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The Wells–Riley model has been widely used to estimate airborne infection risk, typically from a deterministic point of view (i.e., focusing on the average number of infections) or in terms of a per capita probability of infection. Some of its main limitations relate to considering well‐mixed air, steady‐state concentration of pathogen in the air, a particular amount of time for the indoor interaction, and that all individuals are homogeneous and behave equally. Here, we revisit the Wells–Riley model, providing a mathematical formalism for its stochastic version, where the number of infected individuals follows a Binomial distribution. Then, we extend the Wells–Riley methodology to consider transient behaviours, randomness, and population heterogeneity. In particular, we provide analytical solutions for the number of infections and the per capita probability of infection when: (i) susceptible individuals remain in the room after the infector leaves, (ii) the duration of the indoor interaction is random/unknown, and (iii) infectors have heterogeneous quanta production rates (or the quanta production rate of the infector is random/unknown). We illustrate the applicability of our new formulations through two case studies: infection risk due to an infectious healthcare worker (HCW) visiting a patient, and exposure during lunch for uncertain meal times in different dining settings. Our results highlight that infection risk to a susceptible who remains in the space after the infector leaves can be nonnegligible, and highlight the importance of incorporating uncertainty in the duration of the indoor interaction and the infectivity of the infector when estimating risk. [ABSTRACT FROM AUTHOR]

Introduction Material and Methods Results Conclusions This study aimed to validate the Sargent risk stratification algorithm for the prediction of placenta accreta spectrum (PAS) severity using data collected from multiple centers and using the multicenter data to improve the model.We conducted a multicenter analysis using data collected for the IS‐PAS database. The Sargent model's effectiveness in distinguishing between abnormally adherent placenta (FIGO grade 1) and abnormally invasive placenta (FIGO grades 2 and 3) was evaluated. A new model was developed using multicenter data from the IS‐PAS database.The database included 315 cases of suspected PAS, of which 226 had fully documented standardized ultrasound signs. The final diagnosis was normal placentation in 5, abnormally adherent placenta/FIGO grade 1 in 43, and abnormally invasive placenta/FIGO grades 2 and 3 in 178. The external validation of the Sargent model revealed moderate predictive accuracy in a multicenter setting (C‐index 0.68), compared to its higher accuracy in a single‐center context (C‐index 0.90). The newly developed model achieved a C‐index of 0.74.The study underscores the difficulty in developing universally applicable PAS prediction models. While models like that of Sargent et al. show promise, their reproducibility varies across settings, likely due to the interpretation of the ultrasound signs. The findings support the need for updating the current ultrasound descriptors and for the development of any new predictive models to use data collected by different operators in multiple clinical settings. [ABSTRACT FROM AUTHOR]

We construct a coupling between two seemingly very different constructions of the standard additive coalescent, which describes the evolution of masses merging pairwise at rates proportional to their sums. The first construction, due to Aldous and Pitman, involves the components obtained by logging the Brownian continuum random tree (CRT) by a Poissonian rain on its skeleton as time increases. The second one, due to Bertoin, involves the excursions above its running infimum of a linear‐drifted standard Brownian excursion as its drift decreases. Our main tool is the use of an exploration algorithm of the so‐called cut‐tree of the Brownian CRT, which is a tree that encodes the genealogy of the fragmentation of the CRT. [ABSTRACT FROM AUTHOR]

This paper sets out to develop an efficient probabilistic optimal power flow (POPF) algorithm to assess the influence of wind power on power grid. Given a set of wind data at multiple sites, their marginal distributions are fitted by a newly developed generalized Johnson system, whose parameters are specified by a percentile matching method. The correlation of wind speeds is characterized by a flexible Liouville copula, which allows to model the asymmetric dependence structure. In order to improve the efficiency for solving POPF problem, a lattice sampling method is developed to generate wind samples at multiple sites, and a logistic mixture model is proposed to fit distributions of POPF outputs. Finally, case studies are performed, the generalized Johnson system is compared with Weibull distribution and the original Johnson system for fitting wind samples, Liouville copula is compared against Archimedean copula for modelling correlated wind samples, and lattice sampling method is compared with Sobol sequence and Latin hypercube sampling for solving POPF problem on IEEE 118‐bus system, the results indicate the higher accuracy of the proposed methods for recovering the joint cumulative distribution function of correlated wind samples, as well as the higher efficiency for calculating statistical information of POPF outputs. [ABSTRACT FROM AUTHOR]

Probabilistic reliability analysis of a prestressed concrete bridge – part 1 – Semi‐probabilistic reassessment and probabilistic modeling of a single‐span 6‐webbed t‐beam bridge Maintaining the existing transportation infrastructure is a major challenge as the structures continue to age, the traffic loads increase and comprehensive replacement is impossible given limited budgets and resources. On existing structures present material characteristics, geometries or loads can be recorded on an object‐specific basis. In Germany the reassessment of existing bridges is carried out in accordance with the reassessment guidelines at the stages 1 and 2 using the semi‐probabilistic partial safety concept. Only in exceptional cases will a measurement‐based assessment or a scientific analysis acc. to levels 3 and 4 be carried out. However the inclusion of additional information from condition assessment offers many advantages for a realistic reassessment. In probabilistic calculation methods, such information can be taken directly into account. The aim of this two‐part article is to present the potentials and advantages of directly including the results of non‐destructive testing methods when assessing the condition of bridge structures. The concept is presented on a prestressed concrete bridge. The first part deals with the possibilities for transferring the input values of the usual semi‐probabilistic calculation into stochastic models. Starting from the semi‐probabilistic reassessment acc. to current regulations, the probabilistic modeling of all relevant basic variables for the ultimate limit states of bending, shear and torsion is carried out. [ABSTRACT FROM AUTHOR]

Expert judgment often involves estimating magnitudes, such as the frequency of deaths due to a pandemic. Three experiments (Ns = 902, 431, and 755, respectively) were conducted to examine the effect of outcome framing (e.g., half of a threatened group expected to survive vs. die), probability level (low vs. high), and probability format (verbal, numeric, or combined) on the estimated frequency of survivals/deaths. Each experiment found an interactive effect of frame and probability level, which supported the hypothesis that forecasted outcomes received by participants were implicitly quantified as lower bounds (i.e., "at least half"). Responding in a manner consistent with a lower‐bound "at least" interpretation was unrelated to incoherence (Experiments 1 and 2) and positively related to numeracy (Experiments 1 and 3), verbal reasoning (Experiment 3), and actively open‐minded thinking (Experiments 2 and 3). The correlational results indicate that implicit lower bounding is an aspect of linguistic inference and not a cognitive error. Implications for research on framing effects are discussed. [ABSTRACT FROM AUTHOR]

