Evaluation of Aviation Emissions and Environmental Costs in Europe Using OpenSky and OpenAP

In this paper, we propose a data-driven approach that estimates cruise-level flight emissions over Europe using OpenSky ADS-B data and OpenAP emission models. Flight information, including position, altitude, speed, and the vertical rate are obtained from the OpenSky historical database, gathered at a sample rate of 15 s. Emissions from each flight are estimated at a 30-s time interval. This study makes use of the first four months of flights in 2020 over the major part of Europe. The dataset covers the period before and at the start of the COVID-19 pandemic. The aggregated results show cruise-level flight emissions by different airlines, geographic regions, altitudes, and timeframe (e.g., weeks). We also estimate environmental costs associated with aviation in Europe by using marginal cost values from the literature. Overall, we have demonstrated how open flight data from OpenSky can be employed to rapidly assess aviation emissions at varying spatio-temporal resolutions on a continental scale.

Utilizing neural networks for image downscaling and water quality monitoring

Remotely sensed images are becoming highly required for various applications, especially those related to natural resource management. The Moderate Resolution Imaging Spectroradiometer (MODIS) data has the advantages of its high spectral and temporal resolutions but remains inadequate in providing the required high spatial resolution. On the other hand, Sentinel-2 is more advantageous in spatial and temporal resolution but lacks a solid historical database. In this study, four MODIS bands in the visible and near-infrared spectral regions of the electromagnetic spectrum and their matching Sentinel-2 bands were used to monitor the turbidity in Lake Nasser, Egypt. The MODIS data were downscaled to Sentinel-2, which enhanced its spatial resolution from 250 and 500m to 10m.Furthermore, it provided a historical database that was used to monitor the changes in lake turbidity. Spatial approach based on neural networks was presented to downscale MODIS bands to the spatial resolution of the Sentinel-2 bands. The correlation coefficient between the predicted and actual images exceeded 0.70 for the four bands. Applying this approach, the downscaled MODIS images were developed and the neural networks were further employed to these images to develop a model for predicting the turbidity in the lake. The correlation coefficient between the predicted and actual measurements reached 0.83. The study suggests neural networks as a comparatively simplified and accurate method for image downscaling compared to other methods. It also demonstrated the possibility of utilizing neural networks to accurately predict lake water quality parameters such as turbidity from remote sensing data compared to statistical methods.

Next generation aircraft noise-mapping

At CSA, Centre for Sustainable Aviation at KTH Stockholm, several projects have run during the last 4 years. One outcome from this research is the SAFT-program for prediction of aircraft noise contours (noise-mapping) and time-histories in receiving points on ground. SAFT is a versatile and comprehensive tool already including several computational methods such as standard ECACdoc.29 method and more accurate time-stepping simulation-based representations of aircraft sound sources (frequency and direction dependent). The program allows for input of "general aircraft trajectory input" in the sense that either the trajectory data of concern is fitted to the current pre-defined formats or SAFT is easily updated to read a "new" format. Among the pre-defined formats of current version is csv-files prepared from OpenSky Historical database. From these kinds of data thrust and other noise-predictor variables are extracted and applied for noise-mapping. Moreover, SAFT allows for studies of aggregated air-traffic in defined areas as well as of single event flight-trajectories. And for these almost any metric (L, L, L, L, ...) might be extracted together with differences in dB, "Delta-dB", between any two scenarios or individual flights. Could be routing, runway-use, individual flight procedures etc. Anticipated future implementations involve drone trajectories and sound-source representations.

