articles+ search results

TOXICITY testing, SPECIES distribution, CENSORING (Statistics), UNCERTAINTY, GREENHOUSES, and DISTRIBUTION (Probability theory)

This research proposes new perspectives accounting for the uncertainty on 50% effective rates (ER50) as interval input for species sensitivity distribution (SSD) analyses and evaluating how to include this uncertainty may influence the 5% Hazard Rate (HR5) estimation. We explored various endpoints (survival, emergence, shoot-dry-weight) for non-target plants from seven standard greenhouse studies that used different experimental approaches (vegetative vigour vs. seedling emergence) and applied seven herbicides at different growth stages. Firstly, for each endpoint of each study, a three-parameter log-logistic model was fitted to experimental toxicity test data for each species under a Bayesian framework to get a posterior probability distribution for ER50. Then, in order to account for the uncertainty on the ER50, we explored two censoring criteria to automatically censor ER50 taking the ER50 probability distribution and the range of tested rates into account. Secondly, based on dose-response fitting results and censoring criteria, we considered input ER50 values for SSD analyses in three ways (only point estimates chosen as ER50 medians, interval-censored ER50 based on their 95% credible interval and censored ER50 according to one of the two criteria), by fitting a log-normal distribution under a frequentist framework to get the three corresponding HR5 estimates. We observed that SSD fitted reasonably well when there were at least six distinct intervals for the ER50 values. By comparing the three SSD curves and the three HR5 estimates, we shed new light on the fact that both propagating the uncertainty from the ER50 estimates and including censored data into SSD analyses often leads to smaller point estimates of HR5, which is more conservative in a risk assessment context. In addition, we recommend not to focus solely on the point estimate of the HR5, but also to look at the precision of this estimate as depicted by its 95% confidence interval. [ABSTRACT FROM AUTHOR]

MOLECULAR phylogeny, MOLECULAR models, MOLECULAR evolution, LEAD, UNCERTAINTY, and INFORMATION measurement

Aim: Phylogenetic diversity or phylo‐diversity measures use information about evolutionary history and relationships to inform conservation priorities. These metrics are usually derived from the branches of molecular phylogenies. But inferring phylogenetic timescale from molecular data relies on many assumptions about the evolutionary process, most of which are based on statistical convenience rather than biological information. Here we ask whether known patterns of variation in rate of molecular evolution can lead to errors in phylo‐diversity measures. Location: Global. Methods: We generated sequences with biologically realistic rate variation, parameterized by empirically well‐supported relationships between species traits, macroevolutionary patterns and rate of molecular evolution. We then tested how well commonly used phylo‐diversity measures from these phylogenies reflected the true evolutionary history. Results: We show that reconstructed Faith's phylogenetic diversity (FPD) measures differ from true values by an average of about 10% and up to 38%. Species rankings based on evolutionary distinctness (ED) are also affected by rate variation, with the ranks of taxa changing by up to 10‐11 positions after estimation. Main conclusions: We have shown that realistic levels of rate variation can generate error in FPD and ED measures that could potentially influence prioritization ranking. Studies using metrics based on molecular phylogenetic branch lengths should consider the likely effect of uncertainty in phylogenetic reconstruction on their conclusions. [ABSTRACT FROM AUTHOR]

UNCERTAINTY, COOPERATION, FISHERS, COLLECTIVE action, and COMMUNITIES

Cooperation is thought to be a necessary condition to solve collective action dilemmas such as climate change or the sustainable use of common pool resources. Yet, it is poorly understood how situations pervaded by thresholds shape the behaviour of people facing collective dilemmas. Here we provide empirical evidence that resource users facing thresholds maintain on average cooperative behaviours in the sense of maximising their individual earnings while ensuring future group opportunities. A framed field experiment in the form of a dynamic game with 256 Colombian fishers helped us investigate individual behavioural responses to the existence of thresholds, risk and uncertainty. Thresholds made fishers extract less fish compared to situation without thresholds, but risk had a stronger effect on reducing individual fishing effort. Contrary to previous expectations, cooperation did not break down. If cooperation can be maintained in the face of thresholds, then communicating uncertainty is more policy-relevant than estimating precisely where tipping points lay in social-ecological systems. [ABSTRACT FROM AUTHOR]

