Suggestions to the article: medical professionalism research characteristics and hotspots

Scientometrics - The article published on 5 July 2021 is well-written and of interest. However, some improvements could be made, such as ten Tables/Figures can be shortened to highlight the focused...     

Reversal of the Inflammatory Responses in Fabry Patient iPSC-Derived Cardiovascular Endothelial Cells by CRISPR/Cas9-Corrected Mutation

The late-onset type of Fabry disease (FD) with GLA IVS4 + 919G > A mutation has been shown to lead to cardiovascular dysfunctions. In order to eliminate variations in other aspects of the genetic background, we established the isogenic control of induced pluripotent stem cells (iPSCs) for the identification of the pathogenetic factors for FD phenotypes through CRISPR/Cas9 genomic editing. We adopted droplet digital PCR (ddPCR) to efficiently capture mutational events, thus enabling isolation of the corrected FD from FD-iPSCs. Both of these exhibited the characteristics of pluripotency and phenotypic plasticity, and they can be differentiated into endothelial cells (ECs). We demonstrated the phenotypic abnormalities in FD iPSC-derived ECs (FD-ECs), including intracellular Gb3 accumulation, autophagic flux impairment, and reactive oxygen species (ROS) production, and these abnormalities were rescued in isogenic control iPSC-derived ECs (corrected FD-ECs). Microarray profiling revealed that corrected FD-derived endothelial cells reversed the enrichment of genes in the pro-inflammatory pathway and validated the downregulation of NF-κB and the MAPK signaling pathway. Our findings highlighted the critical role of ECs in FD-associated vascular dysfunctions by establishing a reliable isogenic control and providing information on potential cellular targets to reduce the morbidity and mortality of FD patients with vascular complications.     

Neural network-based prediction of the long-term time-dependent mechanical behavior of laminated composite plates with arbitrary hygrothermal effects

Journal of Mechanical Science and Technology - Recurrent neural network (RNN)-based accelerated prediction was achieved for the long-term time-dependent behavior of viscoelastic composite laminated...     

Enhancing students’ botanical learning by using augmented reality

Universal Access in the Information Society - Scientific literacy is considered a crucial part of learners’ basic capacities. In primary schools, scientific literacy is generally cultivated...     

Heavy Water Additive in Formamidinium: A Novel Approach to Enhance Perovskite Solar Cell Efficiency

Heavy water or deuterium oxide (D₂O) comprises deuterium, a hydrogen isotope twice the mass of hydrogen. Contrary to the disadvantages of deuterated perovskites, such as shorter recombination lifetimes and lower/invariant efficiencies, the serendipitous effect of D₂O as a beneficial solvent additive for enhancing the power conversion efficiency (PCE) of triple-A cation (cesium (Cs)/methylammonium (MA)/formaminidium (FA)) perovskite solar cells from ≈19.2% (reference) to 20.8% (using 1 vol% D₂O) with higher stability is reported. Ultrafast optical spectroscopy confirms passivation of trap states, increased carrier recombination lifetimes, and enhanced charge carrier diffusion lengths in the deuterated samples. Fourier transform infrared spectroscopy and solid-state NMR spectroscopy validate the N–H₂ group as the preferential isotope exchange site. Furthermore, the NMR results reveal the induced alteration of the FA to MA ratio due to deuteration causes a widespread alteration to several dynamic processes that influence the photophysical properties. First-principles density functional theory calculations reveal a decrease in PbI₆ phonon frequencies in the deuterated perovskite lattice. This stabilizes the PbI₆ structures and weakens the electron–LO phonon (Fröhlich) coupling, yielding higher electron mobility. Importantly, these findings demonstrate that selective isotope exchange potentially opens new opportunities for tuning perovskite optoelectronic properties.     

Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor

A semiconductor distributor that plays a third-party role in the supply chain will buy diverse components from different suppliers, warehouse and resell them to a number of electronics manufacturers with vendor-managed inventories, while suffering both risks of oversupply and shortage due to demand uncertainty. However, demand fluctuation and supply chain complexity are increasing due to shortening product life cycle in the consumer electronics era and long lead time for capacity expansion for high-tech manufacturing. Focusing realistic needs of a leading distributor for semiconductor components and modules, this study aims to construct a UNISON framework based on deep reinforcement learning (RL) for dynamically selecting the optimal demand forecast model for each of the products with the corresponding demand patterns to empower smart production for Industry 3.5. Deep RL that integrates deep learning architecture and RL algorithm can learn successful policies from the dynamic and complex real world. The reward function mechanism of deep RL can reduce negative impact of demand uncertainty. An empirical study was conducted for validation showing practical viability of the proposed approach. Indeed, the developed solution has been in real settings.     

Bayesian network for integrated circuit testing probe card fault diagnosis and troubleshooting to empower Industry 3.5 smart production and an empirical study

Journal of Intelligent Manufacturing - Probe card that serves as the carrier of die and the transmitter of information is an indispensable test interface for integrated circuit testing. The probe...     

Daily intake of TBT, Cu, Zn, Cd and As for fishermen in Taiwan

The consumption of contaminated seafood has been reported as an important route of human exposure to metals in Taiwan. We consider the concentrations of TBT, Cu, Zn, Cd, As, and the consumption of oysters of Taiwanese to be the important information related to public health in Taiwan. Therefore, the aim of this study was to evaluate the public health risks associated with TBT, Cu, Zn, Cd and As from shellfish for the general population and fishermen of Taiwan. In general, TBT concentrations in various oysters ranging from 0.32 to 1.51 microg/g dry wt. varied with sampling locations. The highest TBT, Cu, and Zn geometric mean (GM) concentrations in oysters of 1.51, 1180 and 1567 microg/g dry wt. were obtained from the Hsiangshan coastal area. The values of oyster consumption for fishermen were 94.1 and 250 g/day for typically and maximally exposed individuals, respectively. In particular, the highest intake (250 g/day) from fishermen was almost two times greater than that of the general population (139 g/day). The THQ (target hazard quotient) values of Hsiangshan's fishermen are 3.87 and 20.50 for TBT and Cu for maximally exposed individuals are higher than other oyster culture areas. It is interesting that those consuming oysters from Hsiangshan, Lukang, Taishi caused abnormally high THQs of TBT and other metals (100% over 1.0), and TBT was attributed to only 3-21% of the total THQs in different fishermen of Taiwan. Our results suggest that current environmental levels of TBT and other metals are associated with a significant potential threat to human health for fishermen resident in coastal areas of Taiwan.     

Smoke development at different energy flux levels in an NBS smoke density chamber

An automatically controlled high-energy flux heater has been developed and utilized in an NBS Smoke Density Chamber.