The Inclusiveness of Maternity Leave Rights over 120 Years and across Five Continents

Even though paid maternity leave was the earliest form of social protection specifically aimed at women workers and is fundamental in securing their economic independence vis-à-vis employers and spouses, it has received scant scholarly attention. Neither the traditional historical accounts of welfare state emergence nor the more recent gendered analyses of developed welfare states have provided comparative accounts of its beginnings and trajectories. Employing the newly created historical database of maternity leave, we provide the first global and historical perspective on paid maternity leave policies covering 157 countries from the 1880s to 2018. Focusing on eligibility rather than generosity, we construct a measure of inclusiveness of paid maternity leaves to highlight how paid maternity leave has shaped not only gender but also social inequality, which has, until recently, largely been ignored by the literature on leave policies. The analyses of coverage expansion by sector and the development of eligibility rules reveal how paid maternity leave has historically stratified women workers by occupation and labor market position but is slowly evolving into a more universal social right across a broad range of countries. Potential drivers for this development are identified using multivariate analysis, suggesting a pivotal role for the political empowerment of women in the struggle for gender and social equality. However, the prevalence of informal labor combined with insufficient or non-existing maternity benefits outside the systems of social insurance still poses significant obstacles to the protection of women workers in some countries.

The Oldest Report of a 1537 Mexico Tsunami Based on Japanese Literature Is Erroneous

According to the Global Historical Database by the National Centers for Environmental Information, the oldest historical tsunami record in Central America is the earthquake tsunami that occurred in Mexico in 1537; however, this record is doubtful because this tsunami is reported by no authority outside Japan. Here, I examined earthquake and tsunami catalogs and found the source of this suspicious data. Imamura (1925) compiled the first part of the chronological table of major earthquakes in the world from the earthquake catalog of the world by Milne (1912). During this compilation, information on the tsunami caused by the 1531 Spain–Portugal earthquake was not copied. The chronological table was published almost annually until 1962; during this time the table was revised in 1958 by Kawasumi, who was the author in charge at the time. The remarks for the 1531 Spain–Portugal earthquake tsunami should have been added during the revision, but the text “tsunami existence” was erroneously added to the next entry for the 1537 Mexico earthquake. The source of the 1537 tsunami report was this miscopy.

Endless Digging and Endless Picking. Sex Ratios and Gendered Labour in Surinamese Plantations, 1830–1863

In this article we study the question why the sex ratio among the enslaved population of plantation workers reversed from a male to a female surplus between 1830 and the abolition of slavery in 1863. We use the Historical Database of Suriname (HDS) to answer this question in three steps. First, we give a broad overview of the changing sex ratios in the various Surinamese regions between 1838 and 1861. Second, we study the age structure on three plantations in the district Coronie in 1830 in detail. Finally, we use muster rolls available for the Catharina Sophia plantation in the period 1848–1849 to analyse the gendered division of labour. Our results indicate that both the male surpluses during the 1830s and the subsequent skew of the sex ratios towards females were the effects of a gendered division of labour, in which plantation managers preferred male labourers for heavy and unhealthy work in the construction and upkeep of plantation polders. This led to an excess mortality of enslaved men.

Evaluation of Working Temperature in Wind Turbine Bearings by Simulation of Lubricant Level

After studies related to the technical state and behavior of the temperatures manifested by the bearings of the generators that make up the Goldwind wind turbines models S50-750, installed in the Gibara II Wind Farm (PE). It was identified and validated as a tool that enables early diagnosis of anomalous bearing behaviors, SolidWorks (SW) computer-aided design and engineering software (CAD-CAE) and the Flow Simulation add-on. Since it allows studies based on the computational fluid dynamics (CFD), of the temperatures that are manifested in the lubricant during the different working regimes of the generator. The studies carried out evaluated the environmental conditions of exploitation in Cuba. It works on obtaining and predicting the values of the thermal state using the principles and methods for the calculation of heat transfer, the forecast statistics apply. The research supports its theories and postulates in a sample of 6 installed equipment, from China, for it had a historical database that collects temperature measurements in different working conditions which allowed to establish correlation between theoretical predictions and real behaviors.

Using Machine Learning Algorithms on Prediction of Stock Price

In this paper, we investigate analysis and prediction of the time-dependent data. We focus our attention on four different stocks are selected from Yahoo Finance historical database. To build up models and predict the future stock price, we consider three different machine learning techniques including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN) and Support Vector Regression (SVR). By treating close price, open price, daily low, daily high, adjusted close price, and volume of trades as predictors in machine learning methods, it can be shown that the prediction accuracy is improved.