bluuebunny/crossref_metadata_2025 huggingface dataset:
Disease Single Nucleotide Polymorphism Selection using Hybrid Feature Selection Technique
Authors: Phogat Manu , Kumar Dharmender
Published: August 2021

According to recent studies the Single Nucleotide Polymorphism (SNPs) plays very important role as genetic marker in various complex diseases. Lots of machine learning techniques are already applied on SNPs data to distinguish between affected and healthy individuals. The major problem with the SNPs dataset is high number of features and small number of samples which are referred as ‘large p’ and ‘small s’ problem. In this paper we proposed a hybrid feature selection method for selecting an optimal subset of SNPs and from that we select the significant SNPs, which act as marker for disease. The method is a hybrid technique based on combination of filter and wrapper method, the (mRMR) Minimum Redundancy Maximum Relevancy and Particle Swarm Optimization for Gene Selection with Support Vector machine (PGOGS-SVM) respectively. The proposed mRMR+PSOGS-SVM approach has been applied to mental retardation SNP dataset taken from NCBI-GEO website. The method has achieved high classification accuracy up to 88% and outperformed all other compared feature selection techniques.
Machine Learning based Heart Disease Diagnosis using Non-Invasive Methods: A Review
Authors: Kumar Narender , Kumar Dharmender
Published: August 2021

Heart disease is the most dangerous disease among all the non-communicable diseases. Annually 17900 thousand of peoples die due to heart problems. Cardiovascular disease (CVD) is the general term used for most of the heart diseases. There are two types of methods for diagnosing a CVD: (i) Invasive Methods (ii) Non-Invasive Methods. Coronary angiography is an invasive method for diagnosing a CVD which is a costly, painful and complicated process. A variety of Non-Invasive (NI) methods are available for diagnosing a CVD. NI methods generate a lot of data which is mainly of 3 kinds :(i) data based on clinical parameters, lab tests and symptoms (ii)data based on raw heart signals (ECG and PCG) (iii)data based on heart images. Majorly, three different machine learning (ML) frameworks may be developed based on the 3 types of data. First framework is simple and main concern is feature selection and classification. Second and third framework is complicated and requires a lot of techniques (preprocessing, segmentation and feature extraction) prior to classification of heart signals and images respectively. In this paper a comprehensive review is presented that summarizes some recent and prevalent machine learning methodologies in all the frameworks. Most of the papers reviewed in this study are from IEEE Explorer, Science Direct, PubMed, Springer, Hindawi, ACM digital library and MDPI libraries. It is found that Support Vector Machines (SVM) and Artificial Neural Networks (ANN) are superseding in most of the studies in all the frameworks. Deep neural network is comparatively newer machine learning methodology which is giving prominent results in classifying heart sound signals and cardiovascular images. The present study will help to automate diagnosis process of heart disease by providing guidelines and avenues to new researchers in domain of machine learning.
Hyperspectral Image Classification Using Deep Learning Models: A Review
Authors: Kumar Deepak , Kumar Dharmender
Published: August 2021

Hyperspectral image (HSI) classification is one of the important topic in the field of remote sensing. In general, HSI has to deal with complex characteristics and nonlinearity among the hyperspectral data which makes the classification task very challenging for traditional machine learning (ML) models. Recently, deep learning (DL) models have been very widely used in the classification of HSIs because of their capability to deal with complexity and nonlinearity in data. The utilization of deep learning models has been very successful and demonstrated good performance in the classification of HSIs. This paper presents a comprehensive review of deep learning models utilized in HSI classification literature and a comparison of various deep learning strategies for this topic. Precisely, the authors have categorized the literature review based upon the utilization of five most popular deep learning models and summarized their main methodologies used in feature extraction. This work may provide useful guidelines for the future research work in this area.
Analysis of Engineering Students’ Understanding in Differentiate Derivative and Integral
Authors: Funny R A
Published: August 2021

Derivative and integral are such fundamental concepts for Engineering students for their advanced coursed. These two concepts are opposite each other, since Integral as an antiderivative of a function f(x) is a function, whose derivative is equal to f(x). However the Engineering students still confused to identify the difference between derivative and integral. This study aimed to examine how students distinguish the understanding between derivative and integral in a sample of second-year aerospace engineering students in one of the private universities in Yogyakarta, Indonesia, and how they solve it. These two concepts have been taught in their high School and first-year in university. The instrument of this study applied the same problems for two questions, to derived and also to integrated, in order to find students understanding in distinguishing the concepts. Qualitative research was chosen as it can describe the students thinking in answering the test. The result reveals how students differentiate solving Derivative and Integral. One-third of these students do not use the symbol of derivative or integral in solving the question. Most of them just use one symbol, which the majority is derivative, the rest do not use any symbol. Using symbol helps students to answer correctly when dealing with two opposite concepts such as derivative and integral. Thus, conceptual and procedural understanding play a further important role. Integral procedures appear to be avoided because of the complex formulas that involve fractions.
Developing the scripting task for mathematical connection between the university and school mathematics content
Authors: Pramasdyahsari A S
Published: August 2021

