Abstract: Doxorubicin, also known as Adriamycin, is an
anthracycline class of drug used in cancer chemotherapy. It is used in
the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute
leukemia, breast cancer, lung cancer, endometrium cancer and ovary
cancers. It functions via intercalating DNA and ultimately killing
cancer cells. The major side effects of doxorubicin are hair loss,
myelosuppression, nausea & vomiting, oesophagitis, diarrhea, heart
damage and liver dysfunction. The minor modifications in the
structure of compound exhibit large variation in the biological
activity, has prompted us to carry out the synthesis of sulfonamide
derivatives. Sulfonamide is an important feature with broad spectrum
of biological activity such as antiviral, antifungal, diuretics, antiinflammatory,
antibacterial and anticancer activities. Structure of the
synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilinoethyl)
benzene sulfonamide confirmed by proton nuclear magnetic
resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools
to assure the position of all protons and hence stereochemistry of the
molecule. Further we have reported the binding potential of
synthesized sulfonamide analogues in comparison to doxorubicin
drug using Auto Dock 4.2 software. Computational binding energy
(B.E.) and inhibitory constant (Ki) has been evaluated for the
synthesized compound in comparison of doxorubicin against Poly
(dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences.
The in vitro cytotoxic study against human breast cancer cell lines
confirms the better anticancer activity of the synthesized compound
over currently in use anticancer drug doxorubicin. The IC50 value of
the synthesized compound is 7.12 μM whereas for doxorubicin is 7.2
μM.
Abstract: In this paper, we regard as a coded transmission over a
frequency-selective channel. We plan to study analytically the
convergence of the turbo-detector using a maximum a posteriori
(MAP) equalizer and a MAP decoder. We demonstrate that the
densities of the maximum likelihood (ML) exchanged during the
iterations are e-symmetric and output-symmetric. Under the Gaussian
approximation, this property allows to execute a one-dimensional
scrutiny of the turbo-detector. By deriving the analytical terminology
of the ML distributions under the Gaussian approximation, we confirm
that the bit error rate (BER) performance of the turbo-detector
converges to the BER performance of the coded additive white
Gaussian noise (AWGN) channel at high signal to noise ratio (SNR),
for any frequency selective channel.
Abstract: The Blue Nile Basin is the most important tributary of
the Nile River. Egypt and Sudan are almost dependent on water
originated from the Blue Nile. This multi-dependency creates
conflicts among the three countries Egypt, Sudan, and Ethiopia
making the management of these conflicts as an international issue.
Good assessment of the water resources of the Blue Nile is an
important to help in managing such conflicts. Hydrological models
are good tool for such assessment. This paper presents a critical
review of the nature and variability of the climate and hydrology of
the Blue Nile Basin as a first step of using hydrological modeling to
assess the water resources of the Blue Nile. Many several attempts
are done to develop basin-scale hydrological modeling on the Blue
Nile. Lumped and semi distributed models used averages of
meteorological inputs and watershed characteristics in hydrological
simulation, to analyze runoff for flood control and water resource
management. Distributed models include the temporal and spatial
variability of catchment conditions and meteorological inputs to
allow better representation of the hydrological process. The main
challenge of all used models was to assess the water resources of the
basin is the shortage of the data needed for models calibration and
validation. It is recommended to use distributed model for their
higher accuracy to cope with the great variability and complexity of
the Blue Nile basin and to collect sufficient data to have more
sophisticated and accurate hydrological modeling.
