Studying Relationship between Citation and Altmetrics of Top Chemistry Researches’ Articles

Abstract: The main objective of the present research is to examine the relationship between the number of citations and the level of altmetrics for testing the validity of these new metrics, at least in terms of being alignment with the test established index. The present research population consist of articles from the top chemistry writers that were profiled at the Scopus Citation Database in 2010. Sample research is the articles by 20 top author. The present research is applied in terms of purpose, and is descriptive and correlative in terms of data collection. Data extraction was performed using Webometric analyst software and citation data was collected from Scopus. SPSS software was used to analyze the data. The research findings show that the articles in question have little presence on social networks. In terms of the amount of attendance and distribution Mendeley, CiteUlike, Twitter, Facebook, Blogs, Google Plus and News, had the largest number of articles and altmetrics respectively. Also, the results show that Mendeley and Twitter have the most relationship with citations. Also, articles have at least one higher citation average altmetric (25.14%) than those with no altmetric (7.58%). In terms of citations\u27 relationship, the Spearman correlation test showed a strong correlation between the number of Mendeley readers, news, and citations. Also, there was a weak correlation between Twitter, CiteUlike, and citations. Finally, there was not a meaningful relationship between Facebook posts, blog posts, Google plus, and citations

Impact of Teaching Scientific Search Methods and Increasing Familiarity with Databases on the Reduction of Information Seeking Anxiety in Students of Dentistry in the University of Medical Sciences, Iran

Background: The negative impact of anxiety on information seeking is of great importance and it has been studied in different ways worldwide. Based on the results of such studies, it is possible to identify different aspects of information seeking anxiety, to design different tools to assess it, to evaluate personal and social factors affecting it, and to identify various methods to inhibit and reduce it. Hence, the current study aimed to evaluate the effect of teaching scientific search methods and increasing familiarity with databases on reducing the level of anxiety among students of dentistry at the Zahedan University of Medical Sciences, Iran. Methods: The current survey included all students of the faculty of dentistry at the Zahedan University of Medical Sciences in the academic year of 2015 - 16 as the study population. A total of 60 volunteers were selected by convenience sampling and were randomly allocated to 2 groups of 30, as the experimental and control groups. The information seeking anxiety scale was used to collect data. Results: The present findings revealed the effectiveness of teaching interventions on reducing the level of information seeking anxiety among students using the independent t test. Specifically, findings revealed a reduction in the anxiety caused by barriers to using information resources (t = 3.79; P value = 0.001), by the barriers to using the computer and Internet (t = 5.35; P value = 0.001), and by information seeking and topic selection barriers (t = 2.50; P value = 0.015). However, the intervention had no effect on the level of anxiety caused by barriers to using the library (t = 0.89; P value = 0.373) and technical barriers (t = 0.68; P value = 0.495). Conclusions: Considering the findings of the current study, some measures can be taken to reduce information seeking anxiety in students, especially in the academic environment. Hence, it is recommended to design other studies to further evaluate information seeking anxiety. Keywords: Teaching, Information Seeking, Anxiety, Students of Faculty of Dentistry at the University of Medical Science

Research data Sharing Case study: Medical faculty members

Purpose: Advances in information and communication technologies have facilitated the research and production of large volumes of data, and this has led to a new paradigm in scientific research called the fourth paradigm of science. The purpose of this study was to evaluate the status of research data sharing among researchers at Kerman University of Medical Sciences.Methodology: This study is a descriptive survey research. The study population consisted of all faculty members of Kerman University of Medical Sciences with 521 members. The sample size was estimated 220 using Cochran formula. Data collection tool was a researcher-built questionnaire. Cronbach's alpha coefficient was used to calculate the reliability of different parts of questionnaire. Data were analyzed using descriptive statistics including frequency, percentage, mean and standard deviation.Findings: The status of research data sharing in terms of human factors with an average of 3.67 is in relatively desirable condition. Among the human factor variables, the factor of understanding the importance and necessity of data sharing with an average of 4.21 is in a better position than other items. Also, the status of research data sharing of technical factors with an average of 2.58 and in terms of organizational factors with an average of 2.35 is in a relatively desirable condition.Among the items of organizational factors, respectively, holding training courses, support of senior managers of the organization, standards and regulations, the existence of a special program for data sharing and communication channels between researchers are in an unfavorable condition. Also, the sharing of research data in terms of legal factors with an average of 2.36 is relatively desirable. Legal frameworks, control of data access, and the organization's obligation to share data in research projects are in poor condition. Cultural factors related to data sharing, with an average of 3.95 are in good condition. Among the items of this dimension, only two items of incentive and motivation mechanisms and reducing unsound competition are in a relatively desirable condition.Results: The results indicated that Data management programs will enable communication with the areas of production, organization, management and preparation of specialized medical data, providing a sharing process for future exploitation. Encouraging the culture of data sharing, holding training courses, designing data sharing agreements, protecting privacy and data confidentiality, financial support, and strengthening the technology infrastructure are among the suggestions of this research

Assessment of the status and factors influencing the adoption of cloud computing in knowledge-based companies Case Study: Kerman Science and Technology Park

