bluuebunny/crossref_metadata_2025 huggingface dataset:
Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes
Authors: Eme Laura , Tamarit Daniel , Caceres Eva F. , Stairs Courtney W. , De Anda Valerie , Schön Max E. , Seitz Kiley W. , Dombrowski Nina , Lewis William H. , Homa Felix , Saw Jimmy H. , Lombard Jonathan , Nunoura Takuro , Li Wen-Jun , Hua Zheng-Shuang , Chen Lin-Xing , Banfield Jillian F. , John Emily St , Reysenbach Anna-Louise , Stott Matthew B. , Schramm Andreas , Kjeldsen Kasper U. , Teske Andreas P. , Baker Brett J. , Ettema Thijs J. G.
Published: June 2023

In the ongoing debates about eukaryogenesis—the series of evolutionary events leading to the emergence of the eukaryotic cell from prokaryotic ancestors—members of the Asgard archaea play a key part as the closest archaeal relatives of eukaryotes1. However, the nature and phylogenetic identity of the last common ancestor of Asgard archaea and eukaryotes remain unresolved2–4. Here we analyse distinct phylogenetic marker datasets of an expanded genomic sampling of Asgard archaea and evaluate competing evolutionary scenarios using state-of-the-art phylogenomic approaches. We find that eukaryotes are placed, with high confidence, as a well-nested clade within Asgard archaea and as a sister lineage to Hodarchaeales, a newly proposed order within Heimdallarchaeia. Using sophisticated gene tree and species tree reconciliation approaches, we show that analogous to the evolution of eukaryotic genomes, genome evolution in Asgard archaea involved significantly more gene duplication and fewer gene loss events compared with other archaea. Finally, we infer that the last common ancestor of Asgard archaea was probably a thermophilic chemolithotroph and that the lineage from which eukaryotes evolved adapted to mesophilic conditions and acquired the genetic potential to support a heterotrophic lifestyle. Our work provides key insights into the prokaryote-to-eukaryote transition and a platform for better understanding the emergence of cellular complexity in eukaryotic cells.
An FSV analysis approach to verify the robustness of the triple-correlation analysis theoretical framework
Authors: Wu Robert M. X. , Zhang Zhongwu , Zhang Huan , Wang Yongwen , Shafiabady Niusha , Yan Wanjun , Gou Jinwen , Gide Ergun , Zhang Siqing
Published: June 2023

Among all the gas disasters, gas concentration exceeding the threshold limit value (TLV) has been the leading cause of accidents. However, most systems still focus on exploring the methods and framework for avoiding reaching or exceeding TLV of the gas concentration from viewpoints of impacts on geological conditions and coal mining working-face elements. The previous study developed a Trip-Correlation Analysis Theoretical Framework and found strong correlations between gas and gas, gas and temperature, and gas and wind in the gas monitoring system. However, this framework's effectiveness must be examined to determine whether it might be adopted in other coal mine cases. This research aims to explore a proposed verification analysis approach—First-round—Second-round—Verification round (FSV) analysis approach to verify the robustness of the Trip-Correlation Analysis Theoretical Framework for developing a gas warning system. A mixed qualitative and quantitative research methodology is adopted, including a case study and correlational research. The results verify the robustness of the Triple-Correlation Analysis Theoretical Framework. The outcomes imply that this framework is potentially valuable for developing other warning systems. The proposed FSV approach can also be used to explore data patterns insightfully and offer new perspectives to develop warning systems for different industry applications.
Sex difference in the association of the triglyceride glucose index with obstructive coronary artery disease
Authors: Lu Ya-Wen , Tsai Chuan-Tsai , Chou Ruey-Hsin , Tsai Yi-Lin , Kuo Chin-Sung , Huang Po-Hsun , Lin Shing-Jong
Published: June 2023

Insulin resistance (IR) is associated with cardiovascular disease in non-diabetic patients. The triglyceride-glucose (TyG) index, incorporating serum glucose and insulin concentrations, is a surrogate insulin resistance marker. We investigated its association with obstructive coronary artery disease (CAD) and sex differences therein. Patients with stable angina pectoris requiring invasive coronary angiography between January 2010 and December 2018 were enrolled. They were divided into two groups according to TyG index. Two interventional cardiologists diagnosed obstructive CAD by angiography review. Demographic characteristics and clinical outcomes were compared between groups. Relative to lower index, patients with higher (≥ 8.60) TyG index had higher BMIs and more prevalent hypertension, diabetes, and elevated lipid profiles [total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), fasting plasma glucose (FPG)]. Higher TyG index increased women’s obstructive CAD risk after multivariate adjustment (adjusted odds ratio (aOR) 2.15, 95% confidence interval (95% CI) 1.08–4.26, p = 0.02) in non-diabetic populations compared with men. No sex difference was found for diabetic patients. Higher TyG index significantly increased the obstructive CAD risk, overall and for non-diabetic women. Larger-scale studies are needed to confirm our findings.
Geoeffective interplanetary magnetic field (IMF) from in situ data: realistic versus idealized spiral IMF
Authors: Bandić Mario , Verbanac Giuliana , Živković Slaviša
Published: June 2023

