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Frontiers | Job Insecurity, Work-Related Flow, and Financial Anxiety in the Midst of COVID-19 Pandemic and Economic Downturn

Frontiers | Job Insecurity, Work-Related Flow, and Financial Anxiety in the Midst of COVID-19 Pandemic and Economic Downturn
frontiersin.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from frontiersin.org Daily Mail and Mail on Sunday newspapers.

New York , United States , Thousand Oaks , Eteläuomen Läi , Saudi Arabia , San Diego , United Kingdom , City Of , Mihali Csikszentmihalyi , Los Angeles , American Psychiatric Association , Your Health , Palgrave Macmillan , Us Census Bureau , Umm Al Qura University , Anxiety Disorder American Psychiatric Association , Cambridge University Press , Congressional Budget Office , Health Psychol , Us Bureau Of Labor Statistics , Oxford University , Cambridge University , Household Pulse , Harcourt Brace Jovanovich , American Psychological Association , Sj Lopez Oxford University ,

Pharmaceutical Patent Perceptions in Japan

Background: The recent trend of pharmaceutical companies commercializing new objects as new drugs based on the findings of academic medical researchers, commonly categorizing them as “academic drug discovery” is increasingly gaining popularity in the pharmaceutical industry. Studies state that academic researchers based in universities have lower motivation to apply for patents. However, none of the studies evaluated the existence and extent of the “motivation for patent” in academic researchers, being lower than that of pharmaceutical companies. This study assesses two hypotheses; H1: academic medical researchers are less likely to believe that the patent system is necessary for pharmaceuticals, and thus have diminished interest in the commercialization of their research findings when compared to those in the pharmaceutical industry, H2: apprehension of the raison d’être of the patent system affects positive impressions on patents among academic medical researchers. ....

United States , Howard Florey , Alexander Fleming , Jikei University School Of Medicine , Kyoto University , Property Association Of Japan , Sapporo Medical University , Sapporo Medical University In Hokkaido , Kanazawa Institute Of Technology , Japan Pharmaceutical Manufacturers Association , Osaka Institute Of Technology , Japan Agency For Medical Research , Meiji University , Tokyo University Of Science , Core Research Facilities , Patent Law , Nobel Prize , Jikei University School , Drug Discovery Medicine , Graduate School , Intellectual Property Association , Kanazawa Institute , Tokyo University , Osaka Institute , Root Mean Square Residual , Goodness Of Fit Index ,

Geostationary Earth Orbit Hyperspectral Infrared Radiance data improve local severe storm forecasts proofed by using a new Hybrid OSSE method

Scientists are developing data assimilation methods for Numerical Weather Prediction models that will increase the quality of initialization data from satellites. The Observing System Simulation Experiment (OSSE) is designed to use data assimilation to investigate the potential impact of future atmospheric observing systems. Traditional OSSE processes require significant effort to compute, simulate, and calibrate information, then assimilate the data to produce a forecast. Therefore, model meteorologists are working to make this process more efficient. ....

United States , Jun Li , University Of Wisconsin , Madison Cooperative Institute For Meteorological Satellite , Advances In Atmospheric Sciences , Observing System Simulation Experiment , Wisconsin Madison Cooperative Institute , Meteorological Satellite , Atmospheric Sciences , Fengyun Meteorological Satellites , Great Plains , Midwestern United States , Root Mean Square Error , Atmospheric Science , Earth Science , Space Planetary Science , Satellite Missions Shuttles , ஒன்றுபட்டது மாநிலங்களில் , ஜூன் லி , பல்கலைக்கழகம் ஆஃப் விஸ்கான்சின் , மாடிசன் கூட்டுறவு நிறுவனம் க்கு வானிலை செயற்கைக்கோள் , விஸ்கான்சின் மாடிசன் கூட்டுறவு நிறுவனம் , வானிலை செயற்கைக்கோள் , வளிமண்டலம் அறிவியல் , நன்று சமவெளி , மத்திய மேற்கு ஒன்றுபட்டது மாநிலங்களில் ,

"Improving rock mechanical properties estimation using machine learning" by Ruizhi Zhong, Matt Tsang et al.

ABSTRACT: Rock mechanical properties (e.g., uniaxial compressive strength or UCS, Young’s modulus, and Poisson’s ratio) are important input parameters for geotechnical assessment and excavation designs. Two common methods used to obtain these parameters are laboratory testing and geophysical logging. The former delivers probably the most reliable results, but can be costly and time-consuming and for a lot of the time it is challenging to source sufficient samples. Alternative ways to better predict rock mechanical properties are needed.
In this case study, the XGBoost machine learning algorithm was applied to correlate laboratory and geophysical logging data with the three mechanaical properties of UCS, Young’s modulus, and Poisson’s ratio. The proposed machine learning approach better predicted UCS values with a smaller Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) and a larger R2. Similarly, better results were obtained for the Young’s modulus prediction us ....

Mean Absolute Error , Root Mean Square Error , சராசரி பிழை , வேர் சராசரி சதுரம் பிழை ,