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Formative assessment is about providing and using feedback and diagnostic information. On this basis, further learning or further teaching should be adaptive and, in the best case, optimized. However, this aspect is difficult to implement in reality, as teachers work with a large number of students and the whole process of formative assessment, especially the evaluation of student performance takes a lot of time. To address this problem, this paper presents an approach in which student performance is collected through a concept map and quickly evaluated using Machine Learning techniques. For this purpose, a concept map on the topic of mechanics was developed and used in 14 physics classes in Germany. After the student maps were analysed by two human raters on the basis of a four-level feedback scheme, a supervised Machine Learning algorithm was trained on the data. The results show a very good agreement between the human and Machine Learning evaluation. Based on these results, an embedding in everyday school life is conceivable, especially as support for teachers. In this way, the teacher can use and interpret the automatic evaluation and use it in the classroom.

This study explores the relation between risk of job automation and participation in adult education and training (AET) and examines variation in that relation across welfare regimes distinguishing between situational and institutional barriers. Using microdata of PIAAC, we analyze participation in formal or nonformal AET for job-related reasons in relation to the risk of automation of the respondents' occupation after controlling for main sociodemographic characteristics. Logistic regression models are run on respondents from 14 European countries representing different welfare regimes: Denmark, Norway, and Sweden (Scandinavian countries); Italy, Greece, and Spain (Southern European); Czech Republic, Slovakia, and Poland (Central and Eastern Europe), Belgium, France, and Germany (Continental); and United Kingdom and Ireland (Anglo-Saxon countries). Our findings confirm that workers in occupations at high risk of automation were found to be consistently less likely to participate in job-related AET, quite irrespective of welfare regime. [The paper was presented at XIII Conferenza Espanet Italia--Il welfare state di fronte alle sfide globali (Venezia, 17 September 2020).]

Purpose: This paper aims to describe the principles underlying the successful implementation of a lecture recording service in higher education. Design/methodology/approach: The paper qualitatively reviews the practices and experiences of several years of automated lecture recording at a medium-sized university in Germany. Findings: The paper concludes that there are several principles that should be followed to successfully implement lecture recordings in higher education. Practical implications: The principles described in this paper can serve as recommendations for other universities that would like to establish or optimize their own lecture recording service. Originality/value: The value of the paper lies mainly in the great amount of experience in successfully running a lecture recording service on which the principles and recommendations are based.

AI and other forms of automation are causing a shift into a more capital-intensive form of capitalism. Many scholars have suggested that we can best understand this process as the cost-efficient substitution of labour by capital in routine tasks based on relative factor costs. However, this model, which has cast firms as endlessly chasing the productivity frontier, has not paid sufficient attention to cross-national divergences in technological changes. This paper builds a comparative historical case study tracing the divergent introduction of credit scoring in British and German bank branches to argue that the introduction of credit scoring was a result of a policy-led process in both countries. Increased liberalisation of financial market institutions benefitted the rise of market-led banking which fundamentally changed the business model of banks resulting in a devaluation of the services provided by branch managers. This case suggests we need to think about the role of politics and policy within our, often deterministic, models of labour-saving technological change. [ABSTRACT FROM AUTHOR]

Copyright of Anaesthesiologie & Intensivmedizin is the property of DGAI e.V. - Deutsche Gesellschaft fur Anasthesiologie und Intensivmedizin e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban simulations play an important role on the way to a climate neutral society. To enable early assessment of different energy concepts for urban developments, energy profiles for different building types are needed. This work describes the development and use of a new engineering tool GenSim to quickly and reliably generate energy profiles for urban simulations and early building energy predictions. While GenSim is a standalone tool to create energy profiles for early design assessment, it was developed in the context of urban simulations to primarily support energy efficient urban developments within Germany. Energy engineers quickly embraced the tool due to its simplicity and comprehensible results. The development of the tool was recently switched to open source to enable its usage to a broader audience. In order to foster its development and use, a detailed testing framework has been established to ensure the quality of the results of the tool. The paper includes a detailed validation section to demonstrate the validity of the results compared to a detailed building energy simulation model and actual measured performance data. [ABSTRACT FROM AUTHOR]

Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task and requires the application of natural language processing methodology. In this article, we implement and evaluate multiple machine learning models for coding energy knowledge in free‐text responses of German K‐12 students to items in formative science assessments which were conducted during synchronous online learning sessions. Dataset: The dataset we collected for this purpose consists of German constructed responses from 38 different items dealing with aspects of energy such as manifestation and transformation. The units and items were implemented with the help of project‐based pedagogy and evidence‐centered design, and the responses were coded for seven core ideas concerning the manifestation and transformation of energy. The data was collected from students in seventh, eighth and ninth grade. Methodology: We train various transformer‐ and feature‐based models and compare their ability to recognize the respective ideas in students' writing. Moreover, as domain knowledge and its development can be formally modeled through knowledge networks, we evaluate how well the detection of the ideas within responses translated into accurate co‐occurrence‐based knowledge networks. Finally, in terms of the descriptive accuracy of our models, we inspect what features played a role for which prediction outcome and if the models pick up on undesired shortcuts. In addition to this, we analyze how much the models match human coders in what evidence within responses they consider important for their coding decisions. Results: A model based on a modified GBERT‐large can achieve the overall most promising results, although descriptive accuracy varies much more than predictive accuracy for the different ideas assessed. For reasons of comparability, we also evaluate the same machine learning architecture using the SciEntsBank 3‐Way benchmark with an English RoBERTa‐large model, where it achieves state‐of‐the‐art results in two out of three evaluation categories. Lay Description: What is already known about this topic?: Formative assessments are needed to test and monitor the development of learners' knowledge throughout a unit to provide them with appropriate automated feedback.Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge.Assessing constructed responses in an automated fashion is a widely researched topic, but the problem is far from solved and most of the work focuses on predicting holistic scores or grades.To allow for a more fine‐grained and analytic assessment of learners' knowledge, systems which go beyond predicting simple grades are required.To guarantee that models are stable and make their predictions for the correct reasons, methods for explaining the models are required. What this papers adds?: A core topic in physics education is the concept of energy.We implement and evaluate multiple systems based on natural language processing technology for assessing learners' conceptual knowledge about energy physics using transformer language models as well as feature‐based approaches.The systems assess students' knowledge about various forms of energy, indicators for the same and the transformation of energy from form into another.As our systems are based on machine learning methodology, we introduce a novel German short answer dataset for training them to detect the respective knowledge elements within students' free‐text responses.We evaluate the performance of these systems using this dataset as well as the well‐established SciEntsBand‐3‐Way dataset and manage to achieve, to our best knowledge, new state‐of‐the‐art results for the latter.Moreover, we apply methodology for explaining model predictions to assess whether predictions are carried out for the correct reasons. Implications for practice and/or policy: It is indeed possible to assess constructed responses for the demonstrated knowledge about energy physics in an analytic fashion using natural language processing.Transformer language models can outperform more specialized feature‐based approaches for this task in terms of predictive and descriptive accuracy.Co‐occurrences of different concepts within the same responses can lead models to learn undesired shortcuts which make them unstable. [ABSTRACT FROM AUTHOR]

