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Objectives To assess the diagnostic performances of chest CT for triage of patients in multiple emergency departments during COVID-19 epidemic, in comparison with reverse transcription polymerase chain reaction (RT-PCR) test. Method From March 3 to April 4, 2020, 694 consecutive patients from three emergency departments of a large university hospital, for which a hospitalization was planned whatever the reasons, i.e., COVID- or non-COVID-related, underwent a chest CT and one or several RT-PCR tests. Chest CTs were rated as “Surely COVID+,” “Possible COVID+,” or “COVID−” by experienced radiologists. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using the final RT-PCR test as standard of reference. The delays for CT reports and RT-PCR results were recorded and compared. Results Among the 694 patients, 287 were positive on the final RT-PCR exam. Concerning the 694 chest CT, 308 were rated as “Surely COVID+”, 34 as “Possible COVID+,” and 352 as “COVID−.” When considering only the “Surely COVID+” CT as positive, accuracy, sensitivity, specificity, PPV, and NPV reached 88.9%, 90.2%, 88%, 84.1%, and 92.7%, respectively, with respect to final RT-PCR test. The mean delay for CT reports was three times shorter than for RT-PCR results (187 ± 148 min versus 573 ± 327 min, p  < 0.0001). Conclusion During COVID-19 epidemic phase, chest CT is a rapid and most probably an adequately reliable tool to refer patients requiring hospitalization to the COVID+ or COVID− hospital units, when response times for virological tests are too long. Key Points • In a large university hospital in Lyon , France , the accuracy , sensitivity , specificity , PPV , and NPV of chest CT for COVID-19 reached 88.9 %, 90.2 %, 88 %, 84.1 %, and 92.7 %, respectively , using RT-PCR as standard of reference. • The mean delay for CT reports was three times shorter than for RT-PCR results ( 187  ±  148 min versus 573  ±  327 min , p  <  0.0001 ). • Due to high accuracy of chest CT for COVID-19 and shorter time for CT reports than RT-PCR results , chest CT can be used to orient patients suspected to be positive towards the COVID + unit to decrease congestion in the emergency departments.

Until recently, robotic surgery has been associated only with the da Vinci robotic system. A novel Senhance ® robotic system (TransEnterix Surgical Inc., Morrisville, NC, USA) was introduced almost 5 years ago. Published reports on experience using this robotic platform are very limited. We present a prospective analysis of the first 100 robotic surgeries in abdominal surgery, gynecology, and urology in Klaipeda University Hospital, Klaipeda, Lithuania. Out of 100 operated patients during the mentioned period, 49 were female and 51 men, age range 27–79 years, on an average 55 years. 39 underwent robotic abdominal surgical procedures, 31—urological, and 30 gynecological surgeries. Duration of surgery varied from 30 min to 6 h and 5 min, on an average 2 h 25 min. Almost half 49 (49%) were operated on for malignant diseases: prostate cancer—27, renal cell carcinoma—1, endometrial cancer—7, ovarian cancer—1, colorectal cancer—13 (7 colon and 6 rectum). In-hospital stay was on an average 4 days, range 1–15 days. There were 3 (3%) conversions: two to laparoscopy (both undergoing robotic radical prostatectomy) and one to open (undergoing total hysterectomy). 6 (6%) complications occurred during 30 postoperative days, 2 demanding surgery. According to the Clavien–Dido classification, they were grade II in 3, grade III a in 1 and grade III b in 2 cases. There was no mortality in this patient population. Our experience with different types of robotic surgeries allows us to state that the Senhance ® robotic system is feasible and safe in general surgery, gynecology, and urology, and wider implementation of this system worldwide is simply a question of time.

