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The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named “openEHR-to-FHIR” that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.
Techno-economic analysis that allocate costs to the energy flows of energy systems are helpful to understand the formation of costs within processes and to increase the cost efficiency. For the economic evaluation, the usefulness or quality of the energy is of great importance. In exergy-based methods, this is considered by allocating costs to the exergy instead of energy. As exergy represents the ability of performing work, it is often named the useful part of energy. In contrast, the anergy, the part of energy, which cannot perform work, is often assumed to be not useful.
However, heat flows as used e.g. in domestic heating are always a mixture of a relative small portion of exergy and a big portion of anergy. Although of lower quality, the anergy is obviously useful for these applications. The question is, whether it makes sense to differentiate between exergy and anergy and take both properties into account for the economic evaluation.
To answer this question, a new methodical concept based on the definition of an anergy-exergy cost ratio is compared to the commonly applied approaches of considering either energy or exergy as the basis for economic evaluation. These three different approaches for the economic analysis of thermal energy systems are applied to an exemplary heating system with thermal storages. It is shown that the results of the techno-economic analysis can be improved by giving anergy an economic value and that the proposed anergy-cost ratio allows a flexible adaptation of the evaluation depending on the economic constraints of a system.
This research focuses on the fundamental ideas and underlying principles of E-Learning technology, as well as theoretical considerations for an optimal learning environment. This theoretical exploration was then used as a basis for the design and construction of a new, interactive Web-Based ESH-Training. The quality and effectiveness of this new course was then compared with that of the existing analog PDF-Training via a test with a diverse sample of employee learners. Learners were later surveyed to ascertain their views on both trainings in terms of the quality of the content, facilitator, resources, and length. Results clearly showed that regardless of demographic factors, most employee learners preferred the new, Web-Based ESH-Training to the analog PDF-Training.
Introduction
Atopic dermatitis (AD) is a common inflammatory skin disease. Many patients are initiating a systemic therapy, if the disease is not adequately controlled with topical treatment only. Currently, there is little real-world evidence on the AD-related medical care situation in Germany. This study analyzed patient characteristics, treatment patterns, healthcare resource utilization and costs associated with systemically treated AD for the German healthcare system.
Methods
In this descriptive, retrospective cohort study, aggregated anonymized German health claims data from the InGef research database were used. Within a representative sample of four million insured individuals, patients with AD and systemic drug therapy initiation (SDTI) in the index year 2017 were identified and included into the study cohort. Systemic drug therapy included dupilumab, systemic corticosteroids (SCS) and systemic immunosuppressants (SIS). Patients were observed for one year starting from the date of SDTI in 2017.
Results
9975 patients were included (57.8% female, mean age 39.6 years [SD 25.5]). In the one-year observation period, the most common systemic drug therapy was SCS (> 99.0%). Administrations of dupilumab (0.3%) or dispensations of SIS were rare (cyclosporine: 0.5%, azathioprine: 0.6%, methotrexate: 0.1%). Median treatment duration of SCS, cyclosporine and azathioprine was 27 days, 102 days, and 109 days, respectively. 2.8% of the patients received phototherapy; 41.6% used topical corticosteroids and/or topical calcineurin inhibitor. Average annual costs for medications amounted to € 1237 per patient. Outpatient services were used by 99.6% with associated mean annual costs of € 943; 25.4% had at least one hospitalization (mean annual costs: € 5836). 5.3% of adult patients received sickness benefits with associated mean annual costs of € 5026.
Conclusions
Despite unfavorable risk–benefit profile, this study demonstrated a common treatment with SCS, whereas other systemic drug therapy options were rarely used. Furthermore, the results suggest a substantial economic burden for patients with AD and SDTI.
Background and Objectives:
Drawing causal conclusions from real-world data (RWD) poses methodological challenges and risk of bias. We aimed to systematically assess the type and impact of potential biases that may occur when analyzing RWD using the case of progressive ovarian cancer.
Methods:
We retrospectively compared overall survival with and without second-line chemotherapy (LOT2) using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal structural Cox model with replicates emulating a reference randomized controlled trial (RCT). To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the
HR of the reference trial.
Results:
The reference trial showed an HR for second line vs. delayed therapy of 1.01 (95% confidence interval [95% CI]: 0.82e1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95% CI: 1.22e1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded an HR of 1.12 (95% CI: 0.96e1.28).
Conclusion:
Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.
Aim
Musculoskeletal disorders are a major public health problem in most developed countries. As a main cause of chronic pain, they have resulted in an increasing prescription of opioids worldwide. With regard to the situation in Germany, this study aimed at estimating the prevalence of musculoskeletal diseases such as chronic low back pain (CLBP) and hip/knee osteoarthritis (OA) and at depicting the applied treatment patterns.
Subject and methods
German claims data from the InGef Research Database were analyzed over a 6-year period (2011–2016). The dataset contains over 4 million people, enrolled in German statutory health insurances. Inpatient and outpatient diagnoses were considered for case identification of hip/knee OA and CLBP. The World Health Organization (WHO) analgesic ladder was applied to categorize patients according to their pain management interventions. Information on demographics, comorbidities, and adjuvant medication was collected.
Results
In 2016, n = 2,693,481 individuals (50.5% female, 49.5% male) were assigned to the study population; 62.5% of them were aged 18–60 years. In 2016, n = 146,443 patients (5.4%) with CLBP and n = 307,256 patients (11.4%) with hip/knee OA were identified. Of those with pre-specified pain management interventions (CLBP: 66.3%; hip/knee OA: 65.1%), most patients received WHO I class drugs (CLBP: 73.6%; hip/knee OA: 68.7%) as the highest level.
Conclusion
This study provides indications that CLBP and hip/knee OA are common chronic pain conditions in Germany, which are often subjected to pharmacological pain management. Compared to non-opioid analgesic prescriptions of the WHO I class, the dispensation of WHO class II and III opioids was markedly lower, though present to a considerable extent.
