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I.J. Good's "On the Principle of Total Evidence" (1967) looms large in decision theory and Bayesian epistemology. Good proves that in Savage 's (1954) decision theory, a coherent agent always prefers to collect, rather than ignore, free evidence. It is now well known that Good's result was prefigured in an unpublished note by Frank Ramsey (Skyrms 2006). The present paper highlights another early forerunner to Good's argument, appearing in Janina Hosiasson's "Why do We Prefer Probabilities Relative to Many Data?" (1931), that has been neglected in the literature. Section 1 reviews Good's argument and the problem it was meant to resolve; call this the value of evidence problem. Section 2 offers a brief history of the value of evidence problem and provides biographical background to contextualize Hosiasson's contribution. Section 3 explicates the central argument of Hosiasson's paper and considers its relationship to Good's (1967). [ABSTRACT FROM AUTHOR]

The 2019 European Society of Cardiology (ESC) guidelines proposed a pre-test probability (PTP) model to determine the likelihood of coronary artery disease (CAD). However, the prediction accuracy of this model has not yet been evaluated in Chinese populations. This study aimed to validate the 2019 ESC-PTP model in predicting CAD using coronary computed tomography angiography (CCTA) outcomes in a Chinese population. A total of 26,346 consecutive patients with suspected CAD who underwent CCTA were included. The 2019 ESC-PTP model and 2013 ESC-PTP model were calculated for each patient, considering age, sex, and the symptom of chest pain, and the patients were categorized into low-, intermediate-, and high-risk groups. The predictive performance of the 2019 ESC-PTP model was evaluated by comparing it with the 2013 ESC-PTP model and the observed prevalence of CAD from CCTA. Among the 11,234 patients analyzed in the study, 1896 (16.9%) patients were found to have obstructive CAD from CCTA. The 2019 ESC-PTP model had better calibration compared to the 2013 ESC-PTP model. After categorization, 80.9% of patients (67.9% in men and 94.4% in women) were in the same risk category as in the 2019 ESC-PTP model, but the risks of younger patients (7.5% versus 2.5%; P ​< ​0.001) and patients with non-anginal chest pain (13.7% versus 8.2%; P ​< ​0.001) were underestimated in the 2019 ESC-PTP model. The 2019 ESC-PTP model demonstrated a good calibration in predicting CAD in a Chinese population who underwent CCTA, but it exhibited an underestimation of CAD probability in younger patients and patients with non-anginal chest pain. [ABSTRACT FROM AUTHOR]

• Ultrasound and d- dimer were integrated for diagnosis of acute aortic syndromes. • The protocol allowed rapid triage for urgent computed tomography angiography. • Protocol based rule-out was safe since no major events were missed within 30 days. • The protocol averted 41 % of computed tomography angiography exams. • Age-adjusted interpretation of d -dimer maximized protocol efficiency. In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting. We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d- dimer (single/age-adjusted cutoff), to select patients for AAI. This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d -dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes. Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0–0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46–50 %) and AAI was averted in 41 % of patients. Using age-adjusted d -dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4–9 %, vs standard cutoff). The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d -dimer maximized efficiency. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov, NCT04430400 [Display omitted] [ABSTRACT FROM AUTHOR]

We use Ehrhart polynomials to estimate the likelihood of each three-candidate social ranking produced by pairwise majority rule assuming an even number of voters and the Impartial Anonymous Culture condition. We then calculate the probability the ranking is transitive and the probability of a weak Condorcet winner. Finally, we determine the weak Condorcet efficiency of various voting rules. We prove that Baldwin, Nanson, Copeland, and ranked pairs are weak Condorcet efficient, as is Borda unless there are no ties. Simulations show that among the rest, Dowdall is typically the most efficient rule for small voter groups and anti-plurality the least. • We focus on potential three-candidate social rankings using pairwise majority rule. • We consider an even number of voters and preferences following the IAC assumption. • Deduces the probability a ranking is transitive or contains a weak Condorcet winner. • The weak Condorcet efficiency of various voting rules is also estimated. • Our study provides a more complete picture of the considered probabilities. [ABSTRACT FROM AUTHOR]

With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control. [ABSTRACT FROM AUTHOR]

