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Optimized production strategy of the major capsid protein HPV 16L1 non-assembly variant in E. coli
(2020)
The capsid of human papillomavirus (HPV) consists of two capsid proteins - the major capsid protein L1 and the minor capsid protein L2. Assembled virus-like particles, which only consist of L1 proteins, are successfully applied as prophylactic vaccines against HPV infections. The capsid subunits are L1-pentamers, which are also reported to protect efficiently against HPV infections in animals.
The recombinant production of L1 has been previously shown in E. coli, yeast, insect cells, plants and mammalian cell culture. Principally, in E. coli-based expression system L1 shows high expression yields but the protein is largely insoluble. In order to overcome this problem reported strategies address fusion proteins and overexpression of bacterial chaperones. However, an insufficient cleavage of the fusion proteins and removal of co-purified chaperones can hamper subsequent down streaming.
We report a significant improvement in the production of soluble L1-pentamers by combining (I) a fusion of a N-terminal SUMO-tag to L1, (II) the heterologous co-expression of the chaperon system GroEL/ES and (III) low expression temperature. The fusion construct was purified in a 2-step protein purification including efficient removal of GroEL/ES and complete removal of the N-terminal SUMO-tag. The expression strategy was transferred to process-controlled high-cell-density fermentation with defined media according to the guidelines of good manufacturing practice. The produced L1 protein is highly pure (>95%), free of DNA (260:280 = 0.5) and pentameric. The production strategy yielded 5.73 mg of purified L1-pentamers per gram dry biomass. The optimized strategy is a suitable alternative for high yield L1-pentamer production and purification as a cheaper process for vaccine production.
The wet-flue-gas desulfurization (FGD) process plays an important role in removing water-soluble flue-gas components such as sulphur dioxide (SO2) and oxidized mercury compounds. Under the reducing environment of the FGD, there is the possibility of re-emission of the already absorbed mercury (Hg) to the gas phase, which may be diminished by the utilization of specific additives. In this study, the effect of two different additives on Hg re-emission from the aqueous phase and Hg partitioning in gypsum and filtrate of a lab-scale wet-limestone FGD is investigated. Furthermore, the behaviour of additives in the presence of different halides is studied. The studied additives are TMT 15® as a sulphidic precipitating agent, which forms non-soluble mercury compounds, and activated lignite (AL) as a carbon-based sorbent, which adsorbs Hg compounds from the aqueous phase. TMT 15® has no significant effect on SO2 absorption; on the other hand, addition of AL improves the SO2-removal efficiency by up to 30%. Using both additives, Hg re-emission is suppressed in all the experimented cases except for AL in the absence of halides, in which Hg re-emission shows no change. Thus, the need to form nucleophilic oxidized mercury compounds in the slurry for the adsorption of oxidized mercury on AL can be concluded. Usage of both additives improves Hg retention in the slurry to different extents. It is shown that, for the additive-free slurries, the Hg-adsorption capacity of the solid fraction of the slurry is the limiting parameter. Moreover, the utilization of both additives results in a significant increase in the Hg concentration of solid fraction. The correlation between redox potential and partitioning of Hg in the slurry is presented by comparing the change in the redox potential of slurries when additives are used.
In a recent study, Gebauer et al. addressed a fundamental question regarding the effects of mind-body practices (MBPs) on the self. Does the practice of MBPs in accordance with traditional contemplative traditions quiet the ego or is the practice of MBPs associated with increased self-centrality, which breeds self-enhancement bias? Both hypotheses were investigated in two separate studies with a longitudinal design. Study 1 included 93 participants, who regularly practiced yoga, and study 2 contained 162 participants, who regularly practiced loving-kindness meditation. In both studies, trait questionnaires of self-centrality and self-enhancement were taken after the practice of yoga (over the course of 15 weeks) or meditation (over the course of 4 weeks). Findings from both studies showed that participants scored higher on measures of self-enhancement and self-centrality after practicing yoga and meditation as compared with not practicing yoga and meditation. Based on these findings, Gebauer et al. argued that MBPs such as yoga and meditation do not quiet the ego, but instead lead to self-enhancement bias through increased self-centrality. We have concerns about the far-reaching conclusions made by Gebauer et al. regarding the effects of MBPs on the self. The key concerns refer to the conceptualization of the quiet ego and to the assessment of the psychological constructs investigated in this study. Gebauer et al. addressed a timely and important research question, but their far-reaching interpretations should be reconsidered due to conceptual and methodological ambiguities.
