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Fulltext Model of a critical size defect in the New Zealand white rabbit’s tibia

Che Nor Zarida Che Seman, Zamzuri Zakaria

International Medical Journal Malaysia, 2018;17(1):13-18.
MyJurnal

Critical size defects (CSD) in the long bones of New Zealand White rabbits (Oryctolagus cuniculus) have been used for years as an experimental model for investigation of the effectiveness of a new bone substitute material. There are varieties of protocols available in the literature. This technical note attempts to present an alternative surgical technique of a CSD in the New Zealand white rabbit tibia. Methods: Thirty-nine New Zealand White rabbits were used in this study. A CSD of approximately 4.5 mm (width) X 9.0 mm (length) was surgically drilled at the proximal tibial metaphysis, approximately 1 cm from the knee joint. The surrounding of soft tissue was repositioned and sutured layer by layer with bioabsorbable surgical suture. Two x-rays of anteroposterior and lateral were taken before assessed under computed tomography scan at 6, 12 and 24 weeks. Results: This alternative method created CSD with less bleeding from the muscle observed. No mortality or other surgical complications observed within 6 weeks, 12 weeks and 24 weeks following surgery. Conclusion: A simple and safe method for performing CSD was demonstrated and recommended as an alternative approach for surgery on New Zealand White rabbits.

Matched MeSH terms: Models, Theoretical
Fulltext Multi-stage feature selection (MSFS) algorithm for UWB-based early breast cancer size prediction

Vijayasarveswari V, Andrew AM, Jusoh M, Sabapathy T, Raof RAA, Yasin MNM, et al.

PLoS One, 2020;15(8):e0229367.
PMID: 32790672 DOI: 10.1371/journal.pone.0229367

Breast cancer is the most common cancer among women and it is one of the main causes of death for women worldwide. To attain an optimum medical treatment for breast cancer, an early breast cancer detection is crucial. This paper proposes a multi- stage feature selection method that extracts statistically significant features for breast cancer size detection using proposed data normalization techniques. Ultra-wideband (UWB) signals, controlled using microcontroller are transmitted via an antenna from one end of the breast phantom and are received on the other end. These ultra-wideband analogue signals are represented in both time and frequency domain. The preprocessed digital data is passed to the proposed multi- stage feature selection algorithm. This algorithm has four selection stages. It comprises of data normalization methods, feature extraction, data dimensional reduction and feature fusion. The output data is fused together to form the proposed datasets, namely, 8-HybridFeature, 9-HybridFeature and 10-HybridFeature datasets. The classification performance of these datasets is tested using the Support Vector Machine, Probabilistic Neural Network and Naïve Bayes classifiers for breast cancer size classification. The research findings indicate that the 8-HybridFeature dataset performs better in comparison to the other two datasets. For the 8-HybridFeature dataset, the Naïve Bayes classifier (91.98%) outperformed the Support Vector Machine (90.44%) and Probabilistic Neural Network (80.05%) classifiers in terms of classification accuracy. The finalized method is tested and visualized in the MATLAB based 2D and 3D environment.

Matched MeSH terms: Models, Theoretical
Fulltext Novel Mangosteen-Leaves-Based Marker Ink: Color Lightness, Viscosity, Optimized Composition, and Microstructural Analysis