Even for the more traditional insurance industry, the Microservices Architecture (MSA) style plays an increasingly important role in provisioning insurance services. However, insurance businesses must operate legacy applications, enterprise software, and service-based applications in parallel for a more extended transition period. The ultimate goal of our ongoing research is to design a microservice reference architecture in cooperation with our industry partners from the insurance domain that provides an approach for the integration of applications from different architecture paradigms. In Germany, individual insurance services are classified as part of the critical infrastructure. Therefore, German insurance companies must comply with the Federal Office for Information Security requirements, which the Federal Supervisory Authority enforces. Additionally, insurance companies must comply with relevant laws, regulations, and standards as part of the business’s compliance requirements. Note: Since Germany is seen as relatively ’tough’ with respect to privacy and security demands, fullfilling those demands might well be suitable (if not even ’over-achieving’) for insurances in other countries as well. The question raises thus, of how insurance services can be secured in an application landscape shaped by the MSA style to comply with the architectural and security requirements depicted above. This article highlights the specific regulations, laws, and standards the insurance industry must comply with. We present initial architectural patterns to address authentication and authorization in an MSA tailored to the requirements of our insurance industry partners.
FID Civil Engineering, Architecture and Urbanism digital - A platform for science (BAUdigital)
(2022)
University Library Braunschweig (UB Braunschweig), University and State Library Darmstadt (ULB Darmstadt), TIB – Leibniz Information Centre for Technology and Natural Sciences and the Fraunhofer Information Centre for Planning and Building (Fraunhofer IRB) are jointly establishing a specialised information service (FID, "Fachinformationsdienst") for the disciplines of civil engineering, architecture and urbanism. The FID BAUdigital, which is funded by the German Research Foundation (DFG, "Deutsche Forschungsgemeinschaft"), will provide researchers working on digital design, planning and production methods in construction engineering with a joint information, networking and data exchange platform and support them with innovative services for documentation, archiving and publication in their data-based research.
To avoid the shortcomings of traditional monolithic applications, the Microservices Architecture (MSA) style plays an increasingly important role in providing business services. This is true even for the more conventional insurance industry with its highly heterogeneous application landscape and sophisticated cross-domain business processes. Therefore, the question arises of how workflows can be implemented to grant the required flexibility and agility and, on the other hand, to exploit the potential of the MSA style. In this article, we present two different approaches – orchestration and choreography. Using an application scenario from the insurance domain, both concepts are discussed. We introduce a pattern that outlines the mapping of a workflow to a choreography.
With the use of an energy management system in an industrial company according to ISO 50001, a step-by-step increase in energy efficiency can be achieved. The realization of energy monitoring and load management functions requires programs on edge devices or PLCs to acquire the data, adapt the data type or scale the values of the energy information. In addition, the energy information must be mapped to communication interfaces (e.g. based on OPC UA) in order to convey this energy information to the energy management application. The development of these energy management programs is associated with a high engineering effort, because the field devices from the heterogeneous field level do not provide the energy information in standardized semantics. To mitigate this engineering effort, a universal energy data information model (UEIM) is developed and presented in this paper.
Wikidata and Wikibase as complementary research data management services for cultural heritage data
(2022)
The NFDI (German National Research Data Infrastructure) consortia are associations of various institutions within a specific research field, which work together to develop common data infrastructures, guidelines, best practices and tools that conform to the principles of FAIR data. Within the NFDI, a common question is: What is the potential of Wikidata to be used as an application for science and research? In this paper, we address this question by tracing current research usecases and applications for Wikidata, its relation to standalone Wikibase instances, and how the two can function as complementary services to meet a range of research needs. This paper builds on lessons learned through the development of open data projects and software services within the Open Science Lab at TIB, Hannover, in the context of NFDI4Culture – the consortium including participants across the broad spectrum of the digital libraries, archives, and museums field, and the digital humanities.
A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
Background: To improve interprofessional collaboration between registered nurses (RNs) and general practitioners (GPs) for nursing home residents (NHRs), the interprof ACT intervention package was developed. This complex intervention includes six components (e.g., shared goal setting, standardized procedures for GPs’ nursing home visits) that can be locally adapted. The cluster‑randomized interprof ACT trial evaluates the effects of this intervention on the cumulative incidence of hospital admissions (primary outcome) and secondary outcomes (e.g., length of hospital stays, utilization of emergency care services, and quality of life) within 12 months. It also includes a process evaluation which is subject of this protocol. The objectives of this evaluation are to assess the implementation of the interprof ACT intervention package and downstream effects on nurse–physician collaboration as well as preconditions and prospects for successive implementation into routine care.
Methods: This study uses a mixed methods triangulation design involving all 34 participating nursing homes (clusters). The quantitative part comprises paper‑based surveys among RNs, GPs, NHRs, and nursing home directors at baseline and 12 months. In the intervention group (17 clusters), data on the implementation of preplanned implementation strategies (training and supervision of nominated IPAVs, interprofessional kick‑off meetings) and local implementation activities will be recorded. Major outcome domains are the dose, reach and fidelity of the implementation of the intervention package, changes in interprofessional collaboration, and contextual factors. The qualitative part will be conducted in a subsample of 8 nursing homes (4 per study group) and includes repeated non‑participating observations and semistructured interviews on the interaction between involved health professionals and their work processes. Quantitative and qualitative data will be descriptively analyzed and then triangulated by means of joint displays and mixed methods informed regression models.
Discussion: By integrating a variety of qualitative and quantitative data sources, this process evaluation will allow comprehensive assessment of the implementation of the interprof ACT intervention package, the changes induced in interprofessional collaboration, and the influence of contextual factors. These data will reveal expected and unexpected changes in the procedures of interprofessional care delivery and thus facilitate accurate conclusions for the further design of routine care services for NHRs.
We present a methodology based on mixed-integer nonlinear model predictive control for a real-time building energy management system in application to a single-family house with a combined heat and power (CHP) unit. The developed strategy successfully deals with the switching behavior of the system components as well as minimum admissible operating time constraints by use of a special switch-cost-aware rounding procedure. The quality of the presented solution is evaluated in comparison to the globally optimal dynamic programming method and conventional rule-based control strategy. Based on a real-world scenario, we show that our approach is more than real-time capable while maintaining high correspondence with the globally optimal solution. We achieve an average optimality gap of 2.5% compared to 20% for a conventional control approach, and are faster and more scalable than a dynamic programming approach.
We present a novel long short-term memory (LSTM) approach for time-series prediction of the sand demand which arises from preparing the sand moulds for the iron casting process of a foundry. With our approach, we contribute to qualify LSTM and its combination with feedback-corrected optimal scheduling for industrial processes.
The sand is produced in an energy intensive mixing process which is controlled by optimal scheduling. The optimal scheduling is solved for a fixed prediction horizon. One major influencing factor is the sand demand, which is highly disturbed, for example due to production interruptions. The causes of production interruptions are in general physically unknown. We assume that information about the future behavior of the sand demand is included in current and past process data. Therefore, we choose LSTM networks for predicting the time-series of the sand demand.
