Miracle-dz/UniFAR-FTUs huggingface dataset:
Shock Wave Structure in the Presence of Energetic Particles

Energetic particles that are not equilibrated with the thermal plasma (such as pickup ions (PUIs), anomalous cosmic rays (ACRs) and solar energetic particles (SEPs)) can modify the structure of collisionless shock waves. This is relevant to the inner and outer heliosphere and the Very Local Interstellar Medium (VLISM) where observations of shock waves in the e.g., the inner heliosphere show that the energetic particle component pressure is greater than the both the magnetic field and thermal gas pressure (Lario et al., 2015). Voyager 2 observations revealed that the heliospheric termination shock (HTS) is very broad and mediated by energetic particles. PUIs and SEPs contribute both a collisionless heat flux and a higher-order viscosity. We show that the incorporation of both effects can completely determine the structure of collisionless shocks mediated by energetic ions. Since the reduced form of the PUI mediated plasma model is structurally identical to the classical cosmic ray two-fluid model (Axford et al., (1982)), we note that the presence of viscosity at least formally eliminates the need of a gas sub-shock in the classical two-fluid model, including in that regime where three are possible. By considering parameters upstream of the heliospheric termination shock (HTS), we show that the thermal gas remains relatively cold and the shock is mediated by PUIs. We determine the structure of the weak interstellar shock observed by Voyager 1. We consider the inclusion of the thermal heat flux and viscosity to address the most general form of an energetic particle-thermal plasma two-fluid model.
Ensembles of Regularized Linear Models

We propose an approach for building ensembles of regularized linear models by optimizing a novel objective function, that encourages sparsity within each model and diversity among them. Our procedure works on top of a given penalized linear regression estimator (e.g., Lasso, Elastic Net, SCAD) by fitting it to possibly overlapping subsets of features, while at the same time encouraging diversity among the subsets, to reduce the correlation between the predictions that result from each fitted model. The predictions from the models are then aggregated. For the case of an Elastic Net penalty and orthogonal predictors, we give a closed form solution for the regression coefficients in each of the ensembled models. An extensive simulation study and real-data applications show that the proposed method systematically improves the prediction accuracy of the base linear estimators being ensembled. Extensions to GLMs and other models are discussed.
Journal of Cancer Biology and Therapeutics Role of Obesity-induced Inflammatory Cytokines on Breast and Thyroid Cancer Therapeutics: A Literature Review

Background: As reported by the Centers for Disease Control and Prevention, cancer is the second leading cause of death in the United States. Several factors are known to be related to causing cancer, obesity is one of them. Currently, the World Health Organization is considering obesity as a “global pandemic”. In the United States, more than 36% of adults are obese. Among them, women are more susceptible to severe obesity (11.5%) compared to men (6.9%). Obesity and overweight have long been associated with several chronic diseases including cancer. According to the International Agency for Research on Cancer, there is substantial evidence that obesity is associated with cancers in 13 anatomical sites such as the endometrium, kidney, gastric, cardiac, colon, rectum, biliary tract, pancreas, breast, esophagus, ovary, thyroid, liver, and meninges. In both men and women, a strong correlation between hormones and obesity-induced inflammatory cytokines is evident in cancer development. Recent studies show that several mechanisms can play a role in obesity-related endocrine cancers, such as alteration of inflammatory, immunological, and metabolic functions, defects in DNA repair, and alteration in gene function. However, a comprehensive picture to show the relationship between obesity-induced inflammatory markers in breast and thyroid cancer is lacking. This review aims to illustrate the link between obesity-induced inflammatory cytokines as well as the occurrence of breast and thyroid cancer and the role of metformin and chemotherapy in the treatment of these cancers. We provide studies on the expression of novel inflammatory markers that may furnish essential clues for the detection, prognosis, prevention, and therapeutic implications of obesity-linked cancers.
Théorie des Matrices Aléatoires Appliquée à la Détection STAP Rang Faible