Comparing multidimensional sensor data from vehicle fleets with methods of sequential data mining
(2020)
Reading and understanding large amounts of sensor data from vehicle test drives becomes more and more important. In order to test vehicle components or analyze exhaust emissions in real test drives, the sensor data obtained from these test drives have to be comparable. Otherwise components or exhaust emissions are tested and analyzed under false conditions. The sensor data obtained during test drives are highly multidimensional which makes it even more complicated to identify recurring patterns. We present a process model to compare different test drives according to their sensor data and so give an answer to the question whether or not test drives in different cities, locations and environments are representative to real driving scenarios. The algorithms we use focus on segmentation of the individual multivariate test drive data and on clustering of the segments according to different methods. We present several segmentation and cluster methods and compare which of them is best suited for comparing test drives. The segmentation method we identified as best suited is based on principal component analysis. As cluster methods we examine hierarchical, partitioning and density-based clustering in detail.
This study investigates how integrated reporting (IR) creates value for investors. It examines how providers of financial capital benefit from an improved firm information environment provided by IR. Specifically, this study investigates the effect of voluntary IR disclosure on analyst earnings forecast accuracy as well as on firm value. To do so, we use an international sample of 167 listed companies that voluntarily publish an integrated report. Our analysis shows no significant effect of a voluntary IR publication on analyst earnings forecast accuracy and no significant effect on firm value. We thus do not find evidence for the fulfillment of IR's promises regarding improved information environment and value creation of voluntary adopters. We conclude that such companies might already have a relatively high level of transparency leading to an absent additional effect of IR disclosure. Positive effects of IR appear to be more relevant in environments where IR is mandatory.
Reliability demonstration is performed before a product is released to the market. Often, this demonstration is based on accelerated life testing of samples with limited sample size. Accelerated life testing aims to parameterize a statistical life-stress model. Based on such a model, the reliability demonstration is performed for the stress a product is experiencing during operation. The reliability needs to be inferred with a confidence interval so that the uncertainty, which stems from limited sample data, can be considered. Typically, the load conditions of a field population show a significant variation of stress. A method to consider the comprehensive statistical uncertainty and distribution of stress and life-stress model was recently published. However, this method is limited to applications with constant stress over time. In this paper we present a first approach for a method that is able to consider the distribution of load spectra and statistical lifetime model as well as their uncertainties due to limited sample sizes and allows the consideration of non-constant, i.e. time-varying, stresses for the reliability demonstration. The presented method enables the reliability inference at use condition with confidence interval for cases in which the data consists of accelerated life testing results and a sample of load spectra. The result of an illustrational evaluation is shown and concepts for further extensions of the method are introduced.
Coverage Probability of Methods for Steady-State Availability Inference with a Confidence Interval
(2020)
The quality of a repairable system can be described using its availability. Typically, a high degree of availability is demanded by the customer. To analyze the availability of a repairable system, the specification of reliability and maintainability are needed. Usually, they are demonstrated based on limited sample sizes, e.g., by analyzing the failure times of a life time test. The evaluation of the test results yields a mean-value distribution of reliability and maintainability as well as its confidence interval. Consequently, the calculated availability based on these inputs also need to be expressed including a confidence interval.
In this paper, firstly several approaches to calculate the confidence interval of steady-state availability based on reliability and maintainability are presented. Afterwards, a procedure to investigate and evaluate the quality and accuracy of the confidence intervals calculated with the presented methods is shown. Therefore, the coverage probability as the most common indicator is used. Based on an exemplary parameter study which is performed, the accuracy of the confidence intervals determined with the methods is investigated and evaluated in the case of exponentially distributed failure and repair times. Finally, several hints for an effective availability calculation with confidence intervals are given.