The sand demand prediction is performed by our multi model approach. This approach outperforms the currently used naive estimation, even when predicting far into the future. Our LSTM based prediction approach can forecast the sand demand with a conformity up to 38 % and a mean value accuracy of approximately 99%. Simulating the optimal scheduling with sand demand prediction leads to an improvement in energy savings of approximately 1.1% compared to the naive estimation. The application of our novel approach at the real production plant of a foundry proves the simulation results and verifies the capability of our approach.
The optimization of lubricated sealing systems with respect to the stick-slip effect requires a friction model that describes the complex friction behavior in the lubricated contact area. This paper presents an efficient dynamic friction model based on the Stribeck curve, which allows to investigate the influencing parameters through finite element (FE) simulations. The simulation of a tribometer test using this friction model proofs that the model correlates well with the tribometer test results. It is shown that the system stiffness has a significant influence on the stick-slip tendency of the system.
Since textual user generated content from social media platforms contains valuable information for decision support and especially corporate credit risk analysis, automated approaches for text classification such as the application of sentiment dictionaries and machine learning algorithms have received great attention in recent user generated content based research endeavors. While machine learning algorithms require individual training data sets for varying sources, sentiment dictionaries can be applied to texts immediately, whereby domain specific dictionaries attain better results than domain independent word lists. We evaluate by means of a literature review how sentiment dictionaries can be constructed for specific domains and languages. Then, we construct nine versions of German sentiment dictionaries relying on a process model which we developed based on the literature review. We apply the dictionaries to a manually classified German language data set from Twitter in which hints for financial (in)stability of companies have been proven. Based on their classification accuracy, we rank the dictionaries and verify their ranking by utilizing Mc Nemar’s test for significance. Our results indicate, that the significantly best dictionary is based on the German language dictionary SentiWortschatz and an extension approach by use of the lexical-semantic database GermaNet. It achieves a classification accuracy of 59,19 % in the underlying three-case-scenario, in which the Tweets are labelled as negative, neutral or positive. A random classification would attain an accuracy of 33,3 % in the same scenario and hence, automated coding by use of the sentiment dictionaries can lead to a reduction of manual efforts. Our process model can be adopted by other researchers when constructing sentiment dictionaries for various domains and languages. Furthermore, our established dictionaries can be used by practitioners especially in the domain of corporate credit risk analysis for automated text classification which has been conducted manually to a great extent up to today.
A semiparametric approach for meta-analysis of diagnostic accuracy studies with multiple cut-offs
(2022)
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without targetcondition). If the outcome of a diagnostic test is binary, results from different studies can easily be summarized in a meta-analysis. However, if the diagnostic test is based on a discrete or continuous measure (e.g., a biomarker), several cut-offs within one study as well as among different studies are published. Instead of taking all information of the cut-offs into account in the meta-analysis, a single cut-off per study is often selected arbitrarily for the analysis, even though there are statistical methods for the incorporation of several cut-offs. For these methods, distributional assumptions have to be met and/or the models may not converge when specific data structures occur. We propose a semiparametric approach to overcome both problems. Our simulation study shows that the diagnostic accuracy is underestimated, although this underestimation in sensitivity and specificity is relatively small. The comparative approach of Steinhauser et al. is better in terms of coverage probability, but may lead to convergence problems. In addition to the simulation results, we illustrate the application of the semiparametric approach using a published meta-analysis for a diagnostic test differentiating between bacterial and viral meningitis in children.
Objective
Cyberknife robotic radiosurgery (RRS) provides single-session high-dose radiotherapy of brain tumors with a steep dose gradient and precise real-time image-guided motion correction. Although RRS appears to cause more radiation necrosis (RN), the radiometabolic changes after RRS have not been fully clarified. 18F-FET-PET/CT is used to differentiate recurrent tumor (RT) from RN after radiosurgery when MRI findings are indecisive. We explored the usefulness of dynamic parameters derived from 18F-FET PET in differentiating RT from RN after Cyberknife treatment in a single-center study population.
Methods
We retrospectively identified brain tumor patients with static and dynamic 18F-FET-PET/CT for suspected RN after Cyberknife. Static (tumor-to-background ratio) and dynamic PET parameters (time-activity curve, time-to-peak) were quantified. Analyses were performed for all lesions taken together (TOTAL) and for brain metastases only (METS). Diagnostic accuracy of PET parameters (using mean tumor-to-background ratio >1.95 and time-to-peak of 20 min for RT as cut-offs) and their respective improvement of diagnostic probability were analyzed.
Results
Fourteen patients with 28 brain tumors were included in quantitative analysis. Time-activity curves alone provided the highest sensitivities (TOTAL: 95%, METS: 100%) at the cost of specificity (TOTAL: 50%, METS: 57%). Combined mean tumor-to-background ratio and time-activity curve had the highest specificities (TOTAL: 63%, METS: 71%) and led to the highest increase in diagnosis probability of up to 16% p. – versus 5% p. when only static parameters were used.
Conclusions
This preliminary study shows that combined dynamic and static 18F-FET PET/CT parameters can be used in differentiating RT from RN after RRS.
Aim:
The most suitable method for assessment of response to peptide receptor radionuclide therapy (PRRT) of neuroendocrine tumors (NET) is still under debate. In this study we aimed to compare size (RECIST 1.1), density (Choi), Standardized Uptake Value (SUV) and a newly defined ZP combined parameter derived from Somatostatin Receptor (SSR) PET/CT for prediction of both response to PRRT and overall survival (OS).
Material and Methods:
Thirty-four NET patients with progressive disease (F:M 23:11; mean age 61.2 y; SD ± 12) treated with PRRT using either Lu-177 DOTATOC or Lu-177 DOTATATE and imaged with Ga-68 SSR PET/CT approximately 10–12 weeks prior to and after each treatment cycle were retrospectively analyzed. Median duration of follow-up after the first cycle was 63.9 months (range 6.2–86.2). A total of 77 lesions (2–8 per patient) were analyzed. Response assessment was performed according to RECIST 1.1, Choi and modified EORTC (MORE) criteria. In addition, a new parameter named ZP, the product of Hounsfield unit (HU) and SUVmean (Standard Uptake Value) of a tumor lesion, was tested. Further, SUV values (max and mean) of the tumor were normalized to SUV of normal liver parenchyma. Tumor response was defined as CR, PR, or SD. Gold standard for comparison of baseline parameters for prediction of response of individual target lesions to PRRT was change in size of lesions according to RECIST 1.1. For prediction of overall survival, the response after the first and second PRRT were tested.