Translation abstract Probabilistic reliability analysis of a prestressed concrete bridge – Part 2 – Mechanical modelling and probabilistic reassessment of a single‐span 6‐webbed t–beam bridgeIn the second part of this article the limit state functions in the ultimate limit state for bending with axial force, shear with shear reinforcement and torsion are presented. The input variables of the mechanical resistance models are accompanied by numerous illustrations. The probabilistic verifications are carried out on the basis of the probabilistic models from the first part of this article and the mechanical models from this second part. In the subsequently compiled reliability analysis, reference is made to the semiprobabilistic calculation results. With the parameter studies it is shown which input variable measurable by non‐destructive testing methods have the greatest influence on the calculated reliability. On this basis finally it is shown what opportunities arise for a reassessment from conducting non‐destructive testing in the inspection. [ABSTRACT FROM AUTHOR]

Summary: Opportunistic network (OppNet) belongs to the category of Mobile Ad‐hoc Networks (MANETs), a kind of Delay Tolerant Network (DTN), where the wireless nodes are completely mobile and the data transmission routes are dynamic. The major challenge in developing a routing model for such a network is the unpredictable nature of the movement of the nodes. In this paper, a spatiotemporal prediction model based on human mobility pattern is proposed using Bayesian posterior probability (BPPR) where several clusters are identified within the network and the day and time duration of nodes visiting those clusters are recorded. The Bayesian posterior probability is then used to determine the probability of the neighbor node visiting the destination's cluster. If the calculated probability for that node is higher than a specified threshold, the packet will be forwarded. A comparison of the results obtained on simulation is made with benchmark models—Epidemic, Prophet, HBPR, EDR, NexT, and EBC, to name a few, where it is found that on average the proposed model outperforms the other models in terms of delivery probability, hop count and number of messages dropped by around 23.89%, 24.8%, 24.4%, 37%, 11%, and 42% respectively, with varying number of nodes, TTL, message generation interval, and buffer size. Similar improvements have been observed in terms of the other two metrics. In terms of overhead ratio, the proposed model outperforms Epidemic, Prophet, HBPR, NexT, and EBC. However, as the number of nodes and TTL are varied, BPPR performs better than NexT by around 9% and 12%, respectively, in terms of average latency. [ABSTRACT FROM AUTHOR]

In everyday perception, we combine incoming sensory information with prior expectations. Expectations can be induced by cues that indicate the probability of following sensory events. The information provided by cues may differ and hence lead to different levels of uncertainty about which event will follow. In this experiment, we employed pupillometry to investigate whether the pupil dilation response to visual cues varies depending on the level of cue‐associated uncertainty about a following auditory outcome. Also, we tested whether the pupil dilation response reflects the amount of surprise about the subsequently presented auditory stimulus. In each trial, participants were presented with a visual cue (face image) which was followed by an auditory outcome (spoken vowel). After the face cue, participants had to indicate by keypress which of three auditory vowels they expected to hear next. We manipulated the cue‐associated uncertainty by varying the probabilistic cue‐outcome contingencies: One face was most likely followed by one specific vowel (low cue uncertainty), another face was equally likely followed by either of two vowels (intermediate cue uncertainty) and the third face was followed by all three vowels (high cue uncertainty). Our results suggest that pupil dilation in response to task‐relevant cues depends on the associated uncertainty, but only for large differences in the cue‐associated uncertainty. Additionally, in response to the auditory outcomes, the pupil dilation scaled negatively with the cue‐dependent probabilities, likely signalling the amount of surprise. [ABSTRACT FROM AUTHOR]

Currently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought‐level maintenance lines are established on the cumulative precipitation‐cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought‐level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought‐level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research. [ABSTRACT FROM AUTHOR]

In vitro dissolution testing is a regulatory required critical quality measure for solid dose pharmaceutical drug products. Setting the acceptance criteria to meet compendial criteria is required for a product to be filed and approved for marketing. Statistical approaches for analyzing dissolution data, setting specifications and visualizing results could vary according to product requirements, company's practices, and scientific judgements. This paper provides a general description of the steps taken in the evaluation and setting of in vitro dissolution specifications at release and on stability. [ABSTRACT FROM AUTHOR]

An attractive feature of using a Bayesian analysis for a clinical trial is that knowledge and uncertainty about the treatment effect is summarized in a posterior probability distribution. Researchers often find probability statements about treatment effects highly intuitive and the fact that this is not accommodated in frequentist inference is a disadvantage. At the same time, the requirement to specify a prior distribution in order to obtain a posterior distribution is sometimes an artificial process that may introduce subjectivity or complexity into the analysis. This paper considers a compromise involving confidence distributions, which are probability distributions that summarize uncertainty about the treatment effect without the need for a prior distribution and in a way that is fully compatible with frequentist inference. The concept of a confidence distribution provides a posterior–like probability distribution that is distinct from, but exists in tandem with, the relative frequency interpretation of probability used in frequentist inference. Although they have been discussed for decades, confidence distributions are not well known among clinical trial statisticians and the goal of this paper is to discuss their use in analyzing treatment effects from randomized trials. As well as providing an introduction to confidence distributions, some illustrative examples relevant to clinical trials are presented, along with various case studies based on real clinical trials. It is recommended that trial statisticians consider presenting confidence distributions for treatment effects when reporting analyses of clinical trials. [ABSTRACT FROM AUTHOR]

Wind energy is now one of the most important alternative sources of renewable energy. The development of wind power generation is a prerequisite to meet environmental and sustainable development requirements while achieving energy security goals. The condition for the effectiveness of the proper operation of a wind power plant is its ability to perform the intended functions, which can be expressed by the coefficient of technical readiness. This article presents an original analysis of the readiness of small wind turbines. As part of the research, an original stochastic operation model was developed based on the application of the Markov process theory. Based on the collected data, a 3‐state phase space of the studied process was identified. Various analyses were carried out to calculate the operating coefficients of wind power plants. The ergodic (boundary) probabilities were calculated using three methods. The conditional probabilities were then determined based on the initial distribution. The resulting readiness factors, not exceeding 30%, indicate the low operational efficiency of the small wind turbines in question. Furthermore, an analysis of the sensitivity of the performance factors was carried out for the analysed objects. [ABSTRACT FROM AUTHOR]

