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On November 30th, 2022, OpenAI released the large language model ChatGPT, an extension of GPT-3. The AI chatbot provides real-time communication in response to users’ requests. The quality of ChatGPT’s natural speaking answers marks a major shift in how we will use AI-generated information in our day-to-day lives. For a software engineering student, the use cases for ChatGPT are manifold: assessment preparation, translation, and creation of specified source code, to name a few. It can even handle more complex aspects of scientific writing, such as summarizing literature and paraphrasing text. Hence, this position paper addresses the need for discussion of potential approaches for integrating ChatGPT into higher education. Therefore, we focus on articles that address the effects of ChatGPT on higher education in the areas of software engineering and scientific writing. As ChatGPT was only recently released, there have been no peer-reviewed articles on the subject. Thus, we performed a structured grey literature review using Google Scholar to identify preprints of primary studies. In total, five out of 55 preprints are used for our analysis. Furthermore, we held informal discussions and talks with other lecturers and researchers and took into account the authors’ test results from using ChatGPT. We present five challenges and three opportunities for the higher education context that emerge from the release of ChatGPT. The main contribution of this paper is a proposal for how to integrate ChatGPT into higher education in four main areas.
On November 30th, 2022, OpenAI released the large language model ChatGPT, an extension of GPT-3. The AI chatbot provides real-time communication in response to users’ requests. The quality of ChatGPT’s natural speaking answers marks a major shift in how we will use AI-generated information in our day-to-day lives. For a software engineering student, the use cases for ChatGPT are manifold: assessment preparation, translation, and creation of specified source code, to name a few. It can even handle more complex aspects of scientific writing, such as summarizing literature and paraphrasing text. Hence, this position paper addresses the need for discussion of potential approaches for integrating ChatGPT into higher education. Therefore, we focus on articles that address the effects of ChatGPT on higher education in the areas of software engineering and scientific writing. As ChatGPT was only recently released, there have been no peer-reviewed articles on the subject. Thus, we performed a structured grey literature review using Google Scholar to identify preprints of primary studies. In total, five out of 55 preprints are used for our analysis. Furthermore, we held informal discussions and talks with other lecturers and researchers and took into account the authors’ test results from using ChatGPT. We present five challenges and three opportunities for the higher education context that emerge from the release of ChatGPT. The main contribution of this paper is a proposal for how to integrate ChatGPT into higher education in four main areas.
The research project "Herbar Digital" was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown, so a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character was transformed into a dynamic form. This was done with the model of an inert ball which was rolled along the written character. During this off-line writer recognition, different mathematical procedures were used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character was used, a recognition rate of about 40% was obtained. By combining multiple characters, the recognition rate rose considerably and reached 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). A global statistical approach using the whole handwritten text resulted in a similar recognition rate. By combining local and global methods, a recognition rate of 99.5% was achieved.
The methods developed in the research project "Herbar Digital" are to help plant taxonomists to master the great amount of material of about 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown. So a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character is transformed into a dynamic form. This is done with the model of an inert ball which is rolled through the written character. During this off-line writer recognition, different mathematical procedures are used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character is used, a recognition rate of about 40% is obtained. By combining multiple characters, the recognition rate rises considerably and reaches 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). Another approach tries to identify the writer by handwritten words. The word is cut out and transformed into a 6-dimensional time series and compared e.g. by means of DTW-methods. A global statistical approach using the whole handwritten sentences results in a similar recognition rate of more than 98%. By combining the methods, a recognition rate of 99.5% is achieved.
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.
Background
The business of clinical research has changed in the past two decades, shifting from industrialised Western countries to so-called emerging markets such as Eastern Europe, Latin America and Africa. An appraisal of the trends could identify associated factors that may have implications for the local populations and their endemic diseases.
Objectives
To identify potential reasons why emerging countries have become attractive places for international sponsors to conduct their clinical trials.
Methods
Using ClinicalTrials.gov, the Pan African Clinical Trials Registry, the National Health Research Database and the Nigeria Clinical Trials Registry, trend data on clinical research development were determined for two emerging African markets, Nigeria and South Africa (SA), from 2010 to 2018. Also, health data on the two countries from the fact sheets of health statistics of the World Health Organization were compared, as well as regulatory and ethical conditions. Available data were analysed using descriptive statistics and trend analysis.