Mohd Basri MS, Liew Min Ren B, A Talib R, Zakaria R, Kamarudin SH

Polymers (Basel), 2021 May 14;13(10).
PMID: 34069259 DOI: 10.3390/polym13101581

Dry mangosteen leaves are one of the raw materials used to produce marker ink. However, research using this free and abundant resource is rather limited. The less efficient one-factor-at-a-time (OFAT) approach was mostly used in past studies on plant-based marker ink. The use of statistical analysis and the regression coefficient model (mathematical model) was considered essential in predicting the best combination of factors in formulating mangosteen leaf-based marker ink. Ideally, ink should have maximum color lightness, minimum viscosity, and fast-drying speed. The objective of this study to study the effect of glycerol and carboxymethyl cellulose (CMC) on the color lightness and viscosity of mangosteen-leaves-based marker ink. The viscosity, color lightness, and drying properties of the ink were tested, the significant effect of glycerol and CMC (responses) on ink properties was identified and the prediction model on the optimum value of the responses was developed by using response surface methodology (RSM). The microstructure of mangosteen leaves was analyzed to study the surface morphology and cell structure during dye extraction. A low amount of glycerol used was found to increase the value of color lightness. A decrease in CMC amounts resulted in low viscosity of marker ink. The optimum formulation for the ink can be achieved when the weight percents of glycerol, benzalkonium chloride, ferrous sulphate, and CMC are set at 5, 5, 1, and 3, respectively. SEM micrographs showed the greatest amount of cell wall structure collapse on samples boiled with the lowest amount of glycerol.

Matched MeSH terms: Models, Theoretical
Prediction of groundwater flowing well zone at An-Najif Province, central Iraq using evidential belief functions model and GIS

Al-Abadi AM, Pradhan B, Shahid S

Environ Monit Assess, 2015 Oct;188(10):549.
PMID: 27600115 DOI: 10.1007/s10661-016-5564-0

The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater flowing well zones could be used to identify new wells and manage groundwater storage in a sustainable manner.

Matched MeSH terms: Models, Theoretical
Fulltext Compact circularly polarized truncated square ring slot antenna with suppressed higher resonances

Sabran MI, Abdul Rahim SK, Leow CY, Soh PJ, Chew BW, Vandenbosch GA

PLoS One, 2017;12(2):e0172162.
PMID: 28192504 DOI: 10.1371/journal.pone.0172162

This paper presents a compact circularly polarized (CP) antenna with an integrated higher order harmonic rejection filter. The proposed design operates within the ISM band of 2.32 GHz- 2.63 GHz and is suitable for example for wireless power transfer applications. Asymmetrical truncated edges on a square ring create a defected ground structure to excite the CP property, simultaneously realizing compactness. It offers a 50.5% reduced patch area compared to a conventional design. Novel stubs and slot shapes are integrated in the transmission line to reduce higher (up to the third) order harmonics. The proposed prototype yields a -10 dB reflection coefficient (S11) impedance bandwidth of 12.53%, a 3 dB axial ratio bandwidth of 3.27%, and a gain of 5.64 dBi. Measurements also show good agreement with simulations.

Matched MeSH terms: Models, Theoretical
Fulltext A mathematical model of healthy diet menu plan for MARA Junior Science College boarding schools

Nurly Diana Jalil, Maslin Masrom, Wan Normeza Wan Zakaria

Journal of Advanced Research Design, 2017;33(1):8-14.
MyJurnal

Adolescents need more attention on eating habits as they go through a critical path
period of physical, physiological and psychological changes from children to adult.
Therefore, planning a proper healthy diet menu is important to adolescents to have
the sufficient nutrients for proper growth. However, manually plan healthy diet menu
is complicated, inefficient and time-consuming. The purpose of this study is to develop
a mathematical model of healthy diet menu plan that minimizes the daily fat intake
and meets the necessary nutrient intake for adolescents aged 13 between 17 years old
within the budget provided by Majlis Amanah Rakyat (MARA) for Malaysia adolescent
in MARA Junior Science College (MJSC) boarding schools. Optimization approach and
binary integer programming method were used to address the diet problem in this
study. The finding of the study indicates that the developed mathematical model of
healthy diet menu plan for MJSC can generate menu plan that minimizes the total fat
intake at minimum level of requirement per day. This menu plan can be used as a
guideline for the management of the boarding schools to provide healthy diet meals
for their students.