Abstract This paper aims to address the issue of predatory publishing, sensu lato. To achieve this, we offer our perspectives, starting initially with some background surrounding the birth of the concept, even though the phenomenon may have already existed long before the popularization of the term "predatory publishing". The issue of predation or "predatory" behavior in academic publishing is no longer limited to open access (OA). Many of the mainstream publishers that were exclusively subscription-based are now evolving towards a state of complete OA. Academics seeking reliable sources of journals to publish their work tend to rely on a journal's metrics such as citations and indexing, and on whether it is blacklisted or whitelisted. Jeffrey Beall raised awareness of the risks of "predatory" OA publishing, and his blacklists of "predatory" OA journals and publishers began to be used for official purposes to distinguish valid from perceived invalid publishing venues. We initially reflect on why we believe the blacklists created by Beall were flawed, primarily due to the weak set of criteria confusing non-predatory with true predatory journals leading to false positives and missing out on blacklisting true predatory journals due to false negatives. Historically, most critiques of "predatory publishing" have relied excessively on Beall's blacklists to base their assumptions and conclusions but there is a need to look beyond these. There are currently a number of blacklists and whitelists circulating in academia, but they all have imperfections, such as the resurrected Beall blacklists, Crawford's OA gray list based on Beall's lists, Cabell's new blacklist with about 11,000 journals, the DOAJ with about 11,700 OA journals, and UGC, with over 32,600 journals prior to its recent (May 2018) purge of 4305 journals. The reader is led into a discussion about blacklists' lack of reliability, using the scientific framework of conducting research to assess whether a journal could be predatory at the pre- and post-study levels. We close our discussion by offering arguments why we believe blacklists are academically invalid. [ABSTRACT FROM AUTHOR]

What are the probability and underlying influence factors of intermittent ovarian function recovery in patients with idiopathic premature ovarian insufficiency (POI)? This was a retrospective cohort study conducted in tertiary hospitals recruiting 162 patients diagnosed with POI based on European Society of Human Reproduction and Embryology criteria from June 2015 to March 2022. The incidence of intermittent ovarian function recovery was evaluated, and the possible influence factors were investigated by univariate and multivariate analysis. Among 162 POI patients, 48 (29.63%) presented intermittent ovarian function recovery, and 11 (6.79%) were natural pregnancies; 114 (70.37%) patients failed to show ovarian function recovery. No association was found between initial clinical features and intermittent ovarian function recovery. In contrast, the variables of FSH, LH, oestradiol, anti-Müllerian hormone (AMH), ovarian volume, passive smoking and weekly exercise time after diagnosis were correlated with intermittent ovarian function recovery in patients with POI and further analysis indicated that FSH concentration at diagnosis (odds ratio [OR] 0.964, 95% confidence interval [CI] 0.934–0.995, P = 0.023), passive smoking (OR 0.369, 95% CI 0.141–0.963, P = 0.042) and weekly exercise time after diagnosis (OR 5.592, 95% CI 1.83–17.088, P = 0.003) were influence factors of intermittent ovarian function recovery in POI patients. The incidence of intermittent ovarian function recovery in patients with idiopathic POI was 29.63%, and the natural pregnancy rate was 6.79%. Lower FSH concentration at diagnosis, no passive smoking and a weekly exercise time ≥1.5 h after the diagnosis may be beneficial for intermittent ovarian function recovery in POI patients. [ABSTRACT FROM AUTHOR]

Although cancer is still the second leading cause of death worldwide, basic research has largely elucidated the underlying mechanisms that lead us deep into the laws of animate and inanimate nature. This review aims to demonstrate that the cancer process profoundly affects and reprograms fundamental principles and concepts of cellular life by harnessing the natural mechanisms of biological evolution. It is shown that mutation and selection – the drivers of cancer formation and progression – are mandatory consequences of Boltzmann's version of the second law of thermodynamics, which stipulates that entropy (or disorder) according to probability never decreases, followed by Darwinian evolution by filtering for the suitable geno- and karyotypes. Cancer research has shown that malignant cells can develop gradually or abruptly depending on the prevailing stress conditions. Similar principles were then observed in the evolution of species, referred to as micro- and macroevolution. Cancer cells can be related to phylogenetically older forms of life, and malignant transformation can be viewed as reverse (atavistic) evolution, accompanied by typical rearrangement of system information and loss of 'social' behavior. It becomes obvious that in nature no distinction is made between normal biology and pathobiology. Instead, everything follows the rules of natural evolution. This illustrates the depth of the cancer problem and may explain the serious difficulties faced in trying to eradicate cancer. • Boltzmann's 2nd law of thermodynamics & Darwin's principle of selection determine evolution of species & cancer development. • Entropy causes mutations that produce genetic variation. • Selection/competition promotes cancer development and phylogenetic evolution. • Cancer cells and primitive forms of cell life share many characteristics (atavism). • Genomes of cancers & organisms can be subject to slow microevolutionary & punctuate macroevolutionary alterations. [ABSTRACT FROM AUTHOR]

We discuss a newly published study examining how phrases are used in clinical trials to describe results when the estimated P-value is close to (slightly above or slightly below) 0.05, which has been arbitrarily designated by convention as the boundary for 'statistical significance'. Terms such as 'marginally significant', 'trending towards significant', and 'nominally significant' are well represented in biomedical literature, but are not actually scientifically meaningful. Acknowledging that 'statistical significance' remains a major determinant of publication, we propose that scientific journals de-emphasise the use of P-values for null hypothesis significance testing, a purpose for which they were never intended, and avoid the use of these ambiguous and confusing terms in scientific articles. Instead, investigators could simply report their findings: effect sizes, P-values, and confidence intervals (or their Bayesian equivalents), and leave it to the discerning reader to infer the clinical applicability and importance. Our goal should be to move away from describing studies (or trials) as positive or negative based on an arbitrary P-value threshold, and rather to judge whether the scientific evidence provided is informative or uninformative. [ABSTRACT FROM AUTHOR]