As part of the research project Open Data Cloud Services (ODCS), we have been trying to overcome some of the limitations introduced through the heterogeneity of spatial open government data (sOGD). In this paper we describe some of the challenges of sODG and one of the tools we built to spatially organize heterogenous sOGD, to make it easier for users to find data and automatically integrate it into existing data structures and in the future allow for crossdataset spatial analysis. In Europe and beyond the number of sOGD is continuously growing. Derived from government mapping and planning programs, remote sensing and other sources, open spatial government data provides insights into a broad range of topics from geology to weather phenomena, to socio-demographic developments and much more. The data is provided through a variety of government institutions. The distributed generation and provision of spatial data through these different stakeholders has created an extremely heterogenous data space. Heterogenous regarding formats, data structure (time, space, and other attributes), spatial granularity, classification, down to publication cycles and the documentation of changes over time. While national and international working groups are working towards more standardisation, and e.g., in Europe, particularly the INSPIRE (European Commission, 2022) initiative had a positive impact on the standardisation of open spatial data's meta data, as our analysis of all (registered) German open data sets showed, the quality and especially taxonomies still vary strongly between data providers. This heterogeneity presents obstacles for all stakeholders alike from the civil society to researchers to companies trying to build business models on top of open data. The goal is to classify data sets across a variety of spatial hierarchies. An exemplary hierarchy are administrative regions (see figure 1). Classifying a certain dataset to cover a certain state and its granularity to be on a community level, allows users to compare this data set to other data sets of the same granularity for other states. Other exemplary hierarchies in Germany are statistical districts or various grid systems. Beyond inconsistencies within individual hierarchies, calculating relationships between different hierarchies or even non-hierarchical organizational systems, e.g. urban density areas, systems based on natural features, is a challenge, which we are trying to overcome with our work. The ODCS infrastructure is comprised of multiple web services for processing OGD. The pipeline for the spatial classification (see Fig. 2) starts with the 1) aggregation of sOGD's meta data from a variety of sources. The resulting meta data is then 2) homogenized and stored in a central database. Based on the meta data the system then decides if this could potentially be a spatial data set (file format, file name, URL structure, etc.) and then tries to 3) download the actual dataset. The downloaded data is then 4) analysed, if necessary, the analysis and classification process is 5) assisted by a user and the resulting classified data or rather the improved meta data is 6) provisioned to the users of the platform. As described above, the classification should provide improved meta data, to serve users a more precise search and, for future applications, allow for automatic spatial analysis across multiple data sources. To build the classification we primarily rely on spatial hierarchies and relationships between data sets (unconnected, touching, intersecting, containing). To identify those relationships, data sets are analysed threefold: 1) The bounding box of the dataset is calculated and compared to existing bounding boxes in the database. Compared to the next two analysis steps this is fast and works for raster as well as vector datasets. For vector datasets we 2) proceed to generate a "union" from the dataset and then compare the union to other already classified datasets. Exact matches are quite rare (even for datasets from the same provider), therefore, we use buffers on the existing data sets as well as the to be classified data set. As figure 3 illustrates, one and the same border can exist in a variety of geometries. Differences resulting from simplification, generalisation, precision, or actual errors in the data. The differences are in part so big, that we implemented a graphical user interface for human assistance, to manually classify "outliers". If a "good enough" match cannot be found, the next best matches are stored in the database and are then provided to the user to choose from. After the dataset's "union" is analysed, we then 3) split the features up into individual polygons, to again compare those to the already classified polygons in our database. Data sets or rather their polygons that could not be classified are added to the manual classification queue and are then classified by the user. Through this semiautomatic process, the library of polygons quickly grows and increases the automation over time. The system also runs a thematic classification based on meta data and data set attributes, which goes beyond the scope of this paper. Due to the limitations of the abstract, we focused on an overview of the method, rather than the technologies used to perform the analysis. In short: GDAL, OGR2OGR, NodeJS, Python, PostgreSQL + PostGIS. While the above-described use case was developed for Germany's OGD portals, the technique is not limited to German spatial data sets, as all applied methods are not language-depended, but only rely on spatial geometries. Even the metadata homogenization, which is not described in depth in this paper, mostly relies on language-independent methods. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to conduct, to the best of our knowledge, the first systematic review of the implementation of Industry 4.0 in BRICS. This review facilitates the identification of main factors that affect the readiness to adopt Industry 4.0 in BRICS and the role of different agents, such as multinationals, the public sector or educative institutions. Design/methodology/approach: Key publications published from 2010 to 2019 have been analysed. A total of 61 papers have been selected from the systematic review. Findings: Three factors of convergence of BRICS to developed economies in terms of Industry 4.0 are identified: (1) the public initiatives that can also result in the attraction of talent from developed countries to BRICS; (2) the role of multinationals and (3) the implication of educational institutions. Research limitations/implications: This review has some limitations. First, some grey literature, such as reports from non-governmental organisations and front-line practitioners' reflections, were not included. Second, only research studies in English were reviewed Practical implications: The heterogeneity of BRICS amongst themselves affects the implementation of Industry 4.0 policies. Therefore, public policies should differ among countries to achieve the different readiness of companies within each country. Industry 4.0 cannot be understood as a manufacturing strategy against delocalisation, as emerging countries, such as BRICS, are also aware of the potential of automation. Originality/value: Based on a systematic review, this article shows that the strategy created by Germany to increase industrial productivity has been also introduced in BRICS countries as a critical factor to improve their competitiveness. [ABSTRACT FROM AUTHOR]

