Scientific Impact Research Articles

A Qualitative Study on the Relationship between Faculty Mobility and Scientific Impact: Toward the Sustainable Development of Higher Education

Faculty mobility is one of the most important research issues in the field of higher education. Reasonable faculty mobility can actively promote the fair, coordinated, balanced, healthy, and sustainable development of higher education. Scientific impact is the best proof of faculty members’ research abilities and is often represented by the quality of their articles. In particular, the gradual increase in citations of high-quality papers is undoubtedly an important reflection of healthy development in the academic field. This paper aims to explore the influence of faculty mobility on scientific impact, while comparative analysis is used to investigate whether there are disciplinary differences in the relationship between faculty mobility and scientific impact. Four major disciplines—sociology, mathematics, mechanical engineering, and philosophy—are selected as the scope of this study. Articles in these four major disciplines from 2000 to 2020 are obtained from the Web of Science, and Spearman’s rank correlation coefficient and the Wilcoxon signed-rank test are used to analyze the collected data. The results indicate the following: (1) faculty mobility has increased, with differences across disciplines; (2) mobility leads to a decrease in the number of citations, which decreases significantly with increased mobility frequency; and (3) the impact of mobility has disciplinary differences, with a relatively obvious decrease in mechanical engineering.

Hand-in-glove Effect of Piperine in Anti-cancer Formulations

Background: Piperine, an active constituent isolated from Piper nigrum, Piper chaba, Piper sarmentosum, Piper guineense and Piper longum which is used to cure a variety of ailments related to lung, stomach, colon, skin etc. like Alzheimer’s, Parkinson’s disease, ulcerative colitis, cancer, arthritis, inflammatory bowel diseases, diabetes etc. Objective: The objective of the review is to study the synergistic effect of piperine specially in cancer. Methods: Patents and current literature mainly emphasizing the synergistic effect of piperine along with other drugs, especially anticancer drugs was reviewed keeping in mind the scientific novelty and impact. Results: Several synergistic combinations of piperine were explored which can be beneficial for the pharmaceutical industry. Conclusion: This review will assist the researchers in the preparation of novel formulations with improved efficacy cutting the cost of developing new drug molecules.

Bibliometric Mapping of the Scientific Production of Lasers in Endodontics: Collaborative Networks, Impact, and Trends

Abstract Aim: The objective of this study is to perform a bibliometric mapping of the scientific production of lasers in endodontics using collaborative networks, impact, and trends. Materials and Methods: This retrospective and descriptive study used a bibliometric design to analyze laser use in endodontics in Scopus from 2018 to 2024. In total, 877 documents were identified using key terms and MeSH. Bibliometric indicators were used to explore scientific activity and impact, and VOSviewer was used for data analysis. Results: It was found that the year with the highest number of publications was 2023, with 166, and the quartiles with the highest productivity were Q1 (40.3%) and Q2 (31.1%). Among the top 5 countries with the highest publications production, Brazil led the group with 125, followed by India (111). Among the institutions with the highest production, the Universidade de São Paulo tops the list with 51 research papers, closely followed by the Tehran University of Medical Sciences with 32 and the Universidade Estadual Paulista Júlio de Mesquita Filho with 30. Among the most outstanding authors, we have Chiniforush Nasim, who has 20 papers; however, Duarte Marco has an h-index of 48, and Sivieri-Araújo Gustavo has the highest number of citations. Conclusion: This bibliometric mapping reaffirmed the vision and trends of lasers in endodontics, with 2023 being the most relevant in terms of scientific production and, among the countries with the highest number of publications, Brazil stood out.