Results:
Based on RECIST 1.1, Choi, MORE, and ZP, 85.3%, 64.7%, 61.8%, and 70.6% achieved a response whereas 14.7%, 35.3%, 38.2%, and 29.4% demonstrated PD (progressive disease), respectively. Baseline ZP and ZPnormalized were found to be the only parameters predictive of lesion progression after three PRRT cycles (AUC ZP 0.753; 95% CI 0.6–0.9, p 0.037; AUC ZPnormalized 0.766; 95% CI 0.6–0.9; p 0.029). Based on a cut-off-value of 1201, ZP achieved a sensitivity of 86% and a specificity of 67%, while ZPnormalized reached a sensitivity of 86% and a specificity of 76% at a cut-off-value of 198. Median OS in the total cohort was not reached. In univariate analysis amongst all parameters, only patients having progressive disease according to MORE after the second cycle of PRRT were found to have significantly shorter overall survival (median OS in objective responders not reached, in PD 29.2 months; p 0.015). Patients progressive after two cycles of PRRT according to ZP had shorter OS compared to those responding (median OS for responders not reached, for PD 47.2 months, p 0.066).
Conclusions:
In this explorative study, we showed that Choi, RECIST 1.1, and SUVmax-based response evaluation varied significantly from each other. Only patients showing progressive disease after two PRRT cycles according to MORE criteria had a worse prognosis while baseline ZP and
ZPnormalized performed best in predicting lesion progression after three cycles of PRRT.
High-performance firms typically have two features in common: (i) they produce in more than one country and (ii) they produce more than one product. In this paper, we analyze the internationalization strategies of multi-product firms. Guided by several new stylized facts, we develop a theoretical model to determine optimal modes of market access at the firm–product level. We find that the most productive firmssell core varieties via foreign direct investment and export products with intermediate productivity. Shocks to trade costs and technology affect the endogenous decision to export or produce abroad at the product-level and, in turn, the relative productivity between parents and affiliates.
Background
Symptoms of depression are prevalent in people living with human immune deficiency virus/acquired immune deficiency syndrome (PLWHA), and worsened by lack of physical activity/exercises, leading to restriction in social participation/functioning. This raises the question: what is the extent to which physical exercise training affected, symptoms of depression, physical activity level (PAL) and social participation in PLWHA compared to other forms of intervention, usual care, or no treatment controls?
Method
Eight databases were searched up to July 2020, according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Only randomised controlled trials involving adults who were either on HAART/HAART-naïve and reported in the English language, were included. Two independent reviewers determined the eligibility of the studies, extracted data, assessed their quality, and risk of bias using the Physiotherapy Evidence Database (PEDro) tool. Standardised mean difference (SMD) was used as summary statistics for the mean primary outcome (symptoms of depression) and secondary outcomes (PAL and social participation) since different measuring tools/units were used across the included studies. Summary estimates of effects were determined using a random-effects model (I2).
Results
Thirteen studies met the inclusion criteria with 779 participants (n = 596 participants at study completion) randomised into the study groups, comprising 378 males, 310 females and 91 participants with undisclosed gender, and with an age range of 18–86 years. Across the studies, aerobic or aerobic plus resistance exercises were performed 2–3 times/week, at 40–60 min/session, and for between 6-24 weeks, and the risk of bias vary from high to low. Comparing the intervention to control groups showed significant difference in the symptoms of depression (SMD = − 0.74, 95% confidence interval (CI) − 1.01, − 0.48, p ≤ 0.0002; I2 = 47%; 5 studies; 205 participants) unlike PAL (SMD = 0.98, 95% CI − 0.25, 2.17, p = 0.11; I2 = 82%; 2 studies; 62 participants) and social participation (SMD = 0.04, 95% CI − 0.65, 0.73, p = 0.91; I2 = 90%; 6 studies; 373 participants).
Conclusion
Physical exercise training could have an antidepressant-like effect in PLWHA but did not affect PAL and social participation. However, the high heterogeneity in the included studies, implies that adequately powered randomised controlled trials with clinical/methodological similarity are required in future studies.
Context: Agile software development (ASD) sets social aspects like communication and collaboration in focus. Thus, one may assume that the specific work organization of companies impacts the work of ASD teams. A major change in work organization is the switch to a 4-day work week, which some companies investigated in experiments. Also, recent studies show that ASD teams are affected by the switch to remote work since the Covid 19 pandemic outbreak in 2020.
Objective: Our study presents empirical findings on the effects on ASD teams operating remote in a 4-day work week organization. Method: We performed a qualitative single case study and conducted seven semi-structured interviews, observed 14 agile practices and screened eight project documents and protocols of agile practices.
Results: We found, that the teams adapted the agile method in use due to the change to a 4-day work week environment and the switch to remote work. The productivity of the two ASD teams did not decrease. Although the stress level of the ASD team member increased due to the 4-day work week, we found that the job satisfaction of the individual ASD team members is affected positively. Finally, we point to affects on social facets of the ASD teams.
Conclusion: The research community benefits from our results as the current state of research dealing with the effects of a 4-day work week on ASD teams is limited. Also, our findings provide several practical implications for ASD teams working remote in a 4-day work week.
Context: Companies adapt agile methods, practices or artifacts for their use in practice since more than two decades. This adaptions result in a wide variety of described agile practices. For instance, the Agile Alliance lists 75 different practices in its Agile Glossary. This situation may lead to misunderstandings, as agile practices with similar names can be interpreted and used differently.
Objective: This paper synthesize an integrated list of agile practices, both from primary and secondary sources.
Method: We performed a tertiary study to identify existing overviews and lists of agile practices in the literature. We identified 876 studies, of which 37 were included.
Results: The results of our paper show that certain agile practices are listed and used more often in existing studies. Our integrated list of agile practices comprises 38 entries structured in five categories. Conclusion: The high number of agile practices and thus, the wide variety increased steadily over the past decades due to the adaption of agile methods. Based on our findings, we present a comprehensive overview of agile practices. The research community benefits from our integrated list of agile practices as a potential basis for future research. Also, practitioners benefit from our findings, as the structured overview of agile practices provides the opportunity to select or adapt practices for their specific needs.
