808 research outputs found
Nematicidal and allelopathic responses of Lantana camara root extract
The impact of root leachates of Lantana camara L., a tropical weed, against Meloidogyne javanica, the
root-knot nematode, was tested under laboratory and pot conditions. Concentrated and diluted root leachate caused
substantial mortality of M. javanica juveniles. Significant suppression of the nematode was achieved when soil was
treated with a full-strength concentration of the leachate. Whilst this high concentration retarded plant height and
shoot fresh weight, more diluted concentrations actually enhanced plant growth. To establish whether this inhibition
of plant growth from the leachate was the result of depleted nitrogen levels in the soil due to the leachate, soil treated
with such leachates was given urea as an additional nitrogen source. Urea not only enhanced nematode suppression
activity of the root leachates but also increased seedling emergence and growth of mungbean. Application of the L.
camara root leachates in combination with Pseudomonas aeruginosa, a plant growth-promoting rhizobacterium,
significantly reduced nematode population densities in roots and subsequent root-knot infection, and enhanced plant
growth. While a high concentration of root leachate slightly reduced P. aeruginosa colonization in the rhizosphere
and inner root tissues, the nematicidal efficacy of the bacterium was unaffected. The root leachate of L. camara was
found to contain phenolic compounds, including p-hydroxybenzoic acid, vanillic acid, caffeic acid, ferulic acid and a
quercetin glycoside, 7-glucoside. It also contained weak enzymic hydrogen cyanide
Massless BTZ black holes in minisuperspace
We study aspects of the propagation of strings on BTZ black holes. After
performing a careful analysis of the global spacetime structure of generic BTZ
black holes, and its relation to the geometry of the SL(2,R) group manifold, we
focus on the simplest case of the massless BTZ black hole. We study the SL(2,R)
Wess-Zumino-Witten model in the worldsheet minisuperspace limit, taking into
account special features associated to the Lorentzian signature of spacetime.
We analyse the two- and three-point functions in the pointparticle limit. To
lay bare the underlying group structure of the correlation functions, we derive
new results on Clebsch-Gordan coefficients for SL(2,R) in a parabolic basis. We
comment on the application of our results to string theory in singular
time-dependent orbifolds, and to a Lorentzian version of the AdS/CFT
correspondence.Comment: 28 pages, v2: reference adde
Comparative evaluation of in vitro cytotoxic effects among parent abietyl alcohol and novel fatty acid ester derivatives against MCF7 and hepatocellular carcinoma cell lines
Synthesis of twelve hitherto unreported esters of abietyl alcohol and screening of these esters against four cancer cell lines including one breast cancer line MCF7 and four hepatocellular carcinoma cell lines (HCC) Huh7, Hep3B, Snu449 and Plc has been determined using SRB assay. The Cell cycle progression showed changes in cellular behaviour after 48 and 72 hours in MCF7 and Huh7 cell lines. Abietyl alcohol was obtained from the reduction of abietic acid, a tricyclic diterpene, isolated from oleoresin of Pinus longifolia Roxberghii
Eye Tracking-Based Diagnosis and Early Detection of Autism Spectrum Disorder Using Machine Learning and Deep Learning Techniques
Eye tracking is a useful technique for detecting autism spectrum disorder (ASD). One of the most important aspects of good learning is the ability to have atypical visual attention. The eye-tracking technique provides useful information about children’s visual behaviour for early and accurate diagnosis. It works by scanning the paths of the eyes to extract a sequence of eye projection points on the image to analyse the behaviour of children with autism. In this study, three artificial-intelligence techniques were developed, namely, machine learning, deep learning, and a hybrid technique between them, for early diagnosis of autism. The first technique, neural networks [feedforward neural networks (FFNNs) and artificial neural networks (ANNs)], is based on feature classification extracted by a hybrid method between local binary pattern (LBP) and grey level co-occurrence matrix (GLCM) algorithms. This technique achieved a high accuracy of 99.8% for FFNNs and ANNs. The second technique used a pre-trained convolutional neural network (CNN) model, such as GoogleNet and ResNet-18, on the basis of deep feature map extraction. The GoogleNet and ResNet-18 models achieved high performances of 93.6% and 97.6%, respectively. The third technique used the hybrid method between deep learning (GoogleNet and ResNet-18) and machine learning (SVM), called GoogleNet + SVM and ResNet-18 + SVM. This technique depends on two blocks. The first block used CNN to extract deep feature maps, whilst the second block used SVM to classify the features extracted from the first block. This technique proved its high diagnostic ability, achieving accuracies of 95.5% and 94.5% for GoogleNet + SVM and ResNet-18 + SVM, respectively
Translational invariance of the Einstein-Cartan action in any dimension
We demonstrate that from the first order formulation of the Einstein-Cartan
action it is possible to derive the basic differential identity that leads to
translational invariance of the action in the tangent space. The
transformations of fields is written explicitly for both the first and second
order formulations and the group properties of transformations are studied.
