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- Übung (1)
All of us are aware of the changes in the information field during the last years. We all see the paradigm shift coming up and have some idea how it will challenge our profession in the future. But how the road to excellence - in education of information specialists in the future - will look like? There are different models (new and old ones) for reorganising the structure of education: * Integration * Specialisation * Step-by step-model * Modul System * Network System / Combination model The paper will present the actual level of discussion on building up a new curriculum at the Department of Information and Communication (IK) at the FH Hannover. Based on the mission statement of the department »Education of information professionals is a part of the dynamic evolution of knowledge society« the direction of change and the main goals will be presented. The different reorganisation models will be explained with its objectives, opportunities and forms of implementation. Some examples will show the ideas and tools for a first draft of a reconstruction plan to become fit for the future. This talk has been held at the German-Dutch University Conference »Information Specialists for the 21st Century« at the Fachhochschule Hannover - University of Applied Sciences, Department of Information and Communication, October 14 -15, 1999 in Hannover, Germany.
The miniaturized Mössbauer-spectrometer (MIMOS II), originally devised by Göstar Klingelhöfer, is further developed by the Renz group at the Leibniz University Hanover in cooperation with the Hanover University of Applied Sciences and Arts. A new processing unit with a two-dimensional (2D) data acquisition was developed by M. Jahns. The advantage of this data acquisition is that no thresholds need to be set before the measurement. The energy of each photon is determined and stored with the velocity of the drive. After the measurement, the relevant area can be selected for the Mössbauer spectrum. Now we have expanded the evaluation unit with a power supply for a MIMOS drive and a MIMOS PIN detector. So we have a very compact MIMOS transmissions measurement setup. With this setup it is possible to process the signals of two detectors serially. Currently we are working on a parallel signal processing.
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 the last years generative models have gained large public attention due to their high level of quality in generated images. In short, generative models learn a distribution from a finite number of samples and are able then to generate infinite other samples. This can be applied to image data. In the past generative models have not been able to generate realistic images, but nowadays the results are almost indistinguishable from real images.
This work provides a comparative study of three generative models: Variational Autoencoder (VAE), Generative Adversarial Network (GAN) and Diffusion Models (DM). The goal is not to provide a definitive ranking indicating which one of them is the best, but to qualitatively and where possible quantitively decide which model is good with respect to a given criterion. Such criteria include realism, generalization and diversity, sampling, training difficulty, parameter efficiency, interpolating and inpainting capabilities, semantic editing as well as implementation difficulty. After a brief introduction of how each model works on the inside, they are compared against each other. The provided images help to see the differences among the models with respect to each criterion.
To give a short outlook on the results of the comparison of the three models, DMs generate most realistic images. They seem to generalize best and have a high variation among the generated images. However, they are based on an iterative process, which makes them the slowest of the three models in terms of sample generation time. On the other hand, GANs and VAEs generate their samples using one single forward-pass. The images generated by GANs are comparable to the DM and the images from VAEs are blurry, which makes them less desirable in comparison to GANs or DMs. However, both the VAE and the GAN, stand out from the DMs with respect to the interpolations and semantic editing, as they have a latent space, which makes space-walks possible and the changes are not as chaotic as in the case of DMs. Furthermore, concept-vectors can be found, which transform a given image along a given feature while leaving other features and structures mostly unchanged, which is difficult to archive with DMs.
As noted by Roman poet Virgil already more than 2,000 years ago: “The greatest wealth is health.”. Without health, there is no happiness, no peace, and no success according to the Reflections Recovery Center from Arizona, United States (USA, U.S.). The goal of the Healthy People 2020-project (HP2020), which is led by the Office of Disease Prevention and Health Promotion (ODPHP), was to “promote quality life, healthy development, and health behaviors across all life stages” among the U.S. population. HP2020 measures progress by using so-called Leading Health Indicators (LHI), reliable data sources, baseline values as well as targets for LHI-individual improvements for every measurable objective to be achieved by 2020 and each following decade. In the further course, these values were compared to student populations from the U.S., Germany, and Poland. The goal of this master's thesis was to obtain more data on international health, particularly among student populations. For the statistical analysis, data were obtained from an online survey that was distributed to students in at least one university in each of the three countries. In total, data from 380 students were analyzed in terms of HP2020 goal attainment. To determine if statistically significant differences were present, the z-test was used. The biggest differences emerged on the following topics: access to healthcare, environmental quality, obesity as well as reproductive and sexual health.
The shift towards RES introduces challenges related to power system stability due to the characteristics of inverter-based resources (IBRs) and the intermittent nature of renewable resources. This paper addresses these challenges by conducting comprehensive time and frequency simulations on the IEEE two-area benchmark power system with detailed type 4 wind turbine generators (WTGs), including turbines, generators, converters, filters, and controllers. The simulations analyse small-signal and transient stability, considering variations in active and reactive power, short-circuit events, and wind variations. Metrics such as rate of change of frequency (RoCoF), frequency nadir, percentage of frequency variation, and probability density function (PDF) are used to evaluate the system performance. The findings emphasise the importance of including detailed models of RES in stability analyses and demonstrate the impact of RES penetration on power system dynamics. This study contributes to a deeper understanding of RES integration challenges and provides insights for ensuring the reliable and secure operation of power systems in the presence of high levels of RES penetration.
Objectives: To assess the relation between the number of clinical trials conducted and respective new drug approvals in India and South Africa.
Design: Construction and analysis of a comprehensive database of completed randomised controlled clinical trials based on clinicaltrials.gov from 1 January 2005 to 31 December 2010 and drug approval data from 2006 until 2013 for India and South Africa.
Setting: USA, the EU, India and South Africa.
Main outcome measures: Percentage of completed randomised clinical trials for an Investigational Medicinal Product (IMP) leading to new drug approval in India and South Africa.
