Globally Published Literature on Library and Information Science Professionals: A Bibliometric Review ( 1970-2021)

The study targets examining the exploration yield on the key terms of librarianship within 52 years (1970-2021). The investigation cover essentially the quantity of articles, language of articles, top research oriented organizations and countries, topmost publication source, highly productive authors, highly interested research area, commonly used keyword and so forth. A complete bibliometric study was directed utilizing the Science Citation Index data set, Web of Science (Core Collection). This research fills in as an asset for future research activities by revealing insight into librarianship.  In particular, the outcomes uncover that the mostly chosen publication category is article and the research referred to articles are from United States and the top productive organization is also from USA. The preferred language is English for publications and the most favored research area is the “Information Science Library Science” during this time span. This bibliometric research is significant for all those researchers who relates to librarianship and who need to see the publication trends in this profession

Role of Cooperative Learning in Improving Language Proficiency and Academic Achievement in English of Elementary Students: An Experimental Study

English language, as it is employed as a common medium used for communication with people, whom native language is not understandable. In this regard, Governments of developing countries paying attention to promoting English. That require upgradation in the curriculum, as well as, the shift of teaching methodology from teacher to student centered, are the basic requisites for making the change in the educational system possible. That provides opportunities for cooperative learning. Therefore the current experimental study was carried out to find the role of cooperative learning in promoting language proficiency and achievement with regards to English among 8th grade students, who are supposed to study in the private schools of Lahore. The 8th grade students enrolled in private schools of Lahore district implied the population of the study. Whereas, the two girls sections of the 8th class of The Educators School, Jinnah Campus, Lahore, were chosen as the sample and nominated as experimental and control groups. Before and after the intervention, English language proficiency tests (EPT) to measure the students' proficiency in English and English achievement test (EAT) to identify students’ achievement in English developed by the researchers were utilized. Findings highlighted that cooperative learning is an effective teaching methodology that proves beneficial in the improvement of 8th grade students' proficiency and achievement in English. It is recommended that our teachers may use such innovative teaching methodologies in their classroom that not only promote students' involvement for discussion on the relevant topi

The emergence of scholarly literature on physical/social distancing related to Coronavirus: A bibliometric analysis

Background: The world is witnessing new public health crises due to the emergence of the novel coronavirus. This study aims to present a bibliometric analysis of research on coronavirus-related physical/social distancing.Design and Methods: In this study, a bibliometric analysis was applied to see the research productivity and its impact on coronavirus-related physical/social distancing. For this purpose, Scopus was used to retrieve the data for the analysis. A total of 2900 records was downloaded from the database for analysis.Results: The findings revealed that the top four authors published their research in the year 2020. The study ranked the British Medical Journal (BMJ) at the top position on publishing the research on the topic. Similarly, the USA took the lead in all countries in producing research on the topic. The researchers preferred the document type ‘Article’ for sharing their research, and a single authorship pattern was dominated on all other patterns.Conclusion: Plenty of bibliometric studies are available on coronavirus, but not a single study is found on coronavirus-related physical/social distancing. This study will be valuable in identifying different bibliometric dimensions on the topic

Characterizing Elite Scholars of Library and Information Science: A Bibliometric Analysis

Publication metrics have become crucial to measure the productivity and impact of individuals and organizations for highlighting their influence upon the knowledge world. This study aims to present a bibliometric analysis of the top two percent highly cited Library and Information Science (LIS) researchers in the Stanford University list of the top two percent researchers of various disciplines published in 2021. We have used the bibliometric method to analyze 254 highly cited LIS researchers. The findings show male dominance and female underrepresentation in LIS research. Leydesdorff, Loet is the most highly cited researcher of the LIS field. The Amsterdam School of Communications Research, Netherlands, is the most highly cited organization of LIS based on the highly cited researchers affiliated with it. The majority of LIS researchers belong to USA and UK. There is a meager contribution of Asian, Australian, and African countries producing highly cited LIS researchers. Highly cited LIS researchers are more familiar with publishing research in information retrieval, information seeking, and bibliometrics. Positions of researchers at different ranks by different measures depict their productivity, impact, h- index, and a composite score. A strong correlation exists between total publications and total citations. The study, in its nature, is unique and will provide an insight for young and emerging researchers for selection of research direction, persons for research collaboration, and a motivation to invest more efforts for impactful research

A Bibliometric Review of Highly Cited and Hot Papers on Coronavirus and COVID 19

The main objective of the study is to identify and examine the characteristics of the highly cited and hot papers on Coronavirus and COVID 19. The distributions of highly cited and hot papers per year, country, organization and journal were analyzed, as well as authorship pattern and most frequently used keywords. The Web of Science (WOS) indexing database was selected to extract the bibliometric data of highly cited and hot papers on Coronavirus. Top cited and hot papers mainly originated from China, the United States, England, and Saudi Arabia and the majority were published from 2019 to 2020. The University of Hong Kong and Huazhong University of Science and Technology were leading organizations. Journal of Medical Virology, the Lancet and The New England Journal of Medicine were top in publishing. Many of the publications have been contributed by multiple authors as compared to a single author. The frequently used keywords included acute respiratory syndrome, pneumonia, coronavirus, outbreak, infection, respiratory syndrome coronavirus, Severe acute respiratory syndrome coronavirus (SARS-CoV), and Middle East Respiratory Syndrome coronavirus (MERS‐CoV). This bibliometric analysis of the highly cited articles on Coronavirus and COVID 19 from Web of Science has demonstrated several significant points, which help to map the progress on COVID 19 development and recent research trends and potentially guide Coronavirus researchers for evaluating and orienting their future research works

