Cables are critical components for a variety of structures such as stay cables and suspenders of cable-stayed bridges and suspension bridges. When in operational service, they are vulnerable to cumulative fatigue damage induced by dynamic loads (e.g., the cyclic vehicle loads and wind excitation). To accurately analyze and predict their dynamics behaviors and performance that could be spatially local and temporal transient, it is essential to perform highresolution vibration measurements, from which their dynamics properties are identified and, subsequently, a high spatial resolution, full-modal-order dynamics model of cable vibration can be established. This study develops a physics-guided, unsupervised machine learning-based video processing approach that can blindly and efficiently extract the fullfield (as many points as the pixel number of the video frame) modal parameters of cable vibration using only the video of an operating (output-only) cable. In particular, by incorporating the physics of cable vibration (taut string model), a novel automated modal motion filtering method is proposed to enable autonomous identification of full-order (as many modes as possible) dynamic parameters, including those weakly excited modes that used to be challenging to identify in operational modal analysis. Therefore, a full-field, full-order modal model of cable vibration is established by the proposed method. Furthermore, this new approach provides a low-cost and noncontact technique to estimate the cable tension using only the video of the vibrating cable where the fundamental frequency is automatically and efficiently estimated to compute the cable tension according to the taut string equation. Laboratory experiments on a bench-scale cable are conducted to validate the developed approach.

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This is a report of the validation process of two scales that measure the OIS-García (optimist interactive style). An attempt was made to establish construct and convergent validity for these two scales. Towards this end, we relied on the Spanish version of the LOT-R (life orientation test-revised). Participants were 350 relatives of a cancer patient with a mean age of 39.87 years (SD = 14.88) and an age range going from 15 to 79 years. Each of the new versions of the OIS1-García and OIS2-García comprised 10 items. The Chronbach alpha internal consistency coefficients were 0.701 for the OIS1 and 0.633 for the OIS2. The Spearman correlation coefficient among these two tests was 0.438, the correlation among LOT-R and OIS1-García was 0.382, and the correlation among LOT-R and OIS2-García was 0.468. As a result, we were able to partially validate both versions of the OIS-García test.These findings serve as encouragement to develop more culturally sensitive and appropriate measurement instruments for specific cultures or populations.

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