General laws of funding for scientific citations:how citations change in funded and unfunded research between basic and applied sciences

Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.

Special Issue:Questions&Data for Better Science and Innovation Call for submissions

Editors Yang Wang,Xi'an Jiaotong University Dongbo Shi,Shanghai Jiaotong University Ye Sun,University College London Zhesi Shen,National Science Library,CAS Topic of the Special Issue What are the top questions towards better science and innovation and the required data to answer these questions?

Enhancing Multicriteria-Based Recommendations by Alleviating Scalability and Sparsity Issues Using Collaborative Denoising Autoencoder

A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.

Early identification of scientific breakthroughs through outlier analysis based on research entities

Purpose:To address the“anomalies”that occur when scientific breakthroughs emerge,this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers,aiming to achieve early identification of scientific breakthroughs in papers.Design/methodology/approach:This study utilizes semantic technology to extract research entities from the titles and abstracts of papers to represent each paper’s research content.Outlier detection methods are then employed to measure and analyze the anomalies in breakthrough papers during their early stages.The development and evolution process are traced using literature time tags.Finally,a case study is conducted using the key publications of the 2021 Nobel Prize laureates in Physiology or Medicine.Findings:Through manual analysis of all identified outlier papers,the effectiveness of the proposed method for early identifying potential scientific breakthroughs is verified.Research limitations:The study’s applicability has only been empirically tested in the biomedical field.More data from various fields are needed to validate the robustness and generalizability of the method.Practical implications:This study provides a valuable supplement to current methods for early identification of scientific breakthroughs,effectively supporting technological intelligence decision-making and services.Originality/value:The study introduces a novel approach to early identification of scientific breakthroughs by leveraging outlier analysis of research entities,offering a more sensitive,precise,and fine-grained alternative method compared to traditional citation-based evaluations,which enhances the ability to identify nascent breakthrough innovations.

Detecting LLM-assisted writing in scientific communication:Are we there yet?

Large Language Models(LLMs),exemplified by ChatGPT,have significantly reshaped text generation,particularly in the realm of writing assistance.While ethical considerations underscore the importance of transparently acknowledging LLM use,especially in scientific communication,genuine acknowledgment remains infrequent.A potential avenue to encourage accurate acknowledging of LLM-assisted writing involves employing automated detectors.Our evaluation of four cutting-edge LLM-generated text detectors reveals their suboptimal performance compared to a simple ad-hoc detector designed to identify abrupt writing style changes around the time of LLM proliferation.We contend that the development of specialized detectors exclusively dedicated to LLM-assisted writing detection is necessary.Such detectors could play a crucial role in fostering more authentic recognition of LLM involvement in scientific communication,addressing the current challenges in acknowledgment practices.

SciCN:A Scientific Dataset for Chinese Named Entity Recognition

Named entity recognition(NER)is a fundamental task of information extraction(IE),and it has attracted considerable research attention in recent years.The abundant annotated English NER datasets have significantly promoted the NER research in the English field.By contrast,much fewer efforts are made to the Chinese NER research,especially in the scientific domain,due to the scarcity of Chinese NER datasets.To alleviate this problem,we present aChinese scientificNER dataset–SciCN,which contains entity annotations of titles and abstracts derived from 3,500 scientific papers.We manually annotate a total of 62,059 entities,and these entities are classified into six types.Compared to English scientific NER datasets,SciCN has a larger scale and is more diverse,for it not only contains more paper abstracts but these abstracts are derived from more research fields.To investigate the properties of SciCN and provide baselines for future research,we adapt a number of previous state-of-theart Chinese NER models to evaluate SciCN.Experimental results show that SciCN is more challenging than other Chinese NER datasets.In addition,previous studies have proven the effectiveness of using lexicons to enhance Chinese NER models.Motivated by this fact,we provide a scientific domain-specific lexicon.Validation results demonstrate that our lexicon delivers better performance gains than lexicons of other domains.We hope that the SciCN dataset and the lexicon will enable us to benchmark the NER task regarding the Chinese scientific domain and make progress for future research.The dataset and lexicon are available at:https://github.com/yangjingla/SciCN.git.

A Brief Overview of the Development and Significance of Modern Scientific Medicine in China:Take Chinese Academy of Medical Science and Peking Union Medical College as an Example

Since the early 20th century,China has gradually established a clinical,educational,and research system centered around modern scientific medicine,which has now become the dominant force in China's medical and health system and services,with the construction and development of the Chinese Academy of Medical Sciences and Peking Union Medical College as the most prominent symbol.The scientific medicine in the new era requires close cooperation across multiple disciplines and fields to build a high-quality and efficient medical and health service system.It also involves combining the excellent traditional Chinese culture with Western medicine to explore a unique path of modern scientific medicine with Chinese characteristics.

Mindfulness and mindful parenting:Strategies for preschoolers with behavioral issues

The behavior issues of preschoolers are closely related to their parents'parenting styles.This editorial discusses the value and strategies for solving behavior issues in preschoolers from the perspectives of mindfulness and mindful parenting.We expect that upcoming studies will place greater emphasis on the behavioral concerns of preschoolers and the parenting practices that shape them,particularly focusing on proactive interventions for preschoolers'behavioral issues.

Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

Cultivation Path of Nursing Undergraduates’Scientific Research and Innovation Ability

Objective: The cultivation of the innovation ability and scientific research is one of the nursing learning objectives for undergraduate students. To explore the method and effect of training system of scientific research innovation ability of nursing undergraduates based on “3332”. Methods: Three course learning modules are constructed: stage-based course learning module, systematic project practice training module and comprehensive practice training module. A practical training platform for scientific research innovation projects is built, and undergraduate scientific research innovation ability training is carried out from both in-class and out-of-class lines. Results: Since 2017, the students have obtained 7 national innovation and entrepreneurship training programs, 52 university-level undergraduate scientific research projects, published more than 10 academic papers, and obtained 2 patent authorization. Conclusions: The training system of scientific research innovation ability of nursing undergraduates based on “3332” is conducive to the development of scientific research innovation ability of nursing students, and to cultivate nursing talents who can adapt to the development of the new era and have better post competence.

Identifying influencing factors and characterizing key issues in urban sustainable development capacity through machine learning

In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda(IDZSDAs),combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity(USDC).After obtaining USDC assessment results through the assessment system,an approach combining Least Absolute Shrinkage and Selection Operator(LASSO)regression and Random Forest(RF)based on machine learning is proposed for identifying influencing factors and characterizing key issues.Combining Coupling Coordination Degree(CCD)analysis,the study further summarizes the systemic patterns and future directions of urban sustainable development.A case study on the IDZSDAs from 2015 to 2022 reveals that:(1)the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process;(2)the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities;and(3)the machine learning-based combined recognition method is scalable and dynamic.It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.

The Four Dimensional Connotation Definition of Scientific Understanding of the Ocean and Human Practical Achievements

By analyzing the sustainable development process of strengthening marine environmental protection and global reporting and assessment of marine environmental conditions since the Human Environment Conference, this paper summarizes the scientific connotation of “scientific understanding of the ocean” reflected in the United Nations Global Marine Environmental Assessment Report, proposes the etymological definition and specific coverage, representative global and regional practical experience of scientific understanding of the ocean, and further analyzes and defines the human activities and cognitive evolution process of “scientific understanding of the ocean”. It marks the leap in human cognition in four dimensions: observation and evaluation, intervention and regulation, disciplinary knowledge system, and supporting guarantee system. It condenses the connotation definitions and human practical achievements of each dimension, and puts forward countermeasures and suggestions to strengthen marine environmental protection and sustainable development.

Scientific Data Intellectual Property Research by Literature Statistics

The main obstacle to the open sharing of scientific data is the lack of a legal protection system for intellectual property.This article analyzes the progress of research papers on intellectual property in scientific data in China through literature search and statistics.Currently,research subjects are unbalanced,research content is uneven,research methods are intellectual single,and research depth is insufficient.It is recommended that different stakeholders engage in deep cross disciplinary cooperation,further improve China’s legal and policy protection system for scientific data intellectual property,and promote the open sharing of scientific data.

Performance Evaluation of Low-Cost Dual-Frequency GNSS Receivers for Precise Positioning in Senegal: Issues and Challenges

The development of this technology has favored the advances noted in recent years in the field of precise positioning. It has also paved the way for a wide range of research into the evaluation of their performance and reliability, their potential use in different fields, the improvement of performance and combined systems, etc. Single-frequency GNSS receivers, which for a long time remained the only category of low-cost GNSS receivers, often limited by their level of accuracy (metric) mainly due to their single-frequency nature, have been joined in the last decade by dual-frequency GNSS receivers developed by certain manufacturers of positioning equipment. These receivers now offer possible alternatives to the relatively expensive conventional (topographic quality) or geodetic receivers and. In this study, the performance of these low-cost dual-frequency receivers was evaluated in static and real-time kinematic GNSS positioning modes. Static positioning was carried out on three points with sessions of 2 h and 4 h over three days with antenna swapping (CHC i50, Leica GS14 and Emlid Reach RS2+). Real-time observations were carried out on eleven (11) points in open, poorly open and not at all open environments, in order to assess not only performance but also receiver sensitivity in environments with a high risk of multipath. The results obtained showed an average agreement of 2 cm in planimetry between the low-cost Emlid RS2+ receiver and the Leica GS14 and CHC i50 receivers. The differences in altimetry are nevertheless greater (sometimes up to decimetres for certain points). Real-time positioning results provided an average convergence of around 1 cm on the E, N and H components with the results from the low-cost Emlid Reach RS2+ and Ublox ZED-F9P receivers and the CHC i50 receiver. Analysis of the results obtained has enabled us to highlight the various issues and challenges associated with this new generation of GNSS receivers, with a view to enhancing their appropriation and optimal integration in the professional and research worlds.