This paper proposes an extended Petri net formalism as a suitable language for composing optimal scheduling problems of industrial production processes with real and binary decision variables. The proposed approach is modular and scalable, as the overall process dynamics and constraints can be collected by parsing of all atomic elements of the net graph. To conclude, we demonstrate the use of this framework for modeling the moulding sand preparation process of a real foundry plant.
Catholic Ownership, Physician Leadership and Operational Strategies: Evidence from German Hospitals
(2022)
Previous research has revealed that Catholic hospitals are more likely follow a strategy of horizontal diversification and maximization of the number of patients treated, whereas Protestant hospitals follow a strategy of horizontal specialization and focus on vertical differentiation. However, there is no empirical evidence pertaining to this mechanism. We conduct an empirical study in a German setting and argue that physician leadership mediates the relationship between ownership and operational strategies. The study includes the construction of a model combining data from a survey and publicly available information derived from the annual quality reports of German hospitals. Our results show that Catholic hospitals opt for leadership structures that ensure operational strategies in line with their general values, i.e., operational strategies of maximizing volume throughout the overall hospital. They prefer part-time positions for chief medical officers, as chief medical officers are identified to foster strategies of maximizing the overall number of patients treated. Hospital owners should be aware that the implementation of part-time and full-time leadership roles can help to support their strategies. Thus, our results provide insights into the relationship between leadership structures at the top of an organization, on the one hand, and strategic choices, on the other.
Coaxial Laser wire Direct Energy Deposition (L-DED) promises a direction-independent buildup due to a centric supply of the welding material. To fabricate Functionally Graded Materials (FGMs), a processing head was designed that is capable of supplying two wire materials into the processing zone. This study investigates the direction dependency of welding seams produced by two 1.4718 metal wires with a diameter of 0.8 mm in a coaxial laser setup using three separately controllable single laser beams with a maximum combined laser power of 660 W. The welding wires are supplied simultaneously to the laser spot under an incidence angle of 3.5° to the middle axis of the processing head. The seam geometry is investigated using a confocal laserscanning-microscope. A comparison of the height, width and macroscopic seam geometry reveals the influence of the welding direction on the seam geometry and quality in Laser Double wire Direct Energy Deposition (LD-DED).
Background: One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician’s ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.
Objectives: The aim of the study is to enhance an existing, interoperable, and rulebased CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.
Methods: We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians’ diagnoses as reference
A proven method to enhance the mechanical properties of additively manufactured plastic parts is the embedding of continuous fibers. Due to its great flexibility, continuous fiber-reinforced material extrusion allows fiber strands to be deposited along optimized paths. Nevertheless, the fibers have so far been embedded in the parts contour-based or on the basis of regular patterns. The outstanding strength and stiffness properties of the fibers in the longitudinal direction cannot be optimally utilized. Therefore, a method is proposed which allows to embed fibers along the principal stresses into the parts in a load-oriented manner. A G-code is generated from the calculated principal stress trajectories and the part geometry, which also takes into account the specific restrictions of the manufacturing technology used. A distinction is made between fiber paths and the matrix so that the average fiber volume content can be set in a defined way. To determine the mechanical properties, tensile and flexural tests are carried out on specimens consisting of carbon fiber-reinforced polyamide. In order to increase the influence of the principal stress-based fiber orientation, open-hole plates are used for the tensile tests, as this leads to variable stresses across the cross section. In addition, a digital image correlation system is used to determine the deformations during the mechanical tests. It was found that the peak load of the optimized open-hole plates was greater by a factor of 3 and the optimized flexural specimens by a factor of 1.9 than the comparison specimens with unidirectional fiber alignment.
Background: Upsurge in cardiopulmonary dysfunctions in Enugu, Nigeria, involved mainly cement workers, automobile spray painters, woodworkers, and Cleaners and was worsened in the dry season, suggesting the need for an occupation-specific characterization of the disease features and seasonal evaluation of air quality for prevention and management.
Methods: We conducted a randomized cross-sectional study of eighty consenting participants (in Achara Layout, Enugu), comprising 20 cement workers (39.50 ± 14.95 years), 20 automobile spray painters (40.75 ± 9.85 years), 20 woodworkers (52.20 ± 9.77 years), and 20 cleaners (42.30 ± 9.06 years). The air quality, some haematological (fibrinogen-Fc, and C-reactive protein-CRP), and cardiopulmonary parameters were measured and analyzed using ANCOVA, at p < 0.05.
Results: The dry season particulate matter (PM) in ambient air exceeded the WHO standards in the New layout [PM10 = 541.17 ± 258.72 µg/m3; PM2.5 = 72.92 ± 25.81 µg/m3] and the University campus [PM10 = 244 ± 74.79 µg/m3; PM2.5 = 30.33 ± 16.10 µg/m3], but the former was twice higher. The PM differed significantly (p < 0.05) across the sites. Forced expiratory volume at the first second (FEV1) (F = 6.128; p = 0.001), and Peak expiratory flow rate (PEFR) (F = 5.523; p = 0.002), differed significantly across the groups. FEV1/FVC% was < 70% in cement workers (55.33%) and woodworkers (61.79%), unlike, automobile spray painters (72.22%) and cleaners (70.66%). FEV1 and work duration were significantly and negatively related in cement workers (r = -0.46; r2 = 0.2116; p = 0.041 one-tailed). CRP (normal range ≤ 3.0 mg/L) and Fc (normal range—1.5–3.0 g/L) varied in cement workers (3.32 ± 0.93 mg/L versus 3.01 ± 0.85 g/L), automobile spray painters (2.90 ± 1.19 mg/L versus 2.54 ± 0.99 mg/L), woodworkers (2.79 ± 1.10 mg/L versus 2.37 ± 0.92 g/L) and cleaners (3.06 ± 0.82 mg/L versus 2.54 ± 0.70 g/L).
Conclusion(s): Poor air quality was evident at the study sites, especially in the dry season. Cement workers and automobile spray painters showed significant risks of obstructive pulmonary diseases while woodworkers had restrictive lung diseases. Cement workers and cleaners recorded the highest risk of coronary heart disease (CRP ≥ 3.0 mg/L). The similarity in Fc and CRP trends suggests a role for the inflammation-sensitive proteins in the determination of cardiovascular risk in cement workers and cleaners. Therefore, there are occupation-specific disease endpoints of public health concern that likewise warrant specific preventive and management approaches among the workers.
