Miracle-dz/UniFAR-FTUs huggingface dataset:
Total Reflection X Ray Fluorescence Analysis

Thank you for reading total reflection x ray fluorescence analysis. As you may know, people have search hundreds times for their chosen readings like this total reflection x ray fluorescence analysis, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious virus inside their desktop computer. total reflection x ray fluorescence analysis is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the total reflection x ray fluorescence analysis is universally compatible with any devices to read.
HRR profile estimation using SLIM

In this study, authors address high-range-resolution (HRR) profile reconstruction, when stepped-frequency waveforms are eventually used to maintain a narrow instantaneous bandwidth, resorting to the sparse learning via iterative minimisation (SLIM) paradigm, a regularised minimisation approach with an $l_q$ l q -norm constraint (for $0 \lt q \le 1$ 0 q ≤ 1 ), providing a variant to the original method. Particularly, the proposed method resorts to the regularised maximum-likelihood estimation paradigm including a term promoting the sparsity of the profile and related to the $l_q$ l q -norm of the vector containing the scatterers’ reflectivities. A priori information on the interference power level is also accounted for, at the design stage, and, assuming that each range cell under test contains at most one scatterer, the actual active scatterers composing the target are determined by exploiting the Bayesian information criterion (BIC). BIC is also used to automatically select the optimised q , so as to make the procedure adaptive with respect to q . Once the location of the active scatterers has been determined, a least-squares approach is also used to obtain even more precise HRR reconstruction. Furthermore, an efficient algorithm to define optimised frequency hopping patterns, in the presence of a continuous and coordinated feedback between the transmitter and receiver, is presented and assessed. The carried out analysis shows that the SLIM-based procedure presents higher accuracy in the HRR profile recovery than other widely used techniques, i.e. the iterative adaptive approach (IAA). Moreover, results demonstrate that the target range profile estimation capabilities are enhanced, both for SLIM and IAA, when the cognitive paradigm is employed.
Mandatory IFRS Adoption and Analyst Coverage: Evidence from the UK

This study investigates whether the mandatory adoption of International Financial Reporting Standards (IFRS) enforce financial analysts to cover the firms with their EPS forecast. After examining a large sample of 10,953 firm year observations from 1,467 distinct UK listed firms for the period between 1990 and 2013, the results suggest that, mandatory IFRS adoption attract more analysts to follow the firms. Where we find the number of financial analyst who cover the IFRS adopters is significantly higher than that for non-adopter firms.
Collective effects in a transient microbunching regime and ion cloud mitigation in ThomX

The thesis is focused on the study of collective effects in a 50 MeV electron storage ring, ThomX, in the absence of synchrotron radiation damping and of longitudinal matching. This thesis is divided in two distinct parts. The first part corresponds to the design of the impedance model (geometric and resistive wakefields, coherent synchrotron radiation) of the storage ring in order to simulate the beam dynamics. The geometric impedance model of the storage ring was obtained via simulation of the individual elements and was checked using wire measurements on prototypes. The coherent synchrotron radiation was simulated taking into account a rectangular vacuum chamber. Beam dynamics simulations, from the RF gun cathode to the storage ring, including collective effects are presented. The simulations are used to optimise the beam dynamics in the storage ring in the micro-bunching regime. The second part is the study of the ion cloud produced by the ionisation of the residual vacuum molecules and the optimisation of the ion clearing techniques. The longitudinal ion accumulation points and the trapping in magnetic fields are both studied analytically and by using a tracking code developed for this purpose. Clearing electrodes and clearing gaps are simulated and optimised using this code and the strategy chosen for the limitation of ion induced effects is described. Finally, the effect of multi-ionisation and ion dissociation is taken into account and the ion effect on the electron beam is estimated.
Fluid Communities: A Community Detection Algorithm

Community detection algorithms are a family of unsupervised graph mining algorithms which group vertices into clusters (i.e., communities). These algorithms provide insight into both the structure of a network and the entities that compose it. In this paper we propose a novel community detection algorithm based on the simple idea of fluids interacting in an environment, expanding and contracting in contact with one another. The Fluid Communities algorithm is based on the propagation methodology, the most efficient approach to community detection in terms of computational cost and scalability. At the same time, the quality of the communities it finds is close to that of the current state-of-the-art community detection algorithms, and significantly superior to the Label Propagation Algorithm (LPA). While all previously proposed propagation-based algorithms can only produce a single clustering for a given graph, the Fluid Communities algorithm can identify a variable number of communities. As a result, the proposed algorithm represents a distinct and scalable tool for analyzing the topology of large scale graphs at multiple degrees of granularity. Keywords—Community Detection, Network Analysis, Graph Mining, Unsupervised Learning.
Simulation numérique d'écoulements autour de corps non profilés par des modèles de turbulence hybrides et un schéma multirate

