Schmalkalden University of Applied Sciences

Online marketplace providers such as Amazon may also offer own-brand products, in this way competing with third-party traders on their platform. Moreover they may exploit nonpublic data on third-party sales to identify opportunities for profit and design their own products, thus engaging in a form of partial imitation that is exclusive to them. Such an asymmetry in the ability to imitate has led to advocating for stricter regulation of online platforms in order to limit their ability to exploit nonpublic data. I propose a dynamic simulation model to study the effects of insider imitation by a platform provider under product differentiation. Using different parametrizations, I am able to show how such a market may evolve in time with or without the presence of insider imitation under different initial conditions. The model also allows to account for subsequent innovation via imitation (which I refer to as copy-and-be-copied dynamics), an aspect not considered by previous studies. These results add to the existing literature and cast further doubts on current regulatory approaches aiming at limiting data exploitation. Results suggest that the presence of insider imitation is unlikely to lead to smaller consumer welfare and larger market concentration and should not be banned on the grounds of standard antitrust concerns.

‘Logic’ is a science that deals with the principles and criteria of the validity of inferences and demonstration, or the formal principles of reasoning. It is said that the specific task of logic as a branch of knowledge is to study the forms of a valid argument and it has been posited that any study of legal reasoning is an attempt to expiscate and explain the criteria as to what constitutes a good or a bad, or an acceptable or an unacceptable, type of legal argument. A syllogism is defined as ‘a formal argument in logic that is formed by two statements and a conclusion which must be true if the two statements are true’. The syllogism is regarded as the logical and analytical framework for legal reasoning in the common law tradition. Aristotle’s contribution to logic, in particular his theory of syllogism, has been regarded as having an unparalleled influence on Western thought. This chapter analyses the veracity of the theory of syllogism as the framework for reasoning in common law reasoning and compares these outcomes to a civil law system, adopting Germany as an exemplar of the latter.

Introduction High email load has been associated with impaired well-being because emails impose specific demands, disturb the workflow, and thereby overtax individuals’ action regulation toward prioritized goals. However, the causes and well-being-related consequences of email load are not yet well understood, as previous studies have neglected the interaction type and function of emails as well as co-occurring stressors as antecedents of high email load and have relied predominantly on cross-sectional designs. Methods In two studies, we aimed to clarify the nature of email load through the lens of action regulation theory. The first study, a two-wave investigation with a fortnightly interval, examined the lagged relationships among email load, work stressors, strain, and affective well-being. The sample included 444 individuals across various occupations and organizations, with 196 of them working from home or remotely at least part of the time. In the second cross-sectional study, we surveyed 257 individuals using a convenience sampling approach, 108 of whom worked from home or remotely at least partially. This study focused on evaluating how different email classes—distinguished by email interaction type (received vs. processed) and email function (communication vs. task)—serve as predictors of high email load. Results In Study 1, we found a positive lagged effect of high email load on strain, even when controlling for the co-occurring stressors time pressure and work interruptions. In addition, lagged effects of email load on time pressure and interruptions were identified, while no evidence was found for the reverse direction. The results of Study 2 suggest that only the number of communication-related emails received, but not the number of task-related emails received, or the number of all emails processed contribute to high email load. Conclusion Findings suggest that email load can be considered a unique stressor and that different classes of email need to be distinguished to understand its nature. Clarifying the sources of email load can help develop effective strategies to address it.

