Abstract: This is the first report from India on a beverage resulting from alcoholic fermentation of the juice of sea buckthorn (Hippophae rhamnoides L) using lab isolated yeast strain. The health promoting potential of the product was evaluated based on its total phenolic content. The most important finding was that under the present fermentation condition, the total phenolic content of the wine product was 689 mg GAE/L. Investigation of influence of bottle ageing on the sea buckthorn wine showed a slight decrease in the phenolic content (534 m mg GAE/L). This study also includes the comparative analysis of the phenolic content of wines from other selected fruit juices like grape, apple and black currant. KeywordsAlcoholic fermentation, Hippophae, Total phenolic content, Wine
Abstract: The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.
Abstract: The first and basic cause of the failure of concrete is repeated freezing (thawing) of moisture contained in the pores, microcracks, and cavities of the concrete. On transition to ice, water existing in the free state in cracks increases in volume, expanding the recess in which freezing occurs. A reduction in strength below the initial value is to be expected and further cycle of freezing and thawing have a further marked effect. By using some experimental parameters like nuclear magnetic resonance variation (NMR), enthalpy-temperature (or heat capacity) variation, we can resolve between the various water states and their effect on concrete properties during cooling through the freezing transition temperature range. The main objective of this paper is to describe the principal type of water responsible for the reduction in strength and structural damage (frost damage) of concrete following repeated freeze –thaw cycles. Some experimental work was carried out at the institute of cryogenics to determine what happens to water in concrete during the freezing transition.
Abstract: A new target detection technique is presented in this
paper for the identification of small boats in coastal surveillance. The
proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any
objects present in the scene from the background. The preprocessing
step results in an image having only the foreground objects, such as
boats, trees and other cluttered regions, and hence reduces the search
region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform
correlator (SPFJTC) technique which produces single and delta-like
correlation peak for a potential target present in the input scene. A
post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the
proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.
Abstract: Abdominal aortic aneurysms rupture (AAAs) is one of the main causes of death in the world. This is a very complex phenomenon that usually occurs “without previous warning". Currently, criteria to assess the aneurysm rupture risk (peak diameter and growth rate) can not be considered as reliable indicators. In a first approach, the main geometric parameters of aneurysms have been linked into five biomechanical factors. These are combined to obtain a dimensionless rupture risk index, RI(t), which has been validated preliminarily with a clinical case and others from literature. This quantitative indicator is easy to understand, it allows estimating the aneurysms rupture risks and it is expected to be able to identify the one in aneurysm whose peak diameter is less than the threshold value. Based on initial results, a broader study has begun with twelve patients from the Clinic Hospital of Valladolid-Spain, which are submitted to periodic follow-up examinations.
Abstract: In the present study, the effect of ferrous sulfate concentration and total solids on bioleaching of heavy metals from sewage sludge has been examined using indigenous iron-oxidizing microorganisms. The experiments on effects of ferrous sulfate concentrations on bioleaching were carried out using ferrous sulfate of different concentrations (5-20 g L-1) to optimize the concentration of ferrous sulfate for maximum bioleaching. A rapid change in the pH and ORP took place in first 2 days followed by a slow change till 16th day in all the sludge samples. A 10 g L-1 ferrous sulfate concentration was found to be sufficient in metal bioleaching in the following order: Zn: 69%>Cu: 52%>Cr: 46%>Ni: 45. Further, bioleaching using 10 g/L ferrous sulfate was found to be efficient up to 20 g L-1 sludge solids concentration. The results of the present study strongly indicate that using 10 g L-1 ferrous sulfate indigenous iron-oxidizing microorganisms can bring down pH to a value needed for significant metal solubilization.
Abstract: The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.
Abstract: Fundamental sensor-motor couplings form the backbone
of most mobile robot control tasks, and often need to be implemented
fast, efficiently and nevertheless reliably. Machine learning
techniques are therefore often used to obtain the desired sensor-motor
competences.
In this paper we present an alternative to established machine
learning methods such as artificial neural networks, that is very fast,
easy to implement, and has the distinct advantage that it generates
transparent, analysable sensor-motor couplings: system identification
through nonlinear polynomial mapping.
This work, which is part of the RobotMODIC project at the
universities of Essex and Sheffield, aims to develop a theoretical understanding
of the interaction between the robot and its environment.
One of the purposes of this research is to enable the principled design
of robot control programs.
As a first step towards this aim we model the behaviour of the
robot, as this emerges from its interaction with the environment, with
the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving
Average models with eXogenous inputs). This method produces
explicit polynomial functions that can be subsequently analysed using
established mathematical methods.
In this paper we demonstrate the fidelity of the obtained NARMAX
models in the challenging task of robot route learning; we present a
set of experiments in which a Magellan Pro mobile robot was taught
to follow four different routes, always using the same mechanism to
obtain the required control law.
