bluuebunny/crossref_metadata_2025 huggingface dataset:
Pillar[6]arene acts as a biosensor for quantitative detection of a vitamin metabolite in crude biological samples
Authors: Ueno Masaya , Tomita Takuya , Arakawa Hiroshi , Kakuta Takahiro , Yamagishi Tada-aki , Terakawa Jumpei , Daikoku Takiko , Horike Shin-ichi , Si Sha , Kurayoshi Kenta , Ito Chiaki , Kasahara Atsuko , Tadokoro Yuko , Kobayashi Masahiko , Fukuwatari Tsutomu , Tamai Ikumi , Hirao Atsushi , Ogoshi Tomoki
Published: December 2020

Metabolic syndrome is associated with obesity, hypertension, and dyslipidemia, and increased cardiovascular risk. Therefore, quick and accurate measurements of specific metabolites are critical for diagnosis; however, detection methods are limited. Here we describe the synthesis of pillar[n]arenes to target 1-methylnicotinamide (1-MNA), which is one metabolite of vitamin B3 (nicotinamide) produced by the cancer-associated nicotinamide N-methyltransferase (NNMT). We found that water-soluble pillar[5]arene (P5A) forms host–guest complexes with both 1-MNA and nicotinamide, and water-soluble pillar[6]arene (P6A) selectively binds to 1-MNA at the micromolar level. P6A can be used as a “turn-off sensor” by photoinduced electron transfer (detection limit is 4.38 × 10−6 M). In our cell-free reaction, P6A is used to quantitatively monitor the activity of NNMT. Moreover, studies using NNMT-deficient mice reveal that P6A exclusively binds to 1-MNA in crude urinary samples. Our findings demonstrate that P6A can be used as a biosensor to quantify 1-MNA in crude biological samples.
Author Correction: Variability in historical emissions trends suggests a need for a wide range of global scenarios and regional analyses
Authors: Pedersen Jiesper Strandsbjerg Tristan , van Vuuren Detlef P. , Aparício Bruno A. , Swart Rob , Gupta Joyeeta , Santos Filipe Duarte
Published: December 2020

A Correction to this paper has been published: https://doi.org/10.1038/s43247-020-00072-9
p–p orbital interaction via magnesium isovalent doping enhances optoelectronic properties of halide perovskites
Authors: Qian Feng , Gong Jue , Hu Mingyu , Ge Chunyu , Padture Nitin P. , Zhou Yuanyuan , Feng Jing
Published: December 2020

p–p orbital interaction through Mg(ii) isovalent doping in methylammonium lead chloride perovskite significantly enhances the electronic properties while not affecting the optical bandgap.
Rh(iii)-Catalyzed acylation of heteroarenes with cyclobutenones via C–H/C–C bond activation
Authors: Cui Yixin , Bai Dachang , Liu Bingxian , Chang Junbiao , Li Xingwei
Published: December 2020

Cyclobutenones were used as an acylating reagent in rhodium(iii)-catalyzed C–H acylation of heteroarenes through C–C cleavage.
Quantifying low fluence ion implants in diamond-like carbon film by secondary ion mass spectrometry by understanding matrix effects
Authors: Jurewicz Amy J. G. , Olinger Chad T. , Burnett Donald S. , Guan Yunbin , Hervig Richard , Rieck Karen D. , Woolum Dorothy S.
Published: December 2020

Secondary ion mass spectrometry (SIMS) data from diamond like carbon (DLC) often give inaccurate, imprecise results when methods tailored for silicon are applied. This work is a guide to accurate and precise results from future SIMS analyses of DLC.
One pot synthesis ofthio-glycosidesviaaziridine opening reactions
Authors: Hribernik Nives , Tamburrini Alice , Falletta Ermelinda , Bernardi Anna
Published: December 2020

thio-Glycosides with a pseudo-disaccharide structure are synthesizedviaaziridine opening reactions starting from glycosyl thioacetates with a one-pot protocol, which affords glycomimetics equipped for easy and stable conjugation to aglycones.
Coordinating capillary infiltration with anodic oxidation: a multi-functional strategy for electrochemical fabrication of graphene
Authors: Duan Pu , Yang Siwei , He Peng , Zhang Penglei , Xie Xiaoming , Ding Guqiao
Published: December 2020

Coordinating the capillarity infiltration with anodic oxidation enables electrochemical fabrication of various graphene materials at different temperatures.
First-principles calculations of an asymmetric MoO2/graphene nanocomposite as the anode material for lithium-ion batteries
Authors: Zhang Qiuyu , Zhu Dongyang , Li Xiaowei , Zhang Yihe
Published: December 2020

The structure of a nanocomposite constructed from MoO2 and graphene and its Li atom adsorption and diffusion properties.
1-Phenyl-N-(benzothiazol-2-yl)methanimine derivatives as Middle East respiratory syndrome coronavirus inhibitors
Authors: Hu Min-Qi , Li Heng , Lin Ying , Zhang Ying , Tang Jie , Zuo Jian-Ping , Yu Li-Fang , Tong Xian-Kun , Tang Wei , Yang Fan
Published: December 2020

