Some of the many tools used for watershed management are mathematical and computer models for wasteload allocations. QUAL2E is one of the most popular water quality models used for such purposes. The question arises as to whether the model is applicable in a different climate such as that in the tropics. In this study, QUAL2E was used to model Sg. Selangor River in Malaysia using the predictive equations for reaeration coefficient (k2) within the model and the measured reaeration coefficients for the river. The study results indicated that use of the reaeration coefficient (k2) measured at Sg. Selangor River did give the lowest standard error (SE) for the simulation of water quality during the 7Q10 low-flow period which is considered as the worst scene scenario in water quality modeling. But during calibration and validation using actual low-flow discharge data, the measured reaeration coefficients did not give the lowest standard error (SE). In conclusion, the results indicated that QUAL2E is applicable in tropical rivers when used with the modeled river parameters (i.e. hydraulic parameters, meteorological conditions etc.). Measured reaeration coefficients produced good results and several predictive equations also produced comparatively good results.
A significant breakthrough and progress have been made in the study of the kinetics of microbial transformation in sewers under aerobic and under changing aerobic/anaerobic conditions. Fundamental knowledge on anoxic kinetics of wastewater is still lacking, so it is not now possible to apply an integrated approach to municipal wastewater treatment incorporating sewer networks as a bio-chemical reactor. This paper presents the results of studies on determining half saturation constants for nitrate, KNO3, and nitrite, KNO2, in raw wastewater. The average values of KNO3 and KNO2, determined from experiments conducted on 7 different wastewater samples were found to be 0.76 gNO3-N/m3 and 0.33 gNO2-N/m3 respectively.
The removal of natural organic matter (NOM) using a continuous flow fixed bed granular activated carbon (GAC) column was studied and the results were then fitted with the Adams-Bohart, Bed-Depth-Service-Time and Clarks models. The GAC, KI-6070 and KI-8085 used in the study had external surface areas of 277 m2/g and 547 m2/g, respectively. Adsorption of NOM by the GAC was complex and involved more than one rate-limiting step. The critical bed depths for KI-6070 and KI-8085 were 0.24 m and 0.3 m, respectively. The Clark model was more effective in simulating the absorbent breakthrough process as compared to the Adams-Bohart model. The lower empty bed contact time (EBCT) i.e. 15 minutes gave a better fit to the Clark Model as compared to EBCT of 20 and 30 minutes.
The sewer is an integral part of the urban wastewater system: the sewer, the wastewater treatment plant and the local receiving waters. The sewer is a reactor for microbial changes of the wastewater during transport, affecting the quality of the wastewater and thereby the successive treatment processes or receiving water impacts during combined sewer overflows. This paper presents the results of studies on anoxic processes, namely denitrification, in the bulk water phase of wastewater as it occurs in sewers. Experiments conducted on 12 different wastewater samples have shown that the denitrification process in the bulk wastewater can be simplified by the reduction of nitrate to nitrogen with significant accumulation of nitrite in the water phase. Utilization of nitrate was observed not to be limited by nitrate for concentrations above 5 gNO3-N/m3. The denitrification rates, under conditions of excess substrate and electron acceptor, were found to be in the range of 0.8-2.0 g NO3-N/(m3h). A discussion on the interaction of the sewer processes and the effects on a downstream located wastewater treatment plant (WWTP) is provided.
There is no report in the English literature on the criteria for neuroablation or neuroaugmentation for the treatment of Parkinson's disease in a developing country like Malaysia. A prospective study of patients with Parkinson's disease from the north-eastern peninsular Malaysia was done to assess their suitability of surgery. Age, race, duration of illness and dementia were considered important factors towards the success of such surgical procedures. A mathematical model is suggested for future cases deemed to be suitable for neuroaugmentative or ablative surgery.