Abstract: This paper describes a proposed support system which
enables applications designers to effectively create VR applications
using multiple haptic APIs. When the VR designers create
applications, it is often difficult to handle and understand many
parameters and functions that have to be set in the application program
using documentation manuals only. This complication may disrupt
creative imagination and result in inefficient coding. So, we proposed
the support application which improved the efficiency of VR
applications development and provided the interactive components of
confirmation of operations with haptic sense previously.
In this paper, we describe improvements of our former proposed
support application, which was applicable to multiple APIs and haptic
devices, and evaluate the new application by having participants
complete VR program. Results from a preliminary experiment suggest
that our application facilitates creation of VR applications.
Abstract: The objective from this paper is to design a solar
thermal engine for space vehicles orbital control and electricity
generation. A computational model is developed for the prediction of
the solar thermal engine performance for different design parameters and conditions in order to enhance the engine efficiency. The engine is divided into two main subsystems. First, the concentrator dish
which receives solar energy from the sun and reflects them to the
cavity receiver. The second one is the cavity receiver which receives
the heat flux reflected from the concentrator and transfers heat to the
fluid passing over. Other subsystems depend on the application required from the engine. For thrust application, a nozzle is
introduced to the system for the fluid to expand and produce thrust.
Hydrogen is preferred as a working fluid in the thruster application.
Results model developed is used to determine the thrust for a
concentrator dish 4 meters in diameter (provides 10 kW of energy),
focusing solar energy to a 10 cm aperture diameter cavity receiver.
The cavity receiver outer length is 50 cm and the internal cavity is 47
cm in length. The suggested design material of the internal cavity is
tungsten to withstand high temperature. The thermal model and
analysis shows that the hydrogen temperature at the plenum reaches
2000oK after about 250 seconds for hot start operation for a flow rate
of 0.1 g/sec.Using solar thermal engine as an electricity generation
device on earth is also discussed. In this case a compressor and
turbine are used to convert the heat gained by the working fluid (air)
into mechanical power. This mechanical power can be converted into
electrical power by using a generator.
Abstract: The study investigated the effects of Teaching Games
for Understanding approach on students ‘cognitive learning outcome.
The study was a quasi-experimental non-equivalent pretest-posttest
control group design whereby 10 year old primary school students
(n=72) were randomly assigned to an experimental and a control
group. The experimental group students were exposed with TGfU
approach and the control group with the Traditional Skill approach of
handball game. Game Performance Assessment Instrument (GPAI)
was used to measure students' tactical understanding and decision
making in 3 versus 3 handball game situations. Analysis of
covariance (ANCOVA) was used to analyze the data. The results
reveal that there was a significant difference between the TGfU
approach group and the traditional skill approach group students on
post test score (F (1, 69) = 248.83, p < .05). The findings of this
study suggested the importance of TGfU approach to improve
primary students’ tactical understanding and decision making in
handball game.
Abstract: Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.
Abstract: Many natural language expressions are ambiguous, and
need to draw on other sources of information to be interpreted.
Interpretation of the e word تعاون to be considered as a noun or a verb
depends on the presence of contextual cues. To interpret words we
need to be able to discriminate between different usages. This paper
proposes a hybrid of based- rules and a machine learning method for
tagging Arabic words. The particularity of Arabic word that may be
composed of stem, plus affixes and clitics, a small number of rules
dominate the performance (affixes include inflexional markers for
tense, gender and number/ clitics include some prepositions,
conjunctions and others). Tagging is closely related to the notion of
word class used in syntax. This method is based firstly on rules (that
considered the post-position, ending of a word, and patterns), and
then the anomaly are corrected by adopting a memory-based learning
method (MBL). The memory_based learning is an efficient method to
integrate various sources of information, and handling exceptional
data in natural language processing tasks. Secondly checking the
exceptional cases of rules and more information is made available to
the learner for treating those exceptional cases. To evaluate the
proposed method a number of experiments has been run, and in
order, to improve the importance of the various information in
learning.
Abstract: Quantitative trait loci (QTL) experiments have yielded
important biological and biochemical information necessary for
understanding the relationship between genetic markers and
quantitative traits. For many years, most QTL algorithms only
allowed one observation per genotype. Recently, there has been an
increasing demand for QTL algorithms that can accommodate more
than one observation per genotypic distribution. The Bayesian
hierarchical model is very flexible and can easily incorporate this
information into the model. Herein a methodology is presented that
uses a Bayesian hierarchical model to capture the complexity of the
data. Furthermore, the Markov chain Monte Carlo model composition
(MC3) algorithm is used to search and identify important markers. An
extensive simulation study illustrates that the method captures the
true QTL, even under nonnormal noise and up to 6 QTL.
