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Fast protein and metabolite liquid chromatography (FPLMC) was introduced years ago to enable the easy separation of high-molecular compounds such as proteins from small molecules and the identification of the low-molecular substances. In this paper, the method is applied for the rapid evaluation of freshness and monitoring the aging of animal meat and fish. A novel chromatographic sensor was developed with a deep UV LED-based photometric detection unit (255–265 nm), an original flow cuvette and registration scheme; the processing of a chromatogram with the sensor takes approximately 15 min. Strict isochronism between the elution of ATP metabolites, mainly hypoxanthine (Hx) and inosine monophosphate (IMP), and the time of maturation of meat or fish, was discovered. A new freshness index H* = [Hx]/[IMP] was introduced, which is proportional to the instrumental delay time in the FPMLC chromatograms: the H* index < 0.5 indicates the presence of inosine monophosphate (IMP) and the high quality of the meat or fish. Reasonably strong correlations were revealed between data obtained by FPMLC and total volatile basic nitrogen TVB-N (for fish) or volatile fatty acids VFA (for meat) content. Moreover, putative nucleotide salvage and an increase in the concentration of IMP were observed in fish after heat treatment using the FPMLC sensor and NMR technique.
Der vorliegende Beitrag befasst sich mit den Herausforderungen, die im Rahmen von Remote Work
in Kooperationen bezüglich der Informations- und
IT-Sicherheit bestehen, insbesondere im Hinblick auf
den sicheren Datenaustausch. Des Weiteren wird die
Wichtigkeit einer ganzheitlichen Sicht von IT-Governance-, Risiko- und Compliance-Management in Verbünden kleiner und mittlerer Unternehmen (KMU)
behandelt. Weiterhin wird aufgezeigt, was bei der
informationstechnischen Absicherung von Kooperationen und IT-Konsortien beachtet werden sollte.
A sample set of calculations is presented in this supplemental document to analytically estimate joint distortion for gas metal arc lap joining of aluminum and steel thin sheets following the published article "Analytical Estimation of Thermomechanical Distortion and Interface Layer Thickness for Gas Metal Arc Lap Joining of Dissimilar Sheets"
Large three-dimensional metallic parts can be printed layer-by-layer using gas metal arc directed energy deposition (GMA-DED) process at a high deposition rate and with little or no material wastage. Fast responsive real-time monitoring of GMA-DED process signatures and their transient variations is required for printing of dimensionally accurate and structurally sound parts. A systematic experimental investigation is presented here on multi-layer GMA-DED with two different scanning strategies using a high strength low alloy (HSLA) filler wire. The dynamic metal transfer, melt pool temperature field and its longitudinal cross-section, and arc voltage and current are monitored synchronously. The transient arc heat input and the melt pool solidification cooling rate are estimated from the monitored signals. The layer-wise variations of the melt pool dimension, surface temperature profile, thermal cycles, and solidification cooling rate are examined for different scanning strategies. It is comprehended that the part defects can be minimized, and the mass production of zero-defect parts can be achieved in GMA-DED process with synchronized monitoring and assessment of the real-time process signatures.
Layered van der Waals ferromagnets, which preserve their magnetic properties down to exfoliated monolayers, are fueling an abundance of fundamental research and nanoscale device demonstration. CrGeTe3 is a prime example of this class of materials. Its temperature-pressure phase diagram features an insulator-to-metal transition and a significant increase in ferromagnetic Curie-Weiss temperatures upon entering the metallic state. We use density functional theory to understand the magnetic exchange interactions in CrGeTe3 at ambient and elevated pressures. We calculate Heisenberg exchange couplings, which provide the correct ferromagnetic ground state and explain the experimentally observed pressure dependence of magnetism in CrGeTe3. Furthermore, we combine density functional theory with dynamical mean-field theory to investigate the effects of electronic correlations and the nature of the high-pressure metallic state in CrGeTe3.