Results: A total of 622 eligible randomised controlled trials were identified as per search criteria for India and South Africa. Clustering them for the same sponsor and the same Investigational New Drug (IND) resulted in 453 eligible trials, that is, 224 for India and 229 for South Africa. The distribution of the market application approvals between the EU/USA as well as India and South Africa revealed that out of clinical trials with the participation of test centres in India and/or South Africa, 39.6% (India) clinical trials and 60.1% (South Africa) clinical trials led to market authorisation in the EU/USA without a New Drug Application (NDA) approval in India or South Africa.
Conclusions: Despite an increase in clinical trial activities, there is a clear gap between the number of trials conducted and market availability of these new drugs in India and South Africa. Drug regulatory authorities, investigators, institutional review boards and patient groups should direct their efforts to ensuring availability of new drugs in the market that have been tested and researched on their population.
BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.
A descriptive cross-sectional study of cholera at Kakuma and Kalobeyei refugee camps, Kenya in 2018
(2020)
Introduction: cholera is a significant public health concern among displaced populations. Oral cholera vaccines are safe and can effectively be used as an adjunct to prevent cholera in settings with limited access to water and sanitation. Results from this study can inform future consideration for cholera vaccination at Kakuma and Kalobeyei.
Methods: a descriptive cross-sectional study of cholera cases at Kakuma refugee camp and Kalobeyei integrated settlement was carried out between May 2017 to May 2018 (one year). Data were extracted from the medical records and line lists at the cholera treatment centres.
Results: the results found 125 clinically suspected and confirmed cholera cases and one related death (CFR 0.8%). The cumulative incidence of all cases was 0.67 (95% CI=0.56-0.80) cases/1000 persons. Incidence of cholera was higher in children under the age of five 0.94(95% CI=0.63-1.36) cases/1000 persons. Children aged <5 years showed 51% increased risk of cholera compared to those aged ≥5 years (RR=1.51; 95% CI=1.00-2.31, p=0.051). Individuals from the Democratic Republic of Congo had nearly 9-fold risk of reporting cholera (RR=8.62; 95% CI=2.55-37.11, p<0.001) while individuals from South Sudan reported 7 times risk of cholera case compared to those from Somalia (RR=7.39; 95% CI=2.78-27.73, p<0.001).
Conclusion: in addition to the improvement of water, sanitation and hygiene (WaSH), vaccination could be implemented as a short-medium term measure of preventing cholera outbreaks. Age, country of origin and settlement independently predicted the risk of cholera.
In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.
The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept to be able to correctly record and interpret unpredictable system dynamics. This contribution presents a generic QoS measurement framework for service-based systems. The framework consists of an XML-based specification for the measurement to be performed – the Information Model (IM) – and the QoS System, which provides an execution platform for the IM. The framework will be applied to a standard business process of the German insurance industry, and the concepts of the IM and their mapping to artifacts of the QoS System will be presented. Furtherm ore, design and implementation of the QoS System’s parser and generator module and the generated artifacts are explained in detail, e.g., event model, agents, measurement module and analyzer module.
The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept in order to be able to correctly record and interpret unpredictable system dynamics. For this purpose, a general measurement methodology and a specific implementation concept are presented in this work.
Background:
Hereditary angioedema (HAE) is a rare genetic disease and characterized by clinical features such as paroxysmal, recurrent angioedema of the skin, the gastrointestinal tract, and the upper airways. Swelling of the skin occurs primarily in the face, extremities and genitals. Gastrointestinal attacks are accompanied by painful abdominal cramps, vomiting and diarrhea. Due to the low prevalence and the fact that HAE patients often present with rather unspecific symptoms such as abdominal cramps, the final diagnosis is often made after a long delay. The aim of this German-wide survey was to characterize the period between occurrence of first symptoms and final diagnosis regarding self-perceived health, symptom burden and false diagnoses for patients with HAE.
Results:
Overall, 81 patients with HAE were included and participated in the telephone-based survey. Of those, the majority reported their current health status as “good” (47.5%) or “very good” (13.8%), which was observed to be a clear improvement compared to the year before final diagnosis (“good” (16.3%), “very good” (11.3%)). Edema in the extremities (85.2%) and in the gastrointestinal tract (81.5%) were the most currently reported symptoms and occurred earlier than other reported symptoms (mean age at onset 18.1 and 17.8 years, respectively). Misdiagnoses were observed in 50.6% of participating HAE patients with appendicitis and allergy being the most frequently reported misdiagnoses (40.0 and 30.0% of those with misdiagnosis, respectively). Patients with misdiagnosis often received mistreatment (80.0%) with pharmaceuticals and surgical interventions as the most frequently carried out mistreatments (65.6 and 56.3% of those with mistreatment, respectively). The mean observed diagnostic delay was 18.1 years (median 15.0 years). The diagnostic delay was higher in older patients and index patients.
Conclusions:
This study showed that self-perceived status of health for patients is much better once the final correct diagnosis has been made and specific treatment was available. Further challenge in the future will still be to increase awareness for HAE especially in settings which are normally approached by patients at occurrence of first symptoms to assure early referral to specialists and therefore increase the likelihood of receiving an early diagnosis.
Library of Congress Subject Headings (LCSH) are popular for indexing library records. We studied the possibility of assigning LCSH automatically by training classifiers for terms used frequently in a large collection of abstracts of the literature on hand and by extracting headings from those abstracts. The resulting classifiers reach an acceptable level of precision, but fail in terms of recall partly because we could only train classifiers for a small number of LCSH. Extraction, i.e., the matching of headings in the text, produces better recall but extremely low precision. We found that combining both methods leads to a significant improvement of recall and a slight improvement of F1 score with only a small decrease in precision.