This paper investigates the use of a neural-network-based intelligent learning system for the prediction of drug release profiles. An experimental study in transdermal iontophoresis (TI) is employed to evaluate the applicability of a particular neural network (NN) model, i.e. the Gaussian mixture model (GMM), in modeling and predicting drug release profiles. A number of tests are systematically designed using the face-centered central composite design (CCD) approach to examine the effects of various process variables simultaneously during the iontophoresis process. The GMM is then applied to model and predict the drug release profiles based on the data samples collected from the experiments. The GMM results are compared with those from multiple regression models. In addition, the bootstrap method is used to assess the reliability of the network predictions by estimating confidence intervals associated with the results. The results demonstrate that the combination of the face-centered CCD and GMM can be employed as a useful intelligent tool for the prediction of time-series profiles in pharmaceutical and biomedical experiments.
A modeling procedure that predicts trihalomethane (THM) formation from field sampling at the treatment plant and along its distribution system using Tampin district, Negeri Sembilan and Sabak Bernam district, Selangor as sources of data were studied and developed. Using Pearson method of correlation, the organic matter measured as TOC showed a positive correlation with formation of THM (r=0.380,P=0.0001 for Tampin and r=0.478,P=0.0001 for Sabak Bernam). Similar positive correlation was also obtained for pH in both districts with Tampin (r=0.362,P=0.0010) and Sabak Bernam (r=0.215,P=0.0010). Chlorine dosage was also found to have low correlation with formation of THM for the two districts with Tampin (r=0.233,P=0.0230) and Sabak Bernam (r=0.505,P=0.0001). Distance from treatment plant was found to have correlation with formation of THM for Tampin district with r=0.353 and P=0.0010. Other parameters such as turbidity, ammonia, temperature and residue chlorine were found to have no correlation with formation of THM. Linear and non-linear models were developed for these two districts. The results obtained were validated using three different sets of field data obtained from own source and district of Seremban (Pantai and Sg. Terip), Negeri Sembilan. Validation results indicated that there was significant difference in the predictive and determined values of THM when two sets of data from districts of Seremban were used with an exception of field data of Sg. Terip for non-linear model developed for district of Tampin. It was found that a non-linear model is slightly better than linear model in terms of percentage prediction errors. The models developed were site specific and the predictive capabilities in the distribution systems vary with different environmental conditions.
As with all membrane processes, turbulence, as promoted by aeration in submerged membrane bioreactors (MBRs) or pumping in sidestream (SS) systems to produce somewhat higher effective cross-flow velocities, increases mass transfer and reduces fouling. This is manifested in an elevated critical flux, the flux at which the membrane permeability is sustained. However, the non-Newtonian nature of the sludge makes precise rheological characterisation difficult. In this study, a calculation of the appropriate hydrodynamics parameters for a SS MBR configuration is presented. Optimisation of the aeration in a submerged MBR system has been attained by defining the minimum air velocity required for Taylor bubble formation.
The objective of this study was to assess the feasibility of the Sequencing Batch Reactor (SBR) system for implementation in Malaysia. Theoretical, field, laboratory investigations, and modelling simulations have been carried out. The results of the study indicated that the SBR system was robust, relatively cost-effective, and efficient under Malaysian conditions. However, the SBR system requires highly skilled operators and continuous monitoring. This paper also attempted to identify operating conditions for the SBR system, which optimise both the removal efficiencies and the removal rates. The removal efficiencies could reach 90-96% for COD, up to 92% for TN, and 95% for SS. An approach to estimate a full operational cycle time, to estimate the de-sludging rate, and to control the biomass in the sludge has also been developed. About 4 hours react time was obtained, as 2.25 hours of nitrification with aerated slow fill and 1.75 hour of denitrification with HAc addition as an additional carbon source. Inefficient settling was one of the problems that affect the SBR effluent quality. The settling time was one hour for achieving Standard B (effluent quality) and 2 hours for Standard A.
A statistical prediction of terrestrial gamma radiation dose rate has been performed, covering the Kota Tinggi district of Peninsular Malaysia. The prediction has been based on geological features and soil types. The purpose of this study is to provide a methodology to statistically predict the gamma radiation dose rate with minimum surveying in an area. Results of statistical predictions using the hypothesis test were compared with the actual dose rate obtained by measurements.