The pre-service mathematics teachers (PMTs) found abstract algebra is difficult and irrelevant to the secondary teaching. Even though several studies have elaborated the connection between them, they cannot explicitly use its connections. Therefore, the study aimed to describe the development of a scripting task design that encourages the secondary mathematics pre-service teacher to use the mathematical connection from abstract algebra to solve the school mathematics problem. The study involves the educational research and development cycle refers to Borg and Gall’s model, which is adjusted to the need of this study. The research procedures consist of three main stages: collecting data, planning, and developing the product. In designing the scripting task, several task principles were involved, such as necessity, two-way synergy, interest, focus, awareness, and self-reflection. The scripting task was developed through at least two considerations that are accomplishing both professionally relevant and mathematically rigorous goals and the relevance of topic for both the university and school mathematics. There is a significant need for further studies for implementing this scripting task to see teachers’ awareness in using the mathematical connection from university mathematics to help their students solve school mathematics problem.
Variation theory-based mathematics teaching: The new method in improving higher order thinking skills
Authors: Baskoro I
Published: August 2021

Variation theory-based mathematics teaching emphasizes variation as necessary condition for learners to be able to discern new aspects of an object of learning. The study aims to describe whether the variation theory-based mathematics teaching is more effective than mathematics teaching using scientific approach in terms of higher order thinking skills of vocational school. This study is quasi-experimental research whose population is all grade X, students of Cipta Bhakti Husada Vocational School. The data collecting instrument in this research was a test, consisting of the higher order thinking skills questions. The result of the study at significance level of 5% show that the variation theory-based mathematics teaching is more effective than mathematics teaching using scientific approach.
Mathematics teacher professional development program: fostering the skills for teaching meaningful mathematics through active learning during pandemic era
Authors: Nurhasanah F , Usodo B , H Ekana C , Kuswardi Y , Sutopo  , Lestari S
Published: August 2021

This is a report of a community service program for mathematics teachers. This program was held for fostering mathematics teachers’ skills in teaching meaningful through active learning using Google Classroom flat form. The program takes place in the Karanganyar region, Surakarta, Indonesia. The participants of this program were junior high school mathematics teachers from Karanganyar district. They were 28 participants. The workshop was held for three days: two days were face-to-face workshop and one day for the online workshop. There are four main topics for the workshop: (1) active learning; (2) Mathematical Abstraction and Mathematical Skills; (3) Developing Question and Students Worksheet; and (4) Designing Active Learning on Google Classroom. The development of offline and online modules in the workshop was based on the theory of I-CARE model. I-CARE Model comprises of five components: Introduction, Connection, Application, Reflection, and Extension. The module consisted of a package for doing workshop which is: Powerpoint slides for offline and online courses; word documents for explaining the structure of the workshop and the worksheet of the participants; a Google classroom for online activity. Due to the pandemic session, the activities of discussion during the workshop were held on online flat form in Google Classroom.
Pre-service teachers’ integrated curriculum approaches to STEM education in classrooms
Authors: Jun-On N , Kaya J
Published: August 2021

This study aims to explore the integration approach employed by pre-service teachers in their STEM lessons. In-depth interviews with six pre-service mathematics teachers and ten pre-service sciences teachers from Lampang Rajabhat University were employed. The interviews were analyzed using the conceptual framework of the curricula integration model described by Robin Fogarty, focusing on the approaches used by pre-service teachers to STEM education. The study revealed that most participated pre-service teachers use connected and shared approaches to STEM education, and they only appeared if standard textbooks provide a guideline. The use of the integrated approach across disciplines by pre-service teachers is infrequent. This study also revealed that pre-service teachers reject subject-integration in their classroom as well as the necessity of implementing technology in their teaching because of time limitations. The findings of this study possess practical importance that they can be utilized for the modification of teacher education and training programs in Lampang Rajabhat University. Consideration of the findings may contribute to the development of the Thailand National Core Curriculum and its objectives. Additionally, there was a contribution to add literature to STEM education in Thailand.
Designing STEM-based AJarMat activities for the study from home program
Authors: Susanto A , Danoebroto S W
Published: August 2021

