Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
Cytochromes P450 (CYPs) play a central role in the Phase I metabolism of drugs and other xenobiotics. It is estimated that CYPs can metabolize up to two-thirds of drugs present in humans. Over the past two decades, there have been numerous advances in in vitro methodologies to characterize drug metabolism and interaction involving CYPs.
This study aimed to develop a three-dimensional finite element model of a functionally graded femoral prosthesis. The model consisted of a femoral prosthesis created from functionally graded materials (FGMs), cement, and femur. The hip prosthesis was composed of FGMs made of titanium alloy, chrome-cobalt, and hydroxyapatite at volume fraction gradient exponents of 0, 1, and 5, respectively. The stress was measured on the femoral prosthesis, cement, and femur. Stress on the neck of the femoral prosthesis was not sensitive to the properties of the constituent material. However, stress on the stem and cement decreased proportionally as the volume fraction gradient exponent of the FGM increased. Meanwhile, stress became uniform on the cement mantle layer. In addition, stress on the femur in the proximal part increased and a high surface area of the femoral part was involved in absorbing the stress. As such, the stress-shielding area decreased. The results obtained in this study are significant in the design and longevity of new prosthetic devices because FGMs offer the potential to achieve stress distribution that more closely resembles that of the natural bone in the femur.
A kinetic model incorporating adsorption, desorption and biodegradation processes was developed to describe the bioregeneration of granular activated carbon (GAC) loaded with 4-chlorophenol (4-CP) and 2,4-dichlorophenol (2,4-DCP), respectively, in simultaneous adsorption and biodegradation processes. The model was numerically solved and the results showed that the kinetic model was well-fitted (R(2)>0.83) to the experimental data at different GAC dosages and at various initial 4-CP and 2,4-DCP concentrations. The rate of bioregeneration in simultaneous adsorption and biodegradation processes was influenced by the ratio of initial chlorophenol concentration to GAC dosage. Enhancement in the rate of bioregeneration was achieved by using the lowest ratio under either one of the following experimental conditions: (1) increasing initial chlorophenol concentration at constant GAC dosage and (2) increasing GAC dosage at constant initial chlorophenol concentration. It was found that the rate enhancement was more pronounced under the second experimental condition.
The effect of the recently developed graphene nanoflakes (GNFs) on the polymerase chain reaction (PCR) has been investigated in this paper. The rationale behind the use of GNFs is their unique physical and thermal properties. Experiments show that GNFs can enhance the thermal conductivity of base fluids and results also revealed that GNFs are a potential enhancer of PCR efficiency; moreover, the PCR enhancements are strongly dependent on GNF concentration. It was found that GNFs yield DNA product equivalent to positive control with up to 65% reduction in the PCR cycles. It was also observed that the PCR yield is dependent on the GNF size, wherein the surface area increases and augments thermal conductivity. Computational fluid dynamics (CFD) simulations were performed to analyze the heat transfer through the PCR tube model in the presence and absence of GNFs. The results suggest that the superior thermal conductivity effect of GNFs may be the main cause of the PCR enhancement.
The wrist is the most complex joint for virtual three-dimensional simulations, and the complexity is even more pronounced when dealing with skeletal disorders of the joint such, as rheumatoid arthritis (RA). In order to analyse the biomechanical difference between healthy and diseased joints, three-dimensional models of these two wrist conditions were developed from computed tomography images. These images consist of eight carpal bones, five metacarpal bones, the distal radius and ulna. The cartilages were developed based on the shape of the available articulations and ligaments were simulated via mechanical links. The RA model was developed accurately by simulating all ten common criteria of the disease related to the wrist. Results from the finite element (FE) analyses showed that the RA model produced three times higher contact pressure at the articulations compared to the healthy model. Normal physiological load transfer also changed from predominantly through the radial side to an increased load transfer approximately 5% towards the ulnar. Based on an extensive literature search, this is the first ever reported work that simulates the pathological conditions of the rheumatoid arthritis of the wrist joint.
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.