This paper focuses on data-driven remaining useful life prediction using ensemble methods for prognostics and health management. An important factor for the performance of an ensemble method is the diversity within the ensemble. An effective neural network ensemble method that emphasizes the generation of diversity is negative correlation learning. It is argued that for both diagnosis and prognosis, the consideration of uncertainties has a substantial added benefit over a simple point estimate. For this reason, a prediction interval is derived for the ensemble method negative correlation learning using the delta method. In the delta method, the neural network is treated as a nonlinear regression model, which is approximated by a Taylor series. A look at the derived formula of the prediction interval, emphasizes that negative correlation learning behaves inversely to a regularization. Furthermore, the formula for a diversity parameter of zero is equal to the prediction interval of the regular multilayer perceptron.
Processing of liquid silicone rubber (LSR) in the injection molding process has a high economic potential. Since there are some fundamental differences compared to classical thermoplastic injection molding, up to now there is a lack of well‐founded knowledge of the process which allows an estimation of the cycle time. Because, in addition to reverse temperature control, LSR processing also involves an irreversible temperature‐ and time‐dependent chemical reaction. In this paper, the complex cross‐linking reaction is first modelled phenomenologically using dynamic differential scanning calorimetry (DSC) measurements and the well‐fitting Kamal‐Sourour model. Afterwards, a temperature and cross‐linking simulation is set up, which reliably simulates the time‐ and travel‐dependent temperature profile and degree of cross‐linking in the mold. Therefore, the released exothermic cross‐linking heat is also taken into account. The simulated temperature values are verified with measurements in the cavity during the injection molding process. The measured values correspond very well with the simulated values at different mold temperatures. It is shown that the influence of the cross‐linking heat on the overall temperature profile in the LSR component during the injection molding process is relatively low. Nevertheless, the model is necessary to determine the degree of cross‐linking ‐ it can be used to calculate the cycle time at which the component of a certain cross‐section can be ejected at a known tool temperature and is fully cross‐linked. With this knowledge, existing processes can be optimized in terms of mold temperature and curing time, but also new components can be calculated economically.
Waste
(2020)
One-dimensional objects as nanowires have been proven to be building blocks in novel applications due to their unique functionalities. In the realm of magnetic materials, iron-oxides form an important class by providing potential solutions in catalysis, magnetic devices, drug delivery, or in the field of sensors. The accurate composition and spatial structure analysis are crucial to describe the mechanical aspects and optimize strategies for the design of multi-component NWs. Atom probe tomography offers a unique analytic characterization tool to map the (re-)distribution of the constituents leading to a deeper insight into NW growth, thermally-assisted kinetics, and related mechanisms. As NW-based devices critically rely on the mechanical properties of NWs, the appropriate mechanical modeling with the resulting material constants is also highly demanded and can open novel ways to potential applications. Here, we report a compositional and structural study of quasi-ceramic one-dimensional objects: α-Fe ⊕ α-FeOOH(goethite) ⊕ Pt and α-Fe ⊕ α-Fe3O4(magnetite) ⊕ Pt core–shell NWs. We provide a theoretical model for the elastic behavior with terms accounting for the geometrical and mechanical nonlinearity, prior and subsequent to thermal treatment. The as-deposited system with a homogeneous distribution of the constituents demonstrates strikingly different structural and elastic features than that of after annealing, as observed by applying atom probe tomography, energy-dispersive spectroscopy, analytic electron microscopy, and a micromanipulator nanoprobe system. During annealing at a temperature of 350 °C for 20 h, (i) compositional partitioning between phases (α-Fe, α-Fe3O4 and in a minority of α-Fe2O3) in diffusional solid–solid phase transformations takes place, (ii) a distinct newly-formed shell formation develops, (iii) the degree of crystallinity increases and (iv) nanosized precipitation of evolving phases is detected leading to a considerable change in the description of the elastic material properties. The as-deposited nanowires already exhibit a significantly large maximum strain (1–8%) and stress (3–13 GPa) in moderately large bending tests, which become even more enhanced after the annealing treatment resulting at a maximum of about 2.5–10.5% and 6–18 GPa, respectively. As a constitutive parameter, the strain-dependent stretch modulus undoubtedly represents changes in the material properties as the deformation progresses.
