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Computational thinking (CT) is an important 21st-century skill. This paper aims at investigating predictors of CT self-efficacy among high-school students. The hypothesized predictors are grouped into three areas: (1) student characteristics, (2) home environment, and (3) learning opportunities. CT self-efficacy is measured with the Computational Thinking Scales (CTS) that comprises five dimensions: creativity, algorithmic thinking, cooperativity, critical thinking, and problem solving. N = 202 high-school students act as the sample, linear regression as the analysis method. The best prediction is possible for algorithmic thinking (R[superscript 2] = 0.511). For cooperativity, the explanatory power of our model it is weak (R[superscript 2] = 0.146). Across all five CTS dimensions, CT self-concept is the best predictor for CT self-efficacy. [For the full proceedings, see ED636095.]

Microwave radiometers are widely used for the retrieval of Liquid Water Path (LWP) and Integrated Water Vapor (IWV) in the context of cloud and precipitation studies. This paper presents a new site-independent retrieval algorithm for LWP and IWV, relying on a single-frequency 89-GHz ground-based radiometer. A statistical approach is used, based on a neural network, which is trained and tested on a synthetic data set constructed from radiosonde profiles worldwide. In addition to 89-GHz brightness temperature, the input features include surface measurements of temperature, pressure and humidity, as well as geographical information and, when available, estimates of IWV and LWP from reanalysis data. An analysis of the algorithm is presented to assess its accuracy, the impact of the various input features, as well as its sensitivity to radiometer calibration and its stability across geographical locations. The new method is then implemented on real data that were collected during a field deployment in Switzerland and during the ICE-POP 2018 campaign in South Korea. The new algorithm is shown to be quite robust, especially in mid-latitude environments with a moderately moist climate, although its accuracy is inevitably lower than that obtained with state-of-the-art multi-channel radiometers. [ABSTRACT FROM AUTHOR]

In the digital age, the use of advanced technology is becoming a new paradigm in police work, criminal justice, and the penal system. Algorithms promise to predict delinquent behaviour, identify potentially dangerous persons, and support crime investigation. Algorithm-based applications are often deployed in this context, laying the groundwork for a 'smart criminal justice'. In this qualitative study based on 32 interviews with criminal justice and police officials, we explore the reasons why and extent to which such a smart criminal justice system has already been established in Switzerland, and the benefits perceived by users. Drawing upon this research, we address the spread, application, technical background, institutional implementation, and psychological aspects of the use of algorithms in the criminal justice system. We find that the Swiss criminal justice system is already significantly shaped by algorithms, a change motivated by political expectations and demands for efficiency. Until now, algorithms have only been used at a low level of automation and technical complexity and the levels of benefit perceived vary. This study also identifies the need for critical evaluation and research-based optimization of the implementation of advanced technology. Societal implications, as well as the legal foundations of the use of algorithms, are often insufficiently taken into account. By discussing the main challenges to and issues with algorithm use in this field, this work lays the foundation for further research and debate regarding how to guarantee that 'smart' criminal justice is actually carried out smartly. [ABSTRACT FROM AUTHOR]

Many slopes in the Alps are prone to rockfall and forests play a vital role in protecting objects such as (rail) roads and infrastructure against rockfall. Decision support tools are required to assess rockfall processes and to quantify the rockfall protection effect of forest stands. This paper presents results of an iterative sequence of tests and improvements of a coupled rockfall and forest dynamics model with focus on the rockfall module. As evaluation data a real-size rockfall experiment in the French Alps and two 2-D rockfall trajectories from Austria and Switzerland were used. Modification of the rebound algorithm and the inclusion of an algorithm accounting for the sudden halt of falling rocks due to surface roughness greatly improved the correspondence between simulated and observed key rockfall variables like run-out distances, rebound heights and jump lengths for the real-size rockfall experiment. Moreover, the observed jump lengths and run-out distances of the 2-D trajectories were well within the stochastic range of variation yielded by the simulations. Based on evaluation results it is concluded that the rockfall model can be employed to assess the protective effect of forest vegetation. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the availability and use of dental and maxillofacial emergency algorithms in Swiss hospitals. A survey was performed among physicians at Swiss emergency departments (ED) and participants of the "36th Annual Meeting of the Society for Oral and Cranio-Maxillofacial Surgery". Eighty-nine EDs in Switzerland were questioned about the availability and use of electronic algorithms in their hospitals. Eighty-one (91%) participated in the study. In 75 (93%) of the EDs, electronic algorithms are used, mainly "medStandards". Six have no available algorithms. Fifty-two (64%) use algorithms daily. Eight (10%) Swiss EDs have maxillofacial and dental algorithms, and 73 (90%) have no access to or do not know about them. For dental algorithms, 28 (38%) of the respondents would like to have access, and 16 (22%) do not desire access. For maxillofacial algorithms, 23 (32%) want to have access and 21 (29%) do not want it. Most (74%) of the participating maxillofacial surgeons did not know about the existence of ED algorithms regarding their specialty. Our study shows that the existence of specific algorithms is often not known. Furthermore, there is a demand for dental and maxillofacial algorithms in Swiss EDs. [ABSTRACT FROM AUTHOR]