Matched MeSH terms: Models, Theoretical
Osteoblasts infill irregular pores under curvature and porosity controls: a hypothesis-testing analysis of cell behaviours

Alias MA, Buenzli PR

Biomech Model Mechanobiol, 2018 Oct;17(5):1357-1371.
PMID: 29846824 DOI: 10.1007/s10237-018-1031-x

The geometric control of bone tissue growth plays a significant role in bone remodelling, age-related bone loss, and tissue engineering. However, how exactly geometry influences the behaviour of bone-forming cells remains elusive. Geometry modulates cell populations collectively through the evolving space available to the cells, but it may also modulate the individual behaviours of cells. To factor out the collective influence of geometry and gain access to the geometric regulation of individual cell behaviours, we develop a mathematical model of the infilling of cortical bone pores and use it with available experimental data on cortical infilling rates. Testing different possible modes of geometric controls of individual cell behaviours consistent with the experimental data, we find that efficient smoothing of irregular pores only occurs when cell secretory rate is controlled by porosity rather than curvature. This porosity control suggests the convergence of a large scale of intercellular signalling to single bone-forming cells, consistent with that provided by the osteocyte network in response to mechanical stimulus. After validating the mathematical model with the histological record of a real cortical pore infilling, we explore the infilling of a population of randomly generated initial pore shapes. We find that amongst all the geometric regulations considered, the collective influence of curvature on cell crowding is a dominant factor for how fast cortical bone pores infill, and we suggest that the irregularity of cement lines thereby explains some of the variability in double labelling data as well as the overall speed of osteon infilling.

Matched MeSH terms: Models, Theoretical
Molecular structure, second- and third-order nonlinear optical properties and DFT studies of a novel non-centrosymmetric chalcone derivative: (2E)-3-(4-fluorophenyl)-1-(4-{[(1E)-(4-fluorophenyl)methylene]amino}phenyl)prop-2-en-1-one

Maidur SR, Patil PS, Ekbote A, Chia TS, Quah CK

Spectrochim Acta A Mol Biomol Spectrosc, 2017 Sep 05;184:342-354.
PMID: 28528255 DOI: 10.1016/j.saa.2017.05.015

In the present work, the title chalcone, (2E)-3-(4-fluorophenyl)-1-(4-{[(1E)-(4-fluorophenyl) methylene]amino}phenyl)prop-2-en-1-one (abbreviated as FAMFC), was synthesized and structurally characterized by single-crystal X-ray diffraction. The compound is crystallized in the monoclinic system with non-centrosymmetric space group P21 and hence it satisfies the essential condition for materials to exhibit second-order nonlinear optical properties. The molecular structure was further confirmed by using FT-IR and 1H NMR spectroscopic techniques. The title crystal is transparent in the Vis-NIR region and has a direct band gap. The third-order nonlinear optical properties were investigated in solution (0.01M) by Z-scan technique using a continuous wave (CW) DPSS laser at the wavelength of 532nm. The title chalcone exhibited significant two-photon absorption (β=35.8×10-5cmW-1), negative nonlinear refraction (n2=-0.18×10-8cm2W-1) and optical limiting (OL threshold=2.73kJcm-2) under the CW regime. In support of the experimental results, a comprehensive theoretical study was carried out on the molecule of FAMFC using density functional theory (DFT). The optimized geometries and frontier molecular orbitals were calculated by employing B3LYP/6-31+G level of theory. The optimized molecular structure was confirmed computationally by IR vibrational and 1H NMR spectral analysis. The experimental UV-Vis-NIR spectrum was interpreted using computational chemistry under time-dependent DFT. The static and dynamic NLO properties such as dipole moments (μ), polarizability (α), and first hyperpolarizabilities (β) were computed by using finite field method. The obtained dynamic first hyperpolarizability β(-2ω;ω,ω) at input frequency ω=0.04282a.u. is predicted to be 161 times higher than urea standard. The electronic excitation energies and HOMO-LUMO band gap for FAMFC were also evaluated by DFT. The experimental and theoretical results are in good agreement, and the NLO study suggests that FAMFC molecule can be a potential candidate in the nonlinear optical applications.

