Abstract: MicroRNAs (miRNAs) are small, non-coding and
regulatory RNAs about 20 to 24 nucleotides long. Their conserved
nature among the various organisms makes them a good source of
new miRNAs discovery by comparative genomics approach. The
study resulted in 21 miRNAs of 20 pre-miRNAs belonging to 16
families (miR156, 157, 158, 164, 165, 168, 169, 172, 319, 390, 393,
394, 395, 400, 472 and 861) in evergreen spruce tree (Picea). The
miRNA families; miR 157, 158, 164, 165, 168, 169, 319, 390, 393,
394, 400, 472 and 861 are reported for the first time in the Picea. All
20 miRNA precursors form stable minimum free energy stem-loop
structure as their orthologues form in Arabidopsis and the mature
miRNA reside in the stem portion of the stem loop structure. Sixteen
(16) miRNAs are from Picea glauca and five (5) belong to Picea
sitchensis. Their targets consist of transcription factors, growth
related, stressed related and hypothetical proteins.
Abstract: Housebuilders in England have been the target of numerous government policies in recent years promoting increased productivity and affordability. As a result, the housebuilding industry is currently faced with objectives to improve the affordability and sustainability of new homes whilst also increasing production rates to 240,000 per year by 2016.Yet amidst a faltering economic climate, the UK Government is forging ahead with the 'Code for Sustainable Homes', which includes stringent sustainable standards for all new homes and sets ambitious targets for the housebuilding industry, the culmination of which is the production of zero carbon homes by 2016.Great uncertainty exists amongst housebuilders as to the costs, benefits and risks of building zero carbon homes. This paper examines the key barriers to zero carbon homes from housebuilders- perspective. A comprehensive opinion on the challenges to deliver zero carbon homes is gathered through a questionnaire survey issued to the major housing developers in England. The study found that a number of cultural, legislative, and financial barriers stand in the way of the widespread construction of zero carbon homes. The study concludes with several recommendations to both the Government and the housebuilding industry to address the barriers that hinder a successful delivery of zero carbon homes in England.
Abstract: In this paper, a Cooperative Multi-robot for Carrying
Targets (CMCT) algorithm is proposed. The multi-robot team
consists of three robots, one is a supervisor and the others are
workers for carrying boxes in a store of 100×100 m2. Each robot has
a self recharging mechanism. The CMCT minimizes robot-s worked
time for carrying many boxes during day by working in parallel. That
is, the supervisor detects the required variables in the same time
another robots work with previous variables. It works with
straightforward mechanical models by using simple cosine laws. It
detects the robot-s shortest path for reaching the target position
avoiding obstacles by using a proposed CMCT path planning
(CMCT-PP) algorithm. It prevents the collision between robots
during moving. The robots interact in an ad hoc wireless network.
Simulation results show that the proposed system that consists of
CMCT algorithm and its accomplished CMCT-PP algorithm
achieves a high improvement in time and distance while performing
the required tasks over the already existed algorithms.
Abstract: Sputter deposition processes, especially for sputtering
from metal targets, are well investigated. For practical reasons, i.e.
for industrial processes, energetic considerations for sputter
deposition are useful in order to optimize the sputtering process. In
particular, for substrates at floating conditions it is required to obtain
energetic conditions during film growth that enables sufficient dense
metal films of good quality. The influence of ion energies, energy
density and momentum transfer is thus examined both for sputtering
at the target as well as during film growth. Different regimes
dominated by ion energy, energy density and momentum transfer
were identified by using different plasma sources and by varying
power input, pressure and bias voltage.
Abstract: We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.
Abstract: Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.
Abstract: In this paper, a new time-delay estimation
technique based on the cross IB-energy operator [5] is
introduced. This quadratic energy detector measures how
much a signal is present in another one. The location of the
peak of the energy operator, corresponding to the maximum of
interaction between the two signals, is the estimate of the
delay. The method is a fully data-driven approach. The
discrete version of the continuous-time form of the cross IBenergy
operator, for its implementation, is presented. The
effectiveness of the proposed method is demonstrated on real
underwater acoustic signals arriving from targets and the
results compared to the cross-correlation method.
Abstract: In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.
Abstract: Vision based tracking problem is solved through a
combination of optical flow, MACH filter and log r-θ mapping.
Optical flow is used for detecting regions of movement in video
frames acquired under variable lighting conditions. The region of
movement is segmented and then searched for the target. A template
is used for target recognition on the segmented regions for detecting
the region of interest. The template is trained offline on a sequence of
target images that are created using the MACH filter and log r-θ
mapping. The template is applied on areas of movement in
successive frames and strong correlation is seen for in-class targets.
Correlation peaks above a certain threshold indicate the presence of
target and the target is tracked over successive frames.
Abstract: This work develops a novel intelligent “model of dynamic decision-making" usingcell assemblies network architecture in robot's movement. The “model of dynamic decision-making" simulates human decision-making, and follows commands to make the correct decisions. The cell assemblies approach consisting of fLIF neurons was used to implement tasks for finding targets and avoiding obstacles. Experimental results show that the cell assemblies approach of can be employed to efficiently complete finding targets and avoiding obstacles tasks and can simulate the human thinking and the mode of information transactions.