We performed classical molecular dynamics simulations to model the scattering process of nitric oxide, NO, off graphene supported on gold. This is motivated by our desire to probe the energy transfer in collisions with graphene. Since many of these collision systems comprising of graphene and small molecules have been shown to scatter non-reactively, classical molecular dynamics appear to describe such systems sufficiently. We directed thousands of trajectories of NO molecules onto graphene along the surface normal, while varying impact position, but also speed, orientation, and rotational excitation of the nitric oxide, and compare the results with experimental data. While experiment and theory do not match quantitatively, we observe agreement that the relative amount of kineti cenergy lost during the collision increases with increasing initial kinetic energy of the NO. Furthermore, while at higher collision energies, all NO molecules lose some energy, and the vast majority of NO is scattered back, in contrast at low impact energies, the fraction of those nitric oxide molecules that are trapped at the surface increases, and some NO molecules even gain some kinetic energy during the collision process. The collision energy seems to preferentially go into the collective motion of the carbon atoms in the graphene sheet.
As part of the European Network for Optimization of Veterinary Antimicrobial Treatment (ENOVAT), a webinar on the topic “Mastitis Treatment in Lactation” was held, in which eight mastitis experts from different European countries (Spain, The Netherlands, Estonia, Ireland, Poland, Finland, Germany, and Italy) presented their treatment approaches for clinical mastitis in lactation. The aim of this study was to compare the therapeutic approaches to identify commonalities and differences. In all eight participating countries, the decision to start treatment is usually made by the veterinarians, while the farm personnel are responsible for treatment administration. Antibiotic treatment is then typically administered intramammarily. The treatment duration often depends on the label instructions and is frequently extended if Staphylococcus aureus or Streptococcus uberis is involved. Administering supportive therapy, especially non-steroidal anti-inflammatory drugs (NSAIDs) is an established practice in all countries. Penicillin is the first-choice drug for the treatment of mastitis in an increasing number of countries. The use of critically important antimicrobials (CIAs) such as quinolones and third- and fourth-generation cephalosporins is at a low level in Finland and The Netherlands. In Estonia, Germany, Italy, and Spain, the use of CIAs is declining and is only allowed if milk samples are analyzed in advance following the legal framework. Systems for monitoring antibiotic use are being introduced in more and more countries. This exchange of different views will help the European countries to move towards a common high standard of antimicrobial stewardship in veterinary medicine.
Severe mastitis can lead to considerable disturbances in the cows’ general condition and even to septicemia and death. The aim of this cross-sectional study was to identify factors associated with the severity of the clinical expression of mastitis. Streptococcus (Str.) uberis (29.9%) was the most frequently isolated pathogen, followed by coliform bacteria (22.3%). The majority of all mastitis cases (n = 854) in this study were either mild or moderate, but 21.1% were severe. It can be deduced that the combination of coliform pathogens and increasing pathogen shedding of these showed associations with severe mastitis. Furthermore, animal-related factors associated with severe disease progression were stages of lactation, and previous diseases in the period prior to the mastitis episode. Cows in early lactation had more severe mastitis. Ketosis and uterine diseases in temporal relation to the mastitis were associated with more severe mastitis in the diseased cows. Hypocalcemia was significantly associated with milder mastitis. As another factor, treatment with corticosteroids within two weeks before mastitis was associated with higher severity of mastitis. Knowledge of these risk factors may provide the basis for randomized controlled trials of the exact influence of these on the severity of mastitis.
Continuous Fiber-Reinforced Material Extrusion with Hybrid Composites of Carbon and Aramid Fibers
(2022)
An existing challenge in the use of continuous fiber reinforcements in additively manufactured parts is the limited availability of suitable fiber materials. This leads to a reduced adaptability of the mechanical properties to the load case. The increased design freedom of additive manufacturing allows the flexible deposition of fiber strands at defined positions, so that even different fiber materials can be easily combined in a printed part. In this work, therefore, an approach is taken to combine carbon and aramid fibers in printed composite parts to investigate their effects on mechanical properties. For this purpose, tensile, flexural and impact tests were performed on printed composite parts made of carbon and aramid fibers in a nylon matrix with five different mixing ratios. The tests showed that the use of hybrid composites for additive manufacturing is a reasonable approach to adapt the mechanical properties to the loading case at hand. The experiments showed that increasing the aramid fiber content resulted in an increase in impact strength, but a decrease in tensile and flexural strength and a decrease in stiffness. Microstructural investigations of the fracture surfaces showed that debonding and delamination were the main failure mechanisms. Finally, Rule of Hybrid Mixture equations were applied to predict the mechanical properties at different mixture ratios. This resulted in predicted values that differed from the experimentally determined values by an average of 5.6%.
The purpose of this research is to explore results that are measured by social enterprises (= SEs) according to their mission and vision. Four SEs are examined for this reason. The status quo of aligned measurements was captured by conducting seven semi-structured interviews with persons from the middle and top management of the considered SEs. A conceptual framework, which categorizes output, outcome and impact measurements, is used as the basis for a structured content analysis. The findings imply that SEs’ measurements are not sufficiently aligned with their mission and vision. Outputs are measured by all considered SEs. However, they fail to measure outcomes with all its sublevels. Especially, measuring mindset change and behavior change outcomes are neglected by the examined SEs. That can lead to adjustments, where SEs only create more outputs but fail to create more outcomes and impact. Furthermore, neglecting outcome measurements makes existing but mostly unsystematic impact measurements invalid, since outputs, outcomes and impact build on each other. The research presented here provides one of the first investigations into the alignment of measurements with mission and vision in the context of SEs. Ultimately, the findings question SEs current measurements and aim to open further perspectives on improving the performance of SEs.
Image captions in scientific papers usually are complementary to the images. Consequently, the captions contain many terms that do not refer to concepts visible in the image. We conjecture that it is possible to distinguish between these two types of terms in an image caption by analysing the text only. To examine this, we evaluated different features. The dataset we used to compute tf.idf values, word embeddings and concreteness values contains over 700 000 scientific papers with over 4,6 million images. The evaluation was done with a manually annotated subset of 329 images. Additionally, we trained a support vector machine to predict whether a term is a likely visible or not. We show that concreteness of terms is a very important feature to identify terms in captions and context that refer to concepts visible in images.
