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Relational Keyword Search (R-KWS) provides an intuitive way to query relational data without requiring SQL, or knowledge of the underlying schema. In this article we describe a comprehensive framework for R-KWS covering snapshot queries on conventional tables and continuous queries on relational streams. Our contributions are summarized as follows: (i) We provide formal semantics, addressing the temporal validity and order of results, spanning uniformly over tables and streams; (ii) we investigate two general methodologies for query processing, graph based and operator based, that resolve several problems of previous approaches; and (iii) we develop a range of algorithms and optimizations covering both methodologies. We demonstrate the effectiveness of R-KWS, as well as the significant performance benefits of the proposed techniques, through extensive experiments with static and streaming datasets. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages; H.3.3. [Information Storage and Retrieval]: Information Search and Retrieval General Terms: Algorithms Additional Key Words and Phrases: Search, relational databases, data streams, query processing, data graph

Computing temporal aggregates is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.) Due to the large volume of such data, performance improvements for temporal aggregate queries are critical. Previous approaches have aggregate predicates that involve only the time dimension. In this article we examine techniques to compute temporal aggregates that include key-range predicates as well (range-temporal aggregates). In particular we concentrate on the SUM aggregate, while COUNT is a special case. To handle arbitrary key ranges, previous methods would need to keep a separate index for every possible key range. We propose an approach based on a new index structure called the Multiversion SB-Tree, which incorporates features from both the SB-Tree and the Multiversion B+-tree, to handle arbitrary key-range temporal aggregate queries. We analyze the performance of our approach and present experimental results that show its efficiency. Furthermore, we address a novel and practical variation called functional range-temporal aggregates. Here, the value of any record is a function over time. The meaning of aggregates is altered such that the contribution of a record to the aggregate result is proportional to the size of the intersection between the record's time interval and the query time interval. Both analytical and experimental results show the efficiency of our result. Categories and Subject Descriptors: H.4.0 [Information Systems Applications]: General General Terms: Algorithms Additional Key Words and Phrases: Temporal aggregates, indexing, range predicates, functional aggregates

Virtually everybody would agree that life satisfaction is of immense importance in everyday life. Thus, it is not surprising that a considerable amount of research using many different methodological approaches has investigated what the best predictors of life satisfaction are. In the present study, we have focused on several key potential influences on life satisfaction including bottom-up and top-down models, cross-cultural effects, and demographic variables. In four independent (large scale) surveys with sample sizes ranging from N = 488 to 40,297, we examined the associations between life satisfaction and various related variables. Our findings demonstrate that prediction of overall life satisfaction works best when including information about specific life satisfaction variables. From this perspective, satisfaction with leisure showed the highest impact on overall life satisfaction in our European samples. Personality was also robustly associated with life satisfaction, but only when life satisfaction variables were not included in the regression model. These findings could be replicated in all four independent samples, but it was also demonstrated that the relevance of life satisfaction variables changed under the influence of cross-cultural effects. [ABSTRACT FROM AUTHOR]

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A recent study has implicated the nucleus accumbens of the ventral striatum in explaining why online-users spend time on the social network platform Facebook. Here, higher activity of the nucleus accumbens was associated with gaining reputation on social media. In the present study, we touched a related research field. We recorded the actual Facebook usage of N = 62 participants on their smartphones over the course of five weeks and correlated summary measures of Facebook use with gray matter volume of the nucleus accumbens. It appeared, that in particular higher daily frequency of checking Facebook on the smartphone was robustly linked with smaller gray matter volumes of the nucleus accumbens. The present study gives additional support for the rewarding aspects of Facebook usage. Moreover, it shows the feasibility to include real life behavior variables in human neuroscientific research. [ABSTRACT FROM AUTHOR]

Psychologists and psychiatrists commonly rely on self-reports or interviews to diagnose or treat behavioral addictions. The present study introduces a novel source of data: recordings of the actual problem behavior under investigation. A total of N = 58 participants were asked to fill in a questionnaire measuring problematic mobile phone behavior featuring several questions on weekly phone usage. After filling in the questionnaire, all participants received an application to be installed on their smartphones, which recorded their phone usage for five weeks. The analyses revealed that weekly phone usage in hours was overestimated; in contrast, numbers of call and text message related variables were underestimated. Importantly, several associations between actual usage and being addicted to mobile phones could be derived exclusively from the recorded behavior, but not from self-report variables. The study demonstrates the potential benefit to include methods of psychoinformatics in the diagnosis and treatment of problematic mobile phone use. [ABSTRACT FROM AUTHOR]