Ce travail est une contribution a la simulation numerique d'ecoulements turbulents autour de corps non profiles. Apres avoir precise les ingredients numeriques et les modeles de turbulence utilises dans nos simulations, nous presentons une etude sur l'evaluation des effets de la procedure dynamique des modeles de sous-maille dans un modele VMS-LES et une approche hybride RANS/VMS-LES. Des problemes d'ecoulements autour d'un cylindre seul et en tandem sont consideres. Nous etudions ensuite le comportement de modeles de turbulence hybrides pour la simulation d'ecoulements en regime sous-critique autour d'un cylindre circulaire. Le calcul de l'ecoulement autour d'un cylindre de section rectangulaire par l'approche VMS-LES est aussi presente. Enfin, dans une derniere partie, apres avoir fait une revue des travaux importants sur les schemas d'avancement en temps multirate, nous proposons une nouvelle approche explicite multirate par agglomeration de volumes finis que nous appliquons a des calculs d'ecoulements turbulents complexes en utilisant un modele de turbulence hybride.
Utilization of broken rice and walnut kernels for development of nutritious snacks using extrusion technology

Walnut kernel supplementation increases the nutritional value of starch based expanded snacks. A systematic study was conducted for optimizing the blending level of broken walnut kernels and broken rice for the production of expanded snacks through co-rotating twin screw extruder. Response surface methodology was used to study the effects of feed composition, feed moisture, screw speed and barrel temperature on specific mechanical energy (SME), bulk density (BD), water absorption index (WAI), water solubility index (WSI), expansion ratio (ER), oil loss during extrusion, complexing index (CI) and breaking strength. Response surface regression models were established to determine the responses as functions of process variables. Regression models for all the responses were highly significant (p<0.01) with high co-efficient of determination (R>0.83). The compromised optimum conditions obtained by numerical optimization for development of extruded snacks were broken walnut kernel flour to broken rice flour ratio (10:90), moisture content 14%, screw speed 550 rpm and die temperature 170 C.
Nucleation of Multiple Buckled Structures in Intertwined DNA Double Helices

We study the statistical-mechanical properties of intertwined double-helical DNAs (DNA braids). In magnetic tweezers experiments we find that torsionally-stressed stretched braids supercoil via an abrupt buckling transition, which is associated with nucleation of a braid end loop, and that the buckled braid is characterized by proliferation of multiple domains. Differences between the mechanics of DNA braids and supercoiled single DNAs can be understood as an effect of increased bulkiness in the structure of the former. The experimental results are in accord with the predictions of a previously-described statistical-mechanical model.
Ceiling and Floors: Gender Wage Gaps by Education in Spain

This paper analyses the gender wage gaps by education throughout the wage distribution in Spain using individual data from the ECHP (1999). Quantile regressions are used to estimate the wage returns to the different characteristics at the more relevant percentiles and a suitable version of the Oaxaca-Blinder decomposition is then implemented to estimate the component of the gender gap not explained by different characteristics. Our main findings are twofold. First, in contrast with the steep pattern found for other countries, the flatter evolution of the gap found in Spain hides a composition effect when the sample is split by education. On the one hand, for the group with college/tertiary education, we find a higher unexplained gap at the top than at the bottom of the distribution, in accordance with the conventional glass ceiling hypothesis. On the other, for the group with lower education, the gap is much higher at the bottom than at the top of the distribution. We label this novel pattern as glass floors and argue that it is due to statistical discrimination exerted by employers in view of the low participation rate of women in this group. Such a hypothesis is confirmed when using the panel structure of the ECHP.
ESTIMATION OF INCIDENT AND REFLECTED WAVES IN RANDOM WAVE EXPERIMENTS

A technique to resolve the incident and reflected waves from the records of composite waves is presented. It is applicable to both regular and irregular trains of waves. Two simultaneous wave records are taken at adjacent locations, and all the amplitudes of Fourier components are analyzed by the FFT technique. The amplitudes of incident and reflected wave components are estimated from the Fourier components, and the incident and reflected wave spectra are constructed by smoothing the estimated periodograms. The wave resolution is effective in the range outside the condition of the gauge spacing being even integer of half wavelength. The ratio of incident and reflected wave energies in the effective resolution range is employed in estimating the overall reflection coefficient. The incident and reflected wave heights are estimated from the composite wave heights by energy consideration.
On the importance of decoding in semi-supervised learning

In many natural language processing (NLP) tasks a large amount of unlabelled data is available while labelled data is hard to attain. Bootstrapping techniques have been shown to be very successful on a variety of NLP tasks using only a small amount of supervision. In this research we have studied different bootstrapping techniques that separate the training step of the algorithm from the decoding step which produces the argmax label on test data. We then explore generative models trained in the conventional way using the EM algorithm but we use an initialization step and a decoding techniques similar to the Yarowsky bootstrapping algorithm. The new approach is tested on the named entity classification and word sense disambiguation tasks and has shown significant improvement over previous generative models.
A Threefold Representation for the Adaptive Simulation of Embedded Deformable Objects in Contact.

