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Fulltext Economic perspective of coronavirus (COVID-19)

Usman M, Ali Y, Riaz A, Riaz A, Zubair A

J Public Aff, 2020 Aug 07.
PMID: 32837324 DOI: 10.1002/pa.2252

This study aims to present a quick overview of the novel coronavirus (afterward COVID-19) which triggers from Wuhan, spread approximately 213 countries and territories around the globe, and still currently ongoing. Particularly, we are interested to investigate the economic perspective of COVID-19. This paper uses data from online published articles and current media sources, as the COVID-19 situation is unfolding yet. To deeply explore the said matter, we divide the economic impact into six dimensions that is, Chinese economy, Central Asian economies, South Asian economies, South East and West Asian economies, European economies, Northern African, and Middle Eastern economies. The paper concludes that epidemic situations like COVID-19 severely affect economies around the globe. The basic reasons behind such severity are immobility of labor, reduction in productivity, discontinuation of the supply chain, a decline in exports, uncertainty, and so on. This study is quite important for businesses and policymakers to estimate and plan current and post-COVID-19 situations.

Matched MeSH terms: Uncertainty
Multivariate relationship modeling using nested fuzzy cognitive map

Motlagh O, Papageorgiou E, Tang S, Zamberi Jamaludin

Sains Malaysiana, 2014;43:1781-1790.

Soft computing is an alternative to hard and classic math models especially when it comes to uncertain and incomplete data. This includes regression and relationship modeling of highly interrelated variables with applications in curve fitting, interpolation, classification, supervised learning, generalization, unsupervised learning and forecast. Fuzzy cognitive map (FCM) is a recurrent neural structure that encompasses all possible connections including relationships among inputs, inputs to outputs and feedbacks. This article examines a new methods for nonlinear multivariate regression using fuzzy cognitive map. The main contribution is the application of nested FCM structure to define edge weights in form of meaningful functions rather than crisp values. There are example cases in this article which serve as a platform to modelling even more complex engineering systems. The obtained results, analysis and comparison with similar techniques are included to show the robustness and accuracy of the developed method in multivariate regression, along with future lines of research.

Matched MeSH terms: Uncertainty
Fulltext Preliminary study on the effects of sample density in activities determination of 137Cs using gamma spectrometry counting system

Yii, Mei Wo, Zaharudin Ahmad

Journal of Nuclear and Related Technologies, 2005;2005(2):41-46.
MyJurnal

Gamma Spectrometry Counting System requires similar counting geometries for the calibration source, reference material and samples. The objectives of this study were to find out the effects of the sample density on 137 Cs activities measurement and propose reasonable corrections. Studies found that the activity of the samples is decreasing when the density of samples increased. Therefore, in order to have a more accurate estimation of samples activities; density corrections should be done either by performs mathematical corrections using equation or by increasing the expanded uncertainty when sample densities deviated from calibration source.

Matched MeSH terms: Uncertainty
Fulltext Urinary Sodium and Potassium, and Risk of Ischemic and Hemorrhagic Stroke (INTERSTROKE): A Case-Control Study

Judge C, O'Donnell MJ, Hankey GJ, Rangarajan S, Chin SL, Rao-Melacini P, et al.

Am J Hypertens, 2021 04 20;34(4):414-425.
PMID: 33197265 DOI: 10.1093/ajh/hpaa176

BACKGROUND: Although low sodium intake (<2 g/day) and high potassium intake (>3.5 g/day) are proposed as public health interventions to reduce stroke risk, there is uncertainty about the benefit and feasibility of this combined recommendation on prevention of stroke.
METHODS: We obtained random urine samples from 9,275 cases of acute first stroke and 9,726 matched controls from 27 countries and estimated the 24-hour sodium and potassium excretion, a surrogate for intake, using the Tanaka formula. Using multivariable conditional logistic regression, we determined the associations of estimated 24-hour urinary sodium and potassium excretion with stroke and its subtypes.
RESULTS: Compared with an estimated urinary sodium excretion of 2.8-3.5 g/day (reference), higher (>4.26 g/day) (odds ratio [OR] 1.81; 95% confidence interval [CI], 1.65-2.00) and lower (<2.8 g/day) sodium excretion (OR 1.39; 95% CI, 1.26-1.53) were significantly associated with increased risk of stroke. The stroke risk associated with the highest quartile of sodium intake (sodium excretion >4.26 g/day) was significantly greater (P < 0.001) for intracerebral hemorrhage (ICH) (OR 2.38; 95% CI, 1.93-2.92) than for ischemic stroke (OR 1.67; 95% CI, 1.50-1.87). Urinary potassium was inversely and linearly associated with risk of stroke, and stronger for ischemic stroke than ICH (P = 0.026). In an analysis of combined sodium and potassium excretion, the combination of high potassium intake (>1.58 g/day) and moderate sodium intake (2.8-3.5 g/day) was associated with the lowest risk of stroke.
CONCLUSIONS: The association of sodium intake and stroke is J-shaped, with high sodium intake a stronger risk factor for ICH than ischemic stroke. Our data suggest that moderate sodium intake-rather than low sodium intake-combined with high potassium intake may be associated with the lowest risk of stroke and expected to be a more feasible combined dietary target.