Cloud computing is one of the most important topics in knowledge-based companies. Small and medium-sized enterprises with a low budget and few human resources are one of the major groups tending to use cloud computing to benefit from this technology. Several components affect the adoption of cloud in these companies, which should be evaluated before making the decision. This study aimed to identify these components and determine how much each component impacts the adoption of cloud in small and medium-sized companies. Accordingly, based on the diffusion of innovation theory and technology-organization-environment (TOE) framework as well as the previous studies, a conceptual model with twelve components was presented. Data were collected via a questionnaire using the descriptive survey method from 59 knowledge-based companies of Kerman Science and Technology Park. In this study, the “need” factor was selected as the desired state and “use” as the current state; then, the mean of the other components was compared with the mean of these two factors. The results of this study showed that based on the gap between the desired state and the current state, the employees’ knowledge of cloud computing, compatibility, complexity, and security and privacy require more attention. Innovation factors, decision makers’ knowledge of cloud computing, benefits, and costs have a better position than other components. Finally, factors effective in the compliance of knowledge-based companies of Kerman Science and Technology Park with cloud computing were ranked using the Vikor method. The need factor (information need), decision makers’ innovation, and benefits were ranked first to third, respectively, and the complexity factor was ranked last among the indicators. Therefore, identifying the current state (not using cloud computing based on the needs or not matching with cloud) and the desired state (using cloud computing based on the needs or matching with the cloud) in knowledge-based companies, based on the criteria or factors whose usefulness was investigated in this study, can be an important step in joining these companies into the cloud, and thus bringing the benefits of this new technology to knowledge-based companies

Value of Los Angeles Motor Scale (LAMS) in the detection of large vessels occlusion in suspected stroke patients; a systematic review and meta-analysis

Introduction Los Angeles Motor Scale (LAMS) is a validated prehospital scoring tool to identify stroke patients with large vessel occlusions (LVOs). While some studies have reported conflicting data in regards to the diagnostic value of LAMS, this systematic review and meta-analysis aims to provide a more concrete evidence for the value of this clinical decision tool in the diagnosis of LVO in suspected stroke patients. Method Online databases of PubMed, Embase, Scopus, and Web of Science were searched until the end of October 2022, for studies evaluating the diagnostic performance of LAMS in the detection of LVOs in suspected stroke patients. Results The results of our analysis demonstrated an AUC of 0.83 (95% CI: 0.79, 0.86), sensitivity of 0.65 (95% CI: 0.54, 0.74), and specificity of 0.83 (95% CI: 0.79, 0.86) for the diagnostic value of LAMS score with a cut-off value of ≥ 4. The diagnostic odds ratio of LAMS score was 8.81 (95% CI: 6.24, 12.45). Sensitivity analyses reveled that diagnostic performance of LAMS improves when utilized for detection of occlusion in the more proximal segments of large vessels, with a sensitivity of 0.75 and specificity of 0.83. Conclusion A high level of evidence showed that LAMS scale does not have a promising diagnostic value in the identification of LVOs in suspected stroke patients. The sensitivity of 0.65 for this tool makes it obsolete as a proper triaging tool. As a suggestion, LAMS could be utilized in conjunction with other additional factors to increase its diagnostic performance

Metformin inhibits polyphosphate-induced hyper-permeability and inflammation

Circulating inflammatory factor inorganic polyphosphate (polyP) released from activated platelets could enhance factor XII and bradykinin resulted in increased capillary leakage and vascular permeability. PolyP induce inflammatory responses through mTOR pathway in endothelial cells, which is being reported in several diseases including atherosclerosis, thrombosis, sepsis, and cancer. Systems and molecular biology approaches were used to explore the regulatory role of the AMPK activator, metformin, on polyP-induced hyper-permeability in different organs in three different models of polyP-induced hyper-permeability including local, systemic shortand systemic long-term approaches in murine models. Our results showed that polyP disrupts endothelial barrier integrity in skin, liver, kidney, brain, heart, and lung in all three study models and metformin abrogates the disruptive effect of polyP. We also showed that activation of AMPK signaling pathway, regulation of oxidant/ anti-oxidant balance, as well as decrease in inflammatory cell infiltration constitute a set of molecular mechanisms through which metformin elicits it's protective responses against polyP-induced hyper-permeability. These results support the clinical values of AMPK activators including the FDA-approved metformin in attenuating vascular damage in polyP-associated inflammatory diseases.Peer reviewe

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Mapping Intellectual Structure of Published Articles in Information Retrieval during 1983-2017.

Abstract Today information and communication cause the daily growth of published information. Studying all scientific production content and structures for specialist in different fields and publications is impossible. This study aims to analyze the articles regarding information retrieval based on the concepts of co-occurrence network analysis and centrality indicators published in Clarivate Analytics Web of Science[1] during 1983-2017. This is a descriptive study, using Scientometric approach. Its statistical population contains all articles related to Information retrieval in Clarivate Analytics Web of Science during1983-2017. The scientific research on Information retrieval starts in 2002. Based on the scientific map of countries, America, England, Canada and Singapore have the most articles in information retrieval field. Iran and Brazil have also been active in research on this field from 2012. The top authors of Articles in IR field articles during 1989-2017 are: Spink, Boregman, Chowdhury and Meado. In the analysis of IR field articles based on co-word anlaysis, 8 subject cluster were observed. Among them related to internal and external factors in information retrieval