Abstract: The question of legal liability over injury arising out
of the import and the introduction of GM food emerges as a crucial
issue confronting to promote GM food and its derivatives. There is a
greater possibility of commercialized GM food from the exporting
country to enter importing country where status of approval shall not
be same. This necessitates the importance of fixing a liability
mechanism to discuss the damage, if any, occurs at the level of
transboundary movement or at the market. There was a widespread consensus to develop the Cartagena
Protocol on Biosafety and to give for a dedicated regime on liability
and redress in the form of Nagoya Kuala Lumpur Supplementary
Protocol on the Liability and Redress (‘N-KL Protocol’) at the
international context. The national legal frameworks based on this
protocol are not adequately established in the prevailing food
legislations of the developing countries. The developing economy
like India is willing to import GM food and its derivatives after the
successful commercialization of Bt Cotton in 2002. As a party to the
N-KL Protocol, it is indispensable for India to formulate a legal
framework and to discuss safety, liability, and regulatory issues
surrounding GM foods in conformity to the provisions of the
Protocol. The liability mechanism is also important in the case where
the risk assessment and risk management is still in implementing
stage. Moreover, the country is facing GM infiltration issues with its
neighbors Bangladesh. As a precautionary approach, there is a need
to formulate rules and procedure of legal liability to discuss any kind
of damage occurs at transboundary trade. In this context, the
proposed work will attempt to analyze the liability regime in the
existing Food Safety and Standards Act, 2006 from the applicability
and domestic compliance and to suggest legal and policy options for
regulatory authorities.
Abstract: Average temperatures worldwide are expected to
continue to rise. At the same time, major cities in developing
countries are becoming increasingly populated and polluted.
Governments are tasked with the problem of overheating and air
quality in residential buildings. This paper presents the development
of a model, which is able to estimate the occupant exposure
to extreme temperatures and high air pollution within domestic
buildings. Building physics simulations were performed using the
EnergyPlus building physics software. An accurate metamodel is
then formed by randomly sampling building input parameters and
training on the outputs of EnergyPlus simulations. Metamodels are
used to vastly reduce the amount of computation time required when
performing optimisation and sensitivity analyses. Neural Networks
(NNs) have been compared to a Radial Basis Function (RBF)
algorithm when forming a metamodel. These techniques were
implemented using the PyBrain and scikit-learn python libraries,
respectively. NNs are shown to perform around 15% better than RBFs
when estimating overheating and air pollution metrics modelled by
EnergyPlus.
Abstract: Value addition to agricultural produce is of possible
potential in reducing poverty, improving food security and
malnutrition, therefore the need to develop small and microenterprises
of sweet potato production. A study was carried out in Nigeria to determine the acceptability
of blends sweet potato (Ipomea batatas) and commodities yellow
maize (Zea mays), millet (Pennisetum glaucum), soybean (Glycine
max), bambara groundnut (Vigna subterranean), guinea corn
(Sorghum vulgare), wheat (Triticum aestivum), and roselle (Hibiscus
sabdariffa) through sensory evaluation. Sweet potato (Ipomea batatas) roots were processed using two
methods: oven and sun drying. The blends were also assessed in
terms of functional, chemical and color properties. Most acceptable blends include BAW (80:20 of sweet
potato/wheat), BBC (80:20 of sweet potato/guinea corn), AAB (60:40
of sweet potato/guinea corn), YTE (100% soybean), TYG (100%
sweet potato), KTN (100% wheat flour), XGP (80:20 of sweet
potato/soybean), XAX (60:40 of sweet potato/wheat), LSS (100%
Roselle), CHK (100% Guinea corn), and ABC (60:40% of sweet
potato/ yellow maize). In addition, carried out chemical analysis
revealed that sweet potato has high percentage of vitamins A and C,
potassium (K), manganese (Mn), calcium (Ca), magnesium (Mg) and
iron (Fe) and fibre content. There is also an increase of vitamin A and
Iron in the blended products.
Abstract: Dengue is a mosquito-borne viral disease endemic in
many countries in the tropics and sub-tropics. The state of Punjab in
India shows cyclical and seasonal variation in dengue cases. The
Case Fatality Rate of Dengue has ranged from 0.6 to 1.0 in the past
years. The department has initiated review of the cases that have died
due to dengue in order to know the exact cause of the death in a case
of dengue. The study has been undertaken to know the other
associated co-morbidities and factors causing death in a case of
dengue. The study used the predesigned proforma on which the
records (medical and Lab) were recorded and reviewed by the expert
committee of the doctors. This study has revealed that cases of
dengue having co-morbidities have longer stay in hospital. Fluid
overload and co-morbidities have been found as major factors leading
to death, however, in a confirmed case of dengue hepatorenal
shutdown was found to be major cause of mortality. The data
obtained will help in sensitizing the treating physicians in order to
decrease the mortality due to dengue in future.
