The astrometric signal of microlensing events caused by free floating planets

Astrometric observations of microlensing events can be used to obtain important information about lenses. During these events, the shift of the position of the multiple image centroid with respect to the source star location can be measured. This effect, which is expected to occur on scales from micro-arcseconds to milli-arcseconds, depends on the lens-source-observer system physical parameters. Here, we consider the astrometric and photometric observations by space and ground-based telescopes of microlensing events towards the Galactic bulge caused by free floating planets (FFPs). We show that the efficiency of astrometric signal on photometrically detected microlensing events tends to increase for higher FFP masses in our Galaxy. In addition, we estimate that during five years of the Gaia observations, about a dozen of microlensing events caused by FFPs are expected to be detectable.     

Predictions on the detection of the free-floating planet population with K2 and spitzer microlensing campaigns

The K2’s Campaign 9 (K2C9) by the Kepler satellite for microlensing observations towards the Galactic bulge started on April 7, 2016, and is going to last for about three months. It offers the first chance to measure the masses of members of the large population of the isolated dark low-mass objects further away in our Galaxy, free-floating planets (FFPs). Intentionally, this observational period of K2 will overlap with that of the 2016 Spitzer follow-up microlensing project expected to start in June, 2016. Therefore, for the first time it is going to be possible to observe simultaneously the same microlensing events from a ground-based telescope and two satellites. This will help in removing the two-fold degeneracy of the impact parameter and in estimating the FFP mass, provided that the angular Einstein ring radius Θ_E is measured. In this paper we calculate the probability that a microlensing event is detectable by two or more telescopes and study how it depends on the mass function index of FFPs and the position of the observers on the orbit.     

Gamma ray burst studies with THESEUS

Gamma-ray Bursts (GRBs) are the most powerful transients in the Universe, over–shining for a few seconds all other γ-ray sky sources. Their emission is produced within narrowly collimated relativistic jets launched after the core–collapse of massive stars or the merger of compact binaries. THESEUS will open a new window for the use of GRBs as cosmological tools by securing a statistically significant sample of high-z GRBs, as well as by providing a large number of GRBs at low–intermediate redshifts extending the current samples to low luminosities. The wide energy band and unprecedented sensitivity of the Soft X-ray Imager (SXI) and X-Gamma rays Imaging Spectrometer (XGIS) instruments provide us a new route to unveil the nature of the prompt emission. For the first time, a full characterisation of the prompt emission spectrum from 0.3 keV to 10 MeV with unprecedented large count statistics will be possible revealing the signatures of synchrotron emission. SXI spectra, extending down to 0.3 keV, will constrain the local metal absorption and, for the brightest events, the progenitors’ ejecta composition. Investigation of the nature of the internal energy dissipation mechanisms will be obtained through the systematic study with XGIS of the sub-second variability unexplored so far over such a wide energy range. THESEUS will follow the spectral evolution of the prompt emission down to the soft X–ray band during the early steep decay and through the plateau phase with the unique ability of extending above 10 keV the spectral study of these early afterglow emission phases.

     

Evaluation of moving-bed biofilm sequencing batch reactor (MBSBR) in operating A<Superscript>2</Superscript>O process with emphasis on biological removal of nutrients existing in wastewater

In this study, the performance of moving-bed biofilm sequencing batch reactor in operating the anaerobic/anoxic/oxic (A²O) process for treatment of wastewaters containing nitrogen and phosphorous was evaluated. For this purpose, a pilot system with two bench-scale sequencing batch reactors with a total volume of 30 L and functional volume of 10 L was used. The installation was elaborated using plexiglass, in which 60% of the functional volume consisted of PVC suspended carriers (Kaldnes K3) with a specific surface area of 560 m²/m³. The independent variables used in this study were hydraulic retention time (HRT) (1.5, 2, 2.5, 3, and 3.5 h) and the initial organic load (300, 500, 800, 1000 mg O₂/L). The results showed impressive performance in the case of an initial organic load of 300 mg O₂/L and HRT of 3 h with maximum removal of COD and TN, respectively, by 95.1 and 89.8%. In the case of an initial organic load of 1000 mg O₂/L and HRT of 3.5 h, the maximum total phosphorus removal was 72.3%. Therefore, according to the analysis of data obtained by different HRTs, it was revealed that the system of A²O has greater efficiency in removing organic matter from wastewater in the shortest possible time.     

Surface nuclear magnetic resonance signals recovery by integration of a non‐linear decomposition method with statistical analysis

Presence of noise in the acquisition of surface nuclear magnetic resonance data is inevitable. There are various types of noise, including Gaussian noise, spiky events, and harmonic noise that affect the signal quality of surface nuclear magnetic resonance measurements. In this paper, we describe an application of a two‐step noise suppression approach based on a non‐linear adaptive decomposition technique called complete ensemble empirical mode decomposition in conjunction with a statistical optimization process for enhancing the signal‐to‐noise ratio of the surface nuclear magnetic resonance signal. The filtering procedure starts with applying the complete ensemble empirical mode decomposition method to decompose the noisy surface nuclear magnetic resonance signal into a finite number of intrinsic mode functions. Afterwards, a threshold region based on de‐trended fluctuation analysis is defined to identify the noisy intrinsic mode functions, and then the no‐noise intrinsic mode functions are used to recover the partially de‐noised signal. In the second stage, we applied a statistical method based on the variance criterion to the signal obtained from the initial phase to mitigate the remaining noise. To demonstrate the functionality of the proposed strategy, the method was evaluated on an added‐noise synthetic surface nuclear magnetic resonance signal and on field data. The results show that the proposed procedure allows us to improve the signal‐to‐noise ratio significantly and, consequently, extract the signal parameters (i.e., and V₀) from noisy surface nuclear magnetic resonance data efficiently.     

Source differentiation, modeling and simulating strong-motion data from Iran

For designing a structure to withstand the effects of strong earthquake ground motions, it is necessary to characterize the type of motion that probably affects the structure. The strong-motion accelerograms contain numerous data regarding the source, path, and receiver. Variables such as the Richter magnitude, hypocenter depth, duration of the event, and focal mechanism relate to the source. The soil parameter and distance to epicenter, relate to the path. The application of autoregressive moving average (ARMA) process in modeling an earthquake accelerogram of three different regions of Iran reveals a formulation, which relates the physical variables via a regression analysis. In order to generate time history data of a probable future earthquake, it is recommended to use the regression equations for a specific type of earthquake focal mechanism if the future earthquake mechanism and physical variables are known; otherwise, regional equations are more suitable.