bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of OrSAEv Model Learning Materials to Strengthen the Characters of Tsunami Disaster Mitigation for Middle School Students (Preliminary Study)
Authors: Isna B U , Madlazim  , Hariyono E , Suprapto N
Published: December 2019

Geologically, Indonesia is a disaster-prone country, especially tsunami. One strategic step that can be taken to minimize the impact of the tsunami is through the education sector as the fundamental sector forming student character. Therefore, this research is aimed to determine the process of strengthening students’ character about earthquake and tsunami disaster mitigation, to find out the experiences of students facing earthquake and tsunami disasters and to find out the disaster learning that has been implemented in schools. This research belongs to a quantitative descriptive type of research. The subjects of this research were 30 students of ninth grade at Donomulyo 1 Public Middle School. The process of collecting the data was done by giving questionnaires and doing interviews. Questionnaires were given to students in the form of questionnaires about strengthening the character of earthquake and tsunami disaster mitigation, and questionnaires about students’ experiences in dealing with tsunami disasters related to learning in class, then interviews were conducted with two science teachers at the school. Samples were taken through the process of purposive sampling which was based on input from science teachers at Donomulyo 1 Public Middle School. Based on the results of the data in related to the analysis and discussion that have been conducted, it can be concluded that there are contradictory results. Where based on the questionnaire is obtained that the character of tsunami disaster mitigation in Donomulyo 1 Public Middle School students is good. However based on the results of interviews with two science teachers and questionnaires how students facing the tsunami and earthquake disasters, the results show that facilities, experience of facing the disasters and disaster learning in classroom are still lack of it. Therefore, it is necessary to test its application to find out whether the character is truly embedded within the students’ mind.
Development of The OrSAEv Learning Materials: Preliminary Study of Student’s Knowledge about Earthquake and Tsunami Mitigation
Authors: Elfiana D E , Madlazim  , Hariyono E , Munasir
Published: December 2019

Geologically, Indonesia is a disaster-prone country, especially tsunami. As a country has kind of disaster and so in the schools of Indonesia should be started to give education of hazard. Therefore, this study aims to determine the level of student knowledge about the earthquake and tsunami disasters, know the experience of students facing earthquake and tsunami disasters, and determine the conditions of counseling and disaster learning that have been applied in school. This type of research is a quantitative descriptive. The subjects of this study were 28 students of MTsN 7 Blitar. Data collection techniques carried out by observation, tests, and questionnaires. The sample of respondents was taken by purposive sampling based on advice from the science teacher at MTsN 7 Blitar. The results of the study are as follows: 1) In terms of the level of student knowledge about the earthquake and tsunami disasters can be categorized as less. 2) student’s experiences in facing with disasters and actions to save themselves in situations and conditions are categorized as not ready. 3) Disaster counseling and learning activities have never been carried out. After adding up the average percentage of each indicator, it is found that the knowledge and preparedness of the community in dealing with the earthquake and tsunami disaster based on their knowledge is still in the category of less prepared with a percentage of 47.9%, so there is still a need for better knowledge and readiness for students reach the level of full preparedness in the face of disaster. Learning methods and materials are needed that can be used to increase student knowledge about earthquake and tsunami mitigations. Therefore, it can be concluded that disaster learning materials need to be developed.
Metacognitive Skills: A Solution in Chemistry Problem Solving
Authors: Azizah U , Nasrudin H , Mitarlis
Published: December 2019

One of the skills needed in the 21st century is thinking skills including metacognitive skills. Many studies showed that undergraduate students who used metacognitive skills are more successful in learning. This study aims to illustrate using metacognitive skills as a solution in chemistry problem solving and undergraduate students’ respond. The design used One Group Pre-test and Post-test Design. The subject of this study was the undergraduate students of chemistry class academic year 2019/2020 as many as 31 people. To obtain the profile data of metacognitive skills and undergraduate students’ respond through an essay test, interview, and questionnaire. Research data were analysed by quantitative descriptive. The results showed that: (1) performance of metacognitive skills of undergraduate students has high category in chemistry problem solving on each indicator. The indicators were goal setting, identify the known knowledge, determining the learning strategies, monitoring the relevance of the known knowledge with learning strategies, monitoring the goal achievement in the making conclusions, and evaluating the process and thinking outcomes, and (2) most of the undergraduate students are pleasant to join to this learning activity. Based on the results of this study, metacognitive skills can be used as a solution in chemistry problem-solving.
Fostering Prospective Physics Teachers’ Creativity in Analysing Education for Sustainable Development Based Curricula
Authors: Jauhariyah M N R , Hariyono E , Abidin E N , Prahani B K
Published: December 2019

