bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraterrestrial hexamethylenetetramine in meteorites—a precursor of prebiotic chemistry in the inner solar system
Authors: Oba Yasuhiro , Takano Yoshinori , Naraoka Hiroshi , Furukawa Yoshihiro , Glavin Daniel P. , Dworkin Jason P. , Tachibana Shogo
Published: December 2020

Despite extensive studies on the formation of organic molecules in various extraterrestrial environments, it still remains under debate when, where, and how such molecules were abiotically formed. A key molecule to solve the problem, hexamethylenetetramine (HMT) has not been confirmed in extraterrestrial materials despite extensive laboratory experimental evidence that it can be produced in interstellar or cometary environments. Here we report the first detection of HMT and functionalized HMT species in the carbonaceous chondrites Murchison, Murray, and Tagish Lake. While the part-per-billion level concentration of HMT in Murchison and Tagish Lake is comparable to other related soluble organic molecules like amino acids, these compounds may have eluded detection in previous studies due to the loss of HMT during the extraction processes. HMT, which can yield important molecules for prebiotic chemistry such as formaldehyde and ammonia upon degradation, is a likely precursor of meteoritic organic compounds of astrochemical and astrophysical interest.
Cytosolic sequestration of the vitamin D receptor as a therapeutic option for vitamin D-induced hypercalcemia
Authors: Rovito Daniela , Belorusova Anna Y. , Chalhoub Sandra , Rerra Anna-Isavella , Guiot Elvire , Molin Arnaud , Linglart Agnès , Rochel Natacha , Laverny Gilles , Metzger Daniel
Published: December 2020

The bioactive vitamin D3, 1α,25(OH)2D3, plays a central role in calcium homeostasis by controlling the activity of the vitamin D receptor (VDR) in various tissues. Hypercalcemia secondary to high circulating levels of vitamin D3leads to hypercalciuria, nephrocalcinosis and renal dysfunctions. Current therapeutic strategies aim at limiting calcium intake, absorption and resorption, or 1α,25(OH)2D3synthesis, but are poorly efficient. In this study, we identify WBP4 as a new VDR interactant, and demonstrate that it controls VDR subcellular localization. Moreover, we show that the vitamin D analogue ZK168281 enhances the interaction between VDR and WBP4 in the cytosol, and normalizes the expression of VDR target genes and serum calcium levels in 1α,25(OH)2D3-intoxicated mice. As ZK168281 also blunts 1α,25(OH)2D3-induced VDR signaling in fibroblasts of a patient with impaired vitamin D degradation, this VDR antagonist represents a promising therapeutic option for 1α,25(OH)2D3-induced hypercalcemia.
Improving the informativeness of Mendelian disease-derived pathogenicity scores for common disease
Authors: Kim Samuel S. , Dey Kushal K. , Weissbrod Omer , Márquez-Luna Carla , Gazal Steven , Price Alkes L.
Published: December 2020

Despite considerable progress on pathogenicity scores prioritizing variants for Mendelian disease, little is known about the utility of these scores for common disease. Here, we assess the informativeness of Mendelian disease-derived pathogenicity scores for common disease and improve upon existing scores. We first apply stratified linkage disequilibrium (LD) score regression to evaluate published pathogenicity scores across 41 common diseases and complex traits (average N = 320K). Several of the resulting annotations are informative for common disease, even after conditioning on a broad set of functional annotations. We then improve upon published pathogenicity scores by developing AnnotBoost, a machine learning framework to impute and denoise pathogenicity scores using a broad set of functional annotations. AnnotBoost substantially increases the informativeness for common disease of both previously uninformative and previously informative pathogenicity scores, implying that Mendelian and common disease variants share similar properties. The boosted scores also produce improvements in heritability model fit and in classifying disease-associated, fine-mapped SNPs. Our boosted scores may improve fine-mapping and candidate gene discovery for common disease.
Molecular rotors with designed polar rotating groups possess mechanics-controllable wide-range rotational speed
Authors: Shao Jian , Zhu Wenpeng , Zhang Xiaoyue , Zheng Yue
Published: December 2020

Molecular rotors with controllable functions are promising for molecular machines and electronic devices. Especially, fast rotation in molecular rotor enables switchable molecular conformations and charge transport states for electronic applications. However, the key to molecular rotor-based electronic devices comes down to a trade-off between fast rotational speed and thermal stability. Fast rotation in molecular rotor requires a small energy barrier height, which disables its controllability under thermal excitation at room temperature. To overcome this trade-off dilemma, we design molecular rotors with co-axial polar rotating groups to achieve wide-range mechanically controllable rotational speed. The interplay between polar rotating groups and directional mechanical load enables a “stop-go” system with a wide-range rotational energy barrier. We show through density functional calculations that directional mechanical load can modulate the rotational speed of designed molecular rotors. At a temperature of 300 K, these molecular rotors operate at low rotational speed in native state and accelerates tremendously (up to 1019) under mechanical load.
Extremely low-frequency electric field suppresses not only induced stress response but also stress-related tissue damage in mice
Authors: Harakawa Shinji , Nedachi Takaki , Suzuki Hiroshi
Published: December 2020

