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Short-term Incentives of Research Evaluations: Evidence from the UK Research Excellence Framework
(2023)
Greenhouse Gas Emission Reduction Potential of Lavender Meal and Essential Oil for Dairy Cows
(2023)
This research aims to evaluate the potential of lavender meal (LM) and lavender essential oil (LEO) to mitigate methane emissions by dairy cows. Locally grown lavender was collected fresh for this purpose, and its oil was extracted using the cold-press method. The resultant LEO and LM and whole lavender (WL) were added to dairy cow concentrate feed at 0%, 0.05%, and 0.10%, and their effects on vitro gas production values and gas concentrations were subsequently assessed. Out of the 30 bioactive compounds isolated from LEO, linalool and linalyl acetate were the most common—accounting for 70.4% of the total. The lavender dose had a significant influence on gas production for up to 12 h. No significant variations were found across the lavender forms when gas kinetics, in vitro degradability, and predicted energy values were compared. The addition of WL to the concentrate feed of dairy cows produced the greatest quantities of methane, carbon dioxide, and hydrogen sulfide, whereas LEO resulted in the lowest values. In contrast, no significant difference in ammonia content was found across the various lavender forms added into dairy cow concentrate feed. The results of this research suggest that adding 0.05–0.10% LM and LEO to concentrate feed may decrease greenhouse gas emissions from dairy cows.
This study aimed to assess the impact of essential oils (EOs) on in vitro gas formation and the degradability of dairy and beef cattle diets. This study also aimed to investigate the effects of different types of EOs on nutrient utilization and rumen microbial activity. The current study was conducted using a fully randomized design consisting of eight experimental treatments, including two control treatments without any additives, and treatments with cinnamon essential oil (CEO), flaxseed essential oil (FEO), and lemon seed essential oil (LEO) at a concentration of 60 mg/kg fresh mass. Two control treatments were used, one with alfalfa silage and dairy concentrate (DC, CON-DC) and the other with alfalfa silage and fattening concentrate (FC, CON-FC). Gas formation, dry matter (DM) digestibility, crude protein (CP) digestibility, effective degradability (ED), and soluble fractions of DM and organic matter (OM) were evaluated. CEO had a substantial effect on gas formation (p < 0.05). When EOs were added to the diets, they increased dry matter digestibility after 24 h of incubation as compared to control treatments. After 24 h of incubation, FCCEO and FCFEO had the highest CP digestibility among the diets. FCLEO considerably enhanced ED, as well as the soluble fraction of DM (a) at a passage rate of 2% per hour. Treatment with FCCEO resulted in a significant increase in soluble fractions compared to the control diets. At a passage rate of 2% h, DCCEO had the maximum ED value. When EOs were introduced to the diet, they dramatically decreased the insoluble portion of CP (b). Compared to the control treatments, gas production was significantly lower in the presence of LEO (FCLEO; p < 0.05). The addition of EOs to cattle diets may increase nutrient utilization and enhance rumen microbial activity. EOs extracted from lemon seeds (at a dose of 60 mg/kg of diet) lowered gas production in both dairy cattle and fattening diets.
Cyclic Tensile Stress Induces Skeletal Muscle Hypertrophy and Myonuclear Accretion in a 3D Model
(2023)
Skeletal muscle is highly adaptive to mechanical stress due to its resident stem cells and the pronounced level of myotube plasticity. Herein, we study the adaptation to mechanical stress and its underlying molecular mechanisms in a tissue-engineered skeletal muscle model. We subjected differentiated 3D skeletal muscle-like constructs to cyclic tensile stress using a custom-made bioreactor system, which resulted in immediate activation of stress-related signal transducers (Erk1/2, p38). Cell cycle re-entry, increased proliferation, and onset of myogenesis indicated subsequent myoblast activation. Furthermore, elevated focal adhesion kinase and β-catenin activity in mechanically stressed constructs suggested increased cell adhesion and migration. After 3 days of mechanical stress, gene expression of the fusogenic markers MyoMaker and MyoMixer, myotube diameter, myonuclear accretion, as well as S6 activation, were significantly increased. Our results highlight that we established a promising tool to study sustained adaptation to mechanical stress in healthy, hypertrophic, or regenerating skeletal muscle.
We explore the different notions of completeness applied in the EPR discussion following and amending the thorough analysis of Arthur Fine. To this aim, we propose a classification scheme for scientific theories that provides a methodology for analyzing the different levels at which interpretive approaches come into play. This allows us to contrast several concepts of completeness that operate on specific levels of the theory. We introduce the notion of theory completeness and compare it with the established notions of Born completeness, Schrödinger completeness and bijective completeness. We relate these notions to the recent concept of ????-completeness and predictable completeness. The paper shows that the EPR argument contains conflicting versions of completeness. The confusion of these notions led to misunderstandings in the EPR debate and hindered its progress. Their clarification will thus contribute to recent debates on interpretational issues of quantum mechanics. Finally, we discuss the connection between the EPR paper and the Einstein–Rosen paper with regard to the question of completeness.