Abstract: Road industry has challenged the prospect of ecoconstruction. Pavements may fit within the framework of sustainable development. Hence, research implements assessments of conventional pavements impacts on environment in use of life cycle approach. To meet global, and often national, targets on pollution control, newly introduced pavement designs are under study. This is the case of Cyprus demonstration, which occurred within EcoLanes project work. This alternative pavement differs on concrete layer reinforced with tire recycling product. Processing of post-consumer tires produces steel fibers improving strength capacity against cracking. Thus maintenance works are relevantly limited in comparison to flexible pavement. This enables to be more ecofriendly, referenced to current study outputs. More specific, proposed concrete pavement life cycle processes emits 15 % less air pollutants and consumes 28 % less embodied energy than those of the asphalt pavement. In addition there is also a reduction on costs by 0.06 %.
Abstract: There is an urgent need to develop novel
Mycobacterium tuberculosis (Mtb) drugs that are active against drug
resistant bacteria but, more importantly, kill persistent bacteria. Our
study structured based on integrated analysis of metabolic pathways,
small molecule screening and similarity Search in PubChem
Database. Metabolic analysis approaches based on Unified weighted
used for potent target selection. Our results suggest that pantothenate
synthetase (panC) and and 3-methyl-2-oxobutanoate hydroxymethyl
transferase (panB) as a appropriate drug targets. In our study, we
used pantothenate synthetase because of existence inhibitors. We
have reported the discovery of new antitubercular compounds
through ligand based approaches using computational tools.
Abstract: Environmental aspects plays a central role in environmental management system (EMS) because it is the basis for the identification of an organization-s environmental targets. The
existing methods for the assessment of environmental aspects are grouped into three categories: risk assessment-based (RA-based),
LCA-based and criterion-based methods. To combine the benefits of
these three categories of research, this study proposes an integrated framework, combining RA-, LCA- and criterion-based methods. The
integrated framework incorporates LCA techniques for the identification of the causal linkage for aspect, pathway, receptor and
impact, uses fuzzy logic to assess aspects, considers fuzzy conditions,
in likelihood assessment, and employs a new multi-criteria decision analysis method - multi-criteria and multi-connection comprehensive
assessment (MMCA) - to estimate significant aspects in EMS. The proposed model is verified, using a real case study and the results show
that this method successfully prioritizes the environmental aspects.
Abstract: Studies in neuroscience suggest that both global and
local feature information are crucial for perception and recognition of
faces. It is widely believed that local feature is less sensitive to
variations caused by illumination, expression and illumination. In
this paper, we target at designing and learning local features for face
recognition. We designed three types of local features. They are
semi-global feature, local patch feature and tangent shape feature.
The designing of semi-global feature aims at taking advantage of
global-like feature and meanwhile avoiding suppressing AdaBoost
algorithm in boosting weak classifies established from small local
patches. The designing of local patch feature targets at automatically
selecting discriminative features, and is thus different with traditional
ways, in which local patches are usually selected manually to cover
the salient facial components. Also, shape feature is considered in
this paper for frontal view face recognition. These features are
selected and combined under the framework of boosting algorithm
and cascade structure. The experimental results demonstrate that the
proposed approach outperforms the standard eigenface method and
Bayesian method. Moreover, the selected local features and
observations in the experiments are enlightening to researches in
local feature design in face recognition.
Abstract: This paper evaluates performances of an adaptive noise
cancelling (ANC) based target detection algorithm on a set of real test
data supported by the Defense Evaluation Research Agency (DERA
UK) for multi-target wideband active sonar echolocation system. The
hybrid algorithm proposed is a combination of an adaptive ANC
neuro-fuzzy scheme in the first instance and followed by an iterative
optimum target motion estimation (TME) scheme. The neuro-fuzzy
scheme is based on the adaptive noise cancelling concept with the
core processor of ANFIS (adaptive neuro-fuzzy inference system) to
provide an effective fine tuned signal. The resultant output is then
sent as an input to the optimum TME scheme composed of twogauge
trimmed-mean (TM) levelization, discrete wavelet denoising
(WDeN), and optimal continuous wavelet transform (CWT) for
further denosing and targets identification. Its aim is to recover the
contact signals in an effective and efficient manner and then determine
the Doppler motion (radial range, velocity and acceleration) at very
low signal-to-noise ratio (SNR). Quantitative results have shown that
the hybrid algorithm have excellent performance in predicting targets-
Doppler motion within various target strength with the maximum
false detection of 1.5%.
Abstract: An alarming emergence of multidrug-resistant strains
of the tuberculosis pathogen Mycobacterium tuberculosis and
continuing high worldwide incidence of tuberculosis has invigorated
the search for novel drug targets. The enzyme glutamate racemase
(MurI) in bacteria catalyzes the stereoconversion of L-glutamate to
D-glutamate which is a component of the peptidoglycan cell wall of
the bacterium. The inhibitors targeted against MurI from several
bacterial species have been patented and are advocated as promising
antibacterial agents. However there are none available against MurI
from Mycobacterium tuberculosis, due to the lack of its threedimensional
structure. This work accomplished two major objectives.
First, the tertiary structure of MtMurI was deduced computationally
through homology modeling using the templates from bacterial
homologues. It is speculated that like in other Gram-positive bacteria,
MtMurI exists as a dimer and many of the protein interactions at the
dimer interface are also conserved. Second, potent candidate
inhibitors against MtMurI were identified through docking against
already known inhibitors in other organisms.