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In der Reihe der nachwachsenden Rohstoffe besitzt Holz als erneuerbare und umweltfreundliche Ressource ein großes Potenzial. Über 11 Mio. ha Holz, das laut der Fachagentur für nachwachsende Rohstoffe (FNR) auch für industrielle Zwecke genutzt werden kann, wuchsen im Jahr 2013 allein auf bundesdeutscher Fläche. 56,8 Mio. m³ jährlicher Holzeinschlag in den letzten zehn Jahren wurde zu knapp der Hälfte stofflich und der Rest energetisch verwertet. Im Rahmen dieser Arbeit konnte auf der Basis vom Holz der Buche, die nach Fichte und Kiefer die dritthäufigste Baumart in Deutschland ist und 15% der deutschen Waldfläche ausmacht, die Fraktionierung der polymeren Hauptbestandteile mit niedrigem energetischen Einsatz erreicht werden. Hierbei werden in einem nachgeschalteten Extraktionsprozess die beiden Komponenten Hemicellulose und Lignin in flüssiger Form von der finalen festen Cellulosefraktion abgetrennt. Die Extraktion der Hemicellulose erfolgt durch eine Liquid Hot Water (LHW)-Behandlung. Untersucht wird der katalytische Zusatz anorganischer Säuren wie H₃PO₄ und H₂SO₄. Im Hinblick auf die weitere Verwertung von Lignin zu aromatischen Synthesebausteinen kommt die Organosolv-Extraktion mit einem Ethanol/Wasser-Gemisch zum Einsatz. Von Vorteil ist die weitere Verwendung beider Stoffströme ohne Fällungsschritt und nachteiliger Verdünnung der Hemicellulose.
We present first results from a newly developed monitoring station for a closed loop geothermal heat pump test installation at our campus, consisting of helix coils and plate heat exchangers, as well as an ice-store system. There are more than 40 temperature sensors and several soil moisture content sensors distributed around the system, allowing a detailed monitoring under different operating conditions.In the view of the modern development of renewable energies along with the newly concepts known as Internet of Things and Industry 4.0 (high-tech strategy from the German government), we created a user-friendly web application, which will connect the things (sensors) with the open network (www). Besides other advantages, this allows a continuous remote monitoring of the data from the numerous sensors at an arbitrary sampling rate.Based on the recorded data, we will also present first results from numerical simulations, taking into account all relevant heat transport processes.The aim is to improve the understanding of these processes and their influence on the thermal behavior of shallow geothermal systems in the unsaturated zone. This will in turn facilitate the prediction of the performance of these systems and therefore yield an improvement in their dimensioning when designing a specific shallow geothermal installation.
Reconstructive surgery and tissue replacements like ureters or bladders reconstruction have been recently studied, taking into account growth and remodelling of cells since living cells are capable of growing, adapting, remodelling or degrading and restoring in order to deform and respond to stimuli. Hence, shapes of ureters or bladders and their microstructure change during growth and these changes strongly depend on external stimuli such as training. We present the mechanical stimulation of smooth muscle cells in a tubular fibrin-PVDFA scaffold and the modelling of the growth of tissue by stimuli. To this end, mechanotransduction was performed with a kyphoplasty balloon catheter that was guided through the lumen of the tubular structure. The bursting pressure was examined to compare the stability of the incubated tissue constructs. The results showed the significant changes on tissues with training by increasing the burst pressure as a characteristic mechanical property and the smooth muscle cells were more oriented with uniformly higher density. Besides, the computational growth models also exhibited the accurate tendencies of growth of the cells under different external stimuli. Such models may lead to design standards for the better layered tissue structure in reconstructing of tubular organs characterized as composite materials such as intestines, ureters and arteries.
Influence of refrigerated storage on tensile mechanical properties of porcine liver and spleen
(2015)
Ein neues tragendes, lagenweise aufgebautes Holzbau-Wandsystem und seine ökonomische und statische Entwicklung werden vorgestellt. Randbedingungen wie Nachhaltigkeit, Ressourceneffizienz und eine beanspruchungsadaptive Konstruktionsweise sind für diese innovative Bauteilentwicklung von zentraler Bedeutung. Eine wesentliche Herausforderung ist die Herstellung der Verbindung der Lagen untereinander zu einem bauphysikalisch und statisch leistungsfähigen Wandsystem. Die Tragfähigkeit und Steifigkeit verschiedener Verbindungsvarianten wurden ebenso wie die Eigenschaften der Wandelemente analytisch, numerisch und experimentell untersucht.
