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1.
Front Psychol ; 13: 943655, 2022.
Article in English | MEDLINE | ID: mdl-36300040

ABSTRACT

Sluggish status of green technology development has stimulated research into new incentives and pathways. Beyond the traditional regulatory-push and demand-pull approaches, we reposition the strength of the technology push. Based on the innovation diffusion theory, a multidimensional path model of knowledge spillover in universities is constructed, and the impact of heterogeneous knowledge spillover channels on green innovation activities of local firms is discussed. We find that R&D collaboration has a significant effect on local firms' quality but not the quantity of green innovation. Contrarily, patent citations and technology transfer have unequal positive effects on the quantity of green innovation of local firms, while there is no evidence that they can also improve the quality of green innovation. Despite regional disparities, strict environmental regulations are pushing companies to cite university patents in some regions. The university knowledge stock has largely contributed to both quantitative and qualitative advances in subsequent green innovation in local firms. Our conclusions provide a precise and objective evaluation of the impact mechanism of multiple knowledge spillover channels in universities on firms' green innovation, as well as a reference for the selection of the form of industry-university-research collaboration.

2.
Front Aging Neurosci ; 13: 766884, 2021.
Article in English | MEDLINE | ID: mdl-34867293

ABSTRACT

Given the limited power of neuropsychological tests, there is a need for a simple, reliable means, such as gait, to identify mild dementia and its subtypes. However, gait characteristics of patients with post-stroke dementia (PSD) and Alzheimer's disease (AD) are unclear. We sought to describe their gait signatures and to explore gait parameters distinguishing PSD from post-stroke non-dementia (PSND) and patients with AD. We divided 3-month post-stroke patients into PSND and PSD groups based on the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the activity of daily living (ADL). Thirty-one patients with AD and thirty-two healthy controls (HCs) were also recruited. Ten gait parameters in one single and two dual-task gait tests (counting-backward or naming-animals while walking) were compared among the groups, with adjustment for baseline demographic covariates and the MMSE score. The area under the receiver operating characteristic curve (AUC) was used to identify parameters discriminating PSD from individuals with PSND and AD. Patients with PSD and patients with AD showed impaired stride length, velocity, stride time, and cadence while patients with PSD had altered stance and swing phase proportions (all p ≤ 0.01, post hoc). Patients with AD had smaller toe-off (ToA) and heel-to-ground angles (HtA) (p ≤ 0.01) than HCs in dual-task gait tests. Individuals with PSD had a shorter stride length, slower velocity, and altered stance and swing phase percentages in all tests (p ≤ 0.01), but a higher coefficient of variation of stride length (CoVSL) and time (CoVST) only in the naming animals-task gait test (p ≤ 0.001) than individuals with PSND. ToA and HtA in the naming animals-task gait test were smaller in individuals with AD than those with PSD (p ≤ 0.01). Statistical significance persisted after adjusting for demographic covariates, but not for MMSE. The pace and the percentage of stance or swing phase in all tests, CoVST in the dual-task paradigm, and CoVSL only in the naming animals-task gait test (moderate accuracy, AUC > 0.700, p ≤ 0.01) could distinguish PSD from PSND. Furthermore, the ToA and HtA in the naming animals-task gait paradigm discriminated AD from PSD (moderate accuracy, AUC > 0.700, p ≤ 0.01). Thus, specific gait characteristics could allow early identification of PSD and may allow non-invasive discrimination between PSD and AD, or even other subtypes of dementia.

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