Characterizing Sparse Asteroid Light Curves with Gaussian Processes

In the era of wide-field surveys like the Zwicky Transient Facility and the Rubin Observatory’s Legacy Survey of Space and Time, sparse photometric measurements constitute an increasing percentage of asteroid observations, particularly for asteroids newly discovered in these large surveys. Follow-up observations to supplement these sparse data may be prohibitively expensive in many cases, so to overcome these sampling limitations, we introduce a flexible model based on Gaussian processes to enable Bayesian parameter inference of asteroid time-series data. This model is designed to be flexible and extensible, and can model multiple asteroid properties such as the rotation period, light-curve amplitude, changing pulse profile, and magnitude changes due to the phase-angle evolution at the same time. Here, we focus on the inference of rotation periods. Based on both simulated light curves and real observations from the Zwicky Transient Facility, we show that the new model reliably infers rotational periods from sparsely sampled light curves and generally provides well-constrained posterior probability densities for the model parameters. We propose this framework as an intermediate method between fast but very limited-period detection algorithms and much more comprehensive but computationally expensive shape-modeling based on ray-tracing codes.

Rotation Period Detection for Earth-like Exoplanets

A terrestrial planet’s rotation period is one of the key parameters that determines its climate and habitability. Current methods for detecting the rotation period of exoplanets are not suitable for terrestrial exoplanets. Here we demonstrate that, under certain conditions, the rotation period of an Earth-like exoplanet will be detectable using direct-imaging techniques. We use a global climate model that includes clouds to simulate reflected starlight from an Earth-like exoplanet and explore how different parameters (e.g., orbital geometry, wavelength, time resolution) influence the detectability of the planet’s rotation period. We show that the rotation period of an Earth-like exoplanet is detectable using visible-wavelength channels with time-series monitoring at a signal-to-noise ratio (S/N) >20 with ∼5–15 rotation periods of data, while the rotation period of a planet with full ocean coverage is unlikely to be detectable. To better detect the rotation period, one needs to plan the observation so that each individual integration would yield a S/N >10, while keeping the integration time shorter than 1/6 to 1/4 of the rotation period of the planet. Our results provide important guidance for rotation period detection of Earth-like exoplanets in reflected light using future space telescopes.

Acute rheumatic fever: 10-year single-center experience: clinical and laboratory findings, with subclinical carditis and treatment complications

Background:Acute rheumatic fever in childhood continues to cause serious morbidity despite all developments. The objective of this study was to evaluate the clinical and laboratory characteristics of patients with acute rheumatic fever and to determine the frequency of subclinical carditis and the side effects of the drugs used in the treatment.Methods:The data of patients hospitalised between 2008 and 2018 with the diagnosis of acute rheumatic fever were included in the study. The relationship of gender and age with the frequency of major symptoms and the distribution of the drugs used in the treatment and their side effects were evaluated.Results:Medical records of 102 patients with complete data were reviewed. 56.9% of the patients were male and the mean age was 10.7 ± 1.9 years. The most common distribution of complaints found were arthritis (51%), arthralgia (25.5%) and fever (16.7%). 10.8% of all patients (n = 11) were diagnosed subclinical carditis via echocardiographic evaluation. The frequency of carditis was higher in female patients with a borderline statistical significance (p = 0.05). However, there was no statistically significant difference between gender and arthritis (p = 0.22) and carditis (p > 0.05). Anti-congestive therapy was required in 22% and inotropic treatment was needed in 6.1% cases. Toxic hepatitis developed in four cases during the acetylsalicylic acid treatment.Conclusions:In a 10-year period, detection of subclinical carditis in 10.8% cases supported that echocardiography should be performed as a standard method for the diagnosis of acute rheumatic fever. Patients should be followed closely in terms of hepatic toxicity due to acetylsalicylic acid used in the treatment.

Design and characteristics assessment of wireless vibration sensor for buildings and houses

<span>This paper reports the wireless vibration detector design and characterization for practical applications. System is built by using the ATmega microcontrollers, working on a free license 433 MHz frequency. Hardware characteristics are defined through experimental assessments. Assessment mainly on sensor output and sensor installation characteristics. As results, hardware is working as expected, where vibration level achieves at most 13% detection for 12 g vibration source. The vertical axis of the MPU6050 vibration detector results 87.5 times higher detection than in horizontal axis. Detected vibration increases from 1.03 g to 2.61 g when source-sensor distance is shortened from 10 cm to 2 cm. The aluminium sheet as sensor pad causes detection of 8.69 times higher than on ceramic pad. The lower the detection period the better the detection amplitude. However, the lower the period, the higher the consumed power. Microcontroller sleep mode is not suitable for short period detection. The node-based data validation to avoid transmitting false detection is not influencial for short period detection.</span>

The discrete Fourier transformation for seasonality and anomaly detection of an application to rare data

PurposeThe discrete Fourier transformation (DFT) has been proven to be a successful method for determining whether a discrete time series is seasonal and, if so, for detecting the period. This paper deals exclusively with rare data, in which instances occur periodically at a low frequency.Design/methodology/approachData based on real-world situations is simulated for analysis.FindingsCycle number detection is done with spectral analysis, period detection is completed using DFT coefficients and signal shifts in the time domain are found using the convolution theorem. Additionally, a new method for detecting anomalies in binary, rare data is presented: the sum of distances. Using this method, expected events which have not occurred and unexpected events which have occurred at various sampling frequencies can be detected. Anomalies which are not considered outliers to be found.Research limitations/implicationsAliasing can contribute to extra frequencies which point to extra periods in the time domain. This can be reduced or removed with techniques such as windowing. In future work, this will be explored.Practical implicationsApplications include determining seasonality and thus investigating the underlying causes of hard drive failure, power outages and other undesired events. This work will also lend itself well to finding patterns among missing desired events, such as a scheduled hard drive backup or an employee's regular login to a server.Originality/valueThis paper has shown how seasonality and anomalies are successfully detected in seasonal, discrete, rare and binary data. Previously, the DFT has only been used for non-rare data.

Long rotation period main-sequence stars from Kepler SAP light curves

ABSTRACT Stellar rotation plays a key role in stellar activity. The rotation period could be detected through light curve variations caused by star-spots. Kepler provides two types of light curves: one is the Pre-search Data Conditioning (PDC) light curves, and the other is the Simple Aperture Photometer (SAP) light curves. Compared with the PDC light curves, the SAP light curves keep the long-term trend, relatively suitable for searches of long-period signals. However, SAP data are inflicted by some artefacts such as quarterly rolls and instrumental errors, making it difficult to find the physical periods in the SAP light curves. We explore a systematic approach based on the light curve pre-processing, period detection, and candidate selection. We also develop a simulated light curve test to estimate our detection limits for the SAP-like LCs. After applying our method to the raw SAP light curves, we found more than 1000 main-sequence stars with periods longer than 30 d; 165 are newly discovered. Considering the potential flaw of the SAP, we also inspect the newly found objects with photometry methods, and most of our periodical signals are confirmed.