Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether ...Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.展开更多
The rapid development of digital education provides new opportunities and challenges for teaching model innovation.This study aims to explore the application of the BOPPPS(Bridge-in,Objective,Pre-assessment,Participat...The rapid development of digital education provides new opportunities and challenges for teaching model innovation.This study aims to explore the application of the BOPPPS(Bridge-in,Objective,Pre-assessment,Participatory learning,Post-assessment,Summary)teaching method in the development of a blended teaching model for the Operations Research course under the background of digital education.In response to the characteristics of the course and the needs of the student group,the teaching design is reconstructed with a student-centered approach,increasing practical teaching links,improving the assessment and evaluation system,and effectively implementing it in conjunction with digital educational technology.This teaching model has shown significant effectiveness in the context of digital education,providing valuable experience and insights for the innovation of the Operations Research course.展开更多
Vector-borne diseases caused by arthropod-borne viruses(arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of ...Vector-borne diseases caused by arthropod-borne viruses(arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms,vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate(NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible;however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.展开更多
This study is dedicated to exploring the role of scientific research team construction and collaborative management mechanisms in applied undergraduate universities in promoting diversified talent training and collabo...This study is dedicated to exploring the role of scientific research team construction and collaborative management mechanisms in applied undergraduate universities in promoting diversified talent training and collaborative innovation models.By forming an interdisciplinary scientific research team and recording in detail the team’s performance,problems encountered,and solutions during the collaborative innovation process,the study found that interdisciplinary team construction significantly improved scientific research timeliness,which was 29.33%higher than that of traditional single-disciplinary teams.Therefore,the construction of interdisciplinary scientific research teams and collaborative management mechanisms are effective ways for applied undergraduate universities to promote diversified talent training and collaborative innovation.展开更多
Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a g...Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.展开更多
BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barr...BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barriers,and professional challenges.Compared to other age groups,they have higher recurrence rates,lower survival rates,and increased risk of depression.Research is lacking on factors influencing depressive symptoms and predictive models for this age group.AIM To analyze factors influencing depressive symptoms in young/middle-aged BC patients and construct a depression risk predictive model.METHODS A total of 360 patients undergoing BC treatment at two tertiary hospitals in Jiangsu Province,China from November 2023 to April 2024 were included in the study.Participants were surveyed using a general information questionnaire,the patient health questionnaire depression scale,the visual analog scale for pain,the revised family support scale,and the long form of the international physical activity questionnaire.Univariate and multivariate analyses were conducted to identify the factors affecting depression in middle-aged and young BC patients,and a predictive model for depression risk was developed based on these findings.RESULTS Among the 360 middle-aged and young BC patients,the incidence rate of depressive symptoms was 38.61%(139/360).Multivariate analysis revealed that tumor grade,patient’s monthly income,pain score,family support score,and physical activity score were factors influencing depression in this patient group(P<0.05).The risk prediction model constructed based on these factors yielded an area under the receiver operating characteristic curve of 0.852,with a maximum Youden index of 0.973,sensitivity of 86.80%,specificity of 89.50%,and a diagnostic odds ratio of 0.552.The Hosmer-Lemeshow test for goodness of fit indicated an adequate model fit(χ^(2)=0.360,P=0.981).CONCLUSION The constructed predictive model demonstrates good predictive performance and can serve as a reference for medical professionals to early identify high-risk patients and implement corresponding preventive measures to decrease the incidence of depressive symptoms in this population.展开更多
The BOF-key is the performance-based research funding system that is used in Flanders, Belgium. In this paper we describe the historical background of the system, its current design and organization, as well as its ef...The BOF-key is the performance-based research funding system that is used in Flanders, Belgium. In this paper we describe the historical background of the system, its current design and organization, as well as its effects on the Flemish higher education landscape. The BOFkey in its current form relies on three bibliometric parameters: publications in Web of Science, citations in Web of Science, and publications in a comprehensive regional database for SSH publications. Taken together, the BOF-key forms a unique variant of the Norwegian model: while the system to a large extent relies on a commercial database, it avoids the problem of inadequate coverage of the SSH. Because the bibliometric parameters of the BOF-key are reused in other funding allocation schemes, their overall importance to the Flemish universities is substantial.展开更多
The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Lium...The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.展开更多