MXenes: Structure, properties, and photothermal applications

The ever-growing interest in MXenes has been driven by their unique electrical, thermal, mechanical, and optical properties. Due to the presence of diverse surface ligands and defect sites, MXenes exhibit desirable and highly tunable optical response in the solar spectrum. In addition, they have also been found to be effective shields for electromagnetic interference thanks to their selective electromagnetic wave absorption capability. These features collectively provide MXenes with promising potentials for photothermal conversion applications. However, the underlying scientific mechanisms, pathways, and potential impact of photothermal conversion by MXenes remain poorly categorized and understood. In this review, the electronic, optical, and plasmonic properties and potential photothermal mechanism of MXene materials are systematically summarized. Current advances in various photothermal applications as well as challenges and opportunities in relevant fields are also presented. This review provides comprehensive understandings on the fundamental properties as well as a guidance for in-depth investigation of the photothermal conversion mechanism.

Indonesia’s Confidence Crisis: A Bibliometrics Analysis

The low self-confidence of students in Indonesia has an impact on many aspects. In education, students often plagiarize their friends' answers to get good grades. Apart from that, cases of bullying, body shaming, and even suicide are caused by students' low self-confidence. This article aims to bibliometrically examine research trends on self-confidence in Indonesia. This article uses bibliometric analysis to conclude the position of the self-confidence crisis on the research map in Indonesia. With the help of Publish or Perish software from Harzing and VOSviewer, 1,000 articles were obtained. These articles were then analyzed based on scientific impact categories from Google Scholar, assisted by Publish or Perish, as well as visual displays from VOSviewer. The display produced by VOSviewer shows that self-confidence is still something that can be researched, especially if it is associated with several keywords that are far from the word self-confidence. Apart from that, from the search results, it was found that parents and educators have a great impact on efforts to increase self-confidence.

Going global by going local: Impacts and opportunities of geographically focused data integration

Abstract Biodiversity conservation is a global challenge that requires the integration of global and local data. Expanding global data infrastructures have opened unprecedented opportunities for biodiversity data storage, curation, and dissemination. Within one such infrastructure—the Global Biodiversity Information Facility (GBIF)—these benefits are achieved by aggregating data from over 100 regional infrastructure nodes. Such, regional biodiversity infrastructures benefit scientific communities in ways that exceed their core function of contributing to global data aggregation, but these additional scientific impacts are rarely quantified. To fill this gap, we characterize the scientific impact of the Atlas of Living Australia, one of the oldest and largest GBIF nodes, as a case study of a regional biodiversity information facility. Our discussion reveals the multifaceted impact of the regional biodiversity data infrastructure. We showcase the global importance of such infrastructures, data sets, and collaborations.

Mpox 1b: Upstanders for Science in Western and Chinese Social Media

At the beginning of the COVID-19 pandemic, scientific literature published research about the presence of hoaxes and evidence in diverse social media, with a huge scientific and social impact. The main results showed that while in Western social media like X there was more false information and less scientific evidence than in the Chinese platform Weibo, but scientific evidence was more retweeted than hoaxes. This research allowed the identification of social activists for science in the social media, who multiplied their impact when scientists provided them with evidence. Third, thanks to the very intense and dialogic work of a diversity of researchers. Mpox clade 1b outbreak, which has now been declared a global public health emergency by WHO, requires a fast reaction from science, already taking place. This article analyzes information disseminated in X and Weibo about mpox. 3089 messages published between 12 and 16 of August 2024 have been analyzed. The results show that while hoaxes around mpox are prevalent in social media, posts containing scientific evidence do receive more interaction. Such findings contribute to the understanding of the health crisis and underscore the need for health authorities to join efforts with citizens to co-create evidence-based communication strategies.

Standards for conducting and reporting consensus and recommendation documents: European Society of Cardiovascular Radiology policy from the Guidelines Committee

