ON THE PROBLEMS IN THEORETICAL PHYSICS – AN OUTLINE

The current paper falls under the category of a series of papers on The General Theory of electromagnetic field. The various problems in theoretical physics include those of electrodynamics, electromagnetism, Newtonian laws, Quantum mechanical laws, Maxwell-Lorentz equations etc which serve as some examples. This paper discusses some important aspects of theoretical physics in the framework of mathematics being used as a very important tool for explaining the natural physical laws. Hence, this paper fulfills the purpose of an introductory overview about the different problems in theoretical physics and the various inter-connectivities

GEOMAGNETISM – A HISTORICAL REVIEW

This specific paper addresses the historical events that had led in the current scenario, to the development of one of the most important fundamental research areas – Geomagnetism, which might even date back to probably millions of years embedded in the core scientific aspects of even ancient civilizations. The solar wind and its associated magnetic field have their source in the Sun and their interaction with the geo-magnetic field which extends into outer space has its origin inside the earth's core. Needless to say, the contributions of many scientific researchers on the dynamics of upper, middle and lower atmospheres of the earth is really outstanding and remarkable, but certain important aspects appear to have been missed. Hence, the Sun-Earth Connectivity is of utmost importance to Space-weather researchers. Moreover, the Sun-earth connectivity through the geomagnetic storm is a process which is still less understood. Space-weather researchers face huge challenges as the geomagnetic storms turn out to be more dangerous and disastrous at times and hence, the aftermath consequences are seen clearly on the ground level and space based technological systems. A gradual understanding of the root level causes can lead to solutions with certain good accuracies which in turn can be helpful in sorting out the various space based and ground based technological challenges. The Real-Time Disturbance Storm time index measured for the month of january 2018 is shown below. The decrease in the earth's magnetic field is clearly shown

A Compendium of Potential Biomarkers of Pancreatic Cancer

Akhilesh Pandey and colleagues describe a compendium of potential biomarkers that can be systematically validated by the pancreatic cancer community

Impacts of Travel Activity and Urbanicity on Exposures to Ambient Oxides of Nitrogen and on Exposure Disparities

Daily exposures to ambient oxides of nitrogen were estimated here for residents of Hillsborough County, FL. The 2009 National Household Travel Survey provided geocoded data on fixed activity locations during each person-day sampled. Routes between activity locations were calculated from transportation network data, assuming the quickest travel path. To estimate daily exposure concentrations for each person-day, the exposure locations were matched with diurnally and spatially varying ambient pollutant concentrations derived from CALPUFF dispersion model results. The social distribution of exposures was analyzed by comparing frequency distributions of grouped daily exposure concentrations and by regression modeling. To investigate exposure error, the activity-based exposure estimates were also compared with estimates derived using residence location alone. The mean daily activity-based exposure concentration for the study sample was 17 μg/m3, with values for individual person-day records ranging from 7.0 to 43 μg/m3. The highest mean exposure concentrations were found for the following groups: black (20 μg/m3), below poverty (18 μg/m3), and urban residence location (22 μg/m3). Urban versus rural residence was associated with the largest increase in exposure concentration in the regression (8.3 μg/m3). Time in nonresidential activities, including travel, was associated with an increase of 0.2 μg/m3 per hour. Time spent travelling and at nonresidential locations contributed an average of 6 and 24 %, respectively, to the daily estimate. A mean error of 3.6 %, with range from −64 to 58 %, was found to result from using residence location alone. Exposure error was highest for those who travel most, but lowest for the sociodemographic subgroups with higher mean exposure concentrations (including blacks and those from below poverty households). This work indicates the importance of urbanicity to social disparities in activity-based air pollution exposures. It also suggests that exposure error due to using residence location may be smaller for more exposed groups

Agent-Based Modeling to Estimate Exposures to Urban Air Pollution from Transportation: Exposure Disparities and Impacts of High-Resolution Data

Better understanding of the complex links between urban transportation, land use, air quality, and population exposure is needed to improve urban sustainability. A goal of this study was to develop an exposure modeling framework that integrates agent-based activity and travel simulation with air pollution modeling for Tampa, Florida. We aimed to characterize exposure and exposure inequality for traffic-related air pollution, and to investigate the impacts of high-resolution information on estimated exposure. To do these, we developed and applied a modeling framework that combines the DaySim activity-based travel demand model, the MATSim dynamic traffic assignment model, the MOVES mobile source emissions estimator, and the R-LINE dispersion model. Resulting spatiotemporal distributions of daily individual human activity and pollutant concentration were matched to analyze population and subgroup exposure to oxides of nitrogen (NOx) from passenger car travel for an average winter day in 2010. Four scenarios using data with different spatiotemporal resolutions were considered: a) high resolution for both activities and concentrations, b) low resolution for both activities and concentrations, c) high resolution for activities, but low resolution for concentrations, and d) vice versa. For the high-resolution scenario, the mean daily population exposure concentration of NOx from passenger cars was 10.2 μg/m3; individual exposure concentrations ranged from 0.2 to 145 μg/m3. Subgroup mean exposure was higher than the population mean for individuals living below-poverty (by ~16%), those with daily travel time over one hour (8%), adults aged 19–45 (7%), blacks (6%), Hispanics (4%), Asians (2%), combined other non-white races (2%), people from middle income households (2%), and residents of urban areas (2%). The subgroup inequality index (a measure of disparity) largely increased with concentration up to the 90th percentile level for these groups. At higher levels, disparities increased sharply for individuals from below poverty households, blacks, and Hispanics. Low-resolution simulation of both activities and concentrations decreased the exposure estimates by 10% on average, with differences ranging from eight times higher to ~90% lower

Impacts of Travel Activity and Urbanicity on Exposures to Ambient Oxides of Nitrogen and on Exposure Disparities

Daily exposures to ambient oxides of nitrogen were estimated here for residents of Hillsborough County, FL. The 2009 National Household Travel Survey provided geocoded data on fixed activity locations during each person-day sampled. Routes between activity locations were calculated from transportation network data, assuming the quickest travel path. To estimate daily exposure concentrations for each person-day, the exposure locations were matched with diurnally and spatially varying ambient pollutant concentrations derived from CALPUFF dispersion model results. The social distribution of exposures was analyzed by comparing frequency distributions of grouped daily exposure concentrations and by regression modeling. To investigate exposure error, the activity-based exposure estimates were also compared with estimates derived using residence location alone. The mean daily activity-based exposure concentration for the study sample was 17 μg/m3, with values for individual person-day records ranging from 7.0 to 43 μg/m3. The highest mean exposure concentrations were found for the following groups: black (20 μg/m3), below poverty (18 μg/m3), and urban residence location (22 μg/m3). Urban versus rural residence was associated with the largest increase in exposure concentration in the regression (8.3 μg/m3). Time in nonresidential activities, including travel, was associated with an increase of 0.2 μg/m3 per hour. Time spent travelling and at nonresidential locations contributed an average of 6 and 24 %, respectively, to the daily estimate. A mean error of 3.6 %, with range from −64 to 58 %, was found to result from using residence location alone. Exposure error was highest for those who travel most, but lowest for the sociodemographic subgroups with higher mean exposure concentrations (including blacks and those from below poverty households). This work indicates the importance of urbanicity to social disparities in activity-based air pollution exposures. It also suggests that exposure error due to using residence location may be smaller for more exposed groups