Sequential climate hazards, such as "warm and wet" compound extremes, have direct societal implications for highly urbanized regions and agricultural production. While typically extreme temperatures and rainfall are inversely correlated during the summer, extreme humid heatwaves often lead to atmospheric instability and moisture convection, increasing the likelihood of extreme precipitation (EP). Little is known about how heatwave characteristics, such as peak intensity and duration, influence EP at a regional scale. Using high‐resolution, sub‐daily station‐based observational records over five decades (1971–2021) across India, we find a robust increase in the frequency of compound humid heat‐peak precipitation events in all seasons. Our sensitivity analysis of the impact of humid heatwave characteristics on the subsequent sub‐daily rainfall extremes reveals that, with an increase in peak heatwave intensity for a given heatwave duration, >50% of sites show an increase in the magnitude of rainfall; conversely, with an increase in heatwave duration for a given peak heatwave intensity, around 67% sites show a decline in sub‐daily rainfall extremes. An asymmetrical shift toward above‐average precipitation extremes in response to humid heat stress is mainly clustered around low‐elevation, densely populated coastal areas and the irrigation‐intensive Indo‐Gangetic Plains. Plain Language Summary: Compound humid heatwave‐extreme rainfall events substantially impact society, as the sequential occurrence of such events has immense damage potential due to the limited recovery time compared to the situation where these events occur in isolation. Detecting spatiotemporal patterns in compound hot‐wet weather extremes is essential for disaster management, projecting future changes, and devising an early warning system for vulnerable populations. Using gauge‐based observations of more than five decades across India, we find a robust increase in the number of compound humid heatwave‐extreme precipitation events over climatologically homogeneous regions of India across all seasons. We analyze how the rainfall extremes depend on the characteristics of the preceding heatwave: we find that rainfall extremes increase with increasing heatwave intensity for more than 50% of sites; in contrast, rainfall extremes decrease with increasing heatwave duration for around 67% of sites. A shift toward higher rainfall in response to humid heat characteristics is apparent in densely populated coastal areas and irrigation‐dominated regions of the country. Key Points: We quantify the exceedance probability of sub‐daily rainfall peaks conditioned on preceding heatwavesA significant upward trend in the frequency of compound heatwave‐extreme precipitation events is detected across all seasonsSub‐daily rainfall peaks shows notable changes in their exceedance probability in response to changing heatwave properties [ABSTRACT FROM AUTHOR]

Across a range of decision contexts, we provide evidence of a novel proximity bias in probability judgments, whereby spatial distance and outcome valence systematically interact in determining probability judgments. Six hypothetical and incentive‐compatible experiments (combined N = 4007) show that a positive outcome is estimated as more likely to occur when near than distant, whereas a negative outcome is estimated as less likely to occur when near than distant (studies 1–6). The proximity bias is explained by wishful thinking and thus perceptions of outcome desirability (study 3), and it does not manifest when an outcome is less relevant for the self, such as the case of outcomes with little consequence for the self (studies 4 and 5) or when estimating outcomes for others who are irrelevant to the self (study 6). Overall, the proximity bias we document deepens our understanding of the antecedents of probability judgments. [ABSTRACT FROM AUTHOR]

Intelligence agencies communicate uncertainty to decision‐makers through verbal probability phrases that correspond to numerical ranges (i.e., probability lexicons) and ordinal levels of confidence. However, decision‐makers may misinterpret the relationship between these concepts and form inappropriate interpretations of intelligence analysts' uncertainty. In two experiments, four ways of conveying second‐order probability to decision‐makers were compared: (a) probability and confidence phrases written in the text of a report, (b) the addition of a probability lexicon, (c) the addition of a probability lexicon that varied numerical ranges according to the level of confidence (i.e., revised lexicon), and (d) a probability phrase written in text followed by a numerical range that varied according to the level of confidence. The revised lexicon was expected to improve interpretations of second‐order probability. The 275 participants in Experiment 1 and 796 participants in Experiment 2 provided numerical estimates corresponding to analytic judgments provided in descriptions about three overseas military operations and also indicated their support for approving or delaying the operations. The results demonstrated that providing the numerical range in the text of the report or providing a probability lexicon, improved interpretations of probability phrases above the verbal phrase‐only condition, but not interpretations of confidence. Participants were unable to correctly interpret confidence with respect to the precision of their estimate intervals and their decisions about the operations. However, in Experiments 2 and 3 the effects on these variables of providing decision‐makers with information about the source of the analyst's uncertainty were examined. In Experiment 3 (n = 510), providing this information improved correspondence between confidence level and approval of the operation. Recommendations are provided regarding additional methods of improving decision‐makers' interpretation of second‐order probability conveyed in intelligence reporting. [ABSTRACT FROM AUTHOR]

Accurate detection of spectrum holes is a useful requirement for cognitive radios that improves the efficiency of spectrum usage. The authors propose three novel, simple, and entropy‐based detectors for spectrum sensing in cognitive radio. The authors evaluate the probability of detection of these three detectors: Vasicek's entropy detector, truncated Vasicek's entropy detector, and Van Es' entropy detector, over a predefined probability of false‐alarm. In particular, the authors provide the approximate and asymptotic test statistics for these detectors in the presence and absence of Nakagami‐m fading, noise variance uncertainty, and optimised detection threshold. Furthermore, the authors provide a detailed comparison study among all the detectors via Monte Carlo simulations and justify authors results through real‐world data. The authors' experimental results establish a superior performance of truncated Vasicek's entropy detector over Vasicek's entropy detector, energy detector, differential entropy detector and Van Es' entropy detector in practically viable scenarios. [ABSTRACT FROM AUTHOR]

The simultaneous occurrence of extreme weather events such as high temperature, low humidity and strong wind speed can cause devastating impacts on the fragile environment and vulnerable ecosystem in arid Northwest China (NW). However, few studies investigate the multivariate compound hot, dry and windy extremes in NW. In this study, we investigate the temporal and spatial variations of the warm‐season trivariate hot, dry and windy (HDW) and bivariate hot and dry (HD), dry and windy (DW), hot and windy (HW) extremes in NW. From 1960 to 2019, we observed more compound HD, DW, HW and HDW days in the hyper‐arid Xinjiang and west Gansu in NW. Simultaneously, DW days, HW days and HDW days consistently declined at rates of −0.48, −0.88 and −0.42 day·10a−1, except for a discernible increasing rate of 0.56 day·10a−1 in HD days. Notably, trends in four multivariate compound extremes all experienced pronounced reversals from a declining to increasing trend in the 1990s. The higher probability of compound HD, DW and HW extremes contributed to a higher probability of HDW in Xinjiang province. Ultimately driven by the significantly rising temperature (0.21°C·10a−1, p < 0.01), four compound extremes suggested increased probability with the largest increase in compound HW probability from 1960–1989 to 1990–2019. Both the rising trends in the occurrence and the increased probability of four compound extremes highlight intense risks of compound extreme weather over NW in recent decades. [ABSTRACT FROM AUTHOR]

This paper proposes a method based on scenario optimization and meta‐heuristic algorithm to optimize the power system stabilizers (PSSs) for enhancement of small‐signal stability (SSS) considering power system uncertainties such as photovoltaic generation, wind turbine generation, and load. The proposed method consists of two stages. In the first stage, the uncertainties are modeled using probability functions and scenarios are created based on them. These scenarios are then used to obtain a joint probability where the most likely probabilities are chosen for the second stage. The second stage utilizes these critical scenarios to formulate an optimization problem. The objective function of the optimization problem is to enhance system's small signal stability margin with PSS parameters as constraints. The proposed method is then solved using a new meta‐heuristic optimization algorithm known as Jelly Search Optimizer to obtain the optimized parameter of PSSs. The proposed method is tested on a two‐area and five‐area system, and the results show that the system SSS margin is improved for the majority of uncertainty situations. Moreover, the proposed method is around 1.6 times faster compared to the conventional probability method when tested in the modified two‐area system while 5.7 times faster when tested in the modified five‐area system. [ABSTRACT FROM AUTHOR]