A series of novel 1-phenyl-N-(benzothiazol-2-yl)methanimine derivatives were synthesized and their in vitro inhibitory potencies were evaluated on MERS-S pseudovirus.
Linear consecutive hexaoxazoles as G4 ligands inducing chair-type anti-parallel topology of a telomeric G-quadruplex
Authors: Sasaki Shogo , Ma Yue , Ishizuka Takumi , Bao Hong-Liang , Hirokawa Takatsugu , Xu Yan , Tera Masayuki , Nagasawa Kazuo
Published: December 2020

G-quadruplex structures (G4s) in guanine-rich regions of DNA play critical roles in various biological phenomena, including replication, translation, and gene expression.
Three cheers for nitrogen: aza-DKPs, the aza analogues of 2,5-diketopiperazines
Authors: Maujean Timothé , Girard Nicolas , Ganesan A. , Gulea Mihaela , Bonnet Dominique
Published: December 2020

An overview of the synthetic strategies to access aza-diketopiperazines, a unique class of N-heterocycles with potential applications in medicinal chemistry.
Benzothiadiazole-based photosensitizers for efficient and stable dye-sensitized solar cells and 8.7% efficiency semi-transparent mini-modules
Authors: Godfroy Maxime , Liotier Johan , Mwalukuku Valid M. , Joly Damien , Huaulmé Quentin , Cabau Lydia , Aumaitre Cyril , Kervella Yann , Narbey Stéphanie , Oswald Frédéric , Palomares Emilio , González Flores Carlos A. , Oskam Gerko , Demadrille Renaud
Published: December 2020

New benzothiadiazole-based dyes are synthesized, characterized and used for the fabrication of robust and efficient solar cells and mini-modules.
Evaluating the Accuracy of Step Tracking and Fall Detection in the Starkey Livio Artificial Intelligence Hearing Aids: A Pilot Study
Authors: Rahme Mohamed , Folkeard Paula , Scollie Susan
Published: December 2020

Purpose

The primary purpose of this study was to examine the efficacy and the effectiveness of Starkey Livio Artificial Intelligence hearing aids in tracking step count. A secondary purpose was to investigate the accuracy of the fall detection and alert system of Livio hearing aids in detecting fall maneuvers.

Method

A participant wore Binaural Starkey Livio receiver-in-the-canal style hearing aids, a Sportline pedometer, and a Fitbit Charge 3 concurrently during both real-world and treadmill walking conditions. The real-world condition was conducted over a 5-day period. Step count for the treadmill protocol was assessed at six different treadmill speeds (2 mph, 2.5 mph, 3 mph, 3.5 mph, 4 mph, 4.5 mph, and 5 mph). The fall detection and alert system were assessed through falling maneuvers of activities of daily living.

Results

In the real-world condition, Livio, Sportline, and Fitbit recorded steps within 1
SD
of each other. In addition, Livio recorded the most accurate steps compared to actual physical steps taken. In the treadmill condition, Livio recorded the least number of steps across all walking paces compared to the rest of the devices. Also, Livio hearing aids detected majority of the engaged falling maneuvers.

Conclusions

The Livio was found to be feasible, consistent, and sensitive in detecting steps and falls. Further research of higher sample size and recruitment of individuals with hearing loss are suggested.
Quantitative Assessment of Learning and Retention in Virtual Vocal Function Exercises
Authors: Van Stan Jarrad H. , Park Se-Woong , Jarvis Matthew , Stemple Joseph , Hillman Robert E. , Sternad Dagmar
Published: December 2020

Purpose

Successful voice therapy requires the patient to learn new vocal behaviors, but little is currently known regarding how vocal motor skills are improved and retained. To quantitatively characterize the motor learning process in a clinically meaningful context, a virtual task was developed based on the Vocal Function Exercises. In the virtual task, subjects control a computational model of a ball floating on a column of airflow via modifications to mean airflow (L/s) and intensity (dB-C) to keep the ball within a target range representing a normative ratio (dB × s/L).

Method

One vocally healthy female and one female with nonphonotraumatic vocal hyperfunction practiced the task for 11 days and completed retention testing 1 and 6 months later. The mapping between the two execution variables (airflow and intensity) and one error measure (proximity to the normative ratio) was evaluated by quantifying distributional variability (tolerance cost and noise cost) and temporal variability (scaling index of detrended fluctuation analysis).

Results

Both subjects reduced their error over practice and retained their performance 6 months later. Tolerance cost and noise cost were positively correlated with decreases in error during early practice and late practice, respectively. After extended practice, temporal variability was modulated to align with the task's solution manifold.

Conclusions

These case studies illustrated, in a healthy control and a patient with nonphonotraumatic vocal hyperfunction, that the virtual floating ball task produces quantitative measures characterizing the learning process. Future work will further investigate the task's potential to enhance clinical assessment and treatments involving voice control.