Matched MeSH terms: Models, Theoretical
Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology

Mogaji KA, Lim HS

Environ Monit Assess, 2017 Jul;189(7):321.
PMID: 28593561 DOI: 10.1007/s10661-017-5990-7

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.

Matched MeSH terms: Models, Theoretical
Fulltext Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks

Hussein AA, Leow CY, Rahman TA

PLoS One, 2017;12(5):e0177326.
PMID: 28493977 DOI: 10.1371/journal.pone.0177326

Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS) is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL) and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL). The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios.

Matched MeSH terms: Models, Theoretical
Fulltext Advances and Future Perspectives in 4D Bioprinting

Ashammakhi N, Ahadian S, Zengjie F, Suthiwanich K, Lorestani F, Orive G, et al.

Biotechnol J, 2018 Dec;13(12):e1800148.
PMID: 30221837 DOI: 10.1002/biot.201800148

Three-dimensionally printed constructs are static and do not recapitulate the dynamic nature of tissues. Four-dimensional (4D) bioprinting has emerged to include conformational changes in printed structures in a predetermined fashion using stimuli-responsive biomaterials and/or cells. The ability to make such dynamic constructs would enable an individual to fabricate tissue structures that can undergo morphological changes. Furthermore, other fields (bioactuation, biorobotics, and biosensing) will benefit from developments in 4D bioprinting. Here, the authors discuss stimuli-responsive biomaterials as potential bioinks for 4D bioprinting. Natural cell forces can also be incorporated into 4D bioprinted structures. The authors introduce mathematical modeling to predict the transition and final state of 4D printed constructs. Different potential applications of 4D bioprinting are also described. Finally, the authors highlight future perspectives for this emerging technology in biomedicine.

Matched MeSH terms: Models, Theoretical
Fulltext Mathematical modelling of molybdenum reduction to Mo-blue by a cyanide-degrading bacterium

Yakasai, H.M., Karamba, K.I., Yasid, N.A., Abd. Rahman, F., Shukor, M.Y., Halmi, M.I.E.

Bioremediation Science and Technology Research, 2016;4(2):1-5.
MyJurnal

Molybdenum, an emerging pollutant, has being demonstrated recently to be toxic to
spermatogenesis in several animal model systems. Metal mines especially gold mine often use
cyanide and hence isolation of metal-reducing and cyanide-degrading bacteria can be useful for
the bioremediation of these pollutants. Preliminary screening shows that three cyanide-degrading
bacteria were able to reduce molybdenum to molybdenum blue (Mo-blue) when grown on a
molybdate low phosphate minimal salts media. Phylogenetic analyses of the 16S rRNA gene of
the best reducer indicates that it belongs to the Serratia genus. A variety of mathematical models
such as logistic, Gompertz, Richards, Schnute, Baranyi-Roberts, von Bertalanffy, Buchanan
three-phase and Huang were used to model molybdenum reduction, and the best model based on
statistical analysis was modified Gompertz with lowest values for RMSE and AICc, highest
adjusted R2 values, with Bias Factor and Accuracy Factor nearest to unity (1.0). The reduction
constants obtained from the model will be used to carry out secondary modelling to study the
effect of various parameters such as substrate, pH and temperature to molybdenum reduction.

Matched MeSH terms: Models, Theoretical
Fulltext The Current and Retrospective Intentional Nature Exposure Scales: Development and Factorial Validity

Wood C, Barron D, Smyth N

Int J Environ Res Public Health, 2019 11 12;16(22).
PMID: 31726784 DOI: 10.3390/ijerph16224443

