A study on the factors that affect the adoption of Smart Water Grid

Due to recent climate changes that accompany drastic changes in water recycle process, extreme floods and droughts are occurring frequently throughout the world. In response to these events, Smart Water Management that refers to implement intelligent water information systems by IT convergence is considered as a new paradigm. In this study, we seek to explore the Smart Water Management, especially the adoption of Smart Water Grid Technology. We aim to review previous studies to identify factors that influence the adoption of the Smart Water Grid and to analyze the importance and priority of the factors affecting Smart Water Grid adoption, thereby presenting the successful adoption measures for Smart Water Grid in Korea. This study set a research model with the influencing factors in relation to the adoption of new IT technologies that were identified through the literature reviews of previous studies based on the TOE framework. This study also conducted empirical analysis of the findings and found out that the issue of privacy protection and security due to hacker’s attack would be emerged as a significant risk factor.     

Multiple Decision Expert Systems for Performance Analysis of a Boiler System

Artificial neural networks (ANN)-based multiple decision expert systems (MDES) were developed for assessing the performance of a boiler system. Different configurations of ANN were used with different decision combination methods, including a neural combiner, to propose the model. The model was developed using the plant data collected over a period of five months to predict steam temperature, pressure, and mass flow rate, using feed water pressure, feed water temperature, conveyor speed, and incinerator exit temperature as the input parameters. The predictive capability of the model is evaluated in terms of both correlation coefficient (R) and mean absolute percentage error (MAPE). The results observed from this work demonstrate that neural combiner and ANN-based MDES can efficiently predict the data on steam properties consistently, and that the model can serve as an efficient tool for monitoring boiler behavior under real-time conditions. Superiority of the proposed model over others under various scenarios is also demonstrated.     

Anticipating infectious disease re-emergence and elimination: a test of early warning signals using empirically based models

Timely forecasts of the emergence, re-emergence and elimination of human infectious diseases allow for proactive, rather than reactive, decisions that save lives. Recent theory suggests that a generic feature of dynamical systems approaching a tipping point—early warning signals (EWS) due to critical slowing down (CSD)—can anticipate disease emergence and elimination. Empirical studies documenting CSD in observed disease dynamics are scarce, but such demonstration of concept is essential to the further development of model-independent outbreak detection systems. Here, we use fitted, mechanistic models of measles transmission in four cities in Niger to detect CSD through statistical EWS. We find that several EWS accurately anticipate measles re-emergence and elimination, suggesting that CSD should be detectable before disease transmission systems cross key tipping points. These findings support the idea that statistical signals based on CSD, coupled with decision-support algorithms and expert judgement, could provide the basis for early warning systems of disease outbreaks.     

Dual-wavelength cascaded Raman fibre laser

Dual-wavelength lasing at 1480 and 1500 nm has been demonstrated from a cascaded Raman fibre laser with a WDM coupler and two pairs of Bragg gratings. Intensity-adjustable, wavelength-tunable laser operation was achieved by tensile stress wavelength tuning of the gratings     

A formation of cobalt silicide on silicon field emitter arrays byelectrical stress

A novel process utilizing electrical stress is proposed for the formation of Co silicide on single crystal silicon (c-Si) FEAs to improve the field emission characteristics. Co silicide FEAs formed by electrical stress (ES) exhibited a significant improvement in turn-on voltage and emission current compared with c-Si FEAs. The improvement mainly comes from the lower effective work function of Co silicide and less blunting of tips during silicidation by electrical stress in an ultra high vacuum (UHV) environment less than 10^-8 torr     

Generalized Approach towards Secretion-Based Protein Production via Neutralization of Secretion-Preventing Cationic Substrate Residues

Many heterologous proteins can be secreted by bacterial ATP-binding cassette (ABC) transporters, provided that they are fused with the C-terminal signal sequence, but some proteins are not secretable even though they carry the right signal sequence. The invention of a method to secrete these non-secretable proteins would be valuable both for understanding the secretory physiology of ABC transporters and for industrial applications. Herein, we postulate that cationic “supercharged” regions within the target substrate protein block the secretion by ABC transporters. We also suggest that the secretion of such substrate proteins can be rescued by neutralizing those cationic supercharged regions via structure-preserving point mutageneses. Surface-protruding, non-structural cationic amino acids within the cationic supercharged regions were replaced by anionic or neutral hydrophilic amino acids, reducing the cationic charge density. The examples of rescued secretions we provide include the spike protein of SARS-CoV-2, glutathione-S-transferase, streptavidin, lipase, tyrosinase, cutinase, growth factors, etc. In summary, our study provides a method to predict the secretability and a tool to rescue the secretion by correcting the secretion-blocking regions, making a significant step in understanding the physiological properties of ABC transporter-dependent protein secretion and laying the foundation for the development of a secretion-based protein-producing platform.     