We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the causes leading to a first revision of primary total knee arthroplasty (TKA) in a specialized knee centre and compare the results with previously published data. Prospectively collected data of a consecutive number of 195 patients after primary TKA and who underwent first revision surgery after completing the diagnostic algorithm for persistent knee pain were included. Data was prospectively collected from a specialized knee centre in which the patients presented between 2015 and 2020 and retrospectively analysed. Indications for revision surgery were categorized using all available information from patients' records. Patients were divided into early (up to two years) and late revision (more than two years). Overall mean time from index to revision surgery was 3.6 years. 49% of knee revisions occurred in the first two years, 51% after two years. 86% of the patients were referred to the knee centre from other surgeons. The most frequent reason for revision was instability, followed by patellofemoral problems, extensor mechanism insufficiency and malalignment. The most frequently performed revision was complete removal and re-implantation of a semi constrained implant design (52.5%) followed by revision using a full constrained implant design (16%). Secondary patella-resurfacing as part of complete revision was carried out in 71.5% of the cases. The majority of the patients showed concurrent reasons for TKA failure with significant correlations amongst another. Furthermore, correlations were identified between indications for revision surgery and revision implant designs. In a specialized knee centre the most common indications for the first TKA revision were instability and patellofemoral and/or extensor mechanism insufficiency followed by malalignment. In most patients there was not only one failure mode, but a combination of many. It is important to establish a standardized diagnostic algorithm to facilitate comprehensive and efficient diagnostics and the optimal treatment. [ABSTRACT FROM AUTHOR]

Missing rainfall data are a major limitation for distributed hydrological modeling and climate studies. Practitioners need reliable approaches that can be employed on a daily basis, often with too limited data in space to feed complex predictive models. In this study we compare different automatic approaches for missing data imputation, including geostatistical interpolation and pattern-based estimation algorithms. We introduce two pattern-based approaches based on the analysis of historical data patterns: (i) an iterative version of K-nearest neighbor (IKNN) and (ii) a new algorithm called vector sampling (VS) that combines concepts of multiple-point statistics and resampling. Both algorithms can draw estimations from variably incomplete data patterns, allowing the target dataset to be at the same time the training dataset. Tested on five case studies from Denmark, Australia, and Switzerland, the algorithms show a different performance that seems to be related to the terrain type: on flat terrains with spatially homogeneous rain events, geostatistical interpolation tends to minimize the average error, while in mountainous regions with nonstationary rainfall statistics, data mining can recover better the rainfall patterns. The VS algorithm, requiringminimal parameterization, turns out to be a convenient option for routine application on complex and poorly gauged terrains. [ABSTRACT FROM AUTHOR]