This study describes how to foster the creativity of prospective physics teachers in analysing ESD-based curriculum and describing the profile of prospective physics teachers’ work as a form of ESD-based curriculum analysis. This study was a qualitative descriptive study using qualitative observation by observing behaviour consisting of independence, integration, motivations, judgment, flexibility, evaluation, questions, opportunity, and frustrations. Then, questionnaire gave to explore more about the attitude about analysis curriculum based on ESD. Besides the work of the prospective teacher in the form of the results of curriculum analysis was assessed based on the four basic components of the curriculum, namely objectives, content, the learning process designed, and the assessment design. To foster the creativity of a prospective teacher to produce an ESD-based curriculum analysis, all of them can make an analysis based on the basic component of the curriculum but still weak in integrating global issues of SDGs and provide solutions to the problems studied.
Implementation of KS-STEM Project: Bridging the STEM curriculum into Science education
Authors: Suprapto N , Ku C-H
Published: December 2019

Currently, interest in STEM education is growing in the world. In Indonesia, STEM practice is gradually developing. Through the partially “KS-STEM Project”, this study was addressed. The project is a longitudinal cross-country project between Taiwan and Indonesia. In regards to the three philosophical foundations (epistemology-ontology-axiology), this study addresses three research questions, as follows: 1) To what extent does the Fuel Cell Car Science Kit facilitate junior high school students’ understanding of the essence of STEM education; 2) To what extent do the students’ outcomes deal with fuel Cell Car Science Kit; 3) What topics can students learn from the Fuel Cell Car Science Kit. The research used a descriptive qualitative approach by using instruments: “Fuel Cell Car Science Kit” as a STEM kit. Participants of the study included 32 junior high school students in East Java, Indonesia. The results of the study included: (1) the description of how STEM Kit facilitates the students’ understanding of the essence of STEM education; (2) the students’ outcomes dealing with the STEM Kit; and (3) several topics that students learn from the STEM Kit. The implication of the current study is to introduce and to involve Indonesian students, especially junior high school students to STEM education.
The Implementation of Guided Discovery Learning Using Virtual Lab Simulation To Reduce Students’ Misconception on Mechanical Wave
Authors: Admoko S , Yantidewi M , Oktafia R
Published: December 2019

This study aims to determine the effectiveness of the implementation of guided discovery learning with virtual lab: Physics Education Technology (PhET) simulation in reducing students’ misconceptions in mechanical wave physics. The design of this study was pre-experimental design with One Group Pretest-Posttest Design. This research was conducted in Mojokerto, East Java, Indonesia. Thirty five 11th grade high school students and one teacher participated in this study. This study applied the certainty of response index (CRI) with Two-tier Diagnostic Test to determine students’ misconception. An analysis of differences in the average of misconception between pretest and posttest and also normalized gain analysis had been performed to find out the effectiveness of guided discovery learning implemetation towards students’ misconception reduction. The treatment was declared effective if the average of misconception in pretest was greater than the postest and the normalized gain was negative, which meant there was a decrease in misconception minimum in the moderate category ( ⩽ -0,3). The results showed that in the initial tests the 3 highest students’ misconceptions occured on the concepts: wavelength, wave velocity and the nature of the wave. But the implementation of guided discovery learning was able to reduce students’ misconceptions significantly. Based on the statistical analysis of T test, it was found that tcount > ttable with α = 0.05 with 1.96 > 1.71. This meant that there were significant differences in average misconception. Through gain analysis, it is also known that  = -1,13 where the average misconception at pretest is 53,33% to 19,55% for posttest. This decrease was included in the high category. According to these analysis results, the application of the Guided Discovery Learning model using Virtual Lab. PhET was able to reduce students’ misconceptions.
Science teacher’s conception about importance of Geoscience learning: A case study of junior high schools in Surabaya Indonesia
Authors: Anggrayni S , Madlazim  , Hariyono E
Published: December 2019

The aim of this study is to identify the science teacher’s conception of the importance of geoscience learning. This study was possessed the conception profile of science teacher about geoscience learning through questionnaire instrument and curriculum analyses to 17 science teachers at three Junior High Schools in Surabaya as the participants. A descriptive quantitative approach is used to analyse the data. Based on the results obtained, almost all the participant stated that geoscience learning is important to teach but more than 50% of science teachers do not teach it because of insufficient time constraints. Based on the curriculum analyses, can be known that the learning method which is done using textbooks only without involving issues which are happening in the present. Therefore, it can be concluded that the developed geoscience learning curriculum for pre-service science teachers needs to be developed.
Improving Student’s Creative Thinking Skill through Blended Learning using Schoology
Authors: Roqobih F D , Yuliani  , Rahayu Y S
Published: December 2019