Although extremely low-frequency electric fields (ELF-EF) have been utilised for therapeutic purposes, the biological effect and the underlying mechanism of ELF-EF have not been elucidated. Here, we developed a mouse model of immobilisation-induced increase in glucocorticoid (GC) to evaluate the effect of ELF-EF. Mice were exposed to 50-Hz 10 kV/m EF via a parallel plate electrode and immobilised as needed. The ELF-EF suppressed the immobilisation-induced increase in blood GC level. Here, the results of 32 tests using the model were pooled and analysed. The suppressive effect of ELF-EF on immobilisation-induced increase in GC was reproduced, and the GC level was slightly higher in the ELF-EF-treated mice than in the sham-controlled mice, a novel observation. The immobilisation-induced increase in lactate dehydrogenase, glutamic oxaloacetic transaminase, and glutamic pyruvic transaminase, markers of tissue damage, was suppressed by co-treatment with EF in the biochemical tests using the same plasma sample. In the metabolome analysis, the changes in corticosterones, leukotrienes, and hydroxyeicosatetraenoic acids, markers of inflammation, showed a pattern similar to that of the plasma GC level. Thus, ELF-EF suppresses the stress response that causes an increase in the GC level and slightly promotes GC production in the absence of stress. Moreover, the suppressive effect of ELF-EF on induced stress response might be involved in stress-induced tissue damage or inflammation in immobilised mice. Overall, the model and the data help explore the biological effect of ELF-EF and explain the stress-relieving effect of EF. They would be useful in determining the medical applications of EF in humans and animals.
Author Correction: Increased insect herbivore performance under elevated CO2 is associated with lower plant defence signalling and minimal declines in nutritional quality
Authors: Johnson Scott N. , Waterman Jamie M. , Hall Casey R.
Published: December 2020

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Construction and validation of a nomogram for predicting cancer-specific survival in hepatocellular carcinoma patients
Authors: Liu Kang , Huang Gaobo , Chang Pengkang , Zhang Wei , Li Tao , Dai Zhijun , Lv Yi
Published: December 2020

The prognosis of patients with hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) is a research hotspot. This study aimed to incorporate important factors obtained from SEER database to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of patients with HCC and ICC. We obtained patient data from SEER database. The nomogram was constructed base on six prognostic factors for predicting CSS rates in HCC patients. The nomogram was validated by concordance index (C-index), the receiver operating characteristic (ROC) curve and calibration curves. A total of 3227 patients diagnosed with HCC (3038) and ICC (189) between 2010 and 2015 were included in this study. The C-index of the nomogram for HCC patients was 0.790 in the training cohort and 0.806 in the validation cohort. The 3- and 5-year AUCs were 0.811 and 0.793 in the training cohort. The calibration plots indicated that there was good agreement between the actual observations and predictions. In conclusion, we constructed and validated a nomogram for predicting the 3- and 5-year CSS in HCC patients. We have confirmed the precise calibration and excellent discrimination power of our nomogram.
Robust quantum point contact operation of narrow graphene constrictions patterned by AFM cleavage lithography
Authors: Kun Péter , Fülöp Bálint , Dobrik Gergely , Nemes-Incze Péter , Lukács István Endre , Csonka Szabolcs , Hwang Chanyong , Tapasztó Levente
Published: December 2020

Detecting conductance quantization in graphene nanostructures turned out more challenging than expected. The observation of well-defined conductance plateaus through graphene nanoconstrictions so far has only been accessible in the highest quality suspended or h-BN encapsulated devices. However, reaching low conductance quanta in zero magnetic field, is a delicate task even with such ultra-high mobility devices. Here, we demonstrate a simple AFM-based nanopatterning technique for defining graphene constrictions with high precision (down to 10 nm width) and reduced edge-roughness (+/−1 nm). The patterning process is based on the in-plane mechanical cleavage of graphene by the AFM tip, along its high symmetry crystallographic directions. As-defined, narrow graphene constrictions with improved edge quality enable an unprecedentedly robust QPC operation, allowing the observation of conductance quantization even on standard SiO2/Si substrates, down to low conductance quanta. Conductance plateaus, were observed at n × e2/h, evenly spaced by 2 × e2/h (corresponding to n = 3, 5, 7, 9, 11) in the absence of an external magnetic field, while spaced by e2/h (n = 1, 2, 3, 4, 5, 6) in 8 T magnetic field.
The link between star formation and gas in nearby galaxies
Authors: Feldmann Robert
Published: December 2020

