Safety distance for preventing hot particle ignition of building insulation materials

Trajectories of flying hot particles were predicted in this work, and the temperatures during the movement were also calculated. Once the particle temperature decreased to the critical temperature for a hot particle to ignite building insulation materials, which was predicted by hot-spot ignition theory, the distance particle traveled was determined as the minimum safety distance for preventing the ignition of building insulation materials by hot particles. The results showed that for sphere aluminum particles with the same initial velocities and diameters, the horizontal and vertical distances traveled by particles with higher initial temperatures were higher. Smaller particles traveled farther when other conditions were the same. The critical temperature for an aluminum particle to ignite rigid polyurethane foam increased rapidly with the decrease of particle diameter. The horizontal and vertical safety distances were closely related to the initial temperature, diameter and initial velocity of particles. These results could help update the safety provision of firework display

Histogram Estimation for Optimal Filter Skyline Query Processing in Wireless Sensor Networks

The skyline query processing technique plays an increasingly important role for multicriteria decision making applications in wireless sensor networks. The technique of saving energy to prolong the lifetime of sensor nodes is one of the dominating challenges to resource-constrained wireless sensor networks. In this paper, we propose an energy-efficient skyline query processing algorithm, called the histogram filter based algorithm (HFA), to efficiently retrieve skyline results from a sensor network. First, we use historical data at the base station to construct histograms for further estimating the probability density distributions of the sensor data. Second, the dominance probability of each tuple is computed based on the histograms, and the optimal tuple which has the largest possibility of dominance/filtering capability is obtained using in-network aggregation approach. After that, the base station broadcasts the optimized tuple as the global filter to each sensor node. Then, the tuples which do not satisfy the skyline query semantics are discarded to avoid unnecessary data transmissions. An extensive experimental study demonstrates that the proposed HFA algorithm performs more efficiently than existing algorithms on reducing data transmissions during skyline query processing, which saves the energy and prolongs the lifetime of wireless sensor networks

Adaptive Filter Updating for Energy-Efficient Top- Queries in Wireless Sensor Networks Using Gaussian Process Regression

Adopting filtering mechanism of dynamic filtering windows installed on sensor nodes to process top- k queries is an important research direction in wireless sensor networks. The mechanism can reduce transmissions of redundant data by utilizing filters. However, existing algorithms based on filters consume a vast amount of energy due to filter updating. In this paper, an energy-efficient top- k query technique based on adaptive filters is proposed. Due to updating filters consuming a large amount of energy, an algorithm named FUGPR based on Gaussian process regression to process top- k queries is provided for saving energy. When the filters change, the sensor readings are predicted to calculate the updating costs of filters; then FUGPR decides whether the filters need to be updated or not. Thus, the energy consumption for updating filters is decreased. Experimental results show that our approach can reduce energy consumption efficiently for updating filters on two distinct real datasets

Prediction-Based Filter Updating Policies for Top- Monitoring Queries in Wireless Sensor Networks

Processing top- k query in an energy-efficient manner is an important topic in wireless sensor networks. Redundant data transmitting between base station and sink node is avoided by installing filters on sensor nodes; thus, communication overhead between base station and sensor nodes is decreased. However, existing algorithms such as FILA, and DAFM consume much energy when updating the filter window. In this paper, we propose a new top- k algorithm named PreFU which is based on prediction models to update window parameters of filters. PreFU can predict the next s step sensor values based on time series predicting models which can be built by historical data. By estimating the cost of updating window parameters based on predicted sensor values, updates of filter window parameters can be reduced. Thus, the cost of updating window parameters is decreased. Experimental results show that our PreFU algorithm is more energy-efficient than existing algorithms while guaranteeing the accuracy of top- k query results

Combinational biosynthesis of phycocyanobilin using genetically-engineered Escherichia coli

Genes of the key enzymes for phycocyanobilin (PCB) biosynthesis were cloned into E. coli and combinationally expressed to produce phycocyanobilin, with autologous heme as substrate. Culture conditions were optimized to achieve similar to 3 mg PCB/l. A protocol for the purification of recombinant phycocyanobilin was established using solvent extraction combined with chromatography, which resulted in a final yield of similar to 0.3 mg PCB/l with a purity > 95 %. Recombinant phycocyanobilin could scavenge hydroxyl radicals with an EC50 of 0.1 mu M.Genes of the key enzymes for phycocyanobilin (PCB) biosynthesis were cloned into E. coli and combinationally expressed to produce phycocyanobilin, with autologous heme as substrate. Culture conditions were optimized to achieve similar to 3 mg PCB/l. A protocol for the purification of recombinant phycocyanobilin was established using solvent extraction combined with chromatography, which resulted in a final yield of similar to 0.3 mg PCB/l with a purity > 95 %. Recombinant phycocyanobilin could scavenge hydroxyl radicals with an EC50 of 0.1 mu M

