An integrative cancer classification based on gene expression data

The advent of integrative approach has shifted cancer classification task from purely data-centric to incorporate prior biological knowledge. Integrative analysis of gene expression data with multiple biological sources is viewed as a promising approach to classify and to reveal relevant cancer-specific biomarker genes. The identification of biomarker genes can be used as a powerful tool for understanding the complex biological mechanisms, and also for diagnosing and treatment of cancer diseases. However, most integrative-based classifiers only incorporate a single type of biological knowledge with gene expression data within the same analysis. For instance, gene expression data is normally integrated with functional ontology, metabolic pathways, or protein-protein interaction networks, where they are then analysed separately and not simultaneously. Apart from that, current methods generates a large number of candidate genes, which still require further experiments and testing to identify the potential biomarker genes. Hence, this study aims to resolve the problems by proposing a systematic integrative framework for cancer gene expression analysis to the classification task. The association based framework is capable to integrate and analyse multiple prior biological sources simultaneously. Set of biomarker genes that are relevant to the cancer diseases of interest are identified in order to improve classification performance and its interpretability. In this paper, the proposed approach is tested on a breast cancer microarray dataset and integrated with protein interaction and metabolic pathway data. The results shows that the classification accuracy improved if both protein and pathways information are integrated into the microarray data analysis

Analysis of temperature and pressure surge distribution for single phase gas flow during wellbore shut-in and start-up

Analysis of temperature and pressure surge distribution for single phase gas flow during wellbore start-up and shut-in is a complex phenomenon for gas producing industries. Its occurrence forced the flowing gas to stop abruptly creating a pressure surge and high temperature within the wellbore system. This situation has to be studied for proper characterization, and protection of the producing wells from damage and premature closure. Many authors studies this phenomena in order to have a permanent solution but yet the problem still remain due to differences in environment. In this work, a one-dimensional transient governing equation based on depth and time dependent for start-up and shut-in has been developed. It is solved by finite difference scheme of Steger Warming Flux Vector Splitting Method (FSM). The method is fully transient and unconditionally stable. Surge pressure were analysed and wellbore temperature is predicted using the unsteady state heat transfer model. The results shows that if shut-in time is short, the sound wave propagation speed is faster than that of its longer time period. The result of this work provides a technical reliance to gas producing industries and can serve as guidance in field operations to avoid gas leakages or wellbore damage

Impact of coarse aggregate on compressive strength of concrete / Jeriscot H. Quayson and Zakari Mustapha.

Over one-third of the volume of concrete is occupied by coarse aggregate and any changes in coarse aggregate type can affect its strength and fracture properties. The paper examined the impact of coarse aggregates on compressive strength of concrete. Slump and compaction factor tests were conducted on the mixture of quartzite and crushed granite course aggregates, and quarry dust (fine aggregate). Nominal mix (1:2:3) was adopted and mix compositions were calculated by absolute weight method. Twelve (12) cubes (150x150mm) of each type of coarse aggregate were cast for 7, 14, 21, and 28 days to determine their compressive strengths. Quartzite was found to have the highest average compressive strength of 24.48N/mm2 with an average density of 2160kg/m3 , while compressive strength of crushed granite was 22.01N/mm2 with an average density of 2300kg/m3 on the 28 day of testing. Concrete made from granite had the highest workability, while concrete made from quartzite aggregate had the highest compressive strength. Densities and compressive strengths of the individual aggregates accounted for the variation in strengths of the concrete, due to differences in properties and strengths. In conclusion, the effect of any type of coarse aggregate on the compressive strength of concrete will be known and also enable contractors to determine the type of aggregate to be selected for a particular work

Alternative Methods of Describing Structure Formation in the Lemaitre-Tolman Model

We describe several new ways of specifying the behaviour of Lemaitre-Tolman (LT) models, in each case presenting the method for obtaining the LT arbitrary functions from the given data, and the conditions for existence of such solutions. In addition to our previously considered `boundary conditions', the new ones include: a simultaneous big bang, a homogeneous density or velocity distribution in the asymptotic future, a simultaneous big crunch, a simultaneous time of maximal expansion, a chosen density or velocity distribution in the asymptotic future, only growing or only decaying fluctuations. Since these conditions are combined in pairs to specify a particular model, this considerably increases the possible ways of designing LT models with desired properties.Comment: Accepted by Phys Rev D. RevTeX 4, 13 pages, no figures. Part of a series: gr-qc/0106096, gr-qc/0303016, gr-qc/0309119. Replacement contains very minor correction

Failure Investigation of a Fill Slope in Putrajaya, Malaysia

On 6th of January 2001, a fill slope collapsed in Putrajaya, Malaysia. The failed slope was 25m in height. The failure caused the slope to pushed two reinforced earth walls and the recently completed jetty and boat docking facilities to collapse. The depth of the failure scar was about 2m with a failure length of about 50m. A failure investigation was then carried out to determine the causes of failure. A total of thirteen new boreholes, fifteen Mackintosh probes and three hand augers were carried out to determine the soil profile. A desk study of existing information and records, site reconnaissance and mapping of the failure area was also carried out to determine the causes and the extent of the failure. Some of the findings of the failure investigation are there were no pile slab found at reinforced earth wall W2 as stated in the drawings and the groundwater table has risen as a result of the filling of the lake, which was carried out after the construction of the fill slope. The groundwater table at failure was found to be much higher than those measured during the site investigation works. Seepages of water were also seen from the failed area