Cardiovascular imaging is exponentially increasing in the diagnosis, risk stratification, and therapeutic management of patients with cardiovascular disease. The European Society of Cardiovascular Radiology (ESCR) is a non-profit scientific medical society dedicated to promoting and coordinating activities in cardiovascular imaging. The purpose of this paper, written by ESCR committees and Executive board members and approved by the ESCR Executive Board and Guidelines committee, is to codify a standardized approach to creating ESCR scientific documents. Indeed, consensus development methods must be adopted to ensure transparent decision-making that optimizes national and global health and reaches a certain scientific credibility. ESCR consensus documents developed based on a rigorous methodology will improve their scientific impact on the management of patients with cardiac involvement.Critical relevance statementThis document aims to codify the methodology for producing consensus documents of the ESCR. These ESCR indications will broaden the scientific quality and credibility of further publications and, consequently, the impact on the diagnostic management of patients with cardiac involvement.Key PointsCardiovascular imaging is exponentially increasing for diagnosis, risk stratification, and therapeutic management.The ESCR is committed to promoting cardiovascular imaging.A rigorous methodology for ESCR consensus documents will improve their scientific impact.

Reconstructing long-term (1980–2022) daily ground particulate matter concentrations in India (LongPMInd)

Abstract. Severe airborne particulate matter (PM, including PM2.5 and PM10) pollution in India has caused widespread concern. Accurate PM concentrations are fundamental for scientific policymaking and health impact assessment, while surface observations in India are limited due to scarce sites and uneven distribution. In this work, a simple structured, efficient, and robust model based on the Light Gradient-Boosting Machine (LightGBM) was developed to fuse multisource data and estimate long-term (1980–2022) historical daily ground PM concentrations in India (LongPMInd). The LightGBM model shows good accuracy with out-of-sample, out-of-site, and out-of-year cross-validation (CV) test R2 values of 0.77, 0.70, and 0.66, respectively. Small performance gaps between PM2.5 training and testing (delta RMSE of 1.06, 3.83, and 7.74 µg m−3) indicate low overfitting risks. With great generalization ability, the openly accessible, long-term, and high-quality daily PM2.5 and PM10 products were then reconstructed (10 km, 1980–2022). This showed that India has experienced severe PM pollution in the Indo-Gangetic Plain (IGP), especially in winter. PM concentrations have significantly increased (p<0.05) in most regions since 2000 (0.34 µgm-3yr-1). The turning point occurred in 2018 when the Indian government launched the National Clean Air Programme, and PM2.5 concentrations declined in most regions (−0.78 µgm-3yr-1) during 2018–2022. Severe PM2.5 pollution caused continuous increased attributable premature mortalities, from 0.73 (95 % confidence interval (CI) [0.65, 0.80]) million in 2000 to 1.22 (95 % CI [1.03, 1.41]) million in 2019, particularly in the IGP, where attributable mortality increased from 0.36 million to 0.60 million. LongPMInd has the potential to support multiple applications of air quality management, public health initiatives, and efforts to address climate change. The daily and monthly PM2.5 and PM10 concentrations are publicly accessible at https://doi.org/10.5281/zenodo.10073944 (Wang et al., 2023a).

Language bias, not knowledge shortfall, underestimates the evidence of megafauna kill sites in South America

The Megafauna Kill Sites (MKS), with irrefutable empirical evidence of human-megafauna interactions over the late Quaternary, have widely been recognized in North America and historically overlooked in South America. Here, we systematically reviewed the MKS from the Americas and showed that the neglected evidence from South American MKS is as robust as or even more robust, in both quantity and quality, than the evidence from North America. However, the South American studies are often limited to low-reach publications (gray literature or local journals) written in Latin languages, which are less cited than English-written publications. Our findings clearly indicate that the neglect of South American MKS is due to its limited scientific impact caused by language bias, and not due to the lack of robust knowledge, inadequate data, or questionable evidence. To reverse this context and put the rich evidence of South American MKS on an international audience, we strongly recommend that South American researchers prioritize publishing their studies in English, the universal language of science since sec. XX. We also suggest making all archaeological evidence readily available in online databases, such as the KillSite database (www.killsitedatabase.com). We believe our recommendations align with the current scope of science, which predominantly operates in English and benefits from the widespread accessibility provided by the internet, and will help South American publications reach international audiences interested in human-megafauna interaction and animal exploitation.