To perform their daily tasks, developers intensively make use of existing resources by consulting open source software (OSS) repositories. Such platforms contain rich data sources, e.g., code snippets, documentations, and user discussions, that can be useful for supporting development activities. Over the last decades, several techniques and tools have been promoted to provide developers with innovative features, aiming to bring in improvements in terms of development effort, cost savings, and productivity. In the context of the EU H2020 CROSSMINER project, a set of recommendation systems has been conceived to assist software programmers in different phases of the development process. The systems provide developers with various artifacts, such as third-party libraries, documentation about how to use the APIs being adopted, or relevant API function calls. To develop such recommendations, various technical choices have been made to overcome issues related to several aspects including the lack of baselines, limited data availability, decisions about the performance measures, and evaluation approaches. This paper is an experience report to present the knowledge pertinent to the set of recommendation systems developed through the CROSSMINER project. We explain in detail the challenges we had to deal with, together with the related lessons learned when developing and evaluating these systems. Our aim is to provide the research community with concrete takeaway messages that are expected to be useful for those who want to develop or customize their own recommendation systems. The reported experiences can facilitate interesting discussions and research work, which in the end contribute to the advancement of recommendation systems applied to solve different issues in Software Engineering.

Requirements engineering (RE) being a foundation of software development has gained a great recognition in the recent era of prevailing software industry. A number of journals and conferences have published a great amount of RE research in terms of various tools, techniques, methods, and frameworks, with a variety of processes applicable in different software development domains. The plethora of empirical RE research needs to be synthesized to identify trends and future research directions. To represent a state-of-the-art of requirements engineering, along with various trends and opportunities of empirical RE research, we conducted a systematic mapping study to synthesize the empirical work done in RE. We used four major databases IEEE, ScienceDirect, SpringerLink and ACM and Identified 270 primary studies till the year 2012. An analysis of the data extracted from primary studies shows that the empirical research work in RE is on the increase since the year 2000. The requirements elicitation with 22 % of the total studies, requirements analysis with 19 % and RE process with 17 % are the major focus areas of empirical RE research. Non-functional requirements were found to be the most researched emerging area. The empirical work in the sub-area of requirements validation and verification is little and has a decreasing trend. The majority of the studies (50 %) used a case study research method followed by experiments (28 %), whereas the experience reports are few (6 %). A common trend in almost all RE sub-areas is about proposing new interventions. The leading intervention types are guidelines, techniques and processes. The interest in RE empirical research is on the rise as whole. However, requirements validation and verification area, despite its recognized importance, lacks empirical research at present. Furthermore, requirements evolution and privacy requirements also have little empirical research. These RE sub-areas need the attention of researchers for more empirical research. At present, the focus of empirical RE research is more about proposing new interventions. In future, there is a need to replicate existing studies as well to evaluate the RE interventions in more real contexts and scenarios. The practitioners’ involvement in RE empirical research needs to be increased so that they share their experiences of using different RE interventions and also inform us about the current requirements-related challenges and issues that they face in their work.

Die Badische Landesbibliothek hat im Rahmen eines Pilotprojekts die Named Entity Recognition (NER) in den Digitalen Sammlungen für ausgewählte Zeitungsbestände realisiert. Grundlage ist eine technische Neuentwicklung in Visual Library, die auf Google Cloud Natural Language basiert. Diese ermöglicht die Erkennung von Normdaten und deren Verknüpfung in den mittels OCR generierten Volltexten. Diese Datenanreicherung schafft neue Rechercheeinstiege für die Nutzerinnen und Nutzer und ermöglicht die Anwendung neuer Recherchemethoden für die Wissenschaft.

With the widespread development of automated driving systems (ADS), it is imperative that standardized testing methodologies be developed to assure safety and functionality. Scenario testing evaluates the behavior of an ADS-equipped subject vehicle (SV) in predefined driving scenarios. This paper compares four modes of performing such tests: closed-course testing with real actors, closed-course testing with surrogate actors, simulation testing, and closed-course testing with mixed reality. In a collaboration between the Waterloo Intelligent Systems Engineering (WISE) Lab and AAA, six automated driving scenario tests were executed on a closed course, in simulation, and in mixed reality. These tests involved the University of Waterloo’s automated vehicle, dubbed the “UW Moose”, as the SV, as well as pedestrians, other vehicles, and road debris. Drawing on both data and the experience gained from executing these test scenarios, the paper reports on the advantages and disadvantages of the four scenario testing modes, and compares them using eight criteria. It also identifies several possible implementations of mixed-reality scenario testing, including different strategies for data mixing. The paper closes with twelve recommendations for choosing among the four modes.