Creative thought is needed in the industrial revolution era 4.0 because learning can take place everywhere and every time. So, the role of technology also needed to support this learning. However, technology cannot fully replace face to face learning. One of the alternative efforts to overcome this problem is by implementing blended learning. Blended learning is learning that combines face-to-face learning in the classroom and online learning that can be done everywhere. This study aimed to evaluate the effectiveness of this learning to improve student’s creative thinking skills in Bryophyte material through blended learning using Schoology. This research implemented to 22 students of Grade X by using one group pre-test and post-test design pattern. Data obtained were the student’s activity and the level of student’s creative thinking skills. The instrument used are observation sheets, pre-test, and post-test sheets. Data were analyzed descriptive-quantitatively. Data on creative thinking skills were analyzed based on gain score, student’s creativity level, and completeness of creative learning indicators. Results of this study indicated that learning process combination of both face-to-face learning and online learning were very successful in improving student’s creative thinking skill significantly, based on learning the outcome, percentage of student’s activity and completeness each creative learning indicators.
Attitude, Knowledge, and Application of STEM Owned by Science Teachers
Authors: Sujarwanto E , Madlazim  , Ibrahim M
Published: December 2019

Providing STEM (Science Technology Engineering Mathematics) education and apply it in learning is influenced by teacher‘s knowledge and attitude towards The purpose of this study is to determine the teachers and lecturers’ attitudes, knowledge, and application of STEM education. Data were collected from the responds of science lecturers and teacher toward a set of STEM instuments. The results point out that respondents strongly agreed to apply STEM education in learning and are sure that students would get added value when applying STEM education. Regarding aspect of knowledge, more than 50% of the respondents have adequate knowledge of the term STEM although more than 50% of the respondents do not grasp the idea of weaknesses and advantages of implementing integrated STEM. Furthermore, 76.2% of respondents tried to implement integrated STEM when teaching with a percentage between 26%-75%. The application of integrated STEM involving the discipline of engineering has a lower percentage of application than integration with other disciplines. The findings also report that obstacles to the implementation of integrated STEM are the ability to apply the mathematics concepts, technological tools available, the duration of learning time, and the process of connecting between disciplines in STEM. This research implies that there is a need to increase the understanding the interrelationships between aspects of STEM, and need to develop STEM-based learning models to support the application of integrated STEM in Science learning.
Evaluation on least square method applied to gamma spectrum de-noising
Authors: Li Fei , Lang Xinle , Chen Yi , Ge Liangquan , Feng Li , Li Siwei
Published: December 2019

Gamma energy spectrum is a way to confirm the type and content of radioactive nuclides in substances. In order to obtain effective data of gamma spectrum, it is necessary to analyze the data of gamma spectrum obtained by the detector. Nevertheless, due to the influence of statistical fluctuation and gamma generated by the environment itself during the measurement of gamma spectrum, the obtained gamma spectrum is not accurate enough as a result of needing spectral analysis of gamma spectrum, and noise reduction can make the spectral data smoother. Therefore, this paper studies the noise reduction algorithm for gamma spectrum analysis, analyzes the design and application of different algorithms in the process of noise reduction, and summarizes the advantages and disadvantages of this algorithm and others.
The satisfaction of entrepreneur instructors and higher vocational students majoring in economic and business administration with the cooperative instruction in the work post practice
Authors: Liao Xifeng
Published: December 2019

From the perspective of both instructors from entrepreneur and students, this research studied the satisfaction level with the cooperative instruction in the Work Post Practice, a very important course for senior students at higher vocational colleges in China. The method of descriptive analysis was adopted. The statistic results illustrated that the practice posts of students didn’t fit well with students’ majors, and students responded that it did improve their professional abilities and qualities soundly. Business instructors demonstrated a higher satisfaction level on students’ work and qualities shown during the practice than students’ self evaluations. Suggestions like using the internet platfom, establishing a stable team of entrepreneur instructors, allocating salary and other subsidies to entrepreneur instructors were proposed to improve instruction quality of the work post practice.
Effects of anesthetic eugenol on respiration and excretion of Sinogastromyzon szechuanensis
Authors: Chen Xiaojiang , Xiong Liling , Wu Jiangu , Wang Quan
Published: December 2019

In order to select a more suitable anesthetic for the breeding and transportation of Sinogastromyzon szechuanensis, we used different concentrations of anesthetic eugenol (0, 6,12,18,24,30 mg•L−1) to test the effects of the respiratory and metabolic on Sinogastromyzon szechuanensis with an average mass of (2.029±0.26) g under the water temperature (18±0.5) °C. Based on regression analysis method, the regression equations of oxygen consumption rate, ammonia removal rate and temperature were calculated. (R2> 0.99). Oxygen consumption rate and ammonia removal rate were calculated and compared by One-Way ANOVA (Turkey method) using SPSS 25.0 software. The multiple comparison results revealed that when the mass concentration of eugenol reached 24 mg•L−1, it could significantly reduce the oxygen consumption rate and ammonia excretion rate (p<0.05). With the increase of eugenol concentration, the oxygen consumption rate and ammonia excretion rate of the Sinogastromyzon szechuanensis first increased and then decreased. Under the influence of eugenol, the oxygen consumption rate and ammonia excretion rate of Sinogastromyzon szechuanensis were increased with the increase of temperature (p<0.01). When the water temperature is 14-26°C, the oxygen-nitrogen ratio is 8.0-19.4, and the temperature is positively correlated with the oxygen-nitrogen ratio. It is concluded that eugenol with a mass concentration of 24 mg•L−1 can make Sinogastromyzon szechuanensis enter the stage of anaesthesia II (sedation), so this concentration is recommended as the anesthetic dosage for transportation, and the anesthetic effect at low temperature is more obvious.
Empirical analysis on intra-industry trade in textile between China and Vietnam
Authors: Yao Lei , Yang Zheng
Published: December 2019