The geoeffective, southward IMF ($$B_\text {s}$$Bs) given in the GSM reference frame as nature presents is compared with that based on idealized, spiral IMF. We obtained$$B_\text {s}$$Bsand$$B_\text {s}$$Bssorted by the IMF polarity ($$B_\text {s}$$Bsfields) from in situ data at a high 16-second resolution. Idealized IMF is derived by omitting the fluctuation of the IMF in the GSEQ Z-direction. Results are: the absolute value of realistic$$B_\text {s}$$Bsis larger than the one from idealized IMF; realistic$$B_\text {s}$$Bspolarity fields exist in all seasons, while those from idealized IMF exist only around spring/fall when the IMF points toward/away from the Sun; idealized$$B_\text {s}$$Bsfields match the predictions of the Russell–McPherron (RM) model almost ideally. The present study has resolved the issue related to the patterns and absolute values of the observed$$B_\text {s}$$Bsfields and those from the RM model that assumes an idealized IMF. It confirms that$$B_{z,\text {GSEQ}}$$Bz,GSEQplays a crucial role for$$B_\text {s}$$Bs. Finally, it paves a way to properly link the variations seen in geomagnetic activity with the pattern of the measured$$B_\text {s}$$Bsfields.
Antimicrobial and Antioxidant Properties of Lignin and Its Composites
Authors: Roy Swarup , Priyadarshi Ruchir , Purohit Shiv Dutt , Rhim Jong-Whan
Published: June 2023

Lignin is the second most abundant plant-derived and fascinating bio-based renewable polymer. It is a primary constituent of lignocellulosic materials found in plant cell walls. Lignin is a commonly available material as a waste product of the paper, pulp, and cellulosic ethanol industries. Lately, lignin and its composites have attracted considerable attention due to the excellent properties of lignin like its high abundance, lightweight nature, good reinforcing ability with polymers, biodegradability, CO2 neutrality, UV-light shielding effect, antioxidant activity, and antimicrobial action. The exceptional physical and functional properties of lignin make it a suitable filler for developing polymer-based composite materials. In this work, the isolation of lignin, its structure, and its functional properties such as antimicrobial and antioxidant potential are comprehensively reviewed. Moreover, the recent progress of lignin in manufacturing different polymer-based antimicrobial and antioxidant composites in food packaging, plant protection, and growth application is also summarized here.
Carbon dot-based superhydrophobic modification of a covalent organic framework for oil-in-water emulsion separation
Authors: Nayak Suman , Hassan Atikur , Das Neeladri , Das Prolay
Published: June 2023

Fabrication of a super hydrophobic composite from self-assembly of a hydrophilic COF and Carbon dots for oil-water separation.
New charge transfer-based organic room temperature phosphorescent trace doping systems
Authors: Zhao Yu-Qiang , Zhu Liping , Lu Jian-Mei , Yu Le , Zhang Lanyun , Zhou Ying
Published: June 2023

A series of organic room temperature phosphorescent trace doping systems were constructed.
Schottky heterogeneous interface design of Ti3C2/Bi4O5I2 to enhance the photocatalytic performance
Authors: Chen Dandan , Li Yan , Xu Haiyan , Xin Yueming , Wang Aiguo , Liu Kaiwei
Published: June 2023

Bi4O5I2 is loaded on Ti3C2 to form a Schottky heterojunction. The specific surface area and band gap energy can be adjusted by forming a heterostructure.
Continuous molecular monitoring of human dermal interstitial fluid with microneedle-enabled electrochemical aptamer sensors
Authors: Friedel Mark , Werbovetz Benjamin , Drexelius Amy , Watkins Zach , Bali Ahilya , Plaxco Kevin W. , Heikenfeld Jason
Published: June 2023

The first in-human demonstration of aptamer sensors is reported; these have the potential to enable continuous molecular monitoring beyond glucose.
CNT/turanite/FeNdCo-alloy electrodes to enhance the capacitance of waterproof/eco-friendly supercapacitors
Authors: Balderas-Soto Marco , Villabona-Leal Edgar Giovanny , Zakhidov Anvar A. , Mtz-Enriquez Arturo I. , Salas Pedro , Molina Andrea , Flores-Zuñiga Horacio , Oliva Jorge
Published: June 2023

We are reporting for the first time waterproof supercapacitors made with seawater (eco-friendly) electrolyte.
Degradation of three β-O-4 lignin model compounds via organic electrolysis and elucidation of the degradation mechanisms
Authors: Uruma Yoshiyuki , Yamada Tomohiro , Kojima Tsubasa , Zhang Tianyuan , Qu Chen , Ishihara Moe , Watanabe Takashi , Wakamatsu Kan , Maekawa Hirofumi
Published: June 2023

Woody biomass comprising cellulose, hemicellulose, and lignin has been the focus of considerable attention as an alternative energy source to fossil fuel for various applications.
Sb(iii)/Gum Arabic composite as a new natural-based environmentally green catalyst for the one-pot pseudo-four-component synthesis of 2H-indazolo[2,1-b] phthalazinetriones
Authors: Keihanfar Mina , Mirjalili Bi Bi Fatemeh , Bamoniri Abdolhamid
Published: June 2023