An approach for analyzing business process execution complexity based on textual data and event log
(2023)
With the advent of digital transformation, organizations increasingly rely on various information systems to support their business processes (BPs). Recorded data, including textual data and event log, expand exponentially, complicating decision-making and posing new challenges for BP complexity analysis in Business Process Management (BPM). Herein, Process Mining (PM) serves to derive insights based on historic BP execution data, called event log. However, in PM, textual data is often neglected or limited to BP descriptions. Therefore, in this study, we propose a novel approach for analyzing BP execution complexity by combining textual data serving as an input at the BP start and event log. The approach is aimed at studying the connection between complexities obtained from these two data types. For textual data-based complexity, the approach employs a set of linguistic features. In our previous work, we have explored the design of linguistic features favorable for BP execution complexity prediction. Accordingly, we adapt and incorporate them into the proposed approach. Using these features, various machine learning techniques are applied to predict textual data-based complexity. Moreover, in this prediction, we show the adequacy of our linguistic features, which outperformed the linguistic features of a widely-used text analysis technique. To calculate event log-based complexity, the event log and relevant complexity metrics are used. Afterward, a correlation analysis of two complexities and an analysis of the significant differences in correlations are performed. The results serve to derive recommendations and insights for BP improvement. We apply the approach in the IT ticket handling process of the IT department of an academic institution. Our findings show that the suggested approach enables a comprehensive identification of BP redesign and improvement opportunities.
The Patellostabilometer: A New Device for Quantification of Mediolateral Patella Displacement
(2023)
Mediolateral patella displacement is of interest for diagnostics and clinically relevant
research questions. Apart from manual testing, no standardized method is currently available. Proper
quantification of patella mobility is necessary to better understand pathologies at the patellofemoral
joint. Patella mobility was assessed in 25 healthy individuals using a Patellostabilometer, a new
prototype instrument for quantification of the mediolateral patella displacement. The participants
underwent measurements of the mediolateral displacement three times using the Patellostabilome-
ter. A maximal force of 10 N was applied for patella movement. Additionally, leg length and
circumference of the knee, upper- and lower-leg were measured. Lateral patella displacement of
18.27 ± 3.76 mm (range 15.85–20.64 mm, interquartile range (IQR) of 4.79) was measured. The medial
patella displacement showed 24.47 ± 6.59 mm (range 19.29–29.76 mm, IQR of 10.47). The test–retest
measurement error was 2.32 ± 1.76 mm (IQR of 2.38 mm), with five outliers. There was greater
test–retest variability between the measurements of the medial displacement compared to the lateral
one. The test–retest variability reached 7% of the patella displacement. Other parameters provided no
significant correlations. Based on the natural patellofemoral mobility, a precise and clinically relevant
quantification of patella mobility is allowed.
The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services.
We present a method for the arbitrage-free interpolation of plain-vanilla option prices and implied volatilities, which is based on a system of integral equations that relates terminal density and option prices. Using a discretization of the terminal density, we write these integral equations as a system of linear equations. We show that the kernel matrix of this system is, in general, ill-conditioned, so that it cannot be solved for the discretized density using a naive approach. Instead, we construct a sparse model for the kernel matrix using singular value decomposition (SVD), which allows us not only to systematically improve the condition number of the kernel matrix, but also determines the computational effort and accuracy of our method. In order to allow for the treatment of realistic inputs that may contain arbitrage, we reformulate the system of linear equations as an optimization problem, in which the SVD-transformed density minimizes the error between the input prices and the arbitrage-free prices generated by our method. To further stabilize the method in the presence of noisy input prices or arbitrage, we apply an 𝐿1-regularization to the SVD-transformed density. Our approach, which is inspired by recent progress in theoretical physics, offers a flexible and efficient framework for the arbitrage-free interpolation of plain-vanilla option prices and implied volatilities, without the need to explicitly specify a stochastic process, expansion basis functions or any other kind of model. We demonstrate the capabilities of our method in a number of artificial and realistic test cases.
Disclinations or disclination clusters in smectic C freely suspended films with topological charges larger than one are unstable. They disintegrate, preferably in a spatially symmetric fashion, into single defects with individual charges of +1, which is the smallest positive topological charge allowed in polar vector fields. While the opposite process of defect annihilation is well-defined by the initial defect positions, disintegration starts from a singular state and the following scenario including the emerging regular defect patterns must be selected by specific mechanisms. We analyze experimental data and compare them with a simple model where the defect clusters adiabatically pass quasi-equilibrium solutions in one-constant approximation. It is found that the defects arrange in geometrical patterns that correspond very closely to superimposed singular defect solutions, without additional director distortions. The patterns expand by affine transformations where all distances between individual defects scale with the same time-dependent scaling factor proportional to the square-root of time.
