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Predicting Down syndrome and neural tube defects using basic risk factors

Khattak MT, Supriyanto E, Aman MN, Al-Ashwal RH

Med Biol Eng Comput, 2019 Jul;57(7):1417-1424.
PMID: 30877513 DOI: 10.1007/s11517-019-01969-0

Congenital anomalies are not only one of the main killers for infants but also one of the major causes of deaths under 5. Among congenital anomalies, Down syndrome or trisomy 21 (T-21) and neural tube defects (NTDs) are considered the most common. Expectant mothers in developing countries may not have access to or may not afford the advanced prenatal screening tests. To solve this issue, this paper explores the practicality of using only the basic risk factors for developing prediction models as a tool for initial risk assessment. The prediction models are based on logistic regression. The results show that the prediction models do not have a high balanced classification rate. However, these models can still be used as an effective tool for initial risk assessment for T-21 and NTDs by eliminating at least 50% of the cases with no or low risk. Graphical Abstract Prenatal Risk Assessment of Trisomy-21 and Neural Tube Defects.

Matched MeSH terms: Models, Theoretical*
Fulltext Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm

Al-Saffar A, Awang S, Tao H, Omar N, Al-Saiagh W, Al-Bared M

PLoS One, 2018;13(4):e0194852.
PMID: 29684036 DOI: 10.1371/journal.pone.0194852

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.

Matched MeSH terms: Models, Theoretical
Fulltext Optimized backoff scheme for prioritized data in wireless sensor networks: A class of service approach

Onwuegbuzie IU, Abd Razak S, Fauzi Isnin I, Darwish TSJ, Al-Dhaqm A

PLoS One, 2020;15(8):e0237154.
PMID: 32797055 DOI: 10.1371/journal.pone.0237154

Data prioritization of heterogeneous data in wireless sensor networks gives meaning to mission-critical data that are time-sensitive as this may be a matter of life and death. However, the standard IEEE 802.15.4 does not consider the prioritization of data. Prioritization schemes proffered in the literature have not adequately addressed this issue as proposed schemes either uses a single or complex backoff algorithm to estimate backoff time-slots for prioritized data. Subsequently, the carrier sense multiple access with collision avoidance scheme exhibits an exponentially increasing range of backoff times. These approaches are not only inefficient but result in high latency and increased power consumption. In this article, the concept of class of service (CS) was adopted to prioritize heterogeneous data (real-time and non-real-time), resulting in an optimized prioritized backoff MAC scheme called Class of Service Traffic Priority-based Medium Access Control (CSTP-MAC). This scheme classifies data into high priority data (HPD) and low priority data (LPD) by computing backoff times with expressions peculiar to the data priority class. The improved scheme grants nodes the opportunity to access the shared medium in a timely and power-efficient manner. Benchmarked against contemporary schemes, CSTP-MAC attained a 99% packet delivery ratio with improved power saving capability, which translates to a longer operational lifetime.

Matched MeSH terms: Models, Theoretical
Fulltext Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection

Mujtaba G, Shuib L, Raj RG, Rajandram R, Shaikh K, Al-Garadi MA

PLoS One, 2017;12(2):e0170242.
PMID: 28166263 DOI: 10.1371/journal.pone.0170242

OBJECTIVES: Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models.
METHODS: Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system.
RESULTS: Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines.
CONCLUSION: The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

Matched MeSH terms: Models, Theoretical
Fulltext A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links' weight to increase network stability

Karimi A, Afsharfarnia A, Zarafshan F, Al-Haddad SA

ScientificWorldJournal, 2014;2014:432952.
PMID: 25114965 DOI: 10.1155/2014/432952

The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure.

Matched MeSH terms: Models, Theoretical
Security robot for the prevention of workplace violence using the Non-linear Adaptive Heuristic Mathematical Model

Tao H, Rahman MA, Al-Saffar A, Zhang R, Salih SQ, Zain JM, et al.