We define confidence to be epistemic if it applies to an observed confidence interval. Epistemic confidence is unavailable—or even denied—in orthodox frequentist inference, as the confidence level is understood to apply to the procedure. Yet there are obvious practical and psychological needs to think about the uncertainty in the observed interval. We extend the Dutch Book argument used in the classical Bayesian justification of subjective probability to a stronger market‐based version, which prevents external agents from exploiting unused information in any relevant subset. We previously showed that confidence is an extended likelihood, and the likelihood principle states that the likelihood contains all the information in the data, hence leaving no relevant subset. Intuitively, this implies that confidence associated with the full likelihood is protected from the Dutch Book, and hence is epistemic. Our goal is to validate this intuitive notion through theoretical backing and practical illustrations. [ABSTRACT FROM AUTHOR]

The historical route travel time data contain a few outliers composed of subpopulations signifying unusual traffic conditions. These outliers compose the right tail of the distribution against the central part occupied by most normal travel times dominating usual traffic conditions likely to be composed of subpopulations. The diverse subpopulations of two types of travel times result in the structural random changes of distribution shapes. This creates the problem for fixing the boundary between the two types of travel times. To address the problem, an adaptive Gaussian mixture model was formulated with two types of components, and an algorithm was put forward to determine the critical number of components in an iterative manner by adapting two types of components to provide an adequate fit to the two parts of the distribution respectively. The determined two types of components can not only fix the boundary to identify outliers reasonably, but also quantify the latent subpopulations of two types of route travel times. Thus, the route‐level travel time variability can be measured under usual/unusual traffic conditions. Two kinds of data were used to illustrate the good effects on the identification of outliers and to demonstrate the vital role of outliers in the measure of variation of route travel time. [ABSTRACT FROM AUTHOR]

In this letter, the authors present a novel expression for the probability of line‐of‐sight (LoS) between a UAV and ground users situated on a gridded street within urban and dense urban environments. Firstly, this study conducts extensive ray‐tracing simulations, encompassing over 50,000 receivers positioned along streets in Brooklyn and Manhattan, respectively. Moreover, the impact of street width on the probability of LoS is investigated, considering three different average widths. By fitting the LoS probability data corresponding to the UAV's elevation angle in two urban environments obtained by simulations, a unified expression representing the relationship between the LoS probability and the UAV's elevation angle is obtained. This obtained LoS probability expression is compared with three existing expressions. The findings presented in this letter can provide some valuable insights for analytical studies on channel modelling between UAVs and ground‐based street users including vehicles. [ABSTRACT FROM AUTHOR]

This paper investigates intelligent reconfigurable surface‐assisted non‐orthogonal multiple access (NOMA) networks for short packet communications where the source with multiple antennas utilizes beamforming technology to serve two end users including a near user and a far user. The analysis system, closed‐form expressions of the average block error rates (BLERs), latency and reliability at all users are derived under assuming perfect channel state information over quasi‐static Rayleigh fading channels. For evaluating the improvement of the network system, a deep neural network (DNN) framework is designed to predict the performance parameters in two cases: (i) BLERs prediction of the users, (ii) transmit power allocation under the constraints of BLERs at each user which satisfy the extremely high reliability requirements of uRLLCs. The extensive results demonstrate that first, the DNN‐based estimation results are more accurate than Monte‐Carlo simulation results with low execution time. Second, the allocated power for each user can be accurately predicted at the high layers. Finally, two methods of evaluating the effectiveness of the DNN model, i.e. root mean square error and mean absolute percentage error, reach low error which verify the power of the designed DNN model for future analysis. [ABSTRACT FROM AUTHOR]

Coal spontaneous combustion is determined by a variety of factors. Testing can describe the changes incoal spontaneous combustion with various factors, however, the dependence of spontaneous combustion on various factors is unclear. Therefore, reliability theory was used to deduce the functional relationship of the dependence of coal spontaneous combustion on various factors, and construct a model algorithm for predicting the probability of occurrence of coal spontaneous combustion, which is adopted to evaluate and rank the degree of influence of various factors on coal spontaneous combustion. Effective prevention methods are proposed by strengthening the role of the most important factors. The results show that, by taking the duration of coal heating to 150°C as the measurement standard of coal spontaneous combustion, the duration of the initial stage of coal heating increases linearly with the increase of specific heat capacity, thermal conductivity, and moisture content of coal. With the increase of oxygen concentration, oxidation rate, and initial temperature of the coal, the duration of the initial stage of coal heating decreases exponentially. With the increase of gas flow seepage velocity in the coal body, the duration of the initial heating stage changes in a parabolic manner. At the same time, the probability of spontaneous combustion decreases exponentially with the increase of specific heat capacity and moisture content of the coal. The probability of coal spontaneous combustion increases linearly with the increase of coal thermal conductivity, oxygen concentration, gas seepage velocity, and rate of oxidation. The dependence of coal spontaneous combustion probability on different factors can be expressed as follows: coal temperature > gas seepage velocity > specific heat capacity > oxidation rate > oxygen concentration > moisture content > thermal conductivity. [ABSTRACT FROM AUTHOR]

Certain kinds of prediction, foreknowledge, and future‐oriented action appear to require settled future truths. But open futurists think that the future is metaphysically unsettled: if it is open whether p is true, then it cannot currently be settled that p is true. So, open futurists—and libertarians who adopt the position—face the objection that their view makes rational action and deliberation impossible. I defuse the epistemic concern: open futurism does not entail obviously counterintuitive epistemic consequences or prevent rational action. [ABSTRACT FROM AUTHOR]

How safe are our structures? – Conceptual paper of the DGGT Working Group 2.15 "Reliability‐Based Methods in Geotechnical Engineering" The future Eurocode 7 will explicitly allow the use of reliability‐based methods in geotechnical planning and design. In Germany, there is hardly any experience in the practical application of such methods so far and thus the reservations towards these methods are plenty. The new DGGT Working Group (WG) 2.15 "Reliability‐Based Methods in Geotechnical Engineering" has set itself the goal of providing a practical access to those methods by means of practice‐oriented instructions and recommendations as well as accompanying training and further education courses. The aim is to clarify the possibilities and limitations and, above all, to exploit their potential. This article presents the general principles as well as the future fields of work of the WG 2.15. Starting with the introduction of relevant technical terms, the implementation of reliability‐based methods within the current codes of practice and regulations is shown. Using the life cycle of a geotechnical structure, the uncertainties in geotechnical designs and assessments are described. Subsequently it is outlined, in which situations and to what extend reliability‐based methods can aid engineers, clients and inspectors in verification and decision‐making processes. In the future, WG 2.15 will develop recommendations on individual topics and publish them successively. [ABSTRACT FROM AUTHOR]