A Look at Service Meshes
(2021)
Service meshes can be seen as an infrastructure layer for microservice-based applications that are specifically suited for distributed application architectures. It is the goal to introduce the concept of service meshes and its use for microservices with the example of an open source service mesh called Istio. This paper gives an introduction into the service mesh concept and its relation to microservices. It also gives an overview of selected features provided by Istio as relevant to the above concept and provides a small sample setup that demonstrates the core features.
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.
Background: After kidney transplantation, immunosuppressive therapy causes impaired cellular immune defense leading to an increased risk of viral complications. Trough level monitoring of immunosuppressants is insufficient to estimate the individual intensity of immunosuppression. We have already shown that virus-specific T cells (Tvis) correlate with control of virus replication as well as with the intensity of immunosuppression. The multicentre IVIST01-trial should prove that additional steering of immunosuppressive and antiviral therapy by Tvis levels leads to better graft function by avoidance of over-immunosuppression (for example, viral infections) and drug toxicity (for example, nephrotoxicity).
Methods/design: The IVIST-trial starts 4 weeks after transplantation. Sixty-four pediatric kidney recipients are randomized either to a non-intervention group that is only treated conservatively or to an intervention group with additional monitoring by Tvis. The randomization is stratified by centre and cytomegalovirus (CMV) prophylaxis. In both groups the immunosuppressive medication (cyclosporine A and everolimus) is adopted in the same target range of trough levels. In the non-intervention group the immunosuppressive therapy (cyclosporine A and everolimus) is only steered by classical trough level monitoring and the antiviral therapy of a CMV infection is performed according to a standard protocol. In contrast, in the intervention group the dose of immunosuppressants is individually adopted according to Tvis levels as a direct measure of the intensity of immunosuppression in addition to classical trough level monitoring. In case of CMV infection or reactivation the antiviral management is based on the individual CMV-specific immune defense assessed by the CMV-Tvis level. Primary endpoint of the study is the glomerular filtration rate 2 years after transplantation; secondary endpoints are the number and severity of viral infections and the incidence of side effects of immunosuppressive and antiviral drugs.
Discussion: This IVIST01-trial will answer the question whether the new concept of steering immunosuppressive and antiviral therapy by Tvis levels leads to better future graft function. In terms of an effect-related drug monitoring, the study design aims to realize a personalization of immunosuppressive and antiviral management after transplantation. Based on the IVIST01-trial, immunomonitoring by Tvis might be incorporated into routine care after kidney transplantation.
HOXA9 and MEIS1 are frequently upregulated in acute myeloid leukemia (AML), including those with MLL‐rearrangement. Because of their pivotal role in hemostasis, HOXA9 and MEIS1 appear non‐druggable. We, thus, interrogated gene expression data of pre‐leukemic (overexpressing Hoxa9) and leukemogenic (overexpressing Hoxa9 and Meis1; H9M) murine cell lines to identify cancer vulnerabilities. Through gene expression analysis and gene set enrichment analyses, we compiled a list of 15 candidates for functional validation. Using a novel lentiviral multiplexing approach, we selected and tested highly active sgRNAs to knockout candidate genes by CRISPR/Cas9, and subsequently identified a H9M cell growth dependency on the cytosolic phospholipase A2 (PLA2G4A). Similar results were obtained by shRNA‐mediated suppression of Pla2g4a. Remarkably, pharmacologic inhibition of PLA2G4A with arachidonyl trifluoromethyl ketone (AACOCF3) accelerated the loss of H9M cells in bulk cultures. Additionally, AACOCF3 treatment of H9M cells reduced colony numbers and colony sizes in methylcellulose. Moreover, AACOCF3 was highly active in human AML with MLL rearrangement, in which PLA2G4A was significantly higher expressed than in AML patients without MLL rearrangement, and is sufficient as an independent prognostic marker. Our work, thus, identifies PLA2G4A as a prognostic marker and potential therapeutic target for H9M‐dependent AML with MLL‐rearrangement.
A novel method has been implemented to prepare metal oxide nanopowders covered with known quantities of adsorbed water; we subsequently studied the γ-radiolysis of ZrO2 nanopowders covered with H2O layers. H2 yields from the adsorbed water radiolysis are of importance in multiple industrial contexts – the nuclear industry being a prime example. Measured H2 yields at water coverages of just below and above one monolayer are around 350 times greater than for neat water, but these yields decrease rapidly with increasing water loading of the ZrO2 nanoparticles, approaching the yield of bulk water at coverages of tens of water layers. The observed plateau of the yields at 0.5 to 2.0 monolayers coverage can be explained by the ease with which electronic excitations in the ZrO2 can be transferred across the interface to the first one or two adsorbed water layers. However, with increasing water loading, energy transfer to water layers further away from the interface becomes less efficient, and above ~30 water layers, most of the water is not affected by any exciton formation in the ZrO2.
The Gravitational Search Algorithm is a swarm-based optimization metaheuristic that has been successfully applied to many problems. However, to date little analytical work has been done on this topic.
This paper performs a mathematical analysis of the formulae underlying the Gravitational Search Algorithm. From this analysis, it derives key properties of the algorithm's expected behavior and recommendations for parameter selection. It then confirms through empirical examination that these recommendations are sound.
Lemmatization is a central task in many NLP applications. Despite this importance, the number of (freely) available and easy to use tools for German is very limited. To fill this gap, we developed a simple lemmatizer that can be trained on any lemmatized corpus. For a full form word the tagger tries to find the sequence of morphemes that is most likely to generate that word. From this sequence of tags we can easily derive the stem, the lemma and the part of speech (PoS) of the word. We show (i) that the quality of this approach is comparable to state of the art methods and (ii) that we can improve the results of Part-of-Speech (PoS) tagging when we include the morphological analysis of each word.