The theories of multi-criteria decision-making (MCDM) and fuzzy logic both aim to model human thinking. In MCDM, aggregation processes and preference modeling play the central role. This paper suggests a consistent framework for modeling human thinking by using the tools of both fields: fuzzy logical operators as well as aggregation and preference operators. In this framework, aggregation, preference, and the logical operators are described by the same unary generator function. Similarly to the implication being defined as a composition of the disjunction and the negation operator, preference operators were introduced as a composition of the aggregative operator and the negation operator. After a profound examination of the main properties of the preference operator, our main goal is the implementation into neural networks. We show how preference can be modeled by a perceptron, and illustrate the results in practical neural applications.
Interpretable neural networks based on continuous-valued logic and multicriteria decision operators
(2020)
Combining neural networks with continuous logic and multicriteria decision-making tools can reduce the black-box nature of neural models. In this study, we show that nilpotent logical systems offer an appropriate mathematical framework for hybridization of continuous nilpotent logic and neural models, helping to improve the interpretability and safety of machine learning. In our concept, perceptrons model soft inequalities; namely membership functions and continuous logical operators. We design the network architecture before training, using continuous logical operators and multicriteria decision tools with given weights working in the hidden layers. Designing the structure appropriately leads to a drastic reduction in the number of parameters to be learned. The theoretical basis offers a straightforward choice of activation functions (the cutting function or its differentiable approximation, the squashing function), and also suggests an explanation to the great success of the rectified linear unit (ReLU). In this study, we focus on the architecture of a hybrid model and introduce the building blocks for future applications in deep neural networks.
The use of small-scale wind turbines (SSWTs) in private households not only allows for increased renewable energy generation, but also improved grid stability and resilience of individual regions. However, there are strict requirements regarding the efficiency, reliability and electrical safety of SSWTs because of their low power levels, long payback period and the fact that they are installed nearby residential areas. This paper proposes a novel yaw inductive power transfer system, based on multilevel inverter, which mitigates the main disadvantages of SSWTs - slip rings, low voltage energy generation etc. The system utilizes low voltage MOSFETs in multilevel boost-series resonant topology combined with ZVS techniques to maximize efficiency. The operating principle, switching waveforms and behavior of the inverter are described and analyzed. Cell voltage balancing algorithms are presented as well. Two different control techniques for power flow regulation have been introduced and compared. The effectiveness of the proposed solution has been verified by building a 3.3 kW prototype system and comprehensive measuring of its performance. The experimental results show that peak power transfer efficiency reaches 92.5% while converting generator voltage from 60 V DC to grid compatible 400 V DC.
Most multi-layer neural networks used in deep learning utilize rectified linear neurons. In our previous papers, we showed that if we want to use the exact same activation function for all the neurons, then the rectified linear function is indeed a reasonable choice. However, preliminary analysis shows that for some applications, it is more advantageous to use different activation functions for different neurons – i.e., select a family of activation functions instead, and select the parameters of activation functions of different neurons during training. Specifically, this was shown for a special family of squashing functions that contain rectified linear neurons as a particular case. In this paper, we explain the empirical success of squashing functions by showing that the formulas describing this family follow from natural symmetry requirements.
Recently the production of electric cars is increasing worldwide. The main target is to lower the greenhouse gas emissions. Even if an electrified vehicle is locally emission-free the manufacturing of lithium ion batteries are producing significant amounts of CO2. In order to decrease the air pollution governments are considering recycling programs to extend battery life and usage of important raw materials. A new approach to recover LiNixMnyCozO2 (NMC) particles while saving the chemical and morphological properties using water was presented by Tim Sieber et al. [1]. With the presented study, we are focusing on the analysis of the effects on the Global Warming Potential (GWP) for the water based recycling process based on a reuse of NMC material in new batteries.