Untersuchungen zur Tragfähigkeit und Steifigkeit eines neuartigen Wandelements in Holzbauweisen
(2018)
Dieser verständliche Einstieg in SAP S/4HANA führt Sie anhand des Beispielunternehmens Global Bike durch die zentralen Abläufe in Vertrieb, Einkauf, Rechnungswesen, Produktion und Lagerverwaltung. Sie werden mit den betriebswirtschaftlichen Grundlagen, den relevanten Organisationsstrukturen und Stammdaten sowie den Prozessen vertraut gemacht. Mithilfe von Praxisbeispielen und Fallstudien sind Sie schon bald SAP-S/4HANA-Profi – für mehr Erfolg in Studium und Beruf!
This easy-to-understand introduction to SAP S/4HANA guides you through the central processes in sales, purchasing and procurement, finance, production, and warehouse management using the model company Global Bike. Familiarize yourself with the basics of business administration, the relevant organizational data, master data, and transactional data, as well as a selection of core business processes in SAP. Using practical examples and tutorials, you will soon become an SAP S/4HANA professional!
Tutorials and exercises for beginners, advanced users, and experts make it easy for you to practice your new knowledge. The prerequisite for this book is access to an SAP S/4HANA client with Global Bike version 4.1.
- Business fundamentals and processes in the SAP system
- Sales, purchasing and procurement, production, finance, and warehouse management
- Tutorials at different qualification levels, exercises, and recap of case studies
- Includes extensive download material for students, lecturers, and professors
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
Intensive poultry operation systems emit a considerable volume of inorganic and organic matter in the surrounding environment. Monitoring cleaning properties of exhaust air cleaning systems and to detect small but significant changes in emission characteristics during a fattening cycle is important for both emission and fattening process control. In the present study, we evaluated the potential of near-infrared spectroscopy (NIRS) combined with chemometric techniques as a monitoring tool of exhaust air from poultry operation systems. To generate a high-quality data set for evaluation, the exhaust air of two poultry houses was sampled by applying state-of-the-art filter sampling protocols. The two stables were identical except for one crucial difference, the presence or absence of an exhaust air cleaning system. In total, twenty-one exhaust air samples were collected at the two sites to monitor spectral differences caused by the cleaning device, and to follow changes in exhaust air characteristics during a fattening period. The total dust load was analyzed by gravimetric determination and included as a response variable in multivariate data analysis. The filter samples were directly measured with NIR spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA), and factor analysis (FA) were effective in classifying the NIR exhaust air spectra according to fattening day and origin. The results indicate that the dust load and the composition of exhaust air (inorganic or organic matter) substantially influence the NIR spectral patterns. In conclusion, NIR spectroscopy as a tool is a promising and very rapid way to detect differences between exhaust air samples based on still not clearly defined circumstances triggered during a fattening period and the availability of an exhaust air cleaning system.
Meitner-Auger-electron emitters have a promising potential for targeted radionuclide therapy of cancer because of their short range and the high linear energy transfer of Meitner-Auger-electrons (MAE). One promising MAE candidate is 197m/gHg with its half-life of 23.8 h and 64.1 h, respectively, and high MAE yield. Gold nanoparticles (AuNPs) that are labelled with 197m/gHg could be a helpful tool for radiation treatment of glioblastoma multiforme when infused into the surgical cavity after resection to prevent recurrence. To produce such AuNPs, 197m/gHg was embedded into pristine AuNPs. Two different syntheses were tested starting from irradiated gold containing trace amounts of 197m/gHg. When sodium citrate was used as reducing agent, no 197m/gHg labelled AuNPs were formed, but with tannic acid, 197m/gHg labeled AuNPs were produced. The method was optimized by neutralizing the pH (pH = 7) of the Au/197m/gHg solution, which led to labelled AuNPs with a size of 12.3 ± 2.0 nm as measured by transmission electron microscopy. The labelled AuNPs had a concentration of 50 μg (gold)/mL with an activity of 151 ± 93 kBq/mL (197gHg, time corrected to the end of bombardment).
