Miracle-dz/UniFAR-FTUs huggingface dataset:
BEAM TEST STAND OF THE RFQ-DRIFTTUBE-COMBINATION FOR THE THERAPY CENTER IN HEIDELBERG *

A beam test stand for the Heidelberg medicine RFQ [1] has been installed at the IAP in Frankfurt. The installation consists of a 8 keV/u H + duoplasmatron ion source, the 400 keV/u RFQ itself and several diagnostic elements comprising a slit-grid emittance measurement system for scanning the transverse beam profile and a bending magnet for measuring the longitudinal beam properties. The test installation will be described in detail, first measurements will be presented and compared to corresponding beam dynamic simulations.
Opportunities for Biorenewables in Oil Refineries

The purpose of this study was to evaluate the potential for using biorenewable feedstocks in oil refineries. Economic analyses were conducted, with support from process modeling and proof of principle experiments, to assess a variety of potential processes and configurations. The study considered two primary alternatives: the production of biodiesel and green diesel from vegetable oils and greases and opportunities for utilization of pyrolysis oil. The study identified a number of promising opportunities for biorenewables in existing or new refining operations. DOE F 241.3 OMB Control No. (2-01) p. 3 of 4 INSTRUCTIONS 1910-1400 Purpose: DOE F 241.3 provides the Office of Scientific and Technical Information (OSTI) information required to appropriately identify, process, and/or announce and disseminate the results of work funded by the U.S. Department of Energy (DOE). For general information or assistance with this form, contact OSTI at (865) 241-6435, or at the following e-mail address: 241user@adonis.osti. gov. When to use: Submit this form with each scientific and technical information (STI) Product. Electronic format is the preferred method for submitting the announcement record and STI Product. When submitting electronically, use the electronic version of the form (http://www.osti.gov/elink; discuss with your DOE Contracting Officer). Describing the data fields: Descriptions of the various DOE F 241.3 data fields, STI Products, format, etc., can be found in ATTACHMENT 3 and other sections of the DOE G 241.1-1A, Guide to the Management of Scientific and Technical Information. Available online at http://www.osti. gov/stip/ DOE Financial Assistance Recipients/Contractors Recipients and Contractors should complete Parts I and II of the form and forward the form along with the STI product to the DOE Contracting Officer who will complete the rest of the form and submit the package to OSTI. NOTE: Sensitive, proprietary, or other STI Products for which access is restricted by statute or regulation shall not be transmitted via open systems networks (e.g., the Internet) unless authorization and/or encryption has been coordinated with OSTI in advance. This form, unless it in itself is classified, can be transmitted via open systems networks (.e.g, the Internet). RECORD STATUS This is a required field. The record status identifies the announcement record or the STI Product as new, or revised. If the record status is not provided, the record is considered "New. " Part I: STI PRODUCT DESCRIPTION (To be completed by Recipient/Contractor) A. STI PRODUCT IDENTIFIERS. 1. Report/Product Number(s). This is a required field. The unique primary report or product number assigned to the STI product. If a report number is not provided, the word "NONE" should be entered. Following are examples of report number formats for multiple volumes, parts, or revisions:
A Cognition-Based Control System for Autonomous Robots

Most approaches to controlling autonomous systems require extensive pre-mission preparation, intensive effort by the human operator, or have strong limitations on the range of possible missions that can be accomplished. In this paper we describe an approach called Cognitive Patterns that promises to alleviate these challenges by replicating three key processes of human cognition—pattern generation, perception/action, and adaptation—and instantiating them in a new architecture which can then be embedded into an autonomous system. An early version of this approach connected high-level knowledge representations in an ontology with a robot's sensing and acting abilities. The advantages of this approach were then demonstrated in a simulation environment. A more refined version, based on lessons learned and called Cognitive Patterns Knowledge Generation, can deal with anomalies, unexpected events, and uncertainties, and is also described in terms of its components, their interactions, and benefits.
Advice to policy-makers for improving services to the drug-death bereaved