A comparative analysis of machine learning approaches for plant disease identification

Background: The problems to leaf in plants are very severe and they usually shorten the lifespan of plants. Leaf diseases are mainly caused due to three types of attacks including viral, bacterial or fungal. Diseased leaves reduce the crop production and affect the agricultural economy. Since agriculture plays a vital role in the economy, thus effective mechanism is required to detect the problem in early stages.Methods: Traditional approaches used for the identification of diseased plants are based on field visits which is time consuming and tedious. In this paper a comparative analysis of machine learning approaches has been presented for the identification of healthy and non-healthy plant leaves. For experimental purpose three different types of plant leaves have been selected namely, cabbage, citrus and sorghum. In order to classify healthy and non-healthy plant leaves color based features such as pixels, statistical features such as mean, standard deviation, min, max and descriptors such as Histogram of Oriented Gradients (HOG) have been used.Results:  382 images of cabbage, 539 images of citrus and 262 images of sorghum were used as the primary dataset. The 40% data was utilized for testing and 60% were used for training which consisted of both healthy and damaged leaves. The results showed that random forest classifier is the best machine method for classification of healthy and diseased plant leaves.Conclusion:  From the extensive experimentation it is concluded that features such as color information, statistical distribution and histogram of gradients provides sufficient clue for the classification of healthy and non-healthy plants

Effects of Seawater Salinity on Seedling Growth Nodulation and Tissue Nitrogen in Acacia nilotica (L.) Delile

A pot experiment was conducted to determine the effect of sea water salinity on growth, nodulation and nitrogen content of Acacia nilotica (L.) Delile seedlings. Eight weeks old seedlings were irrigated with 40, 50, 60, 70 and 80% sea water for one month. After 12 weeks the plants were uprooted and the nodules were observed for their frequency, shapes and sizes. Nodules showed morphological alterations in size and shape in different salinity levels. The root-shoot ratio, nitrogen contents in the leaf, stem and root were analyzed. In general salt stress resulted in a decrease of plant growth, nodulation and percent tissue nitrogen in A. nilotica plants. Root-shoot ratio showed gradual increase with increasing sea water concentrations. Nitrogen contents decreased in leaf and stem, whereas it increased in roots. Nodules showed morphological alterations in size and shape with increasing salinity. A. nilotica accumulated NaCl in the xylem of the roots that may be considered as a preliminary salt tolerant mechanism adopted by the plant

A case of pseudohyperkalemia in a patient presenting with leucocytosis and high potassium level: a Case Report

Pseudohyperkalemia can appear in a variety of settings and should be recognized early. Treatment of pseudohyperkalemia can lead to an inappropriate decrease of actual serum potassium levels which may lead to life threatening conditions. In the case presented, an 81-year-old male presented with massive leucocytosis and an extremely elevated potassium level. This case report emphasizes the importance of recognizing pseudohyperkalemia in a patient with a severely increased potassium and WBC level; such patients may be clinically asymptomatic or may have a normal ECG

A Class of Koszul Algebra and Some Homological Invariants through Circulant Matrices and Cycles

Recent advances in graph theory, linear algebra, and commutative algebra render us to tackle problems in one bough of mathematics with assistance and guidance from others. We will elaborate foremost and conceptually fathomless homological invariants inextricably linked with circulant matrices and cycles through various path lengths in this article, as well as a class of Koszul algebra, which portrays combinatorial correlation, in the end.Scopu

Early predictors in language-based learning disabilities: a bibliometric analysis

IntroductionLanguage-based learning disabilities (LBLD) refers to a spectrum of neurodevelopmental-associated disorders that are characterized by cognitive and behavioral differences in comprehending, processing and utilizing spoken and/or written language. The focus of this work was on identifying early predictors of three main specific LBLD including dyslexia, dyscalculia, and dysgraphia.MethodsThe Web of Science (WoS) was searched for literature related to (neurocognitive, neurophysiological, and neuroimaging) measurements used to identify early predictors of LBLD from 1991 to 25 October 2021. A retrospective bibliometric analysis was performed to analyze collaboration among countries, institutions, authors, publishing journals, reference co-citation patterns, keyword co-occurrence, keyword clustering, and burst keywords using Biblioanalytics software.ResultsIn total, 921 publications related to the identification of LBLD using (neurocognitive, neurophysiological, and neuroimaging) modalities were included. The data analysis shows a slow growth in research on the topic in the 90s and early 2000 and growing trend in recent years. The most prolific and cited journal is Neuroimage, followed by Neuropsychologia. The United States and Finland’s Universities Jyvaskyla and Helsinki are the leading country and institution in this field, respectively. “Neuroimaging,” “brain,” “fMRI,” “cognitive predictor,” “comorbidity,” “cortical thickness” were identified as hotspots and trends of (neurocognitive, neurophysiological, and neuroimaging) modalities in the identification of LBLD.DiscussionEarly predictors of LBLDs would be useful as targets for specific prevention and intervention programs to be implemented at very young ages, which could have a significant clinical impact. A novel finding of neuroimaging predictors combined with neurocognitive and neuropsychological batteries may have implications for future research