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.
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.
The objective of this student project was for the students to develop, conduct, and supervise a training course for basic work place applications (word processing and business graphics). Students were responsible for the planning, organizing and the teaching of the course. As participants, underprivileged adolescents took part in order to learn the handling of IT applications and therefore, improve their job skills and have a better chance to get into employment. Therefore the adolescents do the role of trainees at the course. Our students worked with a population that is continually overlooked by the field.
As a result, the students trained to design and implement training courses, exercised to manage projects and increased their social responsibility and awareness concerning the way of life and living conditions of other young people. The underprivileged adolescents learned to use important business applications and increased their job skills and job chances. The overall design of our concept required extensive resources to supervise and to steer the students and the adolescents. The lecturers had to teach and to counsel the students and had to be on “stand-by” just in case they were needed to solve critical situations between the two groups of young people.
A new type of rotary compressor, called “rotary-chamber compressor”, consists of two interlocking rotors with 4 wings each, that perform non-uniform rotary movements. Both rotors have the same direction of rotation, while one rotor is accelerating, the other rotor is retarding. After surpassing a specific mark, the sequence changes and the leading rotor begins to retard and vice versa. Due to the resulting relative phase difference, the volume between the two wings is changing periodically, which allows pulsating working chambers. The technology was first introduced by its founder Jürgen Schukey in 1987. Since then, no further development on this machine is known to us except our own. In this contribution, a study on the kinematics of the rotary-chamber-compressor is presented. Initial studies have shown that changes in the kinematics of the rotors will have a direct influence on the thermodynamical variables, which, if optimized, can lead to an increased performance of the machine. Therefore, a mathematical model has been developed to obtain the performance parameters from different kinematic concepts by using numerical CFD analysis. Furthermore, additional optimization possibilities will be listed and discussed.
Background: India has the third largest HIV epidemic in the world. The Indian epidemic is characterized by low levels in the general population and elevated concentrations among high-risk groups. The present study was planned to determine the awareness of HIV among students from Mumbai University.
Methods: A cross-sectional study was carried out among students from Mumbai University, India during May–June 2017. Two hundred and fifty students were approached to participate in the study of which 199 agreed to participate (males: 132; females: 67). Pretested questionnaire was distributed and collected data was analyzed using IBM SPSS version 23.
Results: Study participants had high knowledge (86%) and attitude score (87%). There was no significant difference between males and female participants for attitude and knowledge, except for one question regarding knowledge about HIV transmission via breastfeeding to child.
Conclusions: Present study showed that there are no misconceptions or negative attitudes regarding HIV among students. A longitudinal study with a larger sample size across India is recommended for further investigation.
A study to assess the knowledge and attitude towards HIV of pharmacy students from Mumbai university
(2020)
Background: India is the biggest HIV epidemic in the world. The role of a pharmacist is pivotal in educating the general masses. The aim of the study was to determine the knowledge and attitude of pharmacy students from University of Mumbai.
Methods: A cross-sectional study was conducted in University of Mumbai during February-March 2020. Therein, 307 students (214: females and 94: males) participated in the study. The questionnaire was distributed in the classroom and data was collected by means of Google-forms. Furthermore, the data was analysed using IBM SPSS version 23.
Results: The participants demonstrated good knowledge (84%) and attitude (76%) score. With respect to knowledge score, no significant difference was observed except for responses of two questions, aim of the antiretroviral therapy (ART) and Avoidance of sexual intercourse can decrease the risk of HIV. With respect to attitude score, Volunteering to work at an institute for the welfare of HIV patients showed a significant difference.
Conclusion: The current study showed that there were no misconceptions or negative attitude regarding HIV among the students. However, a study with greater sample size must be conducted across India for further investigation.
Background: Immunization is the most cost-effective intervention for infectious diseases which are the major cause of morbidity and mortality worldwide. There is a scarcity of information on the vaccination status of young adults and the role of socioeconomic conditions in India. Objectives: Present study explored the adult vaccination status and influence of income and education of parents on adult vaccination status in university students from Mumbai, India.
Methods: On the basis of the eligibility criterion 149 students were selected for the present study. A total of 8 vaccines namely Tdap/DTP, Varicella, MMR, Influenza, Pneumococcal, Hepatitis A, Hepatitis B and Meningococcal were included in this study for all the respondents. In addition to these vaccines, Human Papilloma Virus vaccine was also included for female respondents.
Results: There were total of 149 (75 male and 74 females) respondents with the mean age of 21.5 years. The top 3 immunizations were Td/Tdap (97.3%), MMR (66.4%) and Hepatitis B (55%) among the respondents. Only 4 (5.5%) female respondents have been immunized against the HPV. Conclusions: Td/Tdap (97.3%) and MMR (66.4%) coverage was in line with the recommendations. For all the other vaccines the coverage was low varying from 5.5% to 35.4%. The vaccination coverage was better in respondents with higher educated and higher income parents. We suggest that patient education, planning by government for the implementation of policy for adult vaccination and involvement of physicians are must for better adult vaccination coverage.
Immunization is the most cost-effective intervention for infectious diseases, which are the major cause of morbidity and mortality worldwide. Vaccines not only protect the individual who is vaccinated but also reduce the burden of infectious vaccine-preventable diseases for the entire community.
1 Adult vaccination is very important given that >25% of mortality is due to infectious diseases.
2 There is a scarcity of information on the vaccination status of young adults and the role of socioeconomic conditions in India.