It is possible to reduce the ecological damage of the manufacturing process of Li-Ion battery cells even with little amounts of recovered cathode material that is used for the production of new battery cells. Based on the suggestion that 95% of the NMC cathode material can be recovered by the hydrometallurgical recovery and the reuse of 10% within the production of new batteries a reduction of the GWP by 7% ,can be identified for the cathode materials. For other impact categories such as Acidification Potential (AP), Eutrophication Potential (EP), and Photochemical Ozone Creation Potential (POCP), savings of 10%, 11%, and 8 % can be achieved respectively.
The studied water based recycling process can be quoted as environment-friendly and leads to a reduction of all impact categories by a re-use of 10% recovered NMC material. Based on this knowledge an additional recycling on substance level is recommended.
In einer Serie von Artikeln stellen wir im IGA Boten die Ergebnisse einer kleinen Studie vor – hier liegt nun der zweite Teil vor Ihnen. Im letzten IGA Boten (siehe Nr. 55) wurden zunächst die Belastungen und potentiell traumatisierenden Situationen in den Blick genommen. In dieser Ausgabe sollen nun die Folgen, die aus den Erfahrungen entstanden sind, beschrieben werden. Warum ist das ein so wichtiges Thema für die Interessengemeinschaft Arthrogryposis? Andreas Krüger, ein Facharzt für Kinderund Jugendpsychiatrie und Psychotherapie beschreibt in seinem Buch „Erste Hilfe für traumatisierte Kinder“ (2017) sehr klar, wie wichtig diese Erkenntnisse für Familien sind und stellt die Frage, warum ein gewisses Grundwissen über eine medizinische Notfallversorgung eine Selbstverständlichkeit ist, während wir so wenig über den »psychischen Notfall« und dessen Versorgung wissen.
The root area of a wind turbine rotor is usually constructed by very thick airfoils with a relative thickness of more than 35%. An airfoil at that thickness is characterized with strong flow separation. To solve this issue, vortex generators can be used as an active control in order to stabilize the airflow and improve the aerodynamic performance, consequently. Boundary layer control however, investigated employing numerical techniques, strongly depend on the employed method as well as the mesh especially due to a weak vortex conservation in the RANS model. Using the method of Delayed detached eddy simulation (DDES) the solution can benefit from effort-efficient boundary layer modeling as well as LES vortex resolving apart from the surface. The present studies aims to investigate suitable numerical approach mesh dependencies in comparison to experimental data, for application to thick airfoil in future studies.
Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)
(2020)
From the customer's perspective, the appeal of electric vehicles depends on the simplicity and ease of their use, such as flexible access to electric power from the grid to recharge the batteries of their vehicles. Therefore, the expansion of charging infrastructure will be an important part of electric mobility. The related charging infrastructure is a big challenge for the load capacity of the grid connection without additional intelligent charge management: if the control of the charging process is not implemented, it is necessary to ensure the total of the maximum output of all xEVs at the grid connection point, which requires huge costs. This paper proposes to build a prediction module for forecasting dynamic charging load using machine learning (ML) techniques. The module will be integrated into a real charge management concept with optimization procedures for controlling the dynamic load point. The value of load forecasting through practical load data of a car park were taken to illustrate the proposed methods. The prediction performance of different ML methods under the same data condition (e.g., holiday data) are compared and evaluated.
Advance Care Planning
(2020)
Das internationale Konzept ‚Advance Care Planning (ACP)‘ etabliert sich in Deutschland sukzessive unter dem Begriff der „Gesundheitlichen Versorgungsplanung für die letzte Lebensphase“. Übergeordnetes Ziel von ACP ist es, Menschen die Möglichkeit zu geben, im Rahmen eines begleiteten Gesprächsprozesses zentrale Vorausverfügungen hinsichtlich ihrer gesundheitlichen Versorgung für Phasen der Nichteinwilligungsfähigkeit zu formulieren und durch eine entsprechende strukturelle Einbettung diesen antizipierten Willensäußerungen im Bedarfsfall Geltung zu verschaffen. Ausgehend von der Skizzierung zentraler Eckpunkte und Rahmungen des Konzeptes arbeitet der Beitrag reflexionswürdige ethische Implikationen und daran gebundene moralische Forderungen heraus, denn das Konzept ist äußerst komplex. Diese Ausführungen sind getragen davon, dass eine qualitätsvolle sowie eine ethisch vertretbare Realisierung des Konzeptes, eine qualitätsvolle Begleitung am Lebensende maßgeblich an das Bewusstsein und den Umgang der professionell im Gesundheitswesen tätigen Personen und Berufsgruppen gebunden ist, die moralischen Forderungen und ethischen Implikationen verantwortungsvoll im Blick zu behalten.
