The Spacelab-Mir-1 "Greenhouse-2" experiment.

The Spacelab-Mir-1 (SLM-1) mission is the first docking of the Space Shuttle Atlantis (STS-71) with the Orbital Station Mir in June 1995. The SLM-1 "Greenhouse-2" experiment will utilize the Russian-Bulgarian-developed plant growth unit (Svet). "Greenhouse-2" will include two plantings (1) designed to test the capability of Svet to grow a crop of Superdwarf wheat from seed to seed, and (2) to provide green plant material for post-flight analysis. Protocols, procedures, and equipment for the experiment have been developed by the US-Russian science team. "Greenhouse-2" will also provide the first orbital test of a new Svet Instrumentation System (SIS) developed by Utah State University to provide near real time data on plant environmental parameters and gas-exchange rates. SIS supplements the Svet control and monitoring system with additional sensors for substrate moisture, air temperature, IR leaf temperature, light, oxygen, pressure, humidity, and carbon-dioxide. SIS provides the capability to monitor canopy transpiration and net assimilation of the plants growing in each vegetation unit (root zone) by enclosing the canopy in separate, retractable, ventilated leaf chambers. Six times during the seed-to-seed experiment, plant samples will be collected, leaf area measured, and plant parts fixed and/or dried for ground analysis. A second planting initiated 30 days before the arrival of a U.S. Shuttle [originally planned to be STS-71] is designed to provide green material at the vegetative development stage for ground analysis. [As this paper is being edited, the experiment has been delayed until after the arrival of STS-71.]     

Solar modulation model with reentrant particles

We developed a one dimensional model of particle transport in the heliosphere. As opposite to widely used models, we apply a method where a quasi-particle is traced back in time. The model gives us the possibility to work on the possible existence of reentrant particles in the heliosphere that can be hardly solved by the traditional forward tracking method. Particles escape from the heliosphere and may reenter back. We estimate how these particles affect the modulation process in the heliosphere. Presented here are the results for different values of particles mean free path in the interstellar space and for different interstellar magnetic field values.     

Analysis of total visual and CCD V-broadband observations of Comet C/1995 O1 (Hale-Bopp): 1995–2001

We developed a general method for determination of water production rates from groundbased visual observations and applied it to Comet Hale–Bopp. Our main objective is to extend the method to include total visual magnitude observations obtained with CCD detector and V filter in the analysis of total visual magnitudes. We compare the CCD V-broadband careful observations of Liller [Liller, W. Pre-perihelion CCD photometry of Comet 1995 O1 (Hale-Bopp). Planet. Space Sci. 45, 1505–1513, 1997; Liller, W. CCD photometry of Comet C/1995 O1 (Hale-Bopp): 1995–2000. Int. Comet Quart. 23(3), 93–97, 2001] with the total visual magnitude observations from experienced international observers found in the International Comet Quarterly (ICQ) archive. A data set of ∼400 CCD observations covering about the same 6 years time span of the ∼12,000 ICQ selected total visual magnitude observations were used in the analysis. A least-square method applied to the water production rates, yields power laws as a function of the heliocentric distances for the pre- and post-perihelion phases. The average dimension of the nucleus as well as its effective active area is determined and compared with values published in the literature.     

The SOHO CELIAS/SEM EUV database from SC23 minimum to the present

The SOHO Solar EUV Monitor has been in operation since December 1995 onboard the SOHO spacecraft. This instrument is a highly stable transmission grating solar extreme ultraviolet spectrometer. It has made nearly continuous full disk solar irradiance measurements both within an 8 nm bandpass centered at 30.4 nm and throughout the 0.1 to 50 nm solar flux region since launch. The 30.4 nm flux, the 0.1 to 50 nm flux and the extracted soft X-ray (0.1 to 5 nm) flux are presented and compared with the behavior of solar proxies.     

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.     

