bluuebunny/crossref_metadata_2025 huggingface dataset:
Early Detection and Rescue of an Unusual Case of Pediatric Acute Liver Failure Associated with Secondary Hemophagocytic Lymphophagocytosis: Case Report from a Liver Transplant Center in India
Authors: Mittal Richa , Malhotra Smita , Jerath Nameet , Mahajan Amita , Sibal Anupam
Published: June 2021

Hemophagocytic lymphohistiocytosis (HLH) is a rare, multisystem, potentially fatal clinicopathologic syndrome. HLH presenting predominantly as pediatric acute liver failure (PALF) has been rarely reported. Early recognition is imperative to initiate life-saving treatment but is often hampered due to the rarity of this syndrome, variable clinical presentations, and nonspecific clinical and laboratory findings. In this article, we reported a case of secondary HLH (H1N1 and RSV positive) presenting as PALF from India. A previously healthy 22-month-old boy presented with fever, vomiting, and altered sensorium for 10 days. He had coagulopathy and deranged liver functions. He was evaluated for underlying etiology and managed on lines of PALF. Due to persistent bicytopenia and excessively high ferritin levels, HLH was strongly suspected though he did not fulfill all clinical criteria for the diagnosis of HLH. Presence of seizures and cerebrospinal fluid analysis was suggestive of central nervous system involvement. There was no evidence of primary HLH on genetic evaluation. Real-time polymerase chain reaction amplifications were positive for RSV and influenza A H1N1, confirming the causative triggers. After the administration of immunosuppressants and oseltamivir, the patient's symptoms improved dramatically and he recovered completely. To the best of our knowledge, this is the fourth case reported worldwide till date of successful rescue of ALF in a child associated with HLH completely without resorting to liver transplantation. Clinical vigilance is crucial for possible presence of HLH with varied initial presentations in PALF despite incomplete diagnostic criteria, with detailed etiological workup for commencing life-saving therapy in time.
Wilson Disease-Induced Acute Liver Failure (NWI = 13) Salvaged without Liver Transplant by Plasmapheresis
Authors: Mirza Nida , Bharadwaj Ravi , Malhotra Smita , Sibal Anupam
Published: June 2021

Wilson disease (WD) is a disorder of copper metabolism resulting in accumulation of copper in vital organs of the human body, predominantly in the liver and the brain. Acute liver failure in WD has a bad prognosis, especially with a score ≥11 in the revised WD prognostic index; emergency liver transplantation is considered the only life-saving option in this scenario. Here, we reported a girl patient with WD-induced liver failure and poor prognostic score who was rescued by plasmapheresis. She also manifested severe Coombs negative hemolytic anemia and acute kidney injury. This case report highlights the utility of an adjunctive modality besides liver transplantation for the management of fulminant liver failure caused by WD.
Bringing the interaction of silver nanoparticles with bacteria to light
Authors: Normani Simone , Dalla Vedova Nicholas , Lanzani Guglielmo , Scotognella Francesco , Paternò Giuseppe Maria
Published: June 2021

In past decades, the exploitation of silver nanoparticles in novel antibacterial and detection devices has risen to prominence, owing to the well-known specific interaction of silver with bacteria. The vast majority of the investigations focus on the investigation over the mechanism of action underpinning bacterial eradication, while few efforts have been devoted to the study of the modification of silver optical properties upon interaction with bacteria. Specifically, given the characteristic localized surface plasmon resonance of silver nanostructures, which is sensitive to changes in the charge carrier density or in the dielectric environment, these systems can offer a handle in the detection of bacteria pathogens. In this review, we present the state of art of the research activity on the interaction of silver nanoparticles with bacteria, with strong emphasis on the modification of their optical properties. This may indeed lead to easy color reading of bacterial tests and pave the way to the development of nanotechnologic silver-based bacterial detection systems and drug-screening platforms.
Teaching an introductory optics lab course online
Authors: Dark Marta L
Published: June 2021

In fall 2020, the Physics Department was tasked with coming up for a plan for optics, our one credit lab course. Because of the continued COVID-19 pandemic, our institution planned to offer a fully online fall semester, with no students residing on campus. The college announced the plan 5 weeks prior to the start of the semester. This paper will detail how optics was taught online using a hybrid format of delivery.
Research on the influence of college students’ self-directed learning behavior based on online learning platform
Authors: Zhang Lulu , Tian Yue , Song Shibo
Published: June 2021

COVID-19 has made physical education almost forced to move to online, and the main way to acquire knowledge has also been transformed from offline to online. Especially for college students, as a group of external conditions supporting and having a strong sense of autonomy, online learning habits will have a lasting impact on subsequent learning production, and even become the second important knowledge acquisition way besides classroom. Therefore, it is necessary to study the use of online learning platform and self-directed learning behavior of college students. Based on TAM and UTAUT, this study supplements the perception theory and self-directed learning theory by extracting the influence factors of live platform. Based on the data analysis of smartpls and SPSS, this paper constructs the structural equation model of self-learning behavior of College Students’ online learning platform, explores the external and internal influence mechanism of self-learning behavior, and provides guidance for online learning platform practitioners and college students’ self-learning behavior.
Structure and software architecture design of an extremely low-cost quadruped robot for education
Authors: Zhang Y N , An M Q
Published: June 2021