Soziale Probleme begünstigen die Entwicklung seelischer Erkrankungen - ihre Lösung fördert das Gelingen der psychotherapeutischen Behandlung. Daher ist eine frühzeitige Einbindung der Klinischen Sozialarbeit mit ihren sozialdiagnostischen Instrumenten und den sozialtherapeutischen Interventionen in den Gesamtbehandlungsplan notwendig. Der vorliegende Band gibt einen grundlegenden Überblick über die Bedeutung dieser Methoden für den psychotherapeutischen Prozess. Dafür zeigen die Autorinnen und Autoren die Schnittstellen der Sozialen Arbeit und der Psychotherapie auf, erläutern zentrale Aspekte einer psychosozialen Diagnostik und Intervention und geben einen ausführlichen Einblick in verschiedene Praxisfelder, in denen Psychotherapie und Soziale Arbeit gleichermaßen involviert sind. Insgesamt stellt dieses Werk die Chancen und Grenzen der Klinischen Sozialarbeit in der Psychotherapie anschaulich und übersichtlich dar und dient somit auch als wertvolle Hilfe für eine erfolgreiche interprofessionelle Zusammenarbeit.
For an efficient operation of a low voltage PMSM an optimized voltage usage is very important. Because of the relation between the low voltage and the high currents in this type of machine, a large voltage reserve is needed to compensate the influence of parameter mismatches and to guarantee a stable current control. As the power is limited by the low voltage in this type of hybrid drive systems, optimizing the voltage usage is also required to maximize the power and the torque availability. This paper describes a closed loop flux control to maximize the voltage usage. The controller feedback is used to estimate and maximize the available torque for each operating point.
Soziale Arbeit, Gesundheitsämter, Medizin und Pflege waren an der Erfassung, Verfolgung, Zwangssterilisierung und Tötung von als »krank« oder »behindert« angesehenen Menschen im Nationalsozialismus beteiligt. Was können wir aus der Einteilung in »lebenswertes« und »lebensunwertes« Leben für heute lernen? Wie kann sich an die getöteten Kinder in den mehr als 30 so genannten »Kinderfachabteilungen« erinnert werden? Welche Forschungsergebnisse gibt es zu den überproportional gestorbenen Säuglingen im Kinderkrankenhaus »Sonnenschein« in Bethel in der NS-Zeit? Zu diesen Fragen liefert das Buch aktuelle Antworten.
Die Perspektive wechseln
(2020)
Mithilfe des Konzepts der gesundheitlichen Versorgungsplanung – auch als Advance Care Planning (ACP) oder „Behandlung im Voraus planen“ (BVP) bekannt – sollen Behandlungsziele fest gelegt werden, und zwar für den Fall, dass der Betroffene seinen Willen nicht äußern kann. Neben der individuellen Gesprächsbegleitung spielen in diesem Zusammenhang auch Fall- besprechungen eine wichtige Rolle. Diese sind zwar gesetzlich vorgesehen, jedoch fehlt bislang eine einheitliche Struktur, an der sich Fachkräfte in der Praxis orientieren können.