Observations of the interstellar medium are key to deciphering the physical processes regulating star formation in galaxies. However, observational uncertainties and detection limits can bias the interpretation unless carefully modeled. Here I re-analyze star formation rates and gas masses of a representative sample of nearby galaxies with the help of multi-dimensional Bayesian modeling. Typical star forming galaxies are found to lie in a ‘star forming plane’ largely independent of their stellar mass. Their star formation activity is tightly correlated with the molecular and total gas content, while variations of the molecular-gas-to-star conversion efficiency are shown to be significantly smaller than previously reported. These data-driven findings suggest that physical processes that modify the overall galactic gas content, such as gas accretion and outflows, regulate the star formation activity in typical nearby galaxies, while a change in efficiency triggered by, e.g., galaxy mergers or gas instabilities, may boost the activity of starbursts.
Physicochemical properties and Mycobacterium tuberculosis transporters: keys to efficacious antitubercular drugs?
Authors: Fullam Elizabeth , Young Robert J.
Published: December 2020

The physicochemical properties of TB drugs are compared oral drugs and antibiotics, which support likely roles for transporters contributing to their efficacy.
Sentence Imitation With Masked Morphemes in Czech: Memory, Morpheme Frequency, and Morphological Richness
Authors: Smolík Filip , Matiasovitsová Klára
Published: December 2020

Purpose

This study examined two markers of language impairment (LI) in a single experiment, testing sentence imitation and grammatical morphology production using an imitation task with masked morphemes. One goal was to test predictions of the morphological richness account of LI in Czech. We also tested the independent contributions of language and memory skills to sentence imitation performance.

Method

Seventeen children with LI (5;1–7;6 [years;months]) and 17 vocabulary-matched typically developing (TD) children (3;8–4;11) were administered a sentence imitation task where each sentence had one noun or verb ending replaced by a coughing sound. In addition, a receptive vocabulary and the digit span (backward and forward) tasks were administered.

Results

Children with LI were significantly less accurate than TD children in sentence imitation task. Both vocabulary and digit span had unique effects on sentence imitation scores. Children with LI were less successful in imitating the target words, especially verbs. However, if they succeeded, their completions of the masked morphemes were no less accurate than in TD children. The accuracy of completions was affected by the morpheme frequency and homophony, but these effects were similar in TD and affected children.

Conclusions

Sentence imitation is a measure of language skills and verbal memory. Results on morpheme completions are consistent with processing models of LI, but some predictions of the morphological richness model were not confirmed. The results suggest that children with LI might have a deficit in organizing morphosyntactic relations in sentences, rather than in morphological processing proper.
A new search for star forming regions in the southern outer Galaxy
Authors: König C. , Urquhart J. S. , Wyrowski F. , Colombo D. , Menten K. M.
Published: December 2020

Context. Star formation in the outer Galaxy is thought to be different from that in the inner Galaxy, as it is subject to different environmental parameters such as metallicity, interstellar radiation field, or mass surface density, which all change with galactocentric radius. Extending our star formation knowledge, from the inner to the outer Galaxy, helps us to understand the influences of the change of the environment on star formation throughout the Milky Way.

Aims. We aim to obtain a more detailed view on the structure of the outer Galaxy, determining physical properties for a large number of star forming clumps and understanding star formation outside the solar circle. As one of the largest expanding Galactic super-shells is present in the observed region, a unique opportunity is taken here to investigate the influence of such an expanding structure on star formation as well.

Methods. We used pointed 12CO(2–1) observations conducted with the APEX telescope to determine the velocity components towards 830 dust clumps identified from 250 μm Herschel/Hi-GAL SPIRE emission maps in the outer Galaxy between 225° < ℓ < 260°. We determined kinematic distances from the velocity components, in order to analyze the structure of the outer Galaxy and to estimate physical properties such as dust temperatures, bolometric luminosities, clump masses, and H2 column densities for 611 clumps. For this, we determined the dust spectral energy density distributions from archival mid-infrared to submillimeter (submm) emission maps.

Results. We find the identified CO clouds to be strongly correlated with the highest column density parts of the H I emission distribution, spanning a web of bridges, spurs, and blobs of star forming regions between the larger complexes, unveiling the complex three-dimensional structure of the outer Galaxy in unprecedented detail. Using the physical properties of the clumps, we find an upper limit of 6% (40 sources) capable of forming high-mass stars. This is supported by the fact that only two methanol Class II masers, or 34 known or candidate H II regions, are found in the whole survey area, indicating an even lower fraction that are able to form high-mass stars in the outer Galaxy. We fail to find any correlation of the physical parameters of the identified (potential) star forming regions with the expanding supershell, indicating that although the shell organizes the interstellar material into clumps, the properties of the latter are unaffected.

