Miracle-dz/UniFAR-FTUs huggingface dataset:
Schädigungsmodell für die Hydroabrasionsbeanspruchung zur probabilistischen Lebensdauerprognose von Betonoberflächen im Wasserbau

Wasserbauliche Anlagen unterliegen vielfaltigen Einwirkungen. Besonders die mechanische Einwirkung auf Betonoberflachen infolge der mit Feststoffen befrachteten Wasserstromung stellt eine masgebende Beanspruchung dar. Die Behandlung der Dauerhaftigkeit von Beton bzgl. des Hydroabrasionsverschleises erfolgte bisher nur ansatzweise. Hinsichtlich der Verschleisprufverfahren, -kennwerte und Schadigungsmodelle existierten Kenntnislucken, die im Rahmen dieser Arbeit geschlossen wurden.
Xin Pan and Helmut Graeb

As semiconductor technology continuously scales, the joint effects of manufacture process variations and operational lifetime parameter degradations have been a major concern for analog circuit designers since they affect the lifetime yield value, i.e., the percentage of the products which can satisfy all of the pre-defined specifications during lifetime operation (Alam, Kang, Paul & Roy, 2007), (Gielen et al., 2008). The analysis and optimization of analog circuits considering process variations alone have been in research for decades, and certain design centering algorithms and commercial software are available to achieve a design for yield (more specifically, fresh yield) (Nassif, 2008), (Antreich et al., 1994). On the other hand, the modeling of device parameter degradations such as Negative Bias Temperature Instability (NBTI) and Hot Carrier Injection (HCI) has been so far focusing mainly on the nominal values without considering the underlying variations during manufacture process (Jha et al., 2005), (Liu et al., 2006) and (Martin-Martinez et al., 2009). A robust analog circuit design is thus needed tolerant of both process variations and lifetime parameter degradations, maximizing the lifetime yield value. Most of the past works quantify the influences of process variations and lifetime degradations separately. However, since lifetime degradations will drift certain device parameters, e.g., Vth, from their fresh values during circuit lifetime operation, the distribution of the circuit-level performance will also shift its position during lifetime, as can be seen in Figure 1, where 1000 Monte-Carlo simulations are run on a fresh and 5-year-old Miller OpAmp. Values of Gain-Bandwidth Product(GBW) and Rising Slew Rate (SR) are shown, both moving towards negative direction. In order to ensure a robust design, it is thus necessary to consider the joint effects of process variations and lifetime parameter degradations during design phase, such that certain weak points can be detected early, and additional safe margins can be assigned properly. In this chapter, a novel design methodology to analyze and optimize the lifetime yield value of analog circuits based on the idea of lifetime worst-case distance is presented. It does not involve Monte-Carlo simulations, and considers process variations and major parameter degradation mechanisms such as NBTI and HCI. The proposed work is based on the preliminary methods presented in (Pan & Graeb, 2009) and (Pan & Graeb, 2010). The content is augmented such that the sizing constraints for both Lifetime Yield Optimization of Analog Circuits Considering Process Variations and Parameter Degradations 6
A CQUISITION OF C HANNEL S TATE I NFORMATION IN H ETEROGENEOUS C LOUD R ADIO A CCESS N ETWORKS : C HALLENGES AND R ESEARCH