Since 2011, the Industry 4.0 initiative is a key research and development direction towards flexible production systems in Germany. The objective of the initiative is to deal with the challenge of an increased production complexity caused by various factors such as increasing global competition between companies, product variety, and individualization to meet customer needs. For this, Industry 4.0 envisions an overarching connection of information technologies with the production process, enabling smart manufacturing. Bringing current production systems to this objective will be a long transformation process, which requires a coherent migration path. The aim of this paper is to represent an exemplary production development way towards Industry 4.0 using eminent formalization approaches and standardized automation technologies. [ABSTRACT FROM AUTHOR]

Truck platoon driving is a current branch of automated driving, which has the potential to radically change the work routine of professional drivers. In a platoon system, one truck (semi-)automatically follows a lead truck with a reduced distance, which produces significant savings in fuel and enables better traffic flow. In a current application of truck platoon driving, the following vehicle operates at level-2 automation. Thus, the driver of the following truck merely has to supervise the semi-automated system, which takes over steering and speed control when engaged. Level-2 truck platoon driving had not been tested with professional drivers in real traffic before. We hypothesized that user acceptance would improve after the experience of platoon driving. Quantitative questionnaires and qualitative interviews were conducted with 10 drivers before and after an extensive Autobahn experience. The results show a clear increase of acceptance after the experience. Platoon driving was evaluated to be more useful, easier to use, and safer after the experience. Besides perceived driving safety, the prestige of truck platooning, the perceived usefulness of the system, and general technology affinity co-determined user acceptance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The purpose of the study was to investigate how drivers use assisted and automated driving systems (DAS), more specifically their usage of SAE Level 1 and Level 2 systems, in different situations. An online survey was distributed to 2500 respondents in China, Germany, Spain, and the USA. The final dataset consisted of 549 respondents, all non‐professional drivers, with access to a minimum of a Level 1 system. A subset, 159 in total, had access also to a Level 2 DAS. The survey included questions on the attitude towards, access to, and usage of Level 1 and Level 2 systems in nine different situations respectively. The data was analysed on an individual and a national level. A cluster analysis showed two main groups: frequent and non‐frequent users. On an individual level, the reported usage of Level 1 and Level 2 DAS respectively differed depending on traffic situation, weather and daylight conditions and driver state. Reports by respondents with access to both Level 1 and Level 2 systems did not reveal any statistically significant differences in usage between situations. The Spanish sample was the only one that showed a consistently different usage pattern compared to samples from China, Germany, and the USA. [ABSTRACT FROM AUTHOR]

In March 1964, the cover page of a popular German weekly magazine entitled Der Spiegel painted a frightening picture: An anthropomorphic robot with six mechanical arms commands an assembly line while a displaced human worker floats aimlessly in the foreground. Ejected from his station, the worker throws up his hands in despair next to a headline that reads, "Automation in Germany, the arrival of robots." Over fifty years later, a cover page from the same magazine evoked similar themes: A giant robot arm yanks an office worker away from his computer under the headline, "You're fired! How computers and robots steal our jobs - and which jobs will be safe." The more things change, the more they stay the same. [ABSTRACT FROM AUTHOR]

• A workflow to generate urban building energy profiles using low-level public data. • The framework combines top-down and bottom-up methods with data uncertainty. • Results show low-level public data significantly improves the model's accuracy. Urban building energy models provide an efficient way to estimate the district's energy demand and have been vigorously developed over the years. However, due to the lack of crucial information about building's physical descriptions, existing datasets cannot always meet the significant data demand for modeling. In addition, it is challenging to balance simulation time while ensuring simulation accuracy. Therefore, in order to solve the above difficulties, this paper makes some improvements and optimizations based on reduced-order building modeling and experience-based archetypes and presents a novel two-step approach combining bottom-up and top-down methods. A case study in a suburban district in Germany was chosen as a sample test case to demonstrate these workflow automation tools. The proposed workflow achieved a mean absolute percentage error of less than 2% for citywide energy demand prediction using low-level public data, compared to an error of 15% in the scenario without public data. The results indicate that although there was a lack of specific input data, the presented workflow was capable of obtaining accurate results with reduced computation time. The presented methodology offers an efficient way to establish urban building energy models using low-level datasets and provide relatively accurate results on a district level. [ABSTRACT FROM AUTHOR]

