Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: Climate change is a phenomenon has been based on
the available evidence from a very long time ago and now its
existence is very probable. The speed and nature of climate
parameters changes at the middle of twentieth century has been
different and its quickness more than the before and its trend changed
to some extent comparing to the past. Climate change issue now
regarded as not only one of the most common scientific topic but also
a social political one, is not a new issue. Climate change is a
complicated atmospheric oceanic phenomenon on a global scale and
long-term. Precipitation pattern change, fast decrease of snowcovered
resources and its rapid melting, increased evaporation, the
occurrence of destroying floods, water shortage crisis, severe
reduction at the rate of harvesting agricultural products and, so on are
all the significant of climate change. To cope with this phenomenon,
its consequences and events in which public instruction is the most
important but it may be climate that no significant cant and effective
action has been done so far. The present article is included a part of
one surrey about climate change in Fars. The study area having
annually mean temperature 14 and precipitation 320 mm .23 stations
inside the basin with a common 37 year statistical period have been
applied to the meteorology data (1974-2010). Man-kendal and
change factor methods are two statistical methods, applying them, the
trend of changes and the annual mean average temperature and the
annual minimum mean temperature were studied by using them.
Based on time series for each parameter, the annual mean average
temperature and the mean of annual maximum temperature have a
rising trend so that this trend is clearer to the mean of annual
maximum temperature.
Abstract: This paper presents a comparative study on
Vanadyl Phthalocyanine (VOPc) thin films deposited by thermal
evaporation and spin coating techniques. The samples
were prepared on cleaned glass substrates and annealed at
various temperatures ranging form 95oC to 155oC. To obtain
the morphological and structural properties of VOPc thin
films, X-ray diffraction (XRD) technique and atomic force
microscopy (AFM) have been implied. The AFM topographic
images show a very slight difference in the thermally grown
films, before and after annealing, however best results are
achieved for the spin-cast film annealed at 125oC. The XRD
spectra show no existence of the sharp peaks, suggesting the
material to be amorphous. The humps in the XRD patterns
indicate the presence of some crystallites.
Abstract: Snow cover is an important phenomenon in
hydrology, hence modeling the snow accumulation and melting is an
important issue in places where snowmelt significantly contributes to
runoff and has significant effect on water balance. The physics-based
models are invariably distributed, with the basin disaggregated into
zones or grid cells. Satellites images provide valuable data to verify
the accuracy of spatially distributed model outputs. In this study a
spatially distributed physically based model (WetSpa) was applied to
predict snow cover and melting in the Latyan dam watershed in Iran.
Snowmelt is simulated based on an energy balance approach. The
model is applied and calibrated with one year of observed daily
precipitation, air temperature, windspeed, and daily potential
evaporation. The predicted snow-covered area is compared with
remotely sensed images (MODIS). The results show that simulated
snow cover area SCA has a good agreement with satellite image
snow cover area SCA from MODIS images. The model performance
is also tested by statistical and graphical comparison of simulated and
measured discharges entering the Latyan dam reservoir.
Abstract: This research were investigated, determined, and
analyzed of the climate characteristically change in the provincial
Udon Thani in the period of 60 surrounding years from 1951 to 2010
A.D. that it-s transferred to effects of climatologically data for
determining global warming. Statistically significant were not found
for the 60 years- data (R2
Abstract: In order to investigate water deficit stress on 24 of
soybean (Glycine Max. L) cultivars and lines in temperate climate, an
experiment was conducted in Iran Seed and Plant Improvement
Institute. Stress levels were irrigation after evaporation of 50, 100,
150 mm water from pan, class A. Randomized Completely Block
Design was arranged for each stress levels. Some traits such as, node
number, plant height, pod number per area, grain number per pod,
grain number per area, 1000 grains weight, grain yield and harvest
index were measured. Results showed that water deficit stress had
significant effect on node number, plant height, pod number per area,
grain number per pod, grain number per area, 1000 grains weight and
harvest index. Also all of agronomic traits except harvest index
influenced significantly by cultivars and lines. The least and most
grain yield was belonged to Ronak X Williams and M41 x Clark
respectively.
Abstract: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: This study determines the effect of naked and heparinbased
super-paramagnetic iron oxide nanoparticles on the human
cancer cell lines of A2780. Doxorubicin was used as the anticancer
drug, entrapped in the SPIO-NPs. This study aimed to decorate
nanoparticles with heparin, a molecular ligand for 'active' targeting
of cancerous cells and the application of modified-nanoparticles in
cancer treatment. The nanoparticles containing the anticancer drug
DOX were prepared by a solvent evaporation and emulsification
cross-linking method. The physicochemical properties of the
nanoparticles were characterized by various techniques, and uniform
nanoparticles with an average particle size of 110±15 nm with high
encapsulation efficiencies (EE) were obtained. Additionally, a
sustained release of DOX from the SPIO-NPs was successful.
Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell
toxicity than the individual HP and confocal microscopy analysis
confirmed excellent cellular uptake efficiency. These results indicate
that HP based SPIO-NPs have potential uses as anticancer drug
carriers and also have an enhanced anticancer effect.