125,465 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

    No full text
    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Dispelling the Myths Behind First-author Citation Counts

    No full text
    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Motor and non-motor symptoms in advanced Parkinson’s disease: current insights and future directions

    No full text
    Advanced Parkinson’s disease (PD) is characterized by significant motor and non-motor complications, including levodopa-resistant symptoms such as freezing of gait (FoG), postural instability, and dysphagia, alongside autonomic dysfunction. As the disease progresses, managing these symptoms becomes increasingly complex. This thesis explores the role of advanced therapies, including levodopa-carbidopa intestinal gel (LCIG) and deep brain stimulation (DBS), in addressing some disabling symptoms such as postural abnormalities, freezing of gait (Fog), speech disturbance, and some nonmotor symptoms such as dysautonomic disturbance and pain. Additionally, it investigates the role of monoamine oxidase type B (MAO-B) inhibitors in managing both motor and cognitive fluctuations in advanced PD. Integrating wearable sensor technologies allows continuous monitoring of motor complications such as dyskinesias and FoG daily, offering a novel approach to individualized treatment. This thesis stresses the demand for a multidisciplinary, patient-centered approach to managing advanced PD, with particular attention to autonomic dysfunctions and axial symptoms, potentially aided by using wearable sensors to obtain an objective measurement to improve the patient’s quality of life
    corecore