This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on m...This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on medical research. Thirty seven research articles published between 2000 and 2018 which employed logistic regression as the main statistical tool as well as six text books on logistic regression were reviewed. Logistic regression concepts such as odds, odds ratio, logit transformation, logistic curve, assumption, selecting dependent and independent variables, model fitting, reporting and interpreting were presented. Upon perusing the literature, considerable deficiencies were found in both the use and reporting of LR. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Also, most studies did not report on validation analysis, regression diagnostics or goodness-of-fit measures;measures which authenticate the robustness of the LR model. Here, we demonstrate a good example of the application of the LR model using data obtained on a cohort of pregnant women and the factors that influence their decision to opt for caesarean delivery or vaginal birth. It is recommended that researchers should be more rigorous and pay greater attention to guidelines concerning the use and reporting of LR models.展开更多
Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we recons...Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.展开更多
We examine the role of big data and machine learning in cancer research.We describe an example in cancer research where gene-level data from The Cancer Genome Atlas(TCGA) consortium is interpreted using a pathway-leve...We examine the role of big data and machine learning in cancer research.We describe an example in cancer research where gene-level data from The Cancer Genome Atlas(TCGA) consortium is interpreted using a pathway-level model.As the complexity of computational models increases,their sample requirements grow exponentially.This growth stems from the fact that the number of combinations of variables grows exponentially as the number of variables increases.Thus,a large sample size is needed.The number of variables in a computational model can be reduced by incorporating biological knowledge.One particularly successful way of doing this is by using available gene regulatory,signaling,metabolic,or context-specific pathway information.We conclude that the incorporation of existing biological knowledge is essential for the progress in using big data for cancer research.展开更多
An analysis of the impact of simulation modelling in three diverse crop-livestock improvement projects in Agricultural Research for Development（AR4D） reveals benefits across a range of aspects including identificati...An analysis of the impact of simulation modelling in three diverse crop-livestock improvement projects in Agricultural Research for Development（AR4D） reveals benefits across a range of aspects including identification of objectives, design and implementation of experimental programs, effectiveness of participatory research with smallholder farmers, implementation of system change and scaling-out of results.In planning change, farmers must consider complex interactions within both biophysical and socioeconomic aspects of their crop and animal production activities.For this, whole-farm models that include household models of food, workload and financial requirements have the most utility and impact.The analysis also proposes improvements in design and implementation of AR4 D projects to improve the utility of simulation modelling for securing positive agronomic and livestock outcomes and lasting legacies.展开更多
A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale ...A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.展开更多
To control the vibration level of ships under construction,MSC Software’s Patran&Nastran modeling solutions can be used to establish a detailed finite element model of a new manned submersible support mother ship...To control the vibration level of ships under construction,MSC Software’s Patran&Nastran modeling solutions can be used to establish a detailed finite element model of a new manned submersible support mother ship based on a line drawing,including the deck layout,bulkhead section,and stiffener distribution.After a comprehensive analysis of the ship simulation conditions,boundaries,and excitation forces of the main operating equipment,modal analysis and calculation of the ship vibration can be conducted.In this study,we calculated and analyzed the vibration response of key points in the stern area of the ship’s main deck and the submersible warehouse area under design loading working conditions.We then analyzed the vibration response of typical decks(including the compass deck,steering deck,captain’s deck,forecastle deck,and main deck)under the main excitation forces and moments(such as the full swing pod and generator sets).The analysis results showed that under DESIDEP working conditions,the vibration of each deck and key areas of the support mother ship could meet the vibration code requirements of the ship’s preliminary design(using the pod excitation and generator sets).Similarly,the vibration response of a scientific research ship under other loading conditions also met the requirements of the code and provided data support for a comprehensive understanding of the ship’s vibration and noise levels.Using actual vibration measurements,the accuracy of the vibration level simulations using finite element modeling was verified,the vibration of each area of the ship comfortably meeting the requirements of the China Classification Society.展开更多
A complex biological system is often required to study the myriad of host-pathogen interactions associated with infectious diseases, especially since the current basis of biology has reached the molecular level. The u...A complex biological system is often required to study the myriad of host-pathogen interactions associated with infectious diseases, especially since the current basis of biology has reached the molecular level. The use of animal models is important for understanding the very complex temporal relationships that occur in infectious disease involving the body, its neuroendocrine and immune systems and the infectious organism. Because of these complex interactions, the choice of animal model must be a thoughtful and clearly defined process in order to provide relevant, translatable scientific data and to ensure the most beneficial use of the animals. While many animals respond similarly to humans from physiological, pathological, and therapeutic perspectives, there are also significant species-by-species differences. A welldesigned animal model requires a thorough understanding of similarities and differences in the responses between humans and animals and incorporates that knowledge into the goals of the study. Determining the intrinsic and extrinsic factors associated with the disease and creating a biological information matrix to compare the animal model and human disease courses is a useful tool to help choose the appropriate animal model. Confidence in the correlation of results from a model to the human disease can be achieved only if the relationship of the model to the human disease is well understood.展开更多