Supplemental Material

https://doi.org/10.23641/asha.13322891
Adaptive algorithm in distance relay with out of step blocking element compatible with smart grid requirements during sub‐synchronous resonance in transmission line
Authors: Rezaei Salman
Published: December 2020

Smart grid comprises utility system and dispersed renewable generations. It establishes bidirectional power transmission and communication among utility system, distributed generations and consumers. Sub‐synchronous resonance (SSR) is a major concern in transmission line. Furthermore, impedance swing during SSR leads in operation of out of step blocking characteristic of distance relay. SSR brings about a significant rise in the magnitudes of voltage and current. It also raises probability of occurrence of ferroresonance. Here, the impact of SSR in utility system is analysed on operation of doubly‐fed induction generator and distance relay with out of step blocking element is given here. Smart grid urge to establish a self‐healing protection, hence, an adaptive algorithm based on sub harmonic and ferroresonance detection is proposed for distance relay. The algorithm discriminates ferroresonance from other nonlinearities by wavelet transform and neural network and utilises time domain analysis to distinguish between different types of ferroresonance. The algorithm is able to observe smart grid protection strategy. It is capable of receiving the commands according to protection strategy to take a correct decision in such conditions to enhance reliability of power electricity in smart grid. Finally, the proposed algorithm is examined in SSR condition to certify the correct operation.
Fuzzy PI controller‐based model reference adaptive control for voltage control of two connected microgrids
Authors: Keshta Hossam E. , Saied Ebtisam M. , Malik Om P. , Bendary Fahmy M. , Ali Ahmed A.
Published: December 2020

An efficient control strategy for two connected microgrids (MGs) is proposed to ensure stable and economic operation. One of the most important means of improving energy efficiency is to achieve the best response for sudden and stochastic disturbances to which the MGs are subjected. Traditionally, MGs are controlled using a linear controller, such as conventional proportional‐integral (PI) controller. Fuzzy PI (FPI) controller‐based model reference adaptive control that can adapt to a wide range of operating conditions for regulating the voltage is investigated and its performance is compared with the conventional linear PI controller that is not able to mitigate these disturbances efficiently. Parameters of the proposed controller are optimised using an advanced optimisation technique called global porcellio scaber algorithm (GPSA). Performance of the controllers is demonstrated on two connected microgrids for a number of scenarios such as load variations, weather fluctuations and faults. Simulation results verify that the proposed control strategy is effective and feasible under various operating conditions for this system. The results also show that the dynamic performance of the system with the model reference adaptive fuzzy PI (MRAFPI) controller is better than that with the most common controller used for this application, the conventional PI controller, for different operating conditions.
KS‐FQA: Keyframe selection based on face quality assessment for efficient face recognition in video
Authors: Bahroun Sahbi , Abed Rahma , Zagrouba Ezzeddine
Published: December 2020

Video is considered as one of the most useful and important forms of multimedia data, that is usually used in several applications. Despite its importance, video indexing and retrieval becomes a challenging task. In order to reduce the amount of data and keep only relevant frames, keyframe extraction becomes necessary in a content‐based video retrieval (CBVR) system. In this paper, a keyframe extraction method is proposed based on the face image quality for video surveillance systems. Data is reduced by rejecting frames without faces. Then, face images are clustered by identity. After that, a set of candidate frames is selected to be proceeded. The face quality assessment is based on four metrics including pose estimation, sharpness, brightness and resolution, and the frame with the best face quality is considered as a keyframe. Experimental tests were carried on several datasets in order to prove the efficiency of authors' method compared with state‐of‐the‐art approaches.
Image denoising method based on variable exponential fractional‐integer‐order total variation and tight frame sparse regularization
Authors: Wang Yingmei , Wang Zhendong
Published: December 2020

This study presents a variational image restoration algorithm based on variable exponential fractional‐order total variation (TV), variable exponential integer‐order TV and tight frame sparse regularization. The energy functional of this variational problem is composed of four parts: a fractional‐order TV regularization term with a variable exponent, an integer‐order TV regularization term with a variable exponent, a data fidelity term and a tight frame regularization term. The variable exponent is a function of the gradient information of the image. The first three parts of the energy functional is the smooth part, and the last part is the non‐smooth part. To minimize the smooth part, the optimization problem can be simply transformed into a gradient descent flow using the variational method. For the non‐smooth part, we use the soft‐thresholding method over the sparse framelet coefficients. As the combination of the fractional‐order derivative and integer‐order derivative, the variable exponent and the sparse regularisation, the proposed method can effectively remove noise of the image, protect the image boundary, and keep image texture details well. Experiments with simulated data and real data are provided to validate the effectiveness of proposed method. This method is robust to noise and is of some practical application value.
Residual dense U‐Net for abnormal exposure restoration from single images
Authors: Que Yue , Lee Hyo Jong
Published: December 2020