The use of fault detection and tolerance measures in wireless sensor networks is inevitable to ensure the reliability of the data sources. In this context, immune-inspired concepts offer suitable characteristics for developing lightweight fault detection systems, and previous works have shown promising results. In this article, we provide a literature review of immune-inspired fault detection approaches in sensor networks proposed in the last two decades. We discuss the unique properties of the human immune system and how the found approaches exploit them. With the information from the literature review extended with the findings of our previous works, we discuss the limitations of current approaches and consequent future research directions. We have found that immune-inspired techniques are well suited for lightweight fault detection, but there are still open questions concerning the effective and efficient use of those in sensor networks.
Using nylon bag techniques, Cornell net carbohydrates and protein systems (CNCPS), and scanning electron microscopy, the authors examined the digestibility and structure of Vicia ervilia (ervil, bitter vetch) after steam flaking, roasting, and microwave processing. During the in situ technique, the samples were incubated at 0, 2, 4, 6, 8, 12, 16, 24, 36, and 48 h. For the description of the ruminal DM (dry matter) and CP (crude protein) degradation kinetics of treated and untreated Vicia ervilia, different models were selected as the best fit for the dry matter (DM) and crude protein (CP) degradation parameters of steam flaked samples. The results showed that both the steam flaking and microwave treatment samples contained high levels of non-protein nitrogen and buffer soluble protein, respectively. In comparison with steam flaking and microwave treatment, roasting decreased and increased the buffer soluble protein and neutral detergent insoluble protein, respectively. The control treatments showed the highest levels of neutral detergent soluble protein and the lowest levels of acid detergent soluble protein. Moreover, steam flaking and roasting decreased and increased the amount of acid detergent insoluble protein, respectively. When using dry heat (microwave and roasting), the acid detergent soluble and insoluble protein fractions were increased. As a result of this experiment, the nitrogen fractions were altered using heat processing. Hence, protein fermented feed and ruminal fermentation conditions can be expressed using these results.
DC/DC-Konverter wandeln eine Eingangsspannung in eine Ausgangsspannung. In diesem Beitrag werden drei solche Konverter behandelt, die aus den drei Grundschaltungen hergeleitet sind. Im Gegensatz zu den Originalstrukturen sind diese nur für einen geringeren Spannungsübersetzungsbereich geeignet, haben aber den Vorteil, dass die elektronischen Schalter immer bei Strom null schalten und die Dioden nicht zwangsweise, sondern immer von selbst ausschalten. Die Gewinnung der Konverterschaltungen wird erläutert, und die Funktionsweisen werden durch mathematische Beschreibung, durch Skizzen und mithilfe des uZ-i-Diagramms erklärt. Weiters werden einige mögliche Erweiterungen der Schaltungen gezeigt.
Connecting material degradation and power loss of PV modules using advanced statistical methodology
(2023)
A Model-Based Approach for Remote Development of Embedded Software for Object Avoidance Applications
(2023)
Equipping rooms used for medical purposes, like e.g., intensive care units,
is an expensive and time-consuming task. In order to avoid extensive subsequent
adjustments due to inappropriate layout visualization or geometric conditions
difficult to identify in 2D plans, it is of utmost importance to provide an optimal
planning environment to future users such as physicians and nurses. In this paper
we present the concept of a fully automatized pipeline, which is designed to
visualize computer aided design (CAD) data using virtual reality (VR). The
immersive VR experience results in improvement of efficiency in the decision-
making process during the planning phase due to better spatial imagination. The
pipeline was successfully tested with CAD data from existing Intensive Care Units.
The results indicate that the pipeline can be a valuable tool in the field of spatial
planning in healthcare, due to simple usage and fast conversion of CAD data. The
next step will be the development of a plugin for CAD tools to allow for interactions
with the CAD models in Virtual Reality, which is not yet possible without manual
intervention
Dieser Beitrag soll interessierten Laien eine Hilfestellung an die Hand geben, ihre Infomaterialien barriereärmer zu gestalten. Einführend erfolgt eine kurze Darstellung der rechtlichen und gesellschaftlichen Situation rund um das Thema Behinderung. Verschiedene Ebenen von Barrieren und Lösungsansätze werden vorgestellt: Organisationale Barrieren von Bildungseinrichtungen werden ebenso wie Barrieren rund um das Bildungsberatungsgespräch adressiert. Der Schwerpunkt liegt bei auf der Gestaltung von Informationsmaterial. Neben einem theoretischen Hintergrund über Lösungsansätze werden praktische Umsetzungen für verschiedene Medien vorgestellt. Der Beitrag wird durch Beispiele guter Praxis in der Umsetzung, eine Checkliste zur Anwendung und weiterführende Ressourcen abgerundet.
Bucket increasing trees are multilabelled generalizations of increasing trees, where each non-leaf node carries b labels, with a fixed integer. We provide a fundamental result, giving a complete characterization of all families of bucket increasing trees that can be generated by a tree evolution process. We also provide several equivalent properties, complementing and extending earlier results for ordinary increasing trees to bucket trees. Additionally, we state second order results for the number of descendants of label j, again extending earlier results in the literature.