Both nature exposure and green exercise (GE) can improve health. However, there are no scales examining frequency of engagement; or that consider interaction with nature. There are also no scales assessing these variables during childhood. The aim of this study was to develop a modified (NES-II) and retrospective (RNES-II) version of the Nature Exposure Scale to incorporate GE and to examine their factor structure and reliability. Exploratory factor analysis (EFA) explored the factor structure of the scales; followed by confirmatory factor analysis to confirm the model fit. Fit indices for the one factor five item NES-II and RNES-II models identified by EFA were poor. Use of modification indices resulted in a good model fit; NES-II: χ(5, n = 385) = 2.638; χnormed = 0.879; CFI= 1.000; RMSEA < 0.001 with 90%CI = 0.000-0.082; SRMR = 0.009; AIC = 36.638. RNES-II: χ(2, n = 385) = 7.149; χnormed = 3.574; CFI = 0.995; RMSEA = 0.082 with 90%CI = 0.023-0.151; SRMR = 0.015; AIC = 43.149. Both models demonstrated very good reliability (α = 0.84; 89 respectively). These findings indicate that the scales can be used to assess current and retrospective nature exposure. However, due to the removal of item one, the authors recommend that the scales be named the 'intentional nature exposure scale' and 'retrospective intentional nature exposure scale'.

Matched MeSH terms: Models, Theoretical
Microwave pyrolysis valorization of used baby diaper

Lam SS, Wan Mahari WA, Ma NL, Azwar E, Kwon EE, Peng W, et al.

Chemosphere, 2019 Sep;230:294-302.
PMID: 31108440 DOI: 10.1016/j.chemosphere.2019.05.054

Used baby diaper consists of a combination of decomposable cellulose, non-biodegradable plastic materials (e.g. polyolefins) and super-absorbent polymer materials, thus making it difficult to be sorted and separated for recycling. Microwave pyrolysis was examined for its potential as an approach to transform used baby diapers into value-added products. Influence of the key operating parameters comprising process temperature and microwave power were investigated. The pyrolysis showed a rapid heating process (up to 43 °C/min of heating rate) and quick reaction time (20-40 min) in valorizing the used diapers to generate pyrolysis products comprising up to 43 wt% production of liquid oil, 29 wt% gases and 28 wt% char product. Microwave power and operating temperature were observed to have impacts on the heating rate, process time, production and characteristics of the liquid oil and solid char. The liquid oil contained alkanes, alkenes and esters that can potentially be used as chemical additives, cosmetic products and fuel. The solid char contained high carbon, low nitrogen and free of sulphur, thus showing potential for use as adsorbents and soil additives. These observations demonstrate that microwave pyrolysis has great prospect in transforming used baby diaper into liquid oil and char products that can be utilised in several applications.

Matched MeSH terms: Models, Theoretical
Fulltext Modelling monthly influenza cases in Malaysia

Norrulashikin MA, Yusof F, Hanafiah NHM, Norrulashikin SM

PLoS One, 2021;16(7):e0254137.
PMID: 34288925 DOI: 10.1371/journal.pone.0254137

The increasing trend in the number new cases of influenza every year as reported by WHO is concerning, especially in Malaysia. To date, there is no local research under healthcare sector that implements the time series forecasting methods to predict future disease outbreak in Malaysia, specifically influenza. Addressing the problem could increase awareness of the disease and could help healthcare workers to be more prepared in preventing the widespread of the disease. This paper intends to perform a hybrid ARIMA-SVR approach in forecasting monthly influenza cases in Malaysia. Autoregressive Integrated Moving Average (ARIMA) model (using Box-Jenkins method) and Support Vector Regression (SVR) model were used to capture the linear and nonlinear components in the monthly influenza cases, respectively. It was forecasted that the performance of the hybrid model would improve. The data from World Health Organization (WHO) websites consisting of weekly Influenza Serology A cases in Malaysia from the year 2006 until 2019 have been used for this study. The data were recategorized into monthly data. The findings of the study showed that the monthly influenza cases could be efficiently forecasted using three comparator models as all models outperformed the benchmark model (Naïve model). However, SVR with linear kernel produced the lowest values of RMSE and MAE for the test dataset suggesting the best performance out of the other comparators. This suggested that SVR has the potential to produce more consistent results in forecasting future values when compared with ARIMA and the ARIMA-SVR hybrid model.

