Car use in the sprawled urban region of Noord‐Brabant is above the Dutch average. Does this reflect car dependency due to the lack of competitive alternative modes? Or are there other factors at play, such as differences in preferences? This article aims to determine the nature of car use in the region and explore to what extent this reflects car dependency. The data, comprising 3,244 respondents was derived from two online questionnaires among employees from the High‐Tech Campus (2018) and the TU/e‐campus (2019) in Eindhoven. Travel times to work by car, public transport, cycling, and walking were calculated based on the respondents’ residential location. Indicators for car dependency were developed using thresholds for maximum commuting times by bicycle and maximum travel time ratios between public transport and car. Based on these thresholds, approximately 40% of the respondents were categorised as car‐dependent. Of the non‐car‐dependent respondents, 31% use the car for commuting. A binomial logit model revealed that higher residential densities and closer proximity to a railway station reduce the odds of car commuting. Travel time ratios also have a significant influence on the expected directions. Mode choice preferences (e.g., comfort, flexibility, etc.) also have a significant, and strong, impact. These results highlight the importance of combining hard (e.g., improvements in infrastructure or public transport provi-sion) and soft (information and persuasion) measures to reduce car use and car dependency in commuting trips.
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Abstract-Architecture Compliance Checking (ACC) is useful to bridge the gap between architecture and implementation. ACC is an approach to verify conformance of implemented program code to high-level models of architectural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Seven tools were tested and compared by means of a custom-made test application. In addition, the code of open source system Freemind was used to compare the tools on the number and precision of reported violation and dependency messages. On the average, 74 percent of 34 dependency types in our custom-made test software were reported, while 69 percent of 109 violating dependencies within a module of Freemind were reported. The test results show large differences between the tools, but all tools could improve the accuracy of the reported dependencies and violations.
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SUMMARY Architecture compliance checking (ACC) is an approach to verify conformance of implemented program code to high-level models of architec tural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Ten tools were tested and compare d by means of a custom-made benchmark. The Java code of the benchmark testware contains 34 different types of dependencies, which are based on an inventory of dependency types in object oriented program code. In a second test, the code of open source system FreeMind was used to compare the 10 tools on the number of reported rule violating dependencies and the exactness of the dependency and violation messages. On the average, 77% of the dependencies in our custom-made test software were reported, while 72% of the dependencies within a module of FreeMind were reported. The results show that all tools in the test could improve the accuracy of the reported dependencies and violations, though large differences between the 10 tools were observed. We have identified10 hard-to-detect types of dependencies and four challenges in dependency detection. The relevance of our findings is substantiated by means of a frequency analysis of the hard-to-detect types of dependencies in five open source systems. DOI: 10.1002/spe.2421
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Untrained listeners demonstrate implicit knowledge of syntactic patternsand principles. Untrained generative music ability, for example singing,humming, and whistling, is a largely unconscious or intuitive applicationof these patterns and principles. From the viewpoint of embodied cognition,listening to music should evoke an internal representation or motorimage which, together with the perception of organized music, shouldform the basis of musical cognition. Indeed, that is what listeners demonstratewhen they sing, hum, or whistle familiar and unfamiliar tunes orwhen they vocally or orally improvise continuations to interruptedphrases. Research on vocal improvisation using continuations sung to aninterrupted musical phrase, has shown that one’s cultural backgroundinfluences the music generated. That should be the case for instrumentalistsas well: when they play familiar or unfamiliar tunes by ear in differentkeys (transposition) or when they improvise variations,accompaniments, or continuations to interrupted phrases, the music theygenerate should reflect the same cognitive structures as their oral improvisations.This study is attempting to validate a test of (non) scoredependencythat will enable assessment of the music student’s implicitknowledge of these structures during performance on the principal instrument.
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Background: Dependency in activities of daily living (ADL) might be caused by multidimensional frailty. Prevention is important as ADL dependency might threaten the ability to age in place. Therefore, this study aimed to assess whether protective factors, derived from a systematic literature review, moderate the relationship between multidimensional frailty and ADL dependency, and whether this differs across age groups. Methods: A longitudinal study with a follow–up after 24 months was conducted among 1027 communitydwelling people aged ≥65 years. Multidimensional frailty was measured with the Tilburg Frailty Indicator, and ADL dependency with the ADL subscale from the Groningen Activity Restriction Scale. Other measures included socio-demographic characteristics and seven protective factors against ADL dependency, such as physical activity and non-smoking. Logistic regression analyses with interaction terms were conducted. Results: Frail older people had a twofold risk of developing ADL dependency after 24 months in comparison to non-frail older people (OR=2.12, 95% CI=1.45–3.00). The selected protective factors against ADL dependency did not significantly moderate this relationship. Nonetheless, higher levels of physical activity decreased the risk of becoming ADL dependent (OR=0.67, 95% CI=0.46–0.98), as well as having sufficient financial resources (OR=0.49, 95% CI=0.35–0.71). Conclusion: Multidimensional frail older people have a higher risk of developing ADL dependency. The studied protective factors against ADL dependency did not significantly moderate this relationship.