PROTECTED areas, CLIMATE change, SPECIES distribution, FRESHWATER biodiversity, UNCERTAINTY, and CASE studies

Identifying priority conservation areas plays a significant role in conserving biodiversity under climate change, but uncertainties create challenges for conservation planning. To reduce uncertainties in the conservation planning framework, we developed an adaptation index to assess the effect of topographic complexity on species adaptation to climate change, which was incorporated into the conservation framework as conservation costs. Meanwhile, the species distributions were predicted by the Maxent model, and the priority conservation areas were optimized during different periods in Sichuan province by the Marxan model. Our results showed that the effect of topographic complexity was critical for species adaptation, but the adaptation index decreased with the temperature increase. Based on the conservation targets and costs, the distributions of priority conservation areas were mainly concentrated in mountainous areas around the Sichuan Basin where may be robust to the adaptation to climate change. In the future, the distributions of priority conservation areas had no evident changes, accounting for about 26% and 28% of the study areas. Moreover, most species habitats could be conserved in terms of conservation targets in these priority conservation areas. Therefore, our approach could achieve biodiversity conservation goals and be highly practical. More importantly, quantifying the effect of topography also is critical for options for planning conservation areas in response to climate change. [ABSTRACT FROM AUTHOR]

LIFTING & carrying (Human mechanics), MOTION, UNCERTAINTY, REACTION forces, and FORECASTING

Analyzing back loading during team manual handling tasks requires the measurement of external contacts and is thus limited to standardized tasks. This paper evaluates the possibility of estimating L5/S1 joint moments based solely on motion data. Ten subjects constituted five two-person teams and handling tasks were analyzed with four different box configurations. Three prediction methods for estimating L5/S1 joint moments were evaluated by comparing them to a gold standard using force platforms: one used only motion data, another used motion data and the traction/compression force applied to the box and one used motion data and the ground reaction forces of one team member. The three prediction methods were based on a contact model with an optimization-based method. Using only motion data did not allow an accurate estimate due to the traction/compression force applied by each team member, which affected L5/S1 joint moments. Back loading can be estimated using motion data and the measurement of the traction/compression force with relatively small errors, comparable to the uncertainty levels reported in other studies. The traction/compression force can be obtained directly with a force measurement unit built into the object to be moved or indirectly by using force platforms on which one of the two handlers stands during the handling task. The use of the proposed prediction methods allows team manual handling tasks to be analyzed in various realistic contexts, with team members who have different anthropometric measurements and with different box characteristics. [ABSTRACT FROM AUTHOR]

ROLLER bearings, FAULT diagnosis (Chemical engineering), CONVOLUTIONAL neural networks, ROTATING machinery, DEMPSTER-Shafer theory, and UNCERTAINTY

Each pattern recognition method has its advantages and disadvantages to diagnose the state of rotating machinery. There are many fault types of rolling bearings with apparent uncertainty. The optimal fusion level is usually challenging to be selected for a specific fault diagnosis task, and extensive human labour and prior knowledge are also highly required during these selections. To solve the above problems, a multimodel decision fusion method based on Deep Convolutional Neural Network and Improved Dempster-Shafer Evidence Theory (DCNN-IDST) is proposed for the inspection of rolling bearing. To solve the defect of the original evidence theory method in the fusion of high-conflict evidence, the fuzzy consistency matrix is introduced. By calculating the factor weight, the reliability and rationality of D-S evidence theory are improved. The DCNN model can learn features from the original data and carry out adaptive feature extraction for multiple sensor information. The features extracted by DCNN adaptively are input into multiple network models for decision fusion. The new method of DCNN-IDST multimodel decision fusion is applied to detect the damage of rolling bearings. To evaluate the effectiveness of the proposed method, both the BP neural network and RBF neural network are used to set up a multigroup comparison test. The result demonstrates that the proposed method can detect the fault of the rolling bearing effectively and achieve the highest diagnosis accuracy among all the tested methods in the experiment. [ABSTRACT FROM AUTHOR]