The main physical properties of ferroelectric crystals are described, and the macroscopic and microscopic viewpoints are discussed along with some applications, such as in capacitors and nonlinear optics. The emphasis is on physical understanding, while the mathematical level is kept to a minimum or supplemented by graphical representations to make the article more accessible.
Dispersal-assembly theories of species coexistence posit that environmental factors play no role in explaining community diversity and structure. Dispersal-assembly theories shed light on some aspects of community structure such as species-area and species-abundance relationships. However, species' environmental associations also affect these measures of community structure. Measurements of species' niche breadth and overlap address this influence. Using a new continuous measure of niche and a dispersal-assembly null model that maintains species' niche breadth and aggregation, we tested two hypotheses assessing the effects of habitat heterogeneity on the ability of dispersal-assembly theories to explain community niche structure. We found that in both homogenous and heterogeneous environments dispersal-assembly theories cannot fully explain observed niche structure. The performance of the dispersal-assembly null models was particularly poor in heterogeneous environments. These results indicate that non-dispersal based mechanisms are in part responsible for observed community structure and measures of community structure which include species' environmental associations should be used to test theories of species diversity.
Forest growth models are useful tools for investigating the long-term impacts of logging. In this paper, the results of the rain forest growth model FORMIND were assessed by a multicriteria decision analysis. The main processes covered by FORMIND include tree growth, mortality, regeneration and competition. Tree growth is calculated based on a carbon balance approach. Trees compete for light and space; dying large trees fall down and create gaps in the forest. Sixty-four different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated. The scenarios differ regarding the logging cycle, logging method, cutting limit and logging intensity. We characterise the impacts with four criteria describing the yield, canopy opening and changes in species composition. Multicriteria decision analysis was used for the first time to evaluate the scenarios and identify the efficient ones. Our results plainly show that reduced-impact logging scenarios are more 'efficient' than the others, since in these scenarios forest damage is minimised without significantly reducing yield. Nevertheless, there is a trade-off between yield and achieving a desired ecological state of logged forest; the ecological state of the logged forests can only be improved by reducing yields and enlarging the logging cycles. Our study also demonstrates that high cutting limits or low logging intensities cannot compensate for the high level of damage caused by conventional logging techniques.
Although the kinetic behaviour of tramadol has been described, the present study is the first to our knowledge, to report specifically on the population pharmacokinetic modelling of tramadol hydrochloride.
Researchers can adopt one of many different measures of central tendency to examine the effect of a treatment variable across groups. These include least squares means, trimmed means, M-estimators and medians. In addition, some methods begin with a preliminary test to determine the shapes of distributions before adopting a particular estimator of the typical score. We compared a number of recently developed adaptive robust methods with respect to their ability to control Type I error and their sensitivity to detect differences between the groups when data were non-normal and heterogeneous, and the design was unbalanced. In particular, two new approaches to comparing the typical score across treatment groups, due to Babu, Padmanabhan, and Puri, were compared to two new methods presented by Wilcox and by Keselman, Wilcox, Othman, and Fradette. The procedures examined generally resulted in good Type I error control and therefore, on the basis of this critetion, it would be difficult to recommend one method over the other. However, the power results clearly favour one of the methods presented by Wilcox and Keselman; indeed, in the vast majority of the cases investigated, this most favoured approach had substantially larger power values than the other procedures, particularly when there were more than two treatment groups.
Formulation of effective sustainability indicators for national assessment demands a comprehensive understanding of the utilisation, diffusion and dissemination of information in policy processes. To illustrate the dynamic of sustainability assessment within the context of policy processes, this paper uses a case study of national sustainability indicators development in Malaysia. Subsequently, this paper ascribes the limited achievement of national sustainability assessment in Malaysia to four types of constraints: meta-policy issues; technical capacities; communication concerns; and the inherent knowledge gaps within the indicator developer community vis-a-vis their theoretical limitations. It is proposed that such constraints will be encountered in many countries. Drawing from the literature on public policy, this paper outlines a framework for investigating indicator behaviour within policy processes based on well-established concepts such as knowledge utilisation and policy learning. I conclude this paper by elaborating on the corresponding future challenges that must be addressed before effective integration of sustainability indicators within policy systems can occur.