Matched MeSH terms: Uncertainty
X-ray spectra and quality parameters from Monte Carlo simulation and analytical filters

Salehi Z, Ya Ali NK, Yusoff AL

Appl Radiat Isot, 2012 Nov;70(11):2586-9.
PMID: 22940409 DOI: 10.1016/j.apradiso.2011.12.007

BEAMnrc was used to derive the X-ray spectra, from which HVL and homogeneity coefficient were determined, for different kVp and filtration settings. Except for the peak at 61 keV, the spectra are in good agreement with the IPEM report 78 data for the case of filtered beams, whereas the unfiltered beams exhibit softer spectra. Although the current attenuation data deviates from the IPEM 78 data by ~±0.5%, this has negligible effects on the calculated HVL values.

Matched MeSH terms: Uncertainty
Be Careful Where You Smile: Culture Shapes Judgments of Intelligence and Honesty of Smiling Individuals

Krys K, -Melanie Vauclair C, Capaldi CA, Lun VM, Bond MH, Domínguez-Espinosa A, et al.

Journal of nonverbal behavior, 2015 12 30;40:101-116.
PMID: 27194817

Smiling individuals are usually perceived more favorably than non-smiling ones-they are judged as happier, more attractive, competent, and friendly. These seemingly clear and obvious consequences of smiling are assumed to be culturally universal, however most of the psychological research is carried out in WEIRD societies (Western, Educated, Industrialized, Rich, and Democratic) and the influence of culture on social perception of nonverbal behavior is still understudied. Here we show that a smiling individual may be judged as less intelligent than the same non-smiling individual in cultures low on the GLOBE's uncertainty avoidance dimension. Furthermore, we show that corruption at the societal level may undermine the prosocial perception of smiling-in societies with high corruption indicators, trust toward smiling individuals is reduced. This research fosters understanding of the cultural framework surrounding nonverbal communication processes and reveals that in some cultures smiling may lead to negative attributions.

Matched MeSH terms: Uncertainty
Security and privacy issues related to the workplace-based security robot system

Guangnan Z, Tao H, Rahman MA, Yao L, Al-Saffar A, Meng Q, et al.

Work, 2021;68(3):871-879.
PMID: 33612530 DOI: 10.3233/WOR-203421

BACKGROUND: An isolated robot must take account of uncertainty in its world model and adapt its activities to take into account such as uncertainty. In the same way, a robot interaction with security and privacy issues (RISAPI) with people has to account for its confusion about the human internal state, as well as how this state will shift as humans respond to the robot.
OBJECTIVES: This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game.
RESULTS: In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities.
CONCLUSION: The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.

Matched MeSH terms: Uncertainty
Using GWAS top hits to inform priors in Bayesian fine-mapping association studies

Walters K, Cox A, Yaacob H

Genet Epidemiol, 2019 Sep;43(6):675-689.
PMID: 31286571 DOI: 10.1002/gepi.22212

The default causal single-nucleotide polymorphism (SNP) effect size prior in Bayesian fine-mapping studies is usually the Normal distribution. This choice is often based on computational convenience, rather than evidence that it is the most suitable prior distribution. The choice of prior is important because previous studies have shown considerable sensitivity of causal SNP Bayes factors to the form of the prior. In some well-studied diseases there are now considerable numbers of genome-wide association study (GWAS) top hits along with estimates of the number of yet-to-be-discovered causal SNPs. We show how the effect sizes of the top hits and estimates of the number of yet-to-be-discovered causal SNPs can be used to choose between the Laplace and Normal priors, to estimate the prior parameters and to quantify the uncertainty in this estimation. The methodology can readily be applied to other priors. We show that the top hits available from breast cancer GWAS provide overwhelming support for the Laplace over the Normal prior, which has important consequences for variant prioritisation. This work in this paper enables practitioners to derive more objective priors than are currently being used and could lead to prioritisation of different variants.