AJarMat or “Ayo Belajar Matematika” was a movement program that involved teachers and parents in guiding children to learn mathematics at home. Especially during a pandemic, learning is done from home so its need parental support. This study aimed to determine parents’ role in assisting children to learn mathematics at home, obtain a STEM-based AJarMat activities design that can be supported by parents, and know the strengths and weaknesses of the design from the parent’s perspective. This research began with a survey on parental perceptions followed by a focus group discussion with two AJarMat ambassador teachers who had attended STEM training and two teacher trainer who had experienced in STEM and AJarMat. The participants of AJarMat from Jaten Public Elementary School were 26 parents of grade VI students. Data were collected using a Likert scale questionnaire 1 to 4, interview and document study then analyzed by descriptive statistics and qualitative analysis. The results showed that parents mainly act as motivators for children to learn mathematics at home. Furthermore, STEM-based AJarMat activities that parents can support include a project to make necklaces from seeds for integer learning and a cake-making project for learning fractions. On the other hand, the strengths of this design are using creative activities and using real objects as counting objects so that students find it easy to understand mathematics, are enjoy and not bored. Lastly, the weaknesses of this design are the difficulty in obtaining materials and the process of making requires special skills and patience.
Using technology, hands-on, and fieldwork activity for GLOBE learning in secondary school
Authors: Umbua L
Published: August 2021

As technology plays a crucial role in daily life, The Institute for the Promotion of Teaching Science and Technology (IPST) has designed “GLOBE Trees around Us” workshop based on GLOBE protocols (Green-Up, Green-Down, and tree height) using learning elements in order for students to measure tree height through mobile application together with Green-Up and Green-Down protocols through lecture and hands-on activities. According to the results from 150 student’s handbooks, more than 87% of students were able to understand Green-Up, Green-Down and tree height protocol by using video clips, paper leaf mock-up, mobile application and fieldwork activity. From the interview of nine teachers from four schools about the Green-Up activity, it shows that about 80% of students concentrated on the workshop better than they did in the classroom and felt enjoyable during the hands-on activity. In terms of the learning elements, it is found that almost 90% of teachers thought they were beneficial to apply in this workshop, especially the GLOBE Observer application. All the teachers agreed that the application is easy to use, and all related materials are easy to prepare. However, the limitation of activity is that the application is not compatible with some devices. Teachers also planned to use the learning elements in classroom or science camp to promote student interest and understanding. In addition, the students may gain problem-solving, collaboration, communication, and thinking skills from attending this workshop.
Integrated STEM education in the thai secondary schools: challenge and addressing of challenges
Authors: Suriyabutr A , Williams J
Published: August 2021

In response to the development of technology and to advance global competitiveness, many nations now face a shortage of a suitably trained STEM workforce. To develop the STEM workforce, STEM education has been integrated into the curriculum, which presents a range of challenges for teachers. Thailand is also in the process of integrating STEM education into their educational system. This paper aims to review the integration of STEM education in Thailand, focusing on the challenges of this implementation. Results from the literature reviewed suggest the challenges of STEM integration in Thailand consists of students’ low engagement in learning in the STEM disciplines, challenges in integrating engineering, and teachers’ knowledge and skills in teaching STEM integration. It also provides a review of possible solutions to each including engaging students by using questioning techniques, using the engineering design process (EDP) as a method to integrate engineering, and support teachers in professional development and collaborative partnerships.
Implementing the Earth System Science Curriculum in School through Research-Based Learning and Technology Enhancing 21stCentury Skills
Authors: Mongkonthan S
Published: August 2021

According to IPST responsible for promoting the teaching of science from elementary to upper secondary schools in Thailand, IPST has developed Earth System Science curriculum since 2009 to raise understanding of the earth system, promote awareness of environmental problems, and increase 21stcentury skills in young generation. This study focused on implementing the ESS curriculum in schools to enhance 21stcentury skills and inspire students to become a young scientist based on research and technology. The process starts with recruit universities to be a partner, arrange a workshop, implement curriculum in school and finally, record student and teacher satisfaction by quantitative descriptive. After twelve years, the results show that, IPST and partners have implemented ESS curriculum in 896 participating schools of normal schools and enrichment science classroom schools all over the country. The schools integrated the curriculum as an additional subject, science subject, and science camps. ESS curriculum created research-based learning in STEM allowing students to employ their knowledge from various disciplines to conduct environmental research. Participants, including students and teachers had positive attitudes toward the curriculum, not only develop research skills, but also the 21stcentury skills, namely critical thinking, collaboration, communication, information literacy, technology literacy and social skills.
Individual deformability compensation of soft hydraulic actuators through iterative learning-based neural network
Authors: Sugiyama Taku , Kutsuzawa Kyo , Owaki Dai , Hayashibe Mitsuhiro
Published: August 2021

