What Drives Creative Crowdsourcing? An Exploratory Study on the Persuasion of Digital Storytelling

Crowdsourcing enterprises increasingly seek to attract and persuade makers to contribute their creativity and wisdom through digital storytelling, however, what are the effective components of digital storytelling and the persuasive effect of digital storytelling on creative crowdsourcing intention are still unclear. To fill this gap, this study explores how digital storytelling persuades makers to generate creative crowdsourcing behavioural intention by utilising Unified Theory of Acceptance and Use of Technology (UTAUT). Results reveal that the persuasion activity of digital storytelling has a positive effect on creative crowdsourcing intention. The effective components of digital storytelling are mainly composed of aesthetic perception, narrative structure and self-reference. UTAUT and its four core concepts (performance expectation, effort expectation, social influence and facilitating condition) mediate the impact of digital storytelling on the creative crowdsourcing intention, which reveals the persuasive source of digital storytelling. We highlight the theoretical implications as well as the practical applications in creative crowdsourcing

Rapid detection of bedding boundaries based on borehole images

Abstract The bedding is an important sedimentary structure phenomenon. The rock bedding structure, the direction of sedimentary transportation and the ancient sedimentary environment analysis can be studied by extracting the bedding boundaries and dips. Electric imaging logging can provide rich information of a borehole wall and circumference, which reflects formation resistivity variations. The bedding boundaries are detected by using the electrical imaging logging data based on an image recognition method in this paper. On an oriented, unwrapped image of a cylindrical borehole, the trace of a planar-bedding boundary appears as a sine wave. The bedding boundaries are detected by the recognition of the sine curves in borehole image. The influence problems of bedding boundary detection caused by fractures and other geological events are solved by statistical analysis technology. Through the techniques of the slope fitting, the speed and accuracy problems of bedding boundary detection are solved, which has good anti-interference performance. The processed results of the theoretical models and the measured borehole images at the varied dip segment indicate that the detected bedding boundaries reflect the real situation, which are identical to those derived by the Autodip

Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstruction

Although recent deep learning methods, especially generative models, have shown good performance in fast magnetic resonance imaging, there is still much room for improvement in high-dimensional generation. Considering that internal dimensions in score-based generative models have a critical impact on estimating the gradient of the data distribution, we present a new idea, low-rank tensor assisted k-space generative model (LR-KGM), for parallel imaging reconstruction. This means that we transform original prior information into high-dimensional prior information for learning. More specifically, the multi-channel data is constructed into a large Hankel matrix and the matrix is subsequently folded into tensor for prior learning. In the testing phase, the low-rank rotation strategy is utilized to impose low-rank constraints on tensor output of the generative network. Furthermore, we alternately use traditional generative iterations and low-rank high-dimensional tensor iterations for reconstruction. Experimental comparisons with the state-of-the-arts demonstrated that the proposed LR-KGM method achieved better performance

Modelling the permeability of random discontinuous carbon fibre preforms

A force-directed algorithm was developed to create representative geometrical models of fibre distributions in directed carbon fibre preforms. Local permeability values were calculated for the preform models depending on the local fibre orientation, distribution and volume fraction. The effect of binder content was incorporated by adjusting the principal permeability values of the meso-scale discontinuous fibre bundles, using corresponding experimental data obtained for unidirectional non-crimp fabrics. The model provides an upper boundary for the permeability of directed carbon fibre preform architectures, where predictions are within one standard deviation of the experimental mean for all architectures studied

Community-based Message Opportunistic Transmission

Mobile Social Networks (MSNs) is a kind of opportunistic networks, which is composed of a large number of mobile nodes with social characteristic. Up to now, the prevalent communitybased routing algorithms mostly select the most optimal social characteristic node to forward messages. But they almost don\u27t consider the effect of community distribution on mobile nodes and the time-varying characteristic of network. These algorithms usually result in high consumption of network resources and low successful delivery ratio if they are used directly in mobile social networks. We build a time-varying community-based network model, and propose a community-aware message opportunistic transmission algorithm (CMOT) in this paper. For inter-community messages transmission, the CMOT chooses an optimal community path by comparing the community transmission probability. For intra-community in local community, messages are forwarded according to the encounter probability between nodes. The simulation results show that the CMOT improves the message successful delivery ratio and reduces network overhead obviously, compared with classical routing algorithms, such as PRoPHET, MaxProp, Spray and Wait, and CMTS