Zusammenfassung Hintergrund Für die Behandlung der Symptome des Post-COVID-19-Syndroms wird derzeit keine kausale Therapie nach evidenzbasierten Kriterien breit empfohlen. Die Evaluation der Veränderungen des Leitsymptoms Fatigue und der sensomotorischen Instabilität durch eine individualisierte beanspruchungsgesteuerte Trainingstherapie sowie durch eine intensivierte kognitive Verhaltenstherapie war das übergeordnete Ziel der Interventionsstudie über einen 3‑jährigen Zeitraum (Q1-2021 bis Q4-2023). Methodik Es wurden in den 3 Jahren im Post-COVID-19-Zentrum Lausitz (Senftenberg) 407 geimpfte nukleokapsidpositive Patienten behandelt. Bei 78 (rd. 19 %) von ihnen wurden als Leitsyndrome Fatigue/immunometabolische Depression und sensomotorische Instabilität konstatiert. Die Evaluation der individualisierten beanspruchungsgesteuerten Trainingstherapie erfolgte anhand der konkreten Post-COVID-19-Syndromatik und motorischer Fatigability-Parameter. Die sekundäre psychosomatische Syndromatik wurde mit kognitiven Fatigability-Parametern und mit Instrumenten der kognitiven Verhaltenstherapie bewertet. Die Untersuchung verhaltensbeeinflussender Parameter fand in Q2-2023 bis Q4-2023 mit einem leitfadengestützten qualitativen Interview unter den Therapieteilnehmern statt. Ergebnisse Die Post-COVID-19-Leitsymptomen „Fatigue“, „sensomotorische Instabilität“, „neuropsychiatrische Symptome“, „kardionale/autonome Dysfunktion“ und „Schmerzen“ verbesserten sich signifikant in der Gesamtkohorte sowie bei der geschlechtsspezifischen Analyse. Eine Verschlechterung trat bei „sekundären psychosomatischen Symptomen“ auf. Für alle motorischen Fatigability-Parameter konnte für die Gesamtkohorte mit dem Cohens d-Wert ein therapeutischer Effekt nachgewiesen werden. Positive Wirkungen erzielte eine Intensivierung der kognitiven Verhaltenstherapie durch eine zunehmende Entwicklung der Eigenaktivität der Patienten sowie deren Selbstkontrolle unter Einsatz von Persuasion und Gamification.

Neutron sources based on laser-accelerated particles have attracted interest as they may provide a compact, cost-effective alternative to conventional sources. Recently, laser-driven neutron sources, based on ion acceleration, demonstrated neutron resonance spectroscopy, imaging and resonance imaging in first proof-of-principle experiments. To drive these sources efficiently with laser-accelerated ions, high laser pulse energies, in the range of tens to hundreds of Joules, with sub-ps pulse duration are needed. This requirement currently limits ion-based laser neutron sources to large-scale laser systems, which typically have maximum repetition rates in the order of a few shots per hour. In this paper, we investigate a potential path to circumvent these limitations by utilizing high repetition rate capable laser wakefield acceleration of electrons to drive a neutron source with high conversion efficiency. Monte Carlo simulations are performed to calculate neutron yields for various electron energies and converter materials, to determine optimal working parameters for an electron-based laser-driven neutron source. The results suggest that conversion efficiencies exceeding 25% can be achieved, depending on the electron energy and converter material. This electron-based approach could provide a neutron source with up to 10 $^{11}$ 11 n/s with state-of-the-art laser sources ( $E_{\text {Laser}} \lesssim {1}\,{\rm J}$ E Laser ≲ 1 J , $\tau _{\text {Laser}} \lesssim {50}\,{\rm fs}$ τ Laser ≲ 50 fs , $\sim {1}\,\textrm{kHz}$ ∼ 1 kHz ).

Quality management must continuously adapt to new business trends and technical progress. However, there is often a lack of time and resources to deal with the development of new methods for quality management. For this reason, the focus in practice is primarily on the question of how established quality management methods can be specifically adapted and expanded for new fields of application. At this point, conceptual modeling and metamodeling are valuable means to integrate new concepts with established quality techniques and methods to further develop the discipline. This paper highlights the topics of “smart services” and “environmental sustainability” and shows how modeling-based solutions for these fields can be purposefully created with the help of metamodeling.