THERMOMETRY, MAGNETIZATION measurement, TEMPERATURE measurements, SPECTROMETRY, UNCERTAINTY, MAGNETIC particles, and MAGNETIC nanoparticles

Magnetic nanoparticle (MNP) thermometry based on magnetic particle spectroscopy is explored as a potential approach for realizing in situ temperature measurement of 3D objects. MNP thermometry relies on the nonlinear magnetization response to an AC drive field. This nonlinear response has functional dependence on frequency and temperature, governed by the complex magnetization dynamics of MNPs suspended in solution. In this work, we introduce our approach for accurate and precise AC magnetization measurements using actively stabilized drive fields ranging from direct current to 10 kHz. To isolate the harmonic response of MNPs from the drive field, we also perform active cancelation to reach drive field suppression up to 120 dB. Active stabilization and cancelation are utilized for real-time, sensitive measurements of AC magnetization of commercial samples, with stability on the timescale of hours. Initial results for MNP thermometry are demonstrated using this technique, and we achieved a total temperature uncertainty of 410 mK and 170 mK at 100 ms and 10 s integration time, respectively. [ABSTRACT FROM AUTHOR]

INTRACRANIAL pressure, BRAIN injuries, UNCERTAINTY, INTRACRANIAL hypertension, STANDARD deviations, and TIME pressure

Magnitude of intracranial pressure (ICP) elevations and their duration have been associated with worse outcomes in patients with traumatic brain injuries (TBI), however published thresholds for injury vary and uncertainty about these levels has received relatively little attention. In this study, we have analyzed high-resolution ICP monitoring data in 227 adult patients in the CENTER-TBI dataset. Our aim was to identify thresholds of ICP intensity and duration associated with worse outcome, and to evaluate the uncertainty in any such thresholds. We present ICP intensity and duration plots to visualize the relationship between ICP events and outcome. We also introduced a novel bootstrap technique to evaluate uncertainty of the equipoise line. We found that an intensity threshold of 18 ± 4 mmHg (2 standard deviations) was associated with worse outcomes in this cohort. In contrast, the uncertainty in what duration is associated with harm was larger, and safe durations were found to be population dependent. The pressure and time dose (PTD) was also calculated as area under the curve above thresholds of ICP. A relationship between PTD and mortality could be established, as well as for unfavourable outcome. This relationship remained valid for mortality but not unfavourable outcome after adjusting for IMPACT core variables and maximum therapy intensity level. Importantly, during periods of impaired autoregulation (defined as pressure reactivity index (PRx)>0.3) ICP events were associated with worse outcomes for nearly all durations and ICP levels in this cohort and there was a stronger relationship between outcome and PTD. Whilst caution should be exercised in ascribing causation in observational analyses, these results suggest intracranial hypertension is poorly tolerated in the presence of impaired autoregulation. ICP level guidelines may need to be revised in the future taking into account cerebrovascular autoregulation status considered jointly with ICP levels. [ABSTRACT FROM AUTHOR]

DEGREES of freedom, PHASE transformations (Physics), SYMMETRY breaking, UNCERTAINTY, CONDENSED matter, and ELECTRON beams

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. Here, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known. [ABSTRACT FROM AUTHOR]

ORGANIZATIONAL performance, CONFIRMATORY factor analysis, STRUCTURAL equation modeling, LANDSCAPE assessment, and UNCERTAINTY