Orientation estimation is one of the core problems in several computer vision tasks. Recently deep learning techniques combined with the Bingham distribution have attracted considerable interest towards this problem when considering ambiguities and rotational symmetries of objects. However, existing works suffer from two issues. First, the computational overhead for calculating the normalisation constant of the Bingham distribution is relatively high. Second, the choice of loss functions is uncertain. In light of these problems, we present an online deep Bingham network to estimate the orientation of objects. We sharply reduce the computational overhead of the normalisation constant by directly applying a numerical integration formula. Additionally, we are the first to give theorems on the convexity and Lipschitz continuity of the Bingham distribution's negative log‐likelihood, which formally indicates that it is a proper choice of the loss function. We test our method on three public datasets, namely the UPNA, the T‐LESS and Pascal3D+, showing that our method outperforms the state‐of‐the‐art in terms of orientation accuracy and time efficiency, which can reduce the runtime by more than 6 h compared to the offline methods. The ablation experiments further demonstrate the effectiveness and robustness of our model. [ABSTRACT FROM AUTHOR]

We develop a statistical approach to model handwriting that accommodates all styles of writing (cursive, print, connected print). The goal is to compute a posterior probability of writership of a questioned document given a closed set of candidate writers. Such probabilistic statements can support examiner conclusions and enable a quantitative forensic evaluation of handwritten documents. Writing is treated as a sequence of disjoint graphical structures, which are extracted using an automated and open‐source process. The graphs are grouped based on the similarity of their shapes through a K‐means clustering template. A person's writing pattern can be characterized by the rate at which graphs are emitted to each cluster. The cluster memberships serve as data for a Bayesian hierarchical model with a mixture component. The rate of mixing between two parameters in the hierarchy indicates writing style. [ABSTRACT FROM AUTHOR]

Research suggests that moral evaluations change during adulthood. Older adults (75+) tend to judge accidentally harmful acts more severely than younger adults do, and this age‐related difference is in part due to the greater negligence older adults attribute to the accidental harmdoers. Across two studies (N = 254), we find support for this claim and report the novel discovery that older adults' increased attribution of negligence, in turn, is associated with a higher perceived likelihood that the accident would occur. We propose that, because older adults perceive accidents as more likely than younger adults do, they condemn the agents and their actions more and even infer that the agents' omission to exercise due care is intentional. These findings refine our understanding of the cognitive processes underpinning moral judgment in older adulthood and highlight the role of subjective probability judgments in negligence attribution. [ABSTRACT FROM AUTHOR]

Steep delay and shallow probability discounting are associated with myriad problem behaviors; thus, it is important to understand factors that influence the degree of discounting. The present study evaluated the effects of economic context and reward amount on delay and probability discounting. Two hundred thirteen undergraduate psychology students completed four delay‐ or probability‐discounting tasks. Participants were exposed to hypothetical narratives involving four bank amounts ($750, $12,000, $125,000, and $2,000,000). The delayed/probabilistic amount was $3,000 for the two smaller bank amounts and $500,000 for the two larger bank amounts. The discounting tasks included five delays to, or probabilities of, receipt of the larger amount. The area under the empirical discounting function was calculated for each participant. Participants discounted delayed and uncertain outcomes more when the bank amount was smaller than the outcome (i.e., the economic context was low). Participants discounted the delayed larger amounts less than delayed smaller amounts, even when the relative economic context was the same. In contrast, probability discounting did not differ across magnitudes, which suggests that economic context may attenuate the magnitude effect in probability discounting. The results further highlight the importance of considering the economic context in delay and probability discounting. [ABSTRACT FROM AUTHOR]

This paper investigates a multiple users cooperative cognitive non‐orthogonal multiple access (NOMA) network with energy harvesting. Primary transmitter and secondary sources serving as energy‐constrained nodes harvest energy from the power beacon PBS. In primary network, primary transmitter sends signals towards primary receiver. In order to make full use of spectrum resources, the secondary network access the licensed spectrum of primary network with overlay mode, where the best secondary source with maximum transmission signal‐to‐noise ratio between primary transmitter and secondary sources act as relays to forward signal via NOMA principle. In this context, two cooperative transmission protocols, namely, traditional NOMA cooperative transmission and adaptive NOMA cooperative transmission are proposed. For NOMA cooperative transmission, relays use NOMA to forward the superimposed signal of primary signal and secondary signal without any constrain. However, for adaptive NOMA cooperative transmission, relays use NOMA by judging whether the transmission between primary transmitter and primary receiver is successful or not. Primary receiver merges signals received from two transmission slots by selection combining. Finally, exact and asymptotic outage probability of primary network and secondary network with two cooperative transmissions are derived and simulated. It is shown that outage performance is improved for the proposed adaptive NOMA cooperative transmission. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model and the relevant computer code are developed to quantify the extraction probability rate of charge carriers (EPRCC) in a perovskite solar cell of the structure: Glass/ITO/PEDOT: PSS/CH3NH3PbI3/PC60BM/Al to investigate the influence of interfaces and grain boundaries. It is found that, without passivation, the probability of an electron generated near the anode reaches to the cathode is only 35%, while by passivating the interfaces and grain boundaries, this probability increases to about 60% at maximum power point condition. Likewise, without passivation, the probability of a hole generated near the electron transport layer‐active layer interface reaches to the hole transport layer is only 15%, while by passivating the interfaces and grain boundaries, this probability increases to about 45% at maximum power point condition. The same calculation has been done at the short‐circuit current condition, and it is found that at the maximum power point condition, passivation works better for increasing the EPRCC than at the short circuit current condition. The authors have also investigated the influence of grain boundary sizes on the EPRCC, and the results show that the EPRCC is almost grain boundary size independent. [ABSTRACT FROM AUTHOR]

Organizations in several domains including national security intelligence communicate judgments under uncertainty using verbal probabilities (e.g., likely) instead of numeric probabilities (e.g., 75% chance), despite research indicating that the former have variable meanings across individuals. In the intelligence domain, uncertainty is also communicated using terms such as low, moderate, or high to describe the analyst's confidence level. However, little research has examined how intelligence professionals interpret these terms and whether they prefer them to numeric uncertainty quantifiers. In two experiments (N = 481 and 624, respectively), uncertainty communication preferences of expert (n = 41 intelligence analysts in Experiment 1) and nonexpert intelligence consumers were elicited. We examined which format participants judged to be more informative and simpler to process. We further tested whether participants treated verbal probability and confidence terms as independent constructs and whether participants provided coherent numeric probability translations of verbal probabilities. Results showed that although most nonexperts favored the numeric format, experts were about equally split, and most participants in both samples regarded the numeric format as more informative. Experts and nonexperts consistently conflated probability and confidence. For instance, confidence intervals inferred from verbal confidence terms had a greater effect on the location of the estimate than the width of the estimate, contrary to normative expectation. Approximately one‐fourth of experts and over one‐half of nonexperts provided incoherent numeric probability translations for the terms likely and unlikely when the elicitation of best estimates and lower and upper bounds were briefly spaced by intervening tasks. [ABSTRACT FROM AUTHOR]