Results
The impact of globalisation is evident from the upward trend in clinical trials in SA before 2010, and the clear downward trend thereafter. One reason for this change could be the alignment of SA’s regulatory and ethical frameworks with the Western world. In contrast,
the upward trend is only just beginning in Nigeria, with the introduction of ethical/regulatory frameworks, and supportive institutions making the business of clinical research more attractive on an international level. Although the number of international and local sponsors increased in Nigeria from 2010 to 2018, only the latter increased in SA, with the former decreasing over the same period. Overall, there is a mismatch between country-specific diseases and the drugs being tested, to the extent that leprosy, which is endemic in Nigeria, and tuberculosis in SA were not in the list of top 10 study areas in either country.
Conclusions
The globalisation trend is evident in the clinical trials business, but cannot be generalised to all emerging countries. Timing and intensity vary from country to country relative to factors that advance the existing profit-orientated business models of the sponsors. Furthermore, various diseases have been localised, which entails a diversely increasing need for research.
Objectives:
The aim was to identify theoretically expected as well as actually reported benefits from drug development and the importance of individual patient benefits compared to the collective benefits to society in general.
Background:
Ethical guidelines require that clinical research involving humans offer the potential for benefit. A number of characteristics can be applied to define research benefit. Often benefit is categorized as being either direct or indirect. Indirect benefits can involve collective benefits for society rather than any benefits to the trial patient or subject. The purpose of this review was to examine which potential individual and societal benefits were mentioned as being expected in publications from government experts and which were mentioned in publications describing completed drug development trial results.
Methods:
Literature on research benefit was first identified by searching the PubMed database using several combinations of the key words benefit and clinical research. The search was limited to articles published in English. A Google search with the same combinations of key words but without any language limitation was then performed. Additionally, the reference lists of promising articles were screened for further thematically related articles. Finally, a narrative review was performed of relevant English- and German-language articles published between 1996 and 2016 to identify which of several potential benefits were either theoretically expected or which were mentioned in publications on clinical drug development trial results.
Results:
The principal benefits from drug development discussed included 2 main types of benefit, namely individual benefits for the patients and collective benefits for society. Twenty-one of an overall total of 26 articles discussing theoretically expected benefits focused on individual patient benefits, whereas 17 out of 26 articles mentioned collective benefits to society. In these publications, the most commonly mentioned theoretically expected individual patient benefit was the chance to receive up-to-date care (38.1%). A general increase in knowledge about health care, treatments, or drugs (70.6%) was the most commonly mentioned theoretically expected benefit for society. In contrast, all 13 publications reporting actual benefits of clinical drug development trials focused on personal benefits and only 1 of these publications also mentioned a societal benefit. The most commonly mentioned individual benefit was an increased quality of life (53.9%), whereas the only mentioned collective benefit to society was a general gain of knowledge (100.0%).
Conclusions:
Both theoretically expected and actually reported benefits in the majority of the included publications emphasized the importance of individual patient benefits from drug development rather than the collective benefits to society in general. The authors of these publications emphasized the right of each individual patient or subject to look for and expect some personal benefit from participating in a clinical trial rather than considering societal benefit as a top priority. From an ethical point of view, the benefits each individual patient receives from his or her participation in a clinical trial might also be seen as a societal benefit, especially when the drug or device tested, if approved for marketing, would eventually be made available for other similar patients from the country in which the clinical trial was conducted.
Objectives
Quality of care largely depends on successful teamwork, which in turn needs effective communication between health professionals. To communicate successfully in a team, health professionals need to strive for the same goals. However, it has been left largely unaddressed which goals professionals consider to be important. In this study, we aim to identify these goals and analyse whether differences between (1) personal and organisational goals, (2) different professions and (3) hierarchical levels exist in neonatal intensive care units (NICUs).
Design
Goals were identified based on a literature review and a workshop with health professionals and tested in a pilot study. Subsequently, in the main study, a cross-sectional employee survey was undertaken.
Setting and participants
1489 nurses and 537 physicians from 66 German NICUs completed the
questionnaire regarding personal and organisational goal importance between May and July 2013. Answers were given based on a 7-point Likert scale varying between none and exceptionally high importance.