Single-Step Fast Tissue Clearing of Thick Mouse Brain Tissue for Multi-Dimensional High-Resolution Imaging

Recent advances in optical clearing techniques have dramatically improved deep tissue imaging by reducing the obscuring effects of light scattering and absorption. However, these optical clearing methods require specialized equipment or a lengthy undertaking with complex protocols that can lead to sample volume changes and distortion. In addition, the imaging of cleared tissues has limitations, such as fluorescence bleaching, harmful and foul-smelling solutions, and the difficulty of handling samples in high-viscosity refractive index (RI) matching solutions. To address the various limitations of thick tissue imaging, we developed an Aqueous high refractive Index matching and tissue Clearing solution for Imaging (termed AICI) with a one-step tissue clearing protocol that was easily made at a reasonable price in our own laboratory without any equipment. AICI can rapidly clear a 1 mm thick brain slice within 90 min with simultaneous RI matching, low viscosity, and a high refractive index (RI = 1.466), allowing the imaging of the sample without additional processing. We compared AICI with commercially available RI matching solutions, including optical clear agents (OCAs), for tissue clearing. The viscosity of AICI is closer to that of water compared with other RI matching solutions, and there was a less than 2.3% expansion in the tissue linear morphology during 24 h exposure to AICI. Moreover, AICI remained fluid over 30 days of air exposure, and the EGFP fluorescence signal was only reduced to ~65% after 10 days. AICI showed a limited clearing of brain tissue >3 mm thick. However, fine neuronal structures, such as dendritic spines and axonal boutons, could still be imaged in thick brain slices treated with AICI. Therefore, AICI is useful not only for the three-dimensional (3D) high-resolution identification of neuronal structures, but also for the examination of multiple structural imaging by neuronal distribution, projection, and gene expression in deep brain tissue. AICI is applicable beyond the imaging of fluorescent antibodies and dyes, and can clear a variety of tissue types, making it broadly useful to researchers for optical imaging applications.     

Characterization of the Secretome of a Specific Cell Expressing Mutant Methionyl-tRNA Synthetase in Co-Culture Using Click Chemistry

Co-culture system, in which two or more distinct cell types are cultured together, is advantageous in that it can mimic the environment of the in vivo niche of the cells. In this study, we presented a strategy to analyze the secretome of a specific cell type under the co-culture condition in serum-supplemented media. For the cell-specific secretome analysis, we expressed the mouse mutant methionyl-tRNA synthetase for the incorporation of the non-canonical amino acid, azidonorleucine into the newly synthesized proteins in cells of which the secretome is targeted. The azidonorleucine-tagged secretome could be enriched, based on click chemistry, and distinguished from any other contaminating proteins, either from the cell culture media or the other cells co-cultured with the cells of interest. In order to have more reliable true-positive identifications of cell-specific secretory bodies, we established criteria to exclude any identified human peptide matched to bovine proteins. As a result, we identified a maximum of 719 secreted proteins in the secretome analysis under this co-culture condition. Last, we applied this platform to profile the secretome of mesenchymal stem cells and predicted its therapeutic potential on osteoarthritis based on secretome analysis.     

Intratracheal Transplantation of Mesenchymal Stem Cells Attenuates Hyperoxia-Induced Microbial Dysbiosis in the Lungs,Brain, and Gut in Newborn Rats

We attempted to determine whether intratracheal (IT) transplantation of mesenchymal stem cells (MSCs) could simultaneously attenuate hyperoxia-induced lung injuries and microbial dysbiosis of the lungs, brain, and gut in newborn rats. Newborn rats were exposed to hyperoxia (90% oxygen) for 14 days. Human umbilical cord blood-derived MSCs (5 × 10⁵) were transplanted via the IT route on postnatal day (P) five. At P14, the lungs were harvested for histological, biochemical, and microbiome analyses. Bacterial 16S ribosomal RNA genes from the lungs, brain, and large intestine were amplified, pyrosequenced, and analyzed. IT transplantation of MSCs simultaneously attenuated hyperoxia-induced lung inflammation and the ensuing injuries, as well as the dysbiosis of the lungs, brain, and gut. In correlation analyses, lung interleukin-6 (IL-6) levels were significantly positively correlated with the abundance of Proteobacteria in the lungs, brain, and gut, and it was significantly inversely correlated with the abundance of Firmicutes in the gut and lungs and that of Bacteroidetes in the lungs. In conclusion, microbial dysbiosis in the lungs, brain, and gut does not cause but is caused by hyperoxic lung inflammation and ensuing injuries, and IT transplantation of MSCs attenuates dysbiosis in the lungs, brain, and gut, primarily by their anti-oxidative and anti-inflammatory effects.