Sb(iii)–Gum Arabic composite as a unique natural-based and nontoxic catalyst was synthesized and characterized by FT-IR, XRD, TGA, ICP, BET, EDX and mapping.
Computational insights into the mechanisms and origins of switchable selectivity in gold(i)-catalyzed annulation of ynamides with isoxazoles via 6π-electrocyclizations of azaheptatrienyl cations
Authors: Badeji Abosede Adejoke , Liu Yuan , Oladipo Segun D. , Osinubi Adejoke Deborah
Published: June 2023

Computational studies shed light on why the incorporation of Au(i)-catalyst, a nitrogen atom and tosylamide group into heptatrienyl cations allows it to undergo 6π electrocyclization to afford seven-membered azepine instead of five-membered pyrrole product.
Gel transformation as a general strategy for fabrication of highly porous multiscale MOF architectures
Authors: Liu Zhang , Navas Javier Lopez , Han Wei , Ibarra Manuel Ricardo , Cho Kwan Joseph Kai , Yeung King Lun
Published: June 2023

The transformation of inorganic gels into MOFs is developed as a general strategy to construct complex porous MOF architectures at nano, micro, and millimeter length scales.
Hydrocarbons from kraft pulp pre-hydrolysis liquors in two steps using heterogeneous catalysis
Authors: Lebedeva Daria , Samec Joseph S. M.
Published: June 2023

Valorizing industrial side streams that are currently burnt to a low value is important to make biorefining more sustainable.
Photocatalytic activity and pH-induced morphological changes of ZnO/CuO nanocomposites prepared by chemical bath precipitation
Authors: Jalali Nargol , Rakhsha Amirhossein , Nami Mohammad , Rashchi Fereshteh , Mastelaro Valmor Roberto
Published: June 2023

Various morphologies of ZnO/CuO nanocomposites were obtained by altering the pH value and their influence on the optical and photocatalytic properties of this nanocomposite against organic dyes was examined.
Human stability assessment and fall detection based on dynamic descriptors
Authors: Gutiérrez Jesús , Martin Sergio , Rodriguez Victor
Published: June 2023

Fall detection systems use a number of different technologies to achieve their goals. This way, they contribute to better life conditions for the elderly community. The artificial vision is one of these technologies and, within this field, it has gained momentum over the course of the last few years as a consequence of the incorporation of different artificial neural networks (ANN's). These ANN's share a common characteristic, they are used to extract descriptors from images and video clips that, properly processed, will determine whether a fall has taken place.

These descriptors, which capture kinematic features associated with the fall, are inferred from datasets recorded by young volunteers or actors who simulate falls. Systems based on this concept offer excellent performances in tests which use that kind of datasets. However, given the well‐documented differences between these falls and the real ones, concerns about system performances when processing falls of elderly people are raised.

This work implements an alternative approach to the classical use of kinematic descriptors. To do it, for the first time to the best of the authors’ knowledge, the authors propose the introduction of human dynamic stability descriptors used in other fields to determine whether a fall has taken place. These descriptors approach the human body in terms of balance and stability; this way, differences between real and simulated falls become irrelevant, as all falls are a direct result of fails in the continuous effort of the body to keep balance, regardless of other considerations. The descriptors are determined by using the information provided by a neural network able to estimate the body centre of mass and the feet projections onto the ground plane, as well as the feet contact status.

The theory behind this new approach and its validity is studied in this article with very promising results, as it is able to match or over exceed the performances of previous systems using kinematic descriptors employing available data and, given the independence of this approach from the conditions of the fall, it has the potential to have a better behaviour than classic systems when facing falls of elderly people.
Analysis of the preliminary campaign for the PETALE program
Authors: Laureau Axel , Gruel Adrien , Lamirand Vincent , Ligonnet Thomas , Sardet Alix , Pautz Andreas
Published: June 2023

The PETALE program aims to provide new experimental data to constrain the stainless steel nuclear data. In this frame, a preliminary measurement campaign has been performed to characterize the neutron flux in key positions of the CROCUS reactor and to develop analysis tools. During this preliminary campaign detailed in the present paper, an efficiency ratio technique has been developed and tested to speed up HPGe measurements by a factor of 30. A second objective of the campaign concerns the propagation of nuclear data uncertainty from the core neutron cross-sections to the reaction rates in the dosimeters. Uncertainties in the core cross sections, such as the uranium cross section, are nuisance parameters that add uncertainty to the dosimeter reaction rate calculation. This component must be fully characterized with covariances to constrain the metal reflector component for Bayesian assimilation. The experimental results are compared to the calculations with different nuclear databases for the nuclear data uncertainty propagation. A good agreement is obtained with the ENDF/B-VII.1 database and a systematic underestimation of around 5–10% in the fast range is observed with the ENDF/B-VIII.0 and JEFF-3.3 databases.
Research on Architecture Strategy and Estimation Model of Digitized and Business-oriented Smart Community System
Authors: Guo Tao , Palaoag Thelma D.
Published: June 2023