Purpose: The purpose of this research was to correlate the constructs of productive dynamic capability and organizational performance mediated by environmental uncertainty in micro and small agroindustries of Brazilian states such as the Rio Grande do Sul, Santa Catarina, and Paraná. Methodology: In order to reach the expected aim, quantitative research using the survey technique was developed. The sample that was used consisting of 138 small and micro-sized of southern Brazilian agroindustries. It was performed confirmatory factor analysis and structural equation modeling for the data analysis. In order to analyze the mediation, the two dimensions of environmental uncertainty, complexity, and dynamism were analyzed each one isolated. Findings: The outcomes show a positive correlation between productive dynamic capability and performance in rural agroindustries. The mediation of both complexity and dynamism presented a positive statistical significance, that is the environmental uncertainty mediated the relationship. This study suggests that the agroindustries productive dynamic capability contributes to its performance, and the perception of environmental uncertainty influences this relation. Originality/Value: The study contributes to the dynamic capabilities' theory, advancing and providing new empirical evidence to the investigations on dynamic capabilities, specifically on productive dynamic capability, when relating the performance construct in micro and small agroindustries. It also contributes to the environmental uncertainty field through its mediating effect on the relation between productive dynamic capability and organizational performance. [ABSTRACT FROM AUTHOR]

CONTROL (Psychology), CANCER patient psychology, DIAGNOSTIC errors, INTERVIEWING, RESEARCH methodology, PSYCHOLOGY of men, PROSTATE tumors, PUBLIC health surveillance, QUALITY of life, RISK assessment, UNCERTAINTY, QUALITATIVE research, PROSTATE-specific antigen, SYMPTOMS, HEALTH literacy, PATIENTS' attitudes, and TUMOR grading

Prostate cancer is a frequently diagnosed cancer and made up 6% of male cancer deaths globally in 2008. Its incidence varies more than 25-fold worldwide, which is primarily attributed to the implementation of the prostate-specific antigen (PSA) test in developed countries. To reduce harm of overdiagnosis, most international guidelines recommend surveillance programmes. However, this approach can entail negative psychosocial consequences from being under surveillance for an (over)diagnosed prostate cancer. To explore men's feelings and experiences in a surveillance programme. Qualitative study with Danish men diagnosed with asymptomatic prostate cancer Gleason score ≤ 6, who are in a surveillance programme 12 semi-structured, individual interviews were conducted and analysed with systematic text condensation and selected theories. Most informants reported that they were astonished at the time of diagnosis. They were aware of the small likelihood of dying from cancer, but in some cases, the uncertainty created ambivalence between knowing and not knowing. The men expressed their risk awareness in different ways: a realization that life does not last forever, uncertainty towards the future, a feeling of powerlessness, and a need for control. The men in this study had substantial psychosocial consequences from being labelled with a cancer diagnosis. Bearing these men's high risk of overdiagnosis in mind, it is important to discuss whether the harms of this diagnosis outweigh the benefits. The psychosocial consequences of being in a prostate cancer surveillance programme should be explored further. Current awareness: The number of men living with an asymptomatic prostate cancer has increased the last 20 years after the implementation of the PSA test. Main Statements: Men living with an asymptomatic, low-risk prostate cancer experience negative psychocosial consequences GPs should consider the possible negative psychosocial consequences in their decision-making of measuring the PSA level [ABSTRACT FROM AUTHOR]

LARGE eddy simulation models, PARAMETERIZATION, BOUNDARY layer (Aerodynamics), SWIRLING flow, UNCERTAINTY, OCEAN, and CONVECTIVE boundary layer (Meteorology)