Abstract: The Internet of Things (IoT) field has been applied in
industries with different purposes. Sensing Enterprise (SE) is an
attribute of an enterprise or a network that allows it to react to
business stimuli originating on the Internet. These fields have come
into focus recently on the enterprises, and there is some evidence of
the use and implications in supply chain management, while
finding it as an interesting aspect to work on. This paper presents a
revision and proposals of IoT applications in supply chain
management.
Abstract: Prior literature in the field of adaptive and
personalized learning sequence in e-learning have proposed and
implemented various mechanisms to improve the learning process
such as individualization and personalization, but complex to
implement due to expensive algorithmic programming and need of
extensive and prior data. The main objective of personalizing
learning sequence is to maximize learning by dynamically selecting
the closest teaching operation in order to achieve the learning
competency of learner. In this paper, a revolutionary technique has
been proposed and tested to perform individualization and
personalization using modified reversed roulette wheel selection
algorithm that runs at O(n). The technique is simpler to implement
and is algorithmically less expensive compared to other revolutionary
algorithms since it collects the dynamic real time performance matrix
such as examinations, reviews, and study to form the RWSA single
numerical fitness value. Results show that the implemented system is
capable of recommending new learning sequences that lessens time
of study based on student's prior knowledge and real performance
matrix.
Abstract: In this paper, de Laval rotor system has been
characterized by a hinge model and its transient response numerically
treated for a dynamic solution. The effect of the ensuing non-linear
disturbances namely rub and breathing crack is numerically
simulated. Subsequently, three analysis methods: Orbit Analysis, Fast
Fourier Transform (FFT), and Wavelet Transform (WT) are
employed to extract features of the vibration signal of the faulty
system. An analysis of the system response orbits clearly indicates
the perturbations due to the rotor-to-stator contact. The sensitivities
of WT to the variation in system speed have been investigated by
Continuous Wavelet Transform (CWT). The analysis reveals that
features of crack, rubs and unbalance in vibration response can be
useful for condition monitoring. WT reveals its ability to detect nonlinear
signal, and obtained results provide a useful tool method for
detecting machinery faults.
Abstract: In order to utilize results from global climate models,
dynamical and statistical downscaling techniques have been
developed. For dynamical downscaling, usually a limited area
numerical model is used, with associated high computational cost.
This research proposes dynamic equation for specific space-time
regional climate downscaling from the Educational Global Climate
Model (EdGCM) for Southeast Asia. The equation is for surface air
temperature. This equation provides downscaling values of surface
air temperature at any specific location and time without running a
regional climate model. In the proposed equations, surface air
temperature is approximated from ground temperature, sensible heat
flux and 2m wind speed. Results from the application of the equation
show that the errors from the proposed equations are less than the
errors for direct interpolation from EdGCM.
Abstract: As one of the convenient and noninvasive sensing
approaches, the automatic limb girth measurement has been applied
to detect intention behind human motion from muscle deformation.
The sensing validity has been elaborated by preliminary researches
but still need more fundamental studies, especially on kinetic
contraction modes. Based on the novel fabric strain sensors, a soft
and smart limb girth measurement system was developed by the
authors’ group, which can measure the limb girth in-motion.
Experiments were carried out on elbow isometric flexion and elbow
isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and
120°/s for 10 subjects (2 canoeists and 8 ordinary people). After
removal of natural circumferential increments due to elbow position,
the joint torque is found not uniformly sensitive to the limb
circumferential strains, but declining as elbow joint angle rises,
regardless of the angular speed. Moreover, the maximum joint torque
was found as an exponential function of the joint’s angular speed.
This research highly contributes to the application of the automatic
limb girth measuring during kinetic contractions, and it is useful to
predict the contraction level of voluntary skeletal muscles.
Abstract: Microcantilevers are the basic MEMS devices, which
can be used as sensors, actuators and electronics can be easily built
into them. The detection principle of microcantilever sensors is based
on the measurement of change in cantilever deflection or change in its
resonance frequency. The objective of this work is to explore the
analogies between mechanical and electrical equivalent of
microcantilever beams. Normally scientists and engineers working in
MEMS use expensive software like CoventorWare, IntelliSuite,
ANSYS/Multiphysics etc. This paper indicates the need of developing
electrical equivalent of the MEMS structure and with that, one can
have a better insight on important parameters, and their interrelation of
the MEMS structure. In this work, considering the mechanical model
of microcantilever, equivalent electrical circuit is drawn and using
force-voltage analogy, it is analyzed with circuit simulation software.