Purpose: We aim to create a model of consumer health information seeking behavior via social media, then to have a better understand of it. After that further efforts should be made to provide targeted recommendations...Purpose: We aim to create a model of consumer health information seeking behavior via social media, then to have a better understand of it. After that further efforts should be made to provide targeted recommendations for media managers to promote health communication via social media. Methods: Our custom model was derived from literature review, empirical research was tested by the use of questionnaire investigation, and then the collected data were analyzed by structural equation model tool SmartPLS. Finally, the custom model was modified according to the experimental results of SmartPLS. Results: A total of 239 (66.39%) of the respondents were female and 121 (33.61%) were male. The maximum of two stages of age were 18 - 29 (70.56%), 30 - 39 (13.89%). Wechat (60.28%), QQ Zone (55.22%), Micro-blog (48.89%) were the most commonly used social media to obtain health information. About 44.72% of respondents used social media to obtain health information multiple times a day. The whole numerical values of AVE, cronbach’s alpha, CR and square roots of AVE were above the benchmarks of themselves and showed great reliability and validity. All the 11 hypotheses had obvious statistical significance, the P-value of eight path coefficients exhibited <0.001, one path coefficient exhibited <0.01 and two path coefficients exhibited <0.05. Conclusions: A suitable model of consumer health information seeking behavior via social media was created and some inner relationships were found. Namely, gratification of health information and its platform had a positive effect on attitudes toward health information seeking behavior. Health information literacy and health status were proved to have a significant influence on attitudes toward health information seeking behavior, subject norms and perceived behavioral control respectively. In addition, attitudes toward the health information seeking behavior, subject norms and perceived behavioral control were proved to positively associate with health information seeking behavior intention.展开更多
Based on the analyses of the credit bank both at home and abroad, explore the effective way to construct the credit transfer model, find out the main problems in the process of transferring, design a much better model...Based on the analyses of the credit bank both at home and abroad, explore the effective way to construct the credit transfer model, find out the main problems in the process of transferring, design a much better model, formulate a new standard for credit transfer and carry out the research on the model design of the academic education's credit transfer in the open university.展开更多
Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess ...Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework(REF)2021 to create a research evaluation ChatGPT.This was applied to 51 of my own articles and compared against my own quality judgements.Findings:ChatGPT-4 can produce plausible document summaries and quality evaluation rationales that match the REF criteria.Its overall scores have weak correlations with my self-evaluation scores of the same documents(averaging r=0.281 over 15 iterations,with 8 being statistically significantly different from 0).In contrast,the average scores from the 15 iterations produced a statistically significant positive correlation of 0.509.Thus,averaging scores from multiple ChatGPT-4 rounds seems more effective than individual scores.The positive correlation may be due to ChatGPT being able to extract the author’s significance,rigour,and originality claims from inside each paper.If my weakest articles are removed,then the correlation with average scores(r=0.200)falls below statistical significance,suggesting that ChatGPT struggles to make fine-grained evaluations.Research limitations:The data is self-evaluations of a convenience sample of articles from one academic in one field.Practical implications:Overall,ChatGPT does not yet seem to be accurate enough to be trusted for any formal or informal research quality evaluation tasks.Research evaluators,including journal editors,should therefore take steps to control its use.Originality/value:This is the first published attempt at post-publication expert review accuracy testing for ChatGPT.展开更多
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 relati...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.展开更多
Pricing a product is one of the most important decisions an organization can make. Marketing research has developed several different approaches to price optimization. They include direct methods such as estimation of...Pricing a product is one of the most important decisions an organization can make. Marketing research has developed several different approaches to price optimization. They include direct methods such as estimation of willingness to pay, indirect methods such as Gabor-Granger and van Westendorp techniques, and product/price mix methods such as various discrete choice models. All of them are widely used in practical marketing research for evaluation of optimal prices for different products and product innovations. This work describes and compares several main of these approaches.展开更多
文摘Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.