Recently historians and philosophers of science have been interested in the role of statistics and probability in investigating population variation. The focus is typically on investigators applying statistics and probability to explain large scale phenomenon that arise out of the collective behavior of numerous and varied individuals. The case studies that inform this work come mostly from molecular physics and 20th century genetical versions of evolutionary theory. Charles Darwin's work on evolution is rarely mentioned in this context except to point out his shortcomings—he made evolutionary theory "ripe" for statistical investigations, but he was not a statistical thinker. But this is a mistake, Darwin was a statistical thinker. In this essay I describe two instances where Darwin utilized statistical methods to investigate evolution. In the light of these cases, we ought to revise our views about Darwin's scientific methodology, in particular, how he came to develop his ideas about evolution and about the nature of his "population thinking". Furthermore, Darwin's cases provide us with an expanded view about what constitutes "statistical thinking" in the biological sciences. In the examples we will find Darwin using statistical measures of type frequencies to detect large scale ensemble effects, confirm hypotheses by comparing between expected and observed averages, and applying the astronomer's law of error to explain evolutionary trends. [ABSTRACT FROM AUTHOR]

A local analysis of a chance system recovers the properties of the totality by accumulating the chance properties of its components. A global analysis considers only the properties of the chance system taken as a whole. It can sometimes provide an easier demonstration of the fitness for purpose of chance systems. Such is the case for the operators of lotteries and for bookmakers at a racetrack. Physical randomizers akin to dice were used extensively in antiquity for gambling, drawing lots and in divination. There is no ancient account of the fitness of these randomizers for these purposes and no ancient theory of the individual chances of outcomes. A global analysis can establish their fitness for purpose. If the rules of gambling and lot drawing are such that everyone has an equal opportunity, they are fair, independently of the individual, local chances. The randomizers are fit for the purposes of divination in so far as it is believed that the oracle has no control on the outcomes of the randomizers. In asking why some earlier culture did not discover probability theory, we presume incorrectly an inevitability to probability theory. The better question is why any culture found the theory at all. • Global analysis of chance systems proceeds independently of the chances of individual outcomes. • It is used by lottery operators and bookmakers. • Before probability theory, it established the fitness of randomizers for gambling and lot drawing. • Physical randomizers are by design irregular in their behavior. • One probabilistic theory covering all physical randomizers is extraordinary and not inevitable. [ABSTRACT FROM AUTHOR]

For the widespread fatigue problems on orthotropic steel decks (OSDs), the failure criteria in the fatigue analyses and assessments should be improved with respect to the crack behaviors and consequences specifically. This paper presents a study on the fatigue failure criteria for OSDs considering the penetrating cracks, which is the most unfavorable case by resulting in premature damage on pavements and the consequent serviceability loss. The fatigue test results on different types of penetrating cracks are analyzed, showing similar fatigue strength in terms of S N curves, yet with different behaviors in crack growth. Further analysis indicates that the failure evaluation should not only focus on the crack growth rates of penetrating cracks, as it may stay at a rather low level and hardly reach the unstable propagation region. Hence, it is proposed to evaluate the damage evolution and life reduction of pavements caused by penetrating cracks. It shows that the penetrating crack with the depths of 0.5 t and 0.75 t will considerably reduce the fatigue life of the pavements on the cracked OSD, and the equivalent crack area is then proposed to determine the fatigue failure criteria considering serviceability. Finally, a study based on Monte-Carlo simulation and probabilistic fracture mechanics is conducted to obtain the time-dependent failure probabilities and reliability indexes. Different target reliability indexes are also considered, which help the management and maintenance of the bridge and benefit its life-cycle performance. • The fatigue failure of OSDs by penetrating cracks are analyzed and compared. • The damage evolution of pavements on a cracked OSD is investigated. • The reliability based failure criteria are proposed considering OSD crack growth and pavement life reduction. [ABSTRACT FROM AUTHOR]

In decision making under risk, where the consequences of choices vary depending on specific probabilities, a proper interpretation of the presented probabilities is essential. However, because people are not good at evaluating numerical values, such as percentages, efforts have been made to accurately convey presented probabilities using visual aids represented by icon arrays. However, previous studies have suggested that icon arrays produce an overestimation of probabilities under specific conditions. Especially, (a) the arrangement of highlighted icons and (b) the severity of the outcomes represented by highlighted icons can lead to an overestimation of probabilities. By considering the absolute estimation of probabilities indicated by icon arrays and manipulating the aforementioned factors, this study investigated whether these factors could elicit an overestimation of probabilities in an additive manner or whether they have interactive effects. Two studies (total N = 1171) consistently showed that the arrangement of highlighted icons and the outcome severity they indicate induced a perceptual bias in the estimation of the probabilities presented in icon arrays in an additive manner. When the highlighted icons were random and the outcomes they indicate were severe, the probabilities presented by the icon arrays were overestimated. Accordingly, the study not only confirms the robustness of the findings of previous studies but also expand our understanding of the probability overestimation caused by icon arrays. Here, we discuss our findings in terms of the impact of risk-related communication. [ABSTRACT FROM AUTHOR]

