The golden rule developed by Gordon E. Moore in 1965 stands forth and upholds its perception, which is observant with trending technology and making organizations, groups and individuals extract benefits from machine. AI, Robotics, Business Intelligence, Big Data and Analytics, Edge Computing, Hyperautomation, Blockchain, Democratization, Human Augmentation, Multiexperience are technical domains and trends supporting ongoing technical progress making mankind to innovate and create superhuman capabilities leaving HRs to fight the battle of replacing technology-literate people with people-literate technology. The likeliness towards analytics and complex algorithms made a breakthrough into a creative zone extending manageable workforce with the rising trends.  https://www.selleckchem.com/ALK.html  The primary study with 108 h of leading Service Organizations of India was made to examine the recent tools and techniques for HR analytics which are adopted by them. As we recognized that analytics is driving force for HRs to be strategic business partner and step further for transforming roles. In addition we identified the implication of analytics on various HR data and decisions made by them.Anticipating the number of hospital beds needed for patients with COVID-19 remains a challenge. Early efforts to predict hospital bed needs focused on deriving predictions from SIR models, largely at the level of countries, provinces, or states. In the USA, these models rely on data reported by state health agencies. However, predicting disease and hospitalization dynamics at the state level is complicated by geographic variation in disease parameters. In addition, it is difficult to make forecasts early in a pandemic due to minimal data. Bayesian approaches that allow models to be specified with informed prior information from areas that have already completed a disease curve can serve as prior estimates for areas that are beginning their curve. Here, a Bayesian non-linear regression (Weibull function) was used to forecast cumulative and active COVID-19 hospitalizations for SD, USA, based on data available up to 2020-07-22. As expected, early forecasts were dominated by prior information, which was derived from New York City. Importantly, hospitalization trends differed within South Dakota due to early peaks in an urban area, followed by later peaks in rural areas of the state. Combining these trends led to altered forecasts with relevant policy implications.
  The online version contains supplementary material available at 10.1007/s41666-021-00094-8.
 The online version contains supplementary material available at 10.1007/s41666-021-00094-8.This paper presents a methodological proposal based on the identification of highly cited papers (HCPs) at domestic-level in the Spanish Public University System (SUPE), in order to find the most outstanding publications in the local context. The principal aim is to detect different activity and impact profiles among Spanish universities and differentiate those institutions that play a more significant role. To determine which and how many are the highly cited papers at the domestic level (HCP-DL) collected in the Web of Science, three citation thresholds (1, 5, and 10%) were established. Thematic classification in Incites/Essential Science Indicators areas is used. The results show a preponderance of HCPs in the field of Space Science, while the polytechnic universities have high visibility in the Computer Science area. It has been observed that the presence of HCPs in a given area is involved with universities specialized in teaching and research activities. In absolute terms, the big non-specialized universities are major producers of HCPs and hold the leading positions in our results. However, when efficiency is analyzed in relative terms, some small, specialized universities reveal themselves to be more efficient at producing HCPs (% of HCPs or citations per HCP). We think that this methodology, due to its simplicity, its ease of calculation, and the knowledge it provides, can be very useful to analyze the national systems of any country, in order to know the impact and visibility of the research carried out in its scientific institutions or research areas.Dimensions was built as a platform to allow stakeholders in the research community, including academic bibliometricians, to more easily create and understand the context of different types of research object through the linkages between these objects. Links between objects are created via persistent identifiers and machine learning techniques, while additional context is introduced via data enhancements such as per-object categorisations and person and institution disambiguation. While these features make analytical use cases accessible for end users, the COVID-19 crisis has highlighted a different set of needs to analyze trends in scholarship as they occur Real-time bibliometrics. The combination of full-text search, daily data updates, a broad set of scholarly objects including pre-prints and a wider set of data fields for analysis, broadens opportunities for a different style of analysis. A subset of these emerging capabilities is discussed and three basic analyses are presented as illustrations of the potential for real-time bibliometrics.The extensive collection of glossy (gl) and eceriferum (cer) mutants of maize and Arabidopsis have proven invaluable in dissecting the branched metabolic pathways that support cuticular lipid deposition. This bifurcated pathway integrates a fatty acid elongation-decarbonylative branch and a fatty acid elongation-reductive branch, which collectively has the capacity to generate hundreds of cuticular lipid metabolites. In this study, a combined transgenic and biochemical strategy was implemented to explore and compare the physiological function of three homologous genes, Gl2, Gl2-like, and CER2, in the context of this branched pathway. These biochemical characterizations integrated new extraction chromatographic procedures with high spatial resolution mass spectrometric imaging methods to profile the cuticular lipids on developing floral tissues transgenically expressing these transgenes in wild-type or cer2 mutant lines of Arabidopsis. Collectively, these datasets establish that both the maize Gl2 and Gl2-like genes are functional homologs of the Arabidopsis CER2 gene.