Many teachers and students face with a serious problem of costs when they build quadruped robot. This paper illustrates a complete process of creating quadruped robot with consideration of extremely low-cost limitation. The creating procedure involves 3 major issues: 1. Driving force transmission structures. 2. Applying finite element analysis (FEA) method of reducing the cost of 3D printing components. 3. To utilize proper electronic chip, sensors and propose a corresponding software system architecture. In conclude, this paper offers a feasible common framework of creating low-cost robot, the hardware architecture and software architecture are suitable for beginning students to learn about robotics.
Mobile authentication scheme based on QKD and IBE
Authors: Chu Meiling , Wu Meng
Published: June 2021

In order to handle the safety problems in mobile communication systems, a mobile identity authentication scheme based on QKD and IBE is proposed. First, the quantum key distribution technology is introduced to handle the safety problems between the private key generator and the cloud services. Next, the IBE algorithm is introduced to encrypt IMSI which makes the scheme more flexible and more efficient. Finally, the quantum time parameter is proposed to manage users’ secret key. Comparing with the existing schemes, the proposed scheme can make full use of the advantages of the QKD and IBE. The mobile identity authentication scheme based on QKD and IBE can be more safe and more efficient.
Research on innovation input of manage strategy based on data analysis
Authors: Liu Liangcan , Gu Wenjie
Published: June 2021

Self-occupaied operation is a common mode of operation in Chinese management, and self-occupaied innovation can help maintaining their core competitiveness and achieving a favorable position. For the purpose of exploring the influence on innovation input, this paper uses the data of A-share listed objects in China from 2016 to 2019, and uses the method of data analysis to perceive the effect on innovation input. The results show that self-occupaied objects are less willing to innovate. Further analysis shows that income constraints strengthen the relationship between objects and relative connections innovation input. Under income constraints, self-occupaied object is better tend to reduce innovation input. This paper improves the research on the innovation and has certain reference significance to the innovation management in China.
Research on point cloud registration of industrial parts based on FGR-ICP algorithm
Authors: Zha Yongjian , Chen Ming , Lu Shenglian
Published: June 2021

In the industrial application environment, there are some challenges to point cloud registration caused by disordered and occluded industrial parts. A point cloud registration method combining fast global alignment (FGR) and improved ICP is proposed for the problem that the traditional Iterative Closest Point (ICP) needs to rely on good initialization quality and easily falls into local optimal solutions. The method can optimize the different components of the objective function alternately by FGR to obtain the optimal initial transformation matrix. An improved ICP algorithm was used for exact matching of the initial transformation results. The experimental results showed that the method in this paper had greatly improved the matching accuracy, and the speed had been improved by an order of magnitude compared with the traditional method.
Outlier detection algorithm based on density and distance
Authors: Qu Ying , Guo Fei
Published: June 2021

In order to solve the problem that the existing outlier detection algorithm is difficult to detect the one-dimensional integer data set with uneven frequency distribution and uniform distance distribution and low accuracy, the advantages of density outlier detection and distance outlier detection can be combined. An outlier detection algorithm DAD (Density and Distance) based on density and distance was proposed. In order to improve the possibility of outlier sample distance, the algorithm can define the weight distance; introduce the global density outlier factor combined with the weight distance as the relative distance, and use the cutting edge strategy to quickly cut the outliers based on the minimum spanning tree. Then, an artificial data set was used to test the algorithm. Experimental results showed that the algorithm had a good outlier detection accuracy in dealing with data sets with uneven frequency distribution and uniform distance distribution.
Research on inquiry letter supervision and stock price crash risk based on fixed effects model
Authors: Zeng Meng
Published: June 2021

This paper examined whether different types of inquiry letters had effects on stock price crash risk. To measure the stock price crash risk, a model was built. Additionally, to study the effects, this paper used a fixed effects model based on the panel data from Shenzhen Stock Exchange and CSMAR database from 2014 to 2019. The results showed that during 2014 and 2016, inquiry letters about asset restructuring significantly reduced stock price crash risk; the risk of stock price crash may be lower when the company received more letters about asset restructuring. However, inquiry letters about regular report and others had no significant effects. During 2017 and 2019, inquiry letters about regular report significantly reduced the stock price crash risk. Similarly, the company’s stock price crash risk may be lower when the company received more letters about regular report. However, inquiry letters about asset restructuring and others had no significant impact. The research aimed to explain the role of different types of inquiry letters in the Chinese stock market through data analysis, which may provide suggestions to prevent stock price crash risk, eventually promoting the capital market's stable development.
Excel VBA programming with Excel to compute the load tranceverse distribution coefficient of G-M method
Authors: Ma Lijun , Che Guowen
Published: June 2021