Work, 2021;68(3):853-861.
PMID: 33612528 DOI: 10.3233/WOR-203419

BACKGROUND: Nowadays, workplace violence is found to be a mental health hazard and considered a crucial topic. The collaboration between robots and humans is increasing with the growth of Industry 4.0. Therefore, the first problem that must be solved is human-machine security. Ensuring the safety of human beings is one of the main aspects of human-robotic interaction. This is not just about preventing collisions within a shared space among human beings and robots; it includes all possible means of harm for an individual, from physical contact to unpleasant or dangerous psychological effects.
OBJECTIVE: In this paper, Non-linear Adaptive Heuristic Mathematical Model (NAHMM) has been proposed for the prevention of workplace violence using security Human-Robot Collaboration (HRC). Human-Robot Collaboration (HRC) is an area of research with a wide range of up-demands, future scenarios, and potential economic influence. HRC is an interdisciplinary field of research that encompasses cognitive sciences, classical robotics, and psychology.
RESULTS: The robot can thus make the optimal decision between actions that expose its capabilities to the human being and take the best steps given the knowledge that is currently available to the human being. Further, the ideal policy can be measured carefully under certain observability assumptions.
CONCLUSION: The system is shown on a collaborative robot and is compared to a state of the art security system. The device is experimentally demonstrated. The new system is being evaluated qualitatively and quantitatively.

Matched MeSH terms: Models, Theoretical
Fulltext Prediction of flood levels along a stretch of the Langat River with insufficient hydrological data

Thamer Ahmed Mohammed, Abdul Halim Ghazali, Al-Hassoun, Saleh

Pertanika Journal of Science & Technology, 2011;19(2):237-248.
MyJurnal

Malaysia is a tropical country and it is subjected to flooding in both the urban and rural areas. Flood
modelling can help to reduce the impacts of flood hazard by taking extra precautions. HEC-RAS model was used to predict the flood levels at selected reach of the Langat River with a total length of 34.4 km. The Langat River is located in the state of Selangor, Malaysia and it is subjected to regular flooding. The selected reach of the Langat River has insufficient data and a methodology was proposed to overcome this particular problem. Since complete floodplain data for the area are not available, the modelling therefore assumed vertical walls at the left and right banks of the Langat River and all the predicted flood levels above the banks were based on this assumption. The HECRAS model was calibrated and the values of Manning’s coefficients of roughness for the Langat River were found to range from 0.04 to 0.10. The discharge values were calculated for 5, 10, 25, 50, and 100 year return periods and the maximum predicted flood depth ranged from 2.1m to 7.8m. Meanwhile, the model output was verified using the historical record and the error between the recorded and predicted water levels was found to range from 3% to 15%.

Matched MeSH terms: Models, Theoretical
Fulltext Optical frequency upconversion technique for transmission of wireless MIMO-type signals over optical fiber

Shaddad RQ, Mohammad AB, Al-Gailani SA, Al-Hetar AM

ScientificWorldJournal, 2014;2014:170471.
PMID: 24772009 DOI: 10.1155/2014/170471

The optical fiber is well adapted to pass multiple wireless signals having different carrier frequencies by using radio-over-fiber (ROF) technique. However, multiple wireless signals which have the same carrier frequency cannot propagate over a single optical fiber, such as wireless multi-input multi-output (MIMO) signals feeding multiple antennas in the fiber wireless (FiWi) system. A novel optical frequency upconversion (OFU) technique is proposed to solve this problem. In this paper, the novel OFU approach is used to transmit three wireless MIMO signals over a 20 km standard single mode fiber (SMF). The OFU technique exploits one optical source to produce multiple wavelengths by delivering it to a LiNbO3 external optical modulator. The wireless MIMO signals are then modulated by LiNbO3 optical intensity modulators separately using the generated optical carriers from the OFU process. These modulators use the optical single-sideband with carrier (OSSB+C) modulation scheme to optimize the system performance against the fiber dispersion effect. Each wireless MIMO signal is with a 2.4 GHz or 5 GHz carrier frequency, 1 Gb/s data rate, and 16-quadrature amplitude modulation (QAM). The crosstalk between the wireless MIMO signals is highly suppressed, since each wireless MIMO signal is carried on a specific optical wavelength.

