bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nanostructured diamond for biomedical applications
Authors: Pandey Prem C , Shukla Shubhangi , Pandey Govind , Narayan Roger J 
Published: December 2020

Abstract
Nanostructured forms of diamond have been recently considered for use in a variety of medical devices due to their unusual biocompatibility, corrosion resistance, hardness, wear resistance, and electrical properties. This review considers several routes for the synthesis of nanostructured diamond, including chemical vapor deposition, hot filament chemical vapor deposition, microwave plasma-enhanced chemical vapor deposition, radio frequency plasma-enhanced chemical vapor deposition, and detonation synthesis. The properties of nanostructured diamond relevant to medical applications are described, including biocompatibility, surface modification, and cell attachment properties. The use of nanostructured diamond for bone cell interactions, stem cell interactions, imaging applications, gene therapy applications, and drug delivery applications is described. The results from recent studies indicate that medical devices containing nanostructured diamond can provide improved functionality over existing materials for the diagnosis and treatment of various medical conditions.
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy
Authors: Virgolin M , Wang Z , Balgobind B V , van Dijk I W E M , Wiersma J , Kroon P S , Janssens G O , van Herk M , Hodgson D C , Zadravec Zaletel L , Rasch C R N , Bel A , Bosman P A N , Alderliesten T 
Published: December 2020

AbstractTo study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, thus 3D dose distributions must be reconstructed from limited information. State-of-the-art methods achieve this by using 3D surrogate anatomies. These can however lack personalization and lead to coarse reconstructions. We present and validate a surrogate-free dose reconstruction method based on Machine Learning (ML). Abdominal planning CTs (n = 142) of recently-treated childhood cancer patients were gathered, their organs at risk were segmented, and 300 artificial Wilms’ tumor plans were sampled automatically. Each artificial plan was automatically emulated on the 142 CTs, resulting in 42,600 3D dose distributions from which dose-volume metrics were derived. Anatomical features were extracted from digitally reconstructed radiographs simulated from the CTs to resemble historical radiographs. Further, patient and radiotherapy plan features typically available from historical treatment records were collected. An evolutionary ML algorithm was then used to link features to dose-volume metrics. Besides 5-fold cross validation, a further evaluation was done on an independent dataset of five CTs each associated with two clinical plans. Cross-validation resulted in mean absolute errors ≤ 0.6 Gy for organs completely inside or outside the field. For organs positioned at the edge of the field, mean absolute errors ≤ 1.7 Gy forDmean, ≤ 2.9 Gy forD2cc, and ≤ 13% forV5 GyandV10 Gy, were obtained, without systematic bias. Similar results were found for the independent dataset. To conclude, we proposed a novel organ dose reconstruction method that uses ML models to predict dose-volume metric values given patient and plan features. Our approach is not only accurate, but also efficient, as the setup of a surrogate is no longer needed.
Wavelength censoring for spectroscopy in optical functional neuroimaging
Authors: White Brian R , Padawer-Curry Jonah A , Ko Tiffany , Baker Wesley , Breimann Jake , Cohen Akiva S , Licht Daniel J , Yodh Arjun G 
Published: December 2020

Abstract
Optical neuromonitoring provides insight into neurovascular physiology and brain structure and function. These methods rely on spectroscopy to relate light absorption changes to variation of concentrations of physiologic chromophores such as oxy- and deoxyhemoglobin. In clinical or preclinical practice, data quality can vary significantly across wavelengths. In such situations, standard spectroscopic methods may perform poorly, resulting in data loss and limiting field-of-view. To address this issue, and thereby improve the robustness of optical neuromonitoring, we develop, in this manuscript, novel methods to perform spectroscopy even when data quality exhibits wavelength-dependent spatial variation. We sought to understand the impact of spatial, wavelength-based censoring on the physiologic accuracy and utility of hemoglobin spectroscopy. The principles of our analysis are quite general, but to make the methodology tangible we focused on optical intrinsic signal imaging of resting-state functional connectivity in mice. Starting with spectroscopy using four sources, all possible subset spectroscopy matrices were assessed theoretically, using simulated data, and using experimental data. These results were compared against the use of the full spectroscopy matrix to determine which subsets yielded robust results. Our results demonstrated that accurate calculation of changes in hemoglobin concentrations and the resulting functional connectivity network maps was possible even with censoring of some wavelengths. Additionally, we found that the use of changes in total hemoglobin (rather than oxy- or deoxyhemoglobin) yielded results more robust to experimental noise and allowed for the preservation of more data. This new and rigorous image processing method should improve the fidelity of clinical and preclinical functional neuroimaging studies.
Multi-channel transcranial temporally interfering stimulation (tTIS): application to living mice brain
Authors: Song Xizi , Zhao Xue , Li Xiaohong , Liu Shuang , Ming Dong 
Published: December 2020