In this paper, by analyzing the calculation principles of load transverse distribution coefficient of G-M method, using office software Excel, the calculation model of a universal worksheet is given, making the computation of load transverse distribution coefficient with G_M method more accurate and swift. The model is very practical, and can offer reference for bridge and highway designers.
Agglomeration and balance: the evolution patterns for regional economic divergence in the pearl river delta area
Authors: Peng Minjing , Xu Zhicheng
Published: June 2021

This study analysed the differences in the process of regional economic development and revealed the dynamic imbalance mechanism of regional economic development in Pearl River Delta (PRD). Based on the statistical yearbook of PRD 1978-2018 GDP and per capita disposable income (PCDI) data, using standard deviation, Gini index, range rate and clustering analysis methods, we analysed regional inequalities to the evolution dating back to nearly 40 years in the PRD. The cross-sectional data showed that the relative difference is stable and the absolute has always been rising in the evolution of the difference in GDP of PRD. However, in terms of PCDI, the relative difference shows a shrinking trend on the whole. Furthermore, the cluster analysis indicated that with the construction of the PRD Metropolitan Areas, the economic development is concentrated in the core cities. However, the PCDI between regions is converge. We suggested that the three major metropolitan areas should further expand and radiate outward to achieve the overall coordinated development of PRD. At the same time, less developed regions should not be afraid of the concentration of production factors in core cities. With the free flow of production factors, the gap between regions has actually narrowed.
Application of ARIMA model on prediction of China’s corn market
Authors: Zhou Liwen
Published: June 2021

ARIMA is a common model for non-stationary time series modeling, the model is essentially the combination of ARMA model and differentiate operation. This study indicated that most of the non-stationary time series can be differentially stationary by the difference of the appropriate order, and can be fitted by the ARMA model. As a relatively mature statistical method, ARIMA has been widely used in the price prediction of energy, agricultural products and stocks due to its advantages such as solid theoretical foundation and good short-term forecasting effect. In this paper, ARIMA was used to take the monthly corn price data of 23 months from April 2019 to February 2021 as the sample, processed and analyzed the data, and made a forecast analysis of the corn price in March 2021 in China. By comparing the experimental results with the actual price, it can be seen that the model established has a good fitting degree and can predict the corn price in China more accurately.
Research on short video recommendation strategy based on big data analysis
Authors: Gao Ting
Published: June 2021

In the era of information explosion, "information overload" has become an unavoidable problem. Vital information acquisition is an unavoidable problem. In the era of big data, using big data technology is undoubtedly an important thinking direction to solve data problems. Based on big data analysis and recommendation, this paper takes DIKW as the model support and takes short video personalized recommendation as an example to provide different personalized short video recommendations for different scenes. Aimed at the current information explosion era, looking for a good recommendation information system.
Evaluation model construction of automobile appearance design based on random forest algorithm
Authors: Zheng Xundong , Yi Shanshan , Deng Xiaotong
Published: June 2021

Random forest algorithm is a nonlinear supervised classification algorithm, which is based on the idea of ensemble learning and consists of multiple decision tree classifiers. The algorithm has strong generalization ability, fault tolerance ability and nonlinear fitting ability, and can learn the deep-seated laws in the sample system according to a small number of samples using information entropy as the criterion. In the form of questionnaire survey, this paper collects the main evaluation factors of automobile appearance modeling design for 100 consumers or potential consumers. After selecting the evaluation factors, 50 consumers or potential consumers score a car according to these evaluation factors, to collect the original data. Experimental results show that the accuracy of the algorithm is as high as 84%, which shows that the model has such a high accuracy that it can be applied to the evaluation of automobile appearance modeling design. At the same time, this method can also be transferred to the appearance modeling design of other models.
Face value big data multiple linear regression model analysis
Authors: Cui Faqiang
Published: June 2021

In order to explore the impact of the live video host’s face value on the consumption of viewers watching the live video, the author formed a 28-person research team from 20:00 pm to 22:00 pm every evening to conduct a 336-hour follow-up survey. A total of 488 valid online questionnaires and 56 personal in-depth interview records were collected. The author classifies the big data obtained in the survey, and then establishes a multiple linear regression analysis model, using a stepwise regression analysis method. At the same time, the Eviews10.0 is used to objectively analyze and accurately verify the classified big data. The conclusion is that the beautification degree of the live video host’s face, eyes and ears is positively correlated with the live video sales revenue, while the live video host’s mouth shape is negatively correlated with the live video sales revenue.
Construction of legal incentive evaluation model based on BP neural network with multiple hidden layers
Authors: Li Jing
Published: June 2021