Background: Surveillance of surgical site infections (SSI) relies on access to data from various sources. Insights into the practices of German hospitals conducting SSI surveillance and their information technology (IT) infrastructures are scarce. The aim of this study was to evaluate current SSI surveillance practices in German hospitals with a focus on employed IT infrastructures. Methods: German surgical departments actively participating in the national SSI surveillance module "OP-KISS" were invited in August 2020 to participate in a questionnaire-based online survey. Depending on whether departments entered all data manually or used an existing feature to import denominator data into the national surveillance database, departments were separated into different groups. Selected survey questions differed between groups. Results: Of 1,346 invited departments, 821 participated in the survey (response rate: 61%). Local IT deficits (n = 236), incompatibility of import specifications and hospital information system (n = 153) and lack of technical expertise (n = 145) were cited as the most frequent reasons for not using the denominator data import feature. Conversely, reduction of workload (n = 160) was named as the main motivation to import data. Questions on data availability and accessibility in the electronic hospital information system (HIS) and options to export data from the HIS for the purpose of surveillance, yielded diverse results. Departments utilizing the import feature tended to be from larger hospitals with a higher level of care. Conclusions: The degree to which digital solutions were employed for SSI surveillance differed considerably between surgical departments in Germany. Improving availability and accessibility of information in HIS and meeting interoperability standards will be prerequisites for increasing the amount of data exported directly from HIS to national databases and laying the foundation for automated SSI surveillance on a broad scale. [ABSTRACT FROM AUTHOR]

In order to find new ways of growing the market, the Dutch General Publishers Association developed an innovation-competition for startups worldwide to bring innovative thinking and ideas into the Dutch Publishing Industry. The competition is the first and only program dedicated to startups leveraging new and creative business ideas around all the elements of book publishing and has its second edition this year. The competition is for startups, who are active in areas such as publishing automation, book retail, data analytics, authoring, book content development, and audience engagement. [ABSTRACT FROM AUTHOR]

We conduct a decomposition analysis based on recentred influence function (RIF) regressions to disentangle the relative importance of automation and robotization for wage inequality in the manufacturing sector in Germany between 1996 and 2017. Our measure of automation threat combines occupation‐specific scores of automation risk with sector‐specific robot densities. We find that besides changes in the composition of individual characteristics, structural shifts among different automation threat groups are a non‐negligible factor associated with wage inequality between 1996 and 2017. Moreover, the increase in wage dispersion among the different automation threat groups has contributed significantly to higher wage inequality in the 1990s and 2000s. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps. However, there is a potential risk of polyps being missed by the gastroenterologist. Automated detection of polyps helps to assist the gastroenterologist during a colonoscopy. There are already publications examining the problem of polyp detection in the literature. Nevertheless, most of these systems are only used in the research context and are not implemented for clinical application. Therefore, we introduce the first fully open-source automated polyp-detection system scoring best on current benchmark data and implementing it ready for clinical application. To create the polyp-detection system (ENDOMIND-Advanced), we combined our own collected data from different hospitals and practices in Germany with open-source datasets to create a dataset with over 500,000 annotated images. ENDOMIND-Advanced leverages a post-processing technique based on video detection to work in real-time with a stream of images. It is integrated into a prototype ready for application in clinical interventions. We achieve better performance compared to the best system in the literature and score a F1-score of 90.24% on the open-source CVC-VideoClinicDB benchmark. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Empirical evidence in Dauth et al. (J Eur Econ Assoc, 2021) suggests that industrial robot adoption in Germany has led to a sectoral reallocation of employment from manufacturing to services, leaving total employment unaffected. We rationalize this evidence through the lens of a general equilibrium model with two sectors, matching frictions and endogenous participation. Automation induces firms to create fewer vacancies and job seekers to search less in the automatable sector (manufacturing). The service sector expands due to the sectoral complementarity in the production of the final good and a positive wealth effect for the household. Analysis across steady states shows that the reduction in manufacturing employment can be offset by the increase in service employment. The model can also replicate the magnitude of the decline in the ratio of manufacturing employment to service employment in Germany between 1994 and 2014. [ABSTRACT FROM AUTHOR]

The papers in this special section focus on the concept of Industry 4.0. From its origin, Industry 4.0?derived from the German term Industrie 4.0?is used as a synonym for Cyber-Physical Production Systems (CPPS), i.e., Cyber-Physical Systems applied in the domain of manufacturing/production. To enable CPPS their automation systems need to be enabled to fulfill the requirements. The term Industrie 4.0 was first used in 2011 at the Hannover Fair and the topic has grown every year not only on the fair. There are still several definitions of Industrie 4.0 (I4.0). [ABSTRACT FROM AUTHOR]