Robotic devices with soft actuators have been developed to realize the effective rehabilitation of patients with motor paralysis by enabling soft and safe interaction. However, the control of such robots is challenging, especially owing to the difference in the individual deformability occurring in manual fabrication of soft actuators. Furthermore, soft actuators used in wearable rehabilitation devices involve a large response delay which hinders the application of such devices for at-home rehabilitation. In this paper, a feed-forward control method for soft actuators with a large response delay, comprising a simple feed-forward neural network (FNN) and an iterative learning controller (ILC), is proposed. The proposed method facilitates the effective learning and acquisition of the inverse model (i.e. the model that can generate control input to the soft actuator from a target trajectory) of soft actuators. First, the ILC controls a soft actuator and iteratively learns the actuator deformability. Subsequently, the FNN is trained to obtain the inverse model of the soft actuator. The control results of the ILC are used as training datasets for supervised learning of the FNN to ensure that it can efficiently acquire the inverse model of the soft actuator, including the deformability and the response delay. Experiments with fiber-reinforced soft bending hydraulic actuators are conducted to evaluate the proposed method. The results show that the ILC can learn and compensate for the actuator deformability. Moreover, the iterative learning-based FNN serves to achieve a precise tracking performance on various generalized trajectories. These facts suggest that the proposed method can contribute to the development of robotic rehabilitation devices with soft actuators and the field of soft robotics.
Climate change shifts forward flowering and reduces crop waterlogging stress
Authors: Liu Ke , Harrison Matthew Tom , Archontoulis Sotirios V , Huth Neil , Yang Rui , Liu De Li , Yan Haoliang , Meinke Holger , Huber Isaiah , Feng Puyu , Ibrahim Ahmed , Zhang Yunbo , Tian Xiaohai , Zhou Meixue
Published: August 2021

Climate change will drive increased frequencies of extreme climatic events. Despite this, there is little scholarly information on the extent to which waterlogging caused by extreme rainfall events will impact on crop physiological behaviour. To improve the ability to reliably model crop growth and development under soil waterlogging stress, we advanced the process-basis of waterlogging in the farming systems model Agricultural Systems Production Systems sIMulator. Our new mathematical description of waterlogging adequately represented waterlogging stress effects on the development, biomass and grain yield of many commercial Australian barley genotypes. We then used the improved model to examine how optimal flowering periods (OFPs, the point at which long-term abiotic stresses are minimal) change under historical and future climates in waterlogging-prone environments, and found that climate change will reduce waterlogging stress and shift forward OFP (26 d earlier on average across locations). For the emissions scenario representative concentration pathway 8.5 at 2090, waterlogging stresses diminished but this was not enough to prevent substantial yield reduction due to increasingly severe high temperature stress (−35% average reduction in yield across locations, genotypes and sowing dates). It was shown that seasonal waterlogging stress patterns under future conditions will be similar to those occurring historically. Yield reduction caused by waterlogging stress was 6% and 4% on average across sites under historical and future climates. To adapt, both genotypic and management adaptations will be required: earlier sowing and planting waterlogging tolerant genotypes mitigate yield penalty caused by waterlogging by up to 26% and 24% under historical and future climates. We conclude that even though the prevalence of waterlogging in future will diminish, climate change and extreme climatic events will have substantial and perverse effects on the productivity and sustainability of Australian farms.
Orthogonal projections on hyperplanes intertwined with unitaries
Authors: Słomczyński Wojciech , Szczepanek Anna
Published: August 2021

Fix a point in a finite-dimensional complex vector space and consider the sequence of iterates of this point under the composition of a unitary map with the orthogonal projection on the hyperplane orthogonal to the starting point. We prove that, generically, the series of the squared norms of these iterates sums to the dimension of the underlying space. This leads us to construct a (device-dependent) dimension witness for quantum systems which involves the probabilities of obtaining certain strings of outcomes in a sequential yes–no measurement. The exact formula for this series in non-generic cases is provided as well as its analogue in the real case.
Study on the allocation of soil and water conservation measures for photovoltaic power station in rocky desertification mountainous area of Guizhou province
Authors: Tan Wei , Cao Shuanghe , He Yao , Li Yangsong
Published: August 2021

Stony desertification is widespread and, and the ecology is very fragile in the southwest Guizhou province. The careless and unreasonable water and soil conservation measures have caused serious water and soil loss and serious damage to the ecological environment. This paper takes a photovoltaic project in this area as an example to study soil and water conservation measures. Based on the author’s practical experience, a scientific and reasonable arrangement system of soil and water conservation measures and preventive management measures are proposed, which can not only provide reference for the prevention and treatment of soil and water conservation of similar projects, but also can be used to guide the main design and site construction, which has a strong guiding significance.
Research on the Evolution Trend of Energy Enterprise Organization Form
Authors: Zhao Jian , Cheng Jiaxu , Xu Yunfei , Wang Han , Sun Lichun
Published: August 2021