The level of intelligence in the community has become an important indicator to reflect the level of urban development. This article starts with the architecture strategy of the system and builds a dynamic digital business smart community system. The goals of software product management for the three-dimensional digital community are clarified, which improves the effectiveness and reliability of system development. Based on the function points, data management system estimation model, geographic information system estimation model, APP system estimation model, and content management system estimation model are created separately. The interaction interfaces of the information management system, information publishing system, activity publishing system with the geographic information system, APP interaction interface, and content management system are unified into the data management system estimation model. By analyzing the technical and economic theory, the bottleneck problem of promoting the application of digital communities is solved, and the development cost of digital community software systems can be predicted clearly. This also facilitates the calculation of the direct economic and social benefits brought by the promotion and application of results.
Safety Assessment of Pressure Vessels Exceeding the Design Service Life of a Petrochemical Company's Rubber Plant
Authors: Zhang Lingxiang , Liu Chang , Du Chenyang , Wang Chao , Zhao Yingfang
Published: June 2023

The rubber plant of a petrochemical company has been built for a long time, some pressure vessels have exceeded the design service life or 20 years. It belongs to the pressure vessel beyond the design service life. A large number of devices and pressure vessels have entered or are about to enter the extended service stage. The detailed safety assessment of all equipment in service beyond the time limit is costly, inefficient and not targeted. Therefore, in this paper, through the screening of time-dependent damage modes. Focus on safety assessment of equipment with time-dependent damage such as corrosion, fatigue and creep. According to the screening and evaluation results, the safety assessment results and inspection management suggestions of the pressure vessel of the whole set of equipment are given. It is hoped that it can provide a reference for enterprises to manage the safety of pressure vessels beyond the design service life.
Research on the Business Model of Enterprise Energy Service Based on Digitalization
Authors: Fu Yuehong , Shi Hongming
Published: June 2023

State Grid e-commerce Co., Ltd. (hereinafter referred to as "State Grid e-commerce company") aims to realize the Internet of core business transactions, and undertakes the important mission of expanding new business areas and cultivating new profit growth points. Through in-depth study of new digital products and business models in the energy service market, expanding the business chain, enhancing the value chain, cultivating new advantages and enhancing new power, the market competitiveness and sustainable development ability of power grid enterprises will be effectively improved, which is a business innovation exploration to actively respond to the reform of power system and the strategic changes of State Grid Corporation.
Digital economy leads the integrated development of rural primary, secondary and tertiary industries
Authors: Cui Huaqing , Wang Chao
Published: June 2023

The rapid development of the digital economy has driven the digital and intelligent transformation and development of rural primary, secondary and tertiary industries, which has a revolutionary impact on the ways and paths of agricultural transformation iteration and rural industrial integration development. The integrated development of primary, secondary and tertiary industries in rural areas is a key measure to continuously promote rural revitalization. The digital economy still faces some challenges in leading the integrated development of rural industries, including high uncertainty in the macro policy environment, weak connection between the implementation and use of digital technology at the meso level and farmers, and the optimization of the interest linkage at the micro subject level. Based on the theory of industrial integration, the article attempts to analyze the empowering points of the digital economy from the perspectives of digital reconstruction of industrial factors, digital and intelligent transformation of the entire production process, and cultivation of new service models. It proposes ways to strengthen the construction of rural digital infrastructure, increase the effective supply of digital economy talents, and build a unified standard collaborative guarantee mechanism to assist in the development of rural industrial integration.
Fundamental Quantitative investment research based on Machine learning
Authors: Xu Jiao
Published: June 2023

In recent years, the status of quantitative investment in China's capital market has been improving, and fundamental quantification has emerged as a promising approach that integratesfundamental analysis and quantitative investment successfully. Hence, this kind of intelligent quantitative investment method has garnered significant attention. In this paper, eight machine learning algorithms, including Lasso regression, ridge regression, partial least squares regression, elastic network regression, decision tree, random forest, support vector machine and K-nearest neighbor method, are used to construct the stock return prediction model. The empirical results show that linear machine learning algorithm outperforms nonlinear machine learning algorithm. The annual return rate of CSI 300 index in the same term is 1.47%, while the investment strategy based on OLS model has an annualized return rate of 35.96%, and the maximum withdrawal rate is only 29.61%, showing its strong return capacity. In this paper, machine learning is introduced in the field of fundamental quantitative investment, which provides investment reference for all kinds of investors and is helpful for the country to promote quantitative investment.
Risk assessment of data asset management based on fuzzy hierarchy method and association rules
Authors: Chen Shuguo , Wu Yaomao , Fu Yue , Zhang Yihong
Published: June 2023

In the current data asset management risk assessment, the processing of assessment indicators is relatively simple, which leads to large errors in the assessment results. To this end, a data asset management risk assessment based on fuzzy hierarchy method and association rules is proposed. Identify risk factors for data asset management. Construct a risk assessment model. Quantify the model indicators based on the fuzzy hierarchy method, generate a judgment matrix and derive a comprehensive assessment vector. Assess risk levels based on association rules. Experiments show that the risk level assessment of the method has a correct rate of 100% and the assessment error of the risk score is 1.86 points, which has high application value.
How can China leapfrog the “middle-income trap” in the digital economy?
Authors: Beinan Guo , Haohan Wu
Published: June 2023

