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The intention of this paper is to analyze the properties of coral aggregate concrete (CAC) that is reinforced by alkali-resistant glass fibers (ARGF) and the bond performance with BFRP (basalt fiber reinforced polymer) bars. Two types of ARGF, denoted by Type A and Type B with different manufacturing technologies and fiber lengths, are used in the test. Tests of compressive strength, splitting tensile strength, and flexural performance were performed on ARGF-CAC with four different contents for the two types of ARGF. It is found that the cubic compressive strength is slightly reduced when the fiber volume fraction exceeds 0.5%, but almost keeps invariable if the fiber content further increases. However, the tensile strength, residual strength retention and flexural toughness are improved as more ARGFs are added into CAC, and even higher with Type B ARGF addition. The optimized volume fraction is 1.5% for both the two types of ARGF based on the evaluation of the workability and mechanical performance. Moreover, central pull-out test was performed to study the bond properties of ARGF-CAC with BFRP bars. It is found that both the maximum average bond stress and residual frictional stress are generally reduced as the bond length is longer. The addition of Type B ARGFs can significantly improve the bond strength; however, the Type A ARGFs seem to have marginal effect.Cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) is one of the strongest diabetes loci identified to date; evidence suggests that it plays an important role in insulin secretion. Dietary factors that affect insulin demand might enhance the risk of diabetes associated with CDKAL1 variants. Our aim was to examine the interactions between dietary protein and fat intake and CDKAL1 genetic variants in relation to the risk of diabetes in Korean adults. Single nucleotide polymorphisms (SNPs) were selected with a genome-wide association study (GWAS) for diabetes after adjustment for age, gender, and examination site. Using data from the Health Examinees (HEXA) Study of the Korean Genome and Epidemiology Study (KoGES), 3988 middle-aged Korean adults between 40-76 years of age (2034 men and 1954 women) were included in the study. Finally, rs7756992 located within the CDKAL1 gene region was selected from GWAS (p-value less then 5 × 10-8). [https://www.selleckchem.com/products/bi-d1870.html Selleckchem BI-D1870] Multivariable logistic regression models were used to evaluate the interactions between genotypes and dietary protein and fat intake in relation to diabetes risk after adjustment for age, gender, BMI, waist circumference, physical activity, smoking status, drinking habits, and examination site. Significant interactions between CDKAL1 rs7756992 and dietary protein and fat intake for the risk of diabetes were observed in men (p-value less then 0.05). In women, significant interactions between dietary protein and fat intake and CDKAL1 variants (rs7756992) were associated with increased risk of diabetes (p-value less then 0.05). Dietary protein and fat intake interacted differently with CDKAL1 variants in relation to the risk of diabetes in Korean adults of both genders. These findings indicate that CDKAL1 variants play a significant role in diabetes and that dietary protein and fat intake could affect these associations.With the rapid development and popularization of Internet of Things (IoT) devices, an increasing number of cyber-attacks are targeting such devices. It was said that most of the attacks in IoT environments are botnet-based attacks. Many security weaknesses still exist on the IoT devices because most of them have not enough memory and computational resource for robust security mechanisms. Moreover, many existing rule-based detection systems can be circumvented by attackers. In this study, we proposed a machine learning (ML)-based botnet attack detection framework with sequential detection architecture. An efficient feature selection approach is adopted to implement a lightweight detection system with a high performance. The overall detection performance achieves around 99% for the botnet attack detection using three different ML algorithms, including artificial neural network (ANN), J48 decision tree, and Naïve Bayes. The experiment result indicates that the proposed architecture can effectively detect botnet-based attacks, and also can be extended with corresponding sub-engines for new kinds of attacks.Contamination of the water and sediment with per- and polyfluoroalkyl substances (PFAS) was studied for the lake impacted by the release of PFAS-containing aqueous film forming foam (AFFF). PFAS concentrations were analyzed in lake water and sediment core samples. ΣPFAS concentrations were in the range of 95-100 ng L-1 in the lake water and 3.0-61 µg kg-1 dry weight (dw) in sediment core samples, both dominated by perfluorohexane sulfonate, perfluorooctane sulfonate; 62 fluortelomer sulfonate was inconsistently present in water and sediment core samples. The sediment-water partitioning coefficients (log Kd) were estimated and ranged 0.6-2.3 L kg-1 for individual perfluoroalkyl carboxylates (PFCAs) and 0.9-5.6 L kg-1 for individual perfluoroalkane sulfonates (PFSAs). The influence of the sediment inorganic content and organic matter on PFAS distribution was investigated. In studied sediments, the mineral content (corresponding to less then 5% of the bulk media mass) was mainly represented by sulfur, iron and calcium. The PFAS distribution was found strongly connected to the sediment mineral content (i.e., Fe, Pb, Rb and As), whereas the sediment organic carbon content did not to have a direct influence on the PFAS distribution. The aim of this study was to improve our understanding of the PFAS distribution in the natural heterogeneous media.Indole derivatives such as isatin (a natural compound), cemtirestat, stobadine, and its derivatives (synthetic compounds) are known to have numerous positive effects on human health due to regulation of oxidative status. The aim of the study was to assess radical scavenging capacities of these compounds and explore their potential protective effects against reactive oxygen species formed during Cu(II) ions and ascorbate-induced degradation of high-molar-mass hyaluronan. Based on the IC50 values determined by the ABTS assay, the most effective compound was SM1M3EC2·HCl reaching the value ≈ 11 µmol/L. The lowest IC50 value reached in the DPPH assay was reported for cemtirestat ≈ 3 µmol/L. Great potency of inhibition of hyaluronan degradation was shown by cemtirestat, followed by isatin even at low concentration 10 µmol/L. On the other hand, stobadine·2HCl had also a protective effect on hyaluronan degradation, however at greater concentrations compared to cemtirestat or isatin. SME1i-ProC2·HCl reported to be a less effective compound and SM1M3EC2·HCl can be considered almost ineffective compared to stobadine·2HCl.