Digital imaging devices sometimes capture images with abnormal exposure because of the complex lighting conditions and limited dynamic range of luminance. In this work, a new residual dense U‐Net is proposed to predict the information that has been lost in saturated image areas, to enable abnormal exposure restoration from a single image. Full advantage of the multi‐level features is taken from all the convolution layers in the restoration process. Specifically, the densely connected convolutional layers are used in a contracting encoder net to extract abundant local features. The transition layer and local residual learning after each dense block is then applied to adaptively learn more effectively from prior with present local features. Further, an expanding decoder net with dense layers is used and added with skip connections to preserve low‐level information and existing details. Finally, multiple global residual learning is used to adaptively extract hierarchical features and help train the network. It is shown that such a network can be trained end‐to‐end from abnormal exposure images and outperform the prior best method on image enhancement. Experimental results show that the proposed model can greatly enhance the dynamic range of an abnormal exposure image.
Feature fusion quality assessment model for DASH video streaming
Authors: Zhang Hong , Li Fan , Yan Zhisheng
Published: December 2020

Dynamic Adaptive Streaming over HTTP (DASH) employs the flexible rate adaptation scheme to combat with time‐varying channel conditions. In addition to compression impairment, DASH video streaming suffers from transmission impairment, such as rate switches and stalling events. Both of them severely degrade users' Quality of Experience (QoE). Herein, an assessment model is established for DASH video streaming by directly jointing multiple QoE influential factors, which quantify impairments resulting from the compression and transmission. To demonstrate the influence of video content characteristics on users' QoE, spatio‐temporal content perceptual features are employed to represent the compression impairment. When reflecting temporal characteristics, a novel motion vector padding method is proposed to quantify the influence of intra macroblock on the human visual system. The proposed model is evaluated on a newly public Waterloo SQoE‐III database, which is available for DASH video streaming. Experimental results demonstrate that the authors' model outperforms the comparative models and owns the strong generalization ability to different video contents. Moreover, the proposed model is statistically superior to the existing models.
Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC
Authors: Li Tiansong , Yu Li , Wang Hongkui , Chen Yamei
Published: December 2020

To alleviate the computation burden of the depth intra coding in 3D‐HEVC, a complexity reduction scheme based on texture feature and spatio‐temporal correlation is proposed. Firstly, a maximum splitting depth layer decision algorithm is proposed to reduce unnecessary splitting depth layer of the coding tree unit utilising the information of the previous encoded I frame in the same view. Secondly, a new texture complexity model is built by pixel‐based statistical method combined with edge detection. Based on the proposed model, the coding unit block is divided into the smooth block, texture or edge block. On the coding unit level, an early termination of coding unit splitting algorithm for smooth blocks is proposed to filter out unnecessary coding blocks. Thirdly, on the predicting unit level, a fast candidate mode decision algorithm considering predicting unit's types and spatial correlation is proposed to decide the candidate mode list directly. Experimental results describe that the proposed algorithm reduces 53.8% depth intra coding time on average, with 0.43% BD‐rate loss on synthesised views.
A hybrid BPSO‐SVM for feature selection and classification of ocular health
Authors: Keerthiveena B. , Esakkirajan S. , Subudhi Badri Narayan , Veerakumar T.
Published: December 2020

Glaucoma and diabetic retinopathy are the most common eye diseases and the leading cause of blindness around the world. The prime objective of this study is to devise and develop an experimental computer‐aided diagnosis system to provide an efficient way for assisting the ophthalmologist in early detection of ocular diseases such as glaucoma and diabetic retinopathy. The proposed technique follows three stages: Pre‐processing, feature selection and classification. Initially, the fundus image is pre‐processed to extract the green channel image, and the obtained green channel image is further enhanced using contrast limited adaptive histogram equalisation technique. Three different kinds of features: Clinical features, transform domain features and structural features are utilised to extract the relevant information from the enhanced fundus images. To avoid redundant information, an improved feature selection mechanism is used to select the optimum set of features from the extracted features. Subsequently, the selected features are used to train the support vector machine classifier for the classification of the retinal diseases with 10‐fold cross‐validation. The performance of the proposed method is assessed using eight different quantitative evaluation measures. The experimental results demonstrate the effectiveness of the proposed work over prior works for the early detection of ocular diseases.
A novel compression approach for truck GPS trajectory data
Authors: Liu Sijing , Chen Gang , Wei Long , Li Guoqi
Published: December 2020

Nowadays, the application of location‐aware devices, such as global positioning system (GPS)‐enabled mobile phones and personal digital assistants (PDAs) is increasing. Based on this, a new demand for efficiently storing trajectory data has arisen. Trajectory compression reduces the storage space and cost, the cost and time of data transmission by retaining critical trajectory points and effectively eliminating redundant data. Herein, a novel trajectory compression method based on stay points (TCSP) is proposed. By using the road network data and the stay points of GPS trajectory data to compress the GPS trajectory data, this method can greatly improve the ratio and accuracy of compression. Experimental results based on real data sets show that the compression rate of this method can stably reach 8.61%, and the compression effect can be restored to the original trajectory route. Compared with the critical point algorithm and the Douglas–Peucker (DP) algorithm, the TCSP method can reach a better compression effect and compression ratio.
Improving the open cluster census
Authors: Hunt Emily L. , Reffert Sabine
Published: December 2020

Context.The census of open clusters in the Milky Way is in a never-before seen state of flux. Recent works have reported hundreds of new open clusters thanks to the incredible astrometric quality of theGaiasatellite, but other works have also reported that many open clusters discovered in the preGaiaera may be associations.

