Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

Selecting Open Innovation Ideas in Teams vs. Nominal Groups: Exploring the Effects of Idea Quantity and Idea Assignment on Idea Selection Quality and Satisfaction with Process

Idea selection is a critical activity in open innovation crowdsourcing projects. Yet, the generation of vast amounts of ideas makes it cognitively challenging to identify the subset of ideas that are worthy of further consideration. We conducted an experiment to explore the influence of idea quantity and idea sharedness on idea selection outcomes evaluated by crowds in the form of teams and nominal groups. We found that higher idea quantity is positively associated with idea selection quality and negatively associated with satisfaction with process. Further, team idea selection quality outperformed individual idea selection quality in both shared information groups and low idea quantity groups. We did not find significant differences between group idea selection quality and individual idea selection quality in the heterogeneous information groups and high idea quantity groups. Theoretical contributions and practical implications are discussed

Can Process Facilitation Improve Globally Distributed Collaboration? An Action Design Research

Distributed collaborators still face problems to organize, to coordinate, and to build consensus. Collaboration tools still have difficulty to configure, to use, and to help facilitate collaboration management. In this study, we conducted an action design research on Company A that relies on distributed collaboration for their business activities. Based on the design theory of collaboration engineering, we designed a process facilitation support application to address the problems identified from Company A with real organizational problems. After rounds of iteration, we proposed two artifacts including facilitated collaboration process and collaborative tools for applications of process guidance. Findings suggest the benefits of facilitated process guidance on globally distributed collaboration. The results of survey show consistently high satisfaction towards the tool and process guidance from the employees. Our research serves as an exploratory investigation in the field of distributed collaboration, and provides evidence regarding the organizational challenges in a business context

Maxwell’s Equations on Cantor Sets: A Local Fractional Approach

Maxwell’s equations on Cantor sets are derived from the local fractional vector calculus. It is shown that Maxwell’s equations on Cantor sets in a fractal bounded domain give efficiency and accuracy for describing the fractal electric and magnetic fields. Local fractional differential forms of Maxwell’s equations on Cantor sets in the Cantorian and Cantor-type cylindrical coordinates are obtained. Maxwell's equations on Cantor set with local fractional operators are the first step towards a unified theory of Maxwell’s equations for the dynamics of cold dark matter

Mappings for Special Functions on Cantor Sets and Special Integral Transforms via Local Fractional Operators

The mappings for some special functions on Cantor sets are investigated. Meanwhile, we apply the local fractional Fourier series, Fourier transforms, and Laplace transforms to solve three local fractional differential equations, and the corresponding nondifferentiable solutions were presented

Exploring Idea Convergence and Conceptual Combination in Open Innovative Crowdsourcing from a Cognitive Load Perspective

Open innovative crowdsourcing has received increasing attention. This study sets out to investigate idea convergence and generation in open innovative crowdsourcing communities from a cognitive load perspective to explore aspects of cognitive idea processing. We have conducted a laboratory experiment to investigate the effects of three manipulations (task complexity, idea presentation, and procedural guidance) on three types of cognitive load and the following idea convergence and generation quality. We have also examined the influencing mechanisms of cognitive loads on satisfaction with process and satisfaction with outcome. Our results show that the three cognitive loads have significant effects: Higher intrinsic cognitive load significantly leads to lower satisfaction with process and outcome. Higher extraneous cognitive load significantly leads to satisfaction with process. Higher germane cognitive load significantly leads to higher convergence quality and lower new idea generation quality

Note on the paper of Fu and Wong on strictly pseudoconvex domains with K\"ahler--Einstein Bergman metrics

It is shown that the Ramadanov conjecture implies the Cheng conjecture. In particular it follows that the Cheng conjecture holds in dimension two

Chiral Antioxidant-based Gold Nanoclusters Reprogram DNA Epigenetic Patterns

Epigenetic modifications sit ‘on top of’ the genome and influence DNA transcription, which can force a significant impact on cellular behavior and phenotype and, consequently human development and disease. Conventional methods for evaluating epigenetic modifications have inherent limitations and, hence, new methods based on nanoscale devices are needed. Here, we found that antioxidant (glutathione) chiral gold nanoclusters induce a decrease of 5-hydroxymethylcytosine (5hmC), which is an important epigenetic marker that associates with gene transcription regulation. This epigenetic change was triggered partially through ROS activation and oxidation generated by the treatment with glutathione chiral gold nanoclusters, which may inhibit the activity of TET proteins catalyzing the conversion of 5-methylcytosine (5mC) to 5hmC. In addition, these chiral gold nanoclusters can downregulate TET1 and TET2 mRNA expression. Alteration of TET-5hmC signaling will then affect several downstream targets and be involved in many aspects of cell behavior. We demonstrate for the first time that antioxidant-based chiral gold nanomaterials have a direct effect on epigenetic process of TET-5hmC pathways and reveal critical DNA demethylation patterns