Short Range Gigabit Wireless Communications Systems: Potentials, Challenges and Techniques

In this paper, we discuss multi-gigabits per second wireless networks in the 60GHz millimeter wave frequency band. Despite the large unlicensed bandwidth offered by the 60GHz frequency band, severe technical challenges exist towards making multi-Gbps a reality. We discuss the challenges in three different layers: PHY, MAC and the application layers. We also discuss some important technologies in overcoming these challenges, including antenna array beamforming, baseband modulation, data aggregation. The worldwide 60GHz regulatory and the ongoing standardization efforts are reviewed as well

A novel unambiguous strategy of molecular feature extraction in machine learning assisted predictive models for environmental properties

Environmental properties of compounds provide significant information in treating organic pollutants, which drives the chemical process and environmental science toward eco-friendly technology. Traditional group contribution methods play an important role in property estimations, whereas various disadvantages emerge in their applications, such as scattered predicted values for certain groups of compounds. In order to address such issues, an extraction strategy for molecular features is proposed in this research, which is characterized by interpretability and discriminating power with regard to isomers. Based on the Henry's law constant data of organic compounds in water, we developed a hybrid predictive model that integrates the proposed strategy in conjunction with a neural network framework. The structure of the predictive model is optimized using cross-validation and grid search to improve its robustness. Moreover, the predictive model is improved by introducing the plane of best fit descriptor as input and adopting k-means clustering in sampling. In contrast with reported models in the literature, the developed predictive model demonstrates improved generality, higher accuracy, and fewer molecular features used in its development

Bibliometric Analysis on the Influencing Factors of International Courses’ Effectiveness from the Perspective of Sustainable Development Education

Sustainable development education is a dynamic and developing process. In recent years, the rapid development of international courses has made great contributions to sustainable development education. The effectiveness of international courses is influenced by many factors. To promote the sustainable development of education and to improve the effectiveness of international courses, this paper studied the influencing factors on international courses by using literature analysis, system dynamics analysis, questionnaire survey, and correlation analysis methods. First, based on the literature analysis, 27 factors affecting course effectiveness were initially obtained. Second, using system dynamics to study the relationship between each factor, five additional factors were added, namely, learning motivation, social focus, lesson planning, class time, and class location. A total of 32 factors influencing course effectiveness were obtained and classified into three categories, namely, students, teachers, and external factors, and a relationship model of the 32 factors influencing course effectiveness was constructed. Finally, a questionnaire survey was conducted to quantify the 32 influencing factors, and a correlation analysis was performed on all undergraduates majoring in safety engineering enrolled in 2018 and 2019 in a university in 2019 and 2020. The results show that among the 32 influencing factors in the three categories of students, teachers, and external factors proposed, there were 7 strong correlations, 22 moderate correlations, and 3 weak correlations. All of the strong correlations belonged to the student dimension, thereby indicating that the effectiveness of international online courses is mainly influenced by student factors. In addition, these influencing factors can not only impact course effectiveness directly, but also indirectly through the interaction between factors. The relationship model of the influencing factors can provide a reference for improving the effectiveness of international programs and realizing the sustainable development research for international courses

Bibliometric Analysis on the Influencing Factors of International Courses’ Effectiveness from the Perspective of Sustainable Development Education

Sustainable development education is a dynamic and developing process. In recent years, the rapid development of international courses has made great contributions to sustainable development education. The effectiveness of international courses is influenced by many factors. To promote the sustainable development of education and to improve the effectiveness of international courses, this paper studied the influencing factors on international courses by using literature analysis, system dynamics analysis, questionnaire survey, and correlation analysis methods. First, based on the literature analysis, 27 factors affecting course effectiveness were initially obtained. Second, using system dynamics to study the relationship between each factor, five additional factors were added, namely, learning motivation, social focus, lesson planning, class time, and class location. A total of 32 factors influencing course effectiveness were obtained and classified into three categories, namely, students, teachers, and external factors, and a relationship model of the 32 factors influencing course effectiveness was constructed. Finally, a questionnaire survey was conducted to quantify the 32 influencing factors, and a correlation analysis was performed on all undergraduates majoring in safety engineering enrolled in 2018 and 2019 in a university in 2019 and 2020. The results show that among the 32 influencing factors in the three categories of students, teachers, and external factors proposed, there were 7 strong correlations, 22 moderate correlations, and 3 weak correlations. All of the strong correlations belonged to the student dimension, thereby indicating that the effectiveness of international online courses is mainly influenced by student factors. In addition, these influencing factors can not only impact course effectiveness directly, but also indirectly through the interaction between factors. The relationship model of the influencing factors can provide a reference for improving the effectiveness of international programs and realizing the sustainable development research for international courses