Le papier se place dans le cadre de detection de cible dans un bruit compose d'un fouillis gaussien de rang faible et d'un bruit blanc gaussien. Dans ce contexte, il est interessant d'utiliser une version adaptative du detecteur Low Rank Normalized Matched Filter, note LR-ANMF qui est fonction de l'estimation du projecteur sur le sous-espace fouillis. On montre dans ce papier que le detecteur LR-ANMF base sur la SCM est consistant quand le nombre de donnees secondaires K -> infty pour une dimension des donnees m fixe mais n'est pas consistant quand m et K tendent vers l'infini au meme ratio. En utilisant les resultats de la theorie des matrices aleatoires, on propose alors une nouvelle version du detecteur LR-ANMF consistante dans les deux cas. L'application du nouveau d'etecteur sur des donnees STAP montre l'interet de notre approche.
Hacienda Pública Española/Review of Public Economics Hacienda Pública Española/Review of Public Economics

Optimal tax theory assigns two different roles to the measure of excess burden, one to compare the costs of alternative tax instruments, and the other to compute the deadweight loss of specific taxes instruments, a measure of the welfare costs of their distortionary effects. This paper claims that the deadweight loss provides a misleading measure of welfare costs from tax distortions, because it makes several unverified assumptions to equate distortions to costs and ensure that its value is greater than zero. Taxes other than the lump-sum tax and tax-induced changes in relative prices cannot generally be assumed to be distortionary.
AI-Based Maize and Weeds Detection on the Edge with CornWeed Dataset

Artificial intelligence (AI) is used more heavily in agricultural applications. Yet, the lack of wireless-fidelity (Wi-Fi) connections on agricultural fields makes AI cloud services unavailable. Consequently, AI models have to be processed directly on the edge. In this paper, we evaluate state-of-the-art detection algorithms for their use in agriculture, in particular plant detection. Thus, this paper presents the CornWeed data set, which has been recorded on farm machines, showing labelled maize crops and weeds for plant detection. The paper provides accuracies for the state-of-the-art detection algorithms on the CornWeed data set, as well as frames per second (FPS) metrics for the considered networks on multiple edge devices. Moreover, for the FPS analysis, the detection algorithms are converted to open neural network exchange (ONNX) and TensoRT engine files as they could be used as future standards for model exchange.
Adaptive Force Control Using a Standard Deviation-based Hybrid Approach

— A good tracking response is essential for a force control system to achieve high performance in object handling. One of the significant challenges of the force control system is that the plant dynamics are directly dependent on the environment and the mechanical properties of the object. It's well-known that the mechanical properties of an object in manufacturing vary based on the type of product, gripper tools, and environment; hence, a non-adaptive controller may not be efficiently adopted. To address this issue, this paper proposes impedance control with hybrid adaptive algorithms to ensure the actuator system tracks the desired force command accurately. Particle Swarm Optimization (PSO) is adopted to adapt the impedance control parameters, thereby applying the capabilities of the learning system. A hybrid adaptive force control with a fitness function of the standard deviation and summation of error is proposed. The tracking response of the conventional adaptive controller was examined and compared with the proposed controller. The simulation results demonstrate the effectiveness of the proposed system.
The comparative impact of different patient-centered medical The comparative impact of different patient-centered medical home domains on satisfaction among individuals living with type home domains on satisfaction among individuals living with type II diabetes II diabetes