Aims.We aim to conduct a comparison of clustering algorithms used to detect open clusters, attempting to statistically quantify their strengths and weaknesses by deriving the sensitivity, specificity, and precision of each as well as their true positive rate against a larger sample.

Methods.We selected DBSCAN, HDBSCAN, and Gaussian mixture models for further study, owing to their speed and appropriateness for use withGaiadata. We developed a preprocessing pipeline forGaiadata and developed the algorithms further for the specific application to open clusters. We derived detection rates for all 1385 open clusters in the fields in our study as well as more detailed performance statistics for 100 of these open clusters.

Results.DBSCAN was sensitive to 50%–62% of the true positive open clusters in our sample, with generally very good specificity and precision. HDBSCAN traded precision for a higher sensitivity of up to 82%, especially across different distances and scales of open clusters. Gaussian mixture models were slow and only sensitive to 33% of open clusters in our sample, which tended to be larger objects. Additionally, we report on 41 new open cluster candidates detected by HDBSCAN, three of which are closer than 500 pc.

Conclusions.When used with additional post-processing to mitigate its false positives, we have found that HDBSCAN is the most sensitive and effective algorithm for recovering open clusters inGaiadata. Our results suggest that many more new and already reported open clusters have yet to be detected inGaiadata.
Value Investment Based on Data Analysis with Comparison of Three Insurance Corporations in the US
Authors: Sun Jinnan
Published: December 2020

Value investment analysis plays a crucial role in people’s judgment of whether an enterprise is worthy of continuing investment. Because it helps people reduce the likelihood of making a bad investment, whether it’s worth it, and how do you combine the various factors. The purpose of this paper is to analyze the value of the company’s investment in the insurance industry. AIG, ALL and MET were selected from a large number of insurance companies. Using P/E and P/S ratio to compare the prospects of several companies of the same type through specific data, investment analysis. Finally, the best companies to invest in among the three companies are obtained by combining the display situation, and give final investment advice.
Research on Motivation and Benefits of Hongdou Group’s Investment in Sihanoukville Special Economic Zone in Cambodia
Authors: Fu Ruolan
Published: December 2020

The overseas economic and trade cooperation zone is an important platform for China’s economic cooperation with other countries. It aims to improve the service management level of the cooperation zone and promote the operational efficiency of the park enterprises by drawing on the excellent experience of China’s Reform and Opening. Due to the increase in domestic production costs and the guidance of the government’s policy of encouraging enterprises to “go global”, the countries along the “Belt and Road” have gradually emerged as a boom in corporate investment cooperation zones. This paper analyzes the input and output of the case of Hongdou Group investing in Cambodia’s special economic zone, Sihanoukville, and finds that this kind way of investment is conducive to enterprises to use policy support to “get advantage and complement each other”. Integrating various resources, and gaining the core competitiveness of enterprises in the host country is also the main motivation for Chinese enterprises to invest abroad in the new era. The analysis believes that the initial stage of investment will bring some financial pressure, but in the middle and late stage will play an important economic role, bring good economic benefits, and will bring positive social benefits to the host country, which will benefit for the bargaining power of enterprises overseas.
Improving Brand Loyalty Through Social Media Marketing: Is It Possible? An empirical study of S-O-R paradigm
Authors: Wang Zichen , Kortana Tanapol , Kuang Wenzhi
Published: December 2020

In this study, a questionnaire survey was conducted by the consumers who purchasing Huawei mobile phones in China under the social media environment as the test subjects. At present, research on self-congruence with brands is still centered offline, so this research aims to broaden the scope of the self- concept exploration to consider the role of self-congruence with brands in the network, besides, to explore that how social media marketing affects the brand loyalty of customers, and whether it will be affected by self-congruence. At the same time, based on the S-O-R theory, a research framework containing six hypotheses was proposed through this study. All hypotheses were supported after data analysis by using SPSS 25, nevertheless, management implications were proposed based on the research conclusions.
Possible Method for Customer Segmentation in Bath Center Based on Neural Net
Authors: Ma Yuxuan
Published: December 2020

With the coming of data era, even small business has ability to collect and store abundant data, which means doing customer segmentation based on data, instead of experience, is possible. This paper chooses a developing business in Chin—bath center, to make customer segmentation with data. In this research, neural net is used to deal with the distance to fit more with the true psychological distance and create the distance score to get more information from the variables about coming of the customers. Possible formula of distance score is also given as a reference. The distance score turns out to be a better measure of the psychological distance and the neural net has a better graph of the distance data than other methods. This paper gives a possible method for customer segmentation in a completely new business area.
The Impact of Healthy Human Capital on the Labor Participation of Chinese Elderly
Authors: Youlu Zhang , Ying Chi
Published: December 2020