Matched MeSH terms: Models, Theoretical
Fulltext Modelling infectious diseases with herd immunity in a randomly mixed population

Law KB, M Peariasamy K, Mohd Ibrahim H, Abdullah NH

Sci Rep, 2021 10 18;11(1):20574.
PMID: 34663839 DOI: 10.1038/s41598-021-00013-2

The conventional susceptible-infectious-recovered (SIR) model tends to magnify the transmission dynamics of infectious diseases, and thus the estimated total infections and immunized population may be higher than the threshold required for infection control and eradication. The study developed a new SIR framework that allows the transmission rate of infectious diseases to decline along with the reduced risk of contact infection to overcome the limitations of the conventional SIR model. Two new SIR models were formulated to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A utilized the declining transmission rate along with the reduced risk of contact infection following infection, while Model B incorporated the declining transmission rate following recovery. Both new models and the conventional SIR model were then used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Further, all three models were used to simulate the transmission dynamics of seasonal influenza in the United States and disease burdens were projected and compared with estimates from the Centers for Disease Control and Prevention. For the simulated infectious disease, in the initial phase of the outbreak, all three models performed expectedly when the sizes of infectious and recovered populations were relatively small. As the infectious population increased, the conventional SIR model appeared to overestimate the infections even when the HIT was achieved in all scenarios with and without vaccination. For the same scenario, Model A appeared to attain the level predicted by the HIT and in comparison, Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. For infectious diseases with high r0, and at low vaccination rates, the level at which the infectious disease was controlled cannot be accurately predicted by the current theorem. Transmission dynamics of infectious diseases with herd immunity can be accurately modelled by allowing the transmission rate of infectious diseases to decline along with the reduction of contact infection risk after recovery or vaccination. Model B provides a credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

Matched MeSH terms: Models, Theoretical
Fulltext Optimal virtual water flows for improved food security in water-scarce countries

Maroufpoor S, Bozorg-Haddad O, Maroufpoor E, Gerbens-Leenes PW, Loáiciga HA, Savic D, et al.

Sci Rep, 2021 10 25;11(1):21027.
PMID: 34697363 DOI: 10.1038/s41598-021-00500-6

The worsening water scarcity has imposed a significant stress on food production in many parts of the world. This stress becomes more critical when countries seek self-sufficiency. A literature review shows that food self-sufficiency has not been assessed as the main factor in determining the optimal cultivation patterns. However, food self-sufficiency is one of the main policies of these countries and requires the most attention and concentration. Previous works have focused on the virtual water trade to meet regional food demand and to calculate trade flows. The potential of the trade network can be exploited to improve the cropping pattern to ensure food and water security. To this end, and based on the research gaps mentioned, this study develops a method to link intra-country trade networks, food security, and total water footprints (WFs) to improve food security. The method is applied in Iran, a water-scarce country. The study shows that 781 × 106 m3 of water could be saved by creating a trade network. Results of the balanced trade network are input to a multi-objective optimization model to improve cropping patterns based on the objectives of achieving food security and preventing water crises. The method provides 400 management scenarios to improve cropping patterns considering 51 main crops in Iran. Results show a range of improvements in food security (19-45%) and a decrease in WFs (2-3%). The selected scenario for Iran would reduce the blue water footprint by 1207 × 106 m3, and reduce the cropland area by 19 × 103 ha. This methodology allows decision makers to develop policies that achieve food security under limited water resources in arid and semi-arid regions.

Matched MeSH terms: Models, Theoretical
Fulltext The link between climate change, food security and fertility: The case of Bangladesh