文摘The rapid development of digital education provides new opportunities and challenges for teaching model innovation.This study aims to explore the application of the BOPPPS(Bridge-in,Objective,Pre-assessment,Participatory learning,Post-assessment,Summary)teaching method in the development of a blended teaching model for the Operations Research course under the background of digital education.In response to the characteristics of the course and the needs of the student group,the teaching design is reconstructed with a student-centered approach,increasing practical teaching links,improving the assessment and evaluation system,and effectively implementing it in conjunction with digital educational technology.This teaching model has shown significant effectiveness in the context of digital education,providing valuable experience and insights for the innovation of the Operations Research course.
文摘Vector-borne diseases caused by arthropod-borne viruses(arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms,vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate(NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible;however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.
基金Research on Innovative Talent Cultivation in Mechanical Engineering Majors under the Background of Emerging Engineering Education(2023SJYB1493)Research and Practice on the Cultivation Mode of Innovative Ability of College Students from the Perspective of Integration of Specialty and Entrepreneurship(2023SJYB1501)Beijing Hopefound Group-Jiangsu Union Technical Institute-Targeted Talent Cultivation and Training Program(2024030732830)。
文摘This study is dedicated to exploring the role of scientific research team construction and collaborative management mechanisms in applied undergraduate universities in promoting diversified talent training and collaborative innovation models.By forming an interdisciplinary scientific research team and recording in detail the team’s performance,problems encountered,and solutions during the collaborative innovation process,the study found that interdisciplinary team construction significantly improved scientific research timeliness,which was 29.33%higher than that of traditional single-disciplinary teams.Therefore,the construction of interdisciplinary scientific research teams and collaborative management mechanisms are effective ways for applied undergraduate universities to promote diversified talent training and collaborative innovation.
基金approved by our institutional Research Ethics Committee(HREC Approval Number H13554).
文摘Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.
基金Supported by Jiangsu Provincial Cadre Healthcare Scientific Research Grant Project,No.BJ23019Jiangsu Provincial Association of Maternal and Child Healthcare Scientific Research Grant Project,No.FYX202350+2 种基金Special Fund for the Project of Enhancing Academic Capability of Integrative Nursing,No.ZXYJHHL-K-2023-M20Jiangsu Provincial Graduate Student Practice and Innovation Program Project,No.SJCX24_0833the Training Project for Backbone Talents in Traditional Chinese Medicine Nursing in Nanjing Region,No.Ningwei Zhongyi[2023]No.8.
文摘BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barriers,and professional challenges.Compared to other age groups,they have higher recurrence rates,lower survival rates,and increased risk of depression.Research is lacking on factors influencing depressive symptoms and predictive models for this age group.AIM To analyze factors influencing depressive symptoms in young/middle-aged BC patients and construct a depression risk predictive model.METHODS A total of 360 patients undergoing BC treatment at two tertiary hospitals in Jiangsu Province,China from November 2023 to April 2024 were included in the study.Participants were surveyed using a general information questionnaire,the patient health questionnaire depression scale,the visual analog scale for pain,the revised family support scale,and the long form of the international physical activity questionnaire.Univariate and multivariate analyses were conducted to identify the factors affecting depression in middle-aged and young BC patients,and a predictive model for depression risk was developed based on these findings.RESULTS Among the 360 middle-aged and young BC patients,the incidence rate of depressive symptoms was 38.61%(139/360).Multivariate analysis revealed that tumor grade,patient’s monthly income,pain score,family support score,and physical activity score were factors influencing depression in this patient group(P<0.05).The risk prediction model constructed based on these factors yielded an area under the receiver operating characteristic curve of 0.852,with a maximum Youden index of 0.973,sensitivity of 86.80%,specificity of 89.50%,and a diagnostic odds ratio of 0.552.The Hosmer-Lemeshow test for goodness of fit indicated an adequate model fit(χ^(2)=0.360,P=0.981).CONCLUSION The constructed predictive model demonstrates good predictive performance and can serve as a reference for medical professionals to early identify high-risk patients and implement corresponding preventive measures to decrease the incidence of depressive symptoms in this population.
文摘The BOF-key is the performance-based research funding system that is used in Flanders, Belgium. In this paper we describe the historical background of the system, its current design and organization, as well as its effects on the Flemish higher education landscape. The BOFkey in its current form relies on three bibliometric parameters: publications in Web of Science, citations in Web of Science, and publications in a comprehensive regional database for SSH publications. Taken together, the BOF-key forms a unique variant of the Norwegian model: while the system to a large extent relies on a commercial database, it avoids the problem of inadequate coverage of the SSH. Because the bibliometric parameters of the BOF-key are reused in other funding allocation schemes, their overall importance to the Flemish universities is substantial.