RADARSAT data have a potential role for coastal pollution monitoring. This study presents a new approach to detect and forecast oil slick trajectory movements. The oil slick trajectory movements is based on the tidal current effects and Fay's algorithm for oil slick spreading mechanisms. The oil spill trajectory model contains the integration between Doppler frequency shift model and Lagrangian model. Doppler frequency shift model implemented to simulate tidal current pattern from RADARSAT data while the Lagrangian model used to predict oil spill spreading pattern. The classical Fay's algorithm was implemented with the two models to simulate the oil spill trajectory movements. The study shows that the slick lengths are effected by tidal current V component with maximum velocity of 1.4 m/s. This indicates that oil slick trajectory path is moved towards the north direction. The oil slick parcels are accumulated along the coastline after 48 h. The analysis indicated that tidal current V components were the dominant forcing for oil slick spreading.
This article uses metric and nonmetric dental data to test the "two-layer" or immigration hypothesis whereby Southeast Asia was initially occupied by an "Australo-Melanesian" population that later underwent substantial genetic admixture with East Asian immigrants associated with the spread of agriculture from the Neolithic period onwards. We examined teeth from 4,002 individuals comprising 42 prehistoric and historic samples from East Asia, Southeast Asia, Australia, and Melanesia. For the odontometric analysis, dental size proportions were compared using factor analysis and Q-mode correlation coefficients, and overall tooth size was also compared between population samples. Nonmetric population affinities were estimated by Smith's distances, using the frequencies of 16 tooth traits. The results of both the metric and nonmetric analyses demonstrate close affinities between recent Australo-Melanesian samples and samples representing early Southeast Asia, such as the Early to Middle Holocene series from Vietnam, Malaysia, and Flores. In contrast, the dental characteristics of most modern Southeast Asians exhibit a mixture of traits associated with East Asians and Australo-Melanesians, suggesting that these populations were genetically influenced by immigrants from East Asia. East Asian metric and/or nonmetric traits are also found in some prehistoric samples from Southeast Asia such as Ban Kao (Thailand), implying that immigration probably began in the early Neolithic. Much clearer influence of East Asian immigration was found in Early Metal Age Vietnamese and Sulawesi samples. Although the results of this study are consistent with the immigration hypothesis, analysis of additional Neolithic samples is needed to determine the exact timing of population dispersals into Southeast Asia.
Increased oxidative stress and mitochondrial dysfunction have been identified as common pathophysiological phenomena associated with neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD). As the age-related decline in the production of melatonin may contribute to increased levels of oxidative stress in the elderly, the role of this neuroprotective agent is attracting increasing attention. Melatonin has multiple actions as a regulator of antioxidant and prooxidant enzymes, radical scavenger and antagonist of mitochondrial radical formation. The ability of melatonin and its kynuramine metabolites to interact directly with the electron transport chain by increasing the electron flow and reducing electron leakage are unique features by which melatonin is able to increase the survival of neurons under enhanced oxidative stress. Moreover, antifibrillogenic actions have been demonstrated in vitro, also in the presence of profibrillogenic apoE4 or apoE3, and in vivo, in a transgenic mouse model. Amyloid-beta toxicity is antagonized by melatonin and one of its kynuramine metabolites. Cytoskeletal disorganization and protein hyperphosphorylation, as induced in several cell-line models, have been attenuated by melatonin, effects comprising stress kinase downregulation and extending to neurotrophin expression. Various experimental models of AD, PD and HD indicate the usefulness of melatonin in antagonizing disease progression and/or mitigating some of the symptoms. Melatonin secretion has been found to be altered in AD and PD. Attempts to compensate for age- and disease-dependent melatonin deficiency have shown that administration of this compound can improve sleep efficiency in AD and PD and, to some extent, cognitive function in AD patients. Exogenous melatonin has also been reported to alleviate behavioral symptoms such as sundowning. Taken together, these findings suggest that melatonin, its analogues and kynuric metabolites may have potential value in prevention and treatment of AD and other neurodegenerative disorders.