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Purpose: This paper examines the leading publication trends including the extent and impact of intellectual capital research in the Journal of Intellectual Capital (JIC) over a two-decade period (2000–2020). The bibliometric analysis offers the description of publications trends such as key authors, articles, cited references, institutions and countries— in other words the extent and impact in the field. This paper also presents the knowledge structure (including conceptual, intellectual and social structures) of JIC, that is prominent themes, co-citation and bibliographic networks. Design/methodology/approach: In order to achieve research objectives, we collected the bibliographic information of the articles published in JIC for the period 2000 to 2020 from the Scopus database on 11.04.2020. The bibliographic information of 737 documents were analysed using to open source analysis tool, that is bibliometrics package in r software and VOSviewer. These tools were used to create the graphical visualization of bibliographic data on basis of co-occurrence, co-citation and bibliographic coupling. Findings: The results show that the journal is progressing in terms of publication quantity and reputation in the field. To date, 737 documents have been published in JIC, which includes 659 research articles, eight editorials, seven notes and 63 review papers. This paper also portrays the author impact list in terms of most impactful articles published in JIC. Country-wise Italy, Australia, and USA exert maximum influence on JIC scholarship. Originality/value: Bibliographic analysis offers a comprehensive understanding of past trends and presents the future direction of a journal. [ABSTRACT FROM AUTHOR]

With more and more political candidates using social media for campaigning, researchers are looking at measuring the effectiveness of this medium. Most research, however, concentrates on the bare count of likes (or twitter mentions) in an attempt to correlate social media presence and winning. In this paper, we propose a novel method, Interaction Strength Plot (IntS) to measure the passive interactions between a candidate’s posts on Facebook and the users (liking the posts). Using this method on original Malaysian General Election (MGE13) and Australian Federal Elections (AFE13) Facebook Pages (FP) campaign data, we label an FP as performing well if both the posting frequency and the likes gathered are above average. Our method shows that over 60% of the MGE13 candidates and 85% of the AFE13 candidates studied in this paper had under-performing FP. Some of these FP owners would have been identified as popular based on bare count. Thus our performance chart is a vital step forward in measuring the effectiveness of online campaigning. [ABSTRACT FROM AUTHOR]

The $20m Australian Urban Research Infrastructure Network (AURIN) project () began in July 2010. AURIN has been tasked with developing a secure, Web-based virtual environment (e-Infrastructure) offering seamless, secure access to diverse, distributed and extremely heterogeneous data sets from numerous agencies with an extensive portfolio of targeted analytical and visualization tools. This is being provisioned for Australia-wide urban and built environment researchers - itself a highly heterogeneous collection of research communities with diverse demands, through a unified urban research gateway. This paper describes these demands and how the e-Infrastructure and gateway is being designed and implemented to accommodate this diversity of requirements, both from the user/researcher perspective and from the data provider perspective. The scaling of the infrastructure is presented and the way in which it copes with the spectrum of big data challenges (volume, veracity, variability and velocity) and associated big data analytics. The utility of the e-Infrastructure is also demonstrated through a range of scenarios illustrating and reflecting the interdisciplinary urban research now possible. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

As more and more photovoltaic (PV) systems are integrated into the grid, the intelligent operation of the grid system is facing significant challenges. Therefore, accurately forecasting PV power output at various time scales is particularly urgent. To meet this demand, this paper proposes an LSTM-Informer model based on an improved Stacking ensemble algorithm (ISt-LSTM-Informer). The proposed model improves the k-fold cross validation in the traditional Stacking algorithm to a time-series cross validation for integrating time-series forecasting models. Simultaneously, it utilizes long short-term memory (LSTM) and Informer as the base models. By integrating the advantages of the two base models, the ISt-LSTM-Informer achieves accurate short and medium-term PV power forecasting. To validate the effectiveness of the model, a historical dataset from a PV system located in Uluru, Australia, is used for various types of experiments. Among them, comparative experiments validate the superiority of the model. Compared with five other methods, the ISt-LSTM-Informer obtains 21 optimal results for the four evaluation metrics of RMSE, MAE, MAPE, and R 2 across eight forecasting time scales. In addition, different combinations of base models are conducted to verify the advantages of the Stacking ensemble algorithm and the two base models, respectively. • A novel multi-timescale photovoltaic power forecasting model is proposed. • Time-series cross validation is introduced into the Stacking algorithm. • LSTM and Informer are utilized as the base models of the Stacking algorithm. • Various methods are compared to verify the proposed model's effectiveness. • The model's predictive accuracy is illustrated through various visualization methods. [ABSTRACT FROM AUTHOR]