Conclusions. Using the APEX telescope in combination with publicly available Hi-GAL, MSX, and Wise continuum emission maps, we were able to investigate the structure and properties of a region of the Milky Way in unprecedented detail.
BAYES-LOSVD: A Bayesian framework for non-parametric extraction of the line-of-sight velocity distribution of galaxies
Authors: Falcón-Barroso J. , Martig M.
Published: December 2020

We introduce BAYES-LOSVD, a novel implementation of the non-parametric extraction of line-of-sight velocity distributions (LOSVDs) in galaxies. We employed Bayesian inference to obtain robust LOSVDs and associated uncertainties. Our method relies on a principal component analysis to reduce the dimensionality on the set of templates required for the extraction and thus increase the performance of the code. In addition, we implemented several options to regularise the output solutions. Our tests, conducted on mock spectra, confirm the ability of our approach to model a wide range of LOSVD shapes, overcoming limitations of the most widely used parametric methods (e.g., Gauss-Hermite expansion). We present examples of LOSVD extractions for real galaxies with known peculiar LOSVD shapes, including NGC 4371, IC 0719, and NGC 4550, using MUSE and SAURON integral-field unit (IFU) data. Our implementation can also handle data from other popular IFU surveys (e.g., ATLAS3D, CALIFA, MaNGA, SAMI).
L’agriculture tunisienne face à la Covid-19 : impacts de la crise sanitaire et perspectives pour une agriculture résiliente
Authors: Elloumi Mohamed
Published: December 2020

L’économie tunisienne a subi de plein fouet les effets de la crise sanitaire Covid-19 et des mesures indispensables pour la juguler prises par les pouvoirs publics comme la fermeture des frontières et le confinement de la population. L’agriculture a dû faire face aux mêmes difficultés ; toutefois, la courte durée du confinement total et la décision des autorités d’exclure les activités agricoles de certaines restrictions ont réduit les effets de la crise sanitaire sur la disponibilité des produits alimentaires. Cependant, la baisse du pouvoir d’achat des franges les plus vulnérables de la population a réduit leur accès à certains produits de base. En définitive, ce sont les principales filières agricoles tunisiennes d’exportation (dattes, huile d’olive…) qui ont été les plus impactées du fait de la baisse de la demande internationale. Enfin, si la réponse des agriculteurs et des différents acteurs qui encadrent le secteur a permis une certaine résilience, il n’en demeure pas moins que cette conjoncture a servi de révélateur d’une crise plus profonde du système alimentaire et agricole qui doit faire face à des défis majeurs comme la dépendance aux marchés extérieurs pour plusieurs produits de base (céréales, soja, viande rouge, huile de graine…) et dont le dépassement nécessite une refonte à la fois du modèle technique et du pacte social entre agriculteurs et consommateurs.
Government subsidies and corporate innovation performance- Based on the empirical analysis of the new energy automobile industry
Authors: Xiaoman Wu , Shiqi Wu
Published: December 2020

This paper selects 112 listed companies in China’s a-share new energy vehicle sector from 2009 to 2018 as a research sample, and uses panel data regression analysis models to empirically test the effects of government subsidies on corporate R&D investment and corporate innovation performance. It shows that government subsidies have a significant promotion effect on enterprises R&D investment; government subsidies have a significant inhibition effect on enterprises’ innovation performance.
Risk Assessment of Internet Credit Based on Big Data Analysis
Authors: HAORU WANG , Zhixuan Yi , YUJIA WEI , Yao Tianpeng , Shuoheng Zhao , qiang Xuzhi
Published: December 2020

In recent years, network technology has continued to develop, and Internet finance has rapidly developed into a new business area. Internet credit is one of the important ways for banks to conduct business, and the scale of online credit has continued to expand. Due to the existence of various unpredictable factors, frequent emergencies, and online financial fraud, the overall market risk in the field of online credit has increased, and the rate of non-performing loans has continued to increase. Online financial fraud cases show that online credit risk has become one of the most prominent risks in the operation of commercial banks, which has a direct impact on the stability and development of commercial banks. We can build a bank database system based on big data, introduce professional big data analysis technical personnel, and constantly improve the big data sharing analysis platform, so that commercial banks can use system data more fully and effectively, and facilitate relevant business personnel to use big data technology for analysis and calculation. Big data is constantly produced, which provides basic materials for online credit risk assessment. Big data analysis technology is gradually mature, and it has the necessary conditions for online credit risk assessment. Based on the theories and technologies related to big data analysis, this paper comprehensively evaluates the online credit risk in the form of example data analysis, thereby effectively reducing the online credit risk coefficient.
Data-Driven Approach for Predicting and Explaining the Risk of Long-Term Unemployment
Authors: Zhao Linan (Frank)
Published: December 2020

Long-term unemployment has significant societal impact and is of particular concerns for policymakers with regard to economic growth and public finances. This paper constructs advanced ensemble machine learning models to predict citizens’ risks of becoming long-term unemployed using data collected from European public authorities for employment service. The proposed model achieves 81.2% accuracy on identifying citizens with high risks of long-term unemployment. This paper also examines how to dissect black-box machine learning models by offering explanations at both a local and global level using SHAP, a state-of-the-art model-agnostic approach to explain factors that contribute to long-term unemployment. Lastly, this paper addresses an under-explored question when applying machine learning in the public domain, that is, the inherent bias in model predictions. The results show that popular models such as gradient boosted trees may produce unfair predictions against senior age groups and immigrants. Overall, this paper sheds light on the recent increasing shift for governments to adopt machine learning models to profile and prioritize employment resources to reduce the detrimental effects of long-term unemployment and improve public welfare.
Research on Application of Big Data in Local Government Debt Audit
Authors: Li Xuefeng
Published: December 2020