With the development of digital technology, energy enterprises have turned to digital transformation. In this context, the organizational form of energy enterprises will also change. This study put forward the path of energy enterprise organizational reform. Taking EDF, Tokyo Electric Power Company and other companies as examples, the study summarized the factors that influence the choice of energy enterprise organization. Finally, the study pointed out the future evolution direction of energy enterprise organization.
Demand Forecasting of Agricultural Cold Chain Logistics Based on Metabolic GM (1,1) Model
Authors: Wang Meng , Li Xin
Published: August 2021

The cold chain logistics is an important part of the whole logistics industry, with the rapid development of China’s economy, people’s living standards rising, consumer demand transformation, people’s demand for cold chain logistics is becoming more and more big, however, in the cold chain logistics industry, gradually increased demand for agricultural products in the public, this article selects 2014-2019 China’s cold chain logistics of agricultural products Based on the metabolic GM(1.1) model, the demand of cold chain logistics of agricultural products in China in the next five years is predicted. The predicted experimental results can provide data reference for relevant departments, in order to provide theoretical support for promoting the balance between supply and demand of cold chain of agricultural products.
Bibliometric Analysis on Decontamination of Chemical Warfare Agents in Last Thirty Years
Authors: Huang Xingqi , Chen Jingfei , Zhao Ting , Jin Yanren , Yan Chunxiao , Wu Yue , Zhang Lingxuan
Published: August 2021

Occurrence of large-scale biochemical wars is of little possibility today, but the international chemical security situation is still not optimistic. Effective decontamination of chemical warfare agents has received close attention, becoming a global necessity. In this paper, data in the Web of Science Core Collection database were selected to systematically investigate the relevant literature about the research progress on decontamination of chemical warfare agents from 1990 to 2020. Origin Pro 2019b and CiteSpace were conducted for multi-dimensional bibliometric analysis on literature type distribution, number of annual publications, countries, institutions, journals, authors, literature co-citation and citation bursts. By August 1, 2020, there are 2,602 papers related have been published and the number of annual publications shows a linear growth tendency. Amongst all 71 countries, United States is the country with the most publications as well as the largest centrality value. US ARMY ranks fourth in the number of publications while with the highest institution-based cooperation. “Nerve agents and blister agents”, “metal-organic frameworks” and “applications of metal-organic frameworks” are prevailing in recent years, which highlights the latest development direction and research frontiers. This article promotes scientific predictions and impact assessments of decontamination of chemical warfare agents.
Potential and contribution factors of carbon emission reduction in the power sector of BTH (Beijing-Tianjin-Hebei) region
Authors: Gao Yanghe , Li Wenxuan , Huang Ren
Published: August 2021

Beijing-Tianjin-Hebei region is not only the national key strategic development area, but also the main battlefield of low-carbon transformation. Beijing-Tianjin-Hebei region accounts for about 1/5 of the national carbon emissions, of which the power sector accounts for a large proportion of carbon emissions. Therefore, the research on the carbon reduction potential and contribution factors of Beijing-Tianjin-Hebei power sector is of great strategic significance to the achievement of BTH Coordinated Development and carbon neutralization strategy. Based on the comprehensive consideration of power generation, transmission, power consumption, power supply and other links, this paper constructs a bottom-up accounting model of CO2 emissions in power industry, and studies the main driving factors affecting carbon emissions by using LMDI method.
Semi-industrial experimental research on the influence of moisture on air dense medium fluidized bed separation
Authors: Li Lingyue
Published: August 2021

This paper conducted a semi-industrial experimental study on the influence of moisture on air heavy medium fluidized bed separation. The research results show that with the increase of coal moisture, the separation accuracy of the separator decreases. When the coal external water is 6.83%, it is difficult to effectively sort the coal; with the increase of the sorting time, the medium moisture will increase slightly; the medium consumption of clean coal and gangue products increases with the increase of the coal external water; when the water exceeds 3%, the media consumption has an almost linear relationship with the external water content; the media with agglomeration or excessive water content is not suitable for direct use as a sorting media and needs to be dried.
Ultrasonic-assisted extraction of carotenoids from navel orange in southern Jiangxi
Authors: Guanwen Suo , Chunli Zhou , Wei Su , Qiao Yan
Published: August 2021

In this study, single factor experiment and orthogonal experiment were used to study the extraction effect of carotenoids from navel orange in southern Jiangxi Province assisted by ultrasonic technology. The experimental results showed that when hexane: ethanol=1:1 as the extraction agent, liquid to solid ratio of 1:30, extraction time of 8 min, ultrasonic power of 250 W, extraction temperature of 25°C, extraction times of 4 times, the best extraction effect of carotenoids from Gannan navel orange was obtained.
Brief introduction of an automobile radiant cooling air-conditioning system based on photovoltaic power generation
Authors: Wan Letao , Liang Zuyi , Song Xiaopeng , Xiang Qingwei , Xiao Shu , Gong Jiang , Tu Min
Published: August 2021