Abstract: This research was conducted in the Mae Sot
Watershed where located in the Moei River Basin at the Upper
Salween River Basin in Tak Province, Thailand. The Mae Sot
Municipality is the largest urban area in Tak Province and situated in
the midstream of the Mae Sot Watershed. It usually faces flash flood
problem after heavy rain due to poor flood management has been
reported since economic rapidly bloom up in recent years. Its
catchment can be classified as ungauged basin with lack of rainfall
data and no any stream gaging station was reported. It was attached
by most severely flood events in 2013 as the worst studied case for
all those communities in this municipality. Moreover, other problems
are also faced in this watershed, such shortage water supply for
domestic consumption and agriculture utilizations including a
deterioration of water quality and landslide as well. The research
aimed to increase capability building and strengthening the
participation of those local community leaders and related agencies to
conduct better water management in urban area was started by mean
of the data collection and illustration of the appropriated application
of some short period rainfall forecasting model as they aim for better
flood relief plan and management through the hydrologic model
system and river analysis system programs. The authors intended to
apply the global rainfall data via the integrated data viewer (IDV)
program from the Unidata with the aim for rainfall forecasting in a
short period of 7-10 days in advance during rainy season instead of
real time record. The IDV product can be present in an advance
period of rainfall with time step of 3-6 hours was introduced to the
communities. The result can be used as input data to the hydrologic
modeling system model (HEC-HMS) for synthesizing flood
hydrographs and use for flood forecasting as well. The authors
applied the river analysis system model (HEC-RAS) to present flood
flow behaviors in the reach of the Mae Sot stream via the downtown
of the Mae Sot City as flood extents as the water surface level at
every cross-sectional profiles of the stream. Both models of HMS and
RAS were tested in 2013 with observed rainfall and inflow-outflow
data from the Mae Sot Dam. The result of HMS showed fit to the
observed data at the dam and applied at upstream boundary discharge
to RAS in order to simulate flood extents and tested in the field, and
the result found satisfying. The product of rainfall from IDV was fair
while compared with observed data. However, it is an appropriate
tool to use in the ungauged catchment to use with flood hydrograph
and river analysis models for future efficient flood relief plan and
management.
Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.
Abstract: Comparisons of financial development across
countries are central to answering many of the questions on factors
leading to economic development. For this reason this study analyzes
the implications of financial system’s development on country’s
economic development. The aim of the article: to analyze the impact
of financial system’s development on economic development. The
following research methods were used: systemic, logical and
comparative analysis of scientific literature, analysis of statistical
data, time series model (Autoregressive Distributed Lag (ARDL)
Model). The empirical results suggest about positive short and long
term effect of stock market development on GDP per capita.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: Various personality profile tests are used to identify
personality strengths and limits in individuals, helping both
individuals and managers to optimize work and team effort in
organizations. One such test, the Hartman’s personality profile,
emphasizes four driving "core motives" influenced or affected by
both strengths and limitations classified into four colors: Red -
motivated by power; Blue - discipline and loyalty; White - peace; and
Yellow – fun loving. Two shortcomings of Hartman’s personality test
are noted; 1) only one selection for every item / situation allowed and
2) selection of an item / option even if not applicable. A test taker
may be as much nurturing as he is opinionated but since
“opinionated” seems less attractive the individual would likely select
nurturing, causing a misidentification in personality strengths and
limits. Since few individuals have a “strong” personality, it is
difficult to assess their true personality strengths and limits allowing
only one choice or requiring unwanted choices, undermining the
potential of the test. We modified Hartman’s personality profile
allowing test takers to make either multiple choices for any item /
situation or leave them blank if applicable. Sixty-eight participants
(38 males and 30 females), 17 - 49 years old, from countries in Asia,
Europe, N. America, CIS, Africa, Latin America, and Oceania were
included. 58 participants (85.3%) reported the modified test, allowing
multiple / no choices better identified their personality strengths and
limits, while 10 participants (14.7%) expressed the original (one
choice version) was sufficient. The overall results show that our
modified test enhanced the identification and balance of core
personalities’ strengths and limits, aiding test takers, managers and
organizations to better assess individual characteristics, particularly
useful in making task-related, teamwork, and management decisions.
Abstract: In this paper, we propose an automatic verification
technology of software patches for user virtual environments on IaaS
Cloud to decrease verification costs of patches. In these days, IaaS
services have been spread and many users can customize virtual
machines on IaaS Cloud like their own private servers. Regarding to
software patches of OS or middleware installed on virtual machines,
users need to adopt and verify these patches by themselves. This task
increases operation costs of users. Our proposed method replicates
user virtual environments, extracts verification test cases for user
virtual environments from test case DB, distributes patches to virtual
machines on replicated environments and conducts those test cases
automatically on replicated environments. We have implemented the
proposed method on OpenStack using Jenkins and confirmed the
feasibility. Using the implementation, we confirmed the effectiveness
of test case creation efforts by our proposed idea of 2-tier abstraction
of software functions and test cases. We also evaluated the automatic
verification performance of environment replications, test cases
extractions and test cases conductions.
Abstract: Collection of storm water runoff and forcing it into the
groundwater is the need of the hour to sustain the ground water table.
However, the runoff entraps various types of sediments and other
floating objects whose removal are essential to avoid pollution of
ground water and blocking of pores of aquifer. However, it requires
regular cleaning and maintenance due to problem of clogging. To
evaluate the performance of filter system consisting of coarse sand
(CS), gravel (G) and pebble (P) layers, a laboratory experiment was
conducted in a rectangular column. The effect of variable thickness
of CS, G and P layers of the filtration unit of the recharge shaft on the
recharge rate and the sediment concentration of effluent water were
evaluated.