基金Ministry of Science and Technology of China(2017YFC1501406)National Key Research and Development Plan Program of China(2017YFA0604500)CMA Youth Founding Program(Q201706&NWPC-QNJJ-201702)
文摘The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.
文摘This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on medical research. Thirty seven research articles published between 2000 and 2018 which employed logistic regression as the main statistical tool as well as six text books on logistic regression were reviewed. Logistic regression concepts such as odds, odds ratio, logit transformation, logistic curve, assumption, selecting dependent and independent variables, model fitting, reporting and interpreting were presented. Upon perusing the literature, considerable deficiencies were found in both the use and reporting of LR. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Also, most studies did not report on validation analysis, regression diagnostics or goodness-of-fit measures;measures which authenticate the robustness of the LR model. Here, we demonstrate a good example of the application of the LR model using data obtained on a cohort of pregnant women and the factors that influence their decision to opt for caesarean delivery or vaginal birth. It is recommended that researchers should be more rigorous and pay greater attention to guidelines concerning the use and reporting of LR models.
基金supported by the DIALOG Program[grant name“Research into Excellence Patterns in Science and Art”]financed by the Ministry of Science and Higher Education in Poland
文摘Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.
文摘We examine the role of big data and machine learning in cancer research.We describe an example in cancer research where gene-level data from The Cancer Genome Atlas(TCGA) consortium is interpreted using a pathway-level model.As the complexity of computational models increases,their sample requirements grow exponentially.This growth stems from the fact that the number of combinations of variables grows exponentially as the number of variables increases.Thus,a large sample size is needed.The number of variables in a computational model can be reduced by incorporating biological knowledge.One particularly successful way of doing this is by using available gene regulatory,signaling,metabolic,or context-specific pathway information.We conclude that the incorporation of existing biological knowledge is essential for the progress in using big data for cancer research.
基金the various projects and others who participated in the review and to ACIAR and CSIRO for logistical and financial supportPC was a research manager for these projects in CSIRO
文摘An analysis of the impact of simulation modelling in three diverse crop-livestock improvement projects in Agricultural Research for Development（AR4D） reveals benefits across a range of aspects including identification of objectives, design and implementation of experimental programs, effectiveness of participatory research with smallholder farmers, implementation of system change and scaling-out of results.In planning change, farmers must consider complex interactions within both biophysical and socioeconomic aspects of their crop and animal production activities.For this, whole-farm models that include household models of food, workload and financial requirements have the most utility and impact.The analysis also proposes improvements in design and implementation of AR4 D projects to improve the utility of simulation modelling for securing positive agronomic and livestock outcomes and lasting legacies.
基金jointly supported by the Main Direction Program of Knowledge Innovation of the Chinese Academy of Sciences(Grant No.KZCX2EW203)the National Key Basic Research Program of China(Grant No.2013CB430105)the National Department of Public Benefit Research Foundation(Grant No.GYHY201006031)
文摘A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.
基金Supported by the Research and Implementation of Sea Trial Technology(Grant No.2016YFC03000704).
文摘To control the vibration level of ships under construction,MSC Software’s Patran&Nastran modeling solutions can be used to establish a detailed finite element model of a new manned submersible support mother ship based on a line drawing,including the deck layout,bulkhead section,and stiffener distribution.After a comprehensive analysis of the ship simulation conditions,boundaries,and excitation forces of the main operating equipment,modal analysis and calculation of the ship vibration can be conducted.In this study,we calculated and analyzed the vibration response of key points in the stern area of the ship’s main deck and the submersible warehouse area under design loading working conditions.We then analyzed the vibration response of typical decks(including the compass deck,steering deck,captain’s deck,forecastle deck,and main deck)under the main excitation forces and moments(such as the full swing pod and generator sets).The analysis results showed that under DESIDEP working conditions,the vibration of each deck and key areas of the support mother ship could meet the vibration code requirements of the ship’s preliminary design(using the pod excitation and generator sets).Similarly,the vibration response of a scientific research ship under other loading conditions also met the requirements of the code and provided data support for a comprehensive understanding of the ship’s vibration and noise levels.Using actual vibration measurements,the accuracy of the vibration level simulations using finite element modeling was verified,the vibration of each area of the ship comfortably meeting the requirements of the China Classification Society.