Background
Online symptom checkers are digital health solutions that provide a differential diagnosis based on a user’s symptoms. During the coronavirus disease 2019 (COVID-19) pandemic, symptom checkers have become increasingly important due to physical distance constraints and reduced access to in-person medical consultations. Furthermore, various symptom checkers specialised in the assessment of COVID-19 infection have been produced.
Objectives
Assess the correlation between COVID-19 risk assessments from an online symptom checker and current trends in COVID-19 infections. Analyse whether those correlations are reflective of various country-wise quality of life measures. Lastly, determine whether the trends found in symptom checker assessments predict or lag relative to those of the COVID-19 infections.
Materials and methods
In this study, we compile the outcomes of COVID-19 risk assessments provided by the symptom checker Symptoma (www.symptoma.com) in 18 countries with suitably large user bases. We analyse this dataset’s spatial and temporal features compared to the number of newly confirmed COVID-19 cases published by the respective countries.
Results
We find an average correlation of 0.342 between the number of Symptoma users assessed to have a high risk of a COVID-19 infection and the official COVID-19 infection numbers. Further, we show a significant relationship between that correlation and the self-reported health of a country. Lastly, we find that the symptom checker is, on average, ahead (median +3 days) of the official infection numbers for most countries.
Conclusion
We show that online symptom checkers can capture the national-level trends in coronavirus infections. As such, they provide a valuable and unique information source in policymaking against pandemics, unrestricted by conventional resources.
Electrolytic capacitors have the disadvantage of
pronounced aging. Non-electrolytic capacitors are therefore used
in applications where long-life is important. In this paper we
present a driving stage for LEDs without any capacitive
elements. The basic topology is a Buck converter with one coil,
one active, and one passive switch. Instead of the output
capacitor, series connections of one or more LEDs and an active
switch are connected. An additional diode is connected between
the output and the input to achieve a current path, when all LED-
paths are off. A nonlinear hysteresis controller is used to achieve
a robust control. A system with three switchable LED-strings is
analyzed. Design hints are given and the function is proved with
the help of LTSpice simulations. The system can be used for
lighting purposes with the possibility to change the chrominance.
The potentiality to transmit data is also treated.
Stellhebel beim Aufbau von Corporate Start-ups. Dargestellt am Start-Up-Projekt „Hallo Sonne“
(2023)
Technologiemanagement
(2023)
MS SPIDOC is a novel sample delivery system designed for single (isolated) particle imaging at X-ray Free-Electron Lasers
that is adaptable towards most large-scale facility beamlines. Biological samples can range from small proteins to MDa
particles. Following nano-electrospray ionization, ionic samples can be m/z-filtered and structurally separated before being
oriented at the interaction zone. Here, we present the simulation package developed alongside this prototype. The first part
describes how the front-to-end ion trajectory simulations have been conducted. Highlighted is a quadrant lens; a simple but
efficient device that steers the ion beam within the vicinity of the strong DC orientation field in the interaction zone to ensure
spatial overlap with the X-rays. The second part focuses on protein orientation and discusses its potential with respect to
diffractive imaging methods. Last, coherent diffractive imaging of prototypical T = 1 and T = 3 norovirus capsids is shown.
We use realistic experimental parameters from the SPB/SFX instrument at the European XFEL to demonstrate that low-
resolution diffractive imaging data (q < 0.3 nm −1 ) can be collected with only a few X-ray pulses. Such low-resolution data
are sufficient to distinguish between both symmetries of the capsids, allowing to probe low abundant species in a beam if
MS SPIDOC is used as sample delivery.
As IoT systems have increased the number of deployed embedded devices drastically and most of these devices are used in safety or security critical environments, the education of embedded software engineers is more important than ever. A critical part of their education is the development of their intuition for secure and safe software. In this paper 1 1 This research was funded by the city of Vienna (MA-23 call 21, project no. 9). we present an evaluation system used to generate fast and accurate feedback for student submission in, but not limited to, embedded software development courses. The system can be used as a first feedback loop to outline to the students where problems exist in their code and give them the opportunity to analyze and correct their errors. These extra steps ensure that the students can and will be notified early about their mistakes and can search for correct solutions, supporting the student's learning process. We present the implementation of the system and analyze its deployment in a microcontroller software development lecture. This analysis was done by means of surveys of the students and lecturers as well as a statistical analysis of the student submissions. The results show that the students made use of this extra features and even would prefer to have this feedback in other software development lectures as well.
