Abstract: The influence of copper and zinc supplements on milk
production performances and health indicators was tested in a 20-
week feeding trial, with 40 Holstein-Friesian lactating cows, devided
in four groups (copper, zinc, copper-zinc and control). Correlations of
the Cu and Zn plasma values with some animal performance criteria
of health (body condition score and somatic cell counts) and
production (milk yield, peak milk yield, fat and crude protein
content) were done. During the 140 days of the experiment, the two
added minerals caused a statistically significant increase (p < 0.05) of
their plasma values after the peak of the cows’ lactations. It was also
observed that subjects that have received copper and zinc
supplements had the lowest number of somatic cell counts in milk.
The Pearson correlation test showed a positive corellation (p = 0.007,
r = + 0.851) between the plasma Zn and the milk production. The
improvement of the nutritional status improved the milk production
performances of the cows as well as their health performances.
Abstract: In biomedical implant field, a new formula is given
for the study of Radio Frequency power attenuation by simultaneous
effects of side and angular misalignment of the supply/data transfer
coils. A confrontation with the practical measurements done into a
Faraday cage, allowed a checking of the obtained theoretical results.
The DC supply systems without material connection and the data
transmitters used in the case of biomedical implants, can be well
dimensioned by taking into account the possibility of power
attenuation by misalignment of transfer coils
Abstract: Development of microprocessor controlled sensor for measurement of wind speed and direction is the aim of this study. Electrical circuits and software were developed to the existing electromechanical part of the sensor TM-W2 becoming the properties of so-called smart sensor. The measured data about wind speed (sensitivity 0.01 m/s) and direction (0-360° by step 10°) are transmitted as 16-bit information. The connection between sensor and control unit is realized by radio communication (FM 433 MHz). Transition range is 220 m if used Quad type antenna. This concept provides substitution of actual cable systems by wireless ones.
Abstract: This study was conducted to evaluate the anti-diabetic
properties of ethanolic extract of two plants commonly used in folk
medicine, Mormodica charantia (bitter melon) and Trigonella
foenum-graecum (fenugreek). The study was performed on STZinduced
diabetic rats (DM type-I). Plant extracts of these two plants
were given to STZ diabetic rats at the concentration of 500 mg/kg
body weight ,50 mg/kg body weight respectively. Cidophage®
(metformin HCl) were administered to another group to support the
results at a dose of 500 mg/kg body weight, the ethanolic extracts and
Cidophage administered orally once a day for four weeks using a
stomach tube and; serum samples were obtained for biochemical
analysis. The extracts caused significant decreases in glucose levels
compared with diabetic control rats. Insulin secretions were increased
after 4 weeks of treatment with Cidophage® compared with the
control non-diabetic rats. Levels of AST and ALT liver enzymes were
normalized by all treatments. Decreases in liver cholesterol,
triglycerides, and LDL in diabetic rats were observed with all
treatments. HDL levels were increased by the treatments in the
following order: bitter melon, Cidophage®, and fenugreek. Creatinine
levels were reduced by all treatments. Serum nitric oxide and
malonaldehyde levels were reduced by all extracts. GSH levels were
increased by all extracts. Extravasation as measured by the Evans
Blue test increased significantly in STZ-induced diabetic animals.
This effect was reversed by ethanolic extracts of bitter melon or
fenugreek.