PGC 38025: A Star-forming Lenticular Galaxy With an Off-nuclear Star-forming Core

Lenticular galaxies (S0s) were considered mainly as passive evolved spirals due to environmental effects for a long time; however, most S0s in the field cannot fit into this common scenario. In this work, we study one special case, SDSS J120237.07+642235.3 (PGC 38025), a star-forming field S0 galaxy with an off-nuclear blue core. We present optical integral field spectroscopic (IFS) observation with the 3.5 meter telescope at Calar Alto (CAHA) Observatory, and high-resolution millimeter observation with the NOrthern Extended Millimeter Array (NOEMA). We estimated the star formation rate (SFR = 0.446 $M_\odot yr^{-1}$) and gaseous metallicity (12 + log(O/H) = 8.42) for PGC 38025, which follows the star formation main sequence and stellar mass - metallicity relation. We found that the ionized gas and cold molecular gas in PGC 38025 show the same spatial distribution and kinematics, whilst rotating misaligned with stellar component. The off-nuclear blue core is locating at the same redshift as PGC 38025 and its optical spectrum suggest it is \rm H\,{\sc ii} region. We suggest that the star formation in PGC 38025 is triggered by a gas-rich minor merger, and the off-nuclear blue core might be a local star-formation happened during the accretion/merger process.Comment: 16 pages, 13 figures, accepted for publication in Ap

Isolation, purification and PEG-mediated transient expression of mesophyll protoplasts in Camellia oleifera

Background: Camellia oleifera (C. oleifera) is a woody edible oil crop of great economic importance. Because of the lack of modern biotechnology research, C. oleifera faces huge challenges in both breeding and basic research. The protoplast and transient transformation system plays an important role in biological breeding, plant regeneration and somatic cell fusion. The objective of this present study was to develop a highly efficient protocol for isolating and purifying mesophyll protoplasts and transient transformation of C. oleifera. Several critical factors for mesophyll protoplast isolation from C. oleifera, including starting material (leaf age), pretreatment, enzymatic treatment (type of enzyme, concentration and digestion time), osmotic pressure and purification were optimized. Then the factors affecting the transient transformation rate of mesophyll protoplasts such as PEG molecular weights, PEG4000 concentration, plasmid concentration and incubation time were explored.Results: The in vitro grown seedlings of C. oleifera 'Huashuo' were treated in the dark for 24 h, then the 1st to 2nd true leaves were picked and vacuumed at - 0.07 MPa for 20 min. The maximum yield (3.5 x 10(7)/g.W) and viability (90.9%) of protoplast were reached when the 1st to 2nd true leaves were digested in the enzymatic solution containing1.5% (w/v) Cellulase R-10, 0.5% (w/v) Macerozyme R-10 and 0.25% (w/v) Snailase and 0.4 M mannitol for 10 h. Moreover, the protoplast isolation method was also applicable to the other two cultivars, the protoplast yield for 'TXP14' and 'DP47' was 1.1 x 10(7)/g.FW and 2.6 x 10(7)/g. FW, the protoplast viability for 'TXP14' and 'DP47' was 90.0% and 88.2%. The purification effect was the best when using W buffer as a cleaning agent by centrifugal precipitation. The maximum transfection efficiency (70.6%) was obtained with the incubation of the protoplasts with 15 mu g plasmid and 40% PEG4000 for 20 min.Conclusion: In summary, a simple and efficient system for isolation and transient transformation of C. oleifera mesophyll protoplast is proposed, which is of great significance in various aspects of C. oleifera research, including the study of somatic cell fusion, genome editing, protein function, signal transduction, transcriptional regulation and multi-omics analyses