Anaerobic treatment processes to remove organic matter from palm oil mill effluent (POME) have been used widely in Malaysia. Still the amounts of total organic and total mineral released from POME that may cause degradation of the receiving environment need to be verified. This paper proposes the use of the hydrodynamic equations to estimate performance of the cascaded anaerobic ponds (CAP) and to calculate amounts of total organic matter and total mineral released from POME. The CAP efficiencies to remove biochemical oxygen demands, chemical oxygen demands, total solids and volatile solids (VS) as high as 94.5, 93.6, 96.3 and 98.2 %, respectively, are estimated. The amounts of total organic matter and total mineral as high as 538 kg VS/day and 895 kg FS/day, respectively, released from POME to the receiving water are calculated. The implication of the proposed hydrodynamic equations contributes to more versatile environmental assessment techniques, sometimes replacing laboratory analysis.
Many of the similarity-based virtual screening approaches assume that molecular fragments that are not related to the biological activity carry the same weight as the important ones. This was the reason that led to the use of Bayesian networks as an alternative to existing tools for similarity-based virtual screening. In our recent work, the retrieval performance of the Bayesian inference network (BIN) was observed to improve significantly when molecular fragments were reweighted using the relevance feedback information. In this paper, a set of active reference structures were used to reweight the fragments in the reference structure. In this approach, higher weights were assigned to those fragments that occur more frequently in the set of active reference structures while others were penalized. Simulated virtual screening experiments with MDL Drug Data Report datasets showed that the proposed approach significantly improved the retrieval effectiveness of ligand-based virtual screening, especially when the active molecules being sought had a high degree of structural heterogeneity.
A femur phantom made of wax and a real human bone was used to study the dose during radiographical procedures. The depth dose inside the phantom was determined using DOSXYZnrc, a Monte Carlo simulation software. The results were verified with measurements using TLD-100H. It was found that for 2.5 mm aluminium filtered 84-kVp X-rays, the radiation dose in the bone reached 57 % higher than the surface dose, i.e. 3.23 mGy as opposed to 2.06 mGy at the surface. The use of real bone introduces variations in the bone density in the DOSXYZnrc model, resulting in a lower attenuation effect than expected from solid bone tissues.
Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield was carried out using response surface methodology (RSM) and Box-Behnken design of experiment. The individual linear and quadratic effects as well as the interactive effects of temperature, NaOH concentration and time on the degree of disintegration were investigated. The optimum degree of disintegration achieved was 61.45% at 88.50 °C, 2.29 M NaOH (24.23%w/w total solids) and 21 min retention time. Linear and quadratic effects of temperature are most significant in affecting the degree of disintegration. The coefficient of determination (R(2)) of 99.5% confirms that the model used in predicting the degree of disintegration process has a very good fitness with the experimental variables. The disintegrated sludge increased the biogas yield by 36%v/v compared to non-disintegrated sludge. The RSM with Box-Behnken design is an effective tool in predicting the optimum degree of disintegration of sewage sludge for increased biogas yield.
Vertical variation in leaf gas exchange characteristics of trees grown in a lowland dipterocarp forest in Peninsular Malaysia was investigated. Maximum net photosynthetic rate, stomatal conductance, and electron transport rate of leaves at the upper canopy, lower canopy, and forest floor were studied in situ with saturated condition photosynthetic photon flux density. The dark respiration rate of leaves at the various heights was also studied. Relationships among gas exchange characteristics, and also with nitrogen content per unit leaf area and leaf dry matter per area were clearly detected, forming general equations representing the vertical profile of several important parameters related to gas exchange. Numerical analysis revealed that the vertical distribution of gas exchange parameters was well determined showing both larger carbon gain for the whole canopy and at the same time positive carbon gain for the leaves of the lowest layer. For correct estimation of gas exchange at both leaf and canopy scales using multi-layer models, it is essential to consider the vertical distribution of gas exchange parameters with proper scaling coefficients.
Numerical models, able to simulate the response of the human cardiovascular system (CVS) in the presence of an implantable rotary blood pump (IRBP), have been widely used as a predictive tool to investigate the interaction between the CVS and the IRBP under various operating conditions. The present study investigates the effect of alterations in the model parameter values, that is, cardiac contractility, systemic vascular resistance, and total blood volume on the efficiency of rotary pump assistance, using an optimized dynamic heart-pump interaction model previously developed in our laboratory based on animal experimental measurements obtained from five canines. The effect of mean pump speed and the circulatory perturbations on left and right ventricular pressure volume loops, mean aortic pressure, mean cardiac output, pump assistance ratio, and pump flow pulsatility from both the greyhound experiments and model simulations are demonstrated. Furthermore, the applicability of some of the previously proposed control parameters, that is, pulsatility index (PI), gradient of PI with respect to pump speed, pump differential pressure, and aortic pressure are discussed based on our observations from experimental and simulation results. It was found that previously proposed control strategies were not able to perform well under highly varying circulatory conditions. Among these, control algorithms which rely on the left ventricular filling pressure appear to be the most robust as they emulate the Frank-Starling mechanism of the heart.