User-related assessment of a level 3 automated driving system, providing functions such as lane- and distance-keeping, stop & go driving, lane change and overtaking, was carried out on a motorway in Germany with the aim to assess user-related issues of automated driving, i.e., behavior when driving with automation on motorways, user experiences, reactions and acceptance. Twenty-one persons drove twice along the test route once with the system switched off and once with the system active. Driving data were logged and driving behavior was observed by two observers in the car and the drivers answered questionnaires. The results revealed that the drivers used the system as it was intended to be used and that the system affected driving positively in several ways, resulting in better speed adaptation, less speed variation, better distance keeping, better lane choice, better indicator usage and fewer dangerous lane changes. No differences with regard to subjective workload were shown. The system was perceived as being both useful and satisfactory. However, it was found that the system did not react to other drivers' intention to make a lane change, especially in situations where they were attempting to merge onto the motorway. Further development is needed to improve the system's ability to recognize other vehicles' intention to enter the vehicle's own lane. Also, the phenomenon of the driver "feeling guilty" because of the system's reckless behavior by not allowing other drivers to merge onto the motorway or hindering other cars behind due to lengthy overtaking should be investigated further. [ABSTRACT FROM AUTHOR]

Background The Aspergillus Galactomannan Lateral Flow Assay (LFA) is a rapid test for the diagnosis of invasive aspergillosis (IA) that has been almost exclusively evaluated in patients with hematologic malignancies. An automated digital cube reader that allows for quantification of results has recently been added to the test kits. Methods We performed a retrospective multicenter study on bronchoalveolar lavage fluid (BALF) samples obtained from 296 patients with various underlying diseases (65% without underlying hematological malignancy) who had BALF galactomannan (GM) ordered between 2013 and 2019 at the University of California, San Diego, the Medical University of Graz, Austria, and the Mannheim University Hospital, Germany. Results Cases were classified as proven (n = 2), probable (n = 56), putative (n = 30), possible (n = 45), and no IA (n = 162). The LFA showed an area under the curve (AUC) of 0.865 (95% confidence interval [CI].815–.916) for differentiating proven/probable or putative IA versus no IA, with a sensitivity of 74% and a specificity of 83% at an optical density index cutoff of 1.5. After exclusion of GM as mycological criterion for case classification, diagnostic performance of the LFA was highly similar to GM testing (AUC 0.892 vs 0.893, respectively). LFA performance was consistent across different patient cohorts and centers. Conclusions In this multicenter study the LFA assay from BALF demonstrated good diagnostic performance for IA that was consistent across patient cohorts and locations. The LFA may serve a role as a rapid test that may replace conventional GM testing in settings where GM results are not rapidly available. [ABSTRACT FROM AUTHOR]

Purpose: Previous research on automation and job disruption is only marginally related to the real estate industry and its characteristics. This study investigates the effects of digitization on jobs in German real estate sector, in order to assess the proportion of jobs threatened to be replaced by automation. Since Germany is the largest EU economy insights for the German real estate market allow a first approximation for Europe. Design/methodology/approach: An extensive database of the German Federal Employment Agency containing job definitions and occupation titles is matched with real estate criteria to create a subset with the relevant real estate occupations. This data is combined with a database of the German Institute of Employment Research reflecting to what extent tasks within jobs can be automated by current technical capabilities. Findings: For the 286 identified occupations within the real estate sector a weighted average of 47 percent substitution probability through current technological capabilities is derived for tasks within the examined occupations. Practical implications: This contribution indicates the extent of the structural change the real estate sector has to face due to digitization: One out of two real estate jobs will have to be re-created. Originality/value: This research quantifies the magnitude of the job killer aspect of digitization in the real estate sector. [ABSTRACT FROM AUTHOR]