This paper firstly analyzes the pain points of traditional automobile air-conditioning systems, then describes the relevant research status of automobile air-conditioning systems at home and abroad, and then focuses on the principle and structure of a new system, and finally analyzes its innovation and application advantages.
Research on the Construction and Application Strategy of Precision Marketing Model for Industrial and Commercial Customers
Authors: Qingyou Yan , Guangyu Qin , Qifeng Wei , Yang Yu , Yunfeng Zou
Published: August 2021

In the new electricity market, the main body of the market has evolved from the traditional electricity generation to the multi subject, and the customer value has changed. Based on the traditional method of evaluating the electricity customer value and new value after the release of power market, design new evaluation indexes for adapting the electric reform. Fuzzy analytic hierarchy process (FAHP) and entropy weight method are adopted to combine the overall weights of the design indexes and TOPSIS method is used to evaluate customer value comprehensively. According to the two dimensions which are customer value classification and customer stickiness, the main service mode for the sale electricity agent is designed. Through the example analysis, the quantitative results and the service strategy are put forward to provide assistant decision support for the differential operation of the sale of electricity entities.
The Dynamic Effects of Agricultural Insurance Development on the Optimization of Agricultural Industrial Structure—Generalized Method of Moments Estimation Based on Dynamic Panel Model
Authors: Qinru Li
Published: August 2021

As an important tool of agricultural risk diversification, agricultural insurance plays a positive role in the optimization of agricultural industrial structure and is one of the important means to support agriculture and benefit agriculture in China at the present stage. Based on the 2010-2019 panel data of 30 provinces (autonomous regions and municipalities) in China, this paper uses the systematic generalized method of moments to empirically investigate the impact of agricultural insurance development on the optimization of agricultural industrial structure. The research results show that the development of agricultural insurance has a significant role in promoting the optimization and upgrading of the agricultural industrial structure in both the long-term and short-term. In addition, agricultural labor force, economic development level, and agricultural risk level all have a significant positive impact on the optimization of agricultural industrial structure. The fixed asset investment of farmers has a certain negative impact on the optimization of the agricultural industry structure. Finally, relevant countermeasures and suggestions are put forward based on the empirical results. The government should combine the needs of industrial structure upgrading, develop new types of insurance, and take measures to stabilize agricultural production.
Forecast of Shanghai Port Throughput Based on ARIMA
Authors: Zhang JianChen
Published: August 2021

The ARIMA model analyzes and predicts the total port throughput of Shanghai Port since its inception in 2016. The mathematical model is used to predict the port throughput, which provides a scientific basis for its formulation of port development strategies and is of great significance to ensure the sustainable development of the port.
Analysis and Research of Port Gathering and Transportation System in Tokyo Port
Authors: Xia MingZhu
Published: August 2021

Port industry belongs to the basic industry of national economy, is the most advanced window of a country’s opening to the outside world, and is an important hub for communication of economic and trade exchanges. The unimpeded collection and distribution energy directly affects the development of port throughput and the development of integrated port area. Therefore, it is one of the key factors to control the efficiency and benefit of port logistics service. This paper analyzes the existing problems of the Tokyo port distribution system and proposes corresponding countermeasures.
Study on the setting of non-motor vehicle left turn waiting area at typical intersection
Authors: Ge DaYun
Published: August 2021

Intersection as a vehicle intersection affects the traffic efficiency of the whole road network, and the mixed traffic of motor vehicles and non motor vehicles brings traffic pressure to the intersection. In order to operate and manage the intersection more efficiently, according to the setting principle of non motor vehicle left turn waiting area, this paper expounds the setting conditions and application scope in detail, and puts forward the setting and research of non motor vehicle left turn waiting area at the intersection. It is found that the setting of non motorized vehicle left turn waiting area can make effective use of the internal space of the intersection and improve its traffic capacity.
Study on fuzzy comprehensive evaluation of integrated development of transportation and postal service in Hunan Province
Authors: Li Xin , Wang Meng
Published: August 2021

Based on the data collection of Hunan Province, this paper uses SPSS software to analyze the correlation between the data of the two industries, and concludes that the development of the two industries presents the characteristics of integration. According to the characteristics of the integrated development system of the two industries, the analytic hierarchy process (AHP) was selected, and four evaluation indexes were selected from the development direction with higher integration degree of the communication and postal services. By calculating the weights of the four indexes, the comprehensive development evaluation system was established. According to the established index system and the fuzzy comprehensive evaluation method, the scoring results of the four indexes are calculated to provide countermeasures and suggestions for the integrated high-quality development of transportation and postal industry in Hunan Province
Research on the circulation of maritime documents based on blockchain technology
Authors: Liu Shaokun
Published: August 2021