Results
Results show that the goals can be subdivided into three main goal dimensions: patients, parents and staff. Furthermore, our results reveal significant differences between different professions and different hierarchical level: physicians rated patient goals with a
mean (95% CI) importance of 6.37 (3.32 to 6.43), which is significantly higher than nurses with a mean (95% CI) importance of 6.15 (6.12 to 6.19) (p<0.01). Otherwise, nurses classified parental goals as more important (p<0.01). Furthermore, professionals in leading positions rate patient goals significantly higher than professionals that are not in leading positions (6.36 (3.28 to 6.44) vs 6.19 (6.15 to 6.22), p<0.01).
Conclusions
Different employee goals need to be considered in decision-making
processes to enhance employee motivation and the effectiveness of teamwork.
The NOA project collects and stores images from open access publications and makes them findable and reusable. During the project a focus group workshop was held to determine whether the development is addressing researchers’ needs. This took place before the second half of the project so that the results could be considered for further development since addressing users’ needs is a big part of the project. The focus was to find out what content and functionality they expect from image repositories.
In a first step, participants were asked to fill out a survey about their images use. Secondly, they tested different use cases on the live system. The first finding is that users have a need for finding scholarly images but it is not a routine task and they often do not know any image repositories. This is another reason for repositories to become more open and reach users by integrating with other content providers. The second finding is that users paid attention to image licenses but struggled to find and interpret them while also being unsure how to cite images. In general, there is a high demand for reusing scholarly images but the existing infrastructure has room to improve.
Wearable sensors in healthcare and sensor-enhanced health information systems: all our tomorrows?
(2012)
Wearable sensor systems which allow for remote or self-monitoring of health-related parameters are regarded as one means to alleviate the consequences of demographic change. This paper aims to summarize current research in wearable sensors as well as in sensor-enhanced health information systems. Wearable sensor technologies are already advanced in terms of their technical capabilities and are frequently used for cardio-vascular monitoring. Epidemiologic predictions suggest that neuro-psychiatric diseases will have a growing impact on our health systems and thus should be addressed more intensively. Two current project examples demonstrate the benefit of wearable sensor technologies: long-term, objective measurement under daily-life, unsupervised conditions. Finally, up-to-date approaches for the implementation of sensor-enhanced health information systems are outlined. Wearable sensors are an integral part of future pervasive, ubiquitous and person-centered health
care delivery. Future challenges include their integration into sensor-enhanced health information systems and sound evaluation studies involving measures of workload reduction and costs.
Background: Depletion of ovarian hormone in postmenopausal women has been associated with changes in the locomotor apparatus that may compromise walking function including muscle atrophy/weakness, weight gain, and bone demineralization. Therefore, handgrip strength (HGS), bone mineral density (BMD) and body composition [percentage body fat mass (%BFM), fat mass (FM), Fat-free mass (FFM) and body mass index (BMI)], may significantly vary and predict WB in postmenopausal women. Consequently, the study sought to 1. Explore body composition, BMD and muscle strength differences between premenopausal and postmenopausal women and 2. Explore how these variables [I.e., body composition, BMD and muscle strength] relate to WB in postmenopausal women.
Method: Fifty-one pre-menopausal (35.74 + 1.52) and 50 postmenopausal (53.32 + 2.28) women were selected by convenience sampling and studied. Six explanatory variables (HGS, BMD, %BFM, FFM, BMI and FM) were explored to predict WB in postmenopausal women: Data collected were analyzed using multiple linear regression, ANCOVA, independent t-test and Pearson correlation coefficient at p < 0.05.
Result: Postmenopausal women had higher BMI(t = + 1.72; p = 0.04), %BFM(t = + 2.77; p = .003), FM(t = + 1.77; p = 0.04) and lower HGS(t = − 3.05; p = 0.001),compared to the premenopausal women. The predicted main effect of age on HGS was not significant, F(1, 197) = 0.03, p = 0.06, likewise the interaction between age and %BFM, F(1, 197) = 0.02, p = 0.89; unlike the predicted main effect of %BFM, F(1, 197) = 10.34, p = .002, on HGS. HGS was the highest predictor of WB (t = 2.203; β=0.3046) in postmenopausal women and combined with T-score right big toe (Tscorert) to produce R2 = 0.11;F (2, 47)=4.11;p = 0.02 as the best fit for the predictive model. The variance (R2) change was significant from HGS model (R2 = 0.09;p = 0.03) to HGS + Tscorert model (R2 = 0.11;p = 0.02). The regression model equation was therefore given as: WB =5.4805 + 0.1578(HGS) + (− 1.3532) Tscorert.