Die Applikation „Slot“ ist eine lehrbegleitende Kommunikations- und Kooperationsplattform, die eine zeitgemäße Lehre, Studienorganisation und Präsentation zulässt.
Slot dient dabei nicht nur als Hilfestellung für Lehrende und Lernende, sondern ermöglicht auch die vollständige Durchführung von effizientem Unterricht. Den Lernenden soll maximale Kontrolle zur Erarbeitung ihres Wissens und Übersichtlichkeit in der Kommunikation geboten werden. Um für die unterschiedlichen Nutzergruppen ein benutzerfreundliches System zu schaffen, steht eine breitgefächerte Funktionsauswahl zur Verfügung: Videochat, Messenger, VR-Raum, Whiteboard, Aufgabenübersicht, Datenabgabe, Kalender, Profil und ToDo-List. Die Nutzungsmöglichkeiten können individuell auf die unterschiedlichen Nutzergruppen und deren entsprechenden Bedürfnissen angepasst werden.
Welchen Einfluss haben Erinnerungen auf unser Bewusstsein und wie definieren sie uns als Individuum? Erinnerungen gehen verloren — sei es durch einfaches Vergessen, traumatische Erlebnisse oder Krankheit. Aber wie sehr wirkt sich das Vergessen auf unsere Persönlichkeit aus? Wenn wichtige Erlebnisse aus unserer Erinnerung verschwinden, bleiben wir dann noch wir selbst?
Für die gestalterische Auseinandersetzung mit diesen Fragen wurde das Medium Film gewählt. Der Film führt uns auf eine Reise durch die Erinnerungs- und Gedankenwelt einer Person, die ihre Erinnerung verloren hat. Mit der Hilfe des Psychologen Dr. Daniel Rose soll ein Memory-Backup durchgeführt werden, um die verlorenen Erinnerungen wiederherzustellen. Dabei sollen ihre Erinnerungen neu aufgesetzt werden, um ihr altes Bewusstsein zurückzugewinnen. Stück für Stück werden die verlorenen Erinnerungen in verschiedenen Bewusstseinsphasen zusammengesetzt und mit ihnen löst sich das Rätsel ihres Verschwindens.
Competence Developing Games (CDGs) are a new concept of how to think about games with serious intentions. In order to emphasize on this topic, a new framework has been developed. It basically relies on learning and motivation theories. This ‘motivational Competence Developing Game Framework’ demonstrates how it is possible to use these theories in a CDG development process. The theoretical derivation and use of the framework is explained in this paper.
In Valais, Switzerland, Scots pines (Pinus sylvestris L.) are declining, mainly following drought. To assess the impact of drought on tree growth and survival, an irrigation experiment was initiated in 2003 in a mature pine forest, approximately doubling the annual precipitation. Tree crown transparency (lack of foliage) and leaf area index (LAI) were annually assessed. Seven irrigated and six control trees were felled in 2006, and needles, stem discs and branches were taken for growth analysis. Irrigation in 2004 and 2005, both with below-average precipitation, increased needle size, area and mass, stem growth and, with a 1-year delay, shoot length. This led to a relative decrease in tree crown transparency (−14%) and to an increase in stand LAI (+20%). Irrigation increased needle length by 70%, shoot length by 100% and ring width by 120%, regardless of crown transparency. Crown transparency correlated positively with mean needle size, shoot length and ring width and negatively with specific leaf area. Trees with high crown transparency (low growth, short needles) experienced similar increases in needle mass and growth with irrigation than trees with low transparency (high growth, long needles), indicating that seemingly declining trees were able to ‘recover’ when water supply became sufficient. A simple drought index before and during the irrigation explained most of the variation found in the parameters for both irrigated and control trees.
A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals.
This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Application of polymers in textile reinforced concrete : from the interface to construction elements
(2006)
Composite improvement of textile reinforced concrete by polymeric impregnation of the textiles
(2006)
Mikrokleben
(2005)
This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time.
The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.
Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan–Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time.
Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.
Weak Representation of the Cumulative Hazard Function under Semiparametric Random Censorship Models
(2001)
Kompakte und perfekte Maße
(1983)
We study the estimation of some linear functionals which are based on an unknown lifetime distribution. The observations are assumed to be generated under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. Under this setup a semi-parametric estimator of the survival function was introduced by the author. If the parametric model assumption is correct, it is known that the estimated functional which is based on this semi-parametric estimator is asymptotically at least as efficient as the corresponding one which rests on the nonparametric Kaplan–Meier estimator.