Despite years of extensive research, achieving the optimal properties for calcium phosphate-based biomaterials remains an ongoing challenge. Recently, ‘biomicroconcretes’ systems consisting of setting-phase-forming bone cement matrix and aggregates (granules/microspheres) have been developed and studied. However, further investigations are necessary to clarify the complex interplay between the synthesis, structure, and properties of these materials. This article focusses on the development and potential applications of hybrid biomaterials based on alpha-tricalcium phosphate (αTCP), hydroxyapatite (HA) and methylcellulose (MC) modified with silver (0.1 wt% or 1.0 wt%). The study presents the synthesis and characterization of silver-modified hybrid granules and seeks to determine the possibility and efficiency of incorporating these hybrid granules into αTCP-based biomicroconcretes. The αTCP and hydroxyapatite provide structural integrity and osteoconductivity, the presence of silver imparts antimicrobial properties, and MC allows for the self-assembling of granules. This combination creates an ideal environment for bone regeneration, while it potentially may prevent bacterial colonization and infection. The material’s chemical and phase composition, setting times, compressive strength, microstructure, chemical stability, and bioactive potential in simulated body fluid are systematically investigated. The results of the setting time measurements showed that both the size and the composition of granules (especially the hybrid nature) have an impact on the setting process of biomicroconcretes. The addition of silver resulted in prolonged setting times compared to the unmodified materials. Developed biomicroconcretes, despite exhibiting lower compressive strength compared to traditional calcium phosphate cements, fall within the range of human cancellous bone and demonstrate chemical stability and bioactive potential, indicating their suitability for bone substitution and regeneration. Further in vitro studies and in vivo assessments are needed to check the potential of these biomaterials in clinical applications.

In the world of professional growth and teacher education, reflection holds a position as a profound but sometimes overlooked phenomenon. At a first glance, reflection can seem like a simple buzzword, used in a lot of circumstances, potentially because it sounds professional and caring but is often used without thought. The multiple uses, both in everyday language and in professional discourse, can make it difficult to determine what it actually means. Throughout this chapter, we will attempt to comment on the intricate ways in which reflection shapes teachers’ perceptions, influences their decisions, and ultimately contributes to their personal and professional growth and self-awareness that have been developed throughout the book. Although it is, of course, an ambitious undertaking that cannot be fully realized in the context of such a brief treatise, the following will attempt to present reflection in more detail in several aspects based on the considerations from this anthology.

This anthology attempts to link the theoretical discussion about reflection in academic teacher training to the practical developing competence (underlying ability) and competencies (actionable skills) needed for classroom success with concrete examples as well as studies that help us understand some of the underlying and sometimes unnamed assumptions and beliefs that guide our teaching of teachers. It offers a collection of insights and tools that aim to guide teacher educators in the teaching of reflective practice and help them to integrate reflection into their students’ everyday actions in order to ensure the quality and further development of their work. The anthology itself is organized around specific tools, broader applications in specific contexts, perceptions, and policies.

The worldwide shortage of professionally trained teachers shows the general necessity to find sustainable forms of teacher education and training—this actually affects all subjects but is particularly visible in the case of German teachers. Research-Based Learning and Action Research, both of which quite significantly involve reflection, seem to offer useful approaches to counter this situation, although further surveys for concrete application are needed. Taking up the issue, the article pursues the question to what extent tools used by Action Research can be a useful instrument in teacher education, even at the undergraduate level. For this purpose, a course offered to German teacher education students in Brazil is presented and, by means of a retrospective survey (n = 12), the impact of the course on the further activity as a German teacher is investigated. The research was based on a grid of questions used in the Goethe-Institut’s “Deutsch Lehren Lernen” program (DLL), which is broadly used in a wide variety of educational contexts and is specifically aimed at practicing reflection techniques. The results suggest that it does not necessarily need a complete training cycle, but that appropriate impulses and suggestions, even for a limited period of time, already can have a long-term impact on the perception of teaching and the reflection skills of the participants involved.

Online marketplace providers such as Amazon may also offer own-brand products, thus competing with third-party traders on their platform. Moreover they may exploit nonpublic data on third-party sales to identify opportunities for profit and design their own products, in this way engaging in a form of partial imitation that is exclusive to them. Such an asymmetry in the ability to imitate has led to advocating for stricter regulation of online platforms in order to limit their ability to exploit nonpublic data. We propose a dynamic simulation model to study the effects of insider imitation by a platform provider under product differentiation. Using different parametrizations, we are able to show how such a market may evolve in time with or without the presence of insider imitation under different initial conditions. The model also allows to account for subsequent innovation via imitation, which is an aspect not considered by previous studies. Our results add to the existing literature and casts further doubts on current regulatory approaches aiming at limiting data exploitation. Our results suggest that the presence of insider imitation is more likely to lead to higher consumer welfare and lower market concentration and should not be banned on the grounds of standard Antitrust concerns. JEL Classifications: D40, D82, D83, L40, O3

