A Systematic Study on Berthing Capacity Assessment of Sanya Yazhou Fishing Port by Typhoon Prediction Model

This paper sheds light on the effect of combination modes on the evaluation of berthing capacity for Sanya Yazhou Fishing Port (SYFP) under hypothetical typhoon conditions. By statistically analysing the maximum probability of moving speeds and directions of historical typhoons passing through the fishing port, the representative typhoon path was determined with the nonparametric regression method. The designed typhoon wind fields of levels 12–17 were generated based on Holland’s parametric wind model. Then, the MIKE 21 BW model was used to obtain the high-precision wave distribution in the fishing port. The boundary conditions (significant wave height and peak period) of the MIKE 21 BW model were calculated by combining the MIKE 21 SW model with the designed typhoon wind fields. In SYFP, ships usually adopt the modes of multi-ship side-by-side and single anchor mooring during typhoons. In fair weather, approximately 158 vessels can be berthed if they are all large ones, while approximately 735 vessels can be moored if they are all small ones. However, with an increase in typhoon levels, the anchoring area for small vessels decreases. From the perspective of wave distribution in the fishing port, the number of large vessels moored was hardly affected by typhoons. This can be attributed to the breakwater, which significantly decreases the large wave height in the fishing port. Finally, a study on the framework of a method for hazard assessment of berthing capacity in the coming typhoon-driven storm waves was set up.

Near-inertial wave modulated turbulence in a Kuroshio anticyclonic eddy

<p>Storm-generated near-inertial waves are a significant source for deep-ocean mixing. However, their energy pathways beyond wind generation and equatorward propagation as low modes are still elusive. Previous studies suggest that the bulk of inertial wind power is lost in the nearfield of storm forcing, but there is little observational evidence to confirm this.</p><p>Finescale horizontal velocity, temperature, salinity and microscale temperature profiles to 500-m depth were collected in the Kuroshio-Oyashio Confluence east of Japan during the storm-seasons of 2016 and 2017 with chi-augmented EM-APEX floats. Temporal sampling was at 1-h resolution during storms, sufficient to resolve near-inertial motions. Turbulent dissipation rates  and diapycnal diffusivities K were inferred from microscale temperature-gradient spectra.  Several floats were trapped near the velocity maximum of anticyclonic eddies.  Mesoscale eddies are known to trap and amplify near-inertial waves and to modulate near-inertial wave distribution and dissipation.</p><p>Near-inertial energy-fluxes within the eddy are mostly inward and downward. Signatures of a critical layer, e.g., increasing vertical wavenumbers, shear, and turbulence are present at the depth where the eddy vorticity approaches the surface value, and strong vertical mean shears and vorticity-gradients occur. Turbulence is reduced by a factor of 10 above 180-m depth, despite elevated near-inertial energy, and enhanced between 200 and 255 m. Three mechanisms for the generation of enhanced turbulence are hypothesized: i) local and remotely forced near-inertial waves superimposing to create shear-unstable layers, ii) kinematic superposition of eddy and near-inertial shear that generates patches of turbulence at inertial periods, iii) a near-inertial critical layer due to dynamic wave/mean interaction. Ray tracing simulations will be performed to examine whether vertical vorticity gradients and/or Doppler shifting are responsible for the presence of a critical layer.</p>

Applying Quantum Mechanics for Extreme Value Prediction of VaR and ES in the ASEAN Stock Exchange

The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the non-novel quantum mechanism, it does interestingly connect with the distributional signals of humans’ brainstorms. The highlighted purpose of this article is to devise a quantum-wave distribution methodically to analyze better risks and returns for stock markets in The Association of Southeast Asian Nations (ASEAN) countries, including Thailand (SET), Singapore (STI), Malaysia (FTSE), Philippines (PSEI), and Indonesia (PCI). Data samples were observed as quarterly trends between 1994 and 2019. Bayesian statistics and simulations were applied to present estimations’ outputs. Empirically, quantum distributions are remarkable for providing “real distributions”, which computationally conform to Bayesian inferences and crucially contribute to the higher level of extreme data analyses in financial economics.