Abstract: Building a service-centric business model requires
new knowledge and capabilities in companies. This paper enlightens
the challenges small and medium sized firms (SMEs) face when
developing their service-centric business models. This paper
examines the premise for knowledge transfer and capability
development required. The objective of this paper is to increase
knowledge about SME-s transformation to service-centric business
models.This paper reports an action research based case study. The
paper provides empirical evidence from three case companies. The
empirical data was collected through multiple methods. The findings
of the paper are: First, the developed model to analyze the current
state in companies. Second, the process of building the service –
centric business models. Third, the selection of suitable service
development methods. The lack of a holistic understanding on
service logic suggests that SMEs need practical and easy to use
methods to improve their business
Abstract: We have investigated statistical properties of the defect turbulence in 1D CGLE wherein many body interaction is involved between local depressing wave (LDW) and local standing wave (LSW). It is shown that the counting number fluctuation of LDW is subject to the sub-Poisson statistics (SUBP). The physical origin of the SUBP can be ascribed to pair extinction of LDWs based on the master equation approach. It is also shown that the probability density function (pdf) of inter-LDW distance can be identified by the hyper gamma distribution. Assuming a superstatistics of the exponential distribution (Poisson configuration), a plausible explanation is given. It is shown further that the pdf of amplitude of LDW has a fattail. The underlying mechanism of its fluctuation is examined by introducing a generalized fractional Poisson configuration.
Abstract: In order to integrate knowledge in heterogeneous
case-based reasoning (CBR) systems, ontology-based CBR system
has become a hot topic. To solve the facing problems of
ontology-based CBR system, for example, its architecture is
nonstandard, reusing knowledge in legacy CBR is deficient, ontology
construction is difficult, etc, we propose a novel approach for
semi-automatically construct ontology-based CBR system whose
architecture is based on two-layer ontology. Domain knowledge
implied in legacy case bases can be mapped from relational database
schema and knowledge items to relevant OWL local ontology
automatically by a mapping algorithm with low time-complexity. By
concept clustering based on formal concept analysis, computing
concept equation measure and concept inclusion measure, some
suggestions about enriching or amending concept hierarchy of OWL
local ontologies are made automatically that can aid designers to
achieve semi-automatic construction of OWL domain ontology.
Validation of the approach is done by an application example.
Abstract: This paper presents a customized deformable model
for the segmentation of abdominal and thoracic aortic aneurysms in
CTA datasets. An important challenge in reliably detecting aortic
aneurysm is the need to overcome problems associated with intensity
inhomogeneities and image noise. Level sets are part of an important
class of methods that utilize partial differential equations (PDEs) and
have been extensively applied in image segmentation. A Gaussian
kernel function in the level set formulation, which extracts the local
intensity information, aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in
segmentation time compared with previous implementations of level
sets. The results indicate the method is more effective than other
approaches in coping with intensity inhomogeneities.
Abstract: Thermite welding is mainly used in world. The
reasons why the thermite welding method is widely used are
that the equipment has good mobility and total working time
of that is shorter than that of the enclosed arc welding method
on site. Moreover, the operating skill, which required for
thermite welding, is less than that of for enclosed arc welding.
In the present research work, heat treatment and combined
'expulsion and heat treatment' techniques were used improve
the mechanical properties and weldment structure. The
specimens were cut in the transverse direction from expulsion
with Heat treated and heat treated Thermite Welded rails.
Specimens were prepared according to AWS standard and
subjected to tensile test, Impact test and hardness and their
results were tabulated. Microstructural analysis was carried
out with the help of SEM. Then analyze to effect of heat
treated and 'expulsion with heat treated' with the properties of
their thermite welded rails. Compare the mechanical and
microstructural properties of thermite welded rails between
heat expulsion with heat treated and heat treated. Mechanical
and microstructural response expulsion with heat treated
thermite welded rail is higher value as compared to heat
treatment.
Abstract: the research was accomplished on fresh in Latvia wild
growing cranberries and cranberry cultivars. The aim of the study
was to evaluate effect of pretreatment method and drying conditions
on the volatile compounds composition in cranberries. Berries
pre-treatment methods were: perforation, halving and
steam-blanching. The berries before drying in a cabinet drier were
pre-treated using all three methods, in microwave vacuum
drier – using a steam-blanching and halving. Volatile compounds in
cranberries were analysed using GC-MS of extracts obtained by
SPME. During present research 21 various volatile compounds were
detected in fresh cranberries: the cultivar 'Steven' - 15, 'Bergman'
and 'Early black' – 13, 'Ben Lear' and 'Pilgrim' – 11 and wild
cranberries – 14 volatile compounds. In dried cranberries 20 volatile
compounds were detected. Mathematical data processing allows
drawing a conclusion that there exists the significant influence of
cranberry cultivar, pre-treatment method and drying condition on
volatile compounds in berries and new volatile compound formation.