Parameterizations of unresolved turbulent processes often compromise the fidelity of large‐scale ocean models. In this work, we argue for a Bayesian approach to the refinement and evaluation of turbulence parameterizations. Using an ensemble of large eddy simulations of turbulent penetrative convection in the surface boundary layer, we demonstrate the method by estimating the uncertainty of parameters in the convective limit of the popular "K‐Profile Parameterization." We uncover structural deficiencies and propose an alternative scaling that overcomes them. Plain Language Summary: Climate projections are often compromised by significant uncertainties which stem from the representation of physical processes that cannot be resolved—such as clouds in the atmosphere and turbulent swirls in the ocean—but which have to be parameterized. We propose a methodology for improving parameterizations in which they are tested against, and tuned to, high‐resolution numerical simulations of subdomains that represent them more completely. A Bayesian methodology is used to calibrate the parameterizations against the highly resolved model, to assess their fidelity and identify shortcomings. Most importantly, the approach provides estimates of parameter uncertainty. While the method is illustrated for a particular parameterization of boundary layer mixing, it can be applied to any parameterization. Key Points: A Bayesian methodology can be used to probe turbulence parameterizations and better understand their biases and uncertaintiesParameterization parameter distributions, learned using high‐resolution simulations, can be used as prior distributions for climate studies [ABSTRACT FROM AUTHOR]

LIGHT curves and UNCERTAINTY

Betelgeuse has been the focus of considerable recent attention - even from the mainstream news media - due to its recent deep minimum, to the extent that 10% of all the light curve data on the star in the AAVSO archive, extending 126 years, have been obtained in just the last six months. While it is not impossible that Betelgeuse will become a supernova in the next few years or decades, what we know about the star makes this unlikely. A large part of the uncertainty comes from the fact that neither the mass nor the distance are well-established. It is not even certain that Betelgeuse will become a core-collapse supernova, Overall, the star appears to have bright ened significantly over the last 60 years, but the evidence for similarly deep minima in 1946,1947 and 1984 relies on fragmentary data and single observers. The entire extreme historical range of Betelgeuse from magnitude 0.1-1.6 appears to have occurred in just the last three years. [ABSTRACT FROM AUTHOR]

RAIN gauges, STATISTICAL reliability, UNCERTAINTY, RAINFALL, KEY performance indicators (Management), and MOUNTAINS

Satellite-based estimates of rainfall are frequently used to complement scarce networks of gauges. Understanding uncertainties is an important step, but it is often hindered by a lack of validation data or misrepresented by spatial-scale-related uncertainties, which are especially important in spatially variable regions such as mountains. This study evaluates the Integrated Multisatellite Retrievals for GPM (IMERG) V05B 30-min estimates for all three runs (Early, Late, Final) over the high tropical Andes. A unique dataset containing 15 rain gauges located within one IMERG grid at elevations ranging from 3800 to 4600 m provides a first evaluation opportunity in this topographical context. The evaluation was based on categorical, statistical, and graphical methods. Error dependencies on precipitation characteristics and data source of the IMERG estimate were investigated. We show that IMERG severely underdetects precipitation events, thus underestimating precipitation depths. Poor detection is partially attributable to the low-intensity nature of precipitation over the region. However, tracing the error to the data source highlights limitations in passive microwave retrievals over the full range of intensities. No IMERG run has best overall performance, emphasizing that run suitability is application specific. The impact of gauge density on performance metrics was also evaluated and showed that subdaily IMERG accuracy is overestimated by sparse networks. A minimum of six gauges was required at the 30-min increment so that performance metrics are within 0.1 points of their true scores. We provide the first comprehensive assessment of 30-min IMERG in a mountainous setting, highlighting the importance of high-density networks for accurate subdaily evaluations. [ABSTRACT FROM AUTHOR]

UNCERTAINTY, FALL foliage, DECISION making, BALANCE of payments, and GROUP process