The labor participation of the elderly is an important level of labor supply in China, and healthy human capital is one of the main factors affecting the labor participation of the elderly. Based on the data of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2014, this paper uses the Probit model to empirically analyze the impact of the healthy human capital of the elderly in China on their labor force participation rate. The results show that when individual characteristic variables, family characteristic variables and social characteristic variables are added, healthy human capital is positively correlated with labor participation of retired elderly people. The better health status is, the higher labor participation rate is. With the decline in health status, the labor force participation rate of retired elderly people decreased significantly. The influence of healthy human capital on labor participation of the elderly in China is also heterogeneous between urban and rural areas, gender and age, among which the influence of healthy human capital on labor participation of the elderly in rural areas, males and young age groups is higher than that in urban areas, females and elderly retirees.
An Input-output Analysis of China’s Innovative Resources based on Knowledge Production Function
Authors: Geng Kangshun , Gu Jijian
Published: December 2020

Under the background of the gradual disappearance of China’s population dividend and the increasing restriction of resources and environment, economic development urgently needs to change from “factor driven” to “innovation driven”. Research on the impact of innovation resources on economic growth is the key to the implementation of innovation driven strategy. According to the knowledge production function, innovation resources are divided into innovation material resources, innovation knowledge resources and innovation human resources. On this basis, the correlation and weight between the input and output of all kinds of innovation resources are investigated to explore the ideas and development direction of optimizing the allocation of innovation resources in China, and to provide practical basis for the formulation of relevant innovation incentive system.
Analysis on the Possibility of Investment in the Mexican Emerging Market
Authors: Wei Shizheng
Published: December 2020

Emerging markets with high uncertainty and turbulent environments are always hard to predict. Unlike advanced markets that are not easy to be influenced by the external environment, emerging markets are still immature and likely to be easily affected. The Mexican peso crisis in 1994 is an example that inappropriate monetary policy was taken when the entire financial system was weak in Mexico at that time. In the global emerging market, Mexican peso plays a significant role in maintaining the stability of the foreign exchange market. This paper aims to analyze the current situation of Mexican domestic emerging markets from its economy, the monetary policy of the central bank of Mexico, and foreign exchange aspects. The analysis can provide information for potential investors to make a decision before they decide to invest in the Mexican emerging markets.
Analysis on German Monetary Policy from 1974 to 1990
Authors: Wang Minxu
Published: December 2020

This article analyzes German monetary policy from 1974 to 1990. During this period, Germany experienced rapid economic growth and maintained the inflation rate at an average low level. This article would like to analyze German monetary policy to find the reasons why Germany could have rapid economic growth and maintain inflation rate at an average low level. Then specific main goal, right choices of monetary policy tools and intermediary indicators, and timely adjustment of the policy were found as the reasons. We also learn some successful experience about monetary policy from Germany and apply them in China.
Impact of Financialization on Operating Profit of Manufacturing Listed Companies
Authors: Shengdao Gan , Qingying Wang , Qiya Zhang
Published: December 2020

This study employs a sample of manufacturing listed companies in China from fiscal year 2008 to 2018, analyzes their financial position and operating performance, and explores the impact of financialization on their operating profits. The results suggest that the financialization of manufacturing listed companies will restrain the growth of operating profit, that is the “crowding out” effect. This paper reminds the listed companies’ controlling shareholders of the economic consequences of financialization at the micro level and the significance of improving the company’s core competitiveness, further promotes companies to strengthen the internal control of financialization for sustainable development of the companies.
Performance Evaluation of Commercial Banks Based on Factor Analysis
Authors: Lv Qin , Wang Yingdong , Zhang Dijia , Yang Muyang , Zheng Yueming
Published: December 2020

China’s commercial banks are the main part of the country’s financial system and a key link in the national economy. However, because of the late start of commercial banks in China, the performance evaluation system of commercial banks is not perfect. Based on the financial data of 36 listed commercial banks in 2018, this paper uses factor analysis method to evaluate the performance of commercial banks, and analyzes the operating conditions of commercial banks.
The Concept and Process of Innovation Leading Based on the longitudinal case study of Haier (1984-2019)
Authors: Yuyue Kan , Haibing Liu
Published: December 2020

Based on the exploratory case study method, this paper attempts to construct a theoretical framework of Innovation Leading from two aspects of concept and process. Based on this research framework, the article makes a longitudinal case study of the Haier Group’s washing machine industry line, which is representative in terms of Innovation Leading the improvement of Core Competence, from 1994 to 2019. The study found: (1) From four dimensions of Value, Attitude, Effect and Driving (VAED), the concept of Innovation Leading is defined exploratory. (2) This paper theoretically discusses the process of Innovation Leading, namely ISAC model, including Innovation Intention, Innovation Strategy, Innovation Action and Core Competence. User demands are the trigger of Innovation Intention, which is the “navigator” and “brain”. The Innovation Strategy is an innovation plan about technology and complementary assets led by Innovation Intention. Innovation Action is the carrier of Innovation Leading, including technological innovation and complementary asset innovation. Core Competence is the goal of innovation, and it is an organic unity of technological competence, market competence, organizational competence and cultural competence.
Scientometric Analysis of Corporate Social Responsibility, Corporate Social Performance and Financial Performance Based on Corporate Governance
Authors: Pan Chung-Lien , Yu Lin , Lin Zhuoshan , Li Jialong , Pan Yu-Chun
Published: December 2020