Context awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it becomes essential to employ relevant text analytics techniques to increase the awareness of process workers, which is important for process execution. The present paper addresses this demand by developing a framework for context awareness based on process executions-related textual data using a well-established layered BPM context model. This framework combines and maps various text analytics techniques to the layers of the context model, aiming to increase the context awareness of process workers and facilitate informed decision-making. The framework is applied in an IT ticket processing case study. The findings show that contextual information obtained using our framework enriches the awareness of process workers regarding the process instance urgency, complexity, and upcoming tasks and assists in making decisions in terms of these aspects.
Compliance-Management
(2023)
Dieses Buch bietet eine komprimierte und praxisorientierte Einführung in die Grundlagen und Anforderungen eines Compliance-Managements, um den Leser schnell mit aktuellen und zentralen Regelungen vertraut zu machen. Dabei wird auf gesetzliche und regulatorische Bestimmungen ebenso eingegangen wie auf betriebswirtschaftliche Notwendigkeiten, um Mitarbeitende und Unternehmen vor den schwerwiegenden Folgen von Compliance-Verstößen zu schützen.
Limitierende Faktoren
(2023)
Wie bei allen Risiken gibt es auch bei Compliance-Risiken kein Null-Risiko. Man wird in der Praxis noch nicht einmal in die unmittelbare Nähe einer Null kommen. Ein Null-Compliance-Risiko ist auch deshalb nicht erreichbar, weil sich ständig neue Risikofelder auftun. So beispielsweise durch Änderung von Geschäftsmodellen oder Vertriebswegen oder durch neue rechtliche Rahmenbedingen.
Unsere Welt verändert sich in unterschiedlichen Tempi und Verwerfungstiefen. Dies ist das einzig Verlässliche für Wirtschaft und Gesellschaft.
Zum einen zählt die kreative Zerstörung zum ‚Markenkern‘ marktwirtschaftlicher Systeme. Die Wirtschaftsakteure stehen dadurch an ihrem jeweiligen Standort unter einer Art (produktivem) Dauerstress. Es gibt Gewinner und Verlierer, weil Wettbewerber unterschiedlich erfolgreich kostensenkende Rationalisierungen, technischen Fortschritt und die Erschließung neuer (globaler) Märkte realisieren. Der damit einhergehende Strukturwandel gilt als wirtschaftssystemischer Normalzustand.
Zum anderen gibt es Krisen. Und auch ‚unter Schock‘ (re-)agieren Akteure ungleich, wie die Corona-Pandemie oder abrupte Veränderungen durch die Finanzkrise zeigen. Einige Akteure und Standorte bleiben mit ihrem jeweiligen Profil und Potenzial (weiterhin) produktiv widerstandsfähig. Für andere verschärfen sich der wirtschaftliche Niedergang und dessen Folgen für die Arbeitsmärkte und Lebensqualität der Betroffenen.
Regionale Wirtschaftsförderung unterstützt, dass sich die Wirtschaftsstrukturen an einem Standort überlebensfähig ausrichten. Doch kann sie auch beim Umgang mit Krisen einen Mehrwert erzielen und zählt dies überhaupt zu ihrem Regelauftrag? Und welche Rolle spielt die Digitalisierung? Der Beitrag stellt den sachlogischen Zusammenhang zwischen diesen Teilfragen her und ordnet neuere Ansätze ein. Zudem werden Ansatzstellen aufgezeigt, um die regionale Wirtschaftsförderung praxisorientiert weiterzuentwickeln. ‚Electronic Government‘ (E-Government) beschreibt dabei den Einsatz von Informationstechnik, Telekommunikation und Medien (ITKM) im öffentlichen Sektor, während ‚Electronic Governance‘ (E-Governance) hybride oder private Akteure miteinbezieht.
Der Beitrag ist wie folgt strukturiert: Zunächst werden Schlüsselbegriffe wie Strukturpolitik und Resilienz geklärt und mit den Kontextfaktoren verknüpft, welche die Steuerungslogik von Wirtschaftsförderung bestimmen. Danach wird diskutiert, inwiefern die Wirtschaftsförderung E-Government und E-Governance nutzen kann, um Resilienz zu stärken und möglichst transformativ wirken zu können.