The drugs we use to treat any condition – from an innocuous cough to a life-threatening cancer – are the outcome of painstaking human clinical trials. These trials are the only way to credibly determine the safety and efficacy of drugs. In recent years there has been a clear shift in clinical trial sites from core developed countries like USA, European countries to developing countries like India, China, South American countries. This shift is related to challenges and opportunities like costs of trials, recruitment issues, and regulatory challenges in developed vs. developing countries. Developing countries and developed countries have their unique disease burden patterns based on various parameters like but not limited to age, health care facilities, health insurance, sanitary conditions, environmental issues, education, nutrition
and GDP. Previous studies have reported that many of the important global diseases are not much explored in clinical trials and many published clinical trials have very less international health relevance. This study was aimed at finding the correlation between disease burdens, number of clinical trials done and trial success rates. We compared 2005 - 2010 Global Burden of Disease data for Germany, India and number of clinical trials from clinicaltrials.gov database done in the same period. Our findings indicated that there was a good correlation between the disease burden and clinical trials for Germany in 2005 and 2010. For India in 2005 there was a moderate positive correlation, 2010 data showed the improvement in India in terms of match between disease burden and clinical trials. But careful observation of the data shows still a need for more trials on Communicable, maternal, neonatal and nutritional disorders.
Background: Pharmacovigilance (PV); also known as drug safety surveillance, is the science of enhancing patient care and patient safety regarding the use of medicines by collecting, monitoring, assessing, and evaluating information from healthcare providers and patients. Pharmacists are pivotal players in adverse drug event (ADE) monitoring and reporting. However, most pharmacists are unaware or not knowledgeable about the guidelines used by their respective countries’ drug regulatory bodies. It is the need of the hour to train pharmacy students on the concept of pharmacovigilance.
Methods: A cross-sectional study was carried out among pharmacy students from Mumbai University, India during May-June 2017. On the basis of the eligibility criterion 352 students were selected for the present study. Four hundred students were approached to participate in the study of which 201 agreed to participate (males: 179; females: 173). Pretested questionnaire was distributed and collected data was analyzed using IBM SPSS version 23.
Results: Overall pharmacovigilance knowledge (44%) and perception (58%) was low among the participants of the present study. Seventy four percent of the participants felt that adverse drug reaction (ADR) reporting should be made compulsory for healthcare professionals. And only 21% agreed that the topic of Pharmacovigilance is well covered in pharmacy curriculum.
Conclusions: Pharmacy council of India, pharmacy teacher’s association and respective pharmacy college should take necessary steps to increase the knowledge and create awareness regarding pharmacovigilance and adverse drug reaction reporting among pharmacy students.
Background
To perform a systematic review about the effect of using clinical pathways on length of stay (LOS), hospital costs and patient outcomes. To provide a framework for local healthcare organisations considering the effectiveness of clinical pathways as a patient management strategy.
Methods
As participants, we considered hospitalized children and adults of every age and indication whose treatment involved the management strategy "clinical pathways". We include only randomised controlled trials (RCT) and controlled clinical trials (CCT), not restricted by language or country of publication. Single measures of continuous and dichotomous study outcomes were extracted from each study. Separate analyses were done in order to compare effects of clinical pathways on length of stay (LOS), hospital costs and patient outcomes. A random effects meta-analysis was performed with untransformed and log transformed outcomes.
Results
In total 17 trials met inclusion criteria, representing 4,070 patients. The quality of the included studies was moderate and studies reporting economic data can be described by a very limited scope of evaluation. In general, the majority of studies reporting economic data (LOS and hospital costs) showed a positive impact. Out of 16 reporting effects on LOS, 12 found significant shortening. Furthermore, in a subgroup-analysis, clinical pathways for invasive procedures showed a stronger LOS reduction (weighted mean difference (WMD) -2.5 days versus -0.8 days)).
There was no evidence of differences in readmission to hospitals or in-hospital complications. The overall Odds Ratio (OR) for re-admission was 1.1 (95% CI: 0.57 to 2.08) and for in-hospital complications, the overall OR was 0.7 (95% CI: 0.49 to 1.0). Six studies examined costs, and four showed significantly lower costs for the pathway group. However, heterogeneity between studies reporting on LOS and cost effects was substantial.
Conclusion
As a result of the relatively small number of studies meeting inclusion criteria, this evidence base is not conclusive enough to provide a replicable framework for all pathway strategies. Considering the clinical areas for implementation, clinical pathways seem to be effective especially for invasive care. When implementing clinical pathways, the decision makers need to consider the benefits and costs under different circumstances (e.g. market forces).
A systematic review of the literature on survey questionnaires to assess self-medication practices
(2017)
Self-medication is of great public health importance as it often bypasses regulatory mechanisms to assure quality of health care. Nevertheless there are no established standards on how to assess self-medication. We therefore intended to systematically retrieve questionnaires and survey tools used to capture self-medication, with the aim to identify the scope of information investigated in this context and commonalities between the tools. We conducted a systematic review of the literature on questionnaires used for self-medication assessment by searching PubMed and Web of Science databases using the combinations of following keywords; self-medication, self-prescription, non-prescription, questionnaire. Truncation was used to ensure retrieval of all possible variations of search terms. The search was limited to articles published between 1st January 2000 and 31st December 2015, human studies and English language. Duplicate and irrelevant studies were excluded from the final review. A total of 158 studies were included in the review. Studies were from diverse geographical locations, most of the studies were from Nigeria 16 (10.1%) followed by India 10 (6.3%) and Iran 8 (5%). Forty-three studies (27.2%) focused on antibiotic self-medication. Majority of the studies (106; 67%) were done with adult populations. The components addressed by the questionnaires covered: reasons for self-medications in 147 (93%) studies, purchasing source in 136 (86%) studies, medical conditions to be treated in 153 (96.8%) studies, adverse events in 67 (42.4%) studies, use of prescribing information in 24 (15.1%) studies and antibiotic resistance awareness in 20 (46.5%) antibiotic studies. For 74 (46.8%) studies, survey questionnaires were self-administered and most studies (57; 36%) were done at homes of respondents. Thirty-seven (23.4%) studies did not report any recall period for self-medication practices. Study response rates varied from 17.9% to 100%, and while validity of the study questionnaire was reported for 100 (63.3%) studies, 15 (9.5%) studies reported reliability test of the study questionnaire. There is a large variety of questionnaires being used for investigating self-medication practices making comparability and meta-analyses very difficult. It is desirable to have a basic set of standardized survey questions on this topic to make available for future research groups in this field.