Regeneration of bone defects is often limited due to compromised bone tissue physiology. Previous studies suggest that engineered extracellular matrices enhance the regenerative capacity of mesenchymal stromal cells. In this study, we used human-induced pluripotent stem cells, a scalable source of young mesenchymal progenitors (hiPSC-MPs), to generate extracellular matrix (iECM) and test its effects on the osteogenic capacity of human bone-marrow mesenchymal stromal cells (BMSCs). iECM was deposited as a layer on cell culture dishes and into three-dimensional (3D) silk-based spongy scaffolds. After decellularization, iECM maintained inherent structural proteins including collagens, fibronectin and laminin, and contained minimal residual DNA. Young adult and aged BMSCs cultured on the iECM layer in osteogenic medium exhibited a significant increase in proliferation, osteogenic marker expression, and mineralization as compared to tissue culture plastic. With BMSCs from aged donors, matrix mineralization was only detected when cultured on iECM, but not on tissue culture plastic. When cultured in 3D iECM/silk scaffolds, BMSCs exhibited significantly increased osteogenic gene expression levels and bone matrix deposition. iECM layer showed a similar enhancement of aged BMSC proliferation, osteogenic gene expression, and mineralization compared with extracellular matrix layers derived from young adult or aged BMSCs. However, iECM increased osteogenic differentiation and decreased adipocyte formation compared with single protein substrates including collagen and fibronectin. Together, our data suggest that the microenvironment comprised of iECM can enhance the osteogenic activity of BMSCs, providing a bioactive and scalable biomaterial strategy for enhancing bone regeneration in patients with delayed or failed bone healing.
The healthcare sector is growing in importance as people continue to age and pandemics complicate the boundary conditions of such systems. The number of innovative approaches to solve singular tasks and problems in this area is only slowly increasing. This is particularly evident when looking at medical technology planning, medical training and process simulation. In this paper a concept for versatile digital improvements to these problems by using state of the art development methods of Virtual Reality (VR) and Augmented Reality (AR) are presented. The programming and design of the software is done with the help of Unity Engine, which provides an open interface for docking with the developed framework for future work. The solutions were tested under domain specific environments and have shown good results and positive feedback.
Interface with WP123200
(2023)
A Turbulent Context
(2023)
Automatic classification of a full-thickness macular hole in optical coherence tomography images
(2023)
ChatGPT 4.0 – friend or foe?
(2023)
Open Data Workshop
(2023)
ChatGPT – Freund oder Feind?
(2023)
ChatGPT – friend or foe?
(2023)
ChatGPT – Freund oder Feind?
(2023)
ChatGPT 4.0 – friend or foe?
(2023)
Fibrin hydrogels have proven highly suitable scaffold materials for skeletal muscle tissue engineering in the past. Certain parameters of those types of scaffolds, however, greatly affect cellular mechanobiology and therefore the myogenic outcome. The aim of this study was to identify the influence of apparent elastic properties of fibrin scaffolds in 2D and 3D on myoblasts and evaluate if those effects differ between murine and human cells. Therefore, myoblasts were cultured on fibrin-coated multiwell plates (“2D”) or embedded in fibrin hydrogels (“3D”) with different elastic moduli. Firstly, we established an almost linear correlation between hydrogels’ fibrinogen concentrations and apparent elastic moduli in the range of 7.5 mg/ml to 30 mg/ml fibrinogen (corresponds to a range of 7.7–30.9 kPa). The effects of fibrin hydrogel elastic modulus on myoblast proliferation changed depending on culture type (2D vs 3D) with an inhibitory effect at higher fibrinogen concentrations in 3D gels and vice versa in 2D. The opposite effect was evident in differentiating myoblasts as shown by gene expression analysis of myogenesis marker genes and altered myotube morphology. Furthermore, culture in a 3D environment slowed down proliferation compared to 2D, with a significantly more pronounced effect on human myoblasts. Differentiation potential was also substantially impaired upon incorporation into 3D gels in human, but not in murine, myoblasts. With this study, we gained further insight in the influence of apparent elastic modulus and culture type on cellular behavior and myogenic outcome of skeletal muscle tissue engineering approaches. Furthermore, the results highlight the need to adapt parameters of 3D culture setups established for murine cells when applied to human cells.
Temporary scaffolds that mimic the extracellular matrix's structure and provide a stable substratum for the natural growth of cells are an innovative trend in the field of tissue engineering. The aim of this study is to obtain and design porous 2D fibroin-based cell matrices by femtosecond laser-induced microstructuring for future applications in muscle tissue engineering. Ultra-fast laser treatment is a non-contact method, which generates controlled porosity-the creation of micro/nanostructures on the surface of the biopolymer that can strongly affect cell behavior, while the control over its surface characteristics has the potential of directing the growth of future muscle tissue in the desired direction. The laser structured 2D thin film matrices from silk were characterized by means of SEM, EDX, AFM, FTIR, Micro-Raman, XRD, and 3D-roughness analyses. A WCA evaluation and initial experiments with murine C2C12 myoblasts cells were also performed. The results show that by varying the laser parameters, a different structuring degree can be achieved through the initial lifting and ejection of the material around the area of laser interaction to generate porous channels with varying widths and depths. The proper optimization of the applied laser parameters can significantly improve the bioactive properties of the investigated 2D model of a muscle cell matrix.
Keywords: biopolymers; femtosecond laser processing; muscle cell matrix 2D model; muscle tissue engineering; silk fibroin.