Machine learning (ML) algorithms are beneficial to compensate for the shortcomings of traditional models in predicting human thermal sensation votes (TSV). Establishing ML models with interpretability is important to explore the thermal comfort of the elderly people. The aim of this study is to establish a logistic regression model and interpret the model for the TSV of the elderly people. Firstly, the input parameter combinations are determined according to the correlation between physiological parameters, environmental parameters and TSV. Secondly, the logistic regression model is established based on over sampling. Finally, the models with different inputs are interpreted by odds ratios and probabilities. The results indicate that, the optimal model inputs are air temperature (T a), mean radiant temperature (T r), humidity (RH), mean skin temperature (MST), wind velocity (V a), and wrist temperature (T wrist). The model's accuracy is 70 %. Increases in eardrum temperature (T ear), heart rate (HR) and T r positively predict "cool". Increases in T a , MST, V a and T wrist positively predict "neutral". Increases in HR and T wrist negatively predict "warm". The comfort zones for T a , V a , MST and T ear are 26.7–29.7 °C, 0–0.2 m/s, 35.5–36.2 °C and 35.0–37.1 °C, respectively. This study can provide design suggestions for indoor environments of the pensioners' buildings. [ABSTRACT FROM AUTHOR]

Darwinian evolution is a nineteenth century descriptive concept that itself has evolved. Selection by survival of the fittest was a captivating idea. Microevolution was biologically and empirically verified by discovery of mutations. There has been limited progress to the modern synthesis. The central focus of this perspective is to provide evidence to document that selection based on survival of the fittest is insufficient for other than microevolution. Realistic probability calculations based on probabilities associated with microevolution are presented. However, macroevolution (required for all speciation events and the complexifications appearing in the Cambrian explosion) are shown to be probabilistically highly implausible (on the order of 10−50) when based on selection by survival of the fittest. We conclude that macroevolution via survival of the fittest is not salvageable by arguments for random genetic drift and other proposed mechanisms. Evolutionary biology is relevant to cancer mechanisms with significance beyond academics. We challenge evolutionary biology to advance boldly beyond the inadequacies of the modern synthesis toward a unifying theory modeled after the Grand Unified Theory in physics. This should include the possibility of a fifth force in nature. Mathematics should be rigorously applied to current and future evolutionary empirical discoveries. We present justification that molecular biology and biochemistry must evolve to aeon (life) chemistry that acknowledges the uniqueness of enzymes for life. To evolve, biological evolution must face the known deficiencies, especially the limitations of the concept survival of the fittest, and seek solutions in Eigen's concept of self-organization, Schrödinger's negentropy, and novel approaches. [ABSTRACT FROM AUTHOR]

Life in an increasingly information-rich but highly uncertain world calls for an effective means of communicating uncertainty to a range of audiences. Senders prefer to convey uncertainty using verbal (e.g., likely) rather than numeric (e.g., 75% chance) probabilities, even in consequential domains, such as climate science. However, verbal probabilities can convey something other than uncertainty, and senders may exploit this. For instance, senders can maintain credibility after making erroneous predictions. While verbal probabilities afford ease of expression, they can be easily misunderstood, and the potential for miscommunication is not effectively mitigated by assigning (imprecise) numeric probabilities to words. When making consequential decisions, recipients prefer (precise) numeric probabilities. The (positive and negative) directionality of verbal probabilities enables them to convey more than uncertainty. Probability terms can communicate uncertainty in a face-saving manner and implicitly shape receivers' cognitions and behavior. Verbal probabilities preclude fine-grained uncertainty communication. Assigning numeric probability ranges to words does not eliminate their imprecise and variable meaning, but can have unintended effects on judgment and decision-making. Senders are misplaced in their belief that verbal expressions of uncertainty are especially helpful for those with lower numeracy and in thinking that these individuals cannot benefit from numeric probability information. The benefits of precise numeric expressions of uncertainty, coupled with receivers' preference for numeric information when it really matters, suggests that senders ought to embrace numeric precision over vague words if they wish to communicate uncertainty clearly. [ABSTRACT FROM AUTHOR]