Medium sand (MS) of three particle sizes, viz. 0.150–0.300 mm
(T1), 0.300–0.425 mm (T2) and 0.425–0.600 mm of thickness 25 cm,
30 cm and 35 cm respectively in the top layer of the filter system and
having seven influent sediment concentrations of 250–3,000 mg/l
were used for experimental study. The performance was evaluated in
terms of recharge rates and clogging time. The results indicated that
100 % suspended solids were entrapped in the upper 10 cm layer of
MS, the recharge rates declined sharply for influent concentrations of
more than 1,000 mg/l. All treatments with higher thickness of MS
media indicated recharge rate slightly more than that of all treatment
with lower thickness of MS media respectively. The performance of
storm water infiltration systems was highly dependent on the
formation of a clogging layer at the filter. An empirical relationship
has been derived between recharge rates, inflow sediment load, size
of MS and thickness of MS with using MLR.
Abstract: This paper seeks to analyse the benefits of big data
and more importantly the challenges it pose to the subject of privacy
and data protection. First, the nature of big data will be briefly
deliberated before presenting the potential of big data in the present
days. Afterwards, the issue of privacy and data protection is
highlighted before discussing the challenges of implementing this
issue in big data. In conclusion, the paper will put forward the debate
on the adequacy of the existing legal framework in protecting
personal data in the era of big data.
Abstract: In this paper, we propose an intelligent system that is
used for monitoring the health conditions of patients. Monitoring the
health condition of patients is a complex problem that involves
different medical units and requires continuous monitoring especially
in rural areas because of inadequate number of available specialized
physicians. The proposed system will improve patient care and drive
costs down comparing to the existing system in Jordan. The proposed
system will be the start point to faster and improve the
communication between different units in the health system in
Jordan. Connecting patients and their physicians beyond hospital
doors regarding their geographical area is an important issue in
developing the health system in Jordan. The ability of making
medical decisions, the quality of medical is expected to be improved.
Abstract: Macro invertebrates have been used to monitor
organic pollution in rivers and streams. Several biotic indices based
on macro invertebrates have been developed over the years including
the Biological Monitoring Working Party (BMWP). A new biotic
index, the Gammarus:Asellus ratio has been recently proposed as an
index of organic pollution. This study tested the validity of the
Gammarus:Asellus ratio as an index of organic pollution, by
examining the relationship between the Gammarus:Asellus ratio and
physical chemical parameters, and other biotic indices such as
BMWP and, Average Score Per Taxon (ASPT) from lakes and
streams at Markeaton Park, Allestree Park and Kedleston Hall,
Derbyshire. Macro invertebrates were sampled using the standard
five minute kick sampling techniques physical and chemical
environmental variables were obtained based on standard sampling
techniques. Eighteen sites were sampled, six sites from Markeaton
Park (three sites across the stream and three sites across the lake). Six
sites each were also sampled from Allestree Park and Kedleston Hall
lakes. The Gammarus:Asellus ratio showed an opposite significant
positive correlations with parameters indicative of organic pollution
such as the level of nitrates, phosphates, and calcium and also
revealed a negatively significant correlations with other biotic indices
(BMWP/ASPT). The BMWP score correlated positively significantly
with some water quality parameters such as dissolved oxygen and
flow rate, but revealed no correlations with other chemical
environmental variables. The BMWP score was significantly higher
in the stream than the lake in Markeaton Park, also The ASPT scores
appear to be significantly higher in the upper Lakes than the middle
and lower lakes. This study has further strengthened the use of
BMWP/ASPT score as an index of organic pollution. But additional
application is required to validate the use of Gammarus:Asellus as a
rapid bio monitoring tool.
Abstract: Near-infrared spectroscopy (NIRS) has been widely
used as a non-invasive method to measure brain activity, but it is
corrupted by baseline drift noise. Here we present a method to measure
regional cerebral blood flow as a derivative of NIRS output. We
investigate whether, when listening to languages, blood flow can
reasonably localize and represent regional brain activity or not. The
prefrontal blood flow distribution pattern when advanced
second-language listeners listened to a second language (L2) was most
similar to that when listening to their first language (L1) among the
patterns of mean and standard deviation. In experiments with 25
healthy subjects, the maximum blood flow was localized to the left
BA46 of advanced listeners. The blood flow presented is robust to
baseline drift and stably localizes regional brain activity.