Abstract

Objective. Transcranial temporally interfering stimulation (tTIS) is a noninvasive neuromodulation method, which has been reported to be able to affect the activity of small neuronal populations. To pinpoint smaller regions of the brain, a multi-channel tTIS strategy is proposed with larger numbers of electrodes and multiple sets of interfering fields. Approach. First, a computational model is adopted to prove the concept of multi-channel tTIS theoretically. Besides, animal experiments are implemented to activate motor cortex neurons in living mice and different frequencies are attempted. Finally, to better understand the envelope modulation properties of the two applied fields, tissue phantom measurement is conducted. Main results. The focality of six-channel (six electrode pairs) tTIS is increased by 46.7% and 70.2% respectively, compared with that of single-channel tTIS when maximal amplitude value drops by 3 dB and 6 dB in a numerical computation experiment. Furthermore, the focality of multi-channel tTIS is less sensitive to the electrode position. Confirmed with the myoelectricity signal, the movement frequencies of the contralateral forepaw are consistent with the corresponding difference frequencies. What is more, compared to single-channel (one electrode pair) tTIS with multi-channel (three electrode pairs) tTIS, the intensity of multi-channel tTIS stimulation is decreased by 28.5% on average in animal experiments. The c-fos-positive neurons of the target region are significantly higher than that of the non-target region. Results of the modulated envelope distribute around the whole region and its amplitude reaches a maximum at the interfering region. Significance. Both computational modeling and animal experiment validate the feasibility of the proposed multi-channel tTIS strategy and confirm that it can enhance focality and reduce scalp sensation.
Study on vegetable emergency support technology under epidemic
Authors: Du Hongyu , Chen Xiangning 
Published: December 2020

Abstract
As an important nutrient source in the diet of residents, vegetables are an important guarantee to enhance immunity. The outbreak of COVID-19 has led to labor restrictions, poor logistics and transportation, and changes in residents’ consumption and eating patterns, which have challenged the traditional supply model of vegetables. In response to this challenge, this study analyzes the outbreak of vegetables reserves, distribution, supply, quality and safety and the influence of supply mode in five aspects. It also analyzes how to carry out technical research in order to make timely adjustments to the supply mode of vegetable products and ensure the residents’ vegetable supply.
Operation task extraction method and application of rice operation machinery in South China based on GNSS
Authors: Li Xiaobing , Yang Jianfeng 
Published: December 2020

Abstract
According to the characteristics of rice planting and rice operation machinery in South China, the paper discusses how to use the satellite of the operation machinery to position trajectory information, to extract operation task by field based on the clustering algorithm of OPTICS, and to calculate the operation area by broken line buffer algorithm. The paper also discusses about parameter setting of OPTICS. The accuracy of extracting tasks by field can be over 84%. When the area of each task is over 3 mu (0.2 hectares), the calculation accuracy can reach over 95%. On the surface of practical application in Guangdong Province in recent three years, the algorithm can meet the requirements of operation charging and government subsidy giving, and realize accurate task differentiation and area calculation.
Ontology-based multi-sensor information integration model for urban gardens and green spaces
Authors: Hu Xin , Chen Qiang , Du Meng 
Published: December 2020

Abstract
With the continuous development of smart landscape and the application of IOT technology in urban gardens and green spaces, the environmental data and soil data collected by various sensors are conceptually inconsistent with each other. The information derived from the data is mostly used independently, and the relationship between data and information in the database is relatively simple, and it is impossible to explore deeper associations between information. To solve this problem, a multi-sensor information integration model based on ontology is studied. Based on the characteristics of the perception terminal data of smart garden management, this article analyzes the ontological relationship between various resources of the garden and green space, and builds the ontology description model of the urban garden and green space based on the five-tuple structure of the ontology and the seven-step method to realize the information integration of perception data and the description of the relationship between sensors, this model provides a unified information model for the smart garden system to achieve information sharing. This paper describes the construction of local ontology and the related methods of global mapping, illustrate the construction process of ontology, and conducts ontology reasoning and ontology query according to the result of construction.
Tech for a Better Planet: A Corpus-based Analysis of the Environmental Disclosure in CSR Reports of Huawei
Authors: Fei Liao 
Published: December 2020

