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- Buchanan, E. M., et al.
(författare)
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The Psychological Science Accelerator's COVID-19 rapid-response dataset
- 2023
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
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| 5. |
- Jones, Benedict C, et al.
(författare)
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To which world regions does the valence-dominance model of social perception apply?
- 2021
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Ingår i: Nature Human Behaviour. - : Springer Science and Business Media LLC. - 2397-3374. ; 5:1, s. 159-169
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Tidskriftsartikel (refereegranskat)abstract
- Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .
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| 6. |
- Moshontz, Hannah, et al.
(författare)
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The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network
- 2018
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Ingår i: Advances in Methods and Practices in Psychological Science. - : SAGE Publications. - 2515-2459 .- 2515-2467. ; 1:4, s. 501-515
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Tidskriftsartikel (refereegranskat)abstract
- Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.
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| 7. |
- Antfolk, M., et al.
(författare)
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Acoustophoresis for label-free separation and concentration of cancer cells
- 2014
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Ingår i: 18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014. - 9780979806476 ; , s. 2508-2509
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Konferensbidrag (refereegranskat)abstract
- Here, an acoustophoresis chip is presented that is capable of separating cancer cells from white blood cells (WBCs) and subsequently concentrating the recovered cells in the same chip. The chip utilizes ultrasound standing waves in two dimensions to pre-align, separate and concentrate the cells. 92% of the cancer cells could be recovered while keeping the contamination level of WBCs to only 0.6%. The recovered cancer cells were concentrated 24 times.
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| 8. |
- Antfolk, M., et al.
(författare)
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An integrated acousto- and dielectrophoresis device for tumor cell separation, concentration, and single-cell trapping
- 2016
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Ingår i: 20th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2016. - 9780979806490 ; , s. 1657-1658
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Konferensbidrag (refereegranskat)abstract
- Many microfluidic devices have been developed to separate rare cells, e.g. circulating tumor cells. The collection and analysis of the separated rare cells pose a challenge as it may lead to loss of target cells since extremely small number of cells are usually suspended in a large volume after separation. Here, we present an integrated device that allows acoustophoretic target cell separation and concentration, followed by dielectrophoretic single-cell trapping. We show that the human prostate cancer cell line DU145 were efficiently separated from peripheral blood mononuclear cells (PBMCs), and 81.7% of DU145 were trapped, with a contamination of 1.7% PBMC.
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| 9. |
- Huang, Huaiqi, et al.
(författare)
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Automatic hand phantom map detection methods
- 2015
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Ingår i: IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings. - 9781479972333
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Konferensbidrag (refereegranskat)abstract
- Many amputees have maps of referred sensation from their missing hand on their residual limb (phantom maps). This skin area can serve as a target for providing amputees with tactile sensory feedback. Providing tactile feedback on the phantom map can improve the object manipulation ability, enhance embodiment of myoelectric prostheses users and help reduce phantom limb pain. The distribution of the phantom map varies with the individual. Here, we investigate a fast and accurate method for hand phantom map shape detection. We present three elementary (group testing, adaptive edge finding and support vector machines (SVM)) and two combined methods (SVM with majority-pooling and SVM with active learning) tested with different types of phantom map models and compare the classification error rates. The results show that SVM with majority-pooling has the smallest classification error rate.
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| 10. |
- Huang, Huaiqi, et al.
(författare)
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Automatic hand phantom map generation and detection using decomposition support vector machines
- 2018
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Ingår i: BioMedical Engineering Online. - : Springer Science and Business Media LLC. - 1475-925X. ; 17:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is a need for providing sensory feedback for myoelectric prosthesis users. Providing tactile feedback can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom limb pain. Many amputees have referred sensation from their missing hand on their residual limbs (phantom maps). This skin area can serve as a target for providing amputees with non-invasive tactile sensory feedback. One of the challenges of providing sensory feedback on the phantom map is to define the accurate boundary of each phantom digit because the phantom map distribution varies from person to person. Methods: In this paper, automatic phantom map detection methods based on four decomposition support vector machine algorithms and three sampling methods are proposed, complemented by fuzzy logic and active learning strategies. The algorithms and methods are tested on two databases: the first one includes 400 generated phantom maps, whereby the phantom map generation algorithm was based on our observation of the phantom maps to ensure smooth phantom digit edges, variety, and representativeness. The second database includes five reported phantom map images and transformations thereof. The accuracy and training/ classification time of each algorithm using a dense stimulation array (with 100 $$\times $$ × 100 actuators) and two coarse stimulation arrays (with 3 $$\times $$ × 5 and 4 $$\times $$ × 6 actuators) are presented and compared. Results: Both generated and reported phantom map images share the same trends. Majority-pooling sampling effectively increases the training size, albeit introducing some noise, and thus produces the smallest error rates among the three proposed sampling methods. For different decomposition architectures, one-vs-one reduces unclassified regions and in general has higher classification accuracy than the other architectures. By introducing fuzzy logic to bias the penalty parameter, the influence of pooling-induced noise is reduced. Moreover, active learning with different strategies was also tested and shown to improve the accuracy by introducing more representative training samples. Overall, dense arrays employing one-vs-one fuzzy support vector machines with majority-pooling sampling have the smallest average absolute error rate (8.78% for generated phantom maps and 11.5% for reported and transformed phantom map images). The detection accuracy of coarse arrays was found to be significantly lower than for dense array. Conclusions: The results demonstrate the effectiveness of support vector machines using a dense array in detecting refined phantom map shapes, whereas coarse arrays are unsuitable for this task. We therefore propose a two-step approach, using first a non-wearable dense array to detect an accurate phantom map shape, then to apply a wearable coarse stimulation array customized according to the detection results. The proposed methodology can be used as a tool for helping haptic feedback designers and for tracking the evolvement of phantom maps.
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