Development of composite particles for pulmonary delivery

In this work, biocompatible and biodegradable poly(D-L-lactide-co-glycolide) (PLGA) microparticles with the potential for use as a controlled release system of vaccines and other drugs to the lung were manufactured using supercritical CO2, through the Supercritical Assisted Atomization (SAA) technique. After performing a controlled variance in production parameters (temperature, pressure, CO2/solution flow ratio) PLGA microparticles were characterized and later used to encapsulate active pharmaceutical ingredients (API). Bovine serum albumin (BSA) was chosen as model protein and vaccine, while sildenafil was the chosen drug to treat pulmonary artery hypertension and their effect on the particles characteristics was evaluated. All the produced formulations were characterized in relation to their morphology (Morphologi G3 and scanning electronic microscopy (SEM)), to their physical-chemical properties (X-ray diffraction (XRD, differential scanning calorimetry (DSC), Fourier transform infrared (FTIR)) and aerodynamic performance using an in vitro aerosolization study – Andersen cascade impactor (ACI) - to obtain data such as the fine particle fraction (FPF) and the mass median aerodynamic diameter (MMAD). Furthermore, pharmacokinetic, biodegradability and biocompatibility tests were performed in order to verify the particle suitability for inhalation. The resulting particles showed aerodynamic diameters between the 3 and 5 μm, yields up to 58% and FPF percentages rounding the 30%. Taken as a whole, the produced microparticles do present the necessary requests to make them appropriate for pulmonary delivery.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

WebGIS applied to improve spatial knowledge of high school students

This research seeks to design and implement a WebGIS application allowing high school students to work with information related to the disciplinary competencies of the competency-teaching model, in Mexico. This paradigm assumes knowledge to be acquired through the application of new technologies and to link it with everyday life situations of students. The WebGIS provides access to maps regarding natural risks in Mexico, e.g. volcanism, seismic activities, or hurricanes; the prototype's user interface was designed with special emphasis on scholar needs for high school students.