INTRODUCTION The past four decades have witnessed a rapid proliferation of wireless networks and transmission technologies. Cellular networks have evolved from the first generation (1G) analog system in the 1980s to the second generation (2G) digital system in the 1990s to the third generation (3G) code-division multiple access (CDMA) system in the 2000s, and then to the fourth generation (4G) orthogonal frequencydivision multiplexing (OFDM) plus multipleinput multiple-output (MIMO) system in the current decade. The popularity of smart mobile phones and the appearance of high-definition applications such as high-quality video streaming continue to impose an increasing demand for high data rate wireless access and services on the existing cellular networks. It is estimated that mobile data traffic will grow 24 times between 2010 and 2015, and more than 200 times between 2010 and 2020 [1]. Heterogeneous networks (HetNets) have been proposed and are recognized as an effective architecture to meet the explosive growth of mobile data traffic [2]. A HetNet mainly consists of two types of nodes: low-power nodes (LPNs) and high-power nodes (HPNs). The LPN includes small cell base stations (BSs), femto BSs, and pico BSs, while the HPN contains macro and micro BSs. In a HetNet, LPNs and HPNs cooperate to provide high data services and ubiquitous coverage for user terminals (UTs), which is often referred to as coordinated multipoint (CoMP) transmission. Although CoMP can provide large cooperative gains and improve data rates of cell edge users, it still has some disadvantages in terms of spectral efficiency (SE) and energy efficiency (EE) due to the backhaul constraints, overhead channel delay, channel estimation accuracy, and high requirements on synchronization. To further improve SE and EE of CoMP, a new system architecture named the heterogeneous cloud radio access network (H-CRAN) was proposed in [3] that benefits from cloud computing and converging network units. In an H-CRAN, the HPNs are installed with massive antennas, and the LPNs are connected via highspeed optical fibers to a cloud often referred to as a baseband unit (BBU) pool. In addition, the LPNs only deal with RF band signal processing, while the cloud covers baseband signal processing for all LPNs. This centralized or autocracylike position of the cloud can provide better cooperation between BSs and lower the total energy consumption. It is worth noting that the architecture of the H-CRAN is similar to that of cloud radio access networks (C-RANs) [4]. The main differences between H-CRANs and C-RANs are the incorporation of HPNs in the H-CRAN and an evoluABSTRACT
Investigating the Metal Line Systems at z = 1.9 toward J2233−606 in the Hubble Deep Field South

The combination of Space Telescope Imaging Spectrograph (STIS) and optical spectroscopy with STIS imaging of the field surrounding J2233-606 affords a unique opportunity to study the physical nature of the quasar absorption-line systems. We present an analysis of the ionization state, chemical abundances, and kinematic characteristics of two metal line systems at z = 1.92 and 1.94 toward J2233-606. We focus on these two systems because (1) the observations provide full coverage of the Lyman series, and hence an accurate determination of their H I column densities, and (2) they exhibit many metal line transitions that allow for a measurement of their ionization state and chemical abundances. Line profile fits of the Lyman series for the two systems indicate log N(H I) = 17.15 ± 0.02 cm-2 evenly distributed between two components for the z = 1.92 system and log N(H I) = 16.33 ± 0.04 cm-2 for the z = 1.94 system. By comparing observed ionic ratios of C and Si against calculations performed with the CLOUDY software package, we find the ionization state is high and well constrained in both systems. Applying ionization corrections to the measured ionic column densities, we determine that the systems exhibit significantly different metallicities: ≈1/50 solar and less than 1/200 solar for the two components of z = 1.92 and ≈40% solar at z = 1.94. The most significant uncertainties regarding these measurements are associated with the assumptions inherent to the CLOUDY simulations. The properties of the z = 1.92 system are consistent with a low-metallicity galaxy (e.g., a dwarf galaxy) as well as absorption by large-scale structure of the intergalactic medium. On the other hand, the high metallicity of the z = 1.94 system suggests significant star formation and is therefore assumed associated with a galactic system. Furthermore, we predict it is the more likely to be observed with the STIS imaging and follow-up observations. If a galaxy is identified, our results provide direct measurements on the properties of the interstellar medium for a z ≈ 2 galaxy.
Depressive Symptoms : A Moderated Mediation Model Of Religious Coping And Spiritual Well-Being In African American Women

Religious coping and spiritual well-being were found to be culturally important resilience factors for African American women suffering from abuse and depressive symptoms. This study aimed to investigate whether: (1) spiritual well-being and its two components of existential and religious well-being mediate the Intimate Partner Violence (IPV)-Depressive Symptoms (DS) link; (2) positive and negative religious coping moderate the IPV-DS association; and (3) the mediating effect of spiritual well-being in the IPV-DS link is moderated by level of religious coping (i.e., moderated mediation). The study utilized data from 208 low income, suicidal and abused African American women, ages 18-55. Only the existential component of spiritual wellbeing was found to fully mediate the IPV-DS link. This indirect effect weakened at higher levels of negative religious coping. As predicted, higher levels of negative religious coping were associated with higher levels of depressive symptoms. Surprisingly, higher levels of negative religious coping were also associated with increases in existential well-being which, in turn, led to decrease in depressive symptoms. The findings underscore the importance of addressing existential well-being and religious coping in clinical interventions and in training for mental health professionals. Clinical and research implications of these findings are discussed and future directions recommended.
FEATURE EXTRACTION FOR CLASSIFICATION: A SURVEY I. LINEAR METHODS