Background: We sought to develop and test an objective scorecard-based system for assessing and categorizing available research sites in Lassa fever-affected countries based on their preparedness and capability to host Lassa fever vaccine clinical trials.
Methods: We mapped available clinical research sites through interrogation of online clinical trial registries and relevant disease-based consortia. A structured online questionnaire was used to assess the capability of clinical trial sites to conduct Lassa fever vaccine clinical trials. We developed a new scoring template by allocating scores to questionnaire parameters based on perceived importance to the conduct of clinical trials as described in the WHO/TDR Global Competency Framework for Clinical Research. Cutoff points of 75% and 50% were used to categorize sites into categories A, B, or C.
Results: This study identified 44 clinical trial sites in 8 Lassa fever-affected countries. Out of these, 35 sites were characterized based on their capacity to hold Lassa fever vaccine clinical trials. A total of 14 sites in 4 countries were identified as ready to host Lassa fever vaccine trials immediately or with little support.
Conclusion: It is feasible to hold Lassa fever vaccine trials in affected countries based on the outcome of the survey. However, the findings are to be validated through sites' visits. This experience with a standardized and objective method of the site assessment is encouraging, and the site selection method used can serve as an orientation to sponsors and researchers planning clinical trials in the region.
Intrusion detection systems and other network security components detect security-relevant events based on policies consisting of rules. If an event turns out as a false alarm, the corresponding policy has to be adjusted in order to reduce the number of false positives. Modified policies, however, need to be tested before going into productive use. We present a visual analysis tool for the evaluation of security events and related policies which integrates data from different sources using the IF-MAP specification and provides a “what-if” simulation for testing modified policies on past network dynamics. In this paper, we will describe the design and outcome of a user study that will help us to evaluate our visual analysis tool.
Ability of Black-Box Optimisation to Efficiently Perform Simulation Studies in Power Engineering
(2023)
In this study, the potential of the so-called black-box optimisation (BBO) to increase the efficiency of simulation studies in power engineering is evaluated. Three algorithms ("Multilevel Coordinate Search"(MCS) and "Stable Noisy Optimization by Branch and Fit"(SNOBFIT) by Huyer and Neumaier and "blackbox: A Procedure for Parallel Optimization of Expensive Black-box Functions"(blackbox) by Knysh and Korkolis) are implemented in MATLAB and compared for solving two use cases: the analysis of the maximum rotational speed of a gas turbine after a load rejection and the identification of transfer function parameters by measurements. The first use case has a high computational cost, whereas the second use case is computationally cheap. For each run of the algorithms, the accuracy of the found solution and the number of simulations or function evaluations needed to determine the optimum and the overall runtime are used to identify the potential of the algorithms in comparison to currently used methods. All methods provide solutions for potential optima that are at least 99.8% accurate compared to the reference methods. The number of evaluations of the objective functions differs significantly but cannot be directly compared as only the SNOBFIT algorithm does stop when the found solution does not improve further, whereas the other algorithms use a predefined number of function evaluations. Therefore, SNOBFIT has the shortest runtime for both examples. For computationally expensive simulations, it is shown that parallelisation of the function evaluations (SNOBFIT and blackbox) and quantisation of the input variables (SNOBFIT) are essential for the algorithmic performance. For the gas turbine overspeed analysis, only SNOBFIT can compete with the reference procedure concerning the runtime. Further studies will have to investigate whether the quantisation of input variables can be applied to other algorithms and whether the BBO algorithms can outperform the reference methods for problems with a higher dimensionality.
The digital transformation with its new technologies and customer expectation has a significant effect on the customer channels in the insurance industry. The objective of this study is the identification of enabling and hindering factors for the adoption of online claim notification services that are an important part of the customer experience in insurance. For this purpose, we conducted a quantitative cross-sectional survey based on the exemplary scenario of car insurance in Germany and analyzed the data via structural equation modeling (SEM). The findings show that, besides classical technology acceptance factors such as perceived usefulness and ease of use, digital mindset and status quo behavior play a role: acceptance of digital innovations, lacking endurance as well as lacking frustration tolerance with the status quo lead to a higher intention for use. Moreover, the results are strongly moderated by the severity of the damage event—an insurance-specific factor that is sparsely considered so far. The latter discovery implies that customers prefer a communication channel choice based on the individual circumstances of the claim.