At present, China is only one step away from crossing the "middle-income trap", which has become a common concern in the industry and academia. Meanwhile, the booming digital economy based on big data, blockchain and artificial intelligence provides an important opportunity for China's economy to "overtake". This paper answers how the digital economy can help China cross the "middle-income trap" from the demand side and the supply side respectively, as well as some thoughts on the policy regulation of the digital economy by government departments in this process, and provides policy suggestions for China to use the digital economy to cross the "middle-income trap".
Study on Digitization Level Evaluation of local Chronicles in Sichuan Province
Authors: Yang Fuyi , Li Yuhan , Huang Yi , Li Yulu
Published: June 2023

Local chronicles, as documents to record the history, culture, politics and other aspects of all parts of our country, have always been the cultural heritage of the Chinese nation, and have guiding significance for our country to continuously carry out the in-depth development of all parts. With the continuous advancement of the information age, the information and digital development of local chronicles has become an inevitable trend. However, the digitalization level of local chronicles across the country is uneven, and there is no set of quantitative standards to measure the degree of digitization development of local chronicles, which makes the process of digitization of local chronicles slow. Based on the national requirements for the digitized process of local chronicles since the 14th Five-Year Plan, this paper establishes an index system for the digitalization level evaluation of local chronicles in Sichuan province. According to the index evaluation system, the fuzzy comprehensive analysis method is used to comprehensively evaluate the digitalization level of Sichuan local chronicles. Finally, according to the evaluation results, this paper puts forward some practical and developmental suggestions.
Design of LEGO Parts Automatic Sorting Scheme
Authors: Wu Xitong
Published: June 2023

With the continuous development of the economy and the growing differentiation of young people's interests, people are willing to spend a lot of energy and money on their favorite games to get a better experience. Nowadays, Lego has entered more and more families. However, due to too many types and quantities of Lego parts, people usually do not know how to effectively organize these parts after each game. Most people choose to throw all these parts into the box, but this will make the parts very confused and seriously affect the game experience when playing next time. To solve this problem, we try to design and develop a Lego classification device to automatically classify different types of Lego parts. We try to use a variety of technical solutions for comparison, from multiple dimensions such as cost calculation, technical implementation details and risk management to comprehensively compare, and finally select the best design scheme.
Vulnerability Evaluation of Port Logistics System Under Public Health Emergencies
Authors: Liu Cuilian , Jiang Hao , Qin Kun
Published: June 2023

It is the goal that evaluating scientifically port logistics system vulnerability level under public health emergencies, exploring the influencing factors of brittleness and improving the production operation and management efficiency of port logistics system. According to the production practice of port logistics system and vulnerability theory, a vulnerability evaluation index system of port logistics system under public health emergencies is established in five aspects, including external risk disturbance, human resource management level, infrastructure level, operation and management level, and intelligence level. The combinatorial weights are obtained by combinatorial empowerment method of game theory, and it is used to process data that evidence theory improved by conflict correction process and mass function with normal cloud model. The vulnerability of Dalian port logistics system is analyzed empirically, and the result is better effectiveness.
Research on Construction Project Cost Prediction Model Based on Recurrent Neural Network
Authors: Wang Yanqin , Ning Xu , Zhen Dong , Yong Wang , Zhang Hongshan
Published: June 2023

At present, the conventional construction project cost prediction method mainly constructs the cost prediction model by quantifying the engineering information, which leads to poor prediction effect due to the lack of construction of cost prediction index system. In this regard, the research of construction cost prediction model based on recurrent neural network is proposed. By classifying and integrating the construction project cost concepts, constructing the prediction index system, combining with the recurrent neural network algorithm, constructing the excitation function and calculating the initialization threshold, and finally constructing the prediction model. In the experiment, the proposed method is verified for the prediction accuracy. After the experiments, it can be proved that when the proposed model is used to predict the engineering cost, the root mean square error of the model output is small and has a more ideal prediction accuracy.
Research on Green Economic Efficiency Measurement and Influencing Factors in Chengdu-Chongqing Twin-City Economic Circle--Analysis Based on Super-Efficient SBM and Tobit Model
Authors: Tan Liqin , Liao Xueqin , Rao Yan
Published: June 2023

Based on the panel data of 16 cities in the Chengdu-Chongqing region from 2005 to 2020, this paper measures the green economic efficiency of each city in the Chengdu-Chongqing region using the super-efficient SBM model that takes into account non-desired outputs, and analyses the influencing factors of green economic efficiency in the Chengdu-Chongqing region using the Tobit model. The results show that the overall green economic efficiency of the Chengdu-Chongqing region is at a moderate level, but shows a fluctuating upward trend with the change of time. From the perspective of the influencing factors: the level of economic development, the level of science and technology, and the endowment structure have a significant positive contribution to the green economic efficiency of the Chengdu-Chongqing region; the environmental regulation does not have a significant contribution to the green economic efficiency due to the differences between cities; the industrial structure dominated by the secondary industry and the urbanisation rate have a significant negative inhibiting effect.
Research on the Energy-saving and Emission Reduction Effect of Green Finance Development--Based on the perspective of energy efficiency and energy consumption structure
Authors: Wang Renxaing , Ji Huiwen
Published: June 2023