The growing volume of information available as input in pattern classification systems has imposed the use of pre-processing techniques which have the purpose of reducing the feature space dimensions. The references in this domain are very large and only an exhaustive approach can be made. This article presents the most used linear methods, comparing their advantages and disadvantages, and showing the best suited methods for several categories of data.
ONLINE TESTING EMBEDDED SYSTEMS: ADAPTING AUTOMATIC CONTROL TECHNIQUES TO MICROELECTRONICS TESTING

Abstract This paper is aimed at exploiting Fault Detection and Isolation (FDI) techniques widely known in automatic control for solving online test problem in embedded Integrated Circuits (ICs). Before reaching this aim, we will briefly review the field of microelectronics testing, introducing basic concepts and techniques. We will next introduce FDI model-based approaches and their application for online testing of embedded ICs considering linear systems with potential faults and disturbances. The parity relation-based residual is specially suitable for this type of application. As an example, we will apply it to concurrent fault detection in a digital embedded filter. The proposed scheme will then be illustrated for a linear digital pass-band elliptic filter.
Abstract—the Position Information of the Nodes in a Wsn Has Become Crucial for Many Advanced Features Such as Routing, Clustering, and Context-based Applications. If the Localization

algorithm is distributed, the sensor nodes are able to calculate the position on their own without the help of a central computer. In this case the design of localization algorithms is a challenge due to the fact that the nodes are limited in relation to the memory capacity, processing power and energy consumption. In this paper we analyze the suitability of a distributed fingerprint-based localization algorithm, where sensor nodes store relevant information called fingerprints in order to use this knowledge during the position calculation. The localization algorithm has been evaluated in a three dimensional scenario using the framework MIXIM of the simulator tool OMNET++.
Ordinally Bayesian incentive compatible voting rules

We study strategic voting after weakening the notion of strategy-proofness to Ordinal Bayesian Incentive Compatibility (OBIC). Under OBIC, truth-telling is required to maximize the expected utility of every voter, expected utility being computed with respect to the voter's prior beliefs and under the assumption that everybody else is also telling the truth. We show that for a special type of priors, i.e., the uniform priors, there exists a large class of social choice functions that are OBIC. However, for priors that are generic in the set of independent beliefs, a social choice function is OBIC only if it is dictatorial. This result underlines the robustness of the Gibbard-Satterthwaite Theorem. Copyright The Econometric Society 2004.
Title: Contribution of the Cesr-regulated Genes Llmg0169 and Llmg2164-2163 To

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Lactotoccus lactis is one of the main components of the starter cultures used in cheese manufacture. As starter, L. lactis must tolerate harsh conditions encountered either during their production in bulk quantities or during dairy products processing. To face these hostile conditions, bacteria monitor the environment and respond by modifying gene expression appropriately. Previous transcriptomic studies showed that the two component system CesSR is the main pathway that triggers the cell envelope stress response in L. Lactis treated with lactococcin 972 (Lcn972), a cell wall synthesis inhibiting bacteriocin. Among the CesR regulated genes, llmg0169 and the operon llmg2164-2163, encoding proteins of unknown function, are among the highest up-regulated genes after activation of CesSR. In this study, we have assessed the contribution of these genes to the survival of L. Lactis to different technologically-relevant stresses. Overexpressing and knock-out mutants of the genes were generated and their viability to low pH, heat, freeze-drying, presence of NaCl, cell wall antimicrobials and lytic phages attack was compared to the wildtype strain. The genes llmg0169 and llmg2164-2163 contributed differently to L. lactis fitness. L. lactis ∆llmg0169 was very sensitive to heat treatment while L. lactis ∆llmg2164 was more sensitive to NaCl. Absence of both genes also compromised viability at low pH. On the contrary, higher expression levels of llmg0169 and llmg2164-2163, up to 26and 14-fold increase determined by qRT-PCR, respectively, did not enhance L. lactis survival in any of the above stressful conditions (heat, pH and NaCl) or after freeze-drying. All the mutants displayed a similar phage susceptibility profile. Overexpression of llmg2164-2163 seemed to specifically protect L. lactis against the bacteriocin Lcn972 but not against other cell wall active antimicrobials. Based on our phenotypic analysis, the investigated genes are required to mount a proper response to guarantee survival of L. lactis under technologically-relevant stresses and their functionality could be a useful marker to select robust dairy starters.
Confounding and control in a multivariate system. An issue in causal attribution