Chen M, Atiqul Haq SM, Ahmed KJ, Hussain AHMB, Ahmed MNQ

PLoS One, 2021;16(10):e0258196.
PMID: 34673797 DOI: 10.1371/journal.pone.0258196

Climate change is likely to worsen the food security situation through its impact on food production, which may indirectly affect fertility behaviour. This study examines the direct and indirect effects of climate change (e.g., temperature and precipitation) via the production of major crops, as well as their short- and long-term effects on the total fertility rate (TFR) in Bangladesh. We used structural equation modelling (SEM) to perform path analysis and distinguish the direct influence of climate change on fertility and its indirect influence on fertility through food security. We also applied the error correction model (ECM) to analyze the time-series data on temperature and precipitation, crop production and fertility rate of Bangladesh from 1966 to 2015. The results show that maximum temperature has a direct effect and indirect negative effect-via crop production-on TFR, while crop production has a direct positive effect and indirect negative effect-via infant mortality-on TFR. In the short term, TFR responds negatively to the maximum temperature but positively in the long term. The effect of rainfall on TFR is found to be direct, positive, but mainly short-term. Although indicators of economic development play an important part in the fertility decline in Bangladesh, some climate change parameters and crop production are non-negligible factors.

Matched MeSH terms: Models, Theoretical
Simulation of Rainfall-Runoff Response in Ecological Swale with On-Line Subsurface Detention Using Infoworks SD

Ghadim HB, Hin LS

Water Environ Res, 2017 Sep 01;89(9):862-870.
PMID: 28855022 DOI: 10.2175/106143017X14902968254764

The Bio-Ecological Drainage System (BIOECODS) is a sustainable drainage (SUDS) to demonstrate the 'control at source' approaches for urban stormwater management in Malaysia. It is an environmentally friendly drainage system that was designed to increase infiltration, reduce peak flow at outlet, improve water quality, through different BMPs, such as grass swale, retention pond, etc. A special feature of BIOECODS is ecological swale with on-line subsurface detention. This study attempted to create a model of ecological swale with on-line subsurface conveyance system with InfoWorks SD. The new technique has been used Storm Water Management Model (SWMM) model to describe overland flow routing and Soil Conservation Service Method (SCS) used to model infiltration or subsurface flow. The modeling technique has been proven successful, as the predicted and observed closely match each other, with a mean error of 4.58 to 7.32%. The calibrated model then used to determine the ratio of the flow exchange between the surface and subsurface drainage system. Results from the model showed that the runoff ratio exchange between the surface and subsurface is 60 to 90%.

Matched MeSH terms: Models, Theoretical
Automated pterygium detection method of anterior segment photographed images

Wan Zaki WMD, Mat Daud M, Abdani SR, Hussain A, Mutalib HA

Comput Methods Programs Biomed, 2018 Feb;154:71-78.
PMID: 29249348 DOI: 10.1016/j.cmpb.2017.10.026

BACKGROUND AND BJECTIVE: Pterygium is an ocular disease caused by fibrovascular tissue encroachment onto the corneal region. The tissue may cause vision blurring if it grows into the pupil region. In this study, we propose an automatic detection method to differentiate pterygium from non-pterygium (normal) cases on the basis of frontal eye photographed images, also known as anterior segment photographed images.
METHODS: The pterygium screening system was tested on two normal eye databases (UBIRIS and MILES) and two pterygium databases (Australia Pterygium and Brazil Pterygium). This system comprises four modules: (i) a preprocessing module to enhance the pterygium tissue using HSV-Sigmoid; (ii) a segmentation module to differentiate the corneal region and the pterygium tissue; (iii) a feature extraction module to extract corneal features using circularity ratio, Haralick's circularity, eccentricity, and solidity; and (iv) a classification module to identify the presence or absence of pterygium. System performance was evaluated using support vector machine (SVM) and artificial neural network.
RESULTS: The three-step frame differencing technique was introduced in the corneal segmentation module. The output image successfully covered the region of interest with an average accuracy of 0.9127. The performance of the proposed system using SVM provided the most promising results of 88.7%, 88.3%, and 95.6% for sensitivity, specificity, and area under the curve, respectively.
CONCLUSION: A basic platform for computer-aided pterygium screening was successfully developed using the proposed modules. The proposed system can classify pterygium and non-pterygium cases reasonably well. In our future work, a standard grading system will be developed to identify the severity of pterygium cases. This system is expected to increase the awareness of communities in rural areas on pterygium.

Matched MeSH terms: Models, Theoretical

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