While big data provides massive information for auditing work, it also changes the specific requirements of audit procedures. The pressure of economic downward has increased the concealment of local government debt risks in China, hence the requirements for its audit have increased accordingly. This paper combines the method of investigation and theoretical analysis to study the status quo of local government debt. Based on big data, the audit procedure of local government debt is designed in order to provide a reference for actual government debt audit work.
Exploring the Impact of Organizational Implants of a Manufacturing Company on Service Innovation in the context of big data: A case study of XI’AN SHAANGU POWER
Authors: Wang Rong , Zhu Dan , Chen Juhong
Published: December 2020

Service innovation has become an important way for manufacturing companies to obtain and maintain their competitive advantages. Organizational implants have been proven to enhance service innovation in manufacturing companies, while the rise of big data offers new opportunities for it. This study aims to explore the impact path from organizational implants of a manufacturing company to service innovation in the context of big data with the application of Single Case Study Method, and XI’AN SHAANGU POWER is selected as research object. The findings are suggested as follows: (1) There are two ways of organizational implants to achieve service innovation for manufactures. One is employee implants, and the other is device implants. (2) Employee implants can create relationship capital, and device implants can generate data resources. (3) Relationship capital has a direct and indirect positive impact on service innovation through professional knowledge acquisition and customer demands mining. (4) Data resources have an indirect positive impact on service innovation through customer demands mining and product technology upgrading.
A Study on Economic Development of the Hui Nationality in Ningxia under the “The Belt and Road Initiative” Strategic System
Authors: Jijian Gu
Published: December 2020

The development of Hui nationality property economy in Ningxia is based on the new institutional economy from the theoretical perspective, and it is found that it is regulated by ethnic groups and habits and so on. The development of its property right economy has been greatly affected, which cannot adapt to the development of modern market economy. Therefore, this paper proposes to completely change the status of the property rights of Hui nationality by reforming the economic behavior and consciousness in religious beliefs, increasing the degree of economic openness, expanding the special education of market economy and clarifying the property right system.
Two-stage DEA for Bank Efficiency Evaluation Considering Shared Input and Unexpected Output Factors
Authors: Aifeng Song , XiaoYang Zhang , Weilai Huang , xue Yang , Juan Yang
Published: December 2020

With the increasingly fierce market competition, only by relying on high-quality products and high customer satisfaction can enterprises survive in the fierce competition. Among many evaluation methods, Data Envelopment Analysis (DEA), as a non-parametric statistical method to effectively deal with multi-input and multi-output problems, has received more and more attention in evaluating the relative efficiency of decision-making units. In the process of bank efficiency evaluation based on DEA method, there will be a situation that banks have both dual role factors and unexpected output factors. The Two-stage DEA model provides an effective analysis method to solve the problem of bank efficiency evaluation of complex organizational structure. In order to evaluate the efficiency of unexpected output with uncertain information, a stochastic DEA model of unexpected output is established.
Research on the Influencing Factors of Purchasing Intention of Brand Agricultural Products from the Perspective of Perceived Value
Authors: Wei Yao , Peng Yuxin , Chen Jiaying
Published: December 2020

According to the theory of customer perceived value and brand agricultural characteristics, this paper puts forward that customer perceived value of the brand agricultural products has a functional value, economic value, emotional value, social value and image value of five dimension. Through empirical analysis, it is proved that the existence of five dimensions of perceived value and the five dimensions have significant positive effects on the purchase intention of brand agricultural products, among them, the effect of social value is the largest. And product involvement has a moderating effect on perceived value and purchase intention. Finally, based on the above steps, this paper puts forward the ranking of consumers’ attention to the perceived value dimension, and accordingly provides more accurate marketing countermeasures for enterprises.
Research and Practice of Quantitative Models on The Freedom of Trade Based on AHP-FCE Method: Taking Major Countries in WTO as Examples
Authors: Sishi Qin , Ji’an Tang , Feng Liu , Shuqian Shao , Shiying Lu
Published: December 2020

In recent years, protectionism and unilateralism in the field of international trade are increasing. The WTO-centric multilateral trade regime has been hit. By researching the index of trade freedom among countries in international trade, this paper takes five important countries in WTO as an example, and constructs the trade freedom index and the national trade freedom model. The study reviewed and analysed global and regional developments in cross-border trade and investigated five varialbes that impacted the index of trade freedom. Then the fuzzy comprehensive analysis method (FCE) is used to obtain the comprehensive evaluation matrix by fuzzy arithmetic processing through the evaluation index weight and fuzzy relation matrix. Therefore, the changing data of the index of trade freedom in five countries from 2017 to 2018 are obtained. It is discovered that there is a significant difference in the index of trade freedom among countries. What’s worse, the average of the global index has declined year by year. This phenomenon is caused by the decline of global trade volume and the prevalence of new trade barriers. In the end, this paper proposes the implementation of multilateral negotiations and the establishment of long-term penalties as possible solutions.
Research on Discrete Dynamic Forecasting Model of Government Human Resources
Authors: Li Qin
Published: December 2020

