A performance evaluation of pruning effects on hybrid neural network

In this paper, we explore the pruning effects on a hybrid mode sequential learning algorithmnamely FuzzyARTMAP-prunable Radial Basis Function (FAM-PRBF) that utilizes FuzzyARTMAP to learn a training dataset and Radial Basis Function Network (RBFN) to performregression and classification. The pruning algorithm is used to optimize the hidden layer ofthe RBFN. The experimental results show that FAM-PRBF has successfully reduced thecomplexity and computation time of the neural network.Keywords: pruning; radial basis function network; fuzzy ARTMAP

Outbreak of acute hepatitis C following the use of anti-hepatitis C virus--screened intravenous immunoglobulin therapy

BACKGROUND and AIMS: Hepatitis C virus (HCV) infection has been associated with intravenous (IV) immunoglobulin (Ig), and plasma donations used to prepare IV Ig are now screened to prevent transmission. Thirty-six patients from the United Kingdom received infusions from a batch of anti-HCV antibody-screened intravenous Ig (Gammagard; Baxter Healthcare Ltd., Thetford, Norfolk, England) that was associated with reports of acute hepatitis C outbreak in Europe. The aim of this study was to document the epidemiology of this outbreak. METHODS: Forty-six patients from the United Kingdom treated with Gammagard (34 exposed and 12 unexposed to the batch) returned epidemiological questionnaires. RESULTS: Eighty-two percent of the exposed patients (28 of 34) became positive for HCV RNA. Eighteen percent of the patients (6 of 34) who had infusions with this batch tested negative for HCV RNA, but 2 of the patients had abnormal liver function and subsequently seroconverted to anti-HCV antibody positive. Twenty-seven percent of the patients (9 of 34) developed jaundice, and 79% (27 of 34) had abnormal liver transferase levels. Virus isolates (n=21), including an isolate from the implicated batch, were genotype 1a and virtually identical by sequence analysis of the NS5 region, consistent with transmission from a single source. CONCLUSIONS: Hepatitis C infection can be transmitted by anti-HCV-screened IV Ig. Careful documentation of IV Ig batch numbers and regular biochemical monitoring is recommended for all IV Ig recipients

Mapping of serotype-specific, immunodominant epitopes in the NS-4 region of hepatitis C virus (HCV):use of type-specific peptides to serologically differentiate infections with HCV types 1, 2, and 3

The effect of sequence variability between different types of hepatitis C virus (HCV) on the antigenicity of the NS-4 protein was investigated by epitope mapping and by enzyme-linked immunosorbent assay with branched oligopeptides. Epitope mapping of the region between amino acid residues 1679 and 1768 in the HCV polyprotein revealed two major antigenic regions (1961 to 1708 and 1710 to 1728) that were recognized by antibody elicited upon natural infection of HCV. The antigenic regions were highly variable between variants of HCV, with only 50 to 60% amino acid sequence similarity between types 1, 2, and 3. Although limited serological cross-reactivity between HCV types was detected between peptides, particularly in the first antigenic region of NS-4, type-specific reactivity formed the principal component of the natural humoral immune response to NS-4. Type-specific antibody to particular HCV types was detected in 89% of the samples from anti-HCV-positive blood donors and correlated almost exactly with genotypic analysis of HCV sequences amplified from the samples by polymerase chain reaction. Whereas almost all blood donors appeared to be infected with a single virus type (97%), a higher proportion of samples (40%) from hemophiliacs infected from transfusion of non-heat-inactivated clotting factor contained antibody to two or even all three HCV types, providing evidence that long-term exposure may lead to multiple infection with different variants of HCV

Effect of Inflow and Infiltration in Sewerage System of Residential Area, Kuantan, Pahang

Inflow and infiltration is a phenomenon in sewerage systems that can have negative effects on the environment and human health if not treated properly. Collaboration has been made between Universiti Malaysia Pahang (UMP) and Indah Water Konsortium Sdn. Bhd. (IWK) where the purpose is to evaluate the amount of inflow and infiltration happening in sewerage systems of residential areas in Kuantan. For this part of the study, one sewer pipeline (MH92a–MH92b) was selected at the residential area of Bandar Putra, having a population equivalent of 1694. The method used in this research was the Flowrate method to tabulate data. ISCO 2150 and 4250 Area Velocity Flowmeters were used to measure flow rate data in the sewer pipeline, whereas ISCO 674 Rain Gauge was used to collect rainfall intensity data. Calibration of all the equipment was done at the Hydrology and Hydraulic Laboratory in UMP. The data was collected for 41 days with each measurement separated by an interval of five minutes. The result shows that the average percentage Infiltration Rate of Qpeak and Qave in this residential catchment were 10.3% and 26.5% which is higher than the value mentioned in Hammer and Hammer (2012). Inflow and infiltration is a real concern, so more study is required to determine whether revision of the infiltration rate recommended in the Malaysian Standard is needed

