Who Can Survive in an ICT-Enabled Crowdfunding Platform?

The importance of socio-technical ecosystems is growing due to the emergence of technology-based platform businesses. However, few researchers have offered theoretical explanations of this phenomenon drawing on the ecosystem perspective. Existing studies on ecosystems have been limited to either natural or social ecosystems and have examined ecosystems as a whole. This study focuses on the survival and evolution of individual participants in the socio-technical ecosystem of a crowdfunding platform. It is hypothesized that adaptability (i.e., intra-role and inter-role exchange) and relationality (i.e., feedback and feed-forward interactivity) are positively related to the amount of funding received and the likelihood of campaign success. Empirical results from regression analysis show that the quality of intra-role and inter-role exchanges determine their influence on funding success. High relationality has a significant, positive influence on the funding received by a campaign. With this insight, this paper lays the groundwork for expanding theoretical research on socio-technical ecosystems

Word-of-Mouth of Cultural Products through Institutional Social Networks

Recently, a number of cultural institutions such as museums, galleries, art auctions, events, and performance centers have been utilizing social network sites (SNS) for promoting and marketing their culture, art content, and events. The online social space is appropriate for cultural products to be viral, since users of SNS mainly share personal interest and spread hedonic consumption with close friends and acquaintances. If viral content drives strong emotions such as joy, arousal, pleasure, sorrow, or horror, it will be transmitted to more people, and rapidly. This study investigates how a certain type of motivation for using a social network service such as Facebook influences trust in art and culture exhibition information providers and the content of the information itself. Results show that people who have an informational motivation for using social media expressed a higher degree of trust in exhibition information provided by institutions such as museums. On the contrary, those who have relational motivation for using social media credited acquaintances such as friends, families, and colleagues more. Trust in the information provider resulted in trust in the content itself, and hence, increased the possibility of word-of-mouth for the corresponding information. An empirical survey was implemented, using followers of the Facebook page of a national museum and users who clicked “Like” on postings of exhibitions. Finally, the potential applications of the result for promotion and marketing of exhibitions of art and culture for public will be discussed

Effects of Skin Surface Temperature on Photoplethysmograph

Photoplethysmograph (PPG) has been widely used to investigate various cardiovascular conditions. Previous studies demonstrated effects of temperature of the measurement environment; however, an integrated evaluation has not been established in environments with gradual air temperature variation. The purpose of this study is to investigate variations and relationships of blood pressure (BP), PPG and cardiovascular parameters such as heart rate (HR), stroke volume (SV), cardiac output (CO) and total peripheral resistance (TPR), by changing skin surface temperature (SST). Local mild cooling and heating was conducted on 16 healthy subjects. The results showed that local SST changes affected Finometer blood pressures (Finger BP), PPG components and TPR, but not the oscillometric blood pressure (Central BP), HR, SV and CO, and indicated that temperature must be maintained and monitored to reliably evaluate cardiovascular conditions in temperature-varying environments

Variation-Aware SRAM Cell Optimization Using Deep Neural Network-Based Sensitivity Analysis

Under process, voltage, and temperature variations, SRAM cell stability largely fluctuates from the nominal value. In the design step, SRAM cell optimization while ignoring the fluctuation induces the yield loss for the stability. Variation-aware optimization of an SRAM cell can prevent the yield loss problem by considering the mean and variance of SRAM cell stability when finding optimal design parameters. This paper proposes a novel SRAM optimization method that uses a deep neural network (DNN). Multiple DNNs from ensemble techniques represent the mean and variance of SRAM cell stability for the nominal design parameters. Subsequent sensitivity analysis of DNN extracts the K design parameters that have the most dominant effects on the mean and variance of SRAM cell stability. Then multidimensional optimization is used to find the optimal values of these K parameters to maximize the mean stability while minimizing its variance. The proposed method achieved an average of 2% error compared to MC simulation. The proposed optimization method takes only 561 s to provide the most optimal design parameter values of an SRAM cell.11Nsciescopu

MDARTS: Multi-objective Differentiable Neural Architecture Search

In this work, we present a differentiable neural architecture search (NAS) method that takes into account two competing objectives, quality of result (QoR) and quality of service (QoS) with hardware design constraints. NAS research has recently received a lot of attention due to its ability to automatically find architecture candidates that can outperform handcrafted ones. However, the NAS approach which complies with actual HW design constraints has been under-explored. A naive NAS approach for this would be to optimize a combination of two criteria of QoR and QoS, but the simple extension of the prior art often yields degenerated architectures, and suffers from a sensitive hyperparameter tuning. In this work, we propose a multi-objective differential neural architecture search, called MDARTS. MDARTS has an affordable search time and can find Pareto frontier of QoR versus QoS. We also identify the problematic gap between all the existing differentiable NAS results and those final post-processed architectures, where soft connections are binarized. This gap leads to performance degradation when the model is deployed. To mitigate this gap, we propose a separation loss that discourages indefinite connections of components by implicitly minimizing entropy.1