The interaction of inter-organizational diversity and team size, and the scientific impact of papers

Large teams are known to be more likely to publish highly cited papers, while small teams are known to be better at publishing highly disruptive papers. However, there is a lack of adequate theoretical understanding of the mechanisms by which scientific collaboration among researchers is related to the scientific impact of their papers. We investigated the mechanisms more closely by focusing on the interaction of inter-organizational diversity and team size in the process of team formation and knowledge dissemination. We analyzed 12,010,102 Web of Science papers and examined how inter-organizational diversity is associated with the relationship of team size with disruption and citations. As a result, we found that not only small teams, but also large teams with great inter-organizational diversity were able to disrupt science and technology effectively. We also found that large teams with greater inter-organizational diversity were more likely to produce highly cited papers. Our findings are robust and consistently observed regardless of publication year, team size, the number of references, and the degree of multidisciplinarity. These results have significant implications for researchers in selecting collaborators to achieve greater impact and for improving the qualitative efficiency of public research investments.

Dynamic patterns of the disruptive and consolidating knowledge flows in Nobel-winning scientific breakthroughs

Abstract Scientific breakthroughs possess the transformative potential to reshape research trajectories and scientific paradigms. However, there is limited systematic evidence on how these breakthroughs influence the evolution of scientific knowledge. Building on the concepts of disruption and consolidation in science, we categorize forward-citing papers into two distinct categories: Disruptive Citing Papers (DCP) and Consolidating Citing Papers (CCP). Analyzing the dynamic patterns of DCP and CCP in Nobel-winning papers, we find that in the early post-publication phase, scientific breakthroughs generate more consolidating citations than disruptive citations. Additionally, CCP in this early phase demonstrate higher scientific impact. However, in the long-term phase, scientific breakthroughs generate more disruptive citations, with DCP often involving larger and more diverse teams. Linguistic analysis also uncovers nuanced differences between CCP and DCP. Furthermore, the dynamic patterns of knowledge flow in scientific breakthroughs differ significantly from control groups. Collectively, our results reveal that scientific breakthroughs initially consolidate knowledge before disrupting it in later phases, offering profound insights into the mechanisms driving scientific progress. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00323

Writing tips for psychoneuroimmunology trainees: Lessons learned from Dr. Kiecolt-Glaser

Psychoneuroimmunology (PNI) researchers can advance their careers and increase their scientific impact by prioritizing their writing skills. In addition to Dr. Kiecolt-Glaser's landmark research that inspired this special issue, her legacy is reflected in her prolific writing. Dr. Kiecolt-Glaser has the unique ability to convey her innovative research clearly and to diverse audiences. She also made writing mentorship a critical part of the training experience in her lab. In these ways, Dr. Kiecolt-Glaser's writing skills and mentorship have shaped both the PNI field and her trainees' careers. In this paper, I distill lessons learned about writing from Dr. Kiecolt-Glaser during my time as a graduate student in her Stress and Health Lab in the 2010s. I reflect on Dr. Kiecolt-Glaser's influence on her trainees' writing habits, summarize “writing pearls” inspired by her feedback/revisions, and provide observations on her writing mentorship habits. These tips are intended to help PNI trainees to clearly communicate their work and to help mentors reflect on ways they can prioritize and advance their trainees' writing skills. Finally, I reflect on how Dr. Kiecolt-Glaser's mentorship and scientific accomplishments had a tremendous impact on my own career development.

Chebulinic Acid: An Incipient Anticancer Agent.