In this paper we show that the estimated functional which is based on this semi-parametric estimator is asymptotically efficient with respect to the class of all regular estimators under this semi-parametric model.
Visual Virology
(2012)
Suspension depletion approach for exemption of infected Solanum jasminoides cells from pospiviroids
(2018)
Despite numerous studies, viroid elimination from infected plants remains a very challenging task. This study introduces for the first time a novel ‘suspension depletion’ approach for exemption of Solanum jasminoides plants from viroids. The proposed method implies initial establishment of suspension cultures of the infected plant cells. The suspended cells were then physically treated (mild thermotherapy, 33 °C), which presumably delayed the replication of the viroid. The viroid concentration in the treated biomass was monitored weekly using pospiviroid-specific PCR. After 10–12 weeks of continuous treatment, a sufficient decrease in viroid concentration was observed such that the infection became undetectable by PCR. The treated single cells then gave rise to microcolonies on a solid culture medium and the obtained viroid-negative clones were further promoted to regenerate into viroid-free plants. Three years of accumulated experimental data suggests feasibility, broad applicability, and good efficacy of the proposed approach.
Changes in intestinal microflora in rats induced by oral exposure to low lead (II) concentrations
(2015)
Heterogeneous Composites on the Basis of Microbial Cells and Nanostructured Carbonized Sorbents
(2012)
The fact that microorganisms prefer to grow on liquid/solid phase surfaces rather than in the surrounding aqueous phase was noticed long time ago [1]. Virtually any surface – animal, mineral, or vegetable – is a subject for microbial colonization and subsequent biofilm formation. It would be adequate to name just a few notorious examples on microbial colonization of contact lenses, ship hulls, petroleum pipelines, rocks in streams and all kinds of biomedical implants. The propensity of microorganisms to become surface-bound is so profound and ubiquitous that it vindicates the advantages for attached forms over their free-ranging counterparts [2]. Indeed, from ecological and evolutionary standpoints, for many microorganisms the surface-bound state means dwelling in nutritionally favorable, non-hostile environments [3]. Therefore, in most of natural and artificial ecosystems surface-associated microorganisms vastly outnumber organisms in suspension and often organize into complex communities with features that differ dramatically from those of free cells [4].
With the variety of toothbrushes on the market, the question arises, which toothbrush is best suited to maintain oral health? This thematic review focuses first on plaque formation mechanisms and then on the plaque removal effectiveness of ultrasonic toothbrushes and their potential in preventing oral diseases like periodontitis, gingivitis, and caries. We overviewed the physical effects that occurred during brushing and tried to address the question of whether ultrasonic toothbrushes effectively reduced the microbial burden by increasing the hydrodynamic forces. The results of published studies show that electric toothbrushes, which combine ultrasonic and sonic (or acoustic and mechanic) actions, may have the most promising effect on good oral health. Existing ultrasonic/sonic toothbrush models do not significantly differ regarding the removal of dental biofilm and the reduction of gingival inflammation compared with other electrically powered toothbrushes, whereas the manual toothbrushes show a lower effectiveness.
Sampling of dry surfaces for microorganisms is a main component of microbiological safety and is of critical importance in many fields including epidemiology, astrobiology as well as numerous branches of medical and food manufacturing. Aspects of biofilm formation, analysis and removal in aqueous solutions have been thoroughly discussed in literature. In contrast, microbial communities on air-exposed (dry) surfaces have received significantly less attention. Diverse surface sampling methods have been developed in order to address various surfaces and microbial groups, but they notoriously show poor repeatability, low recovery rates and suffer from lack of mutual consistency. Quantitative sampling for viable microorganisms represents a particular challenge, especially on porous and irregular surfaces. Therefore, it is essential to examine in depth the factors involved in microorganisms’ recovery efficiency and accuracy depending on the sampling technique used. Microbial colonization, retention and community composition on different dry surfaces are very complex and rely on numerous physicochemical and biological factors. This study is devoted to analyze and review the (a) physical phenomena and intermolecular forces relevant for microbiological surface sampling; (b) challenges and problems faced by existing sampling methods for viable microorganisms and (c) current directions of engineering and research aimed at improvement of quality and efficiency of microbiological surface sampling.