Matched MeSH terms: Uncertainty
Fulltext Urban tinkering

Elmqvist T, Siri J, Andersson E, Anderson P, Bai X, Das PK, et al.

Sustain Sci, 2018;13(6):1549-1564.
PMID: 30546487 DOI: 10.1007/s11625-018-0611-0

Cities are currently experiencing serious, multifaceted impacts from global environmental change, especially climate change, and the degree to which they will need to cope with and adapt to such challenges will continue to increase. A complex systems approach inspired by evolutionary theory can inform strategies for policies and interventions to deal with growing urban vulnerabilities. Such an approach would guide the design of new (and redesign of existing) urban structures, while promoting innovative integration of grey, green and blue infrastructure in service of environmental and health objectives. Moreover, it would contribute to more flexible, effective policies for urban management and the use of urban space. Four decades ago, in a seminal paper in Science, the French evolutionary biologist and philosopher Francois Jacob noted that evolution differs significantly in its characteristic modes of action from processes that are designed and engineered de novo (Jacob in Science 196(4295):1161-1166, 1977). He labeled the evolutionary process "tinkering", recognizing its foundation in the modification and molding of existing traits and forms, with occasional dramatic shifts in function in the context of changing conditions. This contrasts greatly with conventional engineering and design approaches that apply tailor-made materials and tools to achieve well-defined functions that are specified a priori. We here propose that urban tinkering is the application of evolutionary thinking to urban design, engineering, ecological restoration, management and governance. We define urban tinkering as:A mode of operation, encompassing policy, planning and management processes, that seeks to transform the use of existing and design of new urban systems in ways that diversify their functions, anticipate new uses and enhance adaptability, to better meet the social, economic and ecological needs of cities under conditions of deep uncertainty about the future.This approach has the potential to substantially complement and augment conventional urban development, replacing predictability, linearity and monofunctional design with anticipation of uncertainty and non-linearity and design for multiple, potentially shifting functions. Urban tinkering can function by promoting a diversity of small-scale urban experiments that, in aggregate, lead to large-scale often playful innovative solutions to the problems of sustainable development. Moreover, the tinkering approach is naturally suited to exploring multi-functional uses and approaches (e.g., bricolage) for new and existing urban structures and policies through collaborative engagement and analysis. It is thus well worth exploring as a means of delivering co-benefits for environment and human health and wellbeing. Indeed, urban tinkering has close ties to systems approaches, which often are recognized as critical to sustainable development. We believe this concept can help forge much-closer, much-needed ties among engineers, architects, evolutionary ecologists, health specialists, and numerous other urban stakeholders in developing innovative, widely beneficial solutions for society and contribute to successful implementation of SDG11 and the New Urban Agenda.

Matched MeSH terms: Uncertainty
Characterization of MOSkin detector for in vivo dose verification during Cobalt-60 high dose-rate intracavitary brachytherapy

Jamalludin Z, Jong WL, Abdul Malik R, Rosenfeld A, Ung NM

Phys Med, 2019 Feb;58:1-7.
PMID: 30824140 DOI: 10.1016/j.ejmp.2019.01.010

In vivo dosimetry in high dose-rate (HDR) intracavitary brachytherapy (ICBT) is important for assessing the true dose received by surrounding organs at risk during treatment. It also serves as part of the treatment delivery quality assurance and verification program with the use of a suitable dosimeter. Such a dosimeter should be characterized under brachytherapy conditions before clinical application to ensure the accuracy of in vivo measurement. In this study, a MOSFET-based detector, MOSkin, was calibrated and characterized under HDR Cobalt-60 (Co-60) brachytherapy source. MOSkin possessed the major advantages of having small physical and dosimetric sizes of 4.8 × 10-6 mm3 with the ability to provide real-time measurements. Using solid water and polymethyl methacrylate (PMMA) phantom, the detectors' reproducibility, linearity, angular and distance dependency was tested for its suitability as an in vivo detector. Correction factors to account for differences in depth measurements were determined. The MOSkin detector showed a reliable response when tested under Co-60 brachytherapy range of doses with an excellent linearity of R2 = 0.9997 and acceptable reproducibility. A phantom verification study was also conducted to verify the differences between MOSkin responses and treatment planning (TPS) calculated doses. By taking into account several correction factors, deviations ranging between 0.01 and 0.4 Gy were found between MOSkin measured and TPS doses at measurement distance of 20-55 mm. The use of MOSkin as the dosimeter of choice for in vivo dosimetry under Co-60 brachytherapy condition is feasible.

