The response of trilayer graphene nanoribbon (TGN)-based ion-sensitive field-effect transistor (ISFET) to different pH solutions and adsorption effect on the sensing parameters are analytically studied in this research. The authors propose a TGN-based sensor to electrochemically detect pH. To this end, absorption effect on the sensing area in the form of carrier concentration, carrier velocity, and conductance variations are investigated. Also, the caused electrical response on TGN as a detection element is analytically proposed, in which significant current decrease of the sensor is observed after exposure to high pH values. In order to verify the accuracy of the model, it is compared with recent reports on pH sensors. The TGN-based pH sensor exposes higher current compared to that of carbon nanotube (CNT) counterpart for analogous ambient conditions. While, the comparative results demonstrate that the conductance of proposed model is lower than that of monolayer graphene-counterpart for equivalent pH values. The results confirm that the conductance of the sensor is decreased and Vg-min is obviously right-shifted by increasing value of pH. The authors demonstrate that although there is not the experimental evidence reported in the part of literature for TGN sensor, but the model can assist in comprehending experiments involving nanoscale pH sensors.
Tropical forest ecosystems are facing unprecedented levels of degradation, severely compromising habitat suitability for wildlife. Despite the fundamental role biodiversity plays in forest regeneration, identifying and prioritizing degraded forests for restoration or conservation, based on their wildlife value, remains a significant challenge. Efforts to characterize habitat selection are also weakened by simple classifications of human-modified tropical forests as intact vs. degraded, which ignore the influence that three-dimensional (3D) forest structure may have on species distributions. Here, we develop a framework to identify conservation and restoration opportunities across logged forests in Borneo. We couple high-resolution airborne light detection and ranging (LiDAR) and camera trap data to characterize the response of a tropical mammal community to changes in 3D forest structure across a degradation gradient. Mammals were most responsive to covariates that accounted explicitly for the vertical and horizontal characteristics of the forest and actively selected structurally complex environments comprising tall canopies, increased plant area index throughout the vertical column, and the availability of a greater diversity of niches. We show that mammals are sensitive to structural simplification through disturbance, emphasizing the importance of maintaining and enhancing structurally intact forests. By calculating occurrence thresholds of species in response to forest structural change, we identify areas of degraded forest that would provide maximum benefit for multiple high-conservation value species if restored. The study demonstrates the advantages of using LiDAR to map forest structure, rather than relying on overly simplistic classifications of human-modified tropical forests, for prioritizing regions for restoration.
Cardiovascular disease (CVD) is the major cause of death globally. More people die of CVDs each year than from any other disease. Over 80% of CVD deaths occur in low and middle income countries and occur almost equally in male and female. In this paper, different computational models based on Bayesian Networks, Multilayer Perceptron,Radial Basis Function and Logistic Regression methods are presented to predict early risk detection of the cardiovascular event. A total of 929 (626 male and 303 female) heart attack data are used to construct the models.The models are tested using combined as well as separate male and female data. Among the models used, it is found that the Multilayer Perceptron model yields the best accuracy result.
"Wide income differentials, the threat of increased illegal immigration from developing countries, and sub-replacement fertility in the developed countries are some reasons for the recent reassessment of the relationship between migration and development.... The model presented in this article proposes different roles for permanent immigrants, contract workers, professional transients, illegal migrants and others according to the stages of modernization of the sending and receiving countries. The model was found consistent with the experiences of Mauritius, Seychelles, Singapore and, to a lesser extent, Malaysia."
PIP: A model of the determinants of child quality and of the value of a woman's time is developed and tested using data from the Malaysian Family Life Survey of 1976-1977. Child quality is measured by educational attainment; factors influencing the value of the mother's time include size and age composition of household, family income, education, and hours worked. The results indicate that size and age composition of household affect a woman's asking wage. However, more data are needed before the effects of family structure on schooling can be measured with confidence.
"The past 20 years have seen extensive elaboration, refinement, and application of the original Brass method for estimating infant and child mortality from child survivorship data. This experience has confirmed the overall usefulness of the methods beyond question, but it has also shown that...estimates must be analyzed in relation to other relevant information before useful conclusions about the level and trend of mortality can be drawn.... This article aims to illustrate the importance of data analysis through a series of examples, including data for the Eastern Malaysian state of Sarawak, Mexico, Thailand, and Indonesia. Specific maneuvers include plotting completed parity distributions and 'time-plotting' mean numbers of children ever born from successive censuses. A substantive conclusion of general interest is that data for older women are not so widely defective as generally supposed."
Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) - dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients' quality of life. Integrating PK/PD-EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.
The air pollution index (API) is an important figure used for measuring the quality of air in the environment. The API is determined based on the highest average value of individual indices for all the variables which include sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and suspended particulate matter (PM10) at a particular hour. API values that exceed the limit of 100 units indicate an unhealthy status for the exposed environment. This study investigates the risk of occurrences of API values greater than 100 units for eight urban areas in Peninsular Malaysia for the period of January 2004 to December 2014. An extreme value model, known as the generalized Pareto distribution (GPD), has been fitted to the API values found. Based on the fitted model, return period for describing the occurrences of API exceeding 100 in the different cities has been computed as the indicator of risk. The results obtained indicated that most of the urban areas considered have a very small risk of occurrence of the unhealthy events, except for Kuala Lumpur, Malacca, and Klang. However, among these three cities, it is found that Klang has the highest risk. Based on all the results obtained, the air quality standard in urban areas of Peninsular Malaysia falls within healthy limits to human beings.
The effect of different aeration rates on the organic matter (OM) degradation during the active phase of oil palm empty fruit bunch (EFB)-rabbit manure co-composting process under constant forced-aeration system has been studied. Four different aeration rates, 0.13 L min(-1) kg(DM)(-1),0.26 L min(-1) kg(DM)(-1),0.49 L min(-1) kg(DM)(-1) and 0.74 L min(-1) kg(DM)(-1) were applied. 0.26 L min(-1) kg(DM)(-1) provided enough oxygen level (10%) for the rest of composting period, showing 40.5% of OM reduction that is better than other aeration rates. A dynamic mathematical model describing OM degradation, based on the ratio between OM content and initial OM content with correction functions of moisture content, free air space, oxygen and temperature has been proposed.
Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.
The relationship between fertility and mobility is examined with reference to Zelinsky's [1971] mobility transition hypothesis. Five Asian countries (Japan, South Korea, Thailand, Malaysia, China) at different stages of development and mobility transition are compared with respect to shifting sectoral patterns of migration and changing levels of fertility. National trends suggest that the development sequence proposed by Zelinsky on the basis of the European experience does not generally apply to Asia. In four out of five cases examined, fertility declined before substantial urbanization took place. Zelinsky's sequence of mobility change should be modified to fit the experience of developing countries, but the importance of the interrelations hip between fertility decline and mobility change remains
PIP: Malaysian infant mortality differentials are a worthwhile subject for study, because socioeconomic development has very clearly had a differential impact by ethnic group. The Chinese rates of infant mortality are significantly lower than the Malay or Indian rates. Instead of examining the obvious access to care issues, this study considered factors related to the culture of infant care. Practices include the Chinese confinement of the mother in the first month after childbirth ("pe'i yue") and Pillsbury's 12 normative rules for Malaysian Chinese care. Malay practices vary widely by region and history. Indian mothers are restricted by diet. Data-recording flaws do not permit analysis of Sarawak or Sabah. The general assumption that Western medicine favors better health for mothers and infants is substantiated among peninsular communities, however, there are also negative impacts which affect infant mortality. The complex interaction of factors impacting on infant mortality reported in seven previous studies is discussed. A review of these studies reveals that immediate causes are infections, injuries, and dehydration. Indirect causes are birth weight or social and behavioral factors such as household income or maternal education. Indirect factors, which are amenable to planned change and influence the biological proximate determinants of infant mortality, are identified as birth weight, maternal age at birth, short pregnancy intervals or prior reproductive loss, sex of the child, birth order, duration of breast feeding and conditions of supplementation, types of household water and sanitation, year of child's birth, maternal education, household income and composition, institution of birth, ethnicity, and rural residence. Nine factors are identified empirically as not significant: maternal hours of work in the child's first year, maternal occupation, distance from home to workplace, presence of other children or servants, incidence of epidemics in the child's first year of life, community types of sanitation, prices and availability of infant foods, and access to various types of medical care. Future empirical study should consider factors such as class differences, place of residence, or extent of illiteracy as underlying or related to ethnicity. Policy-makers should be aware that future decline in infant mortality rates may depend on the blending of traditional with modern practices.