Aims: The objective of this study is to contribute to an improvement of bereavement services and experiences for the bereaved after drug-related deaths (DRDs) by investigating their expressed opinions on what would constitute improvements. Methods: As part of a larger survey questionnaire, we asked people bereaved by DRDs what advice they would give to politicians to improve bereavement services. Out of 255 respondents, we received 196 written statements of advice, 83 focusing on the time after death. Two-thirds of these respondents were either parents or siblings, the other third were other family members or close friends. A thematic analysis was conducted to examine the written statements. Results: We found four central themes: broad-spectrum help, routinised help, respectful help and competent help. The advice represents a long list of psychosocial support to ideally be offered on a regular and long-term basis. Furthermore, the bereaved also discussed the cognitive and normative side of the services by including considerations about stigma and respect, and the need for more research- and experience-based knowledge about their experiences both before and after DRDs. Conclusions: Many of the services sought by the bereaved are already in place and described in national guidelines for follow-up strategies after sudden unexpected deaths. DRDs, however, has not been included as a task for the services and are not explicitly mentioned in these guidelines. The scope of research and policymaking on drug problems and DRDs should be broadened to include families and social networks in order to make the group more visible and strengthen their influence on policy.
Variable speed brushless DC motor drive for household refrigerator compressor

Household refrigerators usually employ on/off-controlled, constant-speed, single-phase induction motors as compressor drives. This paper describes results obtained on a prototype refrigerator fitted with a variable-speed, three-phase, brushless DC motor drive. Considerations regarding the motor construction are described, and test results of the motor and drive efficiency are presented and discussed.
A New Augmented Lagrangian Method for MPCCs - Theoretical and Numerical Comparison with Existing Augmented Lagrangian Methods

We propose a new augmented Lagrangian (AL) method for solving the mathematical program with complementarity constraints (MPCC), where the complementarity constraints are left out of the AL function and treated directly. Two observations motivate us to propose this method: The AL subproblems are closer to the original problem in terms of the constraint structure; and the AL subproblems can be solved efficiently by a nonmonotone projected gradient method, in which we have closed-form solutions at each iteration. The former property helps us show that the proposed method converges globally to an M-stationary (better than C-stationary) point under MPCC relaxed constant positive linear dependence condition. Theoretical comparison with existing AL methods demonstrates that the proposed method is superior in terms of the quality of accumulation points and the strength of assumptions. Numerical comparison, based on problems in MacMPEC, validates the theoretical results.
Análise Exploratória de Atributos Textuais em Bases de Dados para Identificação de Campos Sensíveis

A iminente implantação da Lei Geral de Proteção de Dados Pessoais brasileira torna urgente a criação de técnicas automatizadas para anonimização de bases de dados. As ferramentas existentes são dependentes de que um especialista manualmente escolha os campos de interesse. Neste trabalho, propõe-se o uso de algoritmos de aprendizado de máquina em atributos textuais a fim de explorar como identificar nomes e outras informações sensíveis. Com isso, espera-se fomentar aplicações capazes de classificar automaticamente campos sensíveis em bancos de dados em um passo anterior à anonimização. A avaliação experimental da representação por frequência de digramas proposta, mostra que é possível obter modelos simples de aprendizado de máquina, como florestas aleatórias e redes neurais, capazes de classificar nomes de pessoas, endereços e descrições textuais com alta taxa de acurácia (97%) usando 676 características.
Embedded Multiprocessor System-on-Chip for Access Network Processing

Master's Thesis from the year 2007 in the subject Computer Science - Applied, grade: 1.0, Technical University of Munich (Institute for Informatics), 82 entries in the bibliography, language: English, abstract: Multicore systems are dominating the processor market; they enable the increase in computing power of a single chip in proportion to the Moore's law-driven increase in number of transistors. A similar evolution is observed in the system-on-chip (SoC) market through the emergence of multi-processor SoC (MPSoC) designs. Nevertheless, MPSoCs introduce some challenges to the system architects concerning the efficient design of memory hierarchies and system interconnects while maintaining the low power and cost constraints. In this master thesis, I try to address some of these challenges: namely, non-cache coherent DMA transfers in MPSoCs, low instruction cache utilization by OS codes, and factors governing the system throughput in MPSoC designs. These issues are investigated using the empirical and simulation approaches. Empirical studies are conducted on the Danube platform. Danube is a commercial MPSoC platform that is based on two 32-bit MIPS cores and developed by Infineon Technologies AG for deployment in access network processing equipments such as integrated access devices, customer premises equipments, and home gateways. Simulation-based studies are conducted on a system based on the ARM MPCore architecture. Achievements include the successful implementation and testing of novel hardware and software solutions for improving the performance of non-cache coherent DMA transfers in MPSoCs. Several techniques for reducing the instruction cache miss rate are investigated and applied. Finally, a qualitative analysis of the impact of instruction reuse, number of cores, and memory bandwidth on the system throughput in MPSoC systems is presented.
A current mode CMOS voltage reference