The economic growth and social responsibility of the company have become hot topics of concern to society. Fulfilling a company’s obligations of social responsibility can establish a good corporate image and benefit the company’s long-term development. Tracking the research fronts in this field can help to understand the hotspots that scholars pay attention to and fill the gaps in the field. We used the scientometric analysis to explore corporate governance research from 1987 to 2020 based on the Web of Science (WoS) database. Our research shows that corporate social responsibility focus on topics such as sustainability, social responsibility, and shareholders, and financial performance will be more skewed towards financial crisis, company value, and other research. The main publications are the Journal of Business Ethics and Corporate Governance-An International Review. The increase in the number of publications and citations reflects the strong interest of scholars in this research area. In this area, the organizations of developed countries are dominant, especially the United States, and China has the largest number of funding agencies, suggests that the economic powers are paying more attention to the literature on economic management. However, corporate social performance articles are relatively small, and strengthening this area can become a future research direction. strengthening this area can become a future research direction.
Bibliometric Analysis of digitization business economy
Authors: Pan Chung-Lien , Lin JiaRong , Wang YiHua , Zhou ZhiXiang , MO YiJiao
Published: December 2020

Digital technology is being applied by different organizations, for example, the sharing economy, blockchain, and other topics are very popular in recent years, which leads to obvious changes in different fields. At the same time, there is growing interest in the digital business economy. However, there is less bibliometrics on the subject, and this is a good solution for addressing the opportunities and risks of digital transformation. Based on 731 articles retrieved from the Web of Science（Wos） database between 2000 and 2020, the study reviewed the literature on “ICT industry”, “digital economy”, “economic analysis” and “market research”. Since 2015, publications have experienced rapid growth in several disciplines, such as management, business, economics, library and information science, business economics, etc. At the same time, research institutions in Germany, the United States, and Sweden have performed well in this field. Using this database, the author analyzed what happened and made a concise keyword map to clearly show the connections among the topics based on the co-occurrence network generated by the keyword data. This paper provides a reference point for researchers, funding agencies, policymakers, and industry professionals to study the progress of the digital business economy.
Countermeasures and Suggestions on Pharmaceutical Production of Drugs in the Market of Cold Medicine based on Ali Health online drug sales platform 2019 big data
Authors: Ning Wang Qian , Bo Su , Lu Zhang , Ya Wen , Xiao Rong Jiang , Yun Jie Xue , Qi An
Published: December 2020

Starting from the basic situation of drug use when patients treat colds. It is found that the quantity of cold cold medicine and warm cold medicine in real life is not in accordance with the epidemiological statistics. There is the possibility of unreasonable production by supplier manufacturers. The purpose of this paper is to remind suppliers that the production of drugs should be carried out according to patients’ disease conditions, so as to avoid misleading the market and thus affecting patients. From the two most important factors that affect the quantity of drugs—the supply and demand of drugs, the author makes statistics on the taste of drugs produced by manufacturers and the taste of drugs purchased by patients. It is found that the choice of cold medicine from both supply and demand is more than that of warm medicine, so it is very important for the education and guidance of manufacturers upstream of the value chain to reduce the mismatch between drug production and patient demand.
Research on Supermarket Product Layout Method Based on Comprehensive Correlation Degree
Authors: Xia Yuqing , Jin Chenxia , Li Fachao
Published: December 2020

The commodity layout of a large supermarket has an important impact on the sales and benefits of the supermarket. The quality of the commodity layout directly affects the consumer’s psychological feeling and purchasing behavior in the shopping process. According to the previous research, we can find that the traditional commodity layout method has the shortcomings of lack of data support, poor stability, and does not include the actual factors such as the impulse purchase behavior of consumers and the purchase law of commodities in the research scope, resulting in the problem that the optimization effect is not obvious. In view of this deficiency, this paper proposes a commodity layout method based on comprehensive correlation degree. Firstly, the concepts of adjacency effect value and placement freedom degree are given. Based on this, transaction data is used to mine association rules of commodities in customers’ shopping baskets, and the influence of the same commodity on surrounding commodities due to different placement positions is further analyzed. Based on the maximization of the comprehensive correlation value, an analytic model for the optimization of commodity layout is established, and the optimal commodity layout is obtained by using genetic algorithm. In this article, the layout of the B supermarket commodity layout is taken as an example. The overall layout is more closely related. It verifies the feasibility and superiority of the commodity layout method based on comprehensive correlation, which can better improve the market competitiveness of the supermarket.
Analysis of domestic and foreign research status of agricultural pollution control based on VOSviewer
Authors: Xin Zhang , Keyu Zhao , Lin Peng
Published: December 2020