Matched MeSH terms: Uncertainty
Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods

Rahmati O, Choubin B, Fathabadi A, Coulon F, Soltani E, Shahabi H, et al.

Sci Total Environ, 2019 Oct 20;688:855-866.
PMID: 31255823 DOI: 10.1016/j.scitotenv.2019.06.320

Although estimating the uncertainty of models used for modelling nitrate contamination of groundwater is essential in groundwater management, it has been generally ignored. This issue motivates this research to explore the predictive uncertainty of machine-learning (ML) models in this field of study using two different residuals uncertainty methods: quantile regression (QR) and uncertainty estimation based on local errors and clustering (UNEEC). Prediction-interval coverage probability (PICP), the most important of the statistical measures of uncertainty, was used to evaluate uncertainty. Additionally, three state-of-the-art ML models including support vector machine (SVM), random forest (RF), and k-nearest neighbor (kNN) were selected to spatially model groundwater nitrate concentrations. The models were calibrated with nitrate concentrations from 80 wells (70% of the data) and then validated with nitrate concentrations from 34 wells (30% of the data). Both uncertainty and predictive performance criteria should be considered when comparing and selecting the best model. Results highlight that the kNN model is the best model because not only did it have the lowest uncertainty based on the PICP statistic in both the QR (0.94) and the UNEEC (in all clusters, 0.85-0.91) methods, but it also had predictive performance statistics (RMSE = 10.63, R2 = 0.71) that were relatively similar to RF (RMSE = 10.41, R2 = 0.72) and higher than SVM (RMSE = 13.28, R2 = 0.58). Determining the uncertainty of ML models used for spatially modelling groundwater-nitrate pollution enables managers to achieve better risk-based decision making and consequently increases the reliability and credibility of groundwater-nitrate predictions.

Matched MeSH terms: Uncertainty
Vulnerability of Vietnam to typhoons: A spatial assessment based on hazards, exposure and adaptive capacity

Nguyen KA, Liou YA, Terry JP

Sci Total Environ, 2019 Sep 10;682:31-46.
PMID: 31121354 DOI: 10.1016/j.scitotenv.2019.04.069

Typhoons have devastating impacts across many Asian countries. Vietnam is presently one of the most disaster-prone nations. Typhoons regularly disrupt human lives and livelihoods in various ways and cause significant damage. Making efficient policy decisions to minimize the vulnerability of affected communities is crucial. This requires a deep understanding of the factors that make a society vulnerable to extreme events and natural disasters. An appropriate approach is integrating the three dimensions of hazard, exposure and sensitivity, and community adaptive capacity. However, the vulnerability and adaptive capacity response to typhoons within Vietnam is poorly investigated. Here, we develop a conceptual framework that incorporates 21 indicators to identify vulnerability and adaptive capacity (VAC) using geospatial techniques at regional scales, applied over Vietnam. We find large spatial differences in VAC and are able to identify the top-priority regions that need to enhance their adaptation to typhoons. The Southern Coastal area, South East and Red River Delta demonstrate high and very high vulnerability because of their physical features and the intensity of typhoons that frequently cross these parts of Vietnam. The lower Mekong Delta and Northern Coastal areas are vulnerable to typhoon-driven flood threats, in particular where compounded by sea-level rise. Our framework successfully identified the spatial distribution and different levels of VAC within acceptable limits of uncertainty. It can therefore serve as a template to tackle national issues in disaster risk reduction in Vietnam and assist in the development of suitable mitigation strategies to achieve sustainable outcomes.