Sorgen am Lebensende
(2020)
Mobilitätshilfen sind allgegenwärtig und existenziell für Menschen, die aufgrund von Krankheit und Pflegebedürftigkeit in ihren Alltagsbewegungen und -fortbewegungen eingeschränkt sind. Mobilität steht in einem direkten Zusammenhang zur Selbstständig-keit und Selbstbestimmung im Alltag. Für viele pflegebedürftige Menschen sind Mobili-tätshilfen entscheiden dafür, ob sie ihren Alltag (wieder) selbst gestalten können. Dabei müssen sie sich innerhalb und außerhalb von Räumen ganz unterschiedlichen Heraus-forderungen stellen. Teilhabe am sozialen, möglicherweise auch am beruflichen Leben wird für viele Betroffene erst dann möglich, wenn die unterschiedlichen Mobilitätshilfen aufeinander und auf die jeweiligen Aktivitäten abgestimmt sind. Für Angehörige und für Pflegefachpersonen stellt sich täglich die Frage, mit welchen Mobilitätshilfen eine siche-re und angemessene Unterstützung möglich ist. Dabei gilt es, die Ausstattung mit Hilfen dem aktuellen Mobilitätsprofil der Betroffenen anzupassen; die Folgen von Über- oder Unterversorgung mit Mobilitätshilfen kann für die Betroffenen gravierende negative Folgen haben!
The aim of the current work was to illustrate the effect of the fibre area correction factor on the results of modelling natural fibre-reinforced composites. A mesoscopic approach is adopted to represent the stochastic heterogeneity of the composite, i.e. a meso-structural numerical model was prototyped using the finite element method including quasi-unidirectional discrete fibre elements embedded in a matrix. The model was verified by the experimental results from previous work on jute fibres but is extendable to every natural fibre with cross-sectional non-uniformity. A correction factor was suggested to fine-tune both the analytical and numerical models. Moreover, a model updating technique for considering the size-effect of fibres is introduced and its implementation was automated by means of FORTRAN subroutines and Python scripts. It was shown that correcting and updating the fibre strength is critical to obtain accurate macroscopic response of the composite when discrete modelling of fibres is intended. Based on the current study, it is found that consideration of the effect of flaws on the strength of natural fibres and inclusion of the fibre area correction factor are crucial to obtain realistic results.
The moisture absorption behavior of flax fiber-reinforced epoxy composites is deliberated to be a serious issue. This property restricts their usage as outdoor engineering structures. Therefore, this study provides an investigation of moisture in flax fibers on the performance of the flax/epoxy composite materials based on their shear responses. The ±45° aligned flax fibers exposed to different relative humidities (RH) and the vacuum infusion process was used to manufacture the composite specimens. The optimum shear strength (40.25 ± 0.75 MPa) was found for the composites manufactured with 35% RH-conditioned flax fibers, but the shear modulus was reduced consistently with increasing RH values. Although shear strength was increased because of fiber swelling with increased moisture absorption rate until 35% RH environments with good microstructures, nonetheless, strength and modulus both started to decrease after this range. A very poor microstructure has been affirmed by the SEM images of the composite samples conditioned at 90% RH environments.
In our present paper, we approach the mixed problem with initial and boundary conditions, in the context of thermoelasticity without energy dissipation of bodies with a dipolar structure. Our first result is a reciprocal relation for the mixed problem which is reformulated by including the initial data into the field equations. Then, we deduce a generalization of Gurtin’s variational principle, which covers our generalized theory for bodies with a dipolar structure. It is important to emphasize that both results are obtained in a very general context, namely that of anisotropic and inhomogeneous environments, having a center of symmetry at each point.
Our study is dedicated to a composite, which, in fact, is a mixture of two thermoelastic micropolar bodies. We formulate the mixed initial boundary value problem in this context and define the domain of influence for given data. For any solution of the mixed problem we associate a measure and prove a second-order differential inequality for it. Based on the maximum principle for the heat equation and on the second-order differential inequality, we establish an estimate which proves that the thermal and the mechanical effects, at large distance from the domain of influence, are dominated by an exponential decay.
Due to the good mechanical properties, flax fiber-reinforced epoxy composites
are being widely used as a green alternative to glass fiber composites. However,
plant fibers absorb moisture from the environment, being in a higher moisture
uptake as the relative humidity (RH) increases. This absorbed moisture deteriorates the mechanical properties of the composites. In this study, geometric
and displacement potential function (DPF) approaches are used to predict the
mechanical properties of flax fiber-reinforced epoxy composites under environmental conditions, in particular, different RH values. The tensile properties
that were measured experimentally strongly agreed with the analytical findings.