The total volume of import and export trades between China and Vietnam exceeded 723 billion yuan in 2018. A comprehensive analysis of the Sino-Vietnamese intra-industry trade in textile is presented. By calculating G-L index and Bruelhart index, this paper analyzed the current situation of intra-industry trade of textile between China and Vietnam. A regression econometric model was established to explore factors affecting the intra-industry trade of textile. The study shows that adjusting textile industry structure and optimizing trade environment between China and Vietnam, as well as strengthening trade liberalization, are of great significance for reference, and are beneficial to promoting coordinated and sustainable development of economic and trade between China and Vietnam.
Study on the influence of the gas superficial velocity on the radon adsorption of activated carbon
Authors: Wang Meng , Gu Yi , Li Fei , Ge Liangquan , Lu Heng , Luo Liang
Published: December 2019

In order to improve the radon adsorption efficiency of activated carbon and provide a reference for reducing the cost of radon purification, the radon adsorption experiment of activated carbon under different gas superficial velocities under the active adsorption mode was studied to measure the radon adsorption quantity of activated carbon. The radon adsorption quantity of apricot shell activated carbon and coal-based activated carbon did not change significantly with the increase of the gas superficial velocity. When the gas superficial velocity increased from 0.9cm/s to 2.0cm/s in turn, the radon adsorption quantity of coconut shell activated carbon did not change significantly. The radon adsorption quantity of coconut shell activated carbon increased first and then decreased when the gas superficial velocity increased from 2.0cm/s to 3.1cm/s. When the gas superficial velocity was about 2.7cm/s, the radon adsorption quantity of coconut shell activated carbon reached its peak value. 2.7cm/s can be selected as the optimum gas superficial velocity for the radon adsorption of coconut shell activated carbon.
Analysis and forecast for growth of lottery sales based on optimal control model
Authors: Liu Zhang , Li Canhua , Wu Jian
Published: December 2019

Based on the optimal control theory, this paper analyzes the relationship among the growth of lottery sales and the accumulation of capital and the rate of accumulation. By the introduction of Hamilton function, we established a mathematical model and calculate the satisfied equation. Using a simple model, we realized data fitting for the corresponding formula by Matlab through dealing with the sales and the funds of prize pool of the super lotto from 2014 to 2018. We made some forecasts according to the results.
Application research of a data stream clustering algorithm in network security defense
Authors: Zhu Canshi , Wang Xiaoyang , Zhu Lin
Published: December 2019

The traditional intrusion detection system feature model is based on static data mining. Its mining algorithm relies on too many assumptions, which makes it difficult for intrusion detection systems to adapt to dynamic and real-time system detection requirements. Using attenuated sliding window technology, data stream mining technology and fusion technology with intrusion detection system, a data flow clustering algorithm based on attenuated sliding window is designed to improve and optimize the feature pattern extraction method of intrusion detection system to solve the dynamics of intrusion detection system. Through algorithm design, algorithm application and intrusion detection system simulation verification, the feasibility and accuracy of the algorithm and the optimized intrusion detection system are proved.
Review on big data application of medical system based on fog computing and IoT technology
Authors: Qin Baoling , Tang Huiying , Chen Hongtao , Cui Liangyun , Liu Jianjie , Yu Xueke
Published: December 2019

From the current general situation of big data in medical systems, most of the medical system architectures of comprehensive related literature are based on cloud computing. With the deepening of big data application in the medical system, the drawbacks of medical network systems are apparent, for example, long network time delay, cloud computing overload, information leakage. A new intelligent medical system based on fog computing and IoT technology is proposed to effectively solve the problem of big data application through the comprehensive analysis of many works of literature. Compared with the traditional cloud computing model, the system which adopts a distributed fog computing model based on edge computing has the advantages of reducing network delay and plays its benefits of distributed, edge and decentralization. That the system takes advantage of IoT’s features of multi-node, low-energy consumption and big data technology is a new type of medical system that integrates intelligence and big data application. The system is effective through the application and practice of many medical institutions. In short, this system has several characteristics. For example, it can effectively improve medical intelligence and big data processing ability, significantly reduce network delay, effectively improve data security and effectiveness, largely improve the management level and service quality of medical institutions, play the important role of artificial intelligence and big data in the medical field, and greatly improve disease screening rate and reduce misdiagnosis rate. Ultimately it leads to reducing the contradiction between doctors and patients, providing patients with more convenience, faster and more efficient service quality, and alleviating the current situation of difficult and time-consuming medical treatment.
The application of EDXRF on soil heavy metal analyzation in a planting area
Authors: Li Xiaozhe , Chen Yi , Ge Liangquan , Li Fei , Tan Wei , Xu Jingru
Published: December 2019