We propose an approach for the interactive simulation of deformable bodies. The key ingredient is a threefold representation of the body. The deformation and dynamic evolution of the body is governed by a cubic background mesh. The mesh is hierarchically stored in an octree-structure, allowing for a fully local adaptive refinement during the simulation. To handle collisions, we employ a tetrahedral mesh, allowing for an efficient collision detection and response. We then show a physicallyplausible way to transfer the contact displacements onto the simulation mesh. A high-resolution surface is embedded into the tetrahedral mesh and only employed for the visualization. We show that by employing the adaptive threefold representation, we can significantly improve the fidelity and efficiency of the simulation. Further, we underline the wide applicability of our method by showing both interactive and off-line animations.
Hybrid ant colony optimization algorithm for unrelated parallel machine scheduling problem

Aiming at the total weighted tardiness scheduling problem of unrelated parallel machine,a kind of hybrid ant colony optimization algorithm was proposed.Variation of Modified Due Date(VMDD) heuristic rules were introduced for pheromone initialization to help escape from local optimal,and Partheno-Genetic Algorithms(PGA) gene transfer operator was incorporated into local search to optimize the currently found best solution.Key parameters of the algorithm were defined by the uniform experimental design statistic analysis.The algorithm was applied in 40 stochastic generation problems with different scale,and results were compared.Results demonstrated that the hybrid algorithms significantly outperformed the competitor with the same iteration.
Recent Northern Winter Climate Trends due to Ozone Changes and Increased Greenhouse Gas Forcing

Besides the increase in greenhouse gas concentrations and aerosols, considerable trends in ozone concentration were recently shown, with positive values mainly in the upper troposphere, and decreasing concentrations in the lower stratosphere of the Northern Hemisphere middle and high latitudes (WMO, 1992). The data basis consists approximately of 15 to 20 years of observations at various locations. The ozone changes are discussed against the background of observed variations of temperature and circulation during the last decades and are compared with the results of General Circulation Model (GCM) simulations of the effects of the increased greenhouse gas concentration, additional aerosols and the modified ozone profile itself. The observed increased lower stratospheric high latitude westerlies are part of a natural coupled mode of lower stratospheric and tropospheric circulation. This coupled mode has its strongest tropospheric effects over the North Atlantic with increased westerlies, and positive air temperature anomalies over Scandinavia and Siberia. The part of this natural coupled mode which is associated with enhanced polar stratospheric westerlies has increased in intensity during the last decades. A primary contribution to this intensification by the low latitude greenhouse-gas effects is suggested. The observed ozone trends, when integrated into a GCM, do not produce substantial changes in circulation supporting the initial greenhouse gas effects. It is concluded that a comprehensive climate model is needed to study future climate scenarios. This should include atmospheric chemistry in combination with a good representation of the whole stratosphere. It appears most probable that greenhouse-gas effects and ozone concentration are not independent of one another.
Technology and social process : oscillations in Iron Age copper production and power in Southern Jordan

Records of technological practice provide an important lens for studying societies and cultures across time and space. This dissertation takes a diachronic view of the role of ancient copper production in the formation and oscillations of power when historical 'state' level societies emerged during the late 2nd - 1st millennium BCE in the southern Levant. The primary study area is Jordan's Faynan district that contains the richest copper ore deposits in the southern Levant and constitutes one of the best preserved records of ancient copper extraction in the world. As demonstrated here, ancient metallurgy played a major role in socio-political processes for south Levantine complex societies during the Iron Age (12th - 6th centuries BCE). The core of this study is the identification of detailed chaines operatoires of changing Iron Age copper production systems. Based on newly excavated archaeometallurgy material culture, surveys, analyses of large technology-related assemblages, and previously published data, the basic components of the changing production systems are defined, and social meanings are extracted
Hip-Hop Honeys and Da Hustlaz: Black Sexualities in the New Hip-Hop Pornography