A current mode CMOS voltage reference uses a p-channel MOSFET threshold voltage extractor circuit to create a current that is inversely proportional to temperature. This current is summed with a current that is proportional to temperature into a resistor to create a voltage that is, to the first order, temperature independent. The output voltage is scalable by adjusting the size of the summing resistor. The circuit operates over temperature from 0 to 100/spl deg/C with a power supply voltage between 3.3 and 7 V. Experimental results show that over these conditions, the output voltage varies by /spl plusmn/3%.
Clocking and Potential Effects in Combustor–Turbine Stator Interactions

Investigations of combustors and turbines separately have been carried out for years by research institutes and aircraft engine companies, but there are still many questions about the interaction effect. In this paper, a prediction of a turbine stator’s potential effect on flow in a combustor and the clocking effect on temperature distribution in a nozzle guide vane are discussed. Numerical simulation results for the combustor simulator and the nozzle guide vane (NGV) of the first turbine stage are presented. The geometry and flow conditions were defined according to measurements carried out on a test section within the framework of the EU FACTOR (full aerothermal combustor–turbine interactions research) project. The numerical model was validated by a comparison of results against experimental data in the plane at a combustor outlet. Two turbulence models were employed: the Spalart–Allmaras and Explicit Algebraic Reynolds Stress models. It was shown that the NGV potential effect on flow distribution at the combustor–turbine interface located at 42.5% of the axial chord is weak. The clocking effect due to the azimuthal position of guide vanes downstream of the swirlers strongly affects the temperature and flow conditions in a stator cascade.
Image denoising algorithm of compressed sensing based on alternating direction method of multipliers

In this paper, we propose an image denoising algorithm for compressed sensing based on alternating direction method of multipliers (ADMM). We prove that the objective function of the iterates approaches the optimal value. We also prove the [Formula: see text] convergence rate of our algorithm in the ergodic sense. At the same time, simulation results show that our algorithm is more efficient in image denoising compared with existing methods.
Bayesian phylogenetic analysis of linguistic data using BEAST

Bayesian phylogenetic methods provide a set of tools to efficiently evaluate large linguistic datasets by reconstructing phylogenies—family trees—that represent the history of language families. These methods provide a powerful way to test hypotheses about prehistory, regarding the subgrouping, origins, expansion, and timing of the languages and their speakers. Through phylogenetics, we gain insights into the process of language evolution in general and into how fast individual features change in particular. This article introduces Bayesian phylogenetics as applied to languages. We describe substitution models for cognate evolution, molecular clock models for the evolutionary rate along the branches of a tree, and tree generating processes suitable for linguistic data. We explain how to find the best-suited model using path sampling or nested sampling. The theoretical background of these models is supplemented by a practical tutorial describing how to set up a Bayesian phylogenetic analysis using the software tool BEAST2.
Ground motion prediction maps using seismic microzonation data and machine learning

Abstract. Past seismic events worldwide demonstrated that damage and death toll depend on both the strong ground motion (i.e., source effects) and the local site effects. The variability of earthquake ground motion distribution is caused by local stratigraphic and/or topographic setting and buried morphologies, that can give rise to amplification and resonances with respect to the ground motion expected at the reference site. Therefore, local site conditions can affect an area with damage related to the full collapse or loss in functionality of facilities, roads, pipelines, and other lifelines. To this concern, the near real time prediction of damage pattern over large areas is a crucial issue to support the rescue and operational interventions. A machine learning approach was adopted to produce ground motion prediction maps considering both stratigraphic and morphological conditions. A set of about 16'000 accelometric data and about 46'000 geological and geophysical data were retrieved from Italian and European databases. The intensity measures of interest were estimated based on 9 input proxies. The adopted machine learning regression model (i.e., Gaussian Process Regression) allows to improve both the precision and the accuracy in the estimation of the intensity measures with respect to the available near real time predictions methods (i.e., Ground Motion Prediction Equation and shaking maps). In addition, maps with a 50 × 50 m resolution were generated providing a ground motion variability in agreement with the results of advanced numerical simulations based on detailed sub-soil models. The variability at short distances (hundreds of meters) was demonstrated to be responsible for 30–40 % of the total variability of the predicted IM maps, making it desirable that seismic hazard maps also consider short-scale effects.
Design And Control System of Automatic Control System of Coal Flow on Belt Conveyor Installation