Conclusion: There are differences in body composition suggesting re-compartmentalization of the body, which may adversely impact the (HGS) muscle strength in postmenopausal women. Muscle strength and BMD areassociated with WB, although, only contribute to a marginal amount of the variance for WB. Therefore, other factors in addition to musculoskeletal health are necessary to mitigate fall risk in postmenopausal women.
For anomaly-based intrusion detection in computer networks, data cubes can be used for building a model of the normal behavior of each cell. During inference an anomaly score is calculated based on the deviation of cell metrics from the corresponding normality model. A visualization approach is shown that combines different types of diagrams and charts with linked user interaction for filtering of data.
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.
This study investigates the influence of traumatic events on the mental health of North Korean refugee women by examining the prevalence and severity of posttraumatic stress disorder (PTSD), depression, and anxiety in comparison with their male counterparts (women = 496; men = 131). Our results suggest that women are at greater risk of developing mental health problems than men. In particular, symptoms of PTSD and anxiety were higher among women who experienced forced repatriation to North Korea, which is operationalized as a constellation of gendered traumatic incidents such as sexual abuse, rape, witnessing infanticides, and forced abortion. The policy implications of our results and suggestions for future studies are discussed.
The use of vibrational sum-frequency spectroscopy (VSFS) to study transferred graphene, produced by chemical vapour deposition, is presented. The VSF spectrum shows a clear CeH stretching mode at ~2924 cm⁻¹, which is attributed to residue of the polymer used for the transfer. This makes VSFS a powerful tool to identify adsorbates and contaminants affecting the properties of graphene.
We report velocity-dependent internal energy distributions of nitric oxide molecules, NO, scattered off graphene supported on gold to further explore the dynamics of the collision process between NO radicals and graphene. These experiments were performed by directing a molecular beam of NO onto graphene in a surface-velocity map imaging setup, which allowed us to record internal energy distributions of the NO radicals as a function of their velocity. We do not observe bond formation but (1) major contributions from direct inelastic scattering and (2) a smaller trapping–desorption component where some physisorbed NO molecules have residence times on the order of microseconds. This is in agreement with our classical molecular dynamics simulations which also observe a small proportion of two- and multi-bounce collisions events but likewise a small proportion of NO radicals trapped at the surface for the entire length of the molecular dynamics simulations (a few picoseconds). Despite a collision energy of 0.31 eV, which would be sufficient to populate NO(v = 1), we do not detect vibrationally excited nitric oxide.
Scientific papers from all disciplines contain many abbreviations and acronyms. In many cases these acronyms are ambiguous. We present a method to choose the contextual correct definition of an acronym that does not require training for each acronym and thus can be applied to a large number of different acronyms with only few instances. We constructed a set of 19,954 examples of 4,365 ambiguous acronyms from image captions in scientific papers along with their contextually correct definition from different domains. We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of the acronym. We show that this method clearly outperforms (classical) cosine similarity. Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.
Using openEHR Archetypes for Automated Extraction of Numerical Information from Clinical Narratives
(2019)
Up to 80% of medical information is documented by unstructured data such as clinical reports written in natural language. Such data is called unstructured because the information it contains cannot be retrieved automatically as straightforward as from structured data. However, we assume that the use of this flexible kind of documentation will remain a substantial part of a patient’s medical record, so that clinical information systems have to deal appropriately with this type of information description. On the other hand, there are efforts to achieve semantic interoperability between clinical application systems through information modelling concepts like HL7 FHIR or openEHR. Considering this, we propose an approach to transform unstructured documented information into openEHR archetypes. Furthermore, we aim to support the field of clinical text mining by recognizing and publishing the connections between openEHR archetypes and heterogeneous phrasings. We have evaluated our method by extracting the values to three openEHR archetypes from unstructured documents in English and German language.