文摘A complex biological system is often required to study the myriad of host-pathogen interactions associated with infectious diseases, especially since the current basis of biology has reached the molecular level. The use of animal models is important for understanding the very complex temporal relationships that occur in infectious disease involving the body, its neuroendocrine and immune systems and the infectious organism. Because of these complex interactions, the choice of animal model must be a thoughtful and clearly defined process in order to provide relevant, translatable scientific data and to ensure the most beneficial use of the animals. While many animals respond similarly to humans from physiological, pathological, and therapeutic perspectives, there are also significant species-by-species differences. A welldesigned animal model requires a thorough understanding of similarities and differences in the responses between humans and animals and incorporates that knowledge into the goals of the study. Determining the intrinsic and extrinsic factors associated with the disease and creating a biological information matrix to compare the animal model and human disease courses is a useful tool to help choose the appropriate animal model. Confidence in the correlation of results from a model to the human disease can be achieved only if the relationship of the model to the human disease is well understood.
文摘Purpose: We aim to create a model of consumer health information seeking behavior via social media, then to have a better understand of it. After that further efforts should be made to provide targeted recommendations for media managers to promote health communication via social media. Methods: Our custom model was derived from literature review, empirical research was tested by the use of questionnaire investigation, and then the collected data were analyzed by structural equation model tool SmartPLS. Finally, the custom model was modified according to the experimental results of SmartPLS. Results: A total of 239 (66.39%) of the respondents were female and 121 (33.61%) were male. The maximum of two stages of age were 18 - 29 (70.56%), 30 - 39 (13.89%). Wechat (60.28%), QQ Zone (55.22%), Micro-blog (48.89%) were the most commonly used social media to obtain health information. About 44.72% of respondents used social media to obtain health information multiple times a day. The whole numerical values of AVE, cronbach’s alpha, CR and square roots of AVE were above the benchmarks of themselves and showed great reliability and validity. All the 11 hypotheses had obvious statistical significance, the P-value of eight path coefficients exhibited <0.001, one path coefficient exhibited <0.01 and two path coefficients exhibited <0.05. Conclusions: A suitable model of consumer health information seeking behavior via social media was created and some inner relationships were found. Namely, gratification of health information and its platform had a positive effect on attitudes toward health information seeking behavior. Health information literacy and health status were proved to have a significant influence on attitudes toward health information seeking behavior, subject norms and perceived behavioral control respectively. In addition, attitudes toward the health information seeking behavior, subject norms and perceived behavioral control were proved to positively associate with health information seeking behavior intention.
文摘Based on the analyses of the credit bank both at home and abroad, explore the effective way to construct the credit transfer model, find out the main problems in the process of transferring, design a much better model, formulate a new standard for credit transfer and carry out the research on the model design of the academic education's credit transfer in the open university.
文摘Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework(REF)2021 to create a research evaluation ChatGPT.This was applied to 51 of my own articles and compared against my own quality judgements.Findings:ChatGPT-4 can produce plausible document summaries and quality evaluation rationales that match the REF criteria.Its overall scores have weak correlations with my self-evaluation scores of the same documents(averaging r=0.281 over 15 iterations,with 8 being statistically significantly different from 0).In contrast,the average scores from the 15 iterations produced a statistically significant positive correlation of 0.509.Thus,averaging scores from multiple ChatGPT-4 rounds seems more effective than individual scores.The positive correlation may be due to ChatGPT being able to extract the author’s significance,rigour,and originality claims from inside each paper.If my weakest articles are removed,then the correlation with average scores(r=0.200)falls below statistical significance,suggesting that ChatGPT struggles to make fine-grained evaluations.Research limitations:The data is self-evaluations of a convenience sample of articles from one academic in one field.Practical implications:Overall,ChatGPT does not yet seem to be accurate enough to be trusted for any formal or informal research quality evaluation tasks.Research evaluators,including journal editors,should therefore take steps to control its use.Originality/value:This is the first published attempt at post-publication expert review accuracy testing for ChatGPT.
文摘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.
文摘Pricing a product is one of the most important decisions an organization can make. Marketing research has developed several different approaches to price optimization. They include direct methods such as estimation of willingness to pay, indirect methods such as Gabor-Granger and van Westendorp techniques, and product/price mix methods such as various discrete choice models. All of them are widely used in practical marketing research for evaluation of optimal prices for different products and product innovations. This work describes and compares several main of these approaches.