This paper analyzes the historical context and systematic importance of Kant's hypothetical use of reason. It does so by investigating the role of hypotheses in Kant's philosophy of science. We first situate Kant's account of hypotheses in the context of eighteenth-century German philosophy of science, focusing on the works of Wolff, Meier, and Crusius. We contrast different conceptions of hypotheses of these authors and elucidate the different theories of probability informing them. We then adopt a more systematic perspective to discuss Kant's idea that scientific hypotheses must articulate real possibilities. We argue that Kant's views on the intelligibility of scientific hypotheses constitute a valuable perspective on scientific understanding and the constraints it imposes on scientific rationality. • Analyzes the role of hypotheses in eighteenth-century German philosophy. • Explains the relation between probability and hypotheses in various authors. • Explains how hypotheses paved the way for obtaining certain truths. • Explores the connection between hypotheses and scientific understanding in Kant. [ABSTRACT FROM AUTHOR]

Railway transportation is an important channel for emergency rescue and disaster relief. Traditionally, the method of evaluating the damage degree of bridges under different seismic intensities from the perspective of structural damage cannot be directly used to judge the traffic capacity of trains on bridges after earthquakes. It is impossible to guarantee the running safety and affect the transportation of materials after the earthquake. Because the damage state of track structure directly affects the running safety of trains, this study combines the relationship between the damage of track structure and the deformation of bridge structure after earthquake, and puts forward the transverse relative displacement of girder end (TRDGE) as the damage index of train running function of railway bridge after earthquake. Then, the OpenSees-TRBF (Train-Railway-Bridge-Foundation Coupled System Dynamic Analysis Platform) co-simulation method is used to carry out the train-track-bridge coupling dynamic calculation under different seismic damage states, and the running safety analysis database under different TRDGEs is established. Then, the Particle Swarm Optimization (PSO) algorithm is used to classify the bridge damage index of traffic capacity through different target safety speeds. Based on the probabilistic seismic demand model, the exceedance probability curve of traffic capacity damage under different seismic intensities is established. Finally, based on the curve, the running safety risk domain of trains on the bridge under different seismic intensities is obtained with a confidence level of 95 %. This study proposes a post-earthquake damage assessment method for railway bridges based on the assurance of running safety probabilities, evaluating the damage degree of the bridge with the residual traffic capacity of the bridge after the earthquake. This study can be applied to assess earthquake damage on existing railway bridges and provide references for the safe speed of trains on the bridge after an earthquake. • A seismic damage assessment method for bridge based on running safety is proposed. • The seismic damage probability curve of bridge based on running safety is established. • The post-earthquake vehicle speed threshold is established. [ABSTRACT FROM AUTHOR]

• A comprehensive probability prediction method for domino effects is developed. • Escalation probability models under different synergistic effects are established. • Different scenarios after unit failure are modeled to obtain domino probability. • Risk reduction measures are proposed based on the posterior probability analysis. Domino effects are a complex phenomenon of accident escalation with high uncertainty, which could lead to catastrophic consequences. Predicting the probability of domino effects presents a great challenge in the field of process safety. In multi-level domino chains, synergistic effects of accidents would further raise the complexity of probability prediction since escalation vectors emitted from those accidents may be coupled. In this paper, four categories of synergistic effects are classified according to the type of accidents and their place on the domino accident sequence. Subsequently, specific models for estimating escalation probability under different synergistic accident scenarios are proposed based on the widely-used probit models, allowing the analysis of the coupling effects of escalation vectors. A probability prediction method for domino chains is further developed using Bayesian Network. The application of the developed method is demonstrated by a case study, and the domino probability is estimated accounting for the synergistic effects and all possible accident scenarios. The key units for promoting accident propagation are further identified through posterior probability analysis. The method would be helpful for domino risk assessment and management of any chemical industrial area. [ABSTRACT FROM AUTHOR]

As efforts to conserve energy and reduce emissions in the global shipping industry intensify, people are constantly looking for new types of energy to replace traditional fuels. Ammonia is considered a novel energy source due to its potential for carbon-neutral shipping when produced from renewable energy sources and is extremely promising for the shipping industry. In this study, the fuel toxicity risk of ammonia-fueled ships under operating conditions was quantified for the first time. The assessment process adopts the traditional quantitative risk assessment (QRA) framework with accident probability calculations based on Bayesian theory, and the process of partial quantification of consequences also guides the delineation of safety zones. The results of the study suggest that ammonia-powered tugboats are at a higher risk of toxic accidents during operation than accidents at sea, but both are within the acceptable limits of current international maritime safety and environmental standards. Finally, safety measures and risk mitigation strategies are proposed based on the study results. This provides important support in safety risk analysis for the design, production and operation of subsequent ammonia fueled vessels and is of great theoretical and practical importance. In this study, we focus on accident probability and accident consequences. Through HAZOP analysis, we identified potential hazardous scenarios and calculated accident probabilities using Bayesian principles in combination with historical data from LNG ships. For the traditional QRA model, we worked on improving the quantification of toxicity consequences. For the first time, we combined the toxic gas concentration field obtained from computational fluid dynamics calculations with dose-response modeling, and applied it to the hazard assessment work for real operating scenarios of ammonia-fueled tugboats. The research shows that both the personal and societal risks of toxic hazards when operating an ammonia-powered tugboat are within the acceptable range under current international maritime safety and environmental standards. [Display omitted] • Quantitative analysis of toxicity risks when operating ammonia-powered tugboats. • Systematic investigation of hazard scenarios during tugboat operations. • Risk assessment of operational and marine accidents for individuals and society. • Safety measures and risk mitigation strategies for ammonia-powered tugboats. [ABSTRACT FROM AUTHOR]