Universities are an integral player of the entrepreneurial ecosystem. Today, almost all universities have startup centers, creative or innovation hubs, co-working spaces, etc. in their structure. A significant part of startups is born in universities and undergo their first testing there. Ukrainian universities train students in wide range of specialities and employ specialists from various fields, which allows to create university startup clinics, including Law Clinic, Business Model Innovation Clinic, Finance Clinic, HR & Culture Clinic, Sales & Marketing Clinic, as well as Soft Skills Clinic and Tech & Digitalization Clinic. The main tasks for each department are disclosed. For the launch of such clinics, a structured algorithm (“action protocol”) is proposed in the paper. The goal is to test various projects in their early stages (stages of uncertainty). The lecturer-student-business interaction is outlined. In sum a favourable environment for the creation of innovative projects is generated. The launching of “multi specialised” startup clinics in Ukrainian universities is a vital step for reforming the education system and a practical step towards the introduction of practical-oriented training as well as raising the impact of Ukrainian entrepreneurial ecosystem locally and globally.

An accurate prediction of complex product quality parameters from process time series by an end-to-end learning approach remains a significant challenge in machine learning. A special difficulty is the application of industrial batch process data because many batch processes generate variable length time series. In the industrial application of such methods, explainability is often desired. In this study, a 1D convolutional neural network (CNN) algorithm with a masking layer is proposed to solve the problem for time series of variable length. In addition, a novel combination of 1D CNN and class activation mapping (CAM) technique is part of this study to better understand the model results and highlight some regions of interest in the time series. As a comparative state-of-the-art unsupervised machine learning method, the One-Nearest Neighbours (1NN) algorithm combined with dynamic time warping (DTW) was used. Both methods are investigated as end-to-end learning methods with balanced and unbalanced class distributions and with scaled and unscaled input data, respectively. The FastDTW and DTAIDistance algorithms were investigated for the DTW calculation. The data set is made up of sensor signals that was collected during the production of plastic parts. The objective was to predict a quality parameter of plastic parts during production. For this research, the quality parameter will be a difficult or only destructively measurable parameter and both methods will be investigated for their applicability to this prediction task. The application of the proposed approach to an industrial facility for producing plastic products shows a prediction accuracy of 83.7%. It can improve the reverence method by approximately 1.4%. In addition to the slight increase in accuracy, the CNN training time was significantly reduced compared to the DTW calculation.

Zusammenfassung Datenschutz ist für in- und externe Meldestellen im Sinne des Hinweisgeberschutzgesetzes (HinSchG) von großer Bedeutung, weil diese spezifische und angemessene Maßnahmen zur Wahrung der Interessen ,,betroffener Personen‘‘ i.S. der DSGVO vorzusehen haben. In der Praxis wird dies nur funktionieren, wenn ,,Interessenskonflikte‘‘ bei am Meldeverfahren beteiligten Personen möglichst vermieden werden. In diesem Beitrag werden relevante Sachverhalte beschrieben und bewertet sowie Handlungsoptionen für Meldestellen pflichtige ,,Beschäftigungsgeber‘‘ skizziert.

We introduced a novel method for visualizing large diophantine datasets and in particular found that mapping the known integer triplets {a,b,c}$\{a,b,c\}$ solving either equations of the type a3+b3+c3=d$a^3+b^3+c^3=d$ or a3+b3+c3=d3$a^3+b^3+c^3=d^3$ on certain proper subgroups of the circle group exposed a very clear breaking in their symmetry and a strongly non-ergodic distribution of the solutions of sums of three cubes that had never been described before. This method could be further applied to a larger diversity of diophantine problems, informing both number-theoretical conjectures and novel methods in computer sciences on the way, along with paving the road for specific uses of machine learning in exploring diophantine datasets with possible applications in cryptography among others.