Maritime goods from the shipper to the consignee will go through cumbersome trade procedures. The traditional paper documents used in this process will cause some damage to the environment. Therefore, it is proposed to introduce blockchain technology in the circulation of shipping documents, and realize paperless customer service by using its characteristics of non-tamperability traceability and trust. This paper first reviews the literature on blockchain in the shipping industry, and then analyses the risks in the circulation of shipping documents and the efficiency of document circulation. Then it puts forward the shipping document circulation system architecture based on alliance block chain, and finally gives policy suggestions.
Example of VOCs waste gas treatment in a pharmaceutical enterprise
Authors: Zhuang Zhipeng , Luo Jinglin , Xu Mingxin
Published: August 2021

This paper introduces the volatile organic waste gas pollution characteristics and the treatment status of chemical pharmaceuticals companies. According to the characteristics of volatile organic waste gas of a pharmaceutical enterprise, after comparing various treatment processes of volatile organic waste gas, the treatment process of alkali washing spray + high efficiency mist eliminator + activated carbon adsorption + nitrogen desorption + condensation was finally adopted. Waste gas treatment scale of 60000m3/h, after stable operation of the equipment. Each emission index reaches the air pollution emission limit stipulated in the “Emission standard of air pollutant for pharmaceutical industry” (GB37823-2019).
The Earth Environment Change Detection Method Based on the Variable Weight Markov Random Field Combined with the Space Gravity Model
Authors: Zhao Ping , Yang Wanyun , Zhao Jian , Liu Dandan , Li Xianye
Published: August 2021

For the traditional earth environment change detection algorithm based on remote sensing image, only the band information of the image is utilized, and it is difficult to obtain the defect of the complete change detection result. Based on the spectral information of the image, the change detection method based on Markov random field model introduces the spatial correlation of pixels, which improves the accuracy of change detection to some extent. However, due to the over-use of spatial correlation in the process of introducing pixel spatial information, these methods have the disadvantage of poor detection results due to the fixed weight parameters in the modelling process. Aiming at the limitations of these methods, this paper proposes the environment of earth change detection method based on the variable weight markov random field combined with the space gravity model. Using the space gravitation model, the use of pixel spatial information is more reasonable, and the idea of variable weight is introduced to improve the defect that the change detection result is too smooth due to the fixed weight parameter. Experiments on real high-resolution remote sensing image datasets verify the effectiveness and feasibility of the proposed method.
Research on the potential of water resources utilization efficiency in the North Canal Basin to improve environmental flow guarantee degree
Authors: Wang Zhuowei , Wu Leixiang , Huang Wei , Yan Xiaoping , Guan Ronghao
Published: August 2021

North Canal is one of the important tributaries of Haihe River, however, it can’t meet the requirement of environmental flow. Improving water resources utilization efficiency is one significance way to enhance the environmental flow guarantee degree, Hence, it’s significant to study the potential of improving water use efficiency of the North Canal Basin. Based on the Analytic Hierarchy Process, this paper comprehensively evaluates the water use efficiency of the North Canal Basin from 2016 to 2019, and analyses the water use efficiency improvement potential. The results show that the water use efficiency of the North Canal Basin is high compared to the national average level, and the water use efficiency of the basin is increasing from 2016 to 2019, and the comprehensive score of water use efficiency in 2019 is the highest at 0.927, and lowest in 2016 at 0.896. The water use efficiency of the North Canal Basin still has the potential to be improved, and with the promotion of ecological civilization construction in China, the environment water consumption in the North Canal Basin is increasing year by year, and the environmental flow guarantee degree of the North Canal Basin will be gradually improved.
Statistical Research on the Influencing Factors of Zhengzhou Metro Passenger Flow
Authors: Liu Xinna
Published: August 2021

Subway passenger flow refers to the number of people entering the subway per unit time, which is an important indicator reflecting the popularity and value of the subway. This paper selects Zhengzhou Metro Line 1, which is currently the most mature and has the most complete passenger flow data in Zhengzhou City. First, using SPSS software to perform principal component analysis on the original data. Second, using MATLAB software to further process the data processed by principal component analysis. Finally, through the establishment of a gray correlation model, the results of Lanzhai Station on Zhengzhou Metro Line 1 are obtained that its import and export passenger flow has the most significant impact on the passenger flow of Zhengzhou Metro Line 1.
Diesel Engine Exhaust Exposure in the Ontario Civil Infrastructure Construction Industry
Authors: Ziembicki Stephanie , Kirkham Tracy L , Demers Paul A , Peters Cheryl E , Gorman Ng Melanie , Davies Hugh W , Tenkate Thomas , Kalenge Sheila , Blagrove-Hall Nicola , Jardine Katherine J , Arrandale Victoria H
Published: August 2021

Objectives

Diesel engine exhaust (DEE) is a known lung carcinogen and a common occupational exposure in Canada. The use of diesel-powered equipment in the construction industry is particularly widespread, but little is known about DEE exposures in this work setting. The objective of this study was to determine exposure levels and identify and characterize key determinants of DEE exposure at construction sites in Ontario.