For the evolution of complex system, especially the unbalanced complex system, dynamic is its universal attribute. In this paper, by introducing the discrete dynamic system model in complex system research, a method of establishing the discrete dynamic system model of government human resources system is proposed from the vertical level. In this study, human resources were forecasted by the method of manpower/population ratio, linear regression and grey system, and the total number of health human resources in A city from 2018 to 2022 was forecasted by weighted average combination method. The results show that we should make great efforts to innovate the training mode of health personnel, improve the enthusiasm of staff, and reasonably control the expansion of hospitals.
The Impact of Share Repurchase on R&D Expenditure: An Empirical Study from High-tech industry
Authors: Cheng Hongwei , Yin Liang , Luo Xinwei
Published: December 2020

After the policy was released in 2018, listed companies increased the frequency and amount of repurchases. Some studies believe that managers will give up long-term investment which is beneficial to the sustainable development of enterprises due to the short-term performance response caused by share repurchases. This paper took the repurchase firms in the high-tech industry from 2008 to 2018 as samples, it is found that the company’s share repurchase promotes R&D expenditure and will not reduce expenditure in R&D for short-term stock price reaction. Furthermore, the heterogeneity study found that in state-owned firms, the company’s share buybacks have a more significant role in promoting R&D expenditure.
Predicting the SP500 Index Trend Based on GBDT and LightGBM Methods
Authors: shangchen Ma
Published: December 2020

Algorithms that are previously difficult to implement have been successfully applied in different fields because of hardware development. Quantitative investment has the characteristics of rationality and efficiency and has obvious advantages over traditional methods. Based on the SP500 index data for 4936 trading days, 10 characteristics such as PSY, MACD, STOCHK and STOCHD were generated. Based on those features, quantitative investment strategies for the GBDT and LightGBM models were constructed. Validation showed that the annualized returns of the two strategies exceeded the direct purchase and holding of the SP500 index, with the annualized returns of 43.4% and 50.7%. The performance of risk control of the two models was also better than the benchmark strategy. The GBDT model had less risk than the LightGBM model when the same benefits were obtained. The accuracy of the LightGBM model was higher than that of the GBDT, and its F1 score was 0.814, while the GBDT model was 0.805. For the different selected components, the results of the principal component analysis showed that the PSY feature weight in the GBDT model was much higher than other features, and a single feature can be applied for straightforward prediction. In the LightGBM model, the seven feature weights such as STOCHK were relatively balanced, and more features can be balanced at the same time to obtain more accurate results. The article designs investment strategies based on the LightGBM model for the first time and provides new ideas for providing a framework for index investment.
Prediction and Empirical Study of Stock Yield Volatility Based on Event Study
Authors: Mingcai Shen , Xin Liu , Xi Huang , Zhaohuan Cao , Ganya Su
Published: December 2020

Stock market event is an important source of information for investment decision, and it is of practical significance to quantify the event and predict the fluctuation range of future return under such event. Most researchers study stock market events horizontally, that is, to study the impact of a current event on the stock price of a certain sector or industry, while the paper attempts to study vertically the impact of a certain event of a single listed company on the return. Based on the internal relations between public announcement and stock yield of listed companies, the paper deduced the daily yield prediction model of event window by VAR(p) to exclude subjective “estimation” in the past and verifies the feasibility of the model.
The Empirical Analysis of High-tech Trade Imbalance Between China and the US
Authors: Zhao Yiming
Published: December 2020

The United States, as a leader in technology industry, has been in a deficit position for a long time in the high-tech trade between China and the United States, which has been increasing year by year. This is obviously contrary to traditional international trade theory and the comparative advantages of the two countries. Based on the US policy restrictions on China ‘s high-tech product exports, the enhancement of China ‘s independent innovation capabilities, and international direct investment in China, this article conducts an empirical analysis to explore the reasons for the China-US high-tech trade imbalance and then gives corresponding policy recommendations.
Research on the Measurement of Manufacturing Industry Integration Level of Shandong Capital City Cluster
Authors: Zhao Yang
Published: December 2020

This paper analyzes the integration level of regional manufacturing industry by measuring the similarity coefficient of manufacturing industry structure and regional division index between Jinan, the capital city of Shandong province, and other cities in the region from 2012 to 2017. From 2012 to 2017, the similarity coefficient of industrial structure of Shandong capital city cluster is declining; the regional division index is rising; and the industrial transformation of Jinan in the region has made remarkable progress, which is conducive to the continuous improvement of regional integration level.
Business model innovation of Qingdao Youzhu Decoration Company
Authors: Haibing Liu , Yuyue Kan
Published: December 2020