Matched MeSH terms: Models, Theoretical
Fulltext Mathematical model for adaptive evolution of populations based on a complex domain

Ibrahim RW, Ahmad MZ, Al-Janaby HF

Saudi J Biol Sci, 2016 Jan;23(1):S45-9.
PMID: 26858564 DOI: 10.1016/j.sjbs.2015.09.012

A mutation is ultimately essential for adaptive evolution in all populations. It arises all the time, but is mostly fixed by enzymes. Further, most do consider that the evolution mechanism is by a natural assortment of variations in organisms in line for random variations in their DNA, and the suggestions for this are overwhelming. The altering of the construction of a gene, causing a different form that may be communicated to succeeding generations, produced by the modification of single base units in DNA, or the deletion, insertion, or rearrangement of larger units of chromosomes or genes. This altering is called a mutation. In this paper, a mathematical model is introduced to this reality. The model describes the time and space for the evolution. The tool is based on a complex domain for the space. We show that the evolution is distributed with the hypergeometric function. The Boundedness of the evolution is imposed by utilizing the Koebe function.

Matched MeSH terms: Models, Theoretical
Fulltext Application of reinforcement learning in cognitive radio networks: models and algorithms

Yau KL, Poh GS, Chien SF, Al-Rawi HA

ScientificWorldJournal, 2014;2014:209810.
PMID: 24995352 DOI: 10.1155/2014/209810

Cognitive radio (CR) enables unlicensed users to exploit the underutilized spectrum in licensed spectrum whilst minimizing interference to licensed users. Reinforcement learning (RL), which is an artificial intelligence approach, has been applied to enable each unlicensed user to observe and carry out optimal actions for performance enhancement in a wide range of schemes in CR, such as dynamic channel selection and channel sensing. This paper presents new discussions of RL in the context of CR networks. It provides an extensive review on how most schemes have been approached using the traditional and enhanced RL algorithms through state, action, and reward representations. Examples of the enhancements on RL, which do not appear in the traditional RL approach, are rules and cooperative learning. This paper also reviews performance enhancements brought about by the RL algorithms and open issues. This paper aims to establish a foundation in order to spark new research interests in this area. Our discussion has been presented in a tutorial manner so that it is comprehensive to readers outside the specialty of RL and CR.

Matched MeSH terms: Models, Theoretical*
Fulltext Determination of important topographic factors for landslide mapping analysis using MLP network

Alkhasawneh MSh, Ngah UK, Tay LT, Mat Isa NA, Al-batah MS

ScientificWorldJournal, 2013;2013:415023.
PMID: 24453846 DOI: 10.1155/2013/415023

Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

Matched MeSH terms: Models, Theoretical*
Predicting the fluorescent enhancement rate by gold and silver nanospheres using finite-difference time-domain analysis

Centeno A, Xie F, Alford N

IET Nanobiotechnol, 2013 Jun;7(2):50-8.
PMID: 24046905

Metal-induced fluorescence enhancement (MIFE) is a promising strategy for increasing the sensitivity of fluorophores used in biological sensors. This study uses the finite-difference time-domain technique to predict the fluorescent enhancement rate of a fluorophore molecule in close proximity to a gold or silver spherical nanoparticle. By considering commercially available fluorescent dyes the computed results are compared with the published experimental data. The results show that MIFE is a complex coupling process between the fluorophore molecule and the metal nanoparticle. Nevertheless using computational electromagnetic techniques to perform calculations it is possible to calculate, with reasonable accuracy, the fluorescent enhancement. Using this methodology it will be possible to consider different shaped metal nanoparticles and any supporting substrate material in the future, an important step in building reliable biosensors capable of detecting low levels of proteins tagged with fluorescence molecules.