Chronic illnesses like type 2 diabetes are costly and difficult to treat. Patient-centered medical homes (PCMH) have the potential to improve patient satisfaction in this population. However, which domains have the most impact on patient satisfaction has not been established. The aim of this study was to assess the relative strength of association between seven PCMH domains and two measures of satisfaction. Cross-sectional data were used in this observational study collected from a random sample of adults aged 18-89 with type 2 diabetes (n=1301) seen at 4 PCMHs. The Ambulatory Care Experiences Survey instrument was used to assess all measures. Dependent variables included 2 measures of patient satisfaction: overall care and personal doctor. Independent variables included patient perceptions of implementation level of 7 PCMH domains categorized into two dimensions: administrative features of care and physician-patient interactions. Administrative features of care include organizational access, integration of care and office staff helpfulness. Physician-patient interactions include communication, comprehensive knowledge and interpersonal treatment. Analysis was conducted using linear regression. The results reveal all physician-patient interaction PCMH domains were significantly associated with both measures of satisfaction. The relationships for administrative features of care were dependent upon the satisfaction outcome being analyzed. Communication and comprehensive knowledge had the strongest association of all domains. The authors conclude variations in importance of PCMH domains on satisfaction exist. Physician-patient interaction domains are the strongest contributors to patient satisfaction and overall experience. Understanding which PCMH domains have the largest impact can inform physician practice’s efforts to improve outcomes of care.
Linear, Discrete, and Quadratic Constraints in Single-image 3D Reconstruction

In this thesis, we investigate the formulation, optimization and ambiguities in single-image 3D surface reconstruction from geometric and photometric constraints. We examine linear, discrete and quadratic constraints for shape from planar curves, shape from texture, and shape from shading. The problem of recovering 3D shape from the projection of planar curves on a surface is strongly motivated by perception studies. Applications include single-view modeling and uncalibrated structured light. When the curves intersect, the problem leads to a linear system for which a direct least-squares method is sensitive to noise. We derive a more stable solution and show examples where the same method produces plausible surfaces from the projection of parallel (non-intersecting) planar cross sections. The problem of reconstructing a smooth surface under constraints that have discrete ambiguities arise in areas such as shape from texture, shape from shading, photometric stereo and shape from defocus. While the problem is computationally hard, heuristics based on semidefinite programming may reveal the shape of the surface. Finally, we examine the shape from shading problem without boundary conditions as a polynomial system. This formulation allows, in generic cases, a complete solution for ideal polyhedral objects. For the general case we propose a semidefinite programming relaxation procedure, and an exact line search iterative procedure with a new smoothness term that favors folds at edges. We use this numerical technique to inspect shading ambiguities.
Nutritional Characteristics and Feeding Value of Dried Corn Bran and Solubles, De-oiled (Solvent Extracted DDGS), and Corn Distillers Oil in Animal Diets Introduction

In addition to corn fermented protein (CFP; Chapters 1, 2, 3, 4, and 5), high-protein distillers dried grains without solubles (HP-DDG) described in Chapter 6, and corn protein concentrate (CPC) described in Chapter 7, several other new corn co-products are being produced by a few ethanol plants using new industrial processes that result in different nutritional profiles and feeding applications. These include wet and dried corn fiber/bran and solubles (CBS), de-oiled DDGS, and corn distillers oil (CDO). Therefore, the purpose of this chapter is to provide current nutritional profiles of each co-product category, describe the benefits and limitations for their use in diets for different animal species, and provide summaries of feeding trials that have been conducted.
Research on informationization control system and its application in expressway centralized steel processing

【 Abstract 】 In the era of big data, digital thinking has become a trend in the future. The traditional method of rebar processing based on decentralized processing methods generally has problems in quality management, safety, economy, processing quality, production efficiency and other aspects. Relying on in building highway project, this paper is based on large data, BIM, cloud computing and other cutting-edge technology, established a complete set of steel intelligent processing flow, and formed a blend of informatization management mode of intensive processing method, respectively, from order, design, storage, production, distribution, raw material quality, data analysis etc were studied. The practice shows that the intelligent processing scheme can save manpower, materials and energy well, guarantee the schedule and quality, optimize management, and realize the all-round improvement of the steel processing industry.
A simple and accurate coupled HLL-type approximate Riemann solver for the two-fluid two-pressure model of compressible flows