Abstract
The CSR report, as a way for stakeholders and the public to understand and audit a company’s practices of social responsibilities, plays an increasingly important role in the construction of the corporate image. Aimed at exploring how Huawei addresses global environmental issues and constructs its green and responsible image as a business, this paper studies the environmental disclosure in Huawei’s CSR reports from 2010 to 2019. Taking Halliday’s Systemic Functional Linguistics (SFL) and Kress and van Leeuwen’s visual grammar as theoretical frameworks and the corpus software AntConc as the analytical tool, this study tries to investigate how the language and images are used to convey Huawei’s environmental concept and build its identity. It is shown that Huawei, by using words and images related with nature, energy conservation as well as green products, highlights the role of technology in solving environmental problems to leave the public an impression of a responsible corporate. However, Huawei doesn’t perform well in terms of guiding the public to participate in natural protection because people’s environmental role is marginalized and natural problems are hedged in the reports. It’s hoped that the findings can help companies to construct their environmental reports more effectively which will not only promote their reputation but also guide the public to protect the planet.
An Empirical Study of The Effect of Urban Street Park on Park Users’ Mood
Authors: Wang Zhipeng , Jiang Yuan , Lu Chao , Zheng Xiaokang 
Published: December 2020

Abstract
Urban street park is an important part of the urban park system, and also a kind of park with high contact frequency in people’s daily life, so it has potential promoting effect on people’s mental health. In order to test the effect of urban street park on the mood state of park users, this study took a street garden in Hefei of China as the research site and used stratified sampling method to carry out a questionnaire survey on park users visiting the park at different time periods. One way ANOVA results show that there is a significant difference in the mood changing scores among park users in the different groups of the satisfaction of the environment of the green landscape space, the resting space and the fitness space. Regression analysis results show that the park users’ satisfaction with the environment of the green landscape space and the resting space and the time spent in the park are positively correlated with their mood changes, indicating that the better quality of the environment of the green landscape space and the resting place of the park, the longer the park users staying in the park, the more positive effect of the park environment on users’ mood state. The conclusion provides a scientific basis for the related research on the mental health effects of urban parks.
Research on conventional triaxial test of recycled aggregate concrete with PVA fiber
Authors: Lin Wang Sheng , Long Zhu Bao , Li Ling 
Published: December 2020

Abstract
The DYS-2500 high temperature and high pressure rock triaxial testing machine was used to perform regular triaxial compression tests on ordinary concrete recycled aggregate concrete and recycled aggregate concrete mixed with PVA fiber. By changing the recycled coarse aggregate replacement rate of recycled aggregate concrete mixed with PVA fiber(the replacement rates, respectively, are: 0%, 30%, 60%, 100%), the performance of recycled concrete with PVA fiber was compared with conventional recycled aggregate concrete and natural aggregate concrete concerning with its mechanical properties, fracturing process, deformation as well as other characteristics of it. Studies have shown that as the replacement rate of recycled aggregate enhanced, the impact it made on its performance grows. When the replacement rate of recycled aggregate is 30%, after mixing with PVA fiber, the compressive strength of recycled aggregate concrete with PVA fiber is greatly improved, reaching 95% of the compressive strength of natural concrete. When the replacement rate of recycled aggregates is the same as the confining pressure, the peak stress of recycled aggregate concrete samples with PVA fibers is 1.12-1.36 times of ordinary recycled aggregate concrete samples.
Frame-based Conceptual Model of Smart City’s Applications in China
Authors: Gu Qinhuan 
Published: December 2020

Abstract
Starting from the development path of modern cities, this thesis expounds the conceptual-based framework of application as well as the development background and overall status of “Smart City”. Specifically, it focuses on analyzing basic applications in three major areas (smart health, smart transportation, and smart community), studies some innovative practices of smart construction in China, and prospects the challenges and trends of smart city development in China.
A Comprehensive Analysis on the Future of Algae Biofuels in China
Authors: Du Yunze 
Published: December 2020

Abstract
As the biggest developing country on this planet, China is progressing in its economy, industry, and technology at an incredible speed, but along with this rapid development is the huge demand for energy. Conventional fossil fuels cover more than 70% of primary energy supply in China, while at the same time bringing environmental and economic issues. Renewable energy, such as bioenergy, might be the solution to resolve the energy crisis faced by China. China has a mild climate, plentiful water resources, and sufficient sunshine that are suitable for algae to grow, so algae biofuels might have a bright future to fulfill the need for energy in China in an ecologically friendly way. Based on existing studies, models, and data, this paper discusses the technological possibility and limitation, economic feasibility, and environmental benefits and concerns of developing algae biofuels in China. Lastly, the paper gives several future prospects to the system in order to make algae biofuels more practical to be a both commercialized and competitive energy source in China.
Application of Phase Change Heat Storage Technology in Vehicle Engineering Field
Authors: Li Changting , Gou Fanghuai , Yu Ruifei 
Published: December 2020

