Improvements in structural and optical properties of wafer-scale hexagonal boron nitride film by post-growth annealing

Remarkable improvements in both structural and optical properties of wafer-scale hexagonal boron nitride (h-BN) films grown by metal-organic chemical vapor deposition (MOCVD) enabled by high-temperature post-growth annealing is presented. The enhanced crystallinity and homogeneity of the MOCVD-grown h-BN films grown at 1050 degrees C is attributed to the solid-state atomic rearrangement during the thermal annealing at 1600 degrees C. In addition, the appearance of the photoluminescence by excitonic transitions as well as enlarged optical band gap were observed for the post-annealed h-BN films as direct consequences of the microstructural improvement. The post-growth annealing is a very promising strategy to overcome limited crystallinity of h-BN films grown by typical MOCVD systems while maintaining their advantage of multiple wafer scalability for practical applications towards two-dimensional electronics and optoelectronics.11Ysciescopu

K-Means Clustering-Based Safety System in Large-Scale Industrial Site Using Industrial Wireless Sensor Networks

A large number of workers and heavy equipment are used in most industrial sizes, and the prevention of safety accidents is one of the most important issues. Therefore, although a number of systems have been proposed to prevent accidents, existing studies assume that workers are gathered in some areas. These assumptions are not suitable for large-scale industrial sites in which workers form as a group and work in a large area. In other words, in a large-scale industrial site, existing schemes are unsuitable for the timely notifying of warnings of threats, and excessive energy is consumed. Therefore, we propose a k-means clustering-based safety system for a large-scale industrial site. In the proposed scheme, workers deployed over a large area are divided into an appropriate number of groups, and threat notification is delivered by a multicasting tree toward each cluster. The notification to workers is delivered through local flooding in each cluster. The simulation results show that the system is able to deliver the notification within a valid time, and it is energy efficient compared to the existing scheme

K-Means Clustering-Based Safety System in Large-Scale Industrial Site Using Industrial Wireless Sensor Networks

A large number of workers and heavy equipment are used in most industrial sizes, and the prevention of safety accidents is one of the most important issues. Therefore, although a number of systems have been proposed to prevent accidents, existing studies assume that workers are gathered in some areas. These assumptions are not suitable for large-scale industrial sites in which workers form as a group and work in a large area. In other words, in a large-scale industrial site, existing schemes are unsuitable for the timely notifying of warnings of threats, and excessive energy is consumed. Therefore, we propose a k-means clustering-based safety system for a large-scale industrial site. In the proposed scheme, workers deployed over a large area are divided into an appropriate number of groups, and threat notification is delivered by a multicasting tree toward each cluster. The notification to workers is delivered through local flooding in each cluster. The simulation results show that the system is able to deliver the notification within a valid time, and it is energy efficient compared to the existing scheme

Rheological Characterization of Powder Mixture Including a Space Holder and Its Application to Metal Injection Molding

Metal injection molding (MIM) with the space holder technique is becoming one of the important fabrication methods for a net-shape production of micro-sized, porous, complex-shaped metal parts. For a successful injection molding step, rheological behavior of MIM feedstock is essential, which includes peculiar characteristics, such as a wall slip phenomenon. SUS 316L stainless steel powder, binder systems (paraffin wax, polypropylene, polyethylene, stearic acid) and three different sizes of spherically-shaped polymethyl methacrylate (PMMA) as a space-holder were used for this study. The porosity was controlled by varying the volume fraction of the space holder and a total of six different feedstocks were prepared. Rheological characteristics of the feedstock was investigated, especially on viscosities, including wall slip quantification by using a capillary rheometer. By thermogravimetric analysis, the debinding process for completely removing the space holder was proposed. Finally, the shrinkage and porosity of the tensile specimen produced through the sintering process were analyzed and the ultimate tensile strength was obtained

Characterization of Mesenchymal Stem Cells Derived from Patients with Cerebellar Ataxia: Downregulation of the Anti-Inflammatory Secretome Profile

Mesenchymal stem cell (MSC) therapy is a promising alternative approach for the treatment of neurodegenerative diseases, according to its neuroprotective and immunomodulatory potential. Despite numerous clinical trials involving autologous MSCs, their outcomes have often been unsuccessful. Several reports have indicated that MSCs from patients have low capacities in terms of the secretion of neurotrophic or anti-inflammatory factors, which might be associated with cell senescence or disease severity. Therefore, a new strategy to improve their capacities is required for optimal efficacy of autologous MSC therapy. In this study, we compared the secretory potential of MSCs among cerebellar ataxia patients (CA-MSCs) and healthy individuals (H-MSCs). Our results, including secretome analysis findings, revealed that CA-MSCs have lower capacities in terms of proliferation, oxidative stress response, motility, and immunomodulatory functions when compared with H-MSCs. The functional differences were validated in a scratch wound healing assay and neuron-glia co-cultures. In addition, the neuroprotective and immunoregulatory protein follistatin-like 1 (FSTL1) was identified as one of the downregulated proteins in the CA-MSC secretome, with suppressive effects on proinflammatory microglial activation. Our study findings suggest that targeting aspects of the downregulated anti-inflammatory secretome, such as FSTL1, might improve the efficacy of autologous MSC therapy for CA