This paper details a theoretical modeling of Brillouin ring fiber laser which incorporates the interaction between multiple Brillouin Stokes signals. The ring cavity was pumped at several Brillouin pump (BP) powers and the output was measured through an optical coupler with various coupling ratios. The first-order Brillouin Stokes signal was saturated with the presence of the second-order Stokes signal in the cavity as a result of energy transfer between them. The outcome of the study found that the optimum point for the first-order Stokes wave performance is at laser power reduction of 10%. Resultantly, at the optimum output coupling ratio of 90%, the BFL was able to produce 19.2 mW output power at BP power and Brillouin threshold power of 60 and 21.3 mW respectively. The findings also exhibited the feasibility of the theoretical models application to ring-type Brillouin fiber laser of various design parameters.
The relationship between microarchitecture to the failure mechanism and mechanical properties can be assessed through experimental and computational methods. In this study, both methods were utilised using bovine cadavers. Twenty four samples of cancellous bone were extracted from fresh bovine and the samples were cleaned from excessive marrow. Uniaxial compression testing was performed with displacement control. After mechanical testing, each specimen was ashed in a furnace. Four of the samples were exemplarily scanned using micro-computed tomography (μCT) and three dimensional models of the cancellous bones were reconstructed for finite element simulation. The mechanical properties and the failure modes obtained from numerical simulations were then compared to the experiments. Correlations between microarchitectural parameters to the mechanical properties and failure modes were then made. The Young's modulus correlates well with the bone volume fraction with R² = 0.615 and P value 0.013. Three different types of failure modes of cancellous bone were observed: oblique fracture (21.7%), perpendicular global fracture (47.8%), and scattered localised fracture (30.4%). However, no correlations were found between the failure modes to the morphological parameters. The percentage of error between computer predictions and the actual experimental test was from 6 to 12%. These mechanical properties and information on failure modes can be used for the development of synthetic cancellous bone.
Experimental findings indicate that in-situ chondrocytes die readily following impact loading, but remain essentially unaffected at low (non-impact) strain rates. This study was aimed at identifying possible causes for cell death in impact loading by quantifying chondrocyte mechanics when cartilage was subjected to a 5% nominal tissue strain at different strain rates. Multi-scale modelling techniques were used to simulate cartilage tissue and the corresponding chondrocytes residing in the tissue. Chondrocytes were modelled by accounting for the cell membrane, pericellular matrix and pericellular capsule. The results suggest that cell deformations, cell fluid pressures and fluid flow velocity through cells are highest at the highest (impact) strain rate, but they do not reach damaging levels. Tangential strain rates of the cell membrane were highest at the highest strain rate and were observed primarily in superficial tissue cells. Since cell death following impact loading occurs primarily in superficial zone cells, we speculate that cell death in impact loading is caused by the high tangential strain rates in the membrane of superficial zone cells causing membrane rupture and loss of cell content and integrity.
Gene expression data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. In order to select a small subset of informative genes from the data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification. In this proposed method, we introduce particles' speed for giving the rate at which a particle changes its position, and we propose a rule for updating particle's positions. By performing experiments on ten different gene expression datasets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO.
The catalytic cracking of waste cooking palm oil to biofuel was studied over different types of nano-crystalline zeolite catalysts in a fixed bed reactor. The effect of reaction temperature (400-500 °C), catalyst-to-oil ratio (6-14) and catalyst pore size of different nanocrystalline zeolites (0.54-0.80 nm) were studied over the conversion of waste cooking palm oil, yields of Organic Liquid Product (OLP) and gasoline fraction in the OLP following central composite design (CCD). The response surface methodology was used to determine the optimum value of the operating variables for maximum conversion as well as maximum yield of OLP and gasoline fraction, respectively. The optimum reaction temperature of 458 °C with oil/catalyst ratio=6 over the nanocrystalline zeolite Y with pore size of 0.67 nm gave 86.4 wt% oil conversion, 46.5 wt% OLP yield and 33.5 wt% gasoline fraction yield, respectively. The experimental results were in agreement with the simulated values within an experimental error of less than 5%.
In earlier models, synaptic plasticity forms the basis for cellular signaling underlying learning and memory. However, synaptic computation of learning and memory in the brain remains controversial. In this paper, we discuss ways in which synaptic plasticity remodels subcellular networks by deflecting trajectories in neuronal state-space as regulating patterns for the synthesis of dynamic continuity that form cognitive networks of associable representations through endogenous dendritic coding to consolidate memory.