Objective: To develop an automated, reproducible method for delineating hospital service areas (HSAs).Data Sources/setting: Discharge data from all Swiss acute care hospitals for the years 2013 to 2016.Study Design: We derived HSAs and hospital referral regions for Switzerland using a newly developed flow-based, automated, objective, and reproducible method using all discharge data. We compared our method to the classical, partially subjective approach used to delineate the Swiss Health Care Atlas by delineating four sets of intervention-specific HSAs.Principal Findings: Based on 4 105 885 discharges, the fully automated method delineated 63 HSAs. Comparison with existing HSAs reveals good overlap and comparable measures of health utilization between the methods and shows that in the Swiss setting, our method outperforms a cluster-based approach to defining HSAs. While the classical method potentially takes an entire day to delineate the regions, our method took approximately 10 minutes.Conclusions: Hospital service areas are used to analyze differences in use of health care that may indicate underuse and overuse. Our new, fully automated, objective, and reproducible method provides a useful tool for hospital services researchers that will enable them to delineate and update patient-flow-based HSAs. [ABSTRACT FROM AUTHOR]

Although the level of digitalization and automation steadily increases in radiology, billing coding for magnetic resonance imaging (MRI) exams in the radiology department is still based on manual input from the technologist. After the exam completion, the technologist enters the corresponding exam codes that are associated with billing codes in the radiology information system. Moreover, additional billing codes are added or removed, depending on the performed procedure. This workflow is time-consuming and we showed that billing codes reported by the technologists contain errors. The coding workflow can benefit from an automated system, and thus a prediction model for automated assignment of billing codes for MRI exams based on MRI log data is developed in this work. To the best of our knowledge, it is the first attempt to focus on the prediction of billing codes from modality log data. MRI log data provide a variety of information, including the set of executed MR sequences, MR scanner table movements, and given a contrast medium. MR sequence names are standardized using a heuristic approach and incorporated into the features for the prediction. The prediction model is trained on 9754 MRI exams and tested on 1 month of log data (423 MRI exams) from two MRI scanners of the radiology site for the Swiss medical tariffication system Tarmed. The developed model, an ensemble of classifier chains with multilayer perceptron as a base classifier, predicts medical billing codes for MRI exams with a micro-averaged F1-score of 97.8% (recall 98.1%, precision 97.5%). Manual coding reaches a micro-averaged F1-score of 98.1% (recall 97.4%, precision 98.8%). Thus, the performance of automated coding is close to human performance. Integrated into the clinical environment, this work has the potential to free the technologist from a non-value adding an administrative task, therefore enhance the MRI workflow, and prevent coding errors. [ABSTRACT FROM AUTHOR]

Top tagging is a recent approach to identifying boosted hadronic top quarks. It avoids reconstructing individual top decay products and instead uses a jet algorithm to reconstruct the entire top decay. Quite generally, geometrically large jets including heavy particles (fat jets) can be analyzed on the level of their subjet constituents. LHC data will soon allow us to establish this new analysis method. We discuss different tagging algorithms, their critical QCD aspects, and currently available experimental results. For the development of taggers and their different applications this review should provide a firm theoretical and algorithmic background. [ABSTRACT FROM AUTHOR]

Background: Most terminally ill cancer patients prefer to die at home, but a majority die in institutional settings. Research questions about this discrepancy have not been fully answered. This study applies artificial intelligence and machine learning techniques to explore the complex network of factors and the cause-effect relationships affecting the place of death, with the ultimate aim of developing policies favouring home-based end-of-life care. Methods: A data mining algorithm and a causal probabilistic model for data analysis were developed with information derived from expert knowledge that was merged with data from 116 deceased cancer patients in southern Switzerland. This data set was obtained via a retrospective clinical chart review. Results: Dependencies of disease and treatment-related decisions demonstrate an influence on the place of death of 13%. Anticancer treatment in advanced disease prevents or delays communication about the end of life between oncologists, patients and families. Unknown preferences for the place of death represent a great barrier to a home death. A further barrier is the limited availability of family caregivers for terminal home care. The family's preference for the last place of care has a high impact on the place of death of 51%, while the influence of the patient's preference is low, at 14%. Approximately one-third of family systems can be empowered by health care professionals to provide home care through open end-of-life communication and good symptom management. Such intervention has an influence on the place of death of 17%. If families express a convincing preference for home care, the involvement of a specialist palliative home care service can increase the probability of home deaths by 24%. Conclusion: Concerning death at home, open communication about death and dying is essential. Furthermore, for the patient preference for home care to be respected, the family's decision for the last place of care seems to be key. The early initiation of family-centred palliative care and the provision of specialist palliative home care for patients who wish to die at home are suggested. [ABSTRACT FROM AUTHOR]