Based on the panel data of 30 provinces from 2010 to 2020, this paper explores the energy-saving and emission reduction effects and action paths of green finance development from the perspective of energy efficiency and energy consumption structure . The results show that green finance has a significant effect on energy-saving and emission reduction. Green finance not only effectively promotes the improvement of energy efficiency, but also promotes the optimization and upgrading of energy consumption structure; Further analysis shows that there are regional differences in the energy efficiency and energy consumption structure of green finance in terms of energy-saving and emission reduction. The potential of green finance in energysaving and emission reduction in the central and western regions is significantly greater than that in the eastern regions; In addition, green finance also has a heterogeneous impact on energy efficiency and energy consumption structure at different quantile levels. At the level of energy efficiency, the dividend period of green finance's energy-saving and emission reduction effect is relatively short, and the potential of green finance's energy-saving and emission reduction effect in adjusting the energy consumption structure is huge. The mechanism analysis found that green technology innovation and industrial structure optimization played a partial intermediary role in the impact of green finance on energy-saving and emission reduction,and green finance has a greater effect on energy conservation and emission reduction at the level of energy consumption structure through industrial structure optimization.
The Analyze of Enterprise Digital Transformation on Management Mode
Authors: Wen Jingyao
Published: June 2023

Covid-19 has stay around us for almost 3 years. People need to stick with their work or their life, meanwhile, with the development of technology, many company think about how to manage their company online, so that we have “ digital management” for almost 3 years. I believe that there are some of company already used it before Covid-19, but in fact, that won’t work long time without some special situation. Under this position, employer spend increasingly money on their digital management, there are positive effect and negative effect. I did search the satisfaction from employers and employees. In this research, I will doing something that is about digital management of use rate in China.
Exploration of the Path of Fine Management to Promote High-Quality Development of Enterprises
Authors: Zhang Ziheng
Published: June 2023

In the current environment of increasingly fierce competition in international and domestic markets, opportunities and challenges coexist in the process of enterprise development. In order to stand out from the fierce competition and achieve long-term development goals, enterprises need to innovate the existing management mode. Lean management, as an advanced management model verified by many enterprises, has been affirmed and paid more attention to by more enterprises. Therefore, with this theme, this paper firstly elaborates on the background of the application of lean management, then specifies the meaning and application of lean management, and finally, proposes how to use lean management strategies to promote the high-quality development of enterprises from various aspects. We hope to inspire and draw reference from more enterprise managers to improve enterprise management and achieve high-quality development of enterprises.
Research on the Influencing Factors of the Return and Exchange Rate of E-commerce Live Broadcast
Authors: Huang Jiajing
Published: June 2023

With the rapid popularization of the Internet, live broadcast has become an increasingly popular e-commerce promotion and marketing strategy. Article 25 of the Consumer Protection Law stipulates that live broadcast with goods as a new online shopping method provides a seven-day service of goods return and exchange without reason. Therefore, it is of great importance to study the return and exchange service of live broadcast e-commerce. This paper analyzes the impact of live broadcast e-commerce return service on sales data from the perspective of merchants and consumers, and helps e-commerce with high return rate to find the reason.
Executive compensation stickiness and oil and gas resource enterprise value
Authors: Yang Hong-bo , Li Lei
Published: June 2023

Taking listed petroleum and petrochemical companies from 2013 to 2021 as samples, this paper empirically examines the impact of stickiness of executive compensation on the value of petroleum and petrochemical enterprises and its influence path. The results show that the stickiness of executive compensation has a positive effect on the value of petroleum and petrochemical enterprises. The stickiness of executive compensation helps to improve the resource utilization rate of petroleum and petrochemical enterprises. Resource utilization plays a partial mediating role on the main effect, and there is an influence path of "stickiness of executive compensation - resource utilization - enterprise value". Equity incentive plays a significant moderating role. The gradual improvement of equity incentive contract will weaken the positive promoting effect of stickiness of executive compensation on the value improvement of petroleum and petrochemical enterprises.
Hybrid Long Short-Term Memory prediction model improved by particle swarm optimization with sine and cosine factors
Authors: Pei Wanyue , Yang Yanfei
Published: June 2023

The Long Short-Term Memory network of deep learning neural network is widely used to predict stock price in financial field. In order to optimize the accuracy of stock price prediction by LSTM network, this paper firstly uses principal component analysis method to extract various influencing indexes of stock. Then, use Circle mapping method to select the initial value more evenly, use sine and cosine factors to improve factors of particle swarm optimization algorithm, so as to find the optimal parameters of LSTM model more effectively. Finally, the optimization results of IPSO algorithm are substituted into the LSTM model for the regression prediction with the principal components. Through empirical analysis and comparative test, the results show that the improved particle swarm optimization algorithm proposed in this paper has better optimization effect, is not prone to local optimal problems, and the prediction model based on this method has higher prediction accuracy.
Research on Credit Risk Assessment Model of Enterprises’ Unpaid Electricity Charge Based on Machine Learning Method
Authors: Hu Jiankun , Wang Haiji , Lu Xueying
Published: June 2023