Background: Most clinical studies report the symptoms experienced by those infected with coronavirus disease 2019 (COVID-19) via patients already hospitalized. Here we analyzed the symptoms experienced outside of a hospital setting.
Methods: The Vienna Social Fund (FSW; Vienna, Austria), the Public Health Services of the City of Vienna (MA15) and the private company Symptoma collaborated to implement Vienna's official online COVID-19 symptom checker. Users answered 12 yes/no questions about symptoms to assess their risk for COVID-19. They could also specify their age and sex, and whether they had contact with someone who tested positive for COVID-19. Depending on the assessed risk of COVID-19 positivity, a SARS-CoV‑2 nucleic acid amplification test (NAAT) was performed. In this publication, we analyzed which factors (symptoms, sex or age) are associated with COVID-19 positivity. We also trained a classifier to correctly predict COVID-19 positivity from the collected data.
Results: Between 2 November 2020 and 18 November 2021, 9133 people experiencing COVID-19-like symptoms were assessed as high risk by the chatbot and were subsequently tested by a NAAT. Symptoms significantly associated with a positive COVID-19 test were malaise, fatigue, headache, cough, fever, dysgeusia and hyposmia. Our classifier could successfully predict COVID-19 positivity with an area under the curve (AUC) of 0.74.
Conclusion: This study provides reliable COVID-19 symptom statistics based on the general population verified by NAATs.
Keywords: Chatbot; Machine learning; Self-reported; Symptom assessment; Symptom checker.
Vortrag im Zuge des Security Monats in Form des FHTW Security Potpourri 2022
In this work we analyse bucket increasing tree families. We introduce two simple stochastic growth processes, generating random bucket increasing trees of size n, complementing the earlier result of Mahmoud and Smythe (1995, Theoret. Comput. Sci.144 221–249.) for bucket recursive trees. On the combinatorial side, we define multilabelled generalisations of the tree families d-ary increasing trees and generalised plane-oriented recursive trees. Additionally, we introduce a clustering process for ordinary increasing trees and relate it to bucket increasing trees. We discuss in detail the bucket size two and present a bijection between such bucket increasing tree families and certain families of graphs called increasing diamonds, providing an explanation for phenomena observed by Bodini et al. (2016, Lect. Notes Comput. Sci.9644 207–219.). Concerning structural properties of bucket increasing trees, we analyse the tree parameter Kn . It counts the initial bucket size of the node containing label n in a tree of size n and is closely related to the distribution of node types. Additionally, we analyse the parameters descendants of label j and degree of the bucket containing label j, providing distributional decompositions, complementing and extending earlier results (Kuba and Panholzer (2010), Theoret. Comput. Sci.411(34–36) 3255–3273.).
In this paper, using the quasilocal formalism of Brown and York, the flow of energy through a closed surface containing a gravitating physical system is calculated in a way that augments earlier results on the subject by Booth and Creighton. To this end, by performing a variation of the total gravitational Hamiltonian (bulk plus boundary part), it is shown that associated tidal heating and deformation effects generally are larger than expected. This is because the aforementioned variation leads to previously unrecognized correction terms, including a bulk-to-boundary inflow term that does not appear in the original calculation of the time derivative of the Brown-York energy and leads to corrective extensions of Einstein’s quadrupole formula in the large sphere limit.
Interference of more and more massive objects provides a spectacular confirmation of quantum theory. It is usually regarded as support for “wave–particle duality” and in an extension of this duality even as support for “complementarity”. We first give an outline of the historical development of these notions. Already here it becomes evident that they are hard to define rigorously, i.e. have mainly a heuristic function. Then we discuss recent interference experiments of large and complex molecules which seem to support this heuristic function of “duality”. However, we show that in these experiments the diffraction of a delocalized center-of-mass wave function depends on the interaction of the localized structure of the molecule with the diffraction element. Thus, the molecules display “dual features” at the same time, which contradicts the usual understanding of wave–particle duality. We conclude that the notion of “wave–particle duality” deserves no place in modern quantum physics.
In this work we discuss a parameter σ on weighted k-element multisets of [n]={1,…,n}. The sums of weighted k-multisets are related to k-subsets, k-multisets, as well as special instances of truncated interpolated multiple zeta values. We study properties of this parameter using symbolic combinatorics. We rederive and extend certain identities for ζtn({m}k). Moreover, we introduce random variables on the k-element multisets and derive their distributions, as well as limit laws for k or n tending to infinity.
Dying Experiments
(2022)
AI Engineering @ FHTW
(2022)
The ERA-Net SES project Regional Renewable Energy Cells (R2EC) [1] aims at developing a scalable system for decentralized, interacting ‘energy cells’ with a high concentration of locally generated renewable energy. ‘Energy cells’ are essentially Renewable Energy Communities (ECs) in the European context. The system aims at maximizing the utilization of locally generated renewable energy through Electrical Storage (ES) as well as high-electric applications like e‑heating, Heat Pumps (HPs), and E‑Vehicles (EVs). The system is also designed to interact with other energy cells locally, thus, improving the utilization of locally generated energy.