Abstract: This paper outlines the application of Knowledge Management (KM) principles in the context of Educational institutions. The paper caters to the needs of the engineering institutions for imparting quality education by delineating the instruction delivery process in a highly structured, controlled and quantified manner. This is done using a software tool EDULOGIC+. The central idea has been based on the engineering education pattern in Indian Universities/ Institutions. The data, contents and results produced over contiguous years build the necessary ground for managing the related accumulated knowledge. Application of KM has been explained using certain examples of data analysis and knowledge extraction.
Abstract: Digital libraries become more and more necessary in
order to support users with powerful and easy-to-use tools for
searching, browsing and retrieving media information. The starting
point for these tasks is the segmentation of video content into shots.
To segment MPEG video streams into shots, a fully automatic
procedure to detect both abrupt and gradual transitions (dissolve and
fade-groups) with minimal decoding in real time is developed in this
study. Each was explored through two phases: macro-block type's
analysis in B-frames, and on-demand intensity information analysis.
The experimental results show remarkable performance in
detecting gradual transitions of some kinds of input data and
comparable results of the rest of the examined video streams. Almost
all abrupt transitions could be detected with very few false positive
alarms.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the prevalence of obesity in this unique
population was of particular interest. Data gathered on a sub-sample
of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1),
competing at the Sydney World Masters Games (2009) demonstrated
a significantly (p
Abstract: A gradient learning method to regulate the trajectories
of some nonlinear chaotic systems is proposed. The method is
motivated by the gradient descent learning algorithms for neural
networks. It is based on two systems: dynamic optimization system
and system for finding sensitivities. Numerical results of several
examples are presented, which convincingly illustrate the efficiency
of the method.
Abstract: Part IV of the Civil Code of the Russian Federation dedicated to legal regulation of Intellectual property rights came into force in 2008. It is a first attempt of codification in Intellectual property sphere in Russia. That is why a lot of new norms appeared. The main problem of the Russian Civil Code (part IV) is that many rules (norms of Law) contradict the norms of International Intellectual property Law (i.e. protection of inventions, creations, ideas, know-how, trade secrets, innovations). Intellectual property rights protect innovations and creations and reward innovative and creative activity. Intellectual property rights are international in character and in that respect they fit in rather well with the economic reality of the global economy. Inventors prefer not to take out a patent for inventions because it is a very difficult procedure, it takes a lot of time and is very expensive. That-s why they try to protect their inventions as ideas, know-how, confidential information. An idea is the main element of any object of Intellectual property (creation, invention, innovation, know-how, etc.). But ideas are not protected by Civil Code of Russian Federation. The aim of the paper is to reveal the main problems of legal regulation of Intellectual property in Russia and to suggest possible solutions. The authors of this paper have raised these essential issues through different activities. Through the panel survey, questionnaires which were spread among the participants of intellectual activities the main problems of implementation of innovations, protecting of the ideas and know-how were identified. The implementation of research results will help to solve economic and legal problems of innovations, transfer of innovations and intellectual property.1
Abstract: When faced with stochastic networks with an uncertain
duration for their activities, the securing of network completion time
becomes problematical, not only because of the non-identical pdf of
duration for each node, but also because of the interdependence of
network paths. As evidenced by Adlakha & Kulkarni [1], many
methods and algorithms have been put forward in attempt to resolve
this issue, but most have encountered this same large-size network
problem. Therefore, in this research, we focus on network reduction
through a Series/Parallel combined mechanism. Our suggested
algorithm, named the Activity Network Reduction Algorithm
(ANRA), can efficiently transfer a large-size network into an S/P
Irreducible Network (SPIN). SPIN can enhance stochastic network
analysis, as well as serve as the judgment of symmetry for the Graph
Theory.