Esterification synthesis of ethyl oleate catalyzed by Brønsted acid–surfactant-combined ionic liquid

3-(N,N-dimethyldodecylammonium) propanesulfonic acid hydrogen sulfate ([SB3-12][HSO4]), a Brønsted acidic-surfactant-combined ionic liquid, was successfully prepared from cheap materials and applied to catalyze the esterification synthesis of ethyl oleate using oleic acid and ethanol as precursors. The produced condition of oleic acid ethyl ester was optimized including the amount of catalyst, reaction time, molar ratio and content of water. Under optimal condition (ethanol to oleic acid molar ratio, 3:1; amount of the catalyst, 5 wt% (based on the mass of oleic acid); reaction time, 3 h; reaction temperature, 78°C; and content of water, 0.4 wt%), the conversion of oleic acid was over 97%. Due to the reverse micelles formed by [SB3-12][HSO4], the micro-reactor not only promoted the esterification toward the desired side of the ester, but also avoided the hydrolysis of ester. Moreover, the [SB3-12][HSO4] could be reused by a simple decantation separating process and noticeable loss of catalytic activity was not observed even after being recycled for five cycles. The green system offers several advantages, such as excellent yield, efficient catalytic activity, free-solvent and simple operational procedure

An Aptamer That Rapidly Internalizes into Cancer Cells Utilizes the Transferrin Receptor Pathway

Strategies to direct drugs specifically to cancer cells have been increasingly explored, and significant progress has been made toward such targeted therapy. For example, drugs have been conjugated into tumor-targeting antibodies to enable delivery directly to tumor cells. Aptamers are an attractive class of molecules for this type of drug targeting as they are high-affinity/high-specificity ligands, relatively small in size, GMP manufacturable at a large-scale, amenable to chemical conjugation, and not immunogenic. Previous work from our group revealed that an aptamer selected to internalize into human prostate cancer cells, called E3, can also target a broad range of human cancers but not normal control cells. Moreover, this E3 aptamer can deliver highly cytotoxic drugs to cancer cells as Aptamer-highly Toxic Drug Conjugates (ApTDCs) and inhibit tumor growth in vivo. Here, we evaluate its targeting mechanism and report that E3 selectively internalizes into cancer cells utilizing a pathway that involves transferrin receptor 1 (TfR 1). E3 binds to recombinant human TfR 1 with high affinity and competes with transferrin (Tf) for binding to TfR1. In addition, knockdown or knockin of human TfR1 results in a decrease or increase in E3 cell binding. Here, we reported a molecular model of E3 binding to the transferrin receptor that summarizes our findings

Sea Cucumber Peptides Ameliorate DSS-Induced Ulcerative Colitis: The Role of the Gut Microbiota, the Intestinal Barrier, and Macrophage Polarization

The incidence of ulcerative colitis (UC) is increasing annually. There are few treatments for UC patients, and some drugs have serious side effects. Sea cucumber peptide (SCP) has anti-inflammatory, antioxidant and other biological activities, and various sea cucumber species are in pharmaceutical development. However, relevant studies on the effects of SCP on UC progression are still lacking. In this study, a mouse model of acute colitis was induced by 3% dextran sulfate (DSS), and the effect of 500 mg/kg SCP on colitis was investigated. The results showed that SCP can alleviate DSS-induced colon damage and intestinal barrier damage. SCP significantly inhibited the expression of inflammatory factors and oxidative stress in UC mice. SCP reversed the intestinal microbiota dysregulation induced by DSS, inhibited the growth of Sutterella, Prevotella_9 and Escherichia-Shigella harmful bacteria, and increased the abundance of Lachnospiraceae_NK4A136_group. At the same time, SCP treatment significantly inhibited the LPS-induced polarization of M1 macrophages, which may be mediated by two monopeptides, IPGAPGVP and TGPIGPPGSP, via FPR2. In conclusion, SCP can protect against colitis by modulating the intestinal microbiota composition and the intestinal barrier and inhibiting the polarization of M1 macrophages