A negative effect of hydropower on river environment includes rapid changes in flow and habitat conditions. Any sudden flow change could force fish to move towards a refuge area in a short period of time, causing serious disturbances in the life cycle of the fish. A probability‐based model was developed to quantify the impact of hydropeaking on habitat suitability for two fish species, brown trout (Salamo trutta) and Grayling (Thymallus thymallus). The model used habitat preference curves, river velocity and depth to develop the suitability maps. The suitability maps reveal that habitat suitability deteriorates as flow increases in the studied part of the river. The probability model showed that, on average, suitability indices are higher for adult grayling than juvenile trout in hydropeaking events in this part of the river. The method developed shows the potential to be used in river management and the evaluation of hydropeaking impacts in river systems affected by hydropower. [ABSTRACT FROM AUTHOR]

Reduced mismatch negativity (MMN), a robust finding in schizophrenia, has prompted interest in MMN as a preclinical biomarker of schizophrenia. The rat brain can generate human‐like mismatch responses (MMRs) which therefore enables the exploration of the neurobiology of reduced MMRs. Given epidemiological evidence that two developmental factors, maternal infection and adolescent cannabis use, increase the risk of schizophrenia, we determined the effect of these two developmental risk factors on rat MMR amplitude in different auditory contexts. MMRs were assessed in awake adult male and female Wistar rats that were offspring of pregnant dams treated with either a viral infection mimetic (poly I:C) inducing maternal immune activation (MIA) or saline control. In adolescence, subgroups of the prenatal treatment groups were exposed to either a synthetic cannabinoid (adolescent cannabinoid exposure: ACE) or vehicle. The context under which MMRs were obtained was manipulated by employing two different oddball paradigms, one that manipulated the physical difference between rare and common auditory stimuli, and another that manipulated the probability of the rare stimulus. The design of the multiple stimulus sequences across the two paradigms also allowed an investigation of context on MMRs to two identical stimulus sequences. Male offspring exposed to each of the risk factors for schizophrenia (MIA, ACE or both) showed a reduction in MMR, which was evident only in the probability paradigm, with no effects seen in the physical difference. Our findings highlight the importance of contextual factors induced by paradigm manipulations and sex for modeling schizophrenia‐like MMN impairments in rats. Our findings demonstrate a schizophrenia‐like reduction in the size of the mismatch responses in a developmental risk factor rat model, a novel finding as the previous research have shown similar effects in pharmacologically manipulated animal models only. The current results underscore the importance of paradigm in utilizing the mismatch negativity as a biomarker for schizophrenia in future studies. [ABSTRACT FROM AUTHOR]

This paper uses actual data on horse racing to illustrate probabilities, odds, and expected values, and offers cautionary remarks about applying textbook formulas to gambling on real‐world sporting events. [ABSTRACT FROM AUTHOR]

Introduction: MODY probability calculator (MPC) represents an easy‐to‐use tool developed by Exeter University to help clinicians prioritize which individuals should be oriented to genetic testing. We aimed to assess the utility of MPC in a Portuguese cohort with early‐onset monogenic diabetes. Methods: This single‐centre retrospective study enrolled 132 participants submitted to genetic testing between 2015 and 2020. Automatic sequencing and, in case of initial negative results, generation sequencing were performed. MODY probability was calculated using the probability calculator available online. Positive and negative predictive values (PPV and NPV, respectively), accuracy, sensitivity and specificity of the calculator were determined for this cohort. Results: Seventy‐three individuals were included according to inclusion criteria: 20 glucokinase (GCK‐MODY); 16 hepatocyte nuclear factor 1A (HNF1A‐MODY); 2 hepatocyte nuclear factor 4A (HNF4A‐MODY) and 35 DM individuals with no monogenic mutations found. The median probability score of MODY was significantly higher in monogenic diabetes‐positive subgroup (75.5% vs. 24.2%, p <.001). The discriminative accuracy of the calculator, as expressed by area under the curve, was 75% (95% CI: 64%–85%). In our cohort, the best cut‐off value for the MODY calculator was found to be 36%, with a PPV of 74.4%, NPV of 73.5% and corresponding sensitivity and specificity of 76.2% and 71.4%, respectively. Conclusions: In a highly pre‐selected group of probands qualified for genetic testing, the Exeter MODY probability calculator provided a useful tool in individuals' selection for genetic testing, with good discrimination ability under an optimal probability cut‐off of 36%. Further geographical and population adjustments are warranted for general use. [ABSTRACT FROM AUTHOR]

Summary: Energy consumption in wireless sensor network (WSN) is one of the important issues as tiny sensor nodes are equipped with a non‐replaceable batteries. Clustering is one of the effective means to prolong the network lifetime in WSN by reducing the number of packets to be sent from cluster heads (CHs) to base station (BS). Recently, game theory techniques have been applied in the clustering process for optimal CH election at each round. However, none of them have considered the energy parameter in their game strategy and multihop routing for data transmission. In this manuscript, an energy‐efficient game‐theoretic clustering and multi‐hop routing scheme (EGCR) has been proposed where the non‐cooperative approach of game theory is used to elect optimal CHs. In the proposed game theoretic framework, each node behaves in a selfish manner while considering the residual energy of nodes and focuses on increasing the overall lifetime of the network. Nash equilibrium is determined among a set of pure and mixed strategies, and then the expected payoff of a node is determined for Nash equilibria. Apart from the energy‐efficient clustering, the EGCR also proposes a multi‐hop routing solution for data transmission that further enhances the lifetime of whole network. In the multi‐hop routing approach, inter‐cluster and intra‐cluster routing techniques are proposed to identify optimal routes from nodes to CHs and from CHs to BS by using various factors such as node centrality, distance from the node to BS, and residual energy. The proposed algorithm is compared with traditional clustering schemes like low‐energy adaptive clustering hierarchy (LEACH) and efficient energy‐aware game theory‐based clustering (EEGC) and also with existing game theory‐based algorithms such as clustered routing for selfish sensors (CROSS), localized game theoretical clustering algorithm (LGCA), and energy‐efficient clustering algorithm based on game theory (ECAGT). Simulation experiments validate that the proposed algorithm enhances the network's lifetime up to 47.49% compared to existing clustering algorithms. [ABSTRACT FROM AUTHOR]