In a power plant unit whose main fuel is coal, there is generally use a belt conveyor installation. This conveyor belt serves to supply coal from the crusher unit to the combustion chamber of the power generation unit. In this study, we discuss a case where the installation of a belt conveyor which was initially only one line was then made a new branch that supplies coal to other power generating units. Equitable capacity distribution and continuity of coal distribution are the main focus of this study. Therefore, a design of automatic control system of coal flow divider on belt conveyor installation was designed. The working principle of this coal flow splitting system is to control the movement of the straight blade plough that directs the flow of coal to each unit at the certain time and continuously. Straight blade plough in the form of steel metal plate with a thickness of about 10 millimeters in which one end is connected to the end of the pneumatic cylinder. Automatic control system of coal flow divider in belt conveyor installation designed using CX-Programmer and CX-Designer applications. CX-Programmer serves to create automatic control logic concepts. While the CX-designer functions to create a Human Machine Interface (HMI), making it easier for operators to control the course of the coal supply process. The results of this study are in the form of control logic lines that can be applied to Programmable Logic Control (PLC) device and Human Machine Interface (HMI) equipment.
An ultrasonically controlled robot submarine for pipe inspection

A model submarine with four legs and without an umbilical is described that is both radio controlled and ultrasonically controlled to walk in a pipe. The ultrasonic communication system is described together with the problem and solutions encountered and worked out. Finally, the leg kinematics, and their actuation system and control are discussed.
Sedentary Behavior and Happiness: The Mediation Effects of Social Capital

Abstract Background and Objectives This study aimed to examine the associations between time spent in 6 different domains of sedentary behavior and happiness and whether social capital mediated such associations among adults and older adults living in a rural area of Japan. Research Design and Methods Cross-sectional data from 3,357 participants (mean age: 60 ± 16 years) were used. 6 domains of sedentary behavior, happiness, and social capital were assessed using a self-report questionnaire. Age-stratified multivariable linear regression models adjusted for covariates were used to examine the associations between 6 domains of sedentary behavior and happiness. For relationships where the direct effect was significant, we tested the mediating effects of 2 social capital measures. Results Among both adults and older adults, more time spent viewing television was significantly associated with lower happiness scores, and more time spent engaging in other leisure activities was significantly associated with higher happiness scores. In addition, more time spent using cell phones and computers was significantly associated with lower happiness scores among the adults. Engaging in activities with neighbors significantly mediated the relationship between other leisure activities and happiness in the adults and older adults, and between television viewing and happiness in the older adults. Discussion and Implications Our findings indicated that less television viewing and more mentally active sedentary behavior (e.g., talking with others and engaging in hobbies) were associated with greater happiness. One aspect of social capital, engaging in activities with neighbors, acts as a potential mediator for relationships between sedentary behavior and happiness.
Penile implant infection factors: a contemporary narrative review of literature

Objective We aim to review and summarize published literature that features implanted penile devices and details infection of these devices as a complication. In particular, we will detail the factors that influence infection of penile implants. Background Types of penile prostheses (PP) include inflatable implants and semirigid implants; these are utilized for treatment of erectile dysfunction. Likely the most feared complication of penile implants is infection. There are a handful of factors that are implicated in device infection. Methods Searches were performed using MEDLINE and PubMed databases using keywords and phrases ‘penile implant AND infection’; ‘penile prosthesis AND infection’; ‘penile implant infection’. We have presented results from our literature search. We divided these into ‘Surgical Elements’ and ‘Patient Selection and Factors. ’ Each topic is discussed in its own section. Conclusions Strides have been made since the initial penile prosthesis (IPP) surgeries to improve infection rates including diabetes control, antibiotic coating of devices, and antibiotic implementation. Going forward, more studies, especially randomized control trials, need to focus on defining levels of diabetic control (sugar control and A1C control), determining the role of metabolic syndrome in infection promotion and determining laboratory values which could be predictive of infection. We present a discussion of important factors to consider in the realm of PP infections. In addition, we include studies which discuss topics for future directions in decreasing the number of infections seen with PP.
Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion

PurposeThe first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.Design/methodology/approachUsing primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.FindingsThis study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.Originality/valueThe uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.