Matched MeSH terms: Uncertainty
Fulltext A rule-based energy management scheme for long-term optimal capacity planning of grid-independent microgrid optimized by multi-objective grasshopper optimization algorithm

Bukar AL, Tan CW, Yiew LK, Ayop R, Tan WS

Energy Convers Manag, 2020 Oct 01;221:113161.
PMID: 32834297 DOI: 10.1016/j.enconman.2020.113161

Off-grid electrification of remote communities using sustainable energy systems (SESs) is a requisite for realizing sustainable development goals. Nonetheless, the capacity planning of the SESs is challenging as it needs to fulfil the fluctuating demand from a long-term perspective, in addition to the intermittency and unpredictable nature of renewable energy sources (RESs). Owing to the nonlinear and non-convex nature of the capacity planning problem, an efficient technique must be employed to achieve a cost-effective system. Existing techniques are, subject to some constraints on the derivability and continuity of the objective function, prone to premature convergence, computationally demanding, follows rigorous procedures to fine-tune the algorithm parameters in different applications, and often do not offer a fair balance during the exploitation and exploration phase of the optimization process. Furthermore, the literature review indicates that researchers often do not implement and examine the energy management scheme (EMS) of a microgrid while computing for the capacity planning problem of microgrids. This paper proposes a rule-based EMS (REMS) optimized by a nature-inspired grasshopper optimization algorithm (GOA) for long-term capacity planning of a grid-independent microgrid incorporating a wind turbine, a photovoltaic, a battery (BT) bank and a diesel generator (

D

g
e
n

). In which, a rule-based algorithm is used to implement an EMS to prioritize the usage of RES and coordinate the power flow of the proposed microgrid components. Subsequently, an attempt is made to explore and confirm the efficiency of the proposed REMS incorporated with GOA. The ultimate goal of the objective function is to minimize the cost of energy (COE) and the deficiency of power supply probability (DPSP). The performance of the REMS is examined via a long-term simulation study to ascertain the REMS resiliency and to ensure the operating limit of the BT storage is not violated. The result of the GOA is compared with particle swarm optimization (PSO) and a cuckoo search algorithm (CSA). The simulation results indicate that the proposed technique's superiority is confirmed in terms of convergence to the optimal solution. The simulation results confirm that the proposed REMS has contributed to better adoption of a cleaner energy production system, as the scheme significantly reduces fuel consumption,

CO

2

emission and COE by 92.4%, 92.3% and 79.8%, respectively as compared to the conventional

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g
e
n

. The comparative evaluation of the algorithms shows that REMS-GOA yields a better result as it offers the least COE (objective function), at $0.3656/kW h, as compared to the REMS-CSA at $0.3662/kW h and REMS-PSO at $0.3674/kW h, for the desired DPSP of 0%. Finally, sensitivity analysis is performed to highlight the effect of uncertainties on the system inputs that may arise in the future.

Matched MeSH terms: Uncertainty
Fulltext Ranking negative emissions technologies under uncertainty

Ng WY, Low CX, Putra ZA, Aviso KB, Promentilla MAB, Tan RR

Heliyon, 2020 Dec;6(12):e05730.
PMID: 33364497 DOI: 10.1016/j.heliyon.2020.e05730

Existing mitigation strategies to reduce greenhouse gas (GHG) emissions are inadequate to reach the target emission reductions set in the Paris Agreement. Hence, the deployment of negative emission technologies (NETs) is imperative. Given that there are multiple available NETs that need to be evaluated based on multiple criteria, there is a need for a systematic method for ranking and prioritizing them. Furthermore, the uncertainty in estimating the techno-economic performance levels of NETs is a major challenge. In this work, an integrated model of fuzzy analytical hierarchy process (AHP) and interval-extended Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed to address the multiple criteria, together with data uncertainties. The potential of NETs is assessed through the application of this hybrid decision model. Sensitivity analysis is also conducted to evaluate the robustness of the ranking generated. The result shows Bioenergy with Carbon Capture and Storage (BECCS) as the most optimal alternative for achieving negative emission goals since it performed robustly in the different criteria considered. Meanwhile, energy requirement emerged as the most preferred or critical criterion in the deployment of NETs based on the decision-maker. This paper renders a new research perspective for evaluating the viability of NETs and extends the domains of the fuzzy AHP and interval-extended TOPSIS hybrid model.