Hip-hop pornography propels the conventions of the nearly soft-core hip-hop video to the extreme, the explicit, the hard-core. The convergence of the outlaw cultures of hip-hop and pornography offers a compelling narrative about how black sexual subjects define authority, legitimacy, legibility, and power. Hip-hop porn provides black women and men an arena for labor and accumulation as well as self-presentation, mediation, and mobility. As a space for work, survival, consumption, and identity-formation, the genre proffers an opportunity to explore the gendering of black (post)modern desires, as well as the potential to think through historical echoes of the current controversies and debates around exactly what constitutes "appropriate" black sexuality. Even as it offers a venue for acts of self-representation, pleasure, and exchange, hip-hop porn's brand of eroticism raises important questions about contemporary black gender and sexual politics. Within the space of hip-hop porn, these gender and sexual politics are produced within a sexual economy of illicit eroticism. The "illicit erotic" challenges ideas that fix the hypersexuality of the black body as always already repugnant, by using fetishized hypersexuality to strategically work with and through modern capitalism. This essay is primarily concerned with exploring how black sexual subjects engage illicit erotic economies as sites to self-fashion themselves according to the values and practices of "radical consumerism," "play-labor," and self- or counter-fetishization.
Interstellar Scintillation Monitoring of the RadioAstron Blazars

The RadioAstron space radio telescope provides a unique opportunity to study the extreme brightness temperatures ($\mathrm{T_B}$) in AGNs with unprecedented long baselines of up to 28 Earth diameters. Since interstellar scintillation (ISS) may affect the visibilities observed with space VLBI (sVLBI), a complementary ground based flux density monitoring of the RadioAstron targets, which is performed near in time to the VLBI observation, could be beneficial. The combination/comparison with the sVLBI data can help to unravel the relative influence of source intrinsic and ISS induced effects, which in the end may alter the conclusions on the $\mathrm{T_B}$ measurements from sVLBI. Since 2013, a dedicated monitoring program has been ongoing to observe the ISS of RadioAstron AGN targets with a number of radio telescopes. Here we briefly introduce the program and present results from the statistical analysis of the Effelsberg monitoring data. We discuss the possible effects of ISS on $\mathrm{T_B}$ measurements for the RadioAstron target B0529+483 as a case study.
Energy Reduction for Asynchronous Circuits in SoC Applications

Gopalakrishnan, Harish. Ph.D., Engineering Ph.D. Program, Wright State University, 2011. Asynchronous Energy Reduction for Noise Mitigation in SOC Circuits. As complexity increases and gate sizes shrink for monolithic, mixed-signal integrated circuit (IC) technologies, two problems become dominant: substrate noise caused by digital clocks interfering with highly sensitive analog and radio frequency (RF) components and parametric variations that can cause circuit delays to vary in excess of 35%. Clockless logic (or asynchronous) circuits address both of these issues and more. Clockless, asynchronous circuits are by nature delay-insensitive making them immune to parametric variations. Even more important is the processing characteristics of clockless asynchronous circuits, which eliminate highly intricate clock signals that cause large power spikes every time they switch. Consequently, asynchronous design is becoming more and more attractive for low-noise, low-power applications. In a clock free environment, energy is a more relevant metric than power. In this work, we present algorithms that attempt to minimize the energy in asynchronous integrated circuits. Our techniques are based on voltage scaling (VS) and gate sizing (GS). On average, performing a two-stage energy reduction with VS followed by GS results in 26% energy reduction.
Multiphonon anharmonicity of MgO

The anharmonic lattice dynamics of MgO has been studied at ambient conditions and at high temperatures by infrared spectroscopy and inelastic x-ray scattering measurements combined with density functional perturbation theory calculations. The agreement between the measured phonon energies and widths with ab initio calculated values provides a direct and pertinent test of the validity of advanced theoretical methods. Long observed anharmonic features in the infrared reflectivity find a clear explanation in terms of well-defined multiphonon scattering processes and lattice dynamics peculiarities, also responsible for a significant and sharp reduction of the longitudinal optical phonon lifetime at critical finite wave vectors. Our work highlights the importance of multiphonon scattering processes on the collective dynamics and related material properties.
How Does Disagreement Benefit Co-teaching?

Learning with noisy labels is one of the most important question in weakly-supervised learning domain. Classical approaches focus on adding the regularization or estimating the noise transition matrix. However, either a regularization bias is permanently introduced, or the noise transition matrix is hard to be estimated accurately. In this paper, following a novel path to train on small-loss samples, we propose a robust learning paradigm called Co-teaching+. This paradigm naturally bridges "Update by Disagreement" strategy with Co-teaching that trains two deep neural networks, thus consists of disagreement-update step and cross-update step. In disagreement-update step, two networks predicts all data first, and feeds forward prediction disagreement data only. Then, in cross-update step, each network selects its small-loss data from such disagreement data, but back propagates the small-loss data by its peer network and updates itself parameters. Empirical results on noisy versions of MNIST, CIFAR-10 and NEWS demonstrate that Co-teaching+ is much superior to the state-of-the-art methods in the robustness of trained deep models.