Police tactical group (PTG) personnel are exposed to physical, mental, and emotional stressors. Consequently, PTG selection courses (SCs) impart similar challenges, often resulting in candidate attrition. Holistic assessment may provide additional support to stakeholders given these risks. Heart Rate Variability (HRV) is an objective holistic stress measure that may be applicable in PTG SCs but has not been thoroughly researched. Therefore, this study aimed to report HRV data in an end-user accessible format and determine the relationship between HRV and attrition. A total of 18 qualified Australian State law enforcement officers completed a 1-day physical readiness assessment. Of those, six males progressed to an additional two-day course, on which this study is focused. This two-day selection consisted of additional physical challenges and occupational assessments. HRV was obtained from 2-lead ECGs and defined as the percentage of R-R intervals that varied by ≥50 ms (pRR50). Data were summarized in a heat map of consecutive short-term analyses. Three candidates withdrew. A logistic regression based on heat map data found high HRV was significant for predicting attrition, χ2 (6) = 8.318, p = 0.004. HRV may provide insight for PTG stakeholders monitoring attrition. While the sample size was limited and replication is needed, this study tentatively establishes value for HRV monitoring in PTG SCs. [ABSTRACT FROM AUTHOR]

The massive property development of high-rises and complex structures above and below the ground surface in cities indicates the lack of land and high demand to use spaces. However, the existing land and property administration systems are mainly two dimensional and not capable of efficiently managing these complex spaces. As ownership rights on plans are recorded in paper or PDF, understanding these rights and making effective decisions and analyses can be difficult without having experience in the art of reading and interpreting plan information. This paper attempts to address these issues by presenting a prototype for visualizing three-dimensional land and property information. The aim of this prototype is to illustrate and communicate the requirements and benefits of a 3D digital cadastre platform. The prototype is a web-based application and includes functionality to display both legal and physical data, interact with 3D models, display administrative data, identify objects and search objects, visualize cross-sections, and undertake measurements in 3D. For this prototype, a multi-story building was selected as a case study and its 3D model was imported into the prototype to display ownership rights. The prototype was then evaluated by various stakeholders and their feedback was considered for future enhancement. [ABSTRACT FROM AUTHOR]

Background and Objectives: Cardiovascular disease is a long-term threat to global public health security, while sedentary behavior is a modifiable behavior among cardiovascular risk factors. This study aimed to analyze the peer-reviewed literature published globally on sedentary behavior and cardiovascular disease (SB-CVD) and identify the hotspots and frontiers within this research area. Materials and Methods: Publications on SB-CVD from 1990 to 2022 were retrieved from the Web of Science Core Collection. CiteSpace and VOSviewer were applied to perform bibliometric and knowledge mapping visualization analyses. Results: A total of 2071 publications were retrieved, presenting a gradual growing trend. Authors from the USA topped the list with 748 (36.12%), followed by authors from England (373, 18.01%) and Australia (354, 17.09%). The University of Queensland, Australia, led with 95 (4.5%) publications. The top five active authors were all from Australia, while Dunstan D and Owen N published the most documents (56, 2.7%). A total of 71.27% of the publications received funding, and the United States Department of Health and Human Services provided 363 (17.53%) grants. Public Environmental Occupational Health (498, 24.05%), Sport Sciences (237, 11.44%), and Cardiac Cardiovascular Systems (212, 10.24%) were the three most popular disciplines, while PLOS One (96, 4.64%) and BMC Public Health (88, 4.25%) were the two most popular journals. Investigations within the SB-CVD research area addressed the entire lifespan, the most popular type of research was the epidemiological study, and the accelerometer was the primary instrument for measuring sedentary behavior. In terms of variables, physical activity and sedentary behavior were the dominant lifestyle behaviors, while obesity and hypertension were common health problems. Occupational physical activity and guidelines are at the frontier and are currently in the burst stage. Conclusions: The last three decades have witnessed the rapid development of the SB-CVD research area, and this study provided further research ideas for subsequent investigations. [ABSTRACT FROM AUTHOR]