By doing so, one can gain access to powerful set of intellectual tools
that have been developed for understanding electrical circuits Later
the analysis is performed using ANSYS/Multiphysics - software based
on finite element method (FEM). It is observed that both mechanical
and electrical domain results for a rectangular microcantlevers are in
agreement with each other.
Abstract: Mechanical behavior of 6082T6 aluminum is
investigated at different temperatures. The strain rate sensitivity is
investigated at different temperatures on the grain size variants. The
sensitivity of the measured grain size variants on 3-D grain is
discussed. It is shown that the strain rate sensitivities are negative for
the grain size variants during the deformation of nanostructured
materials. It is also observed that the strain rate sensitivities vary in
different ways with the equivalent radius, semi minor axis radius,
semi major axis radius and major axis radius. From the obtained
results, it is shown that the variation of strain rate sensitivity with
temperature suggests that the strain rate sensitivity at the low and the
high temperature ends of the 6082T6 aluminum range is different.
The obtained results revealed transition at different temperature from
negative strain rate sensitivity as temperature increased on the grain
size variants.
Abstract: This paper introduces a signal monitoring program
developed with a view to helping electrical engineering students get
familiar with sensors with digital output. Because the output of digital
sensors cannot be simply monitored by a measuring instrument such as
an oscilloscope, students tend to have a hard time dealing with digital
sensors. The monitoring program runs on a PC and communicates with
an MCU that reads the output of digital sensors via an asynchronous
communication interface. Receiving the sensor data from the MCU,
the monitoring program shows time and/or frequency domain plots of
the data in real time. In addition, the monitoring program provides a
serial terminal that enables the user to exchange text information with
the MCU while the received data is plotted. The user can easily
observe the output of digital sensors and configure the digital sensors
in real time, which helps students who do not have enough experiences
with digital sensors. Though the monitoring program was programmed
in the Matlab programming language, it runs without the Matlab since
it was compiled as a standalone executable.
Abstract: In this paper, a robust fault detection and isolation
(FDI) scheme is developed to monitor a multivariable nonlinear
chemical process called the Chylla-Haase polymerization reactor,
when it is under the cascade PI control. The scheme employs a radial
basis function neural network (RBFNN) in an independent mode to
model the process dynamics, and using the weighted sum-squared
prediction error as the residual. The Recursive Orthogonal Least
Squares algorithm (ROLS) is employed to train the model to
overcome the training difficulty of the independent mode of the
network. Then, another RBFNN is used as a fault classifier to isolate
faults from different features involved in the residual vector. Several
actuator and sensor faults are simulated in a nonlinear simulation of
the reactor in Simulink. The scheme is used to detect and isolate the
faults on-line. The simulation results show the effectiveness of the
scheme even the process is subjected to disturbances and
uncertainties including significant changes in the monomer feed rate,
fouling factor, impurity factor, ambient temperature, and
measurement noise. The simulation results are presented to illustrate
the effectiveness and robustness of the proposed method.
Abstract: The underutilization of biomass resources in the
Philippines, combined with its growing population and the rise in
fossil fuel prices confirms demand for alternative energy sources. The
goal of this paper is to provide a comparison of MODIS-based and
Landsat-based agricultural land cover maps when used in the
estimation of rice hull’s available energy potential. Biomass resource
assessment was done using mathematical models and remote sensing
techniques employed in a GIS platform.
Abstract: This study aims to examine the sensory quality of
meatballs made from Balinese beef and buffalo meat after the
addition of smoke powder prior to storage at the temperatures of 2-
5°C for 7 days. This study used meat from Longissimus dorsi muscle
of male Balinese cattle aged 3 years and of male buffalo aged 5 years
as the main raw materials, and smoke powder as a binder and
preservative in making meatballs. The study was based on completely
randomized design (CRD) of factorial pattern of 2 x 3 x 2 where
factors 1, 2 and 3 included the types of meat (cattle and buffalo),
types of smoke powder (oven dried, freeze dried and spray dried)
with a level of 2% of the weight of the meat (w/w), and storage
duration (0 and 7 days) with three replications, respectively. The
parameters measured were the meatball sensory quality (scores of
tenderness, firmness, chewing residue, and intensity of flavor). The
results of this study show that each type of meat has produced
different sensory characteristics. The meatballs made from buffalo
meat have higher tenderness and elasticity scores than the Balinese
beef. Meanwhile, the buffalo meatballs have a lower residue
mastication score than the Balinese beef. Each type of smoke
powders has produced a relatively similar sensory quality of
meatballs. It can be concluded that the smoke powder of 2% of the
weight of the meat (w/w) could maintain the sensory quality of the
meatballs for 7 days of storage.