In huge warehouses or stockrooms, it is often very difficult to find a certain item, because it has been misplaced and is therefore not at its assumed position. This position paper presents an approach on how to coordinate mobile RFID agents using a blackboard architecture based on Complex Event Processing.
Worldwide, seagrass meadows are under threat. Consequently, there is a strong need for seagrass restoration to guarantee the provision of related ecosystem services such as nutrient cycling, carbon sequestration and habitat provision. Seagrass often grows in vast meadows in which the presence of seagrass itself leads to a reduction of hydrodynamic energy. By modifying the environment, seagrass thus serves as foundation species and ecosystem engineer improving habitat quality for itself and other species as well as positively affecting its own fitness. On the downside, this positive feedback mechanism can render natural recovery of vanished and destroyed seagrass meadows impossible. An innovative approach to promote positive feedback mechanisms in seagrass restoration is to create an artificial seagrass (ASG) that mimics the facilitation function of natural seagrass. ASG could provide a window of opportunity with respect to suitable hydrodynamic and light conditions as well as sediment stabilization to allow natural seagrass to re-establish. Here, we give an overview of challenges and open questions for the application of ASG to promote seagrass restoration based on experimental studies and restoration trials and we propose a general approach for the design of an ASG produced from biodegradable materials. Considering positive feedback mechanisms is crucial to support restoration attempts. ASG provides promising benefits when habitat conditions are too harsh for seagrass meadows to re-establish themselves.
In the area of manufacturing and process automation in industrial applications, technical energy management systems are mainly used to measure, collect, store, analyze and display energy data. In addition, PLC programs on the control level are required to obtain the energy data from the field level. If the measured data is available in a PLC as a raw value, it still has to be processed by the PLC, so that it can be passed on to the higher layers in a suitable format, e.g. via OPC UA. In plants with heterogeneous field device installations, a high engineering effort is required for the creation of corresponding PLC programs. This paper describes a concept for a code generator that can be used to reduce this engineering effort.
The network security framework VisITMeta allows the visual evaluation and management of security event detection policies. By means of a "what-if" simulation the sensitivity of policies to specific events can be tested and adjusted. This paper presents the results of a user study for testing the usability of the approach by measuring the correct completion of given tasks as well as the user satisfaction by means of the system usability scale.
For the introduction of technical nursing care innovations, a usability assessment survey is conducted by nursing staff. The questionnaire is used before and after the introduction of technical products. This poster contribution shows the latest comparison of pre- and post-surveys on selected products.
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.
Type 2 Diabetes Mellitus: Risk Evaluation and Advice in Undergraduate Students in Ashrafieh, Lebanon
(2016)
Type 2 diabetes mellitus (T2DM) is a chronic lifestyle disease. It has become evident that T2DM occurs even among the younger age groups.1 In Lebanon, T2DM has a major public health impact through high disease prevalence, significant downstream pathophysiologic effects, and enormous financial liabilities.2
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.
The paper sheds light on the change in the concept of obedience within the Society of Jesus since the 1960s. In the aftermath of the Second Vatican Council, a so-called crisis of authority and obedience took place in the Catholic Church and the religious orders. As a consequence, the notions of responsibility and conscience came to the fore in the Jesuit definition of obedience. The religious concept of obedience, that is the obedience towards God, was reassessed as a service to humanity. The paper analyzes how the change in the concept of obedience gave rise to the promotion of social justice, which the Society of Jesus proclaimed at General Congregation 32 in 1974/75. By including the promotion of social justice into their central mission, Jesuits not only fundamentally transformed their self-conception, but also their ethical values. The paper argues that the pursuit of social justice became a form of religious obedience.
Training and evaluating deep learning models on road graphs for traffic prediction using SUMO
(2024)
The escalation of traffic volume in urban areas poses multifaceted challenges including increased accident risks, congestion, and prolonged travel times. Traditional approaches of expanding road infrastructure face limitations such as space constraints and the potential exacerbation of traffic issues.
Intelligent Transport Systems (ITS) present an alternative strategy to alleviate traffic problems by leveraging data-driven solutions. Central to ITS is traffic prediction, a process vital for applications like Traffic Management and Navigation Systems.
Recent advancements in traffic prediction have witnessed a surge of interest, particularly in deep learning methods optimized for graph-based data processing, being considered the most promising avenue presently.