Radioisotope-guided sentinel lymph node dissection (sLND) has shown high diagnostic reliability in prostate (PCa) and other cancers. To overcome the limitations of the radioactive tracers, magnetometer-guided sLND using superparamagnetic iron oxide nanoparticles (SPIONs) has been successfully used in PCa. This prospective study (SentiMag Pro II, DRKS00007671) determined the diagnostic accuracy of magnetometer-guided sLND in intermediate- and high-risk PCa. Fifty intermediate- or high-risk PCa patients (prostate-specific antigen (PSA) >= 10 ng/mL and/or Gleason score >= 7; median PSA 10.8 ng/mL, IQR 7.4–19.2 ng/mL) were enrolled. After the intraprostatic SPIONs injection a day earlier, patients underwent magnetometer-guided sLND and extended lymph node dissection (eLND, followed by radical prostatectomy. SLNs were detected in in vivo and in ex vivo samples. Diagnostic accuracy of sLND was assessed using eLND as the reference. SLNs were detected in all patients (detection rate 100%), with 447 sentinel lymph nodes SLNs (median 9, IQR 6–12) being identified and 966 LNs (median 18, IQR 15–23) being removed. Thirty-six percent (18/50) of patients had LN metastases (median 2, IQR 1–3). Magnetometer-guided sLND had 100% sensitivity, 97.0% specificity, 94.4% positive predictive value, 100% negative predictive value, 0.0% false negative rate, and 3.0% additional diagnostic value (LN metastases only in SLNs outside the eLND template). In vivo, one positive SLN/LN-positive patient was missed, resulting in a sensitivity of 94.4%. In conclusion, this new magnetic sentinel procedure has high accuracy for nodal staging in intermediate- and high-risk PCa. The reliability of intraoperative SLN detection using this magnetometer system requires verification in further multicentric studies.
Nitric oxide adsorption on a Au(100) single crystal has been investigated to identify the type of adsorption, the adsorption site, and the orientation and alignment of the adsorbed NO relative to the surface. This was done using a combination of 3D-surface velocity map imaging, near-ambient pressure X-ray photoelectron spectroscopy, and density functional theory. NO was observed to be molecularly adsorbed on gold at ~200 K. Very narrow angular distributions and cold rotational distributions of photodesorbed NO indicate that NO adsorbs on high-symmetry sites on the Au crystal, with the N–O bond axis close to the surface normal. Our density functional theory calculations show that NO preferentially adsorbs on the symmetric bridge (2f) site, which ensures efficient overlap of the NO π* orbital with the orbitals on the two neighbouring Au atoms, and with the N–O bond axis aligned along the surface normal, in agreement with our conclusions from the rotational state distributions. The combination of XPS, which reveals the orientation of NO on gold, with 3D-surface velocity map imaging and density functional theory thus allowed us to determine the adsorption site, orientation and alignment of nitric oxide adsorbed on Au(100).
This Innovative Practice Full Paper presents our learnings of the process to perform a Master of Science class with eduScrum integrating real world problems as projects. We prepared, performed, and evaluated an agile educational concept for the new Master of Science program Digital Transformation organized and provided by the department of business computing at the University of Applied Sciences and Arts - Hochschule Hannover in Germany. The course deals with innovative methodologies of agile project management and is attended by 25 students. We performed the class due the summer term in 2019 and 2020 as a teaching pair. The eduScrum method has been used in different educational contexts, including higher education. During the approach preparation, we decided to use challenges, problems, or questions from the industry. Thus, we acquired four companies and prepared in coordination with them dedicated project descriptions. Each project description was refined in the form of a backlog (list of requirements). We divided the class into four eduScrum teams, one team for each project. The subdivision of the class was done randomly.
Since we wanted to integrate realistic projects into industry partners’ implementation, we decided to adapt the eduScrum approach. The eduScrum teams were challenged with different projects, e.g., analyzing a dedicated phenomenon in a real project or creating a theoretical model for a company’s new project management approach. We present our experiences of the whole process to prepare, perform and evaluate an agile educational approach combined with projects from practice. We found, that the students value the agile method using real world problems. However, the results are mainly based on the summer term 2019, this paper also includes our learnings from virtual distance teaching during the Covid 19 pandemic in summer term 2020. The paper contributes to the distribution of methods for higher education teaching in the classroom and distance learning.
Background
Chronic obstructive pulmonary disease (COPD) causes significant morbidity and mortality worldwide. Estimation of incidence, prevalence and disease burden through routine insurance data is challenging because of under-diagnosis and under-treatment, particularly for early stage disease in health care systems where outpatient International Classification of Diseases (ICD) diagnoses are not collected. This poses the question of which criteria are commonly applied to identify COPD patients in claims datasets in the absence of ICD diagnoses, and which information can be used as a substitute. The aim of this systematic review is to summarize previously reported methodological approaches for the identification of COPD patients through routine data and to compile potential criteria for the identification of COPD patients if ICD codes are not available.
Methods
A systematic literature review was performed in Medline via PubMed and Google Scholar from January 2000 through October 2018, followed by a manual review of the included studies by at least two independent raters. Study characteristics and all identifying criteria used in the studies were systematically extracted from the publications, categorized, and compiled in evidence tables.
Results
In total, the systematic search yielded 151 publications. After title and abstract screening, 38 publications were included into the systematic assessment. In these studies, the most frequently used (22/38) criteria set to identify COPD patients included ICD codes, hospitalization, and ambulatory visits. Only four out of 38 studies used methods other than ICD coding. In a significant proportion of studies, the age range of the target population (33/38) and hospitalization (30/38) were provided. Ambulatory data were included in 24, physician claims in 22, and pharmaceutical data in 18 studies. Only five studies used spirometry, two used surgery and one used oxygen therapy.
Conclusions
A variety of different criteria is used for the identification of COPD from routine data. The most promising criteria set in data environments where ambulatory diagnosis codes are lacking is the consideration of additional illness-related information with special attention to pharmacotherapy data. Further health services research should focus on the application of more systematic internal and/or external validation approaches.
During the intraoperative radiograph generation process with mobile image intensifier systems (C-arm) most of the radiation exposure for patient, surgeon and operation room personal is caused by scattered radiation. The intensity and propagation of scattered radiation depend on different parameters, e.g. the intensity of the primary radiation, and the positioning of the mobile image intensifier. Exposure through scattered radiation can be minimized when all these parameters are adjusted correctly. Because radiation is potentially dangerous and could not be perceived by any human sense the current education on correct adjustment of a C-arm is designed very theoretical. This paper presents an approach of scattered radiation calculation and visualization embedded in a computer based training system for mobile image intensifier systems called virtX. With the help of this extension the virtX training system should enrich the current radiation protection training with visual and practical training aspects.