BP neural network, the basic algorithm of deep learning, is a multilayer feedforward algorithm trained according to the error back propagation algorithm. BP neural network has the function of realizing any complex nonlinear mapping, which makes it especially suitable for solving problems with complex internal mechanism and has strong fitting ability. In this paper, the number, type, propagation rate and usage rate of the objects from 2013 to 2019 are collected as input and output neurons to establish a 6-layer BP neural network model. After experimental verification, the average relative error between the statistical value and the predicted value is 0.23%, which proves that the model has high prediction accuracy and can be applied in the evaluation of professional development.
Research progress and trend analysis of computer vision based on cite space
Authors: Liu Yuzhi
Published: June 2021

In recent years, with the rapid development of artificial intelligence and the proposal of efficient algorithms such as deep learning, the ability of computer vision to deal with complex problems has made a qualitative leap. Therefore, the study of computer vision is deepenly expanded from academia to industry, and the application of industry continues to be enriched. It involves many disciplines in natural science and social science. The main applications and technologies include image classification, image recognition, deep learning, convolutional neural network, etc. In this paper, the bibliometrics software CiteSpace was used to conduct visualization processing based on the literatures in the core database of Web of Science with the time span from 2010 to 2020 and the subject words as computer vision. The current situation of scientific research cooperation is analyzed from the perspectives of countries, institutions, individuals and cited literatures themselves. The involvement of computer vision discipline is analyzed from the perspectives of natural sciences and social sciences in front, and analyzed from the funding institutions. Funded institutions are analyzed from the perspective of computer vision discipline. The current research hotspots and development frontiers are analyzed by using maps. It is found that the future computer vision will focus on deep learning, transfer learning and semantic segmentation. Finally, it points out that there are some problems in the current research, such as the lack of close scientific research cooperation, the lack of comprehensive discipline involved, and the difficulty of technology implementation. Three suggestions are put forward to solve these problems: (1) Holding trans-regional academic exchange meetings to promote the sharing of academic achievements. (2) Raising the attention to the partial humanities and promote the depth of disciplines. (3) Considering the cost and efficiency in practical application to accelerate the realization of scenario application.
CO2 adsorption on graphene supported Ni catalysts
Authors: Muttaqien F , Namari N A P , Wella S A , Wungu T D K , Suprijadi
Published: June 2021

We perform density functional theory (DFT) study of CO 2 adsorption on graphene supported Ni catalyst. We implement ordinary PBE functional as well as van der Waals density functional (vdW-DF) to accommodate weakly interaction between CO 2 and graphene. Based on vdW-DF calculations, we obtained that CO 2 is physisorbed on pristine graphene, in contradiction with PBE results. The adsorption energy further increases when we introduce single Ni adatom and small Ni cluster on graphene. The adsorbed CO 2 bond angle and bond length on graphene with single Ni adatom and cluster are deformed from its gas phase condition, indicating that CO 2 is chemically adsorbed on the decorated graphene area. Our results provide useful insight into appropriate design of graphene supported metal catalysts.
Post-disaster effect on radiation safety in multihospital radiological unit: a one-year post-earthquake observation report in Lombok
Authors: Suwandi G R F , Haekal M , Bayuadi I , Craig L A , Fahmi A , Khotimah S N , Prawiro S A , Haryanto F
Published: June 2021

A series of earthquakes that hit Lombok, Nusa Tenggara Barat, in the span of August - September 2018 had caused a massive destruction and major damage especially in the structure of buildings including the radiological unit in the hospitals around the Lombok island. The damage in radiological unit building structures could cause a radiation leak in the surrounding areas and endanger the radiation safety of the hospital personnel. Many efforts were taken from the hospital itself and the government to immediately repair the damages in the structure. This study aimed to reports analysis the damage caused by the earthquake to the building structure and the efforts that were taken to repair the damages one year after the events. The measurements of exposure around the buildings were also performed to assess the results of the building renovation. The results were then compared with the radiation exposure measurements report prior to the events. A series of recommendations was then offered based on the results analysis regarding the enhancement of the shielding.
The Matrix Elements of Area Operator in (2+1) Euclidean Loop Quantum Gravity
Authors: Fahmi K , Zen F P
Published: June 2021

In this article we discuss the matrix elements of area operator in (2+1) Euclidean Loop Quantum Gravity. The Euclidean signature is chosen because it has the same group as (3+1) Lorentzian Loop Quantum Gravity that is SU (2). The techniques used follows what has been done on the volume operator in (3+1) Lorentzian Loop Quantum Gravity. Although both are referred to as volume operator, they both have significantly different forms, so the initial steps of the discussion will be different. The result show that we can express the matrix elements in terms of standard recoupling scheme basis.
Hypocenter Relocation, Determination of Velocity Model and Correction Station in Gede Volcano for December 2017 Data
Authors: Reny  , Srigutomo W. , Faizi H.N.
Published: June 2021