With the increase of heavy metal concentration in soil, serious environmental problems have arisen. At present, heavy metals mainly refer to biotoxic heavy metals, including Lead, Cadmium, Mercury and Chromium, etc., which are produced in large quantities by human activities and difficult to be degraded, resulting in their loss of original activity and chronic poisoning because of the reaction with proteins and enzymes in human body. The soil concentration in the planting area exceeds the standard and is enriched in human beings, animals and plants, which directly endangers the living environment and health. In this paper, the soil in the planting area next to Xiangzhang canteens of Chengdu University of Technology was selected for field investigation, and the data analysis and risk assessment were carried out after testing the concentration of heavy metals in the surrounding soil through reasonable sampling, sample treatment and Energy-Dispersive X-ray fluorescence analysis techniques.
Research on the optimization of express delivery route of logistics base under the constraint of carbon quota
Authors: Liao Zhigao , Deng Zongqi , Jian Kerong , Guo Yi
Published: December 2019

This paper considers the route selection of express delivery under the constraint of carbon emission. Two kinds of path optimization models, not con carbon emissions and under the constraint of carbon quota, are constructed respectively to optimize the distribution route of express delivery stations, and this paper further analyses the impact mechanism of carbon quota on the optimization decision-making of distribution route. Finally, carbon emission policy recommendations are obtained.
RETRACTED: Application research of data mining algorithm in big data environment
Authors: Zhao Zenghui
Published: December 2019

The Hadoop platform forms a complete large-scale ecological distribution system, including HDFS, MapReduce, HBase and other subsystems. This paper analyzes the parallel processing of Hadoop platform and applies it in the field of data mining algorithms. In order to obtain better algorithm efficiency, a K-Modes clustering algorithm based on big data platform is proposed. It uses cluster mode to replace the central node. The mining process uses naive Bayes to improve mining efficiency. The experimental results show that it has better adaptability, saves time and improves the efficiency of the algorithm.
Study on application of entropy averaging method in airborne gamma-ray spectrum for local disturbance elimination
Authors: Xiong Chao , Zhao Jiankun , Wu Hexi , Ge Liangquan
Published: December 2019

This paper briefly describes the basic principle and the entropy averaging method for local disturbance elimination in airborne gamma-ray spectrum. This method was employed to process t boundary of different lithologies and the identification of metal ore points. The results showed that applying the entropy averaging method to eliminate the interference of the airborne gamma-ray spectrum data, and selecting a larger window width, achieve more significant results compared with the ground gamma ray spectrum.
Full multi-dimensional dynamic comprehensive optimization stochastic simulation is the sustainable trend of future petroleum reservoir description
Authors: Xiao Xiaonan
Published: December 2019

Being an important and sustainable approach in future petroleum reservoir description as well as a new frontiers subject in information optimization decision making of today’s oil/gas field development, multi-information stochastic dynamic comprehensive optimization simulation bears profound research significance and broad application prospect. The present paper is an introduction to theoretic performance and characteristics of multi-dimensional stochastic dynamic comprehensive optimization simulation, to classification, steps of model establishment, frequently-adopted approaches and problems to be considered in stochastic simulation. The paper, based on the author’s years of profound study and practice, also indicates the trend and latest application progress of stochastic simulation.
Application of geometric flow and bandelet coefficient combining method to image fusion
Authors: Zhong Mantian
Published: December 2019

Based on the theory of Bandelet transformation, we use Beamlab200 toolbox and Matlab software, adopt new construction of geometric flow and Bandelet coefficient combination method, apply new introduction of smaller absolute value rules, and take advantage of usage of computer simulation to experiment image fusion to explore the coefficient combination method and new introduction of smaller absolute value rules for geometric flow and Bandelet and test effect of their application to image fusion. The result after the experiment proves that this method is superior than the Beamlab 200 toolbox method in terms of running time, convergence speed, standard deviation, signal-to-noise ratio, gradient and image effect. The method can be applied to repair damaged images and others according to the results.
Design of human-like behavior learning machine based on neural network FPGA
Authors: Tang Ming , Hao Shengli
Published: December 2019