Methods

Elemental carbon (EC, a surrogate of DEE exposure) measurements were collected at seven civil infrastructure construction worksites and one trades training facility in Ontario using NIOSH method 5040. Full-shift personal air samples were collected using a constant-flow pump and SKC aluminium cyclone with quartz fibre filters in a 37-mm cassette. Exposures were compared with published health-based limits, including the Dutch Expert Committee on Occupational Safety (DECOS) limit (1.03 µg m−3 respirable EC) and the Finnish Institute of Occupational Health (FIOH) recommendation (5 µg m−3 respirable EC). Mixed-effects linear regression was used to identify determinants of EC exposure.

Results

In total, 149 EC samples were collected, ranging from <0.25 to 52.58 µg m−3 with a geometric mean (GM) of 3.71 µg m−3 [geometric standard deviation (GSD) = 3.32]. Overall, 41.6% of samples exceeded the FIOH limit, mostly within underground worksites (93.5%), and 90.6% exceeded the DECOS limit. Underground workers (GM = 13.20 µg m−3, GSD = 1.83) had exposures approximately four times higher than below grade workers (GM = 3.56 µg m−3, GSD = 1.94) and nine times higher than above ground workers (GM = 1.49 µg m−3, GSD = 1.75). Training facility exposures were similar to above ground workers (GM = 1.86 µg m−3, GSD = 4.12); however, exposures were highly variable. Work setting and enclosed cabins were identified as the key determinants of exposure in the final model (adjusted R2 = 0.72, P < 0.001). The highest DEE exposures were observed in underground workplaces and when using unenclosed cabins.

Conclusions

This study provides data on current DEE exposure in Canadian construction workers. Most exposures were above recommended health-based limits, albeit in other jurisdictions, signifying a need to further reduce DEE levels in construction. These results can inform a hazard reduction strategy including targeted intervention/control measures to reduce DEE exposure and the burden of occupational lung cancer.
MSABrowser: dynamic and fast visualization of sequence alignments, variations and annotations
Authors: Torun Furkan M , Bilgin Halil I , Kaplan Oktay I
Published: August 2021

Sequence alignment is an excellent way to visualize the similarities and differences between DNA, RNA or protein sequences, yet it is currently difficult to jointly view sequence alignment data with genetic variations, modifications such as post-translational modifications and annotations (i.e. protein domains). Here, we present the MSABrowser tool that makes it easy to co-visualize genetic variations, modifications and annotations on the respective positions of amino acids or nucleotides in pairwise or multiple sequence alignments. MSABrowser is developed entirely in JavaScript and works on any modern web browser at any platform, including Linux, Mac OS X and Windows systems without any installation. MSABrowser is also freely available for the benefit of the scientific community.

Availability and implementation

MSABrowser is released as open-source and web-based software under MIT License. The visualizer, documentation, all source codes and examples are available at https://thekaplanlab.github.io/ and GitHub repository https://github.com/thekaplanlab/msabrowser.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.
Multi-project and Multi-profile joint Non-negative Matrix Factorization for cancer omic datasets
Authors: Salazar D A , Pržulj N , Valencia C F
Published: August 2021

Motivation

The integration of multi-omic data using machine learning methods has been focused on solving relevant tasks such as predicting sensitivity to a drug or subtyping patients. Recent integration methods, such as joint Non-negative Matrix Factorization, have allowed researchers to exploit the information in the data to unravel the biological processes of multi-omic datasets.

Results

We present a novel method called Multi-project and Multi-profile joint Non-negative Matrix Factorization capable of integrating data from different sources, such as experimental and observational multi-omic data. The method can generate co-clusters between observations, predict profiles and relate latent variables. We applied the method to integrate low-grade glioma omic profiles from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia projects. The method allowed us to find gene clusters mainly enriched in cancer-associated terms. We identified groups of patients and cell lines similar to each other by comparing biological processes. We predicted the drug profile for patients, and we identified genetic signatures for resistant and sensitive tumors to a specific drug.

Availability and implementation

Source code repository is publicly available at https:/bitbucket.org/dsalazarb/mmjnmf/-Zenodo DOI: 10.5281/zenodo.5150920.

Supplementary information

Supplementary data are available at Bioinformatics online.