The distribution of the volcanoes in indonesia gives positive impacts in the form of fertile land where many residents live to grow crops. Besides having positive impacts, there are also negative impacts in the form of natural disasters. Improvement in mitigation of natural disasters is needed to avoid any form of harm and undesired losses. Information on the accuracy of earthquake parameters is an important part of natural disaster mitigation efforts. Hypocenter relocation of earthquakes is a step to improve the accuracy of earthquake parameter information. The relocation of hypocenters earthquake is performed using the Coupled Velocity-Hypocenter method. The research area is Gede volcano which is included as type A active volcanoes. The data were processed using GAD and VELEST 3.3 software resulted in epicenters that were spread around Gede and Pangrango volcanoes. The hypocentre were distributed between -2.5 – 5.2 km depths based on GAD calculated. After relocation using VELEST 3.3, they were distributed between 1.0 – 10.5 km depth. The calculated. The calculated magnitudes of volcanic earthquakes occurred in December 2017 vary between 0.6 to 2.7. the difference between the initial and final velocity models is small. After station correction step, the velocity profiles beneath the most of station is indicated as sedimentary layers, and beneath of the peak station, it is indicated as instrusive rocks.
The electrical complex impedance measurement of rock samples using simple method on Halmahera rock samples
Authors: Handayani G , Usman M H K
Published: June 2021

The electrical complex impedance is very important physical parameter to determine the fluid and matrix condition of the rock sample. One mechanism in the samples that influences this complex, frequency – dependent behaviour of resistivity is the disseminated metal ores which can block the pores and subsequently trigger the mechanism for storage/delay. Pore water ions build up on either side of the grain, results in the effect of a capacitor. This paper presents a simple experimental set up to measure the complex resistivity of rock samples. The main mechanism is generation of high voltage sinusoidal signal. This is implemented as collector voltage of a transistor. The high voltage sinusoidal signal then is applied on either side of the rock sample. At two distances of the sample we measure the resulting voltage using the oscilloscope. The observed delay can be considered as the measured phase, whereas the amplitude of the observed voltage is considered as the voltage. We determine the absolute impedance as the voltage divided by the current. Using this simple method we measured the complex impedances of 14 rock samples obtained from Halmahera Island. From the results of measurement, we tried to infer and to model the disseminated metal ores of the samples.
Laboratory study of the performances of two individual Condensation Particle Counters
Authors: Bau Sébastien , Payet Raphaël
Published: June 2021

In the general framework of investigating the performances of instruments that can be deployed in occupational hygiene to assess exposure to airborne nanoparticles, this study aims at providing new data relative to two new specimens of individual Condensation Particle Counters (CPC). Though a variety of instruments are available on the market, CPC constitute the devices that are used the most. Designed by the American company Enmont LLC, the first individual CPC allow personal measurements to be carried out. Here, the reliability of the PUFP C110 and C200 has been characterized in the laboratory. Our experimental results highlight that both individual CPC under study are impacted by both particle size (underestimation of the number concentration of ~20% when the modal diameter is lower than 40 nm, n = 21) and hydrophobicity (-60% to -90% compared to the reference concentration when aerosols are hydrophobic, n = 15). Except from these specific cases (n = 44), both individual CPC have a comparable and satisfying response (+30% with regards to the reference concentration).
Assessing a national nanotechnology infrastructure for enforcing nanosafety in consumer food - Funding the infrastructure
Authors: McCarron E , Chambers G
Published: June 2021

Crucial to assessing any national risk assessment infrastructure is the development of keen insights into the funding landscape, the base skill set and expertise levels, risk prioritisation, and stakeholder determination. This paper presents an overview of the first of these criteria with respect to the Irish funding landscape for nanotechnology and nano-agri-food. It examines difficulties with policy enforcement due to a lack of clarity and varying interpretations of the EU definition of nanomaterials and how the funding landscape could potentially facilitate the necessary infrastructure, to underpin regulatory enforcement and risk assessment for nanotechnology in food. In 2008 an assessment of the potential risks associated with nanotechnologies was carried out in Ireland which resulted in a number of recommendations centred around the provision of funding. This study examines Exchequer/public investment over the last decade to develop research infrastructure and it identifies if such investment has helped enhance the enforcement of nano-food safety legislation in Ireland.
Thiolate chitosan nanoparticles capable to delivery nitric oxide: synthesis, characterization and antibacterial potential
Authors: Pelegrino M T , Natividade T R , Gonçalves M C , Nakazato G , Seabra A B
Published: June 2021