Smart Cities require reliable means for managing installations that offer essential services to the citizens. In this paper we focus on the problem of evacuation of smart buildings in case of emergencies. In particular, we present an abstract architecture for situation-aware evacuation guidance systems in smart buildings, describe its key modules in detail, and provide some concrete examples of its structure and dynamics.
Background: Virtual reality (VR) is increasingly used as simulation technology in emergency medicine education and training, in particular for training nontechnical skills. Experimental studies comparing teaching and learning in VR with traditional training media often demonstrate the equivalence or even superiority regarding particular variables of learning or training effectiveness.
Objective: In the EPICSAVE (Enhanced Paramedic Vocational Training with Serious Games and Virtual Environments) project, a highly immersive room-scaled multi-user 3-dimensional VR simulation environment was developed. In this feasibility study, we wanted to gain initial insights into the training effectiveness and media use factors influencing learning and training in VR.
Methods: The virtual emergency scenario was anaphylaxis grade III with shock, swelling of the upper and lower respiratory tract, as well as skin symptoms in a 5-year-old girl (virtual patient) visiting an indoor family amusement park with her grandfather (virtual agent). A cross-sectional, one-group pretest and posttest design was used to evaluate the training effectiveness and quality of the training execution. The sample included 18 active emergency physicians.
Results: The 18 participants rated the VR simulation training positive in terms of training effectiveness and quality of the training execution. A strong, significant correlation (r=.53, P=.01) between experiencing presence and assessing training effectiveness was observed. Perceived limitations in usability and a relatively high extraneous cognitive load reduced this positive effect.
Conclusions: The training within the virtual simulation environment was rated as an effective educational approach. Specific media use factors appear to modulate training effectiveness (ie, improvement through “experience of presence” or reduction through perceived limitations in usability). These factors should be specific targets in the further development of this VR simulation training.
Sustainable tourism is a niche market that has been growing in recent years. At the same time, companies in the mass tourism market have increasingly marketed themselves with a “green” image, although this market is not sustainable. In order to successfully market sustainability, targeted marketing tactics are needed.
The aim of this research is to establish appropriate marketing tactics for sustainable tourism in the niche market and in the mass market. The purpose is to uncover current marketing tactics for both the mass tourism market and the sustainable tourism niche market. It also intends to explore how consumers who are more interested in sustainability differ from consumers with less interest in sustainability in terms of their perception of sustainability in tourism. Furthermore, this research paper will assess the trustworthiness of sustainable travel offers and the trustworthiness of quality seals in sustainable tourism. For this purpose, an online survey was conducted, which was addressed at German-speaking consumers. The survey showed, that consumers with more general interest in sustainability also consider sustainability to be more relevant in tourism. Offers for sustainable travel and quality seals were perceived as not very trustworthy. Moreover, no link could be found between the interest in sustainability and the perception of trustworthiness.
On the basis of the above, it is advisable to directly advertise sustainability in the niche market and to mention sustainability in the mass market only as an accompaniment or not at all. Further research could be undertaken to identify which factors influence the trustworthiness of offers, and trustworthiness of quality seals in sustainable tourism.
During the Corona-Pandemic, information (e.g. from the analysis of balance sheets and payment behavior) traditionally used for corporate credit risk analysis became less valuable because it represents only past circumstances. Therefore, the use of currently published data from social media platforms, which have shown to contain valuable information regarding the financial stability of companies, should be evaluated. In this data e. g. additional information from disappointed employees or customers can be present. In order to analyze in how far this data can improve the information base for corporate credit risk assessment, Twitter data regarding the ten greatest insolvencies of German companies in 2020 and solvent counterparts is analyzed in this paper. The results from t-tests show, that sentiment before the insolvencies is significantly worse than in the comparison group which is in alignment with previously conducted research endeavors. Furthermore, companies can be classified as prospectively solvent or insolvent with up to 70% accuracy by applying the k-nearest-neighbor algorithm to monthly aggregated sentiment scores. No significant differences in the number of Tweets for both groups can be proven, which is in contrast to findings from studies which were conducted before the Corona-Pandemic. The results can be utilized by practitioners and scientists in order to improve decision support systems in the domain of corporate credit risk analysis. From a scientific point of view, the results show, that the information asymmetry between lenders and borrowers in credit relationships, which are principals and agents according to the principal-agent-theory, can be reduced based on user generated content from social media platforms. In future studies, it should be evaluated in how far the data can be integrated in established processes for credit decision making. Furthermore, additional social media platforms as well as samples of companies should be analyzed. Lastly, the authenticity of user generated contend should be taken into account in order to ensure, that credit decisions rely on truthful information only.
Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model.
The antimicrobial activity of a phagemixture and a lactic acid bacteriumagainst Staphylococcus aureus isolates from bovine origin was investigated in vitro with regard to possible applications in the therapy of udder inflammation (mastitis) caused by bacterial infections. The S. aureus isolates used for inoculation derived from quarter foremilk samples of mastitis cases. For the examination of the antimicrobial activity, the reduction of the S. aureus germ density was determined [log10 cfu/mL]. The phage mixture consisted of the three obligatory lytic and S. aureus-specific phages STA1.ST29, EB1.ST11 and EB1.ST27 (1:1:1). The selected Lactobacillus plantarum strain with proven antimicrobial properties and the phage mixture were tested against S. aureus in milk, both alone and in combination. The application of the lactic acid bacterium showed only a low reduction ability for a 24 h incubation period. The bacteriophage mixture as well as its combination with the lactic acid bacterium showed high antimicrobial activity against S. aureus for a 24 h incubation period at 37 C, with only the phage mixture showing significance.
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.