We investigate micrometer-sized flat droplets consisting of an isotropic core surrounded by a nematic rim in freely suspended smectic A liquid-crystal films. In contrast to purely isotropic droplets which are characterized by a sharp edge and no long-range interactions, the nematic fringe introduces a continuous film thickness change resulting in long-range mutual attraction of droplets. The coalescence scenario is divided in two phases. The first one consists in the fusion of the nematic regions. The second phase involves the dissolution of a thin nematic film between the two isotropic cores. The latter has many similarities with the rupture of thin liquid films between droplets coalescing in an immiscible viscous liquid.
Coalescence of biphasic droplets in free-standing smectic films is controlled in part by the rupture of a thin nematic membrane separating the isotropic droplet cores.
Digital transformation initiatives in small and medium-sized enterprises (SME) are often hampered by individual practitioners' perceptions of information and communication technology (ICT). This research employs an educational escape room (ER) game for an intervention towards informed decision-making on ICT adoption in SMEs. ER design and implementation are elaborated and consequently tested with SME practitioners, all embedded in an action-design study based on a qualitative research methodology. The result highlights a trade-off between creating immersive game experiences and achieving learning objectives. Still, the outcome implies an impact on players' perception of ICT integrated in the ER. The findings contribute to the emerging field of serious games for learning and shed light on the potential of game-based interventions for SMEs.
Ubiquitous Music is an interdisciplinary research area that combines methodologies from music, computer science, education, creativity studies, human sciences and engineering.
The Ubiumus 2023 symposium, held at Ulster University and North West Regional College in Derry~Londonderry, Northern Ireland, included contributions on the following topics:
Rapid Prototyping and Live Environments
Ecological Approaches to Ubiquitous Music
Ubiquitous Music Creative Practices, Tools and Influences
The symposium also included a number of artistic contributions and workshops, which are also discussed in the proceedings volume. A number of events (including all paper presentations, an invited lecture, a panel discussion, and a keynote and associated performance) were also documented via video, with a link available in this Proceedings volume.
This paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.
Low code development platforms (LCDP) often promise an easy and fast way to include data processing and support into the otherwise non-digital process. This research explores how to measure the productivity of low code development to assess the effort needed for business users to respond to their need for support via these tools. We chose field experiments as a research method to evaluate the feasibility and derive the metrics for software development with LCDP by novices. The paper provides some insights on how these measures can be implemented in practice, how to support business unit developers to efficiently deliver productive results, and how to evaluate LCDP-based development processes.
This article presents a research outline on the use of microlearning applications to develop digital competencies in Small and Medium-sized Enter-prises (SMEs). The digital transformation of businesses has become essential for their survival, and SMEs need to develop digital competencies (DC) to remain competitive in the market. Microlearning (ML), a form of learning that involves small, bite-sized learning modules, has been gaining popularity in recent years as a way to efficiently and effectively develop skills. Through a semi-systematic literature review approach, our study examines prevalent knowledge in the area of ML and DC and discusses interrelations. As a result, we propose a research roadmap consisting of six research questions targeting four dimensions of ML for DC development in SMEs: 1) context, 2) formats, 3) reward system, and 4) complexity level.
Zur Umsetzung ihres "digitalen Kompass 2030" hat die Kommission zwei weitere Rechtsakte vorgeschlagen. Die mehr als 30 Jahre alte Produkthaftungsrichtlinie soll revidiert und eine neue Richtlinie über die Haftung für künstliche Intelligenz erlassen werden. Damit soll die politisch gewünschte Etablierung von KI in der EU für Wirtschaft und Gesellschaft auch haftungsrechtlich abgesichert werden. Der Beitrag analysiert die Richtlinie über die Haftung für künstliche Intelligenz in ihrem Verhältnis zum Gesetz über künstliche Intelligenz und zur Produkthaftungsrichtlinie.
Gemeinsame Digitalisierung durch die Entwicklung von IT-Governance-Strukturen auf Landesebene
(2022)
Auf dem Weg zum Replikator
(2022)
Towards a Business Process Complexity Analysis Framework Based on Textual Data and Event Logs
(2022)
Glass-ceramic composites consisting of potassium-iron-silicate glass and barium titanate mixed in various proportions were successfully synthesized by low-temperature sintering. The crystal structure of the obtained composite samples, the porosity and the microhardness were studied by the X-ray diffraction, the electron microscopy, the weight method, and the Vickers method. Electrical characteristics (dielectric permittivity, tunability and losses) of as-prepared and annealed in oxygen medium samples were investigated at microwaves. According to structural analysis, the synthesized samples are a mixture of KFeSi glass, ferroelectric BaTiO3, and dielectric barium polytitanates; the ratio of the latter determines the electrical properties of the composites. Depending on the content of barium titanate, the studied composite samples show a permittivity from 50 to 270 with a dielectric loss level of 0,1–0,02 in frequency range from 3 to 10 GHz. Annealing of composite samples in an oxygen-containing environment leads to an increase in their dielectric permittivity and tunability by 10–25% and a twofold decrease in dielectric loss.