Abstract: The overall objective of this research is a strain
improvement technology for efficient pectinase production. A novel
cells cultivation technology by immobilization of fungal cells has
been studied in long time continuous fermentations. Immobilization
was achieved by using of new material for absorption of stores of
immobilized cultures which was for the first time used for
immobilization of microorganisms. Effects of various conditions of
nitrogen and carbon nutrition on the biosynthesis of pectolytic
enzymes in Aspergillus awamori 1-8 strain were studied. Proposed
cultivation technology along with optimization of media components
for pectinase overproduction led to increased pectinase productivity
in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology
can be applied successfully for production of major industrial
enzymes such as α-amylase, protease, collagenase etc.
Abstract: This study explored the relationship between
occupational stress and the perceived effectiveness of men and
women managers in Ghanaian organizations. The exploration is
underlined by attempt to understand the degree to which male and
female managers in Ghanaian organizations experience occupational
stress at the workplace. The purpose is to examine the sources and
extents of occupational stress experienced by male and female
managers in Ghana. Data was collected using questionnaires and
analyzed using both descriptive statistics and correlation analysis.
The results showed that female managers in Ghana are more likely to
report of more stress experiences in the workplace than their male
counterparts. The female managers are more likely to perceive role
conflict and alienation as job stressors while the male managers
perceived blocked career as a major source of workplace stress. It is
concluded that despite the female managers experiencing enormous
level of occupational stress, there was no significant differences
between their managerial effectiveness and that of the male.
Abstract: In-place sorting algorithms play an important role in many fields such as very large database systems, data warehouses, data mining, etc. Such algorithms maximize the size of data that can be processed in main memory without input/output operations. In this paper, a novel in-place sorting algorithm is presented. The algorithm comprises two phases; rearranging the input unsorted array in place, resulting segments that are ordered relative to each other but whose elements are yet to be sorted. The first phase requires linear time, while, in the second phase, elements of each segment are sorted inplace in the order of z log (z), where z is the size of the segment, and O(1) auxiliary storage. The algorithm performs, in the worst case, for an array of size n, an O(n log z) element comparisons and O(n log z) element moves. Further, no auxiliary arithmetic operations with indices are required. Besides these theoretical achievements of this algorithm, it is of practical interest, because of its simplicity. Experimental results also show that it outperforms other in-place sorting algorithms. Finally, the analysis of time and space complexity, and required number of moves are presented, along with the auxiliary storage requirements of the proposed algorithm.
Abstract: The ability of information systems to operate in conjunction with each other encompassing communication protocols, hardware, software, application, and data compatibility layers. There has been considerable work in industry on the development of component interoperability models, such as CORBA, (D)COM and JavaBeans. These models are intended to reduce the complexity of software development and to facilitate reuse of off-the-shelf components. The focus of these models is syntactic interface specification, component packaging, inter-component communications, and bindings to a runtime environment. What these models lack is a consideration of architectural concerns – specifying systems of communicating components, explicitly representing loci of component interaction, and exploiting architectural styles that provide well-understood global design solutions. The development of complex business applications is now focused on an assembly of components available on a local area network or on the net. These components must be localized and identified in terms of available services and communication protocol before any request. The first part of the article introduces the base concepts of components and middleware while the following sections describe the different up-todate models of communication and interaction and the last section shows how different models can communicate among themselves.
Abstract: The purpose of this study is to investigate the effects
of modality principles in instructional software among first grade
pupils- achievements in the learning of Arabic Language. Two modes
of instructional software were systematically designed and
developed, audio with images (AI), and text with images (TI). The
quasi-experimental design was used in the study. The sample
consisted of 123 male and female pupils from IRBED Education
Directorate, Jordan. The pupils were randomly assigned to any one of
the two modes. The independent variable comprised the two modes
of the instructional software, the students- achievement levels in the
Arabic Language class and gender. The dependent variable was the
achievements of the pupils in the Arabic Language test. The
theoretical framework of this study was based on Mayer-s Cognitive
Theory of Multimedia Learning. Four hypotheses were postulated
and tested. Analyses of Variance (ANOVA) showed that pupils using
the (AI) mode performed significantly better than those using (TI)
mode. This study concluded that the audio with images mode was an
important aid to learning as compared to text with images mode.
Abstract: Anchovy (Engraulis Encrasicholus) and sardine
(Sardina Pilchardus) are blue fishes linked to our alimentary tradition
of Mediterranean. In our work, particularly, we tested for the first
time physical and enzymatic methods to verify the freshness of
species of blue fish, anchovy and sardine of Mediterranean. In
connection with to the lowering of the pH after post-mortem stage we
assisted to a increase in proteolytic activity of calpaine and catpsine.
Already after 2 h in post-mortem there was a significant increase.