Matched MeSH terms: Models, Theoretical*
Fulltext Some numerical methods and comparisons for solving mathematical model of surface decontamination by disinfectant solution

Chai, Jin Sian, Hoe, Yeak Su, Ali H. M. Murid

MATEMATIKA, 2018;34(2):0-0.
MyJurnal

A mathematical model is considered to determine the effectiveness of disin-
fectant solution for surface decontamination. The decontamination process involved the
diffusion of bacteria into disinfectant solution and the reaction of the disinfectant killing
effect. The mathematical model is a reaction-diffusion type. Finite difference method and
method of lines with fourth-order Runge-Kutta method are utilized to solve the model
numerically. To obtain stable solutions, von Neumann stability analysis is employed to
evaluate the stability of finite difference method. For stiff problem, Dormand-Prince
method is applied as the estimated error of fourth-order Runge-Kutta method. MATLAB
programming is selected for the computation of numerical solutions. From the results
obtained, fourth-order Runge-Kutta method has a larger stability region and better ac-
curacy of solutions compared to finite difference method when solving the disinfectant
solution model. Moreover, a numerical simulation is carried out to investigate the effect
of different thickness of disinfectant solution on bacteria reduction. Results show that
thick disinfectant solution is able to reduce the dimensionless bacteria concentration more
effectively.

Matched MeSH terms: Models, Theoretical
Fulltext Nonlinear partial differential equations model related to oxidation pond treatment system: a case study of mpho at taman timor oxidation pond, Johor Bahru

Amir S. A. Hamzah, Ali H. M. Murid

MATEMATIKA, 2018;34(2):293-311.
MyJurnal

This study presents a mathematical model examining wastewater pollutant removal through
an oxidation pond treatment system. This model was developed to describe the reaction
between microbe-based product mPHO (comprising Phototrophic bacteria (PSB)), dissolved
oxygen (DO) and pollutant namely chemical oxygen demand (COD). It consists
of coupled advection-diffusion-reaction equations for the microorganism (PSB), DO and
pollutant (COD) concentrations, respectively. The coupling of these equations occurred
due to the reactions between PSB, DO and COD to produce harmless compounds. Since
the model is nonlinear partial differential equations (PDEs), coupled, and dynamic, computational
algorithm with a specific numerical method, which is implicit Crank-Nicolson
method, was employed to simulate the dynamical behaviour of the system. Furthermore,
numerical results revealed that the proposed model demonstrated high accuracy when
compared to the experimental data.

Matched MeSH terms: Models, Theoretical
Fulltext A novel vehicle stationary detection utilizing map matching and IMU sensors

Amin MS, Reaz MB, Nasir SS, Bhuiyan MA, Ali MA

ScientificWorldJournal, 2014;2014:597180.
PMID: 25276855 DOI: 10.1155/2014/597180

Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

Matched MeSH terms: Models, Theoretical
Fulltext Statistical Optimization for Acid Hydrolysis of Microcrystalline Cellulose and Its Physiochemical Characterization by Using Metal Ion Catalyst

Karim MZ, Chowdhury ZZ, Hamid SBA, Ali ME

Materials (Basel), 2014 Oct 13;7(10):6982-6999.
PMID: 28788226 DOI: 10.3390/ma7106982

Hydrolyzing the amorphous region while keeping the crystalline region unaltered is the key technology for producing nanocellulose. This study investigated if the dissolution properties of the amorphous region of microcrystalline cellulose can be enhanced in the presence of Fe(3+) salt in acidic medium. The process parameters, including temperature, time and the concentration of metal chloride catalyst (FeCl₃), were optimized by using the response surface methodology (RSM). The experimental observation demonstrated that temperature and time play vital roles in hydrolyzing the amorphous sections of cellulose. This would yield hydrocellulose with higher crystallinity. The factors that were varied for the production of hydrocellulose were the temperature (x₁), time (x₂) and FeCl₃ catalyst concentration (x₃). Responses were measured in terms of percentage of crystallinity (y₁) and the yield (y₂) of the prepared hydrocellulose. Relevant mathematical models were developed. Analysis of variance (ANOVA) was carried out to obtain the most significant factors influencing the responses of the percentage of crystallinity and yield. Under optimum conditions, the percentage of crystallinity and yield were 83.46% and 86.98% respectively, at 90.95 °C, 6 h, with a catalyst concentration of 1 M. The physiochemical characteristics of the prepared hydrocellulose were determined in terms of XRD, SEM, TGA and FTIR analyses. The addition of FeCl₃ salt in acid hydrolyzing medium is a novel technique for substantially increasing crystallinity with a significant morphological change.