Based on machine learning methods and employing credit big data, this paper explores the idea of constructing a credit risk assessment model for enterprises’ unpaid electricity charges, proposes a system of indicators affecting the risk of unpaid electricity charges, and elaborates on the path of screening key indicators. In this regard, a method for calculating the credit risk score of enterprises’ unpaid electricity charges is given, and suggestions are provided for risk response strategies.
Melanotic Neuroectodermal Tumor of Infancy: A Case Report with Review of Literature
Authors: Patil Vasundhara , Nazneen Jeba , Rai Pranjal , Agarwal Ujjwal , Mahajan Abhishek
Published: June 2023

Melanotic neuroectodermal tumors of infancy are rare pigmented neuroectodermal locally aggressive tumors that usually occur within 1 year of life. Head and neck areas are frequently involved with maxilla being the most common site. Expansile growth and high recurrence rate are characteristics of this cancer. Though rare, radiologists and clinicians must be aware and should consider this entity when diagnosing pediatric head and neck masses. Computed tomography can be used for diagnosing and looking at the extent of the disease and predicting the operative outcome. Surgery with wide resection margin is the mainstay of treatment for these masses. Surgery followed by adjuvant chemotherapy and radiation is reserved for aggressive malignant lesions. Since it has a high recurrence rate, follow-up is done with imaging and clinical examination. Early detection and treatment of recurrence have a favorable outcome for the patients.
ChatGPT—Preliminary Overview with Implications for Medicine and Oncology
Authors: Parikh Purvish M. , Shah Dinesh M. , Parikh Urvish G. , Venniyoor Ajit , Babu Govind , Garg Apurva , Malhotra Hemant
Published: June 2023

This review provides an overview about the OpenAI system's natural language chat bot called ChatGPT. It focuses on the preliminary assessment of its unique features, advantages, limitations, role in manuscript writing, value in oncology, and future implications.
AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks
Authors: Shah Vivswan , Youngblood Nathan
Published: June 2023

In this paper, we present AnalogVNN, a simulation framework built on PyTorch that can simulate the effects of optoelectronic noise, limited precision, and signal normalization present in photonic neural network accelerators. We use this framework to train and optimize linear and convolutional neural networks with up to nine layers and ∼1.7 × 106 parameters, while gaining insights into how normalization, activation function, reduced precision, and noise influence accuracy in analog photonic neural networks. By following the same layer structure design present in PyTorch, the AnalogVNN framework allows users to convert most digital neural network models to their analog counterparts with just a few lines of code, taking full advantage of the open-source optimization, deep learning, and GPU acceleration libraries available through PyTorch.
Shannon entropy for hydrogen atom in Debye and quantum plasma environment
Authors: Verma Nupur , Joshi Rachna
Published: June 2023

The plasma screening effect on Shannon entropy values is studied for atomic states of hydrogen under the more general exponential cosine screened Coulomb (MGECSC) potential, which can be used to model Debye and quantum plasmas. The wavefunctions used in the calculation of Shannon entropy are obtained by solving the Schrödinger equation employing the efficient Numerov technique. Shannon entropy is calculated for hydrogen atom quantum levels using various sets of screening parameters to account for the four different potential forms present in the MGECSC potential. The electron density distributions are considerably altered due to the plasma shielding influence on the embedded hydrogen atoms, and this effect is measured by the shift in Shannon entropy. A greater screening influence on entropy is observed in quantum plasma modeled by the MGECSC potential than that in Debye plasma due to the significant combined effects of screening parameters. Excellent convergence is obtained on comparing our results for plasma-free hydrogen atom with the currently available literature. This study is the first to examine the effects of shielding on Shannon entropy of hydrogen atoms in plasmas modeled by the MGECSC potential. These findings will be important for theoretical and experimental research in the disciplines of atomic physics and plasma diagnostics.
Compressive sensing-based tomography for Absolute X-ray UltraViolet (AXUV) diagnostics
Authors: Yang Menghua , Cheng Zhengbo , Wang Shouzhi , Wang Binbin , Tan Yi , Gao Zhe
Published: June 2023

Absolute x-ray ultraviolet diagnostics ensures 2D coverage of the radiation emission region that enables tomographic reconstruction. However, retrieving the local emissivity via tomography remains a challenge due to its ill-posed nature. Tikhonov regularization with smoothness operation generally performs well but tends to over-smooth regions with steep gradients and local structure in the radiation profile and may introduce artifacts. In this paper, a tomography method based on compressive sensing theory with Tikhonov regularization terms is developed. Experimental results on multiple phantom sets show that the proposed method improves the reconstruction accuracy and quality in regions with steep gradients compared with the Tikhonov regularization method and suppresses the unphysical negative emissivity. The analysis of reconstruction uncertainty shows that the dictionary learning process provides more accurate prior information about steep gradients to improve the quality of reconstructed images, and compressive sensing has the denoising capability to reduce the impact of noise. Finally, the method is validated by data from the Sino-UNIted Spherical Tokamak, showing fewer artifacts and more reliable reconstruction images than the earlier method.
Electrostatic upper-hybrid mode instability driven by a ring electron distribution
Authors: Yoon Peter H. , Omura Yoshiharu
Published: June 2023