Companies are increasingly facing the challenges of a persistent cyber threat landscape. By means of AI, cyber attacks can be efficiently conducted more successful through offensive AI. As for cyber defense, AI can be also utilized against cyber threats (defensive AI). Due to limited resources, especially in small and medium-sized companies (SMEs), there is a need to deploy more effective defensive cyber security solutions. Precisely, the adaptation of AI-based resilient defenses must be driven forward. Therefore, the aim of this paper is to identify and evaluate AI-related use cases with a high impact potential on the cyber security level, while being applicable to SMEs at the same time. In order to reach the research goal, an extensive literature review of several online catalogs, surveys and online platforms was conducted. In conclusion, seven crucial AI-based security features were outlined that are providing a high impact potential to the security level for SMEs. Afterwards, the results are discussed and set into a broader context. Even though AI-based security solutions are providing a large range of advantages, certain challenges and barriers using AI-related security applications are addressed in the paper as well. A high need for usable state of the art AI based cyber security solution for SMEs was identified.
Biomass gasification is recognized as a viable avenue to accelerate the sustainable production of hydrogen. In this work, a numerical simulation model of air gasification of rice husks is developed using the Aspen Plus to investigate the feasibility of producing hydrogen-rich syngas. The model is experimentally validated with rice husk gasification results and other published studies. The influence of temperature and equivalence ratio on the syngas composition, H2 yield, LHVSyngas, H2/CO ratio, CGE, and PCG was studied. Furthermore, the synchronized effects of temperature and ER are studied using RSM to determine the operational point of maximizing H2 yield and PCG. The RSM analysis results show optimum performance at temperatures between 820 °C and 1090 °C and ER in the range of 0.06–0.10. The findings show that optimal operating conditions of the gasification system can be achieved at a more refined precision through simulations coupled with advanced optimization techniques.
Single dielectric microspheres can manipulate light focusing and collection to enhance optical interaction with surfaces. To demonstrate this principle, we experimentally investigate the enhancement of the Raman signal collected by a single dielectric microsphere, with a radius much larger than the exciting laser spot size, residing on the sample surface. The absolute microsphere-assisted Raman signal from a single graphene layer measured in air is more than a factor of two higher than that obtained with a high numerical aperture objective. Results from Mie’s theory are used to benchmark numerical simulations and an analytical model to describe the isolated microsphere focusing properties. The analytical model and the numerical simulations justify the Raman signal enhancement measured in the microsphere-assisted Raman spectroscopy experiments.
Towards Practice-oriented Higher Education for Sustainable Rural Development in Western Kenya
(2021)
The workshop proceedings contain the written versions of the presentations of the Kenyan participants of the final workshop of the DAAD-funded cooperation project "Practice-oriented Higher Education in Western Kenya" (ProUniEdu-WeK) in August 2021 at the Brandenburg University of Applied Sciences (THB).
The contributions give an impression of what has been achieved in the last years on the way to practice-oriented higher education in the participating departments of the Masinde Muliro University of Science and Technology (MMUST) in cooperation with its partners from the THB and what is planned to be done in the years to come.
Implementing Ethical Issues into the Recommender Systems Design Using the Data Processing Pipeline
(2021)
Von Ethik zu Recht : Der AI Act und seine Bedeutung für die Gestaltung von algorithmischen Systemen
(2021)
Vision, Mission und Governance der Landesstrategien im Zeitalter der Hochschul-Digitalisierung
(2021)
Assessing business process complexity based on textual data: Evidence from ITIL IT ticket processing
(2021)
Nutzerzentriertheit als wesentliche Dimension für die Nachhaltigkeit von Digitalisierungsvorhaben
(2021)
Kryptografie
(2021)
Gefrierende Gewässer
(2021)
Personal und Organisation
(2021)