This paper explores the space of (propositional) probabilistic logical languages, ranging from a purely 'qualitative' comparative language to a highly 'quantitative' language involving arbitrary polynomials over probability terms. While talk of qualitative vs. quantitative may be suggestive, we identify a robust and meaningful boundary in the space by distinguishing systems that encode (at most) additive reasoning from those that encode additive and multiplicative reasoning. The latter includes not only languages with explicit multiplication but also languages expressing notions of dependence and conditionality. We show that the distinction tracks a divide in computational complexity: additive systems remain complete for NP , while multiplicative systems are robustly complete for ∃ R. We also address axiomatic questions, offering several new completeness results as well as a proof of non-finite-axiomatizability for comparative probability. Repercussions of our results for conceptual and empirical questions are addressed, and open problems are discussed. [ABSTRACT FROM AUTHOR]

The bulk electricity that powers our society flows along high voltage transmission lines that are conducting cables hung with insulators from a series of transmission towers. High winds can damage these structures and the loss of the transmission line sometimes causes a blackout. When a tower structurally fails, the adjacent towers have unbalanced load, and are more likely to fail, so there is a cascading effect by which tower failures can lead to further tower failures. This paper analyzes the cascading failures of towers due to extreme straight line winds. A dynamic analysis of the transmission tower–insulator–conductor system under wind loads yields fragility curves that describe the probability of structural failure for both intact and failed adjacent towers. The paper then derives novel mathematical formulas for the probabilities of the number of towers that fail. The new formulas apply generally to cascading failure along a line of general components. The calculations use generating functions and computer algebra, and account for the interspersed anchor towers that are strongly built to withstand high winds. The effect of cascading on the number of towers failed and the life cycle cost is quantified in a case study of a transmission line with twenty-five towers. • Formulates probabilistic cascading structural failure of towers in a transmission line. • New mathematical formulas for the probability distribution of the number of towers failed. • Formulas apply generally to cascading along a line of general components. • State of the art dynamic analysis gives tower fragility curves under high wind loads. • Case study quantifies the effects and risk of cascading in a line of 25 towers. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, we investigate the resilience of alternative electric grid configurations by adopting a stylized approach based on graph theory, probabilistic analysis, and simulation. We consider two alternative classes of electricity network topology: binary trees and rectangular lattices. For each topology, we find the probabilities that customers located at various nodes in the network will continue to have power following a disaster, depending on the locations of resources (e.g., generators, storage units) in the network. Then, these probabilities are incorporated into the problem of optimally placing resources throughout the network. This is a cost–benefit problem that weighs the benefits of placing resources closer to customers – that is, pursuing a distributed resilience strategy – against the higher total cost of deploying a greater number of smaller resource units. Our analytical and numerical results thus shed light on the general circumstances in which centralized or distributed resilience strategies are preferable. While optimal resource placements depend on various assumptions, such as the probability that power lines fail and the strength of economies of scale, we find that distributed resilience strategies are more often preferred in the binary tree topology than in the rectangular lattice topology. Rectangular lattices feature greater redundancy in terms of paths between nodes in the network, enabling the system to be fairly resilient even with centralized resources. • Resilience of two alternative electric grid configurations binary trees and rectangular lattices. • Stylized approach based on graph theory, probabilistic analysis, and simulation. • Cost–benefit problem that weighs the benefits of centralized vs distributed resilience strategy. [ABSTRACT FROM AUTHOR]

Probability and reciprocation have been implicated as key variables for understanding altruism and cooperation. Social discounting, which describes the decline in reward value as the recipient increases in social distance, has provided a framework through which to examine altruistic and cooperative choice. A previous study introduced reciprocal discounting as a way of studying perceived altruism from others (termed reciprocal altruism). But probability discounting has not yet been examined in relation to reciprocal discounting. In order to extend research on reciprocal discounting, the present study evaluated correlations between social, reciprocal, and probability discounting as well as relations between standard social distance (used in social discounting) and reciprocal social distance (the participant's perceived social distance placement on someone else's list) among 129 participants. Upon evaluation, the fit of median reciprocal discount rates to the hyperbolic form was replicated. A strong correlation between social and reciprocal discount rates and a moderate correlation between social and probability discount rates were found as well. Additionally, reciprocal and probability discount rates yielded moderate correlations while reciprocal and standard social distance analyses revealed more correspondence between reward values when persons were socially close (i.e., Person 1) or socially distant (i.e., Person 100). This study provides further evidence that reciprocation and probability likely impact altruistic choice while laying groundwork for further investigations into social distance. • Fit of reciprocal discounting to the hyperbolic formula was replicated. • Reciprocal discounting is strongly correlated with social discounting and moderately correlated with probability discounting. • Social distance, reciprocity, and probability are critical variables to studying altruism. [ABSTRACT FROM AUTHOR]