Quasi electrostatic fluctuations in the upper-hybrid frequency range are commonly detected in the planetary magnetospheric environment. The origin of such phenomena may relate to the instability driven by a loss-cone feature associated with the electrons populating the dipole-like magnetic field. The present paper carries out a one-dimensional electrostatic particle-in-cell simulation accompanied by a reduced quasilinear kinetic theoretical analysis to investigate the dynamics of the upper-hybrid mode instability driven by an initial ring electron distribution function, which is a form of loss-cone distribution. A favorable comparison is found between the two approaches, which shows that the reduced quasilinear theory, which is grounded in the concept of a model of the particle distribution function that is assumed to maintain a fixed mathematical form except that the macroscopic parameters that define the distribution are allowed to evolve in time, can be an effective tool in the study of plasma instabilities, especially if it is guided by and validated against the more rigorous simulation result.
Calibration and Sensitivity Analysis of Macro and Meso Parameters of Discrete Element Model for Coal Measure Soil
Authors: Zhang Hong , Zheng Mingxin , Rong Yao , Cui Meng , Cheng Kun
Published: June 2023

The orthogonal test sequence of the meso parameters of the discrete element model was designed by using the orthogonal test method. The calculation method of directly determining the meso parameters from the macro mechanical parameters was established by using the test simulation calculation results and the multi factor nonlinear joint inversion method. The proposed method was applied to the discrete element numerical simulation of triaxial test of coal measure soil. The results show that the numerical simulation results are in good agreement with the stress-strain curves of the triaxial test of coal bearing soil. Through error analysis, it is found that the maximum error of the partial stress peak is 5.4%, the error of the cohesion is 2%, the error of the internal friction angle is 7%, and the error is all within 10%. It verifies that the method for rapid determination of the meso parameters proposed in this paper is feasible, and provides a new idea for the calibration of the meso parameters in the discrete element numerical simulation method.
Design of stress monitoring system for planetary gear shaft
Authors: Gao Chengang , Ma Xiaoping , Yue Yanjiong , Chen Kaiwen , Wang Dacheng , Song Menglin , Cui Hongbin
Published: June 2023

A remote sensing gear shaft stress monitoring system is studied to deal with the stress balance of transmission gear, which realizes the real-time dynamic monitoring of the planetary gear shaft stress. The design of the whole system structure, the installation position of the basic system and the special working environment of the gear are carried out; the circuit of each function unit is designed, which is based on the overall index requirement and installation space limitation; the software program design is carried out on the basis of the hardware circuit; The main components of the system and the principle of dynamic monitoring system are described; each functional unit and the whole of the system are tested and analyzed in detail. The operation results show that the design is reliable, the actual functions of each unit can meet the design index, and has a certain contribution in the field of gear shaft stress monitoring.
Fixed points of parking functions
Authors: McCammond Jon , Thomas Hugh , Williams Nathan
Published: June 2023

We define an action of words in

[
m

]
n

[m]^n

on

R

m

{\mathbb {R}}^m

to give a new characterization of rational parking functions—they are exactly those words whose action has a fixed point. We use this viewpoint to give a simple definition of Gorsky, Mazin, and Vazirani’s zeta map on rational parking functions when

m
m

and

n
n

are coprime [Trans. Amer. Math. Soc. 368 (2016), pp. 8403–8445], and prove that this zeta map is invertible. A specialization recovers Loehr and Warrington’s sweep map on rational Dyck paths (see D. Armstrong, N. A. Loehr, and G. S. Warrington [Adv. Math. 284 (2015), pp. 159–185; E. Gorsky, M. Mazin, and M. Vazirani [Electron. J. Combin. 24 (2017), p. 29; H. Thomas and N. Williams, Selecta Math. (N.S.) 24 (2018), pp. 2003–2034]).
Application of waist inequality to entropy and mean dimension
Authors: Shi Ruxi , Tsukamoto Masaki
Published: June 2023

Waist inequality is a fundamental inequality in geometry and topology. We apply it to the study of entropy and mean dimension of dynamical systems. We consider equivariant continuous maps

π
:
(
X
,
T
)
→
(
Y
,
S
)

\pi : (X, T) \to (Y, S)

between dynamical systems and assume that the mean dimension of the domain

(
X
,
T
)

(X, T)

is larger than the mean dimension of the target

(
Y
,
S
)

(Y, S)

. We exhibit several situations for which the maps

π
\pi

necessarily have positive conditional metric mean dimension. This study has interesting consequences to the theory of topological conditional entropy. In particular it sheds new light on a celebrated result of Lindenstrauss and Weiss [Israel J. Math. 115 (2000), pp. 1–24] about minimal dynamical systems non-embeddable in

[
0
,
1

]

Z

[0,1]^{\mathbb {Z}}

.