Background. Adequate and user-friendly instruments for assessing physical function and disability in older adults are vital for estimating and predicting health care needs in clinical practice. The Late-Life Function and Disability Instrument Computer Adaptive Test (LLFDICAT) is a promising instrument for assessing physical function and disability in gerontology research and clinical practice. Objective. The aims of this study were: (1) to translate the LLFDI-CAT to the Dutch language and (2) to investigate its validity and reliability in a sample of older adults who spoke Dutch and dwelled in the community. Design. For the assessment of validity of the LLFDI-CAT, a cross-sectional design was used. To assess reliability, measurement of the LLFDI-CAT was repeated in the same sample. Methods. The item bank of the LLFDI-CAT was translated with a forward-backward procedure. A sample of 54 older adults completed the LLFDI-CAT, World Health Organization Disability Assessment Schedule 2.0, RAND 36-Item Short-Form Health Survey physical functioning scale (10 items), and 10-Meter Walk Test. The LLFDI-CAT was repeated in 2 to 8 days (mean4.5 days). Pearson’s r and the intraclass correlation coefficient (ICC) (2,1) were calculated to assess validity, group-level reliability, and participant-level reliability. Results. A correlation of .74 for the LLFDI-CAT function scale and the RAND 36-Item Short-Form Health Survey physical functioning scale (10 items) was found. The correlations of the LLFDI-CAT disability scale with the World Health Organization Disability Assessment Schedule 2.0 and the 10-Meter Walk Test were .57 and .53, respectively. The ICC (2,1) of the LLFDI-CAT function scale was .84, with a group-level reliability score of .85. The ICC (2,1) of the LLFDI-CAT disability scale was .76, with a group-level reliability score of .81. Limitations. The high percentage of women in the study and the exclusion of older adults with recent joint replacement or hospitalization limit the generalizability of the results. Conclusions. The Dutch LLFDI-CAT showed strong validity and high reliability when used to assess physical function and disability in older adults dwelling in the community.
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Masonry structures represent the highest proportion of building stock worldwide. Currently, the structural condition of such structures is predominantly manually inspected which is a laborious, costly and subjective process. With developments in computer vision, there is an opportunity to use digital images to automate the visual inspection process. The aim of this study is to examine deep learning techniques for crack detection on images from masonry walls. A dataset with photos from masonry structures is produced containing complex backgrounds and various crack types and sizes. Different deep learning networks are considered and by leveraging the effect of transfer learning crack detection on masonry surfaces is performed on patch level with 95.3% accuracy and on pixel level with 79.6% F1 score. This is the first implementation of deep learning for pixel-level crack segmentation on masonry surfaces. Codes, data and networks relevant to the herein study are available in: github.com/dimitrisdais/crack_detection_CNN_masonry.
The design and mission requirements of aero vehicles, which vary on a day-to-day basis, have become major study concerns in the burgeoning aviation sector. In addition to the design and mission criteria that must be met in an aero vehicle design, the designers' primary goals are to construct original, innovative, environmentally friendly, fuel-efficient, and sustainable designs. In this study, a detailed conceptual design of a helicopter that does not need a notable runway for operation and is limited by mission and design requirements is offered. Within the scope of this research, a competitor analysis study was undertaken in accordance with the defined criteria, and design approaches were chosen based on the outcomes of competitor analysis. In addition, this research, which looks for an environmentally friendly and sustainable design, was developed with the aviation industry's demands in mind by analyzing the International Helicopter Safety Team's (IHST) data. As a result of the reports analyzed and considering the causes and consequences of accidents that have happened, the objective of the design research was to achieve a sustainable, ecologically friendly, and fuel-efficient design by reducing the number of accidents and damage. The planning and design processes as a result of this examination are essential as a step towards the helicopter being an original design and in the context of solution methodologies. This archetypal design aims to shed light on helicopter design studies and serve as a roadmap for future research.
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