Social skills are essential for a successful understanding of agile methods in software development. Several studies highlight the opportunities and advantages of integrating real-world projects and problems while collaborating with companies into higher education using agile methods. This integration comes with several opportunities and advantages for both the students and the company. The students are able to interact with real-world software development teams, analyze and understand their challenges and identify possible measures to tackle them. However, the integration of real-world problems and companies is complex and may come with a high effort in terms of coordination and preparation of the course. The challenges related to the interaction and communication with students are increased by virtual distance teaching during the Covid-19 pandemic as direct contact with students is missing. Also, we do not know how problem-based learning in virtual distance teaching is valued by the students. This paper presents our adapted eduScrum approach and learning outcome of integrating experiments with real-world software development teams from two companies into a Master of Science course organized in virtual distance teaching. The evaluation shows that students value analyzing real-world problems using agile methods. They highlight the interaction with real-world software development teams. Also, the students appreciate the organization of the course using an iterative approach with eduScrum. Based on our findings, we present four recommendations for the integration of agile methods and real world problems into higher education in virtual distance teaching settings. The results of our paper contribute to the practitioner and researcher/lecturer community, as we provide valuable insights how to fill the gap between practice and higher education in virtual distance settings.
Acute stroke care is a time-critical process. Improving communication
and documentation process may support a positive effect on medical outcome. To achieve this goal, a new system using a mobile application has been integrated into existing infrastructure at Hannover Medical School (MHH). Within a pilot project, this system has been brought into clinical daily routine in February 2022. Insights generated may support further applications in clinical use-cases.
The aim of the podcast Digitization of Medicine is to interest a broader audience and, in particular, young women, in research and work in the field of medical informatics. This article presents the usage figures and discusses their significance for further research on the success of science communication. By 24/02/2022, a total of 24,351 downloads had been made. There were slightly more female than male listeners, and they tended to be younger. Despite the importance podcast are gaining for science communication, little is known about the respective user group and further research is needed. In this context, this paper aims to help make the effectiveness of podcasts comparable.
Corynebacterium spp. are frequently detected in bovine quarter milk samples, yet their impact on udder health has not been determined completely. In this longitudinal study, we collected quarter milk samples from a dairy herd of approximately 200 cows, ten times at 14 d intervals. Bacteriologically, Catalase-positive and Gram-positive rods were detected in 22.7% of the samples. For further species diagnosis, colonies were analyzed by MALDITOF MS. Corynebacterium bovis, C. amycolatum, C. xerosis and 10 other Corynebacterium spp. were detected. The three aforementioned species accounted for 88.4%, 8.65% and 0.94% of all cultured Corynebacterium spp., respectively. For further evaluation of infection dynamics, the following three infection definitions were applied: A (2/3 consecutive samples positive for the same species), B (≥1000 cfu/mL in one sample), C (isolated from a clinical mastitis case). Infections according to definition B occurred most frequently and clinical mastitis with Corynebacterium spp. occurred once during sampling. Life tables were used to determine the duration of infection. According to infection definition A, infection durations of 111 d and 98 d were obtained for C. bovis and C. amycolatum, respectively. Exemplarily, longer lasting infections were examined for their strain diversity by RAPD PCR. A low strain diversity was found in the individual quarters that indicates a longer colonization of the udder parenchyma by C. bovis and C. amycolatum.
Rich literature abounds concerning the clinical effectiveness of programs aiming to produce weight gain/obesity prevention outcomes. However, there is very little evidence on how these outcomes are produced, and what interplay of factors made those programs effective (or not) in the environment that produced those effects. This study aims to describe the application of realistic evaluation in the field of obesity prevention, as an approach to unravel those components that influence the capacity of a program to produce its effects and to examine its significance in an effort to understand those components. The concepts of critical realism have informed the development of an interview topic guide, while three European programs were selected as case studies after a rigorous selection process. In total, 26 in-depth semi-structured interviews were taken, paired with personal observation and secondary data research. Several grounded context-mechanisms-outcomes (CMO) configurations were described within the respective context of each location, with the mechanisms introduced from each project resulting in distinctive outcomes. This study highlights the potential of realistic evaluation as a comprehensive framework to explain in which contextual circumstances of each program’s effects are produced, how certain underlying mechanisms produce those effects, and how to explicitly connect the context and the acting mechanisms into distinct outcome patterns, which will ultimately form unique configuration sets for each of the analyzed projects.
Dramatic increases in the number of cyber security attacks and breaches toward businesses and organizations have been experienced in recent years. The negative impacts of these breaches not only cause the stealing and compromising of sensitive information, malfunctioning of network devices, disruption of everyday operations, financial damage to the attacked business or organization itself, but also may navigate to peer businesses/organizations in the same industry. Therefore, prevention and early detection of these attacks play a significant role in the continuity of operations in IT-dependent organizations. At the same time detection of various types of attacks has become extremely difficult as attacks get more sophisticated, distributed and enabled by Artificial Intelligence (AI). Detection and handling of these attacks require sophisticated intrusion detection systems which run on powerful hardware and are administered by highly experienced security staff. Yet, these resources are costly to employ, especially for small and medium-sized enterprises (SMEs). To address these issues, we developed an architecture -within the GLACIER project- that can be realized as an in-house operated Security Information Event Management (SIEM) system for SMEs. It is affordable for SMEs as it is solely based on free and open-source components and thus does not require any licensing fees. Moreover, it is a Self-Contained System (SCS) and does not require too much management effort. It requires short configuration and learning phases after which it can be self-contained as long as the monitored infrastructure is stable (apart from a reaction to the generated alerts which may be outsourced to a service provider in SMEs, if necessary). Another main benefit of this system is to supply data to advanced detection algorithms, such as multidimensional analysis algorithms, in addition to traditional SIEMspecific tasks like data collection, normalization, enrichment, and storage. It supports the application of novel methods to detect security-related anomalies. The most distinct feature of this system that differentiates it from similar solutions in the market is its user feedback capability. Detected anomalies are displayed in a Graphical User Interface (GUI) to the security staff who are allowed to give feedback for anomalies. Subsequently, this feedback is utilized to fine-tune the anomaly detection algorithm. In addition, this GUI also provides access to network actors for quick incident responses. The system in general is suitable for both Information Technology (IT) and Operational Technology (OT) environments, while the detection algorithm must be specifically trained for each of these environments individually.