Modeling of COVID-19 total hospitalizations in the United States

The SARS-CoV-2 (COVID-19) virus continues to increase across the globe affecting allaspects of modern life. It remains unknown whether COVID-19 hospitalizations can be effectivelymodeled using regression analysis. Specifically, it is unknown which regression model mayaccurately reflect past or future trends in COVID-19 hospitalizations. We wanted to see whetherwe could develop a simple model to describe both previous and future COVID-19 hospitalizations.The graph for total hospital admissions for COVID-19 shows a curve similar to a sine wave withpeaks in total hospitalizations occurring in April, July, and December. We used regression analysisfor total COVID-19 hospitalizations to provide insight into potential factors influencing COVID-19hospitalizations and predict future hospitalizations. We found that the total hospitalizations in theUnited States followed a sine-wave distribution with peaks in hospitalizations every 3.5 monthsbetween April and November 2020. However, the sine-wave distribution for COVID-19 disappearedwhen the model was extended to December 2020. In general, mathematical modeling ofhospitalizations works best when there is an established pattern of disease transmission frommultiple years of data collection; COVID-19 is a novel virus for which we have less than a year’sworth of data from which to draw conclusions. Furthermore, there remains uncertainty aboutthe trajectory of COVID-19 cases and hospitalizations in the future, particularly with the recentemergency use authorization of the Pfizer and Moderna COVID-19 vaccines.Keywords: SARS-CoV-2, COVID-19, hospitalizations, ventilator, morbidity, and mortality

Spacetime Paths as a Whole

The mathematical similarities between non-relativistic wavefunction propagation in quantum mechanics and image propagation in scalar diffraction theory are used to develop a novel understanding of time and paths through spacetime as a whole. It is well known that Feynman’s original derivation of the path integral formulation of non-relativistic quantum mechanics uses time-slicing to calculate amplitudes as sums over all possible paths through space, but along a definite curve through time. Here, a 3+1D spacetime wave distribution and its 4-momentum dual are formally developed which have no external time parameter and therefore cannot change or evolve in the usual sense. Time is thus seen “from the outside”. A given 3+1D momentum representation of a system encodes complete dynamical information, describing the system’s spacetime behavior as a whole. A comparison is made to the mathematics of holograms, and properties of motion for simple systems are derived.

ANALASYS OF EXPORT OF COSMETIC PRODUCTS OF SOUTH KOREA TO RUSSIA AND PHENOMENON OF "KOREAN WAVE"

The article presents the dynamics of the export of South Korea’s cosmetics from 2011 to 2019. The article considers a description of cultural phenomenon, which is named "Korean wave", distribution in the spheres of the entertainment industry and impact on the economy of the Republic of Korea

FEM based 3D modelling of partial discharge detection and localization in an oil-filled power transformer using piezoelectric acoustic sensor

The main cause of insulation degradation is due to partial discharges (PDs) occurring inside the transformer, and its detection and localization are the most effective, non-destructive methods to assess the insulation condition of the transformer. Among the PD detection methods, the acoustic PD detection technique is popular because of its various advantages. The acoustic PD detection method for accurate PD source localization becomes quite challenging when PD occurs inside the transformer core and windings. As the acoustic sound wave can be distorted and vibration with its distribution, so the type of PD sensors with their setting in the transformer should be thoroughly investigated and chosen. In this work, via simulation, the acoustic sound distribution inside the power transformer due to PD occurs is studied. Based on the knowledge of acoustic pressure wave distribution, a Lead Zirconate Titanate (PZT-5H) sensor is designed using Finite element method based COMSOL Multiphysics software and placed it on the outer walls of the transformer for PD detection and localization. The PD induction position has been recognized from the sensor signal using an artificial neural network. The results of PD detection and localization by the proposed piezoelectric sensor and COMSOL probe point are in good agreement.