These methods typically rely on real-life datasets containing traffic sensor data such as METR-LA and PeMS. However, the finite nature of real-life data prompts exploration into augmenting training and testing datasets with simulated traffic data.
This thesis explores the potential of utilizing traffic simulations, employing the microscopic traffic simulator SUMO, to train and test deep learning models for traffic prediction. A framework integrating PyTorch and SUMO is proposed for this purpose, aiming to elucidate the feasibility and effectiveness of using simulated traffic data for enhancing predictive models in traffic management systems.
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
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.
Nowadays, most recommender systems are based on a centralized architecture, which can cause crucial issues in terms of trust, privacy, dependability, and costs. In this paper, we propose a decentralized and distributed MANET-based (Mobile Ad-hoc NETwork) recommender system for open facilities. The system is based on mobile devices that collect sensor data about users locations to derive implicit ratings that are used for collaborative filtering recommendations. The mechanisms of deriving ratings and propagating them in a MANET network are discussed in detail. Finally, extensive experiments demonstrate the suitability of the approach in terms of different performance metrics.
In this paper the workflow of the project 'Untersuchungs-, Simulations- und Evaluationstool für Urbane Logistik` (USEfUL) is presented. Aiming to create a web-based decision support tool for urban logistics, the project needed to integrate multiple steps into a single workflow, which in turn needed to be executed multiple times. While a service-oriented system could not be created, the principles of service orientation was utilized to increase workflow efficiency and flexibility, allowing the workflow to be easily adapted to new concepts or research areas.
Objectives: Injury to major white matter pathways during language-area associated glioma surgery often leads to permanent loss of neurological function. The aim was to establish standardized tractography of language pathways as a predictor of language outcome in clinical neurosurgery.
Methods: We prospectively analyzed 50 surgical cases of patients with left perisylvian, diffuse gliomas. Standardized preoperative Diffusion-Tensor-Imaging (DTI)-based tractography of the 5 main language tracts (Arcuate Fasciculus [AF], Frontal Aslant Tract [FAT], Inferior Fronto-Occipital Fasciculus [IFOF], Inferior Longitudinal Fasciculus [ILF], Uncinate Fasciculus [UF]) and spatial analysis of tumor and tracts was performed. Postoperative imaging and the resulting resection map were analyzed for potential surgical injury of tracts. The language status was assessed preoperatively, postoperatively and after 3 months using the Aachen Aphasia Test and Berlin Aphasia Score. Correlation analyses, two-step cluster analysis and binary logistic regression were used to analyze associations of tractography results with language outcome after surgery.
Results: In 14 out of 50 patients (28%), new aphasic symptoms were detected 3 months after surgery. The preoperative infiltration of the AF was associated with functional worsening (cc = 0.314; p = 0.019). Cluster analysis of tract injury profiles revealed two areas particularly related to aphasia: the temporo-parieto-occipital junction (TPO; temporo-parietal AF, middle IFOF, middle ILF) and the temporal stem/peri-insular white matter (middle IFOF, anterior ILF, temporal UF, temporal AF). Injury to these areas (TPO: OR: 23.04; CI: 4.11 – 129.06; temporal stem: OR: 21.96; CI: 2.93 – 164.41) was associated with a higher-risk of persisting aphasia.
Conclusions: Tractography of language pathways can help to determine the individual aphasia risk profile presurgically. The TPO and temporal stem/peri-insular white matter were confirmed as functional nodes particularly sensitive to surgical injuries.
Agile methods require constant optimization of one’s approach and leading to the adaptation of agile practices. These practices are also adapted when introducing them to companies and their software development teams due to organizational constraints. As a consequence of the widespread use of agile methods, we notice a high variety of their elements:
Practices, roles, and artifacts. This multitude of agile practices, artifacts, and roles results in an unsystematic mixture. It leads to several questions: When is a practice a practice, and when is it a method or technique? This paper presents the tree of agile elements, a taxonomy of agile methods, based on the literature and guidelines of widely used agile methods. We describe a taxonomy of agile methods using terms and concepts of software engineering, in particular software process models. We aim to enable agile elements to be delimited, which should help companies, agile teams, and the research community gain a basic understanding of the interrelationships and dependencies of individual components of agile methods.