Neural network has been widely used in image recognition, because it can imitate the behavior of biological visual nerve to obtain high recognition accuracy. Aiming at image recognition, this paper studies the machine self-learning system of image recognition results based on neural network FPGA, designs the data sensing and image recognition processing module based on neural network, and studies the key problems of the system self-recognition and machine self-learning process. The image recognition module uses bionics and parallax principle to get the synchronous exposure image of surrounding scenery, reconstruct the three-dimensional shape and position of surrounding objects, and get the information needed by the system design through image processing algorithm. On the basis of this module, a machine self-learning algorithm based on the result of image recognition is designed to build a knowledge base for the machine and guide the machine by modifying the weight and making decision to realize human-like behavior of machine self-learning. The experimental results show that the recognition accuracy of dynamic image recognition in image recognition network is about 80% compared with the corresponding static image recognition, and the time and power consumption are reduced by 24%, 27.8% and 41% respectively.
Data mining in psychological experiments: a research of the relationship between personality, resilience and investment behavior rigidity
Authors: Gao Kai , Qiao Xiaoqian , Mei Zhipeng
Published: December 2019

Data mining in psychological experiments is to discover the relationship between other data and psychological data, so as to discover the psychological state of the subjects. Based on the psychological assessment data of students from Jiangsu Vocational College of Agriculture and Forestry during 2017-2019, we applied the association rules in big data processing to calculate the scores of personality, resilience and rigidity of investment behavior of the subjects. The following conclusions are drawn through analysis of promotion degree and correlation degree between values of each attribute. Firstly, pruning lift is of great significance to understand the associated relationship among personality, resilience and investment behavior rigidity. Secondly, the more openness individuals in the Big Five personality, the stronger the investment behavior rigidity. The stronger the neuroticism, the weaker the investment behavior rigidity. The stronger the extroversion, the stronger the investment behavior rigidity. Thirdly, psychological resilience as a mediator affects the impact of openness and neuroticism on the rigidity of investment behavior.
Matrix factorization recommendation algorithms based on knowledge map representation learning1
Authors: Huang Xuejian , Min Lu , Wang Gensheng , Gan Tian , Li Zhipeng
Published: December 2019

The matrix factorization recommendation algorithm does not consider characteristics of the recommendation object itself, resulting in poor recommendation results. Therefore, a matrix factorization recommendation algorithm based on knowledge map representation learning is proposed. Firstly, the recommendation object is represented as a low dimensional semantic vector by using the knowledge map distributed representation learning algorithm. Then the semantic similarity between objects is calculated, and the semantic similarity is incorporated into the objective optimization function of matrix factorization, so that the feature vectors obtained by matrix factorization can also contain semantic knowledge, which makes up for the shortcoming of matrix factorization recommendation algorithm that does not consider characteristics of the recommendation object itself from the semantic perspective. The experimental results show that the improved algorithm has higher accuracy, recall and coverage than the traditional matrix factorization recommendation algorithm.
Fixed spray type anti-ice deicing control system design
Authors: Liu Wenjiang , Chen Yunquan , Hou Fujin , Jing Yucai , Chen Jie
Published: December 2019

This paper takes intelligent control technology as the core technology, combines with meteorological and road freezing information collection technology and water supply and drainage technology. Firstly, this paper introduces the design of grading subsystem of fixed spray type anti-ice and snow removal control system, and proposes a new type of nozzle suitable for the viaduct at the same time, which can improve spraying effect of the deicing liquid while improving safety guarantee. Then based on analysis of collected on-site road conditions and meteorological actual data and combined with logic control algorithm, a live ice and snow early warning mathematical model is designed to predict the snowy condition of the road surface, and automatically control equipment to spray deicing fluid before or after road icing.. It uses PID control technology to ensure pressure balance inside the spray pipe. The real-time field data is connected to the cloud server with 4G wireless transmission technology, and the existing data and current data are compared and analyzed through the recursive neural network, so as to further accurately predict the ice and snow situation, classify danger level according to national road safety standards, and release it to other platforms. Based on application of actual field, this paper designs a method that can be combined with prevention in advance and post-disposal to eliminate road icing and reduce risks of vehicle driving safety in severe weather.
The analysis method and application of automobile driving direction deviation
Authors: Chen Peijiang , Zhang Mei , Wu Liying
Published: December 2019

When the automobile body deviates, being one of the hidden dangers of road traffic safety, it affects not only the automobile operation stability, but also the accuracy of headlight detection results. The driving directions analyzing method based on binocular stereo vision was presented. The shape center of the front license plate was extracted as automobile body feature point based on mathematical morphology and Hough transform. The sequence of the feature points was fitted into a straight line, which was the driving direction of the automobile. The measurement error of the headlight beam irradiation was corrected. The experiment results show that that this method can effectively detect the deviation angle of the automobile driving direction, and improve the accuracy of headlight detection.
Investigation on mechanical and tribological behaviour of titanium diboride reinforced martensitic stainless steel
Authors: Sadhasivam M , Mohan N , Sankaranarayanan Sankara Raman , Babu S P Kumaresh
Published: December 2019