There are many problems in home decoration industry, such as imperfect industry system, lack of integrity of enterprises, low quality of construction personnel, etc. However, Qingdao Youzhu Home Decoration Co., Ltd. has achieved rapid growth with the innovation of business model. Therefore, based on Qingdao Youzhu Home Decoration Co., Ltd., this paper attempts to analyze the company’s business model innovation. The conclusion shows that the company’s business model canvas includes nine modules of important partners, value proposition, key business, core resources, customer segmentation, customer relationships, Channel access, revenue sources and cost structure, and each module plays an important role.
Overview of Machine Learning for Stock Selection Based on Multi-Factor Models
Authors: Li Haoxuan , Zhang Xueyan , Li Ziyan , Zheng Chunyuan
Published: December 2020

In recent years, many scholars have used different methods to predict and select stocks. Empirical studies have shown that in multi-factor models, machine learning algorithms perform better on stock selection than traditional statistical methods. This article selects six classic machine learning algorithms, and takes the CSI 500 component stocks as an example, using 19 factors to select stocks. In this article, we introduce four of these algorithms in detail and apply them to select stocks. Finally, we back-test six machine learning algorithms, list the data, analyze the performance of each algorithm, and put forward some ideas on the direction of machine learning algorithm improvement.
Research on the Evaluation of Innovation Performance of Regional High-tech industry Based on Grey Relation Analysis
Authors: Li Peizhe
Published: December 2020

Scientific evaluation of the innovation performance of regional high-tech industry has an important impact on promoting the healthy development of high-tech industry and promoting regional economic growth. On the basis of constructing the index system of regional high-tech industry innovation performance evaluation, the index weight is determined based on the entropy weight method, and the gray correlation analysis method is used to evaluate and rank the regional high-tech industry innovation performance. The results show that there is a large gap in the innovation performance level of regional high- tech industries in China, and the innovation performance level of coastal areas is higher, such as Guangdong, Jiangsu, Zhejiang and other provinces; the innovation performance level of western areas is lower, such as inner Ningxia, Xinjiang, Qinghai and other provinces. The evaluation result of this method is scientific and objective, and it has a good effect in high-tech industry innovation performance evaluation. The conclusion of this paper can provide corresponding enlightenment for the innovation activities of regional high-tech industries in China.
Guanxi, Co-Production and New Product Performance: a Moderated Mediating Effect Model
Authors: Minglei Xie
Published: December 2020

Guanxi is an important channel for small and medium-sized enterprises（SMEs）to obtain external resources, but literatures did not pay much attention on the impact of Guanxi on the mechanism of enterprise innovation. This paper examines the mediating effect of the relationship on co-production in the process of new product development by examining the sample data of 275 small and medium enterprises from the Yangtze river delta and the pearl river delta in China, and further examines the moderating effect of dynamic environment. It is found that the relationship can directly improve the performance of new products of SMEs, and can also play an indirect role through co-production. Dynamic environments enhance the relationship between co-production and new product performance.
The Impact of Industrial Transfer on Industrial Structure Upgrading in Central China Take Hubei Province as an example
Authors: Chen Chun , Yuan Hong , Lin Weiyan , Xia Qing
Published: December 2020

In the construction plan of China (Hubei) pilot free trade zone issued by China (Hubei) pilot free trade zone in 2018, it is pointed out that industrial transfer should be orderly undertaken, which undoubtedly provides a strong institutional guarantee for Hubei to undertake industrial transfer. This paper analyzes the mechanism of industrial transfer on industrial structure upgrading: capital accumulation mechanism, technology progress mechanism, industry aggregation mechanism. At the same time through empirical analysis it is concluded that: build the double logarithm model of Hubei province to undertake industry shift after the provincial labor resources, science and technology innovation ability, industrial concentration degree of ascension for the upgrading of industrial structure in Hubei province has a certain role in promoting, especially the size of the capital and the increase of the number of high-tech talent to upgrade the industrial structure to promote the most significant effect. Therefore, the government should intensify efforts to introduce domestic and foreign capital, cultivate and attract more high-tech talents, focus on improving the quality of workers, expand the scale of industrial agglomeration within the province, and enhance the ability of scientific and technological innovation.
Related Research on News Sentiment Tendency and Stock Price Fluctuation
Authors: Li Hongye
Published: December 2020

In recent years, with further development of the Internet and artificial intelligence, the research on using news sentiments, and then predicting investor behavior has become more feasible. Based on the news information obtained from the Internet, this article analyzes the investor ‘s emotions about the news, further predicts the behavior of investors, and then the rise and fall of investment asset prices. We use news sentiment tendency and stock price of listed companies to analyze whether the news sentiment really affects the stock price and the degree of its influence.