Abstract: In order to Study the efficacy application of green
manure as chickpea pre plant, field experiments were carried out in
2007 and 2008 growing seasons. In this research the effects of
different strategies for soil fertilization were investigated on grain
yield and yield component, minerals, organic compounds and
cooking time of chickpea. Experimental units were arranged in splitsplit
plots based on randomized complete blocks with three
replications. Main plots consisted of (G1): establishing a mixed
vegetation of Vicia panunica and Hordeum vulgare and (G2):
control, as green manure levels. Also, five strategies for obtaining the
base fertilizer requirement including (N1): 20 t.ha-1 farmyard manure;
(N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate;
(N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5): 10 t.ha-1
farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1 triple super
phosphate were considered in sub plots. Furthermoree four levels of
biofertilizers consisted of (B1): Bacillus lentus + Pseudomonas
putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus +
Pseudomonas putida + Trichoderma harzianum; and (B4): control
(without biofertilizers) were arranged in sub-sub plots. Results
showed that integrating biofertilizers (B3) and green manure (G1)
produced the highest grain yield. The highest amounts of yield were
obtained in G1×N5 interaction. Comparison of all 2-way and 3-way
interactions showed that G1N5B3 was determined as the superior
treatment. Significant increasing of N, P2O5, K2O, Fe and Mg content
in leaves and grains emphasized on superiority of mentioned
treatment because each one of these nutrients has an approved role in
chlorophyll synthesis and photosynthesis abilities of the crops. The
combined application of compost, farmyard manure and chemical
phosphorus (N5) in addition to having the highest yield, had the best
grain quality due to high protein, starch and total sugar contents, low
crude fiber and reduced cooking time.
Abstract: Hepatitis B and hepatitis C are among the most
significant hepatic infections all around the world that may lead to
hepatocellular carcinoma. This study is first time performed at the
blood transfussion centre of Omar hospital, Lahore. It aims to
determine the sero-prevalence of these diseases by screening the
apparently healthy blood donors who might be the carriers of HBV or
HCV and pose a high risk in the transmission. It also aims the
comparison between the sensitivity of two diagnostic tests;
chromatographic immunoassay – one step test device and Enzyme
Linked Immuno Sorbant Assay (ELISA). Blood serum of 855
apparently healthy blood donors was screened for Hepatitis B surface
antigen (HBsAg) and for anti HCV antibodies. SPSS version 12.0
and X2 (Chi-square) test were used for statistical analysis. The seroprevalence
of HCV was 8.07% by the device method and by ELISA
9.12% and that of HBV was 5.6% by the device and 6.43% by
ELISA. The unavailability of vaccination against HCV makes it more
prevalent. Comparing the two diagnostic methods, ELISA proved to
be more sensitive.
Abstract: Hydrogen diffusion is the main problem for corrosion fatigue in corrosive environment. In order to analyze the phenomenon, it is needed to understand their behaviors specially the hydrogen behavior during the diffusion. So, Hydrogen embrittlement and prediction its behavior as a main corrosive part of the fractions, needed to solve combinations of different equations mathematically. The main point to obtain the equation, having knowledge about the source of causing diffusion and running the atoms into materials, called driving force. This is produced by either gradient of electrical or chemical potential. In this work, we consider the gradient of chemical potential to obtain the property equation. In diffusion of atoms, some of them may be trapped but, it could be ignorable in some conditions. According to the phenomenon of hydrogen embrittlement, the thermodynamic and chemical properties of hydrogen are considered to justify and relate them to fracture mechanics. It is very important to get a stress intensity factor by using fugacity as a property of hydrogen or other gases. Although, the diffusive behavior and embrittlement event are common and the same for other gases but, for making it more clear, we describe it for hydrogen. This considering on the definite gas and describing it helps us to understand better the importance of this relation.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.