Abstract: In this paper, we have reported birefringence
manipulation in regenerated high birefringent fiber Bragg grating
(RPMG) by using CO2 laser annealing method. The results indicate
that the birefringence of RPMG remains unchanged after CO2 laser
annealing followed by slow cooling process, but reduced after fast
cooling process (~5.6×10-5). After a series of annealing procedures
with different cooling rates, the obtained results show that slower the
cooling rate, higher the birefringence of RPMG. The volume, thermal
expansion coefficient (TEC) and glass transition temperature (Tg)
change of stress applying part in RPMG during cooling process are
responsible for the birefringence change. Therefore, these findings
are important to the RPMG sensor in high and dynamic temperature
environment. The measuring accuracy, range and sensitivity of
RPMG sensor is greatly affected by its birefringence value. This
work also opens up a new application of CO2 laser for fiber annealing
and birefringence modification.
Abstract: Within this paper, latest results on processing of energetic nanomaterials by means of the Spray Flash Evaporation technique are presented. This technology constitutes a highly effective and continuous way to prepare fascinating materials on the nano- and micro-scale. Within the process, a solution is set under high pressure and sprayed into an evacuated atomization chamber. Subsequent ultrafast evaporation of the solvent leads to an aerosol stream, which is separated by cyclones or filters. No drying gas is required, so the present technique should not be confused with spray dying. Resulting nanothermites, insensitive explosives or propellants and compositions are foreseen to replace toxic (according to REACH) and very sensitive matter in military and civil applications. Diverse examples are given in detail: nano-RDX (n-Cyclotrimethylentrinitramin) and nano-aluminum based systems, mixtures (n-RDX/n-TNT - trinitrotoluene) or even cocrystalline matter like n-CL-20/HMX (Hexanitrohexaazaisowurtzitane/ Cyclotetra-methylentetranitramin). These nanomaterials show reduced sensitivity by trend without losing effectiveness and performance. An analytical study for material characterization was performed by using Atomic Force Microscopy, X-Ray Diffraction, and combined techniques as well as spectroscopic methods. As a matter of course, sensitivity tests regarding electrostatic discharge, impact, and friction are provided.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.
Abstract: This paper describes the development of a DNA-based
nanobiosensor to detect the dengue virus in mosquito using
electrically active magnetic (EAM) nanoparticles as concentrator and
electrochemical transducer. The biosensor detection encompasses
two sets of oligonucleotide probes that are specific to the dengue
virus: the detector probe labeled with the EAM nanoparticles and the
biotinylated capture probe. The DNA targets are double hybridized to
the detector and the capture probes and concentrated from
nonspecific DNA fragments by applying a magnetic field.
Subsequently, the DNA sandwiched targets (EAM-detector probe–
DNA target–capture probe-biotin) are captured on streptavidin
modified screen printed carbon electrodes through the biotinylated
capture probes. Detection is achieved electrochemically by measuring
the oxidation–reduction signal of the EAM nanoparticles. Results
indicate that the biosensor is able to detect the redox signal of the
EAM nanoparticles at dengue DNA concentrations as low as 10
ng/μl.
Abstract: Noninvasive diagnostics of diseases via breath
analysis has attracted considerable scientific and clinical interest for
many years and become more and more promising with the rapid
advancements in nanotechnology and biotechnology. The volatile
organic compounds (VOCs) in exhaled breath, which are mainly
blood borne, particularly provide highly valuable information about
individuals’ physiological and pathophysiological conditions.
Additionally, breath analysis is noninvasive, real-time, painless, and
agreeable to patients. We have developed a wireless sensor array
based on single-stranded DNA (ssDNA)-functionalized single-walled
carbon nanotubes (SWNT) for the detection of a number of
physiological indicators in breath. Seven DNA sequences were used
to functionalize SWNT sensors to detect trace amount of methanol,
benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol,
which are indicators of heavy smoking, excessive drinking, and
diseases such as lung cancer, breast cancer, and diabetes. Our test
results indicated that DNA functionalized SWNT sensors exhibit
great selectivity, sensitivity, and repeatability; and different
molecules can be distinguished through pattern recognition enabled
by this sensor array. Furthermore, the experimental sensing results
are consistent with the Molecular Dynamics simulated ssDNAmolecular
target interaction rankings. Thus, the DNA-SWNT sensor
array has great potential to be applied in chemical or biomolecular
detection for the noninvasive diagnostics of diseases and personal
health monitoring.