Microservices build a deeply distributed system. Although this offers significant flexibility for development teams and helps to find solutions for scalability or security questions, it also intensifies the drawbacks of a distributed system. This article offers a decision framework, which helps to increase the resiliency of microservices. A metamodel is used to represent services, resiliency patterns, and quality attributes. Furthermore, the general idea for a suggestion procedure is outlined.
Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories “governance”, “modeling” and “standards”, the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling.
The negative effects of traffic, such as air quality problems and road congestion, put a strain on the infrastructure of cities and high-populated areas. A potential measure to reduce these negative effects are grocery home deliveries (e-grocery), which can bundle driving activities and, hence, result in decreased traffic and related emission outputs. Several studies have investigated the potential impact of e-grocery on traffic in various last-mile contexts. However, no holistic view on the sustainability of e-grocery across the entire supply chain has yet been proposed. Therefore, this paper presents an agent-based simulation to assess the impact of the e-grocery supply chain compared to the stationary one in terms of mileage and different emission outputs. The simulation shows that a high e-grocery utilization rate can aid in decreasing total driving distances by up to 255 % relative to the optimal value as well as CO 2 emissions by up to 50 %.
Microservices are meanwhile an established software engineering vehicle, which more and more companies are examining and adopting for their development work. Naturally, reference architectures based on microservices come into mind as a valuable thing to utilize. Initial results for such architectures are published in generic and in domain-specific form. Missing to the best of our knowledge however, is a domain-specific reference architecture based on microservices, which takes into account specifics of the insurance industry domain. Jointly with partners from the German insurance industry, we take initial steps to fill this gap in the present article. Thus, we aim towards a microservices-based reference software architecture for (at least German) insurance companies. As the main results of this article we thus provide an initial such reference architecture together with a deeper look into two important parts of it.
In the context of the ongoing digitization of interdisciplinary subjects, the need for digital literacy is increasing in all areas of everyday life. Furthermore, communication between science and society is facing new challenges, not least since the COVID-19 pandemic. In order to deal with these challenges and to provide target-oriented online teaching, new educational concepts for the transfer of knowledge to society are necessary. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a didactic concept for the creation of E-Learning classes was developed. A key factor for the didactic concept is addressing heterogeneous target groups to reach the broadest possible spectrum of participants. The concept has already been used for the creation of the first ZLG E-Learning courses. This article outlines the central elements of the developed didactic concept and addresses the creation of the ZLG courses. The courses created so far appeal to different target groups and convey diverse types of knowledge at different levels of difficulty.
In this poster we present the ongoing development of an integrated free and open source toolchain for semantic annotation of digitised cultural heritage. The toolchain development involves the specification of a common data model that aims to increase interoperability across diverse datasets and to enable new collaborative research approaches.
Toward a service-based workflow for automated information extraction from herbarium specimens
(2018)
Over the past years, herbarium collections worldwide have started to digitize millions of specimens on an industrial scale. Although the imaging costs are steadily falling, capturing the accompanying label information is still predominantly done manually and develops into the principal cost factor. In order to streamline the process of capturing herbarium specimen metadata, we specified a formal extensible workflow integrating a wide range of automated specimen image analysis services. We implemented the workflow on the basis of OpenRefine together with a plugin for handling service calls and responses. The evolving system presently covers the generation of optical character recognition (OCR) from specimen images, the identification of regions of interest in images and the extraction of meaningful information items from OCR. These implementations were developed as part of the Deutsche Forschungsgemeinschaft funded a standardised and optimised process for data acquisition from digital images of herbarium specimens (StanDAP-Herb) Project.
We have combined the velocity map imaging technique with time-of-flight measurements to study the surface photochemistry of KBr single crystals. This approach yields 3-dimensional velocity distributions of Br atoms resulting from 193 nm photodesorption. The velocity distributions indicate that at least two non-thermal mechanisms contribute to the photodesorption dynamics. Our experimental geometry also allows us to measure the Br(²P₃⁄₂):Br(²P₁⁄₂) branching ratio, which is found to be 24:1.