Various information technology (IT) infrastructures for biobanking, networks of biobanks and biomaterial management are described in the literature. As pre-analytical variables play a major role in the downstream interpretation of clinical as well as research results, their documentation is essential. A description for mainly automated documentation of the complete life-cycle of each biospecimen is lacking so far. Here, the example taken is from the University Medical Center Göttingen (UMG), where the workflow of liquid biomaterials is standardized between the central laboratory and the central biobank. The workflow of liquid biomaterials from sample withdrawal to long-term storage in a biobank was analyzed. Essential data such as time and temperature for processing and freezing can be automatically collected. The proposed solution involves only one major interface between the main IT systems of the laboratory and the biobank. It is key to talk to all the involved stakeholders to ensure a functional and accepted solution. Although IT components differ widely between clinics, the proposed way of documenting the complete life-cycle of each biospecimen can be transferred to other university medical centers. The complete documentation of the life-cycle of each biospecimen ensures a good interpretability of downstream routine as well as research results. [ABSTRACT FROM AUTHOR]

The accuracy of computer numerical control machine tools can be improved by identifying error sources affecting the overall position error and orientation errors. Because of their inevitable nature, the position errors cannot be entirely eliminated from the machinery, but they can be identified, measured and compensated during the manufacturing process of the components by developing and using a mathematical model. In this present work, different mathematical models have been developed for the errors measured by laser interferometer at different nominal positions of X, Y and Z axes both in forward and reverse direction movement as per VDI 3441 Germany standard. Using Akaike information criterion, the best model is selected for each axis and later the best model's coefficients have been optimized by considering both minimizing sum square errors and maximizing R 2 values using teaching–learning-based optimization algorithm. Technique for Order Preference by Similarity to the Ideal Solution method has been adopted to convert the dual objectives into a single objective. An improvement of 1%–71% in R 2 values was reported to prove the effectiveness of the proposed optimization algorithm, Teaching–Learning-Based Optimization algorithm, with the same sum square error values. [ABSTRACT FROM AUTHOR]

After years of hypothetical surveys and simulator studies, automated vehicles (AVs) are now being tested in realistic traffic environments adding validity to knowledge about their acceptance. We present data from a pilot test with participants (n = 125) after experiencing a ride in an electric AV on a large clinic area in Berlin, Germany. As a first contribution, we bridge the gap between missing definitions of key constructs, confusion about their operationalisations, and a rigorous test of their statistical properties and data structure by examining scales on acceptance, trust, perceived safety, intention to use, and—for the first time applied to AVs—the emotions amusement, fear, surprise, and boredom. Tests of reliability and normality were satisfying for almost all constructs (Cronbach’s alphas ≥ .69; six of eight scales normally distributed). The vehicles were accepted (M = 1.22; SD = 0.70; range -2 to 2), trusted (M = 3.29; SD = 0.81; range 1 to 5), and perceived as safe (M = 3.29; SD = 1.03; range 1 to 5). However, factor analyses did not reflect the hypothesised data structure, and validity concerns question the suitability of some constructs for attitude assessment of electric AVs. Our open item for comments added valuable insights in qualitative aspects of user attitudes towards electric AVs regarding driving style, technical features, and (unsettling) audio-visual feedback. We thus argue for broader conceptualisations of key constructs based on interdisciplinary exchange and multi-methodical study designs. [ABSTRACT FROM AUTHOR]

Nowadays, big data analytics are increasingly replacing human decision-making processes in practice fields. In the welfare context, however, they are still being explored only marginally. The following theoretical discussion draws on the example of the MAEWIN project to explore the challenges of using big data when developing decision support systems in the context of social work. The project reveals some similarities with the well-known challenges of big data research (e.g., with regard to data protection, bias, and handling probabilities). However, it also has to face further challenges such as the different knowledge approaches within social work. [ABSTRACT FROM AUTHOR]

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today's advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems. This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS). Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data. Results: Three categories among today's accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots. Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS. Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control. Identification of green spots evaluates safety benefits of state-of-the-art level 0-2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero. [ABSTRACT FROM AUTHOR]