Application of Academic Salons in Cultivating the Scientific Research Skills of First-Year Nursing Master’s Students

Objective:To explore the application effect of academic salons on developing the scientific research skills of first-year nursing master’s students.Methods:According to Wallas’four-stage model of the creative process,from November 2022 to February 2023,66 first-year nursing master’s students from the School of Nursing at Zhejiang Chinese Medical University were selected using a convenient sampling method to participate in a multidisciplinary academic salon consisting of a total of 8 sessions held once every two weeks.Before the first and after the last academic salon,postgraduate research skills evaluation questionnaires and perception of research skills acquisition questionnaires were used to assess first-year nursing master’s students.A semi-structured interview was conducted with nine students after the final academic salon.Results:The total scores for scientific research skills and sense of achievement among first-year nursing master’s students after the academic salon were higher than those before the salon,and the difference was statistically significant.The interview results showed that the“salon theme,”“tutor comments,”and“sharer output”are the focus of the first-year nursing master’s students in the academic salon.Conclusions:Academic salons can enhance postgraduate students’scientific research skills and foster a greater appreciation for scientific research.We can enhance academic salons by carefully choosing relevant themes,inviting knowledgeable presenters and expert tutors to provide feedback,and prioritizing equality and effective communication.

Comparative Study on the Policy of Multiplicity Issues in Clinical Trials at Home and Abroad

Objective To study the content of China’s guiding principles on multiplicity issues in clinical trials,and to provide reference for the revision of China’s relevant guiding principles.Methods Based on ICH E9,the similarities and differences of the guiding principles of US Food and Drug Administration(FDA),European Medicines Agency(EMA),and National Medical Products Administration(NMPA)on the multiplicity issues in clinical trials were compared one by one.Results and Conclusion In general,NMPA guidelines are based on ICH E9,but in detail,the guidelines of FDA and EMA focus differently on the multiplicity issues.Therefore,NMPA guidelines need to be detailed and comprehensive.NMPA guidelines can be refined by referring to foreign guidelines to improve the practical guiding significance for clinical research and promote the level of domestic clinical trials in line with international standards.

Three Dimensions of Cultivating New Generations: Value Implication, Scientific Connotation, and Cultivation Path

The new generation of the times is the latest requirement for young people in the new era,and it is the latest training goal for young people put forward by the Party and the country in the face of the second centennial goal.At the 19th National Congress,it was put forward by the country that the concept of“new generation of the times”for the first time,indicating the training direction and theoretical guidance for the new generation of the times.The new age requires young people to have firm ideals and beliefs,excellent skills,and a great spirit of responsibility.The proposition of cultivating a new generation of the times is a deep exploration and summary of Marx’s theory of“all-round human development,”Lenin’s youth view and the education view of excellent traditional Chinese culture,and the proposition needs to strengthen the leadership of the Party,give play to the leading role of socialist core values,and the youth themselves should actively act to realize the transformation of theoretical and practical results.

The States-of-arts and Key Scientific Issues on Durability Research of Concrete Structures

Concrete has traditionally been regarded as a durable material requiring little or no maintenance. However, over the past several decades, a number of durability related problems have emerged and stimulated research into the factors relating to concrete durability globally. The challenge now facing practicing engineers is how to design and build structures that not only satisfy the specified structural requirements, but also achieve the performance levels required from a durability standpoint. Research works on concrete structural durability have been widely reported in the literature over the last several decades. In this paper, reviews of four stages of research work on durability, i e, environments, materials, components, and structures, were presented. Afterwards, the key scientific issues in this field were also pointed out.

Six statistical issues in scientific writing that might lead to rejection of a manuscript

Communication plays an important role in advancing scientific fields and disciplines,defining what knowledge is made accessible to the public,and guiding policymaking and regulation of public authorities for the benefit of the environment and society.Hence,what is finally published is of great importance for scientific advancement,social development,environmental and public health,and economic agendas.In recognition of these,the goal of a researcher is to communicate research findings to the scientific community and ultimately,to the public.However,this may often be challenging due to competition for publication space,although to a lesser extent nowadays that online-only publications have expanded.This editorial introduces six statistics-related issues in scientific writing that you should be aware of.These issues can lead to desk rejection or rejection following a peer review,but even if papers containing such issues are published,they may prevent cumulative science,undermine scientific advancement,mislead the public,and result in incorrect or weak policies and regulations.Therefore,addressing these issues from the early research stages can facilitate scientific advancement and prevent rejection of your paper.

U.Taxonstand:An R package for standardizing scientific names of plants and animals

The scientific names of organisms are key identifiers of plants and animals.Correctly treating scientific names is a prerequisite for biodiversity research and documentation.Here,we present an R package,’U.Taxonstand’,which can standardize and harmonize scientific names in plant and animal species lists at a fast speed and at a high rate of matching success.Unlike most of other similar R packages each of which works with only one taxonomic database,U.Taxonstand can work with all taxonomic databases,as long as they are properly formatted.Multiple databases for plants and animals that can be directly used by U.Taxonstand,which include bryophytes,vascular plants,amphibians,birds,fishes,mammals,and reptiles,are available online.U.Taxonstand can be a very useful tool for botanists,zoologists,ecologists and biogeographers to standardize and harmonize scientific names of organisms.