Nitric oxide (NO) is a small but powerful molecule. It is involved in several biological pathways such as vasodilation, wound healing and toxicity towards pathogens. At high concentrations, NO has a toxicity towards bacteria, virus and fungi which has a great biomedical potential. However, NO has a small half-life of just a few seconds and this hazards its clinical application. In this scenario, the combination of nanotechnology with NO donors can create new strategies to load and deliver NO. Polymeric nanomaterial intrinsically have advantages such as low toxicity, biodegradability and low-cost. In this study, we used chemically modified chitosan (CS) to prepare nanoparticles capable of loading and releasing NO with antibacterial activity. CS was chemically modified to add a thiol group (-SH) to its structure. This modification was performed by the reaction with thioglycolic acid (TGA) in the presence of a carbodiimide (EDC). The thiol groups in CS structure serve a double function: create an anchorage site for NO and increase polymer mucoadesivity. The synthesis of thiolated chitosan nanoparticles (TCS NP) occurred by ionotropic gelation method using sodium tripolyphosphate (TPP) as counter ion. The NO donor precursor molecule, mercaptosuccinic acid (MSA), was encapsulated into TCS NP to increase loading capacity of NO. To identify the best paraments of the synthesis we used the ratios 1:3, 1:4, 1:5, 1:6 and 1:7 for TCS:TPP. TCS NPs were characterized by dynamic light scattering (DLS), microscopy electron transmission (MET) and nanoparticle tracking analysis (NTA). The release of NO was characterized by a kinetic using Uv-vis spectroscopy. Finally, the antibacterial potential was evaluated by minimum inhibitory concentration (MIC) assay against Staphylococcus aureus, Streptococcus mutans and Escherichia coli strains. The ratio 1:5 showed the most adequate size parameters and the other analysis were performed using it. The hydrodynamic size was found to be 113.0 ± 1.6 nm, PDI of 0.292 ± 0.035 and zeta potential of 27.1 ± 0.9. The MET images indicated small and spherical nanoparticles. The kinetic profiles showed a linear release of NO reaching the 100% after 150 min. The antibacterial effect was tested for E. coli, S. aureus and S. mutans. The MIC values was 50 µg mL for NO-CS NP, this result was 50% lower compared to TCS NPs for S. mutans and E. coli. The TCS NP has suitable properties for the biomedical field with potential for antibacterial application.
Reservoir ecological operation by quantifying outflow disturbance to aquatic community dynamics
Authors: Wang Yibo , Liu Pan , Wu Chen , Li Xiao , An Rihui , Xie Kang
Published: June 2021

Reservoir operation causes spatiotemporal variations in outflow, which influence the dynamics of downstream aquatic communities. However, empirical evidence of community responses to hydrological alteration remains limited for dam-regulated rivers. This study focused on quantifying the streamflow disturbance to multi-population dynamics in downstream of the China’s Danjiangkou Reservoir. First, the stochastic population dynamics model (PDM) was used to simulate aquatic community dynamics. Then, the flow–ecology relationship was established to identify community response to reservoir outflow. Third, two novel ecological indicators, stable time (ST) and coefficient of variation at stable time (CVST), were proposed to evaluate the resilience and resistance of multi-population systems, respectively. Finally, the reservoir operating rule curves were optimized by considering tradeoffs between socioeconomic and ecological objectives. The coevolution processes of multi-population systems (fish, phytoplankton, zooplankton, zoobenthos, and macrophytes) were simulated by stochastic PDMs. The population densities of stable states showed continuous downward trends with increasing degree of hydrological alteration for multi-population systems, and aquatic community systems could be destroyed when alteration reached its acceptable maximum. The greater the degree of hydrological alteration, the longer the recovery time from an unstable to a stable state, and the weaker resistance for each population system. The resilience and resistance of downstream multi-population systems were enhanced by optimizing reservoir outflow. The optimization results illustrated that the performances of the multiple objectives of water supply, hydropower generation, and ST were improved by 2.37%, 2.40%, and 2.67%, respectively, whereas the performance of CVST was the same as the conventional operation. The flow–ecology relationship provided an approach to quantify the impacts of reservoir outflow on an aquatic community, which is helpful in guiding ecological flow strategies.
Multi-criteria decision approach with stakeholders for food waste management
Authors: Abu R , Aziz M A A , Sapuan N , Abdullah T A T , Hassan C H C , Noor Z Z
Published: June 2021

The activities related to agri-food production and the disposal of its waste account for a large number of greenhouse gas emissions. In many cases, food waste (FW) management is established by making a single assessment for its sustainability based on economical or environmental impacts. However, social impact assessments on stakeholders are often incomplete or missing, and its efficiency is seldom measured. Decision-making in waste management strategies, such as the acquisition of appropriate waste treatment sites or methods used, frequently involves multiple stakeholders such as government, municipalities, industries, experts, or public sectors. Due to the complication of differing criteria and alternatives in FW management technology, a multi-criteria decision-making (MCDM) methodology is recommended to certify the quality of the decision-making process. This paper reviews the use of MCDM as decision supporting techniques in modelling and analysing decision making in situations with multiple stakeholders for FW management. The synthesis results obtained through the MCDM tool will be more reliable when requesting confirmation from stakeholders based on a recommended minimum range of criteria for each sustainability dimension in the FW issues. Finally, potential studies in this area have been proposed.
Nutrient digestibility of dairy cows fed with chopped and ensiled elephant grass
Authors: Pratama A , Salundik  , Jayanegara A
Published: June 2021

