The basic oxygen furnace slag (BOF) was wide used in road construction, but there was a lack of characteristics in different asphalt mixtures. This study investigates the properties of hot-mixed asphalt (HMA) containing stone mastic asphalt (SMA), porous asphalt (PA) and dense-graded BOF as a partial substitution for natural aggregates. The purpose of this study is to evaluate various BOF slag contents in the asphalt mixtures would affect the cooling behavior after compaction. Asphalt mixture specimens contained 0%, 20%, 40% and 60% BOF slag, respectively, as coarse aggregate. Test results showed that BOF slag has a lipophilic property, so it can be adsorbed by asphalt cement, thereby reducing the cost of asphalt. The stability value of all asphalt mixtures increases with the proportion of BOF slag replacement. In addition, the voids in the mineral aggregate (VMA) value variable exhibited significant differences among asphalt mixtures, and could determine the deviation of the cooling trend of asphalt mixtures. Furthermore; it was found that the cooling procedure of the BOF slag used in dense-graded asphalt mixture takes about 100 min, and that the temperature tends to be moderate; however, it took about 120 min of cooling the SMA and PA mixture with BOF slag. In addition, the voids distribution of dense asphalt mixture was not uniform. It would result in various locations of thermal energy temperature on asphalt mixtures that were inconsistent.

This study aims to exploit the distinctive properties of carbon nanotube materials, which are particularly pronounced at the microscopic scale, by deploying fabrication techniques that allow their features to be observed macroscopically. Specifically, we aim to create a semiconductor device that exhibits flexibility and the ability to modulate its electromagnetic wave absorption frequency by means of biasing. Initially, we fabricate a sheet of carbon nanotubes through a vacuum filtration process. Subsequently, phosphorus and boron elements are separately doped into the nanotube sheet, enabling it to embody the characteristics of a PN diode. Measurements indicate that, in addition to the fundamental diode's current-voltage relationship, the device also demonstrates intriguing transmission properties under the TEM mode of electromagnetic waves. It exhibits a frequency shift of approximately 2.3125 GHz for each volt of bias change. The final result is a lightweight and flexible carbon-based semiconductor microwave filter, which can conform to curved surfaces. This feat underscores the potential of such materials for innovative and effective electromagnetic wave manipulation.

Recently, the awareness of energy conservation, carbon emission reduction, and environmental protection in Taiwan has begun to gradually improve, and bicycles have become an important vehicle for residents. In 2009, Kaohsiung began promoting public bicycle sharing. The number of users in that year amounted to 140,000. By 2015, the accumulated number of users reached nine million. This study adopted the Theory of Planned Behavior (TPB) to explore the factors influencing the behavioral intentions of public bicycle users, including the three dimensions of attitude, subjective norm, and perceived behavioral control, and probed into the relationship between the factors influencing the behavioral intentions of public bicycle users in Kaohsiung City and the dimensions. This study used a questionnaire to collect data and SPSS & AMOS for statistical analysis. The empirical results demonstrated that the most prominent factors influencing the behavioral intentions of public bicycle users in Kaohsiung City included perceived behavioral control, attitude, and subjective norm, in order. Among the influencing factors in the three dimensions, personal interests, main groups, and self-competence had a positive and significant correlation. Administrators should provide more incentives related to the three influencing factors to encourage the public in Kaohsiung City to use public bicycles more frequently as their short-distance travel mode, so as to achieve the purposes of saving energy, reducing carbon emissions, and protecting the urban environment.

In the field of machine learning, cluster analysis has always been a very important technology for determining useful or implicit characteristics in the data. However, the current mainstream cluster analysis algorithms require comprehensive analysis of the overall data to obtain the best parameters in the algorithm. As a result, handling large-scale datasets would be difficult. This research proposes a distributed related clustering mechanism for Unsupervised Learning, which assumes that if adjacent data are similar, a group can be formed by relating to more data points. Therefore, when processing data, large-scale datasets can be distributed to multiple computers, and the correlation of any two datasets in each computer can be calculated simultaneously. Later, results are processed through aggregation and filtering before assembled into groups. This method would greatly reduce the pre-processing and execution time of the dataset; in practical application, it only needs to focus on how the relevance of the data is designed. In addition, the experimental results show the accuracy, applicability, and ease of use of this method.

Melittin, a natural antimicrobial peptide, displays a broad-spectrum antimicrobial activity, which has caused increasing attention as a potential antibiotic alternative. However, melittin has not been used widely at present due to its high hemolysis and low proteolytic stability. In this study, N-terminal fatty acid was conjugated to melittin to develop new melittin-derived lipopep-tides (MDLs) for improving the limitation of melittin. Our results showed that, the antimicrobial activity of MDLs was increased by 2 to 16 times compared with native melittin, and the stability of these MDLs against trypsin and pepsin degradation was increased by 50 to 80%. Besides, the hemolytic of the MDLs decreased when the length of the carbon chain of fatty acids exceeded 10. Among them, the newly designed analog Mel-C8 showed optimal antimicrobial activity and protease stability. The antimicrobial mechanism studied revealed that the MDLs showed a rapid bactericidal effect by interacting with LPS or LTA and penetrating the bacterial cell membrane. In conclusion, we designed and synthesized a new class of MDLs with potent antimicrobial activity, high proteolytic stability, and low hemolysis through N-terminal fatty acid conjugation.

This study explored the effects of pBD114 (porcine β-defensin 114) on inflammatory response. The results in RAW264.7 cells showed that 100 μg/mL of pBD114 significantly increased the concentrations of TNFα and IL-10, and 10 μg/mL of pBD114 significantly decreased the concen-tration of TNFα in LPS-induced RAW264.7 cell cultures at 10 ng/mL. These results suggest that pBD114 can exhibit pro-inflammatory or anti-inflammatory activities under certain conditions. RNA-seq analysis was performed to gain further insight into the effects of pBD114 on the in-flammatory response. Among pBD114 promoting RAW264.7 pro-inflammatory response, pBD114 significantly up-regulated 1170 genes and down-regulated 724 genes. KEGG enrichment found that the DEGs were significantly enriched in immune- and signal-transduction-related signaling pathways. PPI and KDA analyses revealed that Bcl10 and Bcl3 were the key genes. In addition, pBD114 significantly up-regulated 12 genes and down-regulated 38 genes in the an-ti-inflammatory response. KEGG enrichment analysis revealed that the DEGs were mainly en-riched in the "Cytokine-cytokine receptor interaction" signaling pathway, and PPI and KDA analyses showed that Stat1 and Csf2 were the key genes. The results of qRT-PCR verified those of RNA-seq. In vivo mice tests also confirmed the pro- or anti-inflammatory activity of pBD114. Although the inflammatory response is a rapid and complex physiological reaction to noxious stimuli, this study found that pBD114 plays an essential role in the inflammatory response mainly by acting on genes related to immunity, signal transduction, signaling molecules, and interactions.

A novel drive current model covering the effects of source/drain voltage (VDS) and gate voltage (VGS) and incorporating drift and diffusion current on the surface channel at the nano-node level, especially beyond 28nm node is presented. The effect of the diffusion current added is more satisfactory to describe the behavior of the drive current in nano-node MOSFETs, fabricated with the atomic-layer-deposition (ALD) technology. This breakthrough in model establishment can expose the long and short channel devices together. Introducing the variables of VDS and VGS, the mixed current model more effectively and meaningfully demonstrates the drive current of MOSFETs under the operation of horizontal, vertical, or mixed electrical field. In comparison between the simulation and experimental consequences, the electrical performance is impressive. The error between both is less than 1%, better than the empirical adjustment to issue a set of drive current models.