Background
Systematic reviews demonstrated that gait variables are the most reliable predictors of future falls, yet are rarely included in fall screening tools. Thus, most tools have higher specificity than sensitivity, hence may be misleading/detrimental to care. Therefore, this study aimed to determine the validity, and reliability of the velocity field diagram (VFD -a gait analytical tool), and the Timed-up-and-go test (TUG)-commonly used in Nigeria as fall screening tools, compared to a gold standard (known fallers) among community-dwelling older adults.
Method
This is a cross-sectional observational study of 500 older adults (280 fallers and 220 non-fallers), recruited by convenience sampling technique at community health fora on fall prevention. Participants completed a 7-m distance with the number of steps and time it took determined and used to compute the stride length, stride frequency, and velocity, which regression lines formed the VFD. TUG test was simultaneously conducted to discriminate fallers from non-fallers. The cut-off points for falls were: TUG times ≥ 13.5 s; VFD’s intersection point of the stride frequency, and velocity regression lines (E1) ≥ 3.5velots. The receiver operating characteristic (ROC) area under the curves (AUC) was used to explore the ability of the E1 ≥ 3.5velots to discriminate between fallers and non-fallers. The VFD’s and TUG’s sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined. Alpha was set at p < 0.05.
Results
The VFD versus TUG sensitivity, specificity, PPV and NPV were 71%, 27%, 55%, and 42%, versus 39%, 59%, 55%, and 43%, respectively. The ROC’s AUC were 0.74(95%CI:0.597,0.882, p = 0.001) for the VFD. The optimal categorizations for discrimination between fallers/non-fallers were ≥ 3.78 versus ≤ 3.78 for VFD (fallers versus non-fallers prevalence is 60.71% versus 95.45%, respectively), with a classification accuracy or prediction rate of 0.76 unlike TUG with AUC = 0.53 (95% CI:0.353,0.700, p = 0.762), and a classification accuracy of 0.68, and optimal characterization of ≥ 12.81 s versus ≤ 12.81 (fallers and non-fallers prevalence = 92.86% versus 36.36%, respectively).
Conclusion
The VFD demonstrated a fair discriminatory power and greater reliability in identifying fallers than the TUG, and therefore, could replace the TUG as a primary tool in screening those at risk of falls.
Recent developments in the field of deep learning have shown promising advances for a wide range of historically difficult computer vision problems. Using advanced deep learning techniques, researchers manage to perform high-quality single-image super-resolution, i.e., increasing the resolution of a given image without major losses in image quality, usually encountered when using traditional approaches such as standard interpolation. This thesis examines the process of deep learning super-resolution using convolutional neural networks and investigates whether the same deep learning models can be used to increase OCR results for low-quality text images.
Data and Information Science: Book of Abstracts at BOBCATSSS 2022 Hybrid Conference, 23rd - 25th of May 2022, Debrecen.
This year marks the 30th anniversary of the BOBCATSSS. The BOBCATSSS is an international, annual symposium designed for librarians and information professionals in a rapidly changing environment. Over the past 30 years, the conference has included exciting topics, great venues, interested guests and engaging presenters.
This year we would like to introduce the topics of the many papers presented in the Book of Abstracts for the first time in presence at the University of Debrecen and hybrid. The Book of Abstracts provides an overview of all presentations given at BOBCATSSS. Presentations are listed in alphabetical order by title and include speeches, Pecha Kuchas, posters and workshops.
The theme of BOBCATSSS is Data and Information Science. Data and information are the basis for decisions and processes in business, politics and science. Particularly important in the current era of digital transformation. This is exactly where this year's subthemes come in. They deal with data science, openness as well as institutional roles.
In this paper we investigate how concreteness and abstractness are represented in word embedding spaces. We use data for English and German, and show that concreteness and abstractness can be determined independently and turn out to be completely opposite directions in the embedding space. Various methods can be used to determine the direction of concreteness, always resulting in roughly the same vector. Though concreteness is a central aspect of the meaning of words and can be detected clearly in embedding spaces, it seems not as easy to subtract or add concreteness to words to obtain other words or word senses like e.g. can be done with a semantic property like gender.
Visual effects and elements in video games and interactive virtual environments can be applied to transfer (or delegate) non-visual perceptions (e.g. proprioception, presence, pain) to players and users, thus increasing perceptual diversity via the visual modality. Such elements or efects are referred to as visual delegates (VDs). Current fndings on the experiences that VDs can elicit relate to specifc VDs, not to VDs in general. Deductive and comprehensive VD evaluation frameworks are lacking. We analyzed VDs in video games to generalize VDs in terms of their visual properties. We conducted a systematic paper analysis to explore player and user experiences observed in association with specifc VDs in user studies. We conducted semi-structured interviews with expert players to determine their preferences and the impact of VD properties. The resulting VD framework (VD-frame) contributes to a more strategic approach to identifying the impact of VDs on player and user experiences.
Network convergence is an increasing trend in the automation domain. More and more plant owners strive for a unification of networks in their plants. This yields a seamless network structure, simplified supervision, and reduced training effort for the personnel, as only one unified network technology needs to be handled. Ethernet-APL is one piece of the puzzle for such a converged network, supporting various real time protocols like PROFINET, EtherNet, HART-IP as well as the middleware protocol OPC UA. This paper gives an overview on the impact of Ethernet-APL field devices to OT security and proposes how to ensure OT security for them.
AlphaGo’s victory against Lee Sedol in the game of Go has been a milestone in artificial intelligence. After this success, the team behind the program further refined the architecture and applied it to many other games such as chess or shogi. In the following thesis, we try to apply the theory behind AlphaGo and its successor AlphaZero to the game of Abalone. Due to limitations in computational resources, we could not replicate the same exceptional performance.
Companies worldwide have enabled their employees to work remotely as a consequence of the Covid 19 pandemic. Software development is a human-centered discipline and thrives on teamwork. Agile methods are focusing on several social aspects of software development. Software development teams in Germany were mainly co-located before the pandemic. This paper aims to validate the findings of existing studies by expanding on an existing multiple-case study. Therefore, we collected data by conducting semi-structured interviews, observing agile practices, and viewing project documents in three cases. Based on the results, we can confirm the following findings: 1) The teams rapidly adapted the agile practices and roles, 2) communication is more objective within the teams, 3) decreased social exchange between team members, 4) the expectation of a combined approach of remote and onsite work after the pandemic, 5) stable or increased (perceived) performance and 6) stable or increased well-being of team members.