Rising sea levels caused by climate change are increasing the risk of overtopping on coastal structures. Moreover, there is a growing societal concern about the visual impact of these structures, which leads to the lowering of their crest freeboards. In previous studies, safety during overtopping events was assessed considering the overtopping layer thickness (h c), the overtopping flow velocity (u c) and the individual wave overtopping volume (V). Existing models in the literature to estimate h c , u c and V on mound breakwater crests are mainly deterministic, involve a chain of successive estimations leading to accumulated errors and/or do not account for the dependencies between h c , u c and V. This study proposes a model to describe the joint probability distribution of h c , u c and V based on bivariate copulas. Experimental data from small-scale 2D physical tests conducted on mound breakwaters with three armor layers (single-layer Cubipod®, and double-layer cubes and rocks) in depth-limited breaking wave conditions on two mild bottom slopes and dimensionless crest freeboards between 0.33 and 3.20 is used. Lognormal distribution functions are proposed for each variable and a multivariate dependence model is developed through a one-tree vine-copula. The parameters of this model are quantified directly using wave characteristics and the structure geometry minimizing the accumulated errors in the final predictions. The application of the model is illustrated by computing the probability of not fulfilling at least a tolerability limit for one of the studied variables (OR probability). The OR probability is computed both considering the dependence and assuming independence between the variables and a significant difference is obtained. It is concluded that by accounting for the multivariate dependence between the variables, it is possible to reduce the crest freeboard and, thus, achieve a more economic design within the required safety level. • Distribution functions are proposed to describe each overtopping variable. • A one-tree vine-copula is proposed to model the dependence of overtopping variables. • The model allows to compute the probability of not fulfilling at least one limit. • The model is quantified based on wave characteristics and structure geometry. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) algorithms, specifically Artificial Neural Networks (ANNs), have proved their effectiveness in solving complex problems in many different applications and multiple fields. This paper focuses on optimizing the activation function (AF) block of the NN hardware architecture. The AF block used is based on a probability-based sigmoid function approximation block (P-SFA) combined with a novel real-time probability module (PRT) that calculates the probability of the input data. The proposed NN design aims to use the least amount of hardware resources and area while maintaining a high recognition accuracy. The proposed AF module in this work consists of two P-SFA blocks and the PRT component. The architecture proposed for implementing NNs is evaluated on Field Programmable Gate Arrays (FPGAs). The proposed design has achieved a recognition accuracy of 97.84 % on a 6-layer Deep Neural Network (DNN) for the MNIST dataset and a recognition accuracy of 88.58% on a 6-layer DNN for the FMNIST dataset. The proposed AF module has a total area of 1136 LUTs and 327 FFs, a logical critical path delay of 8.853 ns. The power consumption of the P-SFA block is 6 mW and the PRT block is 5 mW. [ABSTRACT FROM AUTHOR]

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In this paper we study the preference-based activity scheduling problem, where based on preference sets of participants, activities need to be scheduled in parallel, such that participants can attend as many of their preferred activities as possible. The Activity Scheduling Problem (ASP) takes as input the activities, time slots, participants and their set of preferences, and is supposed to output an optimal schedule. Attendance is the number of preferred activities a participant can attend. We present two lower bounds on the average attendance over all participants, based on linearity of expectation. The first is a bound that involves the different parameters of ASP; we prove that this bound is tight. The second bound is such that no matter how many activities, participants, and time slots are included in the event, there is always a schedule that guarantees an average attendance of (1 − 1 / e) of the preferred activities for the participants. A further result, based on applying the Lovász local lemma to hypergraph coloring, presents a lower bound on the minimum attendance over all participants. We show that for various values of the problem's parameters this bound is better than a simple bound, although the simple bound may be tight for instances with a very large number of participants. [ABSTRACT FROM AUTHOR]

The purpose of this review is to draw attention to the presence and significance of murmurs other than the murmur of aortic regurgitation, in patients with aortic dissection. For that purpose, a literature search was conducted using Pubmed and Googlescholar. The search terms were "dissecting aneurysm of the aorta", "systolic murmurs", "ejection systolic murmurs", "holosystolic" murmurs, "continuous murmurs", and "Austin-Flint" murmur. Murmurs other than the murmur of aortic regurgitation, which were associated with aortic dissection, fell into the categories of systolic murmurs, some of which were holosystolic, and continuous murmurs, the latter attributable to fistulae between the dissecting aneurysm and the left atrium, right atrium, and the pulmonary artery, respectively. Mid-diastolic murmurs were also identified, and these typically occurred in association with both the systolic and the early diastolic murmurs. Among patients with systolic murmurs clinical features which enhanced the pre-test probability of aortic dissection included back pain, stroke, paraplegia, unilateral absence of pulses, interarm differences in blood pressure, hypertension, shock, bicuspid aortic valve, aortic coarctation, Turner's syndrome, and high D-dimer levels, respectively. In the absence of the murmur of aortic regurgitation timely diagnosis of aortic dissection could be expedited by increased attention to parameters which enhance pretest probability of aortic dissection. That logic would apply even if the only murmurs which were elicited were systolic murmurs. [ABSTRACT FROM AUTHOR]