This paper is concerned with the design of a very simple and efficient Godunov-type method for the so-called two-fluid two-pressure compress-ible model for two-phase flows. It is a contribution to the proceedings of a workshop organized by the EDF R&D French utility company and devoted to the verification of numerical schemes for two-phase flows. The present study focuses on the convective part of the two-fluid two-pressure model and is a short form of a longer paper [1] where the numerical strategy also takes into account additional terms associated with sources, pressure relaxation and drag forces. Numerical simulations and comparisons with other strategies are proposed in the last section.
Multisensor Characterization of Mammatus

AbstractMultisensor observations of anvil mammatus are analyzed in order to gain a more detailed understanding of their spatiotemporal structure and microphysical characterization. Remarkable polarimetric radar signatures are detected for the Pentecost 2014 supercell in Northrhine Westfalia, Germany, and severe storms in Oklahoma along their mammatus-bearing anvil bases. Radar reflectivity at horizontal polarization ZH and cross-correlation coefficient ρHV decrease downward toward the bottom of the anvil while differential reflectivity ZDR rapidly increases, consistent with the signature of crystal depositional growth. The differential reflectivity ZDR within mammatus exceeds 2 dB in the Pentecost storm and in several Oklahoma severe convective storms examined for this paper. Observations from a zenith-pointing Ka-band cloud radar and a Doppler wind lidar during the Pentecost storm indicate the presence of a supercooled liquid layer of at least 200–300-m depth near the anvil base at temperatures between −.
Spin Hall effects

In solid-state materials with strong relativistic spin-orbit coupling, charge currents generate transverse spin currents. The associated spin Hall and inverse spin Hall effects distinguish between charge and spin current where electron charge is a conserved quantity but its spin direction is not. This review provides a theoretical and experimental treatment of this subfield of spintronics, beginning with distinct microscopic mechanisms seen in ferromagnets and concluding with a discussion of optical-, transport-, and magnetization-dynamics-based experiments closely linked to the microscopic and phenomenological theories presented.
Coulomb interaction-induced jitter amplification in RF-compressed high-brightness electron source ultrafast electron diffraction

We have theoretically and experimentally demonstrated an RF compression-based jitter-amplification effect in high-brightness electron source ultrafast electron diffraction (UED), which degrades the temporal resolution significantly. A detailed analysis and simulations reveal the crucial role of the longitudinal and transverse Coulomb interaction for this jitter-amplification effect, which accord very well with experimental results. An optimized compact UED structure for full compression has been proposed, which can suppress the jitter by half and improve the temporal resolution to sub-100 fs. This Coulomb interaction-induced jitter amplification exists in nearly the whole ultrafast physics field where laser-electron synchronization is required. Moreover, it cannot be suppressed completely. The quantified explanation for the mechanism and optimization provides important guidance for photocathode accelerators and other compression-based ultrashort electron pulse generation and precise control.
Simulating the Universe: Nonlinear Formation and Evolution of Cosmic Structure

Simulating the Universe: Nonlinear Formation and Evolution of Cosmic Structure Jeffrey David Emberson Doctor of Philosophy Graduate Department of Astronomy and Astrophysics University of Toronto 2016 In this thesis, we harness the power of modern scientific computing to explore the formation and evolution of cosmological structure in a wide variety of astrophysical scenarios. We explore the nonlinear dynamics associated with the interplay between cold dark matter (CDM), baryons, ionizing radiation, and cosmic neutrinos, within regimes where analytic calculations necessarily fail. We begin by providing an overview of structure formation and its connections to the fields of study considered here: the epoch of reionization, galactic substructure evolution, and cosmic neutrinos. We then present a rigorous numerical convergence study of cosmological hydrodynamics simulations post-possessed with radiative transfer to study the impact of small-scale absorption systems within the intergalactic medium (IGM) during the onset of reionization. We present converged statistics of the IGM on smaller scales and earlier times than previously considered. Moreover, we provide strict resolution limits for hydrodynamic simulations to properly resolve the unheated IGM. Next we study the infall and dynamical evolution of CDM halos in a galactic host. We find the behaviour of low-mass subhalos is qualitatively different than previously described for high-mass subhalos. In particular, the evolution of low-mass subhalos, with masses less than 0.1 per cent that of the host, is mainly driven by their concentration. This presents an opportunity to use concentration as a predictive indicator of substructure evolution. We finish this thesis with an investigation of a recently proposed method for constraining individual neutrino mass from cosmological observations. Such a detection depends on the ability to reconstruct the CDM-neutrino relative velocity, which we show can be accomplished using linear transformations of an observed galaxy field. Based on this, we perform the world’s largest cosmological N -body simulation and present preliminary results for the observational prospects of cosmic neutrinos.
Femtoscopic and non-femtoscopic two-pion correlations in the light of recent ALICE LHC results

