the jet core due to both shock and expansion structures, as well as the interior shear layer generated from the Mach disk triple point.
The role of equivalent metrics in fixed point theory

Metrical fixed point theory is accomplished by a wide class of terms: \roster \item"$\bullet$" operators (bounded, Lipschitz, contraction, contractive, nonexpansive, noncontractive, expansive, dilatation, isometry, similarity, Picard, weakly Picard, Bessaga, Janos, Caristi, pseudocontractive, accretive, etc.), \item"$\bullet$" convexity (strict, uniform, hyper, etc.), \item"$\bullet$" deffect of some properties (measure of noncompactness, measure of nonconvexity, minimal displacement, etc.), \item"$\bullet$" data dependence (stability, Ulam stability, well-posedness, shadowing property, etc.), \item"$\bullet$" attractor, \item"$\bullet$" basin of attraction$\ldots$ \endroster The purpose of this paper is to study several properties of these concepts with respect to equivalent metrics.
Beam-induced heat loads on the beam screens of the inner triplets for the HL-LHC

The expected heat load induced on the beam screens has been evaluated for the triplet assemblies in the four experimental Insertion Regions (IRs) of the HL-LHC. The contribution from electron cloud effects has been estimated using PyECLOUD macroparticle simulations. The presence of a surface treatment for the reduction of the Secondary Electron Yield has been taken into account. The contribution from the impedance of the beam screen has been evaluated taking into account the impact of the temperature and of the magnetic field on the resistivity of the surface. Geneva, Switzerland February 2018
On the geometry of Halphen surfaces, associated K3 surfaces, and F-theory

We study the structures of a family of rational elliptic surfaces, called Halphen surfaces of index 2. These surfaces have bisections, but they do not have a global section. We construct several examples of Halphen surfaces of index 2 with type $I_{n}$ fibers. By considering double covers of the Halphen surfaces of index 2, we obtain genus-one fibered K3 surfaces without a global section. Consequently, we obtain examples of K3 surfaces without a section with type $I_n$ fibers. Furthermore, we consider F-theory compactifications on the resulting K3 surfaces without a section times a K3 surface. We find that SU(5) gauge symmetry arises in one of these compactifications.
Collaborative Team Learning in Information Systems: A Pedagogy for Developing Team Skills and High Performance

Business schools must learn how to deliver graduates who are capable team players, particularly in the field of information systems where IS personnel are frequently cited as lacking in interpersonal and teams skills, and where information technology work is increasingly structured around team-based projects. We report here on the effectiveness of a collaborative pedagogical approach called team learning, which was used in a database management systems course. The team learning methodology requires students and their teammates to bear sole responsibility for learning in teams, with the professor acting as a “Guide on the Side” (16). Using an experimental design, this study demonstrates that teams consistently outperformed individuals, which critical team skills improved over time, and that important team skills were positively associated with team performance.
Modeling and numerical simulation of crack growth and damage with a phase field approach

Phase field methods allow for convenient and efficient moving interface simulations. In this paper phase field approaches of different order are presented, and applied to simulate damage in solids of temperature dependent and non‐linear elastic materials. The numerical framework provides a NURBS based finite element method which minimizes the numerical and computational effort without impairing the smoothness required by the problem.