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Untrained listeners demonstrate implicit knowledge of syntactic patternsand principles. Untrained generative music ability, for example singing,humming, and whistling, is a largely unconscious or intuitive applicationof these patterns and principles. From the viewpoint of embodied cognition,listening to music should evoke an internal representation or motorimage which, together with the perception of organized music, shouldform the basis of musical cognition. Indeed, that is what listeners demonstratewhen they sing, hum, or whistle familiar and unfamiliar tunes orwhen they vocally or orally improvise continuations to interruptedphrases. Research on vocal improvisation using continuations sung to aninterrupted musical phrase, has shown that one’s cultural backgroundinfluences the music generated. That should be the case for instrumentalistsas well: when they play familiar or unfamiliar tunes by ear in differentkeys (transposition) or when they improvise variations,accompaniments, or continuations to interrupted phrases, the music theygenerate should reflect the same cognitive structures as their oral improvisations.This study is attempting to validate a test of (non) scoredependencythat will enable assessment of the music student’s implicitknowledge of these structures during performance on the principal instrument.
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Presented at the 2015 European Conference on Software Architecture Workshops. DOI 10.1145/2797433.2797491 http://dl.acm.org/citation.cfm?id=2797491 Software architecture reconstruction and compliance checking rely on supporting tools that analyze the modules in the code and their dependencies. Tools may provide a dependency type for each dependency to provide more detail on the actual usage relation. This study is aimed on the identification of dependency characteristics which can be determined accurately and which might be interesting for architects and researchers in the context of architecture reconstruction and compliance checking. A classification is proposed which distinguishes dependency types, related subtypes, and several other characteristics. To enable reflection on the usefulness of the classified dependency details, a prototype implementation has been developed for the analysis of Java based systems. A frequency analysis of the classified dependency characteristics in three open source systems is presented, as well as an analysis of a set of rule violating dependencies in one of these systems.
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BACKGROUND: Sarcopenia might be a relevant lead for optimization of the condition of patients with head and neck cancer (HNC) before chemoradiotherapy (CRT) to prevent long-term functional swallowing impairment, such as feeding tube dependency.METHODS: Regression analyses were performed to assess the association between skeletal muscle mass index (SMI), as a measure of sarcopenia, and prolonged (>90 days) feeding tube dependency in 128 patients with HNC treated with primary CRT.RESULTS: Sixty-one patients (48%) became prolonged feeding tube-dependent. Lower SMI increased the risk of prolonged feeding tube dependency in multivariable analysis (risk ratio 1.08; 95% confidence interval 1.02-1.14, P = .01) adjusted for body mass index, abnormal diet, and socioeconomic status.CONCLUSIONS: Sarcopenia contributes to the risk of prolonged feeding tube dependency of patients with HNC treated with primary CRT. As sarcopenia might be a modifiable factor prior to treatment, it should be explored as a target for pretreatment patients' condition.
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The aim of this study was to assess the predictive ability of the frailty phenotype (FP), Groningen Frailty Indicator (GFI), Tilburg Frailty Indicator (TFI) and frailty index (FI) for the outcomes mortality, hospitalization and increase in dependency in (instrumental) activities of daily living ((I)ADL) among older persons. This prospective cohort study with 2-year follow-up included 2420 Dutch community-dwelling older people (65+, mean age 76.3±6.6 years, 39.5% male) who were pre-frail or frail according to the FP. Mortality data were obtained from Statistics Netherlands. All other data were self-reported. Area under the receiver operating characteristic curves (AUC) was calculated for each frailty instrument and outcome measure. The prevalence of frailty, sensitivity and specifcity were calculated using cutoff values proposed by the developers and cutoff values one above and one below the proposed ones (0.05 for FI). All frailty instruments poorly predicted mortality, hospitalization and (I)ADL dependency (AUCs between 0.62–0.65, 0.59–0.63 and 0.60–0.64, respectively). Prevalence estimates of frailty in this population varied between 22.2% (FP) and 64.8% (TFI). The FP and FI showed higher levels of specifcity, whereas sensitivity was higher for the GFI and TFI. Using a different cutoff point considerably changed the prevalence, sensitivity and specifcity. In conclusion, the predictive ability of the FP, GFI, TFI and FI was poor for all outcomes in a population of pre-frail and frail community-dwelling older people. The FP and the FI showed higher values of specifcity, whereas sensitivity was higher for the GFI and TFI.
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Background: Due to differences in the definition of frailty, many different screening instruments have been developed. However, the predictive validity of these instruments among community-dwelling older people remains uncertain. Objective: To investigate whether combined (i.e. sequential or parallel) use of available frailty instruments improves the predictive power of dependency in (instrumental) activities of daily living ((I)ADL), mortality and hospitalization. Design, setting and participants: A prospective cohort study with two-year followup was conducted among pre-frail and frail community-dwelling older people in the Netherlands. Measurements: Four combinations of two highly specific frailty instruments (Frailty Phenotype, Frailty Index) and two highly sensitive instruments (Tilburg Frailty Indicator, Groningen Frailty Indicator) were investigated. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for all single instruments as well as for the four combinations, sequential and parallel. Results: 2,420 individuals participated (mean age 76.3 ± 6.6 years, 60.5% female) in our study. Sequential use increased the levels of specificity, as expected, whereas the PPV hardly increased. Parallel use increased the levels of sensitivity, although the NPV hardly increased. Conclusions: Applying two frailty instruments sequential or parallel might not be a solution for achieving better predictions of frailty in community-dwelling older people. Our results show that the combination of different screening instruments does not improve predictive validity. However, as this is one of the first studies to investigate the combined use of screening instruments, we recommend further exploration of other combinations of instruments among other study populations.
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