Objective: Left turn across path with traffic from the opposite direction (LTAP/OD) is the second most frequent car-to-car intersection crash type after straight crossing path (SCP) in Germany and the United States. Intersection automated emergency braking (AEB) for passenger cars can address these crashes. This study investigates 2 implementation strategies of intersection AEB addressing LTAP/OD crashes: (1) only the turning car is equipped with an intersection AEB and (2) turning and straight-heading cars are equipped with an intersection AEB. For each strategy, the influence of a safety zone around the vehicles that should not be entered is evaluated in terms of accident avoidance, injury mitigation, and change in velocity (delta-V) of remaining accidents. Results are given as a function of market penetration. Methods: A total of 372 LTAP/OD crashes from the time series precrash matrix (PCM), a subsample of the German In-Depth Accident Study (GIDAS), were resimulated in the PRediction of Accident Evolution by Diversification of Influence factors in COmputer simulation (PRAEDICO) simulation framework. A Kudlich-Slibar rigid-body impact model and an injury risk curve derived from GIDAS were used to predict remaining moderate to fatal (Maximum Abbreviated Injury Scale [MAIS] 2 + F) injuries among car occupants. Results: With a safety zone of 0.2 m, when the turning vehicle only was equipped with an intersection AEB, 59% of the crashes were avoided at a 100% market penetration. With both vehicles equipped the percentage increased to 77%. MAIS 2 + F injured occupants were reduced by 60 and 76%, respectively. Considering both the turning and the straight-heading vehicles, the delta-V decreased strongly with market penetration in remaining left-side impacts but only slightly in remaining frontal and right-side impacts. Eliminating the safety zone substantially decreases effectiveness in all conditions. Conclusions: Implementation strategy and safety zone definition strongly influence the real-life performance of intersection AEB. AEB should be applied not only for the turning vehicle but also for the straight-going vehicle to benefit from the full potential. Situationally appropriate safety zone definitions, in line with human hazard perception, need more attention and are a key to balance true positive and false positive performance. Remaining delta-V does not decrease broadly; hence, there is no evidence that future LTAP/OD crashes will be generally of lower severity. This highlights the need for continuous development of in-crash protection. [ABSTRACT FROM AUTHOR]

Wie der Sozialstaat digital wurde: Die Computerisierung der Rentenversicherung im geteilten Deutschland [How the welfare state went digital: The computerization of pension insurance in divided Germany] By Thomas Kasper. As demonstrated in I The Government Machine i , Jon Agar's classic study of the history of computing in Britain, government computing sought to gain control over state action and in turn fomented a view of government as an information-processing entity. [Extracted from the article]

Introduction: [68Ga]Ga-DO3A-VS-Cys40-Tuna-2 (previously published as [68Ga]Ga-DO3A-VS-Cys40-S01-GCG) has shown high-affinity specific binding to the glucagon receptor (GCGR) in vitro and in vivo in rats and non-human primates in our previous studies, confirming the suitability of the tracer for drug development applications in humans. The manufacturing process of [68Ga]Ga-DO3A-VS-Cys40-Tuna-2 was automated for clinical use to meet the radiation safety and good manufacturing practice (GMP) requirements. Methods: The automated synthesis platform (Modular-Lab PharmTrace, Eckert & Ziegler, Eurotope, Germany), disposable cassettes for 68Ga-labeling, and pharmaceutical-grade 68Ge/68Ga generator (GalliaPharm®) used in the study were purchased from Eckert & Ziegler. The parameters such as time, temperature, precursor concentration, radical scavenger, buffer concentration, and pH, as well as product purification step, were investigated and optimized. Process optimization was conducted with regard to product quality and quantity, as well as process reproducibility. The active pharmaceutical ingredient starting material DO3A-VS-Cys40-Tuna-2 (GMP-grade) was provided by Sanofi Aventis. Results: The reproducible and GMP-compliant automated production of [68Ga]Ga-DO3A-VS-Cys40-Tuna-2 with on-line documentation was developed. The non-decay-corrected radiochemical yield was 45.2 ± 2.5% (n = 3, process validation) at the end of the synthesis with a labeling synthesis duration of 38 min and a quality controlincluding release procedure of 20 min. The radiochemical purity of the product was 98.9 ± 0.6% (n = 17) with the total amount of the peptide in the preparation of 48 ± 2 µg (n = 3, process validation). Radionuclidic purity, sterility, endotoxin content, residual solvent content, and sterile filter integrity tests met the acceptance criteria. The product was stable at ambient temperature for at least 2 h. Conclusion: The fully automated GMP-compliant manufacturing process was developed and thoroughly validated. The resulting [68Ga]Ga-DO3A-VS-Cys40-Tuna-2 was used in a clinical study for accurate quantification of GCGR occupancy by a dual anti-diabetic drug in vivo in humans. [ABSTRACT FROM AUTHOR]