Analysis of information diffusion for threshold models on arbitrary networks

Diffusion of information via networks has been extensively studied for decades. We study the general threshold model that embraces most of the existing models for information diffusion. In this paper, we first analyze diffusion processes under the linear threshold model, then generalize it into the general threshold model. We give a closed formula for estimating the final cascade size for those models and prove that the actual final cascade size is concentrated around the estimated value, for any network structure with node degrees ω(log n), where n is the number of nodes. Our analysis analytically explains the tipping point phenomenon that is commonly observed in information diffusion processes. Based on the formula, we devise an efficient algorithm for estimating the cascade size for general threshold models on any network with any given initial adopter set. Our algorithm can be employed as a subroutine for numerous algorithms for diffusion analysis such as influence maximization problem. Through experiments on real-world and synthetic networks, we confirm that the actual cascade size is very close to the value computed by our formula and by our algorithm, even when the degrees of the nodes are not so large

The development of digital histopathology platform using quantitative phase imaging and artificial intelligence

Here, we propose a portable, multimodal, fully-automated digital histopathology platform based on quantitative phase imaging (QPI) and artificial intelligence (AI). Our system clearly visualized cells and tissues of histology slides without labeling at various magnifications up to 40x. It was also built as small form factor and operated by wireless control of the custom-built Android application considered mobility and user-interface. Moreover, our system equipped AI guidance which converted quantitative phase images to conventional H&E stained brightfield images with high accuracy. With validation tests on several tissues, we confirmed that our device has competitive performance over traditional methods in histopathologic works

<i>Deionococcus proteotlycius</i> Genomic Library Exploration Enhances Oxidative Stress Resistance and Poly-3-hydroxybutyrate Production in Recombinant <i>Escherichia coli</i>

Cell growth is inhibited by abiotic stresses during industrial processes, which is a limitation of microbial cell factories. Microbes with robust phenotypes are critical for its maximizing the yield of the target products in industrial biotechnology. Currently, there are several reports on the enhanced production of industrial metabolite through the introduction of Deinococcal genes into host cells, which confers cellular robustness. Deinococcus is known for its unique genetic function thriving in extreme environments such as radiation, UV, and oxidants. In this study, we established that Deinococcus proteolyticus showed greater resistance to oxidation and UV-C than commonly used D. radiodurans. By screening the genomic library of D. proteolyticus, we isolated a gene (deipr_0871) encoding a response regulator, which not only enhanced oxidative stress, but also promoted the growth of the recombinant E. coli strain. The transcription analysis indicated that the heterologous expression of deipr_0871 upregulated oxidative-stress-related genes such as ahpC and sodA, and acetyl-CoA-accumulation-associated genes via soxS regulon. Deipr_0871 was applied to improve the production of the valuable metabolite, poly-3-hydroxybutyrate (PHB), in the synthetic E. coli strain, which lead to the remarkably higher PHB than the control strain. Therefore, the stress tolerance gene from D. proteolyticus should be used in the modification of E. coli for the production of PHB and other biomaterial

Factors Affecting Zero-Waste Behaviours of College Students

This study evaluated the recognition and attitude toward microplastic and zero waste among college students and investigated the factors influencing their zero-waste behaviours. The study was conducted from 20 August 2021 to 10 September 2021, including students at a university in G metropolitan city, Republic of Korea. A total of 196 data were analysed. Statements were developed to verify how the use of disposables and the recognition, attitude, and behaviours related to zero waste were affected during the COVID-19 pandemic. Family type and usage of disposables were the factors affecting zero-waste behaviour in Model 1. In Model 2, which included the subcategory of zero-waste recognition, the health effects of microplastics and environmental preservation were significant factors. In Model 3, which included the subcategory of zero-waste attitude, the health effects of microplastics (&beta; = 0.149, p = 0.016), use of eco-friendly products (&beta; = 0.342, p &lt; 0.001), and environmental preservation (&beta; = 0.317, p &lt; 0.001) were significant factors. The use of plastic products increased dramatically during the COVID-19 pandemic. Research and education are needed to promote zero-waste behaviours with a focus on microplastics. Raising awareness of the health effects of microplastics can enhance the effectiveness of education

Reactive Disperse Dyes Bearing Various Blocked Isocyanate Groups for Digital Textile Printing Ink

Wastewater management is of considerable economic and environmental importance for the dyeing industry. Digital textile printing (DTP), which is based on sublimation transfer and does not generate wastewater, is currently being explored as an inkjet-based method of printing colorants onto fabric. It finds wide industrial applications with most poly(ethylene terephthalate) (PET) and nylon fibers. However, for additional industrial applications, it is necessary to use natural fibers, such as cotton. Therefore, to expand the applicability of DTP, it is essential to develop a novel reactive disperse dye that can interact with the fabric. In this study, we introduced a blocked isocyanate functional group into the dye to enhance binding to the fabric. The effect of sublimation transfer on fabrics as a function of temperature was compared using the newly synthesized reactive disperse dyes with different blocking groups based on pyrazole derivatives, such as pyrazole (Py), di-methylpyrazole (DMPy), and di-tert-butylpyrazole (DtBPy). Fabrics coated with the new reactive disperse dyes, including PET, nylon, and cotton, were printed at 190 °C, 200 °C, and 210 °C using thermal transfer equipment. In the case of the synthesized DHP-A dye on cotton at 210 °C, the color strength was 2.1, which was higher than that of commercial dyes and other synthesized dyes, such as DMP-A and DTP-A. The fastness values of the synthesized DHP-A were measured on cotton, and it was found that the washing and light fastness values on cotton are higher than those of commercial dyes. This study confirmed the possibility of introducing isocyanate groups into reactive disperse dyes