Background: Mounting evidence shows that smartphone usage heavily disrupts our work life and social activities. Moreover, it is possible that overuse could resemble addictive tendencies. A key contributing factor to smartphone overuse seems to be usage of the messaging application WhatsApp. Although WhatsApp is one of the most commonly used communication applications on smartphones, research in this area is scarce. Given the huge societal debate on the impact of smartphone usage on our daily lives, the present study undertook a large-scale investigation in order to provide numbers on smartphone usage generally--and use of WhatsApp in particular, with the aim of providing a basis for a scientific debate. Methods: In a large sample of N = 2,418 users, we recorded WhatsApp behaviour over a 4 week period. Results: Our data show that use of WhatsApp accounted for 19.83% (= 32.11 min) of all smartphone behaviour (compare: Facebook only 9.38% = 15.19 min). The mean of general daily smartphone usage was 161.95 min. Females used WhatsApp for significantly longer periods of time than males and younger age was associated with longer duration of WhatsApp use. While the personality trait Extraversion was positively associated with daily WhatsApp use, Conscientiousness showed an inverse correlation with the length of daily WhatsApp use. Conclusions: The numbers on smartphone usage in the present study show that the smartphone dominates our daily life. In particular WhatsApp is a driving force, here. Given the length of daily smartphone and WhatsApp usage, more studies need to be conducted to better understand smartphone usage. [ABSTRACT FROM AUTHOR]

Computing temporal aggregates is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.) Due to the large volume of such data, performance improvements for temporal aggregate queries are critical. Previous approaches have aggregate predicates that involve only the time dimension. In this article we examine techniques to compute temporal aggregates that include key-range predicates as well (range-temporal aggregates). In particular we concentrate on the SUM aggregate, while COUNT is a special case. To handle arbitrary key ranges, previous methods would need to keep a separate index for every possible key range. We propose an approach based on a new index structure called the Multiversion SB-Tree, which incorporates features from both the SB-Tree and the Multiversion B+-tree, to handle arbitrary key-range temporal aggregate queries. We analyze the performance of our approach and present experimental results that show its efficiency. Furthermore, we address a novel and practical variation called functional range-temporal aggregates. Here, the value of any record is a function over time. The meaning of aggregates is altered such that the contribution of a record to the aggregate result is proportional to the size of the intersection between the record's time interval and the query time interval. Both analytical and experimental results show the efficiency of our result. [ABSTRACT FROM AUTHOR]

Smartphone technology has the potential to facilitate dietary assessment in epidemiological studies. Measurement error might be reduced by real time recording being more feasible with mobile methods. Our aim was to develop NutriDiary, a smartphone app for conducting three-day weighed dietary records. It provides a digital version of the established pen-and-paper method in the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, an open cohort study from infancy to adulthood. NutriDiary was developed as a text-based app including brand specific recording of food products. Usability of the beta version of NutriDiary was evaluated in the DONALD study. Participants or their parents were offered to test the app for the annual dietary record and were asked to fill in an app-integrated evaluation questionnaire. Usability was assessed by the System Usability Scale (SUS) and in-app behavior recordings. In the beta version of NutriDiary, a consumed food item is selected using a free-text search from the integrated in-house database LEBTAB. To ease the process of recording, NutriDiary offers some usability features such as a recipe editor, an integrated help mode and a photo function for collecting information on branded food products. In total, 32 mostly female participants (69%) used the app with 21 subjects recording their own dietary intake and 11 subjects conducting a record for their child. However, a relatively large proportion of DONALD participants also refused using the app because they preferred the traditional pen-and-paper method as being easier. Among participants of the feasibility study, subjective usability of NutriDiary was "good" but considerable differences in individual ratings were observed (median SUS = 80, IQR = 23.75, minimum = 45). Although 38% of participants reported technical issues, 88% stated they would use the app again. Technical problems included issues related to setting the time, editing of entered food items and the photo function. In-app behavior recordings showed that the help mode and recipe function were well-used (72% and 63%, respectively). Feedback from the study staff revealed that the post-processing of the dietary data obtained with NutriDiary was still time-consuming. Overall, the beta version of the NutriDiary app was well-received by most participants. Some aspects for improvement such as a barcode scanning function and extension of the database were identified. Moreover, NutriDiary will be further optimized by implementing an automated recipe simulation function. [ABSTRACT FROM AUTHOR]