A variety of different adjacent energy cells in three countries, Austria (AT), Belgium (BE), and Norway (NO), are analyzed, and the results are used for the development of regional and renewable energy cell systems. This approach aims at developing tailor-made solutions that meet the different local and regional requirements and the electrical energy demand of the observed energy cells. A unique opportunity is created, as the three countries are at varying levels of regional development in the field of energy communities, and the regional requirements and conditions differ significantly. A comprehensive investigation of the technical and economic viability of the ECs in the three regions is conducted on a simulation level. The technical simulation results show an increased self-consumption of individual users and the overall cell in all of the observed testbeds, while the economic analysis shows economic benefits at varying levels in each of the observed testbeds. The implemented R2EC system ascertains both technical and economic viability in the observed testbeds.
A system is invariant with respect to an input transformation if we can transform any dynamic input by this function and obtain the same output dynamics after adjusting the initial conditions appropriately. Often, the set of all such input transformations forms a Lie group, the most prominent examples being scale-invariant (, ) and translational-invariant () systems, the latter comprising linear systems with transfer function zeros at the origin. Here, we derive a necessary and sufficient normal form for invariant systems and, by analyzing this normal form, provide a complete characterization of the mechanism by which invariance can be achieved. In this normal form, all invariant systems (i) estimate the applied input transformation by means of an integral feedback, and (ii) then apply the inverse of this estimate to the input before processing it in any other way. We demonstrate our results based on three examples: a scale-invariant “feed-forward loop”, a bistable switch, and a system resembling the core of the mammalian circadian network.
The current shift in teaching and learning away from the physical
classroom to blended and digital learning environments presents many
challenges and opportunities for both teachers and learners. A
somewhat overlooked aspect of this transition concerns the issue of
student collaboration in blended learning situations. Students teaming
up to improve their learning process, exchange ideas and achieve
learning goals has been an integral part of the higher education
experience for many, while also strengthening students social skills.
With the physical distancing and accompanying shift to increased
online learning settings of the past few years, establishing this
collaboration between students has become more and more difficult.
Well-conceived digital social learning spaces and opportunities might
be a way to compensate for these missed out traditional learning
situations with peers in or after class.
Going beyond typical group work activities teachers often utilize in
their classes, Moodle offers a wide variety of opportunities for
teachers to design these digital learning spaces tailored to the
specific needs and objectives of their classes and students. Following
a student-centred learning paradigm and a conception of the teacher as
a designer and enabler of learning opportunities, we want to present a
few use cases of Moodle activities, plugins and integrated tools
suitable for designing these social spaces online. Among others we
would like to showcase possible scenarios for peer assessments, open
video conferencing rooms for students with BigBlueButton,
collaborative test preparation with StudentQuiz, and connecting
learners through a creative usage of the database activity. Picking up
these different resources, we hope to motivate and inspire educators
to design and roll out collaborative online spaces for their students
to enable better teamwork and achieve deeper learning.
Entrepreneurs keep the economy and society going by implementing new ideas. Entrepreneurship competencies such as creativity, risk tolerance or perseverance do not only emerge in professional life, but are already developed in early phases of socialization. Entrepreneurship education with its strongly action-oriented teaching and learning formats plays a triggering and process-reinforcing role in this respect. However, the competencies acquired through entrepreneurship education are also increasingly important for successful action in dependent employment. This article first shows that the goals and means of Entrepreneurship Education harmonize with the high practical relevance of teaching required by the Austrian Universities of Applied Sciences Act. Against this background, a concrete example of implementation is used to illustrate how the curricular anchoring of a student project in an engineering course can promote not only the practical relevance of teaching, but also the teaching of entrepreneurial competencies and the transfer of innovation between the university and industry.
The traditional methods of fighting metal fires are not always safe for firefighters. The sand and salts that are thrown onto the fire to suffocate the flames can lead to splashes of molten metal, putting the firefighters and the surroundings at risk. A novel process is described where magnesium fires are brought under control using a simple two-step process. First, coated cellulose flakes, which contain approx. 30% inorganic salts, are blown onto the fire from a distance of several meters. Due to its low bulk density, the material settles smoothly on the fire and immediately covers the flames for several seconds. Before the hot metal can break through this cover, a fine water spray is applied to the fire. The water spray wets the top layer of the cellulose flakes, which will begin to char from the bottom. The water evaporates from within the cellulose flake layer and withdraws heat. It was observed that no hydrogen is formed and that this technique can safely control fires. It is judged that 90 kg of flakes could safely bring a pile of 75 kg of burning Mg flakes under control. By using a pneumatic conveying unit for the flakes, firefighters can effectively and efficiently cover the flames from a safe distance. This novel method could be recommended to firefighters in industrial magnesium processing plants, as well as local firefighters in the vicinity of such plants.