It is widely agreed that, in establishing whether variable X causes variable Y, a third variable Z may confound the relation and thus hinder causal assessment. The solution developed within the ‘traditional’ framework is to control for any third variable, susceptible of confounding the relation between X and Y. This paper examines complex systems of variables, characterised by multiple causes and multiple effects. The paper advances the view that in such contexts confounding is a moot issue, under a suitable specification of the causal model. When networks of causal relations are considered, possible confounders are included in the appropriate causal paths from the causes to the outcome. The challenge for the model builder then amounts to developing a structural model that specifies the role of variables in each path, rather than just controlling for possible confounders.
An optimized vector quantization for color image compression

Image Data compression using vector quantization (VQ) has received a lot of attention in the recent years because of its optimality in rate distortion and adaptability. A fundamental goal of data compression is to reduce the bit rate for transmission or data storage while maintaining an acceptable fidelity or image quality. The combination of subband coding and vector quantization can provide a powerful method for compressing color images. Most of the existing VQ algorithms however suffer from a number of serious problems like long search process, codebook initialization, getting trapped in local minima, etc. This work investigates the development of an image compression algorithm using a variable block size vector quantization technique for generation of optimal codebook by employing a neuro-fuzzy clustering approach to ensure minimum distortion. Each color image is decomposed into R, G, and B color planes prior to application of wavelet transform and vector quantization to each color plane. Each color plane is preprocessed by performing multiresolution wavelet decomposition. The multiresolution nature of the discrete wavelet transform is utilized to decompose the images into more directionally decorrelated sub-images, which are more suitable for quantization and coding. Vector quantization is performed on each of the subimages at different resolutions and a multiresolution codebook scheme is utilized. This new approach to image compression facilitates generation of an improved globally optimal codebook, and a simpler search scheme. Finally, the codebooks generated from the three encoded color planes are entropy coded for obtaining higher compression at minimum distortion. Each color plane codebook is decoded and the reconstructed color planes are combined to form the final reconstructed image. The reconstructed images are compared with those of other standard compression algorithms, in terms of Mean square error (MSE), and Peak signal-to-noise rafio (PSNR).
WEIGHTED GRANULAR BEST MATCHING ALGORITHM FOR CONTEXT-AWARE COMPUTING SYSTEMS

iv ÖZ . v DEDICATION.vi ACKNOWLEDGMENTS . vii TABLE OF CONTENTS . viii LIST OF TABLES.xi LIST OF FIGURES . xii LIST OF ACRONYMS . xiii CHAPTER
President's Address Spring 2014 Addresses for Euromech Officers

This work summarises the impact of Coriolis forces on the formation of a vortex ring. The initial formation of the ring and subsequent transient migration to a steady structure is described, focussing on the processes by which the transition occurs. A side-by-side comparison of vortices generated with and without the impact of Coriolis forces is made using 3 component planar velocity field data in a reference plane moving with the vortex ring. Subsequent to generation, an axially aligned vortex wake is formed, which is shown to induce a secondary vortex shedding phenomenon.
Principles of mathematical analysis