Forage scarcity hinders the development of the dairy farm. Developing measures for preserving and optimizing forage supply are among the solutions to cope with this problem. This research aimed to evaluate nutrient digestibility of dairy cows given different forage treatments. The forage used was elephant grass (EG, Pennisetum purpureum) and subjected to four dietary treatments, i.e., intact EG (FW), chopped EG (FC), ensiled EG (SW), and ensiled and chopped EG (SC). Proximate analyses were performed on the respective treatments. The in vivo evaluation was then conducted by feeding the diets to dairy cows with a 4 × 4 Latin square design set (n=4 replications). Each period’s length was 21 days, in which the first 14 days was for feed adaptation, and the last seven days was for collecting data. Results showed that chopping and ensiling treatments improved daily feed consumption. Ensiled EG (SW and SC) resulted significantly (p<0.05) higher in dry matter, organic matter, and crude fat digestibility compared to non ensiled EG (FC and FW). Crude protein digestibility for SC treatment was significantly higher (p<0.05) among all treatments. Crude fiber digestibility for SC treatment was also significantly (P<0.05) higher among all treatments with an exemption of SW. The effectiveness of treatments on feed consumption and nutrient digestibility can be sorted, as follows SC>SW>FW>FC. It can be concluded that combination of chopping and ensiling (SC) proved the best result and thus may be implemented to preserve and optimize forage supply.
Image High Frequency Information Restoration Algorithm Based on Deep Learning
Authors: Ma Liang , Zhou Rongji , Zhang Ke
Published: June 2021

In order to effectively recover the high-frequency information of images, this paper proposes a deep neural network based on feature compensation to reconstruct super-resolution images. In this method, intensive deep convolutional neural network and residual network are combined, and the high-frequency information of the original image is extracted separately after up sampling and fused with the reconstructed super-resolution image to form high-frequency feature compensation, which can improve the image quality. Through experimental comparison, the effect of the super resolution image reconstructed by the proposed algorithm is improved by about 1dB compared with that reconstructed by the SRCNN algorithm.
Research on Incentive Choice of Public Order Based on a Survey of Shared Bicycle Parking
Authors: Zhang Yuxuan , Zhou Yaodong
Published: June 2021

Taking the shared bicycle parking order as the starting point, a variety of scenarios (daily, hurry, and other people’s violations) and two freeloading psychological incentives (speculation and conformity) are constructed. It is believed that (1) The effect of incentives on individual travelers is limited, and there are certain internal distortions in the two-dimensional effects of norms and travel. (2) Incentives are effective for speculative travelers, while they have no significant effect on herd mentality travelers. Even drive travelers with a strong sense of social norms deviate from normative behavior. (3) Travelers with stronger speculative psychology are more sensitive to the time loss that may be embedded in incentives. (4) The range of available incentives with unique characteristics is different. The applicability of electronic fences is relatively stronger.
Structural analysis of pile-foundation offshore platform
Authors: Yin Qingguo , Zhang Xiaochun , Jiang Xiaobo , Li Haiwei , Yang Ling , Wang Xiaoyan , Dong Yuezhou , Zhu Yan
Published: June 2021

This paper takes the pile-foundation platform of Dagang Oilfield in paralic zones as the research object, provides a reference basis for further selection by analyzing the advantages and disadvantages of single platform type and multi-platform type. The key structural parameters including platform load calculation, deck bottom elevation determination and ultimate bearing capacity calculation of pressurized piles are analyzed and studied. The specific ideas of pile-foundation platform design are proposed, and the analysis process and important formulas of the methods used in the design are elaborated to give the research results, which has high reference significance for the old platform to extend its service life and the construction of the new platform.
Analysis and Optimization of Saline-alkaline Water Comprehensive Utilization System
Authors: Sun Zhilin , Zhai Chaoqun , Shu Junwei
Published: June 2021

On the basis of the previous field experiment and the actual situation in Xinjiang, four saline-alkaline water comprehensive utilization systems are proposed to optimize concentration and desalination process. Based on chemistry, thermodynamics and heat transfer, combined with economic costs and benefits, steam production and entransy are analyzed in this paper, the results show that the comprehensive efficiency of the dual heat source system is better than that of the single heat source system. Two-stage dual heat source system with series and parallel multi pass heat collecting has the best efficiency, but the comprehensive efficiency is similar to that of single-stage dual heat source system. These systems have their own strengths, which provide reference for brine treatment in salinization areas.
Numerical simulation studies of the flow field and pollutant dispersion in the street canyon under different thermal stratifications
Authors: Shi Xuefeng , Guo Dongpeng , Yao Rentai
Published: June 2021