The research results of the thesis are divided into two parts: (1) A CNN neural network capable of analyzing news that may have an impact on stock prices in the near future is designed and trained to obtain a timely response and form a simulated investment decision for investors to adjust the investment strategy timely; (2) Combined with the economic indicators, this article uses the LSTM neural network to comprehensively investigate whether the emotional tendency of the news has a significant impact on the stock price. This article draws four kinds of images, which can test the accuracy of the model from different angles and guide consumers’ investment.
The Influence and Impact of the Exchange Rate on the Economy
Authors: Zhao Yuxin
Published: December 2020

This paper analyzes the influence and impact on the exchange rate from several aspects. Firstly, the primary factors influenced by the exchange rate, export, the prices and costs are introduced in this paper. Productivity refers to the increase because the local currency strengthens. Then, it indicates that the exchange rate affects productivity. The last part about influential factors is the effect on the number of tourists. After analyzing the impact of the exchange rate, some suggestions about exchange rate policies are put forward. The exchange rate is an essential element, and it requires to attach importance to both the logical operation and the appropriate use of policy.
A Takeover Strategy Based on the Business Analysis of Transportation and Real Estate Industry
Authors: Wu Zhe
Published: December 2020

This paper aims to find out two proper target firms and make a proper advice for M&A, thus providing a method of how to assess the possible merger and acquisition. This paper will make suggestions for Jaffa Ltd, since it is an influential Australian based commodities trading company which encounter a dilemma of decreasing growth. Since the whole industry has the same problem, acquiring other newly developing companies from different industries will be a good strategy for this kind of companies that own a large amount of cash yet has difficulty in developing in its own field. With the business analysis, Jaffa Ltd is supposed to take over GMG and AZJ.
Estimation of the Impact of the New International Land and Sea Trade Channel on the Development of the Trade Potential of 8 Domestic Provinces and Cities
Authors: Jijian Gu , Lipeng Feng , Liyan He , Heng Zhong
Published: December 2020

The new international land and sea trade channel is an important part of China’s “The Belt and Road Initiative” going south, with Chongqing as the operating center, and 7 provinces and cities such as Guangxi, Guizhou, and Gansu as key nodes. Gravity Model of Trade is adopted to analyze the issue of trade creation effect and trade transfer effect in the flow of China-ASEAN trade in detail. According to the theoretical trade value calculated by the export gravity model, the actual trade value was divided by the theoretical value to calculate the trade potential coefficient, which has been applied to measure the trade potential of export of 8 provinces and cities to the ten ASEAN countries. It is concluded that trading partners are in different types ranging from “potential remodeling”, “potential expansion” to “great potential”, and heterogeneity tests are performed to prove the self-consistency of the effect measurement. Further, it is proposed that to further develop trade relations, we must develop positive factors to promote export trade, stimulate trade needs of partner countries, and actively develop trade market countermeasures.
The Application of Topological Data Analysis in Practice and Its Effectiveness
Authors: Cheng Liang
Published: December 2020

Topological Data Analysis(TDA) is a new and fast growing field in data science. TDA provides an approach to analyze data sets and derive their relevant feature out of complex high-dimensional data, which greatly improves the working efficiency in many fields. In this paper, the author mainly discusses some mathematics concepts about topology, methods in TDA and the relation between these topological concepts and data sets (how to apply topological concepts on data). The problems of TDA, mathematical algorithm using in TDA and two application-examples are introduced in this paper. In addition, the advantages, limitations, and the direction of future development of TDA are discussed.
Research on building a smart supply chain system to promote the high-quality economic development of Guangdong, Hong Kong and Macao
Authors: CAO Yonghui , JIANG He
Published: December 2020

To promote the construction of Guangdong, Hong Kong and Macao Bay area is a major decision made by the Party Central Committee, a new measure to promote the formation of a new pattern of comprehensive opening-up in the new era, and a new practice to promote the development of the cause of “one country, two systems”. Promoting the construction of the Great Bay area of Guangdong, Hong Kong and Macao is conducive to deepening exchanges and cooperation between the mainland and Hong Kong and Macao, and is of great significance for Hong Kong and Macao to participate in national development strategies, enhance competitiveness and maintain long-term prosperity and stability. From the perspective of smart supply chain, this paper proposes to build a smart supply chain system in Guangdong, Hong Kong and Macao to promote high-quality economic development.
ARIMA and Multiple Linear Regression Additive Model for SO2 Monitoring Data’s Calibration
Authors: Yan Xu , Shuangting Lan
Published: December 2020

SO2 is one of the main air pollutants produced by industrial waste gas, civil combustion and automobile exhaust. Real-time monitoring of the concentration of SO2 can grasp the air quality in time and take corresponding measures to the pollution sources. Monitoring data may be affected by the internal factors and the external factors. ARIMA was used for the internal factor as A. Meteorological factors were taken as external factors, and the difference of SO2 between the standard data and monitoring data was taken as dependent variable. Multivariate linear regression was modeled as B. Time series calibration model was obtained Y=A+B. The error analysis showed that the accuracy of SO2 was improved. The additive model could effectively calibrate SO2 monitoring data.