This, combined with the preliminary results from the Hamiltonian formulation
(arXiv:0907.1553 [gr-qc]), allows us to conclude that without any modification,
the Einstein-Cartan action in any dimension higher than two possesses not only
rotational invariance but also a form of \textit{translational invariance in
the tangent space}. We argue that \textit{not} only a complete Hamiltonian
analysis can unambiguously give an answer to the question of what a gauge
symmetry is, but also the pure Lagrangian methods allow us to find the same
gauge symmetry from the \textit{basic} differential identities.Comment: 25 pages, new Section on group properties of transformations is
added, references are added. This version will appear in General Relativity
and Gravitatio
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The effect of WIN55, 212-2 on protein S100, matrix metalloproteinase-2 and nitric oxide expression of chondrocyte monolayer
YesStudies have been conducted to highlight the anti-inflammatory and immunosuppressive properties of
synthetic cannabinoids as well as their potential for cartilage repair. Various wound healing techniques can be
used to investigate the mechanisms of chondrocyte repair in monolayers or three dimensional tissues constructs.
In this work the effect of WIN55, 212-2 (WIN-2) on nitric oxide (NO) and matrix metalloproteinase-2 (MMP-2)
expressed by wounded chondrocyte monolayers was investigated. Moreover, expression of collagen type-I and
type-II, fibronectin and S100 proteins were detected using immunofluorescence and quantitatively verified using
ELISA based techniques following treatment with 1 μM and 2 μM of WIN-2. Treating chondrocytes with 1 μM
of WIN-2 significantly increased expression of collagen type-II, fibronectin and S100, and significantly reduced
collagen type-I expressions as compared to the control groups. On the other hand, both concentrations of WIN-2
significantly reduced the expression of the inflammation markers NO and MMP-2 in a dose dependent manner.
These findings highlight the potential use of the synthetic cannabinoids for improving cartilage healing properties
as well as acting as an anti-inflammatory agent which could be used to enhance tissue engineering protocols
aimed at cartilage repair
Step and Step-Nc as a Tool for Big Data in Cloud Manufacturing
The terms big data, cloud manufacturing, predictive and additive manufacturing, and Internet of Things (IoT) are being most commonly used in the manufacturing industry nowadays. These terms are related to the fourth industrial revolution that emphasizes automation and data exchange between manufacturing tools/elements. Communication occurs between machines, products and even technicians or operators through various technologies while creating records of each interaction resulting in rapid growth of amount of data to be stored. Data acquisition is not a major issue since a structure or framework can properly connect these data in improving manufacturing efficiency. However, lack of effort in collecting and storing manufacturing data in the whole product life cycle process has made integration to be almost difficult to achieve. In this study, the adoption of STEP-NC method/technique was demonstrated in suiting the current explosion of big data in the industrial and manufacturing sector. The proposed methodology was developed through a study of an entity file structure and hierarchical concept in STEP and STEP-NC in gathering manufacturing data in a unified database. The challenge would be in making sense of the data, revealing the patterns in it and using them for operational improvements. The outcome of this study will be useful to support strategic decision making in product manufacturing
Clonal structure of Ceratocystis manginecans populations from mango wilt disease in Oman and Pakistan
Ceratocystis manginecans has recently been described from Oman and Pakistan
where the fungus causes a serious wilt disease of mango. In both countries, the disease has
moved rapidly throughout mango producing areas leading to the mortality of thousands of
mango trees. The disease is associated with the infestation of the wood-boring beetle
Hypocryphalus mangiferae that consistently carries C. manginecans. The aim of this study
was to consider the population structure of C. manginecans isolated from Oman and Pakistan
using microsatellite markers and amplified fragment length polymorphisms (AFLPs).Population genetic analysis of C. manginecans isolates from diseased mango tissue and bark
beetles associated with the disease in Oman and Pakistan, showed no genetic diversity. The
apparently clonal nature of the population suggests strongly that C. manginecans was
introduced into these countries as a single event or from another clonal source.Tree Protection Co-operative Programme (TPCP), National Research Foundation (NRF), South Africa and the Ministry of Agriculture and Fisheries in Sultanate of Oman.http://link.springer.com/journal/13313hb201
A novel 96-microwell-based high-throughput spectrophotometric assay for pharmaceutical quality control of crizotinib, a novel potent drug for the treatment of non-small cell lung cancer
This study describes the development and validation of a novel 96-microwell-based high throughput spectrophotometric assay for pharmaceutical quality control of crizotinib (CZT), a novel drug for the treatment of non-small cell lung cancer. We examined the reaction between CZT and 1,2-naphthoquinone-4-sulphonate, a chromogenic reagent. A red-colored product showing a maximum absorption peak (λmax) at 490 nm was produced in an alkaline medium (pH 9). We examined stoichiometry of the reaction and postulated the reaction mechanism. To our knowledge, this is the first study to describe a color-developing reaction for the proposed assay. The reaction was performed in a 96-microwell plate, and the absorbance of the colored product was measured using an absorbance reader at 490 nm. Under optimized reaction conditions, Beer's law, which shows a correlation between absorbance and CZT concentration, was obeyed in the range of 4-50 µg/well with an appropriate correlation coefficient (0.999). The limits of detection and quantification were 1.73 and 5.23 µg/well, respectively. The assay showed high precision and accuracy. The proposed assay was applied successfully for the determination of CZT in capsules. Thus, the assay proposed in this study is practical and valuable for routine application in pharmaceutical quality control laboratories.</p
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