Matched MeSH terms: Uncertainty
Fulltext Assessing Financial Risk Spillover and Panic Impact of Covid-19 on European and Vietnam Stock market

Moslehpour M, Al-Fadly A, Ehsanullah S, Chong KW, Xuyen NTM, Tan LP

Environ Sci Pollut Res Int, 2022 Apr;29(19):28226-28240.
PMID: 34993822 DOI: 10.1007/s11356-021-18170-2

This study examined the influence of tail risks on global financial markets, which aids in better understanding of the emergence of COVID-19. This study looks at the global and Vietnamese stock markets impacted by the COVID-19 pandemic to identify systemic emergencies. Risk dependent value (CoVaR) and Delta link VaR are two important tail-related risk indicators used in Conditional Bivariate Dynamic Correlation (DCC) (CoVaR). The empirical findings demonstrate that when COVID-19's worldwide spread widens, the volatility transmission of systemic risks across the global stock market and multiple exchanges shifts and becomes more relevant over time. At the time of COVID-19, the world industrial market was larger than the Vietnamese stock market, and the Vietnamese stock market posed a lesser danger to the global market. A closer examination of the link between the Vietnam value-at-risk (VaR) range index sample and the world stock index indicates a significant degree of downside risk integration in key monetary systems, particularly during the COVID-19 era. Our study findings may help regulators, politicians, and portfolio risk managers in Vietnam and worldwide during the unique moment of uncertainty created by the COVID-19 epidemic.

Matched MeSH terms: Uncertainty
Rapid assessment of total MCPD esters in palm-based cooking oil using ATR-FTIR application and chemometric analysis

Goh KM, Maulidiani M, Rudiyanto R, Wong YH, Ang MY, Yew WM, et al.

Talanta, 2019 Jun 01;198:215-223.
PMID: 30876552 DOI: 10.1016/j.talanta.2019.01.111

The technique of Fourier transform infrared spectroscopy is widely used to generate spectral data for use in the detection of food contaminants. Monochloropropanediol (MCPD) is a refining process-induced contaminant that is found in palm-based fats and oils. In this study, a chemometric approach was used to evaluate the relationship between the FTIR spectra and the total MCPD content of a palm-based cooking oil. A total of 156 samples were used to develop partial least squares regression (PLSR), artificial neural network (nnet), average artificial neural network (avNNET), random forest (RF) and cubist models. In addition, a consensus approach was used to generate fusion result consisted from all the model mentioned above. All the models were evaluated based on validation performed using training and testing datasets. In addition, the box plot of coefficient of determination (R2), root mean square error (RMSE), slopes and intercepts by 100 times randomization was also compared. Evaluation of performance based on the testing R2 and RMSE suggested that the cubist model predicted total MCPD content with the highest accuracy, followed by the RF, avNNET, nnet and PLSR models. The overfitting tendency was assessed based on differences in R2 and RMSE in the training and testing calibrations. The observations showed that the cubist and avNNET models possessed a certain degree of overfitting. However, the accuracy of these models in predicting the total MCPD content was high. Results of the consensus model showed that it slightly improved the accuracy of prediction as well as significantly reduced its uncertainty. The important variables derived from the cubist and RF models suggested that the wavenumbers corresponding to the MCPDs originated from the -CH=CH2 or CH=CH (990-900 cm-1) and C-Cl stretch (800-700 cm-1) regions of the FTIR spectrum data. In short, chemometrics in combination with FTIR analysis especially for the consensus model represent a potential and flexible technique for estimating the total MCPD content of refined vegetable oils.

Matched MeSH terms: Uncertainty
Simulation of live-cell imaging system reveals hidden uncertainties in cooperative binding measurements

Watabe M, Arjunan SNV, Chew WX, Kaizu K, Takahashi K

Phys Rev E, 2019 Jul;100(1-1):010402.
PMID: 31499827 DOI: 10.1103/PhysRevE.100.010402

We propose a computational method to quantitatively evaluate the systematic uncertainties that arise from undetectable sources in biological measurements using live-cell imaging techniques. We then demonstrate this method in measuring the biological cooperativity of molecular binding networks, in particular, ligand molecules binding to cell-surface receptor proteins. Our results show how the nonstatistical uncertainties lead to invalid identifications of the measured cooperativity. Through this computational scheme, the biological interpretation can be more objectively evaluated and understood under a specific experimental configuration of interest.