The role of metal matrix composites (MMCs) has gained huge momentum in various researches as well as in industrial applications due to their high stiffness and higher strength to weight ratio. It helps in achieving enormous weight reduction without compromising the strength of the material. In this study, a novel attempt was made to fabricate MMCs with martensitic stainless steel as matrix and titanium diboride (TiB2) as reinforcement. The AISI 420 matrix with different weight percentages (1%, 2%, and 4%) of TiB2 reinforcement was fabricated by vacuum induction melting technique (VIM). The aim of this study was to analyze the influence of TiB2 particle addition on the mechanical and tribological properties of AISI 420 composites. X-ray diffraction studies revealed the presence of TiB2 phase in the composite along with peak shifting and broadening of the steel matrix due to induced strain. Optical microscopy showed the distribution of TiB2 particles in the matrix along with a significant amount of grain refinement of the composite due to the addition of TiB2. Microhardness results showed that the presence of TiB2 improved the hardness with AISI 420/4%TiB2 composite possessing the maximum hardness. Tensile test results indicated a significant improvement in the ultimate tensile and yield strength of the composite with the addition of TiB2. The wear tests were carried out on a pin on disc tribometer for various loads at a different sliding distance for steady sliding velocity. The dispersion of TiB2 particle helped in achieving better wear resistance of the composites. Wear surface morphology was carried out to explore the wear mechanisms. Among the various wear mechanisms, abrasion and oxidation phenomena dominated in the composites. Taguchi optimization technique predicted that wt% of TiB2 and applied load as influencing factors on the wear rate of the material.
Effect of texture evolution on corrosion resistance of AZ80 magnesium alloy subjected to applied force in simulated body fluid
Authors: Xiong Ying , Yang Zengyuan , Zhu Tao , Jiang Yanyao
Published: December 2019

The electrochemical corrosion behavior of a rolled AZ80 magnesium alloy after pre-compressive strain along different orientation in a simulated body fluid (SBF) was investigated by immersion test for 48 h. The results showed that the corrosion resistance is related to the crystal texture of the material. The texture evolution induced by plastic deformation changed the corrosion behavior of the magnesium alloy. Slip and twin associated with plastic deformation changed the orientation of crystallographic planes. The surface containing highly concentrated orientation of (0002) basal plane has higher corrosion resistance. The appearance of

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1
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tension twinning could improve the corrosion resistance of magnesium alloy with specific orientation. However, the coexistence of

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tension twinning with high volume fraction and slip with high density dislocation reduced the corrosion resistance and corrosion anisotropy of the magnesium alloy.
Tailoring IONP shape and designing nanocomposite IONS@GN toward modification of SPCE to enhance electrochemical degradation of organic dye
Authors: Ognjanović Miloš , Stanković Dalibor M , Fabián Martin , Vranješ-Đurić Sanja , Antić Bratislav , Dojčinović Biljana
Published: December 2019

Iron oxide nanoparticles (IONP) with different distinctive morphologies (spherical, cubic, flower-like and needles) were utilized for modification of screen-printed carbon electrodes (SPCE) to be used for synthetic organic dye degradation by an electrochemical approach. This platform was implemented for removal of the synthetic organic dye, Reactive Black 5 (RB5) in aqueous solution. Modified SPCE with spherically shaped IONP (IONS) had the highest dye removal efficiency. Thus, IONS were then used for surface decoration of the most common carbon-based materials (graphene, graphene oxide, carboxylated graphene, graphene nanoribbons, graphene nanoplatelets, single- and multi-wall carbon nanotubes), and the nanocomposites formed were deposited on the electrode surfaces. Using IONS/graphene composite (IONS@GN) for electrode modification resulted in the best effect. Removal of RB5 with this electrode was 51% better in comparison with bare SPCE, reducing the time required for complete dye degradation from 61 to 30 min Using IONS-modified SPCE, total RB5 removal occurred in 51 min, improving the performance by 16% over that of bare SPCE. The effects determined, i.e., the best IONP morphology and best type of carbon-based material for nanocomposite formation to enhance RB5 removal will provide guidelines for further modifications of SPCE with nanomaterials and nanocomposites, for application of this electrochemical approach in the degradation of organic pollutants.
Metal hydride hydrogen compressors for energy storage systems: layout features and results of long-term tests
Authors: Tarasov Boris P , Bocharnikov Mikhail S , Yanenko Yurii B , Fursikov Pavel V , Minko Konstantin B , Lototskyy Mykhaylo V
Published: December 2019