This study aimed to investigate the effects of slaughter age (young vs. old), muscle type (Longissimus dorsi (LD), Gluteus medius (GM)) and fat deposits (kidney knob and channel fat, subcutaneous fat, intramuscular fat) on chemical, organoleptic, textural characteristics and fatty acid composition of Holstein Friesian bull meat. For this purpose, the carcasses of 26 Holstein Friesian bulls that had been fattened on the same private farm were assigned to two experimental groups based on their age at slaughter: a young group (YG) (average age: 17.0 ± 1.0 months old) and an old group (OG) (average age: 22.0 ± 1.0 months old). The percentage of crude protein, panel tenderness score, polyunsaturated fatty acid (PUFA) and saturated fatty acid (SFA) content, the PUFA/SFA ratio and the hypocholesterolemic fatty acid (DFA)/hypercholesterolemic fatty acid (OFA) ratio of the bull carcasses decreased significantly with increasing slaughter age. By contrast, the OFA content of the carcasses significantly increased (p < 0.05) with increasing slaughter age. Advanced slaughter age resulted in lower panel tenderness scores. Additionally, the meat of the bulls in the OG was considered to be less healthy because of the less desirable fatty acid composition and nutritional indices, such as the PUFA/SFA and hypocholesterolemic/hypercholesterolemic ratios, compared to the meat from the bulls in the YG. Furthermore, the intramuscular fat and internal fat contained high percentages of PUFA and SFA and high PUFA/SFA and hypocholesterolemic/hypercholesterolemic ratios. Interestingly, the percentage of OFA content in the internal and intramuscular fat tissues decreased with increasing slaughter age. In conclusion, this study provided evidence that slaughter age and muscle and fat type are essential sources of variations in the textural characteristics, sensory panel attributes and fatty acid profile of meat from Holstein Friesian bulls.
The aim of this study was to investigate the effect of different forms of Lentilactobacillus buchneri on the in vitro methane production, fermentation characteristics, nutritional quality, and aerobic stability of corn silage treated with or without urea. The following treatments were applied prior to ensiling: (1) no urea treatment and LB; (2) no urea treatment+freeze dried LB; (3) no urea treatment+preactivated LB; (4) with urea treatment+no LB; (5) with urea treatment+freeze dried LB; (6) with urea treatment+preactivated. LB was applied at a rate of 3 × 108 cfu/kg on a fresh basis, while urea was applied at a rate of 1% on the basis of dry matter. Data measured at different time points were analyzed according to a completely randomized design, with a 2 × 3 × 5 factorial arrangement of treatments, while the others were analyzed with a 2 × 3 factorial arrangement. Preactivated LB was more effective than freeze-dried LB in reducing silage pH, ammonia nitrogen, cell-wall components, yeast count, and carbon dioxide production, as well as increasing lactic acid and residual water-soluble carbohydrate and aerobic stability (p < 0.0001). A significant reduction in the methane ratio was observed after 24 h and 48 h incubation with preactivated forms of LB (p < 0.001). The results indicated that preactivated LB combined with urea improved fermentation characteristics, nutritional quality, and aerobic stability and reduced the methane ratio of corn silages.
Methane is the main greenhouse gas (GHG) emitted by ruminants. Mitigation strategies are required to alleviate this negative environmental impact while maintaining productivity and ruminants’ health. To date, numerous methane mitigation strategies have been investigated, reported and suggested by scientists to the livestock industry. In this review, the authors will focus on the commonly practiced and available techniques expanding the knowledge of the reader on the advances of methane mitigation strategies with a focus on the recent literature. Furthermore, the authors will attempt to discuss the drawbacks of the strategies in terms of animal health and performance reduction as well as the concept of feed and energy loss, adding an economic perspective to methane emission mitigation which is in the farmers’ direct interest. As a whole, many factors are effective in reducing undesired methane production, but this is definitely a complex challenge. Conclusively, further research is required to offer effective and efficient methane production mitigation solutions in ruminants worldwide, thus positively contributing to climate change.
Quail is used in cookery, but mainly for its egg production around the globe, and sustainable poultry farming practices have been searched. The use of colostrum (beestings or first milk from cows) in quails’ diet can play an important role in providing probiotics and reducing the need for antibiotics, which, in addition to better quail performance, is effective in reducing environmental impacts. The results of the current research show that the continuous use of bovine colostrum (BC) in laying quails’ diets has beneficial effects on their performance, egg traits, blood indexes and antioxidant status.
Methane emission from enteric fermentation in ruminants is the single most relevant greenhouse gas source in agriculture, and it is amongst the largest anthropogenic ones. As ruminants are needed globally for meat, milk and other goods production on a huge scale, feed additives could offer an interesting solution to reduce CH4 emissions. Methane emission strategies are investigated to maintaining productivity and the overall health of the animal. Some strategies have shown to reduce the propagation and/or eliminate ruminal flora affecting the health and productivity of the animal. Therefore, identifying beneficial strategies leads to improving productivity and the health of the animal and environment.
Perspectives on Virtual Reality in Higher Education for Robotics and Related Engineering Disciplines
(2022)
Industrial engineering education has a strong focus on and affinity towards technology. While Virtual Reality hardware and applications advance and learning behaviour changes, it is particularly interesting to determine the possible use of Virtual Reality for teaching engineering subjects, for example fundamentals of robotics.
