Importance of the code of ethics in the organization

Counteracting the unethical actions and influencing the behavior of the human factor towards ethical behavior must be a priority of a company’s policy. The research and recommendations in this direction outline the necessity of an Ethic code that shall comprise individual and company values, and whose harmonious interaction shall provide stability and efficiency of the management process. This code shall serve as a balancing force among the various interests and systems of values, which shall thus establish common ethical standards of behavior.Протидія антіетичним діям и вплив етичної поведінки на поведінку людського фактору повинні бути пріоритетом політики компанії. Дослідження та рекомендації в цьому напрямку дозволили намітити необхідність в етичному кодексі, який повинен включати індивідуальні та організаційні цінності, і гармонічну взаємодію, яка забезпечує стабільність і ефективність процесу управління. Цей кодекс буде виступати в якості врівноважуючої сили між різними інтересами та системами цінностей, які встановлюють загальні етичні норми поведінки.Противодействие неэтичным действиям и влияние этического поведения на поведение человеческого фактора должны быть приоритетом политики компании. Исследования и рекомендации в этом направлении позволили наметить необходимость в этическом кодексе, который должен включать в себя индивидуальные и организационные ценности, и гармоничное взаимодействие обеспечивающее стабильность и эффективность процессауправления. Этот кодекс будет выступать в качестве уравновешивающей силы между различными интересами и системами ценностей, которые должны, таким образом, установить общие этические нормы поведения

Simulations of inner magnetosphere dynamics with an expanded RAM-SCB model and comparisons with Van Allen Probes observations

Abstract Simulations from our newly expanded ring current-atmosphere interactions model with self-consistent magnetic field (RAM-SCB), now valid out to 9 R E, are compared for the first time with Van Allen Probes observations. The expanded model reproduces the storm time ring current buildup due to the increased convection and inflow of plasma from the magnetotail. It matches Magnetic Electron Ion Spectrometer (MagEIS) observations of the trapped high-energy (\u3e50 keV) ion flux; however, it underestimates the low-energy (\u3c10 keV) Helium, Oxygen, Proton, and Electron (HOPE) observations. The dispersed injections of ring current ions observed with the Energetic particle, Composition, and Thermal plasma (ECT) suite at high (\u3e20 keV) energy are better reproduced using a high-resolution convection model. In agreement with Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) observations, RAM-SCB indicates that the large-scale magnetic field is depressed as close as ∼4.5 RE during even a moderate storm. Regions of electromagnetic ion cyclotron instability are predicted on the duskside from ∼6 to ∼9 RE, indicating that previous studies confined to geosynchronous orbit may have underestimated their scattering effect on the energetic particles. Key Points Expanded RAM-SCB model reproduces well high-energy (\u3e50 keV) MagEIS observations The magnetic field is depressed as close as ∼4.5 RE during even a moderate storm EMIC wave growth extends on duskside from ∼6 to ∼9 RE during storm main phase

Application and testing of the L neural network with the self-consistent magnetic field model of RAM-SCB

Abstract We expanded our previous work on L neural networks that used empirical magnetic field models as the underlying models by applying and extending our technique to drift shells calculated from a physics-based magnetic field model. While empirical magnetic field models represent an average, statistical magnetospheric state, the RAM-SCB model, a first-principles magnetically self-consistent code, computes magnetic fields based on fundamental equations of plasma physics. Unlike the previous L neural networks that include McIlwain L and mirror point magnetic field as part of the inputs, the new L neural network only requires solar wind conditions and the Dst index, allowing for an easier preparation of input parameters. This new neural network is compared against those previously trained networks and validated by the tracing method in the International Radiation Belt Environment Modeling (IRBEM) library. The accuracy of all L neural networks with different underlying magnetic field models is evaluated by applying the electron phase space density (PSD)-matching technique derived from the Liouville\u27s theorem to the Van Allen Probes observations. Results indicate that the uncertainty in the predicted L is statistically (75%) below 0.7 with a median value mostly below 0.2 and the median absolute deviation around 0.15, regardless of the underlying magnetic field model. We found that such an uncertainty in the calculated L value can shift the peak location of electron phase space density (PSD) profile by 0.2 RE radially but with its shape nearly preserved. Key Points L* neural network based on RAM-SCB model is developed L* calculation accuracy is estimated by PSD matching using RBSP data L* uncertainty causes a radial shift in the electron phase space density profile

Global, collisional model of high‐energy photoelectrons

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95539/1/grl8976.pd

A bounce‐averaged kinetic model of the ring current ion population

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94668/1/grl7966.pd

Energy Content of the Stormtime Ring Current

Given the important role the ring current plays in magnetospheric energetics, it is essential to understand its strength and evolution in disturbed times. There are currently three main methods for deducing the strength of the ring current: measuring ground magnetic perturbations, measuring high-altitude magnetic perturbations, or directly measuring ring current particles. The use of ground magnetometers is the most convenient, and many use the ground magnetometer-derived Dst index as a proxy for the ring current. Recent work suggests, however, that a substantial portion of Dst may not be caused only by the ring current but also by local induction effects or other magnetospheric currents, so simply using the Dst index may yield inaccurate results. This study uses direct particle measurements to calculate the strength of the ring current and compares this to the measured Dst values. We investigate several magnetic storm intervals, using the Polar Charge and Mass Magnetospheric Ion Composition Experiment (CAMMICE) to measure ring current ions. We then use the Dessler-Parker-Sckopke relation to compare this to the measured Dst. This analysis is used both to understand the general behavior of the ring current compared to Dst as well as to compare the usefulness of the Dst proxy for different types of storms. Ring current ions are shown in this analysis to contribute, on average, half of the Dst depression, with a large variation among individual events

Excitation of EMIC waves detected by the Van Allen Probes on 28 April 2013

Abstract We report the wave observations, associated plasma measurements, and linear theory testing of electromagnetic ion cyclotron (EMIC) wave events observed by the Van Allen Probes on 28 April 2013. The wave events are detected in their generation regions as three individual events in two consecutive orbits of Van Allen Probe-A, while the other spacecraft, B, does not detect any significant EMIC wave activity during this period. Three overlapping H+ populations are observed around the plasmapause when the waves are excited. The difference between the observational EMIC wave growth parameter (Eh) and the theoretical EMIC instability parameter (Sh) is significantly raised, on average, to 0.10 ± 0.01, 0.15 ± 0.02, and 0.07 ± 0.02 during the three wave events, respectively. On Van Allen Probe-B, this difference never exceeds 0. Compared to linear theory (Eh\u3eSh), the waves are only excited for elevated thresholds