The present paper provides insight into an emerging research discipline called Psychoinformatics. In the context of Psychoinformatics, we emphasize the cooperation between the disciplines of psychology and computer science in handling large data sets derived from heavily used devices, such as smartphones or online social network sites, in order to shed light on a large number of psychological traits, including personality and mood. New challenges await psychologists in light of the resulting “Big Data” sets, because classic psychological methods will only in part be able to analyze this data derived from ubiquitous mobile devices, as well as other everyday technologies. As a consequence, psychologists must enrich their scientific methods through the inclusion of methods from informatics. The paper provides a brief review of one area of this research field, dealing mainly with social networks and smartphones. Moreover, we highlight how data derived from Psychoinformatics can be combined in a meaningful way with data from human neuroscience. We close the paper with some observations of areas for future research and problems that require consideration within this new discipline. [ABSTRACT FROM AUTHOR]

Introduction: When consulting a specialist in orthopaedics and trauma surgery, personal assessment and manual clinical examination by the doctor on site are essential. Nevertheless, implementation of video consultation hours has been made legally easier in Germany. The present pilot study examines the possibility of video-based assessment of the urgency of treatment in outpatient orthopaedic and trauma patients., Materials and Methods: Within an ex ante study design, 40 patients with an orthopaedic clinical picture for trauma surgery with elective, urgent or emergency indication were selected from consultation hours. A short questionnaire was filled in based on the information provided and a medical colleague simulated a movement sequence based on the patient information. After modification to the "red flags" and "yellow flags" established in spinal orthopaedics, nine short questions were recorded, which inquire about the urgency of a medical consultation. The video-based movement sequence is based on a 60 s long instruction video in which motor tests and movement sequences are demonstrated: Cervical spine movement in all levels, elevation of the upper extremity, test of the finger-floor distance when "bending forward over-bending", possibility of crouching from standing and getting up again, standing on heels and toes., Results: In 91.1% (n = 328) of the cases, the diagnosis was associated with the same joint or the same pathological entity. In 37.5% (n = 135) of the cases an emergency indication was seen, in 10.8% (n = 39) of the cases an urgent indication and in 51.6% (n = 186) of the cases it was seen to offer an elective indication. 12.5% (n = 45) of the cases were evaluated as "false positives" with regard to an emergency or urgent presentation. This means that the test persons were classified as "emergency" or "urgent", although there was no preventable dangerous course or medical emergency. 18 cases (5%) were evaluated as "false negative"., Discussion: The screening questionnaire presented and the short video assessment are technically feasible and practicable method for the initial evaluation in video-based online medical consultation. In addition, the questionnaire presented in combination with the short video assessment was suitable as an instrument for assessing the urgency of the consultation and selecting preventable dangerous processes and acute emergencies., Conclusion: The questionnaire, in combination with the short video assessment, is a suitable method for the social distancing requirements during limited accessibility of the medical system. Nevertheless, a false negative rate of 5% is too high to implement the questionnaire presented into daily clinics without further optimisation., Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

Virtually everybody would agree that life satisfaction is of immense importance in everyday life. Thus, it is not surprising that a considerable amount of research using many different methodological approaches has investigated what the best predictors of life satisfaction are. In the present study, we have focused on several key potential influences on life satisfaction including bottom-up and top-down models, cross-cultural effects, and demographic variables. In four independent (large scale) surveys with sample sizes ranging from N = 488 to 40,297, we examined the associations between life satisfaction and various related variables. Our findings demonstrate that prediction of overall life satisfaction works best when including information about specific life satisfaction variables. From this perspective, satisfaction with leisure showed the highest impact on overall life satisfaction in our European samples. Personality was also robustly associated with life satisfaction, but only when life satisfaction variables were not included in the regression model. These findings could be replicated in all four independent samples, but it was also demonstrated that the relevance of life satisfaction variables changed under the influence of cross-cultural effects., Competing Interests: The authors declare no conflict of interest.