Validation of perceived physical fatigability using the simplified-Chinese version of the Pittsburgh Fatigability Scale.

BACKGROUND: The Pittsburgh Fatigability Scale (PFS) was developed to capture fatigue and demand in a single tool, filling a gap that no validated questionnaire existed to measure perceived fatigability. Since fatigability is a more sensitive measure of a person's susceptibility to fatigue, we validated the simplified-Chinese version of the PFS among Chinese community-dwelling older adults. METHODS: This cross-sectional study was conducted in an urban community in Beijing between November 2018 and July 2019. The PFS was translated into simplified-Chinese by the translation, retro-translation method. Internal consistency of the Physical subscale of the PFS was evaluated by Cronbach's alpha. Convergent validity and discriminant validity were evaluated against physical performance measures (i.e., Short Physical Performance Battery & Timed Up and Go Test) and daily living performance (i.e., Barthel Index & Instrumental activity of daily living). RESULTS: Our study included 457 participants, including 182 men (39.8%) and 275 women (60.2%). The age range of the included participants was 61-96 years (mean = 84.8 years, SD = 5.8 years). The simplified-Chinese version of PFS Physical scores showed strong internal consistency (Cronbach's alpha = 0.81). Higher PFS Physical scores were associated with worse physical performance, and daily living performance (|correlation coefficient| range: 0.36-0.56, p < .001). Age- and sex-adjusted PFS Physical scores had moderate to good overall discrimination for correctly classifying people by their physical performance and daily living performance (AUCs range 0.70-0.87, p < .001). CONCLUSIONS: The PFS simplified-Chinese version is a valid instrument to assess perceived physical fatigability in Chinese-speaking older adults with good convergent validity. Thus, the PFS, with low cost and greater feasibility, is a desired tool to measure fatigability in large population studies.

Metavalent Bonding in Layered Phase-Change Memory Materials.

Metavalent bonding (MVB) is characterized by the competition between electron delocalization as in metallic bonding and electron localization as in covalent or ionic bonding, serving as an essential ingredient in phase-change materials for advanced memory applications. The crystalline phase-change materials exhibits MVB, which stems from the highly aligned p orbitals and results in large dielectric constants. Breaking the alignment of these chemical bonds leads to a drastic reduction in dielectric constants. In this work, it is clarified how MVB develops across the so-called van der Waals-like gaps in layered Sb2 Te3 and Ge-Sb-Te alloys, where coupling of p orbitals is significantly reduced. A type of extended defect involving such gaps in thin films of trigonal Sb2 Te3 is identified by atomic imaging experiments and ab initio simulations. It is shown that this defect has an impact on the structural and optical properties, which is consistent with the presence of non-negligible electron sharing in the gaps. Furthermore, the degree of MVB across the gaps is tailored by applying uniaxial strain, which results in a large variation of dielectric function and reflectivity in the trigonal phase. At last, design strategies are provided for applications utilizing the trigonal phase.

Designing Inorganic Semiconductors with Cold-Rolling Processability.

While metals can be readily processed and reshaped by cold rolling, most bulk inorganic semiconductors are brittle materials that tend to fracture when plastically deformed. Manufacturing thin sheets and foils of inorganic semiconductors is therefore a bottleneck problem, severely restricting their use in flexible electronic applications. It is recently reported that a few single-crystalline 2D van der Waals (vdW) semiconductors, such as InSe, are deformable under compressive stress. Here it is demonstrated that intralayer fracture toughness can be tailored via compositional design to make inorganic semiconductors processable by cold rolling. Systematic ab initio calculations covering a range of van der Waals semiconductors homologous to InSe are reported, leading to material-property maps that forecast trends in both the susceptibility to interlayer slip and the intralayer fracture toughness against cracking. GaSe is predicted, and experimentally confirmed, to be practically amenable to being rolled to large (three quarters) thickness reduction and length extension by a factor of three. The fracture toughness and cleavage energy are predicted to be 0.25 MPa m0.5 and 15 meV Å-2 , respectively. The findings open a new realm of possibility for alloy selection and design toward processing-friendly group-III chalcogenides for practical applications.

Method for enhancing single-trial P300 detection by introducing the complexity degree of image information in rapid serial visual presentation tasks.

The application of electroencephalogram (EEG) generated by human viewing images is a new thrust in image retrieval technology. A P300 component in the EEG is induced when the subjects see their point of interest in a target image under the rapid serial visual presentation (RSVP) experimental paradigm. We detected the single-trial P300 component to determine whether a subject was interested in an image. In practice, the latency and amplitude of the P300 component may vary in relation to different experimental parameters, such as target probability and stimulus semantics. Thus, we proposed a novel method, Target Recognition using Image Complexity Priori (TRICP) algorithm, in which the image information is introduced in the calculation of the interest score in the RSVP paradigm. The method combines information from the image and EEG to enhance the accuracy of single-trial P300 detection on the basis of traditional single-trial P300 detection algorithm. We defined an image complexity parameter based on the features of the different layers of a convolution neural network (CNN). We used the TRICP algorithm to compute for the complexity of an image to quantify the effect of different complexity images on the P300 components and training specialty classifier according to the image complexity. We compared TRICP with the HDCA algorithm. Results show that TRICP is significantly higher than the HDCA algorithm (Wilcoxon Sign Rank Test, p<0.05). Thus, the proposed method can be used in other and visual task-related single-trial event-related potential detection.