The paper describes two computer games which we developed to teach abstract physics concepts: A Slower Speed of Light, designed to teach Special Relativity, and Kirchhoff's Revenge, designed to teach circuit laws. We report on experiences and research results using these games in physics lessons at college and high school level, user feedback, as well as information informally gathered from \"Let's Play\" videos on YouTube. Finally, we describe plans for future developments.

In the ever expanding universe of formal methods, several tools exist that can be exploited to validate early system designs, and that are applicable to problems of the railway domain. In this paper, we present an experience report in formal modelling and verification using seven different formal environments, namely UMC, Promela/SPIN, NuSMV, mCRL2, CPN Tools, FDR4 and CADP. In particular, we model and verify an algorithm that addresses a typical railway problem, namely deadlock avoidance in train scheduling. The algorithm is designed according to a prototypical architecture, the so-called blackboard pattern, in which a set of global data are atomically updated by a set of concurrent guarded agents. Our experience, limited to the specific problem, shows that the design of the algorithm can be translated into the different formalisms with acceptable effort, while deep proficiency with the tools is required to optimise the performance. The current paper establishes the preliminary foundations for the concept of formal methods diversity in the development of railway systems. The concept is based on the idea that if different non-certified formal environments are used to verify the same design, this increases the confidence on the verification results. Furthermore, by checking that the number of states generated during the verification process is the same for each framework, the designer can have an initial indication of the equivalence of the diverse models. The industrial application of this promising concept requires further research, and appropriate guidelines shall be established to identify the proper formal environments to use for a specific railway problem, and to define an industrial process in which formal methods diversity can be exploited at its full benefits. The paper presents the different models developed, compares the tools employed in terms of language features and performance, and discusses the industrial implications of the concept of formal methods diversity in the railway domain.

Software product-line engineering is arguably one of the most successful methods for establishing large portfolios of software variants in an application domain. However, despite the benefits, establishing a product line requires substantial upfront investments into a software platform with a proper product-line architecture, into new software-engineering processes (domain engineering and application engineering), into business strategies with commercially successful product-line visions and financial planning, as well as into re-organization of development teams. Moreover, establishing a full-fledged product line is not always possible or desired, and thus organizations often adopt product-line engineering only to an extent that deemed necessary or was possible. However, understanding the current state of adoption, namely, the maturity or performance of product-line engineering in an organization, is challenging, while being crucial to steer investments. To this end, several measurement methods have been proposed in the literature, with the most prominent one being the Family Evaluation Framework (FEF), introduced almost two decades ago. Unfortunately, applying it is not straightforward, and the benefits of using it have not been assessed so far. We present an experience report of applying the FEF to nine medium- to large-scale product lines in the avionics domain. We discuss how we tailored and executed the FEF, together with the relevant adaptations and extensions we needed to perform. Specifically, we elicited the data for the FEF assessment with 27 interviews over a period of 11 months. We discuss experiences and assess the benefits of using the FEF, aiming at helping other organizations assessing their practices for engineering their portfolios of software variants.

The benefits and outcomes of robotic surgery are well established in the literature across multiple specialties. The increasing need for and dissemination of this technology associated with high costs, demand adequate planning during its implementation. Therefore, after years of training several robotic surgeons and establishing multiple robotic programs worldwide, the purpose of this article is to focus on the necessary elements in the initial phase of establishing a robotics program. We summarized in our article crucial factors when implementing a robotic program. Therefore, we explained in detail the critical aspects of the program design, implementation, marketing, research and outcomes, and ultimately improving efficiency. The creation of a robotics planning committee composed of several hospital individuals contributes in different lines of work such as cost evaluation, staff training, and OR modifications. A multidisciplinary approach and a robotic lead surgeon are also recommended to guarantee surgical volume and satisfactory outcomes. Furthermore, market analysis should evaluate the competition with other centres and potential surgical candidates in that area. Data collection should also be considered a vital element of the program organization, which assures quality control and helps to diagnose any program deficiency. We believe that the robotic program should be individualized according to the economy and reality of each centre. The success and duration of a robotic surgery program depend on long-term results. Therefore, careful planning with a robotic committee defining the types of procedures to be performed and appropriate multidisciplinary training to avoid surgery cancelations are crucial factors in establishing a successful program.