Quantitative Study on Human Error in Emergency Activities of Road Transportation Leakage Accidents of Hazardous Chemicals

The emergency rescue process of road transportation leakage accidents involving hazardous chemicals is complex and includes various emergency activities. A quantitative study of human errors in emergency activities is conducive to seeking the focus of the emergency rescue process. To quantitatively analyze human error in emergency activities during the emergency rescue process of road transportation leakage accidents of hazardous chemicals, sequentially timed events plotting (STEP) and the cognitive reliability and error analysis method (CREAM), were used. First, STEP was used to analyze six laws, regulations and standards, as well as 54 accident cases, to derive 24 emergency activities in the emergency rescue process. Then, CREAM was used to analyze and obtain the probability of human error for each emergency activity. Two high error level emergency activities, five medium error level emergency activities, and seventeen low error level emergency activities were identified after the human error levels of the emergency activities were classified. The results show that two emergency activities, the initial handling of the accident, and cleanup of the leakage site, should be prioritized in the emergency rescue process of road transportation leakage accidents of hazardous chemicals

Synthesized indicator for evaluating security of strategic minerals in China: A case study of lithium

The transition of the economic growth in China from high-speed to high-quality development provides new challenges to strategic minerals (SMs) security. Under the transition, combined with its development status, but also to maintain global coexistence from the entire industrial chain, we in this paper first expound the security connotation of SMs and take lithium resources as an example to evaluate its security in China. Monte Carlo Simulation (MCS) is used for sensitivity analysis. Results show that the security level of China's lithium resources is rising but fluctuating, and it is closely related to changes in the sub-object of coexistence. Our results illustrate that the proposed synthesized security indicator can effectively evaluate the security status of China's lithium resources. Therefore, it should be possible to be adapted for evaluating the security status of other SMs

<it>In vivo</it> functional expression of a screened <it>P. aeruginosa</it> chaperone-dependent lipase in <it>E. coli</it>

<p>Abstract</p> <p>Background</p> <p>Microbial lipases particularly <it>Pseudomonas</it> lipases are widely used for biotechnological applications. It is a meaningful work to design experiments to obtain high-level active lipase. There is a limiting factor for functional overexpression of the <it>Pseudomonas</it> lipase that a chaperone is necessary for effective folding. As previously reported, several methods had been used to resolve the problem. In this work, the lipase (LipA) and its chaperone (LipB) from a screened strain named AB which belongs to <it>Pseudomonas aeruginosa</it> were overexpressed in <it>E. coli</it> with two dual expression plasmid systems to enhance the production of the active lipase LipA without <it>in vitro</it> refolding process.</p> <p>Results</p> <p>In this work, we screened a lipase-produced strain named AB through the screening procedure, which was identified as <it>P. aeruginosa</it> on the basis of 16S rDNA. Genomic DNA obtained from the strain was used to isolate the gene <it>lipA</it> (936 bp) and lipase specific foldase gene <it>lipB</it> (1023 bp). One single expression plasmid system <it>E. coli</it> BL21/pET28a-<it>lipAB</it> and two dual expression plasmid systems <it>E. coli</it> BL21/pETDuet-<it>lipA</it>-<it>lipB</it> and <it>E. coli</it> BL21/pACYCDuet-<it>lipA</it>-<it>lipB</it> were successfully constructed. The lipase activities of the three expression systems were compared to choose the optimal expression method. Under the same cultured condition, the activities of the lipases expressed by <it>E. coli</it> BL21/pET28a-<it>lipAB</it> and <it>E. coli</it> BL21/pETDuet-<it>lipA</it>-<it>lipB</it> were 1300 U/L and 3200 U/L, respectively, while the activity of the lipase expressed by <it>E. coli</it> BL21/pACYCDuet-<it>lipA</it>-<it>lipB</it> was up to 8500 U/L. The lipase LipA had an optimal temperature of 30°C and an optimal pH of 9 with a strong pH tolerance. The active LipA could catalyze the reaction between fatty alcohols and fatty acids to generate fatty acid alkyl esters, which meant that LipA was able to catalyze esterification reaction. The most suitable fatty acid and alcohol substrates for esterification were octylic acid and hexanol, respectively.</p> <p>Conclusions</p> <p>The effect of different plasmid system on the active LipA expression was significantly different. pACYCDuet-<it>lipA</it>-<it>lipB</it> was more suitable for the expression of active LipA than pET28a-<it>lipAB</it> and pETDuet-<it>lipA</it>-<it>lipB</it>. The LipA showed obvious esterification activity and thus had potential biocatalytic applications. The expression method reported here can give reference for the expression of those enzymes that require chaperones.</p

Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm

Multi-objective optimization (MOO) is frequently used to solve many practical problems of chemical processes but process designers only need a limited number of valuable solutions in the final results. In this study, an optimization strategy associated with an improved genetic algorithm was developed to search valuable solutions for stakeholders' preference more purposefully. The algorithm was improved to reduce overlapping solutions as a result of the discrete variables in practical problems, and it allowed users to set a reference point or an angle associated with a reference point to make solutions converge into the preferred spaces. Three test functions and two practical problems were used to highlight that the proposed strategy could make designers optimize processes more efficiently. Especially, the angle-based algorithm could be more effective than the distance-based one on the tri-objective problems. Thus, the developed strategy is robust in the optimization of processes assisted with the designer's preference. (C) 2019 Elsevier Ltd. All rights reserved

Predictive deep learning models for environmental properties: the direct calculation of octanol-water partition coefficients from molecular graphs

As an essential environmental property, the octanol-water partition coefficient (K-OW) quantifies the lipophilicity of a compound and it could be further employed to predict toxicity. Thus, it is an indispensable factor that should be considered for screening and development of green solvents with respect to unconventional and novel compounds. Herein, a deep-learning-assisted predictive model has been developed to accurately and reliably calculate log K-OW values for organic compounds. An embedding algorithm was specifically established for generating signatures automatically for molecular structures to express structural information and connectivity. Afterwards, the Tree-structured long short-term memory (Tree-LSTM) network was used in conjunction with signature descriptors for automatic feature selection, and it was then coupled with the back-propagation neural network to develop a deep neural network (DNN), which is used for modeling quantity structure-property relationship (QSPR) to predict log K-OW. Compared with an authoritative estimation method, the proposed DNN-based QSPR model exhibited better predictive accuracy and greater discriminative power in terms of the structural isomers and stereoisomers. As such, the proposed deep learning approach can act as a promising and intelligent tool for developing environmental property prediction methods for guiding development or screening of green solvents

Low energy-density recording with a highrepetitionrate laser beam in gold-nanorodembedded discs

In this paper, we report on the low energy-density recording with a high-repetition-rate femtosecond pulsed beam in homogenous goldnanoroddispersed discs by using low numerical aperture (NA) microoptics. By focusing a femtosecond pulsed beam at a repetition rate of 82 MHz using a low NA DVD optical head, the spatially-stretched energy density introduces a temperature rising of the polymer matrix. This temperature rising facilitates the surface melting of gold nanorods, which leads to over one-order-of-magnitude reduction in the energy-density threshold for recording, compared with that by focusing single pulses through a high NA objective. Applying this finding, we demonstrate the dual-layer recording in gold-nanorod-dispersed discs with an equivalent capacity of 69 GB. Our results demonstrate the potential of ultra-high density three-dimensional optical memory with a low-cost and DVDcompatible apparatus