People often face the challenge of evaluating competing explanations. One approach is to assess the explanations' relative probabilities–for example, applying Bayesian inference to compute their posterior probabilities. Another approach is to consider an explanation's qualities or "virtues," such as its relative simplicity (i.e., the number of unexplained causes it invokes). The current work investigates how these two approaches are related. Study 1 found that simplicity is used to infer the inputs to Bayesian inference (explanations' priors and likelihoods). Studies 1 and 2 found that simplicity is also used as a direct cue to the outputs of Bayesian inference (the posterior probability of an explanation), such that simplicity affects estimates of posterior probability even after controlling for elicited (Study 1) or provided (Study 2) priors and likelihoods, with simplicity having a larger effect in Study 1, where posteriors are more uncertain and difficult to compute. Comparing Studies 1 and 2 also suggested that simplicity plays additional roles unrelated to approximating probabilities, as reflected in simplicity's effect on how "satisfying" (vs. probable) an explanation is, which remained largely unaffected by the difficulty of computing posteriors. Together, these results suggest that the virtue of simplicity is used in multiple ways to approximate probabilities (i.e., serving as a cue to priors, likelihoods, and posteriors) when these probabilities are otherwise uncertain or difficult to compute, but that the influence of simplicity also goes beyond these roles. [ABSTRACT FROM AUTHOR]

Predictions of time (e.g., work hours) are often based on the aggregation of estimates of elements (e.g., activities and subtasks). The only types of estimates that can be safely aggregated by summation are those reflecting predicted average outcomes (expected values). The sums of other types of estimates, such as bounds of confidence intervals or estimates of the mode, do not have the same interpretation as their components (e.g., the sum of the 90% upper bounds is not the appropriate 90% upper bound of the sum). The present research shows that this can be a potential source of bias in predictions of time. In Studies 1 and 2, professionals with experience in estimation provided total estimates of time that were inconsistent with their estimates of individual tasks. Study 3 shows that this inconsistency can be attributed to improper aggregation of time estimates and demonstrates how this can produce both overestimation and underestimation—and also confidence intervals that are far too wide. Study 4 suggests that the results may reflect a more general fallacy in the aggregation of probabilistic quantities. The inconsistencies and biases appear to be largely driven by a tendency to naïvely sum (2 + 2 = 4) probabilistic (stochastic) values. This summation fallacy may be consequential in contexts where informal estimation methods (expert judgment) are used. [ABSTRACT FROM AUTHOR]

Background: Social anxiety (SA) is characterized by concerns about the expected occurrence (probability) and anticipated distress (cost) of social threats. Unclear is whether SA correlates specifically with biased expectations of belongingness or status threats., Aims: We aimed to discern if SA is uniquely tied to biased expectancies of either belongingness or status threats., Materials and Methods: We assessed 757 participants' perceptions of exclusion and put-down scenarios, analysing associations between SA and threat perceptions., Discussion: Our findings support the status-sensitivity hypothesis, suggesting individuals with high SA are particularly attuned to the perceived cost of status threats, potentially informing treatment approaches., Conclusion: Understanding SA's link to status concerns enhances therapeutic strategies, emphasizing the need to address status-related situations, cognitions, and emotions in interventions., (© 2024 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Background and Objectives: Probability discounting (PD), which refers to the process of adjusting the value of future probabilities when making decisions, is a method of measuring impulsive decision-making; however, the relationship between PD and nicotine remains unclear. The current study aimed at investigating the significance of PD in individuals who smoke., Methods: According to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched the PubMed, Embase, PsycINFO, and Web of Science databases for articles comparing individuals who smoke and their tobacco-naïve controls using PD task as outcome measure from inception to May 2023. The main outcome was an overall difference in PD function, while subgroup analysis and meta-regression were conducted to examine the analysis methods and the moderators of PD., Results: Fourteen studies in total involving 384 individuals who smoke and 493 controls (mean age = 24.32 years, range = 15.1-38.05 years) were analyzed. The effect of smoking on PD was significant (g = 0.51, p = .02). The discounting parameter from the equation, compared to the area under the curve, was more sensitive to estimating PD function (p = .01). Regression analysis showed positive correlations of PD with female percentage, age, and the number of probability options (all p < .04), but not with the number of choices at each probability and maximum reward magnitude (all p > .07). There was no significant publication bias across the eligible studies (p = .09)., Conclusion and Scientific Significance: Our findings, which are the first to demonstrate a smaller PD (i.e., prone to risk-taking) in individuals who smoke, shed light on the appropriate analysis method, gender effect, age, and probability options on the PD function., (© 2024 The American Academy of Addiction Psychiatry (AAAP).)

It is more and more important to analyse and process complex data for gaining more valuable knowledge and making more accurate decisions. The multigranulation decision theory based on conditional probability and cost loss has the advantage of processing decision‐making problems from multi‐levels and multi‐angles, and the neighbourhood rough set model (NRS) can facilitate the analysis and processing of numerical or mixed type data, and can address the limitation of multigranulation decision‐theoretic rough sets (MG‐DTRS), which is not easy to cope with complex data. Based on the in‐depth study of hybrid‐valued decision systems and MG‐DTRS models, this study analysed neighbourhood MG‐DTRS (NMG‐DTRS) deeply by fusing MG‐DTRS and NRS; a matrix‐based approach for approximation sets of NMG‐DTRS model was proposed on the basis of the matrix representations of concepts; the positive, boundary and negative domains were constructed from the matrix perspective, and the concept of positive decision recognition rate was introduced. Furthermore, the authors explored the related properties of NMG‐DTRS model, and designed and described the corresponding solving algorithms in detail. Finally, some experimental results that were employed not only verified the effectiveness and feasibility of the proposed algorithm, but also showed the relationship between the decision recognition rate and the granularity and threshold. [ABSTRACT FROM AUTHOR]

Background: The duration of beta‐blocker therapy in patients without heart failure (HF) or left ventricular systolic dysfunction after acute myocardial infarction (AMI) is unclear. Hypothesis: Continuous beta‐blocker therapy is associated with an improved prognosis. Methods: This is a prospective, multicenter, cohort study. One thousand four hundred and eighty‐three patients eventually met the inclusion criteria. The study groups included the continuous beta‐blocker therapy group (lasted ≥6 months) and the discontinuous beta‐blocker therapy group (consisting of the no‐beta‐blocker therapy group and the beta‐blocker therapy <6 months group). The inverse probability treatment weighting was used to control confounding factors. The study tried to learn the role of continuous beta‐blocker therapy on outcomes. The median duration of follow‐up was 13.0 months. The primary outcomes were cardiac death and major adverse cardiovascular events (MACE). The secondary outcomes were all‐cause death, stroke, unstable angina, rehospitalization for HF, and recurrent myocardial infarction (MI). Results: Compared with discontinuous beta‐blocker therapy, continuous beta‐blocker therapy was associated with a reduced risk of unstable angina, recurrent MI, and MACE (hazard ratio [HR]: 0.51; 95% CI: 0.32–0.82; p = 0.006); but this association was not available for cardiac death (HR: 0.57; 95% CI: 0.24–1.36; p = 0.206). When compared to the subgroups of no‐beta‐blocker therapy and beta‐blocker therapy <6 months, respectively, continuous beta‐blocker therapy was still observed to be associated with a reduced risk of unstable angina, recurrent MI, and MACE. Conclusions: Continuous beta‐blocker therapy was associated with a reduced risk of unstable angina or recurrent MI or MACE in patients without HF or left ventricular systolic dysfunction after AMI. [ABSTRACT FROM AUTHOR]