Terminalia chebula (T. chebula) comprising chebulinic acid as its principle active constituent is used to cure various diseases. T. chebula and chebulinic acid are used as antimicrobial, antioxidant, antidiabetic, anti-inflammatory, hepatoprotective, antimutagenic, radioprotective, cardioprotective, antiproliferative, antiarthritic, anticaries, and so on. The objective of this current study is to give an overview of the recent literature and patents of T. chebula and chebulinic acid including methods of its isolation/extraction and their application in the prevention of various cancers and other diseases. Present research and patents highlighting the anti-cancer potential of T. chebula and chebulinic acid have been studied and discussed keeping in view the scientific novelty and impact. Both T. chebula and chebulinic acid are currently being explored for their anticancer potential in vitro and in vivo. They are either incorporated alone or in combination with other plants or drugs to show their activity and many clinical trials are also going on various potentials of the plant and chebulinic acid. Novel extraction techniques are also explored and patented. Efforts are being made to improve the bioavailability by developing Novel herbal drug delivery systems of the plant extract or chebulinic acid itself. Anti-cancer potential of T. chebula and chebulinic acid may be well established by promising clinical trials and may open new interventions in various tumors. Clinical trials in conjunction with standard therapies are required to explore and validate the actual potential of T. chebula and chebulinic acid respectively.

Latent variable modeling of scientific impact: Estimation of the Q model parameters with structural equation models

Abstract Statistical modeling of scientific productivity and impact provides insights into bibliometric measures used also to quantify differences between individual scholars. The Q model decomposes the log-transformed impact of a published paper into a researcher capacity parameter and a random luck parameter. These two parameters are then modeled together with the log-transformed number of published papers (i.e., an indicator of productivity) by means of a trivariate normal distribution. In this work we propose a formulation of the Q model that can be estimated as a structural equation model. The Q model as a structural equation model allows us to quantify the reliability of researchers’ Q parameter estimates. It can be extended to incorporate person covariates and multivariate extensions of the Q model could also be estimated. We empirically illustrate our approach to estimate the Q model and also provide openly available code for R and Mplus.

A la cacería de Eclipses solares

Throughout the course of history, solar eclipses have had a scientific and cultural impact in human society. On Oc-tober 14th 2023 and April 8th 2024 two solar eclipses were visible from México and the Universidad Autónoma Metropolitana, Unidad Azcapotzalco documented both. Through this experience, we invite the community to ponder on the relevance these events have together with their corresponding utility and the way in which the interested reader can become an eclipse hunter

Maximizing the Utility of Alzheimer’s Disease Trial Data: Sharing of Baseline A4 and LEARN Data

BackgroundThe Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies were conducted between 2014 and 2023, with enrollment completed in 2017 and final study results reported in 2023. The study screening process involved the collection of initial clinical, cognitive, neuroimaging, and genetic measures to determine eligibility. Once randomized, enrolled participants were assessed every four weeks over a 4.5-year follow-up period during which longitudinal clinical, cognitive, and neuroimaging measures were collected. A large number of longitudinal fluid biospecimens were also collected and banked. Consistent with the NIH data sharing policy and the principles of Open Science, the A4/LEARN investigators aimed to share data as broadly and early as possible while still protecting participant privacy and confidentiality and the scientific integrity of the studies.ObjectivesWe describe the approach, methods, and platforms used to share the A4 and LEARN pre-randomization study data for secondary research use. Preliminary results measuring the impact of these efforts are also summarized. We conclude with a discussion of lessons learned and next steps.DesignThe materials shared included de-identified quantitative and image data, analysis software, instruments, and documentation.SettingThe A4 and LEARN Studies were conducted at 67 clinical trial sites in the United States, Canada, Japan, and Australia.ParticipantsThe A4 study screened (n=6763), enrolled, and randomized (n=1169) participants between the ages of 65 and 85 with a blinded follow-up period of 240 weeks followed by an open-label period of variable length. The LEARN study screened and enrolled individuals (n=538) who were ineligible for the A4 study based on nonelevated measures of amyloid accumulation using positron emission tomography imaging (amyloid PET).MeasurementsWe provide descriptive measures of the data shared and summarize the frequency, characteristics, and status of all data access requests submitted to date. We evaluate the scientific impact of the data-sharing effort by conducting a literature search to identify related publications.ResultsThe A4 and LEARN pre-randomization study data were released in December 2018. As of May 8, 2024, 1506 requests have been submitted by investigators and citizen scientists from more than 50 countries. We identified 49 peer-reviewed publications that acknowledge the A4/LEARN study.ConclusionsOur initial results provide evidence supporting the feasibility and scientific utility of broad and timely sharing of Alzheimer’s disease trial data.