In many countries around the world (including Australia), the prescribing of opioid analgesic drugs is an increasing trend associated with significant increases in drug-related patient harm such as abuse, overdose, and death. In Australia, the Medicines Regulation and Quality Unit within Queensland Health maintains a database recording opioid analgesic drug prescriptions dispensed across the State (population 4.703 million). In this work, we propose the use of network visualisation and analysis as a tool for improved understanding of these data. Prescribing data for Fentanyl patches, a strong opioid with high potential for misuse and subsequent harm, across Queensland, Australia from 2011 to 2018 is analysed as an example of using network analysis, where prescribing patterns are viewed as a dynamic, bipartite graph of the interactions between patients and prescribers over time. The technique provides a global view of a large state-wide prescribing dataset, including the distribution of subgraph structures present. Local analysis is also carried out to demonstrate the clinical utility of the technique, including the dynamics of the graph structure over time. A variety of network statistics that measure network structural and dynamic properties are presented to reveal the characteristics and trends of drug seeking and prescribing behaviours. This approach has been recognised by healthcare professionals at Queensland Health as leading to new and useful insights on the relationship between patients and prescribers and supporting their advisory role to reduce patient harm from inappropriate use of prescription drugs. [ABSTRACT FROM AUTHOR]

Background: Administrative data are used to examine variation in thirty-day mortality across health services in several jurisdictions. Hospital performance measurement may be error-prone as information about disease severity is not typically available in routinely collected data to incorporate into case-mix adjusted analyses. Using ischaemic stroke as a case study, we tested the extent to which accounting for disease severity impacts on hospital performance assessment. Methods: We linked all recorded ischaemic stroke admissions between July, 2011 and June, 2014 to death registrations and a measure of stroke severity obtained at first point of patient contact with health services, across New South Wales, Australia’s largest health service jurisdiction. Thirty-day hospital standardised mortality ratios were adjusted for either comorbidities, as is typically done, or for both comorbidities and stroke severity. The impact of stroke severity adjustment on mortality ratios was determined using 95% and 99% control limits applied to funnel plots and by calculating the change in rank order of hospital risk adjusted mortality rates. Results: The performance of the stroke severity adjusted model was superior to incorporating comorbidity burden alone (c-statistic = 0.82 versus 0.75; N = 17,700 patients, 176 hospitals). Concordance in outlier classification was 89% and 97% when applying 95% or 99% control limits to funnel plots, respectively. The sensitivity rates of outlier detection using comorbidity adjustment compared with gold-standard severity and comorbidity adjustment was 74% and 83% with 95% and 99% control limits, respectively. Corresponding positive predictive values were 74% and 91%. Hospital rank order of risk adjusted mortality rates shifted between 0 to 22 places with severity adjustment (Median = 4.0, Inter-quartile Range = 2–7). Conclusions: Rankings of mortality rates varied widely depending on whether stroke severity was taken into account. Funnel plots yielded largely concordant results irrespective of severity adjustment and may be sufficiently accurate as a screening tool for assessing hospital performance. [ABSTRACT FROM AUTHOR]

Objective: Children with severe obesity have greater risk of adverse health outcomes. The purpose of this study was to assess trends in the prevalence of morbid and severe obesity in Australian children between 1985 and 2012. Methods: Secondary analysis of four national Australian cross-sectional surveys of measured height/weight in 7–15 year olds: Australian Health and Fitness Survey 1985 (n = 8,486), National Nutrition Survey 1995 (n = 1,541), the National Children’s Nutrition and Physical Activity Survey 2007 (n = 2,585) and the National Health Survey 2012 (n = 2,940). International Obesity Taskforce cut-point was used for morbid obesity (equivalent to a BMI ≥35kg/m2 at age 18 years). Severe obesity class 2 was defined as BMI ≥120% and <140% of the 95th percentile of the CDC 2000 growth charts or a BMI ≥35 and <40, and severe obesity class 3 as BMI ≥140% of the 95th percentile or a BMI ≥40. Results: Between 1985 and 2012 the prevalence of morbid obesity increased from 0.2% to 1.8%, class 2 severe obesity from 0.3% to 2.0%, and class 3 from 0.1% to 0.5%. Children with morbid obesity represented 11.3% of children with obesity in 1985 and increased to 22.5% in 2012 (P = 0.005). Children with severe obesity represented 19.3% of children with obesity in 1985 and increased to 32.0% in 2012 (P = 0.016). The greatest increase was observed between 1995 and 2007. The proportion of children who were classified as morbidly or severely obese was not significantly different between 2007 and 2012, nor was it significantly different between age and sex groups. Conclusion: Prevalence of morbid and severe obesity among children is low, but has significantly increased between 1985 and 2012. In contrast to overweight and obese children, children with morbid obesity require tertiary intervention. Failure to treat these children will have significant implications for the individual child and community. [ABSTRACT FROM AUTHOR]