Abstract: Cell volume, together with membrane potential and
intracellular hydrogen ion concentration, is an essential biophysical
parameter for normal cellular activity. Cell volumes can be altered by
osmotically active compounds and extracellular tonicity.
In this study, a simple mathematical model of osmotically induced
cell swelling and shrinking is presented. Emphasis is given to water
diffusion across the membrane. The mathematical description of the
cellular behavior consists in a system of coupled ordinary differential
equations. We compare experimental data of cell volume alterations
driven by differences in osmotic pressure with mathematical
simulations under hypotonic and hypertonic conditions. Implications
for a future model are also discussed.
Abstract: Random epistemologies and hash tables have garnered
minimal interest from both security experts and experts in the last
several years. In fact, few information theorists would disagree with
the evaluation of expert systems. In our research, we discover how
flip-flop gates can be applied to the study of superpages. Though
such a hypothesis at first glance seems perverse, it is derived from
known results.
Abstract: Geometric and mechanical properties all influence the
resistance of RC structures and may, in certain combination of
property values, increase the risk of a brittle failure of the whole
system.
This paper presents a statistical and probabilistic investigation on
the resistance of RC beams designed according to Eurocodes 2 and 8,
and subjected to multiple failure modes, under both the natural
variation of material properties and the uncertainty associated with
cross-section and transverse reinforcement geometry. A full
probabilistic model based on JCSS Probabilistic Model Code is
derived. Different beams are studied through material nonlinear
analysis via Monte Carlo simulations. The resistance model is
consistent with Eurocode 2. Both a multivariate statistical evaluation
and the data clustering analysis of outcomes are then performed.
Results show that the ultimate load behaviour of RC beams
subjected to flexural and shear failure modes seems to be mainly
influenced by the combination of the mechanical properties of both
longitudinal reinforcement and stirrups, and the tensile strength of
concrete, of which the latter appears to affect the overall response of
the system in a nonlinear way. The model uncertainty of the
resistance model used in the analysis plays undoubtedly an important
role in interpreting results.
Abstract: Urban areas have been expanded throughout the
globe. Monitoring and modelling urban growth have become a
necessity for a sustainable urban planning and decision making.
Urban prediction models are important tools for analyzing the causes
and consequences of urban land use dynamics. The objective of this
research paper is to analyze and model the urban change, which has
been occurred from 1990 to 2000 using CORINE land cover maps.
The model was developed using drivers of urban changes (such as
road distance, slope, etc.) under an Artificial Neural Network
modelling approach. Validation was achieved using a prediction map
for 2006 which was compared with a real map of Urban Atlas of
2006. The accuracy produced a Kappa index of agreement of 0,639
and a value of Cramer's V of 0,648. These encouraging results
indicate the importance of the developed urban growth prediction
model which using a set of available common biophysical drivers
could serve as a management tool for the assessment of urban
change.
Abstract: Modelling of the earth's surface and evaluation of
urban environment, with 3D models, is an important research topic.
New stereo capabilities of high resolution optical satellites images,
such as the tri-stereo mode of Pleiades, combined with new image
matching algorithms, are now available and can be applied in urban
area analysis. In addition, photogrammetry software packages gained
new, more efficient matching algorithms, such as SGM, as well as
improved filters to deal with shadow areas, can achieve more dense
and more precise results.
This paper describes a comparison between 3D data extracted
from tri-stereo and dual stereo satellite images, combined with pixel
based matching and Wallis filter. The aim was to improve the
accuracy of 3D models especially in urban areas, in order to assess if
satellite images are appropriate for a rapid evaluation of urban
environments.
The results showed that 3D models achieved by Pleiades tri-stereo
outperformed, both in terms of accuracy and detail, the result
obtained from a Geo-eye pair. The assessment was made with
reference digital surface models derived from high resolution aerial
photography. This could mean that tri-stereo images can be
successfully used for the proposed urban change analyses.
Abstract: The study of the electrical signals produced by neural
activities of human brain is called Electroencephalography. In this
paper, we propose an automatic and efficient EEG signal
classification approach. The proposed approach is used to classify the
EEG signal into two classes: epileptic seizure or not. In the proposed
approach, we start with extracting the features by applying Discrete
Wavelet Transform (DWT) in order to decompose the EEG signals
into sub-bands. These features, extracted from details and
approximation coefficients of DWT sub-bands, are used as input to
Principal Component Analysis (PCA). The classification is based on
reducing the feature dimension using PCA and deriving the supportvectors
using Support Vector Machine (SVM). The experimental are
performed on real and standard dataset. A very high level of
classification accuracy is obtained in the result of classification.