Relational hyperevent models for the coevolution of coauthoring and citation networks

Abstract The development of appropriate statistical models has lagged behind the ambitions of empirical studies analysing large scientific networks—systems of publications connected by citations and authorship. Extant research typically focuses on either paper citation networks or author collaboration networks. However, these networks involve both direct relationships, as well as broader dependencies between references linked by multiple citation paths. In this work, we extend recently developed relational hyperevent models to analyse networks characterized by complex dependencies across multiple network modes. We introduce new covariates to represent theoretically relevant and empirically plausible mixed-mode network configurations. This model specification allows testing hypotheses that recognize the polyadic nature of publication data, while accounting for multiple dependencies linking authors and references of current and prior papers. We implement the model using open-source software to analyse publicly available data on a large scientific network. Our findings reveal a tendency for subsets of papers to be cocited, indicating that the impact of these papers may be partly due to endogenous network processes. More broadly, the analysis shows that models accounting for both the hyperedge structure of publication events and the interconnections between authors and references significantly enhance our understanding of the mechanisms driving scientific production and impact.

Ten year citation prediction model for systematic reviews using early years citation data

Citation counts are frequently used for assessing the scientific impact of articles. Current approaches for forecasting future citations counts have important limitations. This study aims to analyse and predict the trajectories of citation counts of systematic reviews (SR) based on their citation profiles in the previous years and predict quantiles of future citation counts. We included all SR published between 2010 and 2012 in medical journals indexed in the Web of Science. A longitudinal k-means (KML) clustering approach was applied to identify trajectories of citations counts 10 years after publication, according to the yearly citation count, the proportion of all cites attained in a specific year and the annual variation in citation counts. Finally, we built multinomial logistic regression models aiming to predict in what tercile or quartile of citation counts a SR would be 10 years after publication. Using clustering approaches, we obtained 24 groups of SR. Two groups (7.9% of the articles) had an average of > 200 citations, while two other groups (10.4% of the articles) presented an average of < 10 citations. The model predicting terciles of citation counts attained an accuracy of 72.8% (95%CI = 71.1–74.3%) and a kappa coefficient of 0.59 (95%CI = 0.57–0.62). Prediction of citation quartiles (combining the second and third quartiles into a single group) attained a accuracy of 76.2% (95%CI = 74.7–77.8%) and a kappa coefficient of 0.62 (95%CI = 0.59–0.64). This study provides an approach for predicting of future citations of SR based exclusively on citation counts from the previous years, with the models developed displaying an encouraging accuracy and agreement.

Exploring Sustainable Investment: In-Depth Analysis of Socially Responsible Investing (SRI) and ESG Strategies

Theoretical background: In recent years, there has been an increase in social and environmental awareness, which has forced companies to change their approach to investment. Large companies are burdened with responsibility for contemporary, global problems such as the depletion of natural resources, the ongoing process of environmental degradation and inequalities in living standards between poor and rich countries. Therefore, when making investments, companies must evaluate them not only in terms of financial returns, but also in terms of their social, ecological and ethical impact. Two key approaches to this new investment paradigm stand out: socially responsible investment (SRI) and ESG investment (a three-pronged view of environmental, social and corporate governance). They focus on sustainable investments in order to achieve positive results for investors’ portfolios as well as for society and the environment. Purpose of the article: The following article examines both approaches, analysing their relevance, objectives, tools and economic and social impacts. Research methods: For this purpose, specialist journals published between 2001 and 2023 were searched in the Web of Science database. A literature review of socially responsible investment and ESG investment shows that interest in these concepts has increased rapidly in recent years. In addition, reports available on the websites of selected companies were analyzed. Main findings: The scientific impact on the studied concepts also makes it possible to determine future research directions. The literature contains results confirming that companies applying these approaches in their operations, achieve better results.