Abstract
With the development of human economy and science and technology, and the problem of energy shortages has become increasingly prominent. New energy research is the focus of attention worldwide, and phase change heat storage technology is one of the main means to improve the efficiency of new energy utilization, it is a hot area of research in recent years. This paper briefly introduces the importance of phase change heat storage technology, and briefly summarizes the classification, enhanced heat transfer technology and application fields of phase change materials. The application of phase change heat storage technology in vehicle engineering is prospected and discussed.
Analysis of electric-heat characteristics and power storage capacity of emergency power supply in substation based on energy saving and environmental friendly materials
Authors: Wang Xun , Tan Yinghui , Yu Wenbo , Feng Xuemin , Ma Guoyi , Chen Ming 
Published: December 2020

Abstract
With the continuous increase of DC power system of substation, DC emergency power supply is needed for technical transformation and troubleshooting of DC power supply system. In order to study the ideal backup tool of DC power supply with light weight, small volume and easy to carry, and guarantee safety and stability of the renovation of substation dc system, this paper studies the ternary lithium ion battery with the advantages of large capacity and small volume. The paper intends to master the heating and cooling conditions of ternary lithium-ion batteries in charging and discharging process. Then, the feasibility application in substation emergency power supply of ternary lithium ion battery is analysed. The example results prove that the use of ternary lithium ion battery could meet the demand of using a variety of scenarios of transformer substation, and improve the reliability of dc power supply system.
Research and Discussion on Design Method of Energy-saving Architecture Oriented to the Full Life Cycle
Authors: Chen Li Sheng 
Published: December 2020

Abstract
The full life cycle architectural design requires to start at the design stage, fully consider the important links in each stage of architectural design, construction as well as operation management and optimize the design of green energy saving on the basis of the concept of taking the whole situation into consideration. Different from traditional architectural design, the building energy-saving design oriented to the full life cycle has higher design requirements for the integrity, coordination, integration and parallelism of the project life cycle. In this paper, it starts from the design concepts of energy saving, environmental protection and green to discuss the methods of energy saving and emission reduction in architectural design. It aims to provide some references for green architectural design.
Fault location of secondary equipment in smart substation based on switches and deep neural networks
Authors: Liu Xiaoping , Li Yalei , Li Wenzhuo , Zhang Fujia , Zhang Jinhu , Li Ang 
Published: December 2020

Abstract
With the continuous development of smart substations, the functions of switches have been continuously improved. To improve the efficiency of the operation and maintenance of secondary equipment, this article proposes a fault location method for secondary equipment in smart substations based on switches and deep neural networks. First, the key alarm signal capture function and traffic statistics function are configured on the switch. Secondly, based on alarm information, traffic statistics, and message subscription relationships, the representation of the fault feature information method is proposed. Using the training rules of deep learning, the fault location model of secondary equipment based on deep neural network is established and the fault location steps are given. Taking the line spacing of smart substations as an example, simulations verify the effectiveness of the fault location method, and good location results can still be obtained in an environment with insufficient feature information reliability.
Research progress on logistics network optimization under low carbon constraints
Authors: Fang Xiaohong , Nie Li , Mu Hua 
Published: December 2020

Abstract
In this paper, a literature review was conducted on the optimization of logistics network under low carbon constraints. This paper summarized the basic research process of logistics network optimization, and discussed the basic problems of logistics network optimization (distribution center location and vehicle distribution route optimization) and the compound optimization problems of logistics network (forward logistics network optimization and reverse logistics network optimization). In this paper, we mainly discuss the mathematical model constructed by one or more of the goals of minimum carbon emissions, minimum sum of total costs, minimum total delivery time and minimum total delivery distance, and the solving strategies using heuristic algorithms such as particle swarm optimization, genetic algorithm, and ant colony algorithm. It provided the latest technology in this field for the researchers of enterprise logistics network model and points out the future development trend.
Effect of molten salt phase change layer on thermal performance of solar vacuum collector
Authors: Xia Nanya , Wang Hua , Xie Shukuan , Ma Xiaomeng 
Published: December 2020

Abstract
A novel straight through vacuum solar energy collector with molten salt phase change thermal storage layer was proposed. Solar salt (60% NaNO3-40% KNO3) was used as phase change materials (PCMs), and the effect of phase change material layer on the thermal performance of straight-through type vacuum solar energy collector has been studied numerically. The results show that: A 13 mm thick phase change material layer was added to the collector tube with an outer diameter of 17 mm, and the heat storage was increased by 53.57%; when the solar radiation is stopped, a constant temperature of 4min-16min is maintained, and then the temperature drops more slowly than that without addition. Molten salt phase change layer can significantly reduce the influence of solar cycle and instability on the straight-through solar vacuum collector tube.