Chapter 1: The Real and Complex Number Systems Introduction Ordered Sets Fields The Real Field The Extended Real Number System The Complex Field Euclidean Spaces Appendix Exercises Chapter 2: Basic Topology Finite, Countable, and Uncountable Sets Metric Spaces Compact Sets Perfect Sets Connected Sets Exercises Chapter 3: Numerical Sequences and Series Convergent Sequences Subsequences Cauchy Sequences Upper and Lower Limits Some Special Sequences Series Series of Nonnegative Terms The Number e The Root and Ratio Tests Power Series Summation by Parts Absolute Convergence Addition and Multiplication of Series Rearrangements Exercises Chapter 4: Continuity Limits of Functions Continuous Functions Continuity and Compactness Continuity and Connectedness Discontinuities Monotonic Functions Infinite Limits and Limits at Infinity Exercises Chapter 5: Differentiation The Derivative of a Real Function Mean Value Theorems The Continuity of Derivatives L'Hospital's Rule Derivatives of Higher-Order Taylor's Theorem Differentiation of Vector-valued Functions Exercises Chapter 6: The Riemann-Stieltjes Integral Definition and Existence of the Integral Properties of the Integral Integration and Differentiation Integration of Vector-valued Functions Rectifiable Curves Exercises Chapter 7: Sequences and Series of Functions Discussion of Main Problem Uniform Convergence Uniform Convergence and Continuity Uniform Convergence and Integration Uniform Convergence and Differentiation Equicontinuous Families of Functions The Stone-Weierstrass Theorem Exercises Chapter 8: Some Special Functions Power Series The Exponential and Logarithmic Functions The Trigonometric Functions The Algebraic Completeness of the Complex Field Fourier Series The Gamma Function Exercises Chapter 9: Functions of Several Variables Linear Transformations Differentiation The Contraction Principle The Inverse Function Theorem The Implicit Function Theorem The Rank Theorem Determinants Derivatives of Higher Order Differentiation of Integrals Exercises Chapter 10: Integration of Differential Forms Integration Primitive Mappings Partitions of Unity Change of Variables Differential Forms Simplexes and Chains Stokes' Theorem Closed Forms and Exact Forms Vector Analysis Exercises Chapter 11: The Lebesgue Theory Set Functions Construction of the Lebesgue Measure Measure Spaces Measurable Functions Simple Functions Integration Comparison with the Riemann Integral Integration of Complex Functions Functions of Class L2 Exercises Bibliography List of Special Symbols Index
A Study of Distributed Evolutionary Algorithms for Multi-objective Optimisation

Most popular Evolutionary Algorithms for single multi-objective optimisation are motivated by the reduction of the computation time and the resolution larger problems. A promising alternative is to create new distributed schemes that improve the behaviour of the search process of such algorithms. In the multi-objective optimisation problems, more exploration of the search space is required to obtain the whole or the best approximation of the Pareto front. Almost all proposed Parallel Multi-Objective Evolutionary Algorithms (PMOEAs) are based on the specialisation concept which means dividing the objective and/or the search space then assigning each part to a processor. One processor called the organiser or the coordinator is usually charged to direct the whole algorithm. In this paper, we present a new parallel scheme of multi-objective evolutionary algorithms which is based on a clustering technique. This new parallel algorithm is implemented and compared to three PMOEAs which are cone-separation [1], Divided Range Multi-Objective Genetic Algorithm (DRMOGA) [8] and a Parallel Strength Pareto Evolutionary Algorithm (PSPEA) based on the island model without migration.
Recent Update on MRSA

Methicillin-resistant S. aureus (MRSA) isolates are resistant to all available penicillins and other ß-lactam antimicrobial drugs. Staphylococcus aureus is the most commonly isolated human bacterial pathogen and is an important cause of skin and soft tissue infections (SSTIs), endovascular infections, pneumonia, septic arthritis, endocarditis, osteomyelitis, foreign-body infections, and sepsis. They were once confined largely to hospitals and health care environments, and patients frequenting these facilities, however, there has been an explosion in the number of MRSA infections in the community that have been responsible for a large proportion of the increased disease burden in the last decade. This review deals with the pathogenesis, virulence mechanisms, risk factors, and clinical presentation, diagnosis and treatment strategies for MRSA.