Machine Learning Framework for Early Routability Prediction with Artificial Netlist Generator

Recent routability research has exploited a machine learning (ML)-based modeling methodologies to consider various routability factors that are derived from placement solution. These factors are very related to the circuit characteristics (e.g., pin density, routing congestion, demand of routing resources, etc), and lack of circuit benchmarks in training can lead to poor predictability for 'unseen' circuit designs. In this paper, we propose a machine learning (ML) framework for early routability prediction modeling. The method includes a new artificial netlist generator (ANG) that generates an artificial gate-level netlist from the user-specified topology characteristics of synthetic circuit, even with real world circuit-like. In this framework, we exploit that ANG that supports obtaining ground truths for use in training ML-based model, the training dataset that have a wide range of topological characteristics provides strong ability to inference noisy, previous-unseen data. Compared to a design-specific training dataset [4] that is used for routability prediction modeling, we increase the test accuracy of binary classification ('pass' or 'fail') on timing, DRC and routability by 6.3%, 8.6% and 6.6%, and reduce the generalization error [12] by as much as 87% compared to design-specific training dataset [4].1

Inhibitory effect of traditional oriental medicine-derived monoamine oxidase B inhibitor on radioresistance of non-small cell lung cancer

Increased survival of cancer cells mediated by high levels of ionizing radiation (IR) reduces the effectiveness of radiation therapy for non-small cell lung cancer (NSCLC). In the present study, danshensu which is a selected component of traditional oriental medicine (TOM) compound was found to reduce the radioresistance of NSCLC by inhibiting the nuclear factor-κB (NF-κB) pathway. Of the various TOM compounds reported to inhibit the IR activation of NF-κB, danshensu was chosen as a final candidate based on the results of structural comparisons with human metabolites and monoamine oxidase B (MAOB) was identified as the putative target enzyme. Danshensu decreased the activation of NF-κB by inhibiting MAOB activity in A549 and NCI-H1299 NSCLC cells. Moreover, it suppressed IR-induced epithelial-to-mesenchymal transition, expressions of NF-κB-regulated prosurvival and proinflammatory genes, and in vivo radioresistance of mouse xenograft models. Taken together, this study shows that danshensu significantly reduces MAOB activity and attenuates NF-κB signaling to elicit the radiosensitization of NSCLC

Steric Effect on the Nucleophilic Reactivity of Nickel(III) Peroxo Complexes

A set of nickel(III) peroxo complexes bearing tetraazamacrocyclic ligands, [Ni-III(TBDAP)(O-2)](+) (TBDAP = N,Ni-di-tert-butyl-2,11-diaza[3.3](2,6)pyridinophane) and [Ni-III(CHDAP)(O-2)](+) (CHDAP = N,N'-dicyclohexyl-2,11-diaza[3.3](2,6)pyridinophane), were prepared by reacting [Ni-II(TBDAP)(NO3)(H2O)](+) and [Ni-II(CHDAP)(NO3)](+), respectively, with H2O2 in the presence of triethylamine. The mononuclear nickel(III) peroxo complexes were fully chatacterized by various physicochemical methods, such as UV-vis, electrospray ionization mass spectrometry, resonance Raman, electron paramagnetic resonance, and X-ray analysis. The spectroscopic and structural characterization clearly shows that the NiO2 cores are almost identical where the peroxo ligand is bound in a side-on fashion. properties of the supporting ligands were confirmed by X-ray crystallography, where the CHDAP ligand gives enough space around the Ni core compared to the TBDAP ligand. The nickel(III) peroxo complexes showed reactivity in the oxidation of aldehydes. In the aldehyde deformylation reaction, the nucleophilic reactivity of the nickel(III) peroxo, complexes was highly dependent on the steric properties of the macrocyclic ligands, with. a reactivity order of [Ni-III(TBDAP)(O-2)](+) < [Ni-III(CHDAP)(O-2)](+). This result provides fundamental insight into the mechanism of the structure (steric) reactivity relationship of metal peroxo intermediates