This paper simulates the flow and dispersion in the street canyon under different thermal stratifications using three-dimensional (3-D) Computational Fluid Dynamics (CFD) methodology, and compares the simulated results with the wind-tunnel experiment data reported by Uehara et al. Monin-Obukhov length (L) is used to describe the atmospheric flow under different thermal stratifications. The results show that the effect of thermal stratification on the flow structure and pollutant dispersion within the street canyon is significant. The magnitude of velocity in the middle part of the street canyon is relatively small under different conditions. The intensity of vortex is significantly influenced by thermal stratification. The maximum value of k/U
700
2 appears near the windward corner of the building under different conditions. The high-concentration region appears in the upwind part of the canyon. The normalized concentration on the leeward side is greater than those of windward side within the street canyon under different conditions.
Preparation of Activated Carbon-PVDF Blend Membrane and Its Effect on the Decolorization of Azo Dyes
Authors: Ye Qian , Li Jin , Han Qi , Xu Meilan , Jiang Linyu , Yan Bin
Published: June 2021

In this article, various ratios of activated carbon and amounts of the cross-linking agent were used to prepare mediator functionalized PVDF membrane with N, N-dimethylacetamide (DMAc) as the solvent and polyvinylidene fluoride (PVDF) as the polymer. The membrane structure was characterized by an electron microscope. Moreover, the influence of the prepared membrane on the decolorization rate of the dye was investigated to optimize the addition amounts of activated carbon and the cross-linking agent. As the addition amount of cross-linking agent in the blend membrane increased, the decolorization effect continuously improved. However, the decolorization rate tended to be stable when the cross-linking agent reached a specific value. The addition of activated carbon significantly accelerated the rate of degradation and decolorization of the microbial system.
Desertification Combating in the Mauritania
Authors: You Yuan , Zhou Jie , Wang Yongdong
Published: June 2021

The Islamic Republic of Mauritania known as “the desert of the Republic”, is located in the Western Sahara, which accounted for 2/3 land area of it, the remaining belongs to the edge of the desert semi-desert areas. With the purpose of survival, people are forced to deforestation destroyed the grass, excessive land reclamation, pasture overload use, which has formed a “deepening poverty and desertification, exacerbated by desertification poverty” vicious circle. The paper summarizes the present situation of Mauritania on combating desertification, two aspects of causes and problems in desertification from natural factors and human factors were analyzed respectively, characteristics and countermeasures arising in a desertification combating. Desertification has seriously threatened the people’s survival and development, which have become the country’s urgent need to face. The Mauritanian government has taken a series of effective measures on combating desertification, and Mauritania active in communication and collaboration with an international community in desertification, and actively serves as an agency in “the pan-African Great Green Wall” Initiative.
Efficient Region Segmentation of PV Module in Infrared Imagery using Segnet
Authors: Xie Ying , Shen Yu , Zhang Kanjian , Zhang Jinxia
Published: June 2021

As renewable energy, solar energy resources are a major focus. The flaw detection of the PV production system is an important guarantee for the stable operation of the system. Hotspot detection is a key step. It is very important to extract the efficient region in the infrared image of the photovoltaic module in advance to improve the hot spot detection precision. In this paper, we propose an effective region segmentation method for infrared image of photovoltaic module based on SegNet, which greatly improves the calculation efficiency and detection accuracy. We use mask processing to hide the irrelevant background area in the original image and label the image data with labelme software. We trained and validated the model using infrared images of photovoltaic modules captured by the portable infrared imager provided by the electric company, and we assessed the model. This paper is the first attempt to use deep learning technology to solve the engineering problem of effective region segmentation of photovoltaic module infrared image. The experimental results show that the segmentation effect of our proposed methodology is remarkable in practical technical applications.
Revolutionize China’s Auto Market Setup by Chinese EV Brands? Answers from Consumers
Authors: Li Li , Li Yijinghong , Lei Kewen , Li Yue , Luo Yixi
Published: June 2021

As the foreign and joint venture brands introduced thier electric vehicle (EV) into China, the pattern of China’s EV market changed quietly. Under such circumstance, whether Chinese EV brands can subvert the structure of the Chinese automobile market is a question worth studying. This article uses the discrete choice experiment (DCE) to answer this question from the perspective of consumer preference. We divided the entire EV market into mid-end and high-end EV markets, a binary logit regression model was used to analyze the possibility of consumers’ purchase choice of EVs in different markets depending on the different levels of price, range, energy efficiency, number of super charging stations, service stores and installation of automated driving system. We finally found that compared with the high-end EV market, Chinese domestic EV brands are more competitive in the mid-end market, but even in the mid-end market, Chinese branding EVs are still not as attractive to consumers as joint venture brands. Generally speaking, although Chinese domestic EV brands will cause certain changes in China’s overall automotive market structure, the changes would be very limited. In the future, the Chinese brand EVs should improve its brand-specific charging service levels which can greatly increase thier competitiveness.