This work summarises the results of development and long-term testing of two prototype models of industrial-scale metal-hydride thermal sorption hydrogen compressors, TSC1-3.5/150 (up to 11 Nm3 h−1; water cooling/steam heating) and TSC2-3.5/150 (up to 15 Nm3 h−1; heating and cooling by circulating oil). Both compressors have a two-stage layout utilising LaNi5 for the stage 1 and La0.5Ce0.5Ni5 for stage 2, thus providing hydrogen compression from 0.35 to 15 MPa at a cooling temperature of about 20 °C and a heating temperature between 150 °C and 160 °C. The compressors were operating for one year each and exhibited a satisfactory performance. The results of this work can be used in various medium-to-large scale hydrogen compression applications, including renewable energy systems.
Smartphone-Based Measurement of Executive Function in Older Adults with and without HIV
Authors: Moore Raeanne C , Campbell Laura M , Delgadillo Jeremy D , Paolillo Emily W , Sundermann Erin E , Holden Jason , Schweitzer Pierre , Heaton Robert K , Swendsen Joel
Published: December 2019

Objective

To examine feasibility, convergent validity and biases associated with a mobile color-word interference test (mCWIT) among older persons living with HIV (PLHIV).

Method

Over a 14-day period, 58 PLHIV and 32 HIV-uninfected individuals (aged 50–74) completed the mCWIT on smartphones once per day in real-world settings. Participants also completed a comprehensive laboratory-based neuropsychological evaluation.

Results

A high rate of compliance was observed (86%) in the repeated administration of the mCWIT. A practice effect was observed in the overall sample concerning mCWIT subscores, and these learning effects were greater for PLHIV. Stabilization of performance was observed after 6 (HIV+) and 7 days (HIV−) for completion time and after 2 (HIV−) and 3 days (HIV+) for mCWIT errors. A minor fatigue effect was observed in the overall sample which was unassociated with group status. Moderate to strong correlations were found between mCWIT completion time and mCWIT errors with global neurocognition and with all of the individual neurocognitive domains. The strongest associations were with mCWIT completion time and laboratory-based global neurocognition, executive function, and working memory scores.

Conclusions

Cognitive testing administered within the context of a person’s daily life provides qualitatively different data than neuropsychological testing completed in clinical settings, and it may constitute a more ecologically valid indicator of cognitive performance than traditional methods. Mobile cognitive testing has potential to help characterize real-time cognitive performance and serve as a complementary assessment tool to traditional methods.
Sounds of senescence: male swamp sparrows respond less aggressively to the songs of older individuals
Authors: Zipple Matthew N , Peters Susan , Searcy William A , Nowicki Stephen
Published: December 2019

Age-related changes in assessment signals occur in a diverse array of animals, including humans. Age-related decline in vocal quality in humans is known to affect perceived attractiveness by potential mates and voters, but whether such changes have functional implications for nonhuman animals is poorly understood. Most studies of age-related change in animal signals focus on increases in signal quality that occur soon after the age of first breeding (“delayed maturation”), but a few have shown that signal quality declines in older individuals after a mid-life peak (“behavioral senescence”). Whether other individuals are able to detect this senescent decline of assessment signals has not previously been tested. Here we use playback experiments to show that wild male swamp sparrows (Melospiza georgiana) respond more aggressively to songs from 2-year-old males as compared with songs from the same males when they are 10 years old. Senescence in signals that, like birdsong, affect reproductive success through intrasexual competition or mate choice may be of evolutionary significance.
Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows
Authors: Sun Hui-Zeng , Zhou Mi , Wang Ou , Chen Yanhong , Liu Jian-Xin , Guan Le Luo
Published: December 2019

Motivation

Enhancing the utilization of human-inedible crop by-products by ruminants to produce high-quality milk for human consumption is an emerging global task. We performed a multi-omics-based study to decipher the regulatory biological processes of milk production when cows fed low-quality crop by-products with the aim to improve their utilization.

Results

Seven types of different high-throughput omics data were generated across three central organs [rumen, liver and mammary gland (MG)] and biofluids (rumen fluid and blood) that involved in milk production. The integrated multi-omics analysis including metabolomics, metagenomics and transcriptomics showed altered microbiome at compositional and functional levels, microbial metabolites in the rumen, down-regulated genes and associated functions in liver and MG. These changes simultaneously contributed to down-regulated three key metabolic nodes (propionate, glucose and amino acid) across these organs and biofluids that led to lowered milk yield and quality when cows consumed corn stover (CS). Hippuric acid was identified as a biomarker that led to low milk production in CS-fed cows, suggesting a future evaluation parameter related to the metabolic mechanism of low-quality forage utilization. This study unveils the milk production-related biological mechanism across different biofluids and tissues under a low-quality forage diet, which provides a novel understanding and potential improvement strategies for future crop by-products utilization and sustainable ruminant production.

Availability and implementation

The raw files of metagenomics, metabolomics, and transcriptomics data can be accessed at NCBI SRA (No. SRR5028206), EMBI-EBI (No. MTBLS411), and GEO (NO. GSE78524) databases respectively.

Supplementary information

Supplementary data are available at Bioinformatics online.