Risk matrices are a common way to communicate the likelihood and potential impacts of a variety of risks. Until now, there has been little empirical work on their effectiveness in supporting understanding and decision making, and on how different design choices affect these. In this pair of online experiments (total n = 2699), we show that risk matrices are not always superior to text for the presentation of risk information, and that a nonlinear/geometric labeling scheme helps matrix comprehension (when the likelihood/impact scales are nonlinear). To a lesser degree, results suggested that changing the shape of the matrix so that cells increase in size nonlinearly facilitates comprehension as compared to text alone, and that comprehension might be enhanced by integrating further details about the likelihood and impact onto the axes of the matrix rather than putting them in a separate key. These changes did not affect participants' preference for reducing impact over reducing likelihood when making decisions about risk mitigation. We recommend that designers of risk matrices consider these changes to facilitate better understanding of relationships among risks. [ABSTRACT FROM AUTHOR]

Can perceptual experiences be states of uncertainty? We might expect them to be, if the perceptual processes from which they are generated, and the behaviors they help produce, take account of probabilistic information. Yet, it has long been presumed that perceptual experiences purport to tell us about our environment, without hedging or qualifying. Against this long‐standing view, I argue that perceptual experiences may well occasionally be states of uncertainty, but that they are never probabilistically structured. I criticize a powerful line of reasoning that we should expect perceptual experience to be probabilistic, given their interfaces with unconscious probabilistic information, with behavior responsive to it, and with credences. [ABSTRACT FROM AUTHOR]

Graphics, uncertainty, and semantics are three approaches to building models. The combination of the three approaches is a way to develop a stronger modeling method. This article surveys the research efforts toward combining these aspects, which can be divided into two routes: One is to combine graphics and uncertainty as probabilistic graphical models and then incorporate semantics, and the other is to combine graphics and semantics and then incorporate probability to handle uncertainty. The models and methods involved in these efforts are introduced and their expressiveness, pros, and cons are discussed. [ABSTRACT FROM AUTHOR]

Chances are that edutainment fun items can engage students in discussing and learning key concepts about probability. [ABSTRACT FROM AUTHOR]

Objectives: Population‐level measures of seropositivity are critical for understanding the epidemiology of an emerging pathogen, yet most antibody tests apply a strict cutoff for seropositivity that is not learnt in a data‐driven manner, leading to uncertainty when classifying low‐titer responses. To improve upon this, we evaluated cutoff‐independent methods for their ability to assign likelihood of SARS‐CoV‐2 seropositivity to individual samples. Methods: Using robust ELISAs based on SARS‐CoV‐2 spike (S) and the receptor‐binding domain (RBD), we profiled antibody responses in a group of SARS‐CoV‐2 PCR+ individuals (n = 138). Using these data, we trained probabilistic learners to assign likelihood of seropositivity to test samples of unknown serostatus (n = 5100), identifying a support vector machines‐linear discriminant analysis learner (SVM‐LDA) suited for this purpose. Results: In the training data from confirmed ancestral SARS‐CoV‐2 infections, 99% of participants had detectable anti‐S and ‐RBD IgG in the circulation, with titers differing > 1000‐fold between persons. In data of otherwise healthy individuals, 7.2% (n = 367) of samples were of uncertain serostatus, with values in the range of 3‐6SD from the mean of pre‐pandemic negative controls (n = 595). In contrast, SVM‐LDA classified 6.4% (n = 328) of test samples as having a high likelihood (> 99% chance) of past infection, 4.5% (n = 230) to have a 50–99% likelihood, and 4.0% (n = 203) to have a 10–49% likelihood. As different probabilistic approaches were more consistent with each other than conventional SD‐based methods, such tools allow for more statistically‐sound seropositivity estimates in large cohorts. Conclusion: Probabilistic antibody testing frameworks can improve seropositivity estimates in populations with large titer variability. [ABSTRACT FROM AUTHOR]

Emerging parametric insurance products targeted at regional governments consider an index of flooding as the instrument for payoff and rate setting. Inundation extent from satellite remote sensing may provide a more direct measure of flood risk in this context than hydraulic modeling of flow and inundation. Here, we examine satellite‐based fractional inundated area as a proxy for flood impact that can be used for index insurance payment at a regional scale. Typical methods for estimating return periods from unbounded distributions such as the Generalized Extreme Value distribution are not appropriate for fractional flooded area, which is bounded by 0 and 1. Here we examine alternative bounded distributions (2 parameter and a 4 parameter Beta) to estimate return periods and quantify uncertainty using a bootstrap sampling procedure for the short duration satellite record of fractional flooded area. We consider two examples with distinct flood dynamics (a) a country (Bangladesh) where a flood can cover the majority of the land surface, and (b) a river basin (the Rio Salado basin in Argentina) where the worst flood covered only a modest fraction of the watershed. We explore how a parametric insurance policy based on fractional flooded area could be priced based on a typical approach used in the industry, that accounts for uncertainty for small sample estimation. Our exploratory approach to model selection illustrates how estimating the uncertainty price influences insurance contract pricing and is important to consider the choice of distribution beyond just the traditional measures of goodness of fit. Plain Language Summary: Index insurance, catastrophe bonds, and other types of risk transfer instruments could play an important role in adapting to floods and ensuring sustainable development in a world of increasing flood risk. In this article, we examine how satellite time series of inundation can be used to develop an emerging type of flood insurance, known as parametric or index‐based insurance. Unlike traditional indemnity insurance, which relies on adjusters to estimate loss for individual damage, index insurance uses data ex‐ante to determine payout contracts when pre‐specified thresholds are crossed. Inundation extent from satellite remote sensing may provide a more direct measure of flood risk than data from models or stream gauges. However, typical methods used to estimate return periods for floods from models and gauges are not appropriate for fractional inundated area measurements from satellites. Here we provide a more appropriate method to estimate return periods and quantify uncertainty to price an insurance product leveraging the relatively short satellite record. Example applications for Bangladesh and Rio Salado, Argentina are provided. We show why estimating and pricing uncertainty ultimately influences insurance contract pricing and can help governments select insurance policies that align with their flood adaptation strategy. Key Points: Estimating return periods for fractional inundated area with the oft‐used Generalized Extreme Value distribution is inappropriateBounded distributions (e.g., Beta) reduce uncertainty estimates for probability of exceedance from short duration inundation time seriesExample design and price of parametric flood insurance with fractional inundated area in Bangladesh and Argentina accounting for uncertainty [ABSTRACT FROM AUTHOR]