Evaluation of different morphotypes of mango (mangifera indica l.) for use as rootstock in seedlings production

The experiment was designed to assess the growth performance of improved cultivars of Mango grafted on adapted local morphological types. Two trials were conducted in 2005/2006 and 2006/2007 wet season at the teaching and research farm of Faculty of Agriculture, Bayero University, Kano (110 58’N and 80 25’E) situated in Sudan Savanna ecological zone of Nigeria. The experiment consisted of four morphotypes (Binta Siga, Gwaiwar Rago, Dankamaru and Fafaranda) factorially combined with three scions (Alphonso, Peach and Taymour) and laid out in a completely randomized design with three repetitions. The results showed that Binta Siga was identified as the best rootstock in terms of plant establishment probably due to production of higher number of roots, stem diameter, number of leaves, percentage take and general crop vigor. Taymour was observed to be the best scion in terms of compatibility with most of the rootstocks as expressed by its superior performance with regard to the characters mentioned earlier. Binta Siga is therefore recommended for use as rootstock by nursery men in Mango seedlings production for higher profit margin in Kano environmen

Farmers’ Perception of Climate Change in Central Agricultural Zone of Borno State, Nigeria

The study analysed farmer’s perception of climate change in Central Agricultural Zone of Borno State, Nigeria. Data were collected from 160 respondents in the study area. Descriptive and inferential statistics (multiple regression analysis) were used. The result showed that all the variables except sex and marital status were significant at either 1% or 5% level of significance and positively signed. The study concluded that respondents in the study area perceived climate changes which were greatly influenced by their socio economic characteristics. Lack of current knowledge and information on climate, lack of credit facilities and poor extension services on climate change adaptation were identified to be the major constraints of adaptation to climate change in the study area. The study recommended that efforts should be made in improving the knowledge and skills of extension service personnel about climate change and adaptation management strategies and making the extension services more accessible to farmers. Key words: Farmers’ Perception, Climate Change, Agricultural Zone, Borno State

Capacity building in Ocean Bathymetry: The Nippon Foundation GEBCO Training Programme at the University of New Hampshire

A successful Capacity Building project in hydrography is underway at the University of New Hampshire. Organised by the General Bathymetric Chart of the Oceans and sponsored by the Nippon Foundation, the programme trains hydrographers and other marine scientists in bathymetric mapping. Participants are formally prepared to produce bathymetric maps when they return to their home countries through a combination of graduate level courses and workshops, practical field training, participation in deep ocean research cruises, working visits to other laboratories and institutions, focused lectures from visiting experts, and the preparation of a bathymetry map of their area from public domain data. Intangible but necessary preparation includes the networking with professionals in bathymetry and related fields within Ocean Mapping, and the building of a cadre of graduates who will form the basis of international bathymetric mapping in the future

Functional properties of whey protein concentrate texturized at acidic pH: effect of extrusion temperature

Reactive supercritical fluid extrusion (RSCFX) process at acidic condition (pH 3.0) was used to generate texturized whey protein concentrate (TWPC) and the impacts of process temperature on product's physicochemical properties were evaluated. TWPC extruded at 50 and 70 °C formed soft-textured aggregates with high solubility than that extruded at 90 °C that formed protein aggregates with low solubility. Total free sulfhydryl contents and solubility studies in selected buffers indicated that TWPC is primarily stabilized by non-covalent interactions. Proteins texturized at 90 °C showed an increased affinity for 1-anilino-naphthalene-8-sulfonate (ANS) and a decreased affinity for cis-parinaric acid (CPA), indicating changes in protein structure. Water dispersion of TWPC at room temperature showed thickening function with pseudoplastic behavior. Secondary gelation occurred in TWPC obtained at 50 and 70 °C by heating the cold-set gels to 95 °C. TWPC texturized at 90 °C produced cold-set gels with good thermal stability. Compared to control, TWPC formed stable oil-in-water emulsions. Factors such as degree of protein denaturation and the balance of surface hydrophobicity and solubility influenced the heat- and cold-gelation and emulsifying properties of the protein ingredients. TWPC generated by low and high temperature extrusions can thus be utilized for different products requiring targeted physicochemical functionalities

Real-Time Detection of Abandoned Object using Centroid Difference Method

An abandoned object is one that remains stationary for an extended period. Such object might contain explosives and if left on purpose could cause death and injuries to people especially in crowded places. Abandoned objects need to be detected on time to prevent what might endanger people’s lives and health. Various methods have been developed to detect abandoned objects. The most reliable one is the vision-based method which automatically detects the abandoned object using image processing. The efficiency of the method was tested and evaluated on the customized datasets as well as the i-Lids advanced video surveillance system database. The Self -organizing Background Subtraction (SOBS) method overrides other methods in terms of its detection accuracy and simplicity of implementation, but fails for dynamic background scenarios. This work presents a real time vision-based object detection method using the centroid difference to improve on the accuracy of the detection and to tackle challenges of dynamic background of the SOBS method. Matlab Image processing toolbox was used to achieve this goal. The strategy is basically decomposed into two; foreground detection and stationary foreground object (SFO) detection. Gaussian Mixture Model is used for detecting the presence of newly introduced object into a scene (foreground detection), while the blob tracking approach based on frame counting is used to determine whether the detected foreground object is static/ abandoned or not. The results show that the detection accuracy of 83% was obtained which outperform the SOBS method with 67% accuracy. Future research should focus on tracking the person that abandoned the object for onward prosecution