Visual analysis of the field of agricultural pollution prevention and control will help researchers to fully understand the research status at home and abroad, and better fit the current situation for further research. Mothod: Web of Science database was used to retrieve 2,214 literatures related to agricultural pollution prevention and control from 2000 to 2018 as data sources, and VOSviewer software was used for visual analysis. The results showed that the research heat of agricultural pollution control showed a good upward trend; Since 2010, China’s rapid growth in the volume of publications has ranked first, while the United States has remained stable for a long time, ranking second; Chinese institutions hold eight of the top 10 spots, with the Chinese academy of sciences at the absolute center of the field; In the research hotspot, it is divided into three clusters.1# In the field of agricultural pollution prevention and control, we have the ability to effectively control nitrogen, quality and phosphorus; China has made in-depth research on sediments, heavy metals and agricultural soils.3# Indian researchers have paid considerable attention to the prevention and control of surface water, drainage basins and groundwater pollution, and carried out in-depth research work for this purpose.
Performance Evaluation of Collaborative Innovation of Industry, University and Research Institute in China
Authors: Xuangong Zhu , Ning Wang
Published: December 2020

As an important form of technological innovation, the collaborative innovation of industry-university-research institute has attracted more and more attention from the business circles, science and technology management departments and academic circles in China. Against this background, the performance evaluation model of industry-university-research collaboration innovation was established on the basis of the input-output perspective, and the factor analysis was used to scientifically assess the performance of industry-university-research collaboration innovation in 29 provinces and cities in China. The scores and rankings were analyzed in detail.
Ernährungsmedizinische Aspekte beim Kurzdarmsyndrom
Authors: Berger Stefanie , Traub Julia
Published: December 2020

Das Kurzdarmsyndrom ist ein komplexes Krankheitsbild, welches in der Therapie einen multidisziplinären Ansatz bedarf. Nur durch eine optimale ernährungsmedizinische, medikamentöse und chirurgische Behandlung sowie durch ein grundlegendes Verständnis der pathophysiologischen Konsequenzen des veränderten Intestinaltrakts seitens der behandelnden Personen, kann eine adäquate Therapie gewährleistet werden. Insbesondere in der akuten Phase ist die Aufrechterhaltung des Ernährungszustands sowie der Flüssigkeitshomöostase eine komplexe Herausforderung. Die zu Beginn notwendige parenterale Ernährung, soll mit einer frühen enteralen und/oder oralen Ernährung ergänzt werden. Dadurch wird der Adaptationsprozess des verbleibenden Restdarms günstig beeinflusst und die Nährstoffresorption verbessert. Zudem ist ein optimales Elektrolyt- und Flüssigkeitsmanagement notwendig. In dieser Übersichtsarbeit wird die akute Phase des Kurzdarmsyndroms behandelt. Es werden ernährungsmedizinische Konsequenzen des veränderten Intestinaltrakts sowie das postoperative Therapiekonzept mit dem Fokus auf ernährungstherapeutische Interventionen beschrieben.
Fatigue und Fatigability bei Multipler Sklerose –
Leistungsbeurteilung
Authors: Dettmers Christian , Schmidt Roger , Jöbges Michael
Published: December 2020

Fatigue ist eines der häufigsten Symptome bei Patienten mit Multipler
Sklerose (MS) 1
2. Fatigue kann das Symptom sein, das die berufliche
Leistungsfähigkeit am gravierendsten beeinträchtigt 3
4. Der
Großteil der MS-Patienten ist im erwerbsfähigen Alter. Für
die sozialmedizinische Leistungsbeurteilung ist besonders problematisch, dass es
sich bei der Fatigue um ein subjektives Phänomen handelt, dass nicht
objektiv messbar ist.
Lower Extremity Pain and Pitching Kinematics and Kinetics in Collegiate Softball Pitchers
Authors: Oliver Gretchen D. , Friesen Kenzie B. , Barfield Jeff W. , Giordano Kevin A. , Bordelon Nicole M. , Anz Adam W. , Goodlett Michael D. , Andrews James R.
Published: December 2020

The primary aims of the study were (1) to examine kinematics and kinetics of those pitching with and without lower extremity pain in collegiate softball pitchers, and (2) to determine if there was an association between the lower extremity pain and lower extremity kinematics, trunk kinematics, and shoulder kinetics in collegiate softball pitchers. Thirty-seven NCAA Division I female collegiate softball pitchers (19.8±1.3 yrs,173.7±7.7 cm, 79.0±12.4 kg) participated. Participants were divided into two groups, those who were currently experiencing lower extremity pain and those who were not. Participants threw three rise ball pitches. Kinematic data were collected at 100 Hz using an electromagnetic tracking system. Mann-Whitney U tests revealed no significant kinematic or kinetic differences between pitchers with and without lower extremity pain. Additionally, there were no significant correlations between pain and recorded kinematic and kinetic variables. Considering there were no biomechanical differences observed between pitchers, coaches and athletic trainers should take caution with athlete assessment since athletes may not display altered biomechanics. Further examination into the duration and degree of pain is needed in an attempt to fully understand the implication of pain and pitching mechanics.