This paper presents a study which examines the possible use of Virtual Reality learning environments at higher learning institutions. The study shows perspectives of students and lecturers and identifies opportunities and challenges for the use of Virtual Reality in industrial engineering education. The results of the indicated study show that the participants have a positive attitude towards Virtual Reality and strong motivation for in class use. The study results also suggest, that Virtual Reality content creation should be included in engineering curricula.
Hochschulen und Studiengänge sprechen Studieninteressierte nicht
bevölkerungsrepräsentativ an. Nach einem kurzen Abriss der aktuellen Lage und
der Diversitätsdimensionen werden anhand einer adaptierten Form der „4R-
Methode“ des Gender-Mainstreamings Kommunikationsarten, -medien und
-ebenen mit Blick auf Kommunizierende und Kontexte beleuchtet. Dieser Beitrag
soll Hochschulen und Studiengängen einen einfachen Leitfaden an die Hand
geben, die eigene Sprache auf den verschiedenen Kommunikationskanälen
kritisch zu reflektieren und inkludierender zu gestalten, um Stereotypisierung zu
vermeiden und alle anzusprechen
Dry powder inhalers are used by a large number of patients worldwide to treat respiratory diseases. The objective of this work is to experimentally investigate changes in aerosol particle diameter and particle number concentration of pharmaceutical aerosols generated by four dry powder inhalers under realistic inhalation and exhalation conditions. To simulate patients undergoing inhalation therapy, the active respiratory system model (xPULM™) was used. A mechanical upper airway model was developed, manufactured, and introduced as a part of the xPULM™ to represent the human upper respiratory tract with high fidelity. Integration of optical aerosol spectrometry technique into the setup allowed for evaluation of pharmaceutical aerosols. The results show that there is a significant difference (p < 0.05) in mean particle diameter between inhaled and exhaled particles with the majority of the particles depositing in the lung, while particles with the size of (>0.5 μm) are least influenced by deposition mechanisms. The fraction of exhaled particles ranges from 2.13% (HandiHaler®) over 2.94% (BreezHaler®), and 6.22% (Turbohaler®) to 10.24% (Ellipta®). These values are comparable to previously published studies. Furthermore, the mechanical upper airway model increases the resistance of the overall system and acts as a filter for larger particles (>3 μm). In conclusion, the xPULM™ active respiratory system model is a viable option for studying interactions of pharmaceutical aerosols and the respiratory tract regarding applicable deposition mechanisms. The model strives to support the reduction of animal experimentation in aerosol research and provides an alternative to experiments with human subjects.
Bidirectional electric vehicle supply equipment and charging stations (EVSE) offer new business models and can provide services to the electrical grid. The smart grid lab in Vienna gives unique testing possibilities of future smart grids, as different type of electrical equipment can be operated at a reconstructed, well-known distribution grid. In this work the harmonic and supraharmonic emissions of a bidirectional EVSE are measured according to IEC61000-4-7 and IEC61000-4-30 Ed3 standard as well as the high-frequency grid impedance. In addition, the efficiency and the power factor are determined at various operating points. Although THDi at nominal power (10 kW) is very low and the efficiency and power factor is very high, at low power levels the opposite situation arise. Supraharmonic emissions remain stable independent of the charging/discharging power, and both wideband and narrowband emissions occur. The additional capacitance when connecting the EVSE impacts the high-frequency grid impedance substantially and generates resonance points.
Abstract: The biological investigation of a population’s shape diversity using digital images is typi-
cally reliant on geometrical morphometrics, which is an approach based on user-defined landmarks.
In contrast to this traditional approach, the progress in deep learning has led to numerous applications
ranging from specimen identification to object detection. Typically, these models tend to become black
boxes, which limits the usage of recent deep learning models for biological applications. However, the
progress in explainable artificial intelligence tries to overcome this limitation. This study compares
the explanatory power of unsupervised machine learning models to traditional landmark-based
approaches for population structure investigation. We apply convolutional autoencoders as well
as Gaussian process latent variable models to two Nile tilapia datasets to investigate the latent
structure using consensus clustering. The explanatory factors of the machine learning models were
extracted and compared to generalized Procrustes analysis. Hypotheses based on the Bayes factor are
formulated to test the unambiguity of population diversity unveiled by the machine learning models.
The findings show that it is possible to obtain biologically meaningful results relying on unsupervised
machine learning. Furthermore we show that the machine learning models unveil latent structures
close to the true population clusters. We found that 80% of the true population clusters relying on
the convolutional autoencoder are significantly different to the remaining clusters. Similarly, 60% of
the true population clusters relying on the Gaussian process latent variable model are significantly
different. We conclude that the machine learning models outperform generalized Procrustes analysis,
where 16% of the population cluster was found to be significantly different. However, the applied
machine learning models still have limited biological explainability. We recommend further in-depth
investigations to unveil the explanatory factors in the used model.
Keywords: generalized procrustes analysis; machine learning; convolutional autoencoder; Gaussian
process latent variable models