• The multi-island genetic algorithm (MIGA) is applied to optimize the configuration of a universal selective solar absorber, which is superior to traditional genetic algorithm (GA) in finding the global optimum. • The optimization design is conducted to achieve maximum absorptance A (λ) over solar spectrum and minimum emittance ε (λ) in the mid-infrared band at the same time. • A set of optimal geometric parameters are obtained, with the solar absorptance greater than 0.932 with 96% probability and mid-infrared emittance lower than 0.058 simultaneously. • The optimal absorber is a combination of great characteristics, such as highly spectral selectivity, polarization independence and angle insensitivity. Based on the demand for ideal selective solar absorbers to harvest a full solar spectrum, we present an auspicious method, the multi-island genetic algorithm (MIGA), to optimize the configuration of a universal selective solar absorber, which can avoid the premature phenomenon and superior to traditional genetic algorithm. The selective solar absorber equipped with the set of optimal geometric parameters exhibits the solar absorptance greater than 0.932 with 96% probability and mid-infrared emittance lower than 0.058 at the same time considering unavoidable 20% fabrication uncertainties in the design variables. In addition, the absorber is a combination of great characteristics, such as polarization independence and angle insensitivity. The hybrid resonance modes of Wood's anomaly, surface plasmon polariton and magnetic polariton are responsible for the high absorption performance. The MIGA method presented is proved to be an effective and robust tool in the optimization of micro-nano structures with manufacturability for thermal and energy applications. [ABSTRACT FROM AUTHOR]

There have been several recent high-profile space events, notably the conjunctions of the Aeolus and Starlink spacecraft (both maneuverable) and the IRAS and GGSE-4 spacecraft (both dead). Here, we examine the timeline, activities, and risks associated with each of these conjunction events. To accomplish this, we fused observations from the Space Surveillance Network (SSN) to produce a sequence of high-accuracy orbit solutions and used that sequence to generate three-dimensional, dynamic progressions of each conjunction's miss distance, collision probability and its relation to the dilution threshold. Probability of Collision (Pc) is an essential tool for assessing conjunction threats. The Pc Topology tool characterizes the evolution of a conjunction's miss distance and collision probability, both of which are critical inputs to the maneuver avoidance decision-making process and exposing SSA deficiencies. We show the effect of combined hardbody radius (CHBR) on Pc as well as modeling with different shapes. Additionally, the Pc Topology tool reveals the calculation's placement in/out of the dilution region. The European Space Agency commanded the Aeolus spacecraft to perform an emergency maneuver to avoid this high-probability collision hazard. Our results indicate that this maneuver was warranted based upon ESA's decision threshold criteria and the Pc Topology trending analysis. While both collision events fortunately did not occur, we estimated the potential debris fields that these events may have generated had they occurred. Realizing that large debris production might be a factor in maneuver decision making, we then assess the impact of these fragmentation fields upon estimated operator workload and subsequent collision risk. • We examine the timeline, activities, and risks associated with the conjunctions of the Aeolus and Starlink spacecraft (both maneuverable) and the IRAS and GGSE-4 spacecraft (both dead). • We also introduce an improved method to compute collision probability. • We fused observations from the Space Surveillance Network (SSN) to produce a sequence of high-accuracy orbit solutions and used that sequence to generate three-dimensional, dynamic progressions of each conjunction's miss distance, collision probability and its relation to the dilution threshold using the Probability of Collision (Pc) Topology tool for assessing conjunction threats. • While both collision events fortunately did not occur, we estimated the potential debris fields that these events may have generated had they occurred. We then assessed the impact of these fragmentation fields upon estimated operator workload and subsequent collision risk. [ABSTRACT FROM AUTHOR]

Charles Darwin's On the Origin of Species has an unusual format. After presenting his theory of Natural Selection in its first four chapters, there follows a series of five chapters presenting a large number of problems and objections to the theory which, he admits, appear overwhelming. Not until chapter 10 does he begin to present what he takes to be the positive evidence for his theory. In this paper I trace the evolution of this structure from its first hints in his Species Notebooks , through the 1842 Sketch and 1844 Essay to the Origin , showing that it reflects a growing awareness on Darwin's part of what I call 'In Principle Impossible' arguments against his theory, and of a systematic strategy for disarming them. [ABSTRACT FROM AUTHOR]

Coalitional manipulation in voting is considered to be any scenario in which a group of voters decide to misrepresent their votes in order to secure an outcome they all prefer to the outcome of the election when they vote