Deep Learning Applied to the Asteroseismic Modeling of Stars with Coherent Oscillation Modes

We develop a novel method based on machine learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-D parameter space. A deep neural network is trained on a precomputed asteroseismology grid containing about 62 million coherent oscillation-mode frequencies derived from stellar evolution models. These models are representative of the core-hydrogen burning stage of intermediate-mass and high-mass stars. The evolution models constitute a 6D parameter space and their predicted low-degree pressure- and gravity-mode oscillations are scanned, using a genetic algorithm. A software pipeline is created to find the best fitting stellar parameters for a given set of observed oscillation frequencies. The proposed method finds the optimal regions in the 6D parameters space in less than a minute, hence providing the optimal starting point for further and more detailed forward asteroseismic modeling in a high-dimensional context. We test and apply the method to seven pulsating stars that were previously modeled asteroseismically by classical grid-based forward modeling based on a $\chi^2$ statistic and obtain good agreement with past results. Our deep learning methodology opens up the application of asteroseismic modeling in +6D parameter space for thousands of stars pulsating in coherent modes with long lifetimes observed by the $Kepler$ space telescope and to be discovered with the TESS and PLATO space missions, while applications so far were done star-by-star for only a handful of cases. Our method is open source and can be used by anyone freely.Comment: Accepted for publication in PASP Speciale Volume on Machine Learnin

Bird surveys for REDD+: avian communities indicate forest degradation in a Peruvian coffee landscape

Shade coffee cultivation in the Peruvian Andes assists in reducing emissions from deforestation because it avoids conversion to non-forest land uses such as coca and sun grown coffee farming. REDD+ is a potential finance mechanism which may provide incentives for local coffee cooperatives to maintain high shade tree cover. REDD+ has potential multiple benefits other than carbon sequestration, including the conservation of biodiversity. When monitoring for REDD+, surveys of bird biodiversity may prove to be particularly valuable: apart from their high intrinsic value and their value as essential ecosystem service providers, birds inhabiting forest habitats are extremely sensitive to forest loss and forest degradation and are therefore potential useful indicators for the impact of habitat and climate disturbances on biodiversity and environmental health.
We analyzed the impact of coffee cultivation on the conservation of birds and assessed what can be learned from bird surveys when monitoring the Peruvian mountain forests for REDD+. Using twelve day-long transect walks, bird species were recorded in two sites in the buffer zone of the Bahuaja-Sonene National Park in SE Peru. The two sites had contrasting human pressure: one site an intimate mixture of shade coffee plantations, orchards, secondary forest patches and coca plantations and the other site secondary forest with patchily distributed shade coffee, fruit and coca plantations. An indirect gradient approach (non-metric multidimensional scaling and multi-response permutation procedure tests) was used to detect differences in forest degradation between sites.
In a two-dimensional ordination space, individual counts of the less disturbed site were separated from the other counts, but sites did not differ significantly at the community-level. Observed birds were indicative for one habitat type. The bird assemblage was dominated by species of forest edges and second growth habitat (78%). The majority of species (68%) had a wide range covering Amazonia and the east slopes of the Andes; only 25 species (29%) were more or less restricted to Andes and the outlying ridges.
The current state of the forest, in both sites with contrasting human influence, can be described as disturbed secondary montane evergreen forest of the transition zone between the Andes and the Amazon. Despite severe human impact, several forest specialists (22%) of both Andean montane and Amazonian forest persisted –including the enigmatic Andean cock-of-the-rock and Military macaw. For such species, REDD+ projects should not only focus on the sustainable management of the shade coffee stands but also aim to conserve the remaining old-growth secondary forest patches

Comparison of uplink SAR values in train environment for different wireless technologies

A comparison of uplink Specific Absorption Rate (SAR) values in a train environment for different wireless technologies using macrocells or femtocells is presented. The comparison is based on both simulations and real-life experiments. Compared to a typical GSM900 macrocell scenario, the largest SAR reduction is observed when using a UMTS femtocell base station, which leads to uplink SAR reductions by a factor 358,820

Assessment and comparison of total RF-EMF exposure in femtocell and macrocell base station scenarios

The indoor coverage of a mobile service can be drastically improved by deployment of an indoor femtocell base station (FBS). However, the impact of its proximity on the total exposure of the human body to radio-frequency (RF) electromagnetic fields (EMFs) is unknown. Using a framework designed for the combination of near-field and far-field exposure, the authors assessed and compared the RF-EMF exposure of a mobile-phone (MP) user that is either connected to an FBS or a conventional macrocell base station while in an office environment. It is found that, in average macrocell coverage and MP use-time conditions and for Universal Mobile Telecommunications System technology, the total exposure can be reduced by a factor of 20-40 by using an FBS, mostly due to the significant decrease in the output power of the MP. In general, the framework presented in this study can be used for any exposure scenario, featuring any number of technologies, base stations and/or access points, users and duration

Prediction and comparison of downlink electric-field and uplink localised SAR values for realistic indoor wireless planning

In this paper, for the first time a heuristic network calculator for both whole-body exposure due to indoor base station antennas or access points (downlink exposure) and localised exposure due to the mobile device (uplink exposure) in indoor wireless networks is presented. As an application, three phone call scenarios are investigated (Universal Mobile Telecommunications System (UMTS) macrocell, UMTS femtocell andWiFi voice-over-IP) and compared with respect to the electric-field strength and localised specific absorption rate (SAR) distribution. Prediction models are created and successfully validated with an accuracy of 3 dB. The benefits of the UMTS power control mechanisms are demonstrated. However, dependent on the macrocell connection quality and on the user's average phone call connection time, also the macrocell solution might be preferential from an exposure point of view for the considered scenario