This study examines the possibility that estimation of the effect of breast-feeding on infant survival is affected by selection bias, in that children who are healthier at birth may be more likely to be breast-fed. Data are from the 1976 Malaysian Family Life Survey. "Ordinary logit models for breast-feeding and survival are estimated, and the results suggest that selection is indeed present. For example, children of higher birth weight appear to be more likely to be breast-fed and likely to survive. In addition, weight at birth and the duration of breast-feeding appear to be linked." Using birth weight as an indicator for the child's health, the authors conclude that "the direct influence of breast-feeding on survival remains of overwhelming importance even after corrections for selection bias are made."
Guillain-Barré syndrome (GBS) is an acute immune-mediated neuropathy that has variable disease course and outcome. The Erasmus GBS outcome score (EGOS), modified EGOS (mEGOS), and Erasmus GBS respiratory insufficiency score (EGRIS) are prognostic models designed to predict the functional outcome of GBS patients at 6 months (EGOS and mEGOS) and the need for mechanical ventilation within a week of admission (EGRIS). The models were primarily developed in the Dutch GBS population, and thus the usefulness of these models in other GBS cohorts is less clear. In the current study, we aimed to validate mEGOS, EGOS, and EGRIS in Malaysian GBS patients. A total of 107 patients with GBS and its variants were consecutively recruited. Patients with GBS and Miller Fisher syndrome (MFS) were analysed separately. In the GBS cohort, high mEGOS and EGOS scores were significantly correlated with poor outcome at 6 months (mEGOS on admission: r = .381, P = .005; mEGOS at day 7 of admission: r = .507, P
The ability of speech synthesis system to synthesize emotional speech enhances the user's experience when using this kind of system and its related applications. However, the development of an emotional speech synthesis system is a daunting task in view of the complexity of human emotional speech. The more recent state-of-the-art speech synthesis systems, such as the one based on hidden Markov models, can synthesize emotional speech with acceptable naturalness with the use of a good emotional speech acoustic model. However, building an emotional speech acoustic model requires adequate resources including segment-phonetic labels of emotional speech, which is a problem for many under-resourced languages, including Malay. This research shows how it is possible to build an emotional speech acoustic model for Malay with minimal resources. To achieve this objective, two forms of initialization methods were considered: iterative training using the deterministic annealing expectation maximization algorithm and the isolated unit training. The seed model for the automatic segmentation is a neutral speech acoustic model, which was transformed to target emotion using two transformation techniques: model adaptation and context-dependent boundary refinement. Two forms of evaluation have been performed: an objective evaluation measuring the prosody error and a listening evaluation to measure the naturalness of the synthesized emotional speech.
The current study is proposing a design envelope for porous Ti-6Al-4V alloy femoral stems to survive under fatigue loads. Numerical computational analysis of these stems with a body-centered-cube (BCC) structure is conducted in ABAQUS. Femoral stems without shell and with various outer dense shell thicknesses (0.5, 1.0, 1.5, and 2 mm) and inner cores (porosities of 90, 77, 63, 47, 30, and 18%) are analyzed. A design space (envelope) is derived by using stem stiffnesses close to that of the femur bone, maximum fatigue stresses of 0.3σys in the porous part, and endurance limits of the dense part of the stems. The Soderberg approach is successfully employed to compute the factor of safety Nf > 1.1. Fully porous stems without dense shells are concluded to fail under fatigue load. It is thus safe to use the porous stems with a shell thickness of 1.5 and 2 mm for all porosities (18-90%), 1 mm shell with 18 and 30% porosities, and 0.5 mm shell with 18% porosity. The reduction in stress shielding was achieved by 28%. Porous stems incorporated BCC structures with dense shells and beads were successfully printed.
Ionic liquids (ILs) are class of solvent whose properties can be modified and tuned to meet industrial requirements. However, a high number of potentially available cations and anions leads to an even increasing members of newly-synthesized ionic liquids, adding to the complexity of understanding on their impact on aquatic organisms. Quantitative structure activity∖property relationship (QSAR∖QSPR) technique has been proven to be a useful method for toxicity prediction. In this work,σ-profile descriptors were used to build linear and non-linear QSAR models to predict the ecotoxicities of a wide variety of ILs towards bioluminescent bacterium Vibrio fischeri. Linear model was constructed using five descriptors resulting in high accuracy prediction of 0.906. The model performance and stability were ascertained using k-fold cross validation method. The selected descriptors set from the linear model was then used in multilayer perceptron (MLP) technique to develop the non-linear model, the accuracy of the model was further enhanced achieving high correlation coefficient with the lowest value being 0.961 with the highest mean square error of 0.157.