Almost similar results were found for the tensile strain those were measured
experimentally and the one predicted by the geometric function.
However, the predicted strain values were 38% and 42% less than the experimental ones for 0% and 95% RH conditioned composites, respectively, when
DPF was used. Good conformity between the experimental, analytical, and
DPF formulation for predicting mechanical properties ensures the practical
applicability of this study. The formulations established in this work could,
therefore, be utilized to analytically solve laminated composites under specific
boundary conditions in structural applications.
We consider the mixed initial-boundary value problem in the context of the
Moore-Gibson-Thompson theory of thermoelasticity for dipolar bodies. We consider the case of heat conduction with dissipation. Even if the elasticity tensors
are not supposed to be positively defined, we have proven both, the uniqueness
and the instability of the solution of the mixed problem. In the case that the mass
density and the thermal conductivity tensor are positive, we obtain the uniqueness
of the solution using some Lagrange type identities.
Effect of voids in a heat-flux dependent theory for thermoelastic bodies with dipolar structure
(2020)
Die Demokratie scheint in Deutschland gefestigt zu sein, gleichzeitig wird sie jedoch von einer nennenswerten Anzahl von Bürgerinnen und Bürgern – auch von Jugendlichen – zunehmend in Frage gestellt. Die Bundesregierung hat auf diesem Hintergrund für den nächsten Kinder- und Jugendbericht das Thema „Förderung demokratischer Bildung im Kindes- und Jugendalter“ vorgesehen. Kurt Möller und Oliver Hohner gehen in ihrem Beitrag der Frage nach, welche Potentiale für Demokratiebildung die Offene Kinder- und Jugendarbeit bietet; auch die Aufsuchende Jugend(sozial)arbeit nehmen sie in den Blick. Die Autoren haben im Herbst 2019 eine Online-Befragung unter Einrichtungen der Offenen Kinder- und Jugendarbeit und Aufsuchenden Jugend(sozial)arbeit durchgeführt. Das Vorgehen, die wichtigsten Ergebnisse und zentrale Schlussfolgerungen daraus stellen sie vor. Abgefragt wurden u.a. die Häufigkeit von Diskussionen über politische Themen in den genannten Arbeitsfeldern, Ausgrenzungen unter Jugendlichen oder die Intensität von Beteiligung und Mitbestimmung der Jugendlichen. Deutlich wird ein erheblicher Bedarf an Aus-, Fort- und Weiterbildung zu solchen Herausforderungen. Die Autoren arbeiten auch Spezifika und Unterschiede zwischen den Arbeitsfeldern der Offenen Kinder- und Jugendarbeit und der Aufsuchenden Jugend(sozial)arbeit heraus.
Suchthilfe und Suchtprävention sind zentrale Tätigkeitsfelder für Fachkräfte der Sozialen Arbeit. Das Wissen um Suchtgefährdung und der fachliche Umgang mit missbrauchenden und abhängigen Menschen sind angesichts der Risiko-Klientel in vielen Bereichen der Sozialen Arbeit (z.B. der Wohnungslosenhilfe, Jugendhilfe) wesentlicher Bestandteil des Berufsprofils. Das Buch ist angelegt als systematisches Grundlagenwerk zur Sozialen Arbeit in der Suchthilfe und Suchtprävention. Es entfaltet die Theorie und die relevanten Wissensbestände in enger Ausrichtung auf ihre Bedeutung für die Bewältigung beruflicher Anforderungen und stellt die dafür notwendigen Handlungskonzepte anschaulich vor.
Complete book:
Social work as a democratically constituted profession committed to human rights is currently facing cross-border encroachments and attacks by right-wing populist movements and governments. With the Bundestag elections in September 2017, the question of the extent to which right-wing populist forces succeed in influencing the discourse with xenophobic and nationalist arguments arises in Germany too. The authors examine how social work can respond effectively to nationalism, exclusion, de-solidarization and a basic skepticism about science and position itself against this background.