Correlation of IRTAM and FPMU data confirming the application of IRTAM to support ISS Program safety

A “Real-Time” plasma hazard assessment process was developed to support International Space Station (ISS) Program real-time decision-making providing solar array constraint relief information for Extravehicular Activities (EVAs) planning and operations. This process incorporates real-time ionospheric conditions, ISS solar arrays’ orientation, ISS flight attitude, and where the EVA will be performed on the ISS. This assessment requires real-time data that is presently provided by the Floating Potential Measurement Unit (FPMU) which measures the ISS floating potential (FP), along with ionospheric electron number density (Ne) and electron temperature (Te), in order to determine the present ISS environment. Once the present environment conditions are correlated with International Reference Ionosphere (IRI) values, IRI is used to forecast what the environment could become in the event of a severe geomagnetic storm. If the FPMU should fail, the Space Environments team needs another source of data which is utilized to support a short-term forecast for EVAs. The IRI Real-Time Assimilative Mapping (IRTAM) model is an ionospheric model that uses real-time measurements from a large network of digisondes to produce foF2 and hmF2 global maps in 15?min cadence. The Boeing Space Environments team has used the IRI coefficients produced in IRTAM to calculate the Ne along the ISS orbital track. The results of the IRTAM model have been compared to FPMU measurements and show excellent agreement. IRTAM has been identified as the FPMU back-up system that will be used to support the ISS Program if the FPMU should fail.     

Clinorotation reduces number, but not size, of cartilaginous nodules formed in micromass cultures of mouse limbbud cells.

In previous studies we used a ground based model to investigate the cellular responses to microgravity by exposing micromass cultures of embryonic limb cells to simulated weightlessness on a clinostat. Cultures set up in T-flasks and rotated at 30 rpm showed that clinostatted cultures had less chondrocyte differentiation than stationary or rotation controls, as assessed by number of nodules/culture stained with cartilage specific Alcian blue. In the current study, nodule size and shape of these nodules was assessed by interactive measurement of area, perimeter, circularity, and equivalent diameters, using the Optimas imaging software. Results show no significant difference in any of the measurements, indicating that clinorotation has no effect on expansion of the nodules either by differentiation of cells within the nodule, or by recruitment of cells into the nodule. The reduction in number of nodules without an alteration in size and shape indicates that the effect of simulated microgravity is to reduce the cell interactions required for the initial condensation of cells into a nodule, probably by interference with cell adhesion molecules.     

Comprehensive data reduction package for the Immersion GRating INfrared Spectrograph: IGRINS

We present a Python-based data reduction pipeline package (PLP) for the Immersion GRating INfrared Spectrograph (IGRINS), an instrument that covers the complete H- and K-bands in one exposure with a spectral resolving power of 40,000. The reduction steps carried out by the PLP include flat-fielding, background removal, order extraction, distortion correction, wavelength calibration, and telluric correction using spectra of A type standard stars. As the spectrograph has no moving parts, the PLP automatically reduces the data using predefined functions for the processes of order extraction, distortion correction, and wavelength calibration. Before the telluric correction of the target spectra, the intrinsic hydrogen absorption features of the standard A star are removed with a Gaussian fitting algorithm. The final result is the flux of the target as a function of wavelength. Users can customize the predefined functions for the extraction of the spectrum from the echellogram and adjust the parameters for the fitting functions for the spectra of celestial objects, using “fine-tuning” options, as necessary. Presently, the PLP produces the best results for point-source targets.     

Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms

We have developed a new approach towards a new database of the ionospheric parameter $f_{o}F2$. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio propagation. The current databases, generated by CCIR (Committee Consultative for Ionospheric Radiowave propagation) and URSI (International Union of Radio Science), and used by the IRI (International Reference Ionosphere) model, are based on Fourier expansions and have been built in the 60s from the available ionosondes at that time. The main goal of this work is to upgrade the databases by using new available ionosonde data. To this end we used the IRI diurnal/spherical expansions to represent the $f_{o}F2$ variability, and computed its coefficients by means of a genetic algorithm (GA). In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmósfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958–2009. The new GA coefficients provide a global better fit of the IRI model to the observed $f_{o}F2$ than the CCIR coefficients. Since the same formulae and the same number of coefficients were used, the overall integrity of IRI’s typical ionospheric feature representation was preserved. The best improvements with respect to CCIR are obtained at low solar activities, at large (in absolute value) modip latitudes, and at night-time. The new method is flexible in the sense that can be applied either globally or regionally. It is also very easy to recompute the coefficients when new data is available. The computation of a third set of coefficients corresponding to days of medium solar activity in order to avoid the interpolation between low and high activities is suggested. The same procedure as for $f_{o}F2$ can be perfomed to obtain the ionospheric parameter M(3000)F2.