Matched MeSH terms: Models, Theoretical
Fulltext Metasurface Reflector (MSR) Loading for High Performance Small Microstrip Antenna Design

Ahsan MR, Islam MT, Ullah MH, Singh MJ, Ali MT

PLoS One, 2015;10(5):e0127185.
PMID: 26018795 DOI: 10.1371/journal.pone.0127185

A meander stripline feed multiband microstrip antenna loaded with metasurface reflector (MSR) structure has been designed, analyzed and constructed that offers the wireless communication services for UHF/microwave RFID and WLAN/WiMAX applications. The proposed MSR assimilated antenna comprises planar straight forward design of circular shaped radiator with horizontal slots on it and 2D metasurface formed by the periodic square metallic element that resembles the behavior of metamaterials. A custom made high dielectric bio-plastic substrate (εr = 15) is used for fabricating the prototype of the MSR embedded planar monopole antenna. The details of the design progress through numerical simulations and experimental results are presented and discussed accordingly. The measured impedance bandwidth, radiation patterns and gain of the proposed MSR integrated antenna are compared with the obtained results from numerical simulation, and a good compliance can be observed between them. The investigation shows that utilization of MSR structure has significantly broadened the -10 dB impedance bandwidth than the conventional patch antenna: from 540 to 632 MHz (17%), 467 to 606 MHz (29%) and 758 MHz to 1062 MHz (40%) for three distinct operating bands centered at 0.9, 3.5 and 5.5 GHz. Additionally, due to the assimilation of MSR, the overall realized gains have been upgraded to a higher value of 3.62 dBi, 6.09 dBi and 8.6 dBi for lower, middle and upper frequency band respectively. The measured radiation patterns, impedance bandwidths (S11

Matched MeSH terms: Models, Theoretical
Fulltext Development and validation of a Database Forensic Metamodel (DBFM)

Al-Dhaqm A, Razak S, Othman SH, Ngadi A, Ahmed MN, Ali Mohammed A

PLoS One, 2017;12(2):e0170793.
PMID: 28146585 DOI: 10.1371/journal.pone.0170793

Database Forensics (DBF) is a widespread area of knowledge. It has many complex features and is well known amongst database investigators and practitioners. Several models and frameworks have been created specifically to allow knowledge-sharing and effective DBF activities. However, these are often narrow in focus and address specified database incident types. We have analysed 60 such models in an attempt to uncover how numerous DBF activities are really public even when the actions vary. We then generate a unified abstract view of DBF in the form of a metamodel. We identified, extracted, and proposed a common concept and reconciled concept definitions to propose a metamodel. We have applied a metamodelling process to guarantee that this metamodel is comprehensive and consistent.

Matched MeSH terms: Models, Theoretical*
Modeling population harvesting of rodents for the control of hantavirus infection

Yusof F, Md. Ismai l, Ali N

Sains Malaysiana, 2010;39.

Hantaviruses are infectious agents that can cause diseases resulting in deaths in humans and are hosted by rodents without affecting the hosts themselves. A simple mathematical model describing the spread of the Hantavirus infection in rodents has been proposed and developed by Abramson and Kenkre where the model takes into account the temporal and spatial characteristics of this infection. In this paper, we extended this model to include the process of harvesting and study the impact of different harvesting strategies in the spread of the Hantavirus infection in rodents. Several numerical simulations were carried out and the results are discussed.

Matched MeSH terms: Models, Theoretical
Effect of predators on the spread of hantavirus infection

Yusof F, Md Ismail A.I.B., Ali N

Sains Malaysiana, 2014;43:1045-1051.

Hantavirus is a serious disease caused by rodents which can lead to mortality. Many efforts have been carried out by researchers to develop and analyze mathematical models of Hantavirus infection. In this paper, the Peixoto and Abramson (2006) biodiversity model is modified to include the effect of predators and study the prediction of the modified model. When rodent and predator populations are in competition, the predator populations have the effect of reducing the prevalence of infection. Predators may be used for control and reduces the number of competing species to stabilize the populations at a persistent equilibrium.

Matched MeSH terms: Models, Theoretical

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