Matched MeSH terms: Uncertainty
Fulltext A review on criteria and decision-making techniques in solving landfill site selection problems

Nur Azriati Mat, Aida Mauziah Benjamin, Syariza Abdul-Rahman

Journal of Advanced Review on Scientific Research, 2017;37(1):14-32.
MyJurnal

The selection of landfill, which happens to be an environmental issue, has attracted
the attention of many researchers from the fields of waste management and
environmental sciences worldwide. Hence, in the attempt to overcome this problem,
some decision-making techniques, including Geographic Information Systems (GIS)
and Multi-Criteria Decision Analysis (MCDA), have been widely utilized in prior studies,
where multiple criteria, particularly in site selection process, have been employed.
With that, this article identifies the selection criteria for landfill selection and presents
a review concerning decision-making techniques that have been used in past studies
for two important phases involved during the process of site selection, namely, (1)
preliminary site screening, and (2) assessment of site suitability. As such, some 82
articles chosen from 34 peer-reviewed journals had been investigated in detail. The
results showed that 42.68% of the selected articles integrated GIS and MCDA
techniques to solve the problem of landfill site selection, and this is followed by
integrating GIS and fuzzy MCDA technique (18.29%). Both these techniques are indeed
powerful tools that can guide decision-makers to solve problems in making decisions
on the basis of various criteria under certainty and uncertainty results, mainly involving
environmental issues.

Matched MeSH terms: Uncertainty
An offset-free MPC formulation for nonlinear systems using adaptive integral controller

Hermansson AW, Syafiie S

ISA Trans, 2019 Aug;91:66-77.
PMID: 30782432 DOI: 10.1016/j.isatra.2019.01.037

This paper investigates a novel offset-free control scheme based on a multiple model predictive controller (MMPC) and an adaptive integral action controller for nonlinear processes. Firstly, the multiple model description captures the essence of the nonlinear process, while keeping the MPC optimization linear. Multiple models also enable the controller to deal with the uncertainty associated with changing setpoint. Then, a min-max approach is utilized to counter the effect of parametric uncertainty between the linear models and the nonlinear process. Finally, to deal with other uncertainties, such as input and output disturbances, an adaptive integral action controller is run in parallel to the MMPC. Thus creating a novel offset-free approach for nonlinear systems that is more easily tuned than observer-based MPC. Simulation results for a pH-controller, which acts as an example of a nonlinear process, are presented to demonstrate the usefulness of the technique compared to using an observer-based MPC.

Matched MeSH terms: Uncertainty
Fulltext Visual perception of kuda and sila service techniques in sepak takraw

Mohamad Razali Abdullah, Saidon Amri, Suppiah, Pathmanathan K.

Movement Health & Exercise, 2012;1(1):25-37.
MyJurnal

Two major types of services in sepak takraw are kuda and sila services. Even though both services are delivered at high speed, each is composed of different kinematic features. The purpose of the study was to determine the fundamental differences in perceptual strategies in
anticipating the kuda and sila services. The receiver of the game in sepak takraw makes decisions under severe time constraint in both spatial and temporal uncertainty. The study examined two groups of 12 players each; the experts and the novices. Perceptual displays in anticipation of the
kuda and sila services were prompted using video stimulations consisting of seven temporal occlusions t1 (240 milliseconds at pre-contact), t2 (160 milliseconds at pre-contact), t3 (80 milliseconds at pre-contact, t4 (0 millisecond at contact), t5 (80 milliseconds at post-contact), t6 (160
milliseconds at post-contact), and t7 (no occlusion). Significant differences amongst expert players in anticipating kuda and sila services were at t1 F (14, 180) = 2.37; p < 0.05], t2 F (14, 180) = 5.60; p < 0.05], t3 F (14, 180) = 3.81; p < 0.05] and t4 F (14, 180) = 2.00; p < 0.05]. Similar comparisons at t5, t6, and t7 did not yield any significant differences. In addition, there were significant differences amongst novice players in anticipating kuda and sila services at t2 F (14,
180) = 2.27; p < 0.05], t3 F (14, 180) = 1.94; p < 0.05], t4 F (14, 180) = 2.61; p < 0.05], and t5 F (14, 180) = 9.38; p < 0.05]. Overall findings revealed that expert players found it more difficult to anticipate kuda service compared to sila service at t1. Hence, the kuda service is more
difficult to anticipate than sila service. Participants of this study demonstrated a more effective visual perceptual strategy to counter attack a sila service than they would with a kuda service.

Matched MeSH terms: Uncertainty

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