Complexes like iron (II)-triazoles exhibit spin crossover behavior at ambient temperature and are often considered for possible application. In previous studies, we implemented complexes of this type into polymer nanofibers and first polymer-based optical waveguide sensor systems. In our current study, we synthesized complexes of this type, implemented them into polymers and obtained composites through drop casting and doctor blading. We present that a certain combination of polymer and complex can lead to composites with high potential for optical devices. For this purpose, we used two different complexes [Fe(atrz)3](2 ns)2 and [Fe(atrz)3]Cl1.5(BF4)0.5 with different polymers for each composite. We show through transmission measurements and UV/VIS spectroscopy that the optical properties of these composite materials can reversibly change due to the spin crossover effect.
Obesity and excess adiposity account for approximately 20% of all cancer cases; however, biomarkers of risk remain to be elucidated. While fibroblast growth factor-2 (FGF2) is emerging as an attractive candidate biomarker for visceral adipose tissue mass, the role of circulating FGF2 in malignant transformation remains unknown. Moreover, functional assays for biomarker discovery are limited. We sought to determine if human serum could stimulate the 3D growth of a non-tumorigenic cell line. This type of anchorage-independent 3D growth in soft agar is a surrogate marker for acquired tumorigenicity of cell lines. We found that human serum from cancer-free men and women has the potential to stimulate growth in soft agar of non-tumorigenic epithelial JB6 P+ cells. We examined circulating levels of FGF2 in humans in malignant transformation in vitro in a pilot study of n = 33 men and women. Serum FGF2 levels were not associated with colony formation in epithelial cells (r = 0.05, p = 0.80); however, a fibroblast growth factor receptor-1 (FGFR1) selective inhibitor significantly blocked serum-stimulated transformation, suggesting that FGF2 activation of FGFR1 may be necessary, but not sufficient for the transforming effects of human serum. This pilot study indicates that the FGF2/FGFR1 axis plays a role in JB6 P+ malignant transformation and describes an assay to determine critical serum factors that have the potential to promote tumorigenesis.
Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing in institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, structured data is limited and often exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic and consistent view on research information across organisational and national boundaries is not feasible. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.
From an ethical perspective, clinical research involving humans is only acceptable if it involves the potential for benefit. Various characteristics can be applied to differentiate research benefit. Often benefit is categorized in direct or indirect benefit, whereby indirect benefit might be further differentiated in collective or benefit for the society, excluding or including the trial patient in the long term. Ethical guidelines, such as the Declaration of Helsinki in its latest version, do not precisely favor a particular type of benefit.
The practice, attitude, and knowledge of complementary and alternative medicine in Mumbai, India
(2020)
Background: In the recent times, there has been a resurging interest in the use of complementary and alternative medicine (CAM) in India. The present study was conducted to examine the prevalence of CAM use in Mumbai, the knowledge and attitude regarding CAM regarding its safety and efficacy and the reasons for the use of CAM.
Methods: A cross-sectional study was conducted among the general population of Mumbai and its adjoining regions during January-July 2020. 205 residents participated in the study and were asked to fill a pretested questionnaire. The collected data was analyzed using IBM SPSS version 23.
Results: Out of the 205 responses, 163 (79.51%) agreed to have used CAM at least once in their life. Of these, 108 (52.68%) respondents used Ayurveda and 105 (51.21%) used homeopathy. 60 (36.81%) of the respondents practicing CAM used it for common gastrointestinal (GIT)-related disorder with a 100% recovery rate, 125 (76.67%) for infectious diseases with a 93.6% recovery rate. 99 (60.74%) of the respondents preferring CAM for its safety profile, 68 (41.72%) believed that CAM is time tested and thus is efficacious. An integrative approach was suggested by 118 (57.56%) of all the respondents.
Conclusions: There is a disparity between the high prevalence in the use of CAM and its knowledge. However, a general consensus suggests that CAM is efficacious and is practiced for various indications.
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.
This paper reflects the content of the presentation “The Next Generation: Ethernet-APL for Safety Systems” at the NAMUR Annual General Meeting 2022. It deals with the use of the Ethernet Advanced Physical Layer (Ethernet-APL) in combination with the PROFINET/PROFIsafe protocol for safety applications. It describes the virtues of the digital communication between the field and safety system. In parallel the aspect of OT security for this use case is touched as well. The paper proposes a secure architecture, where safety- and non-safety field communications are still separated. At the end a set of requirements for the development of future APL devices is described.