Perceptual organization is the process of grouping scene elements into whole entities. A classic example is contour integration, in which separate line segments are perceived as continuous contours. Uncertainty in such grouping arises from scene ambiguity and sensory noise. Some classic Gestalt principles of contour integration, and more broadly, of perceptual organization, have been re-framed in terms of Bayesian inference, whereby the observer computes the probability that the whole entity is present. Previous studies that proposed a Bayesian interpretation of perceptual organization, however, have ignored sensory uncertainty, despite the fact that accounting for the current level of perceptual uncertainty is one the main signatures of Bayesian decision making. Crucially, trial-by-trial manipulation of sensory uncertainty is a key test to whether humans perform near-optimal Bayesian inference in contour integration, as opposed to using some manifestly non-Bayesian heuristic. We distinguish between these hypotheses in a simplified form of contour integration, namely judging whether two line segments separated by an occluder are collinear. We manipulate sensory uncertainty by varying retinal eccentricity. A Bayes-optimal observer would take the level of sensory uncertainty into account—in a very specific way—in deciding whether a measured offset between the line segments is due to non-collinearity or to sensory noise. We find that people deviate slightly but systematically from Bayesian optimality, while still performing "probabilistic computation" in the sense that they take into account sensory uncertainty via a heuristic rule. Our work contributes to an understanding of the role of sensory uncertainty in higher-order perception. Author summary: Our percept of the world is governed not only by the sensory information we have access to, but also by the way we interpret this information. When presented with a visual scene, our visual system undergoes a process of grouping visual elements together to form coherent entities so that we can interpret the scene more readily and meaningfully. For example, when looking at a pile of autumn leaves, one can still perceive and identify a whole leaf even when it is partially covered by another leaf. While Gestalt psychologists have long described perceptual organization with a set of qualitative laws, recent studies offered a statistically-optimal—Bayesian, in statistical jargon—interpretation of this process, whereby the observer chooses the scene configuration with the highest probability given the available sensory inputs. However, these studies drew their conclusions without considering a key actor in this kind of statistically-optimal computations, that is the role of sensory uncertainty. One can easily imagine that our decision on whether two contours belong to the same leaf or different leaves is likely going to change when we move from viewing the pile of leaves at a great distance (high sensory uncertainty), to viewing very closely (low sensory uncertainty). Our study examines whether and how people incorporate uncertainty into contour integration, an elementary form of perceptual organization, by varying sensory uncertainty from trial to trial in a simple contour integration task. We found that people indeed take into account sensory uncertainty, however in a way that subtly deviates from optimal behavior. [ABSTRACT FROM AUTHOR]

ECONOMIC policy, WAVELETS (Mathematics), STOCKS (Finance), STOCK exchanges, UNCERTAINTY, and INVESTOR confidence

This study explores how global economic policy uncertainty (EPU) shocks comove with stock returns (SR) of eight African countries—Botswana, Ghana, Kenya, Morocco, Namibia, Nigeria, South Africa, and Zambia. The study employed daily data from December 2010 to December 2019 using wavelet coherence analysis. The results showed that global EPU comoves with most of the SR of African markets and was concentrated in the longer term, especially during the period between 2011 and 2019, although not substantially. The findings indicate that short-term investments in African stocks are less susceptible to global economic policy uncertainty. It is recommended that foreign investors could hedge agaist policy uncertainties by investing in stock listed in African Stock exchanges while appropriate country-level policies are deployed to manage long-term effect of EPU. [ABSTRACT FROM AUTHOR]

PLASMODIUM falciparum, MALARIA, PLASMODIUM, UNCERTAINTY, COASTS, DNA sequencing, and CONFIDENCE intervals

Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. Fractions of highly-related sample pairs (whose classification using a threshold accounts for uncertainty) were greater within cities versus between. However, based on both highly-related fractions and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with transmission events involving parasites from five clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this hypothesis. For the first time in malaria epidemiology (and to our knowledge in ecological and epidemiological studies more generally), we account for uncertainty around estimated relatedness (an important consideration for studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use threshold-free methods to compare parasite populations and identify clonal components. Threshold-free methods are especially important in analyses of malaria parasites and other recombining organisms with mixed mating systems where thresholds do not have clear interpretation (e.g. due to clonal propagation) and thus undermine the cross-comparison of studies. Author summary: In this study we aimed to characterise connectivity between populations of Plasmodium falciparum malaria parasites sampled from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. We found that connectivity along the coast is consistent with accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission and thus presenting a possible opportunity for targeted intervention. Our study makes methodological contributions that could be adapted to analyses of other recombining organisms. Akin to numerous studies in both epidemiology and ecological, to characterise connectivity, we used genetic data and computed estimates of relatedness based on identity-by-descent (IBD). However, unlike previous studies, confidence intervals around relatedness estimates were included in our analyses. This is an important consideration for all studies that plan to use limited genetic data to estimate IBD-based relatedness. To identify groups of clonal parasites and to compare parasite populations across cities, we used methods that avoid thresholds, e.g. of highly-related parasite pairs. Threshold-free methods promote cross-comparison in studies of recombining organisms for which thresholds do not have a clear interpretation (e.g. for malaria parasites, where the frequency of clonal propagation varies in space and time and is not fully understood). [ABSTRACT FROM AUTHOR]

EQUATIONS of state, APPLIED sciences, SCIENTIFIC community, NATURAL history, and UNCERTAINTY

Sophisticated hydrodynamic codes are commonly used to understand and predict events relevant to natural and applied sciences. The degree to which these simulations reflect reality, however, is dependent on how well we understand the materials and underlying physics involved. These research communities need material models that communicate the uncertainty in the physical properties, which at their basest form comes from the uncertainty in the underlying experimental measurements. We have constructed a new framework for using both experimental measurements and the associated experimental uncertainties to build equation-of-state models that reflect not only current best measurements but also the accuracy of those measurements. This method had been used to construct an ensemble of equation-of-state models for copper that communicates the experimental uncertainties in the data through the equation-of-state model, which is available for application in any simulation metric of interest. [ABSTRACT FROM AUTHOR]

PREJUDICES, UNCERTAINTY, ACTIONS & defenses (Law), WAIVER, and ARBITRATION (Administrative law)

Arbitration agreements are common in commercial and consumer contracts.But two parties can litigate an arbitrable dispute in court if neither party seeks arbitration. That presents a problem if one party changes its mind and invokes its arbitration rights months or years after the lawsuit was filed and substantial litigation activity has taken place. Federal and state courts agree that a party can waive its arbitration rights by engaging in sufficient litigation activity without seeking arbitration, but they take different approaches to deciding how much litigation is too much. Two basic methods exist. Some courts say waiver requires the party opposing arbitration to show it would be prejudiced by the delay. Others say that waiver does not require a showing of prejudice. This Note demonstrates that the presence or absence of a prejudice requirement does not accurately capture the disagreements between the federal circuit courts. Indeed, some circuits that impose a prejudice requirement will find waiver in circumstances where other courts that do not impose a prejudice requirement will not. These divergent approaches result in uncertainty, delay, and expense, undermining arbitration’s benefits. To resolve the circuit split, this Note proposes a bright-line standard under which engaging in litigation never supports a finding of waiver. It also shows that this approach is consistent with common law waiver doctrine and the Federal Arbitration Act. [ABSTRACT FROM AUTHOR]

ROBOT control systems, TRACKING control systems, MANIPULATORS (Machinery), LYAPUNOV stability, SLIDING mode control, and UNCERTAINTY

Robotic manipulators are open to external disturbances and actuation failures during performing a task such as trajectory tracking. In this paper, we present a modifed controller consisting of a global fast sliding surface combined with an adaptive neural network which is called adaptive fast sliding neural control (AFSNC) for a robotic manipulator to precise stable trajectory tracking performance under the external disturbances. The adaptive term is employed to reduce uncertainties due to unmodeled dynamics. Tracking error asymptotically converges to zero according to the Lyapunov stability theorem. Numerical examples have been carried on a planar two-links manipulator to verify the control approach efficiency. The experimental results show that the proposed control approach performs satisfactory trajectory tracking and tracks the desired trajectory in less time with reduced chattering effect compared to the other methods. [ABSTRACT FROM AUTHOR]