Characterization of Mn-Doped Vanadium Phosphorus Oxide (VPO) Catalyst: Effect of Ball Milling

The effect of ball milling on the structure and surface reactivity of the Mn-doped vanadium phosphorus oxide (V–P–O) catalyst is discussed. Mn-doped VOHPO4·½H2O precursor was prepared via organic method. The precursor was ball milled in isopropyl alcohol using agate balls for 60 min at 800 rpm. XRD, BET surface area measurements, SEM, O2-TPD, H2-TPR and TPD of NH3 were used to characterize properties of the final catalysts. The results revealed that mechanical treatment of Mn-doped V–P–O catalyst increased surface area as well as reduced particle size of the material. Furthermore, process also increased exposure of (001) crystallographic plane of VOHPO4·½H2O precursor. The secondary structure of the milled material is also lost. The total amount of oxygen desorbed (from O2-TPD) and removed (by H2-TPR) from milled material is higher compared to the unmilled one. The surface acidity of the catalyst was also increased after milling process, as evidenced by lower desorption temperature and higher total amount of the ammonia desorbed

Estimating logged-over lowland rainforest aboveground biomass in Sabah, Malaysia using airborne LiDAR data

Unprecedented deforestation and forest degradation in recent decades have severely depleted the carbon storage in Borneo. Estimating aboveground biomass (AGB) with high accuracy is crucial to quantifying carbon stocks for Reducing Emissions from Deforestation and Forest Degradation-plus implementation (REDD+). Airborne Light Detection and Ranging (LiDAR) is a promising remote sensing technology that provides fine-scale forest structure variability data. This paper highlights the use of airborne LiDAR data for estimating the AGB of a logged-over tropical forest in Sabah, Malaysia. The LiDAR data was acquired using an Optech Orion C200 sensor onboard a fixed wing aircraft. The canopy height of each LiDAR point was calculated from the height difference between the first returns and the Digital Terrain Model (DTM) constructed from the ground points. Among the obtained LiDAR height metrics, the mean canopy height produced the strongest relationship with the observed AGB. This single-variable model had a root mean squared error (RMSE) of 80.02 t ha-1 or 22.31% of the mean AGB, which performed exceptionally when compared with recent tropical rainforest studies. Overall, airborne LiDAR did provide fine-scale canopy height measurements for accurately and reliably estimating the AGB in a logged-over forest in Sabah, thus supporting the state's effort in realizing the REDD+ mechanism

Passive Microwave Remote Sensing for Sea Ice Thickness Retrieval Using Neural Network and Genetic Algorithm

Abstract-Over the years, global warming has gained much attention from the global community. The fact that the sea ice plays an important role and has significant effects towards the global climate has prompted scientists to conduct various researches on the sea ice in the Polar Regions. One of the important parameters being studied is the sea ice thickness as it is a direct key indication towards the climate change. However, to conduct studies on the sea ice scientists are often facing with tough challenges due to the unfavorable harsh weather conditions and the remoteness of the Polar Regions. Thus, microwave remote sensing offers an attractive mean for the observation and monitoring of the changes of sea ice in the Polar Regions for the scientists. In this paper, we will be presenting 2 approaches using passive microwave remote sensing to retrieve sea ice thickness. The first approach involves the training and testing of the neural network (NN) by using data sets generated from the Radiative Transfer Theory with Dense Medium Phase and Amplitude Correction Theory (RT-DMPACT) forward scattering model. Once training is completed, the inversion for sea ice thickness could be done speedily. The second approach utilizes a genetic algorithm (GA) which would perform a search routine to identify possible solutions in sea ice thickness that would match the corresponding brightness temperatures profile of the sea ice. The results obtained from both approaches are presented and tested by using Special Scanning Microwave Imager (SSM/I) data with the aid of the sea ice measurements in the Arctic sea