Long-term (21-30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km(2) Baru catchment, slope erosion measurements over 1990-2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994-1996 landslides. Analysis and modelling of 5-15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km(-2) a(-1) 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout (210)Pb and (137)Cs values from a lateral bench core indicate that sedimentation rates in the 721 km(2) Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7-13 times when steep terrain was logged in 1992-1993 and 1999-2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale.
The purpose of this study was to determine the baseline motorcycle riders' perception-response times (PRTs) in an expected object braking task and to determine the significant difference between PRTs of older and younger riders.
The performance of a chemical process plant can gradually degrade due to deterioration of the process equipment and unpermitted deviation of the characteristic variables of the system. Hence, advanced supervision is required for early detection, isolation and correction of abnormal conditions. This work presents the use of an adaptive neuro-fuzzy inference system (ANFIS) for online fault diagnosis of a gas-phase polypropylene production process with emphasis on fast and accurate diagnosis, multiple fault identification and adaptability. The most influential inputs are selected from the raw measured data sets and fed to multiple ANFIS classifiers to identify faults occurring in the process, eliminating the requirement of a detailed process model. Simulation results illustrated that the proposed method effectively diagnosed different fault types and severities, and that it has a better performance compared to a conventional multivariate statistical approach based on principal component analysis (PCA). The proposed method is shown to be simple to apply, robust to measurement noise and able to rapidly discriminate between multiple faults occurring simultaneously. This method is applicable for plant-wide monitoring and can serve as an early warning system to identify process upsets that could threaten the process operation ahead of time.
Homogenous strain analysis (HSA) was developed to evaluate regional cardiac function using tagged cine magnetic resonance images of heart. Current cardiac applications of HSA are however limited in accurately detecting tag intersections within the myocardial wall, producing consistent triangulation of tag cells throughout the image series and achieving optimal spatial resolution due to the large size of the triangles. To address these issues, this article introduces a harmonic phase (HARP) interference method. In principle, as in the standard HARP analysis, the method uses harmonic phases associated with the two of the four fundamental peaks in the spectrum of a tagged image. However, the phase associated with each peak is wrapped when estimated digitally. This article shows that special combination of wrapped phases results in an image with unique intensity pattern that can be exploited to automatically detect tag intersections and to produce reliable triangulation with regularly organized partitioning of the mesh for HSA. In addition, the method offers new opportunities and freedom for evaluating myocardial function when the power and angle of the complex filtered spectra are mathematically modified prior to computing the phase. For example, the triangular elements can be shifted spatially by changing the angle and/or their sizes can be reduced by changing the power. Interference patterns obtained under a variety of power and angle conditions were presented and specific features observed in the results were explained. Together, the advanced processing capabilities increase the power of HSA by making the analysis less prone to errors from human interactions. It also allows strain measurements at higher spatial resolution and multi-scale, thereby improving the display methods for better interpretation of the analysis results.
One of the most important goals in bioinformatics is the ability to predict tertiary structure of a protein from its amino acid sequence. In this paper, new feature groups based on the physical and physicochemical properties of amino acids (size of the amino acids' side chains, predicted secondary structure based on normalized frequency of β-Strands, Turns, and Reverse Turns) are proposed to tackle this task. The proposed features are extracted using a modified feature extraction method adapted from Dubchak et al. To study the effectiveness of the proposed features and the modified feature extraction method, AdaBoost.M1, Multi Layer Perceptron (MLP), and Support Vector Machine (SVM) that have been commonly and successfully applied to the protein folding problem are employed. Our experimental results show that the new feature groups altogether with the modified feature extraction method are capable of enhancing the protein fold prediction accuracy better than the previous works found in the literature.
In this study, palm oil mill effluent (POME) was solubilized by batch thermo-alkaline pre-treatments. A three-factor central composite design (CCD) was applied to identify the optimum COD solubilization condition. The individual and interactive effects of three factors, temperature, NaOH concentration and reaction time, on solubilization of POME were evaluated by employing response surface methodology (RSM). The experimental results showed that temperature, NaOH concentration and reaction time all had an individual significant effect on the solubilization of POME. But these three factors were independent, or there was insignificant interaction on the response. The maximum COD solubilization of 82.63% was estimated under the optimum condition at 32.5 degrees C, 8.83g/L of NaOH and 41.23h reaction time. The confirmation experiment of the predicted optimum conditions verified that the RSM with the central composite design was useful for optimizing the solubilization of POME.
The range-gated imaging systems are reliable underwater imaging system with the capability to minimize backscattering effect from turbid media. The tail-gating technique has been developed to fine tune the signal to backscattering ratio and hence improve the gated image quality. However, the tail-gating technique has limited image quality enhancement in high turbidity levels. In this paper, we developed a numerical model of range-gated underwater imaging system for near target in turbid medium. The simulation results matched the experimental work favorably. Further investigation using this numerical model shows that the multiple scattering components of the backscattering noise dominate for propagation length larger than 4.2 Attenuation Length (AL). This has limited the enhancement of tail-gating technique in high turbidity conditions.