The hydrokinetic predictions for the HBT radii in heavy ion collisions at the LHC energies are compared with the recent results of the ALICE Collaboration. The role of non-equilibrium and non-hydrodynamic stage of the matter evolution in formation of the femtoscopy scales at the LHC energies is analyzed. Non-femtoscopic two-pion correlations in proton-proton collisions at the LHC energies are analyzed and a simple model that takes into account correlations induced by the conservation laws and minijets is proposed. It gives reasonable description of the non-femtoscopic correlations of like-sign and unlike-sign pion pairs in proton-proton collision events reported by the ALICE Collaboration.
Accreted Metallicity-Stellar Mass Relationship

There is increasing observational and theoretical evidence for a tight correlation between the metallicity and total mass of accreted stellar halos for galaxies with Milky Way-like stellar masses. Using the Illustris cosmological hydrodynamical simulations, we explore this relationship for central galaxies spanning a broad range in dark matter halo masses. We find that there exists a general accreted metallicity-stellar mass relationship over 3 orders of magnitude in accreted stellar mass. This arises due to the accreted stellar metallicity being set by the dominant accreted progenitor, which also contributes the bulk of its stellar material. We show that the scatter in accreted metallicity at a fixed accreted stellar mass encodes information about the stellar mass of the dominant progenitor, while the density and metallicity gradients of the accreted stellar halo provides information about the time of accretion of the dominant progenitor. We demonstrate that the total accreted stellar metallicity and accreted stellar mass can be reconstructed from aperture measurements along the minor axis of edge-on disk galaxies. These correlations highlight the potential for observational studies of stellar halos to quantify our understanding of the most dominant events in the growth history of galaxies. We explore the implication of our models for our understanding of the accretion histories of the Milky Way, M31 and NGC 5128. In particular, a relatively late and massive accretion is favoured for M31; additionally, we provide a first estimate of the accreted stellar mass for NGC 5128.
Trojan Horse cross section measurements and their impact on primordial nucleosynthesis

Big Bang Nucleosynthesis (BBN) nucleosynthesis requires several nuclear physics inputs and, among them, an important role is played by nuclear reaction rates. They are among the most important input for a quantitative description of the early Universe. An up-to-date compilation of direct cross sections of d(d,p)t, d(d,n)3He and 3He(d,p)4He reactions is given, being these ones among the most uncertain bare-nucleus cross sections. An intense experimental effort has been carried on in the last decade to apply the Trojan Horse Method (THM) to study reactions of relevance for the BBN and measure their astrophysical S(E)-factor. The result of these recent measurements is reviewed and compared with the available direct data. The reaction rates and the relative error for the four reactions of interest are then numerically calculated in the temperature ranges of relevance for BBN (0.01<T9 <10) and compared with up-to-date reaction rate compilations. Their value were therefore used as input physics for primordial nucleosynthesis calculations in order to evaluate their impact on the calculated primordial abundances of D, 3,4He and 7Li. These ones were then compared with the observational primordial abundance estimates in different astrophysical sites. A comparison was also performed with calculations using other reaction rates compilations available in literature.