Effects of upholstery materials on the burning behavior of real‐scale residential upholstered furniture mock‐ups

Fire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF.     

Continuous Flow Fabrication of Block Copolymer–Grafted Silica Micro‐Particles in Environmentally Friendly Water/Ethanol Media

Polymer‐grafted inorganic particles (PGIPs) are attractive building blocks for numerous chemical and material applications. Surface‐initiated controlled radical polymerization (SI‐CRP) is the most feasible method to fabricate PGIPs. However, a conventional in‐batch reaction still suffers from several disadvantages, including time‐consuming purification processes, low grafting efficiency, and possible gelation problems. Herein, a facile method is demonstrated to synthesize block copolymer–grafted inorganic particles, that is, poly(poly(ethylene glycol) methyl ether methacrylate) (PPEGMEMA)‐b‐poly(N‐isopropylacrylamide) (PNIPAM)–grafted silica micro‐particles using continuous flow chemistry in an environmentally friendly aqueous media. Immobilizing the chain transfer agent and subsequent SI‐CRP can be accomplished sequentially in a continuous flow system, avoiding multi‐step purification processes in between. The chain length (MW) of the grafted polymers is tunable by adjusting the flow time or monomer concentration, and the narrower molar mass dispersity (Р< 1.4) of the grafted polymers reveals the uniform polymer chains on the particles. Moreover, compared with the in‐batch reaction at the same condition, the continuous system also suppresses possible gelation problems.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

Isolation of antimicrobial agent from the marine algae Cystoseira hakodatensis

Cystoseira hakodatensis is an unutilised brown algae belonging to family Sargassaceae. A crude methanol extract from the algae showed inhibitory effects on the growths of Bacillus cereus and Bacillus licheniformis. To isolate the major antimicrobial agent, a sequential active‐guided isolation procedure was applied: liquid–liquid extraction, column chromatography and bio‐autography. A marked antimicrobial agent (active α) was isolated in hydrophobic fraction and was determined to phenolics without carbohydrates and proteins by phytochemical test. Regarding the antimicrobial potential, the isolated active α showed better inhibitory effects against B. cereus and B. licheniformis at 2 and 4 times of lower concentrations (62.5 and 31.3 μg mL^?1) in comparison with epigallocatechin gallate. These results showed that C. hakodatensis is a potential source of antimicrobial agent capable of preventing the growth of the two bacteria.     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

Low-cost and two-cycle hardware structures of PRINCE lightweight block cipher

In this paper, low-cost and two-cycle hardware structures of the PRINCE lightweight block cipher are presented. In the first structure, we proposed an area-constrained structure, and in the second structure, a high-speed implementation of the PRINCE cipher is presented. The substitution box (S-box) and the inverse of S-box (S-box⁻¹) blocks are the most complex blocks in the PRINCE cipher. These blocks are designed by an efficient structure with low critical path delay. In the low-cost structure, the S-boxes and S-boxes⁻¹ are shared between the round computations and the intermediate step of PRINCE cipher. Therefore, the proposed architecture is implemented based on the lowest number of computation resources. The two-cycle implementation of PRINCE cipher is designed by a processing element (PE), which is a general and reconfigurable element. This structure has a regular form with the minimum number of the control signal. Implementation results of the proposed structures in 180-nm CMOS technology and Virtex-4 and Virtex-6 FPGA families are achieved. The proposed structures, based on the results, have better critical path delay and throughput compared with other's related works.     

测井资料在优选压裂层位中的应用

压裂是低孔、低渗油层改造的主要增产措施。根据常规测井资料、岩石物理实验分析数据及试油成果。研究储层四性关系，确定区块的低孔、低渗储层评价标准。进一步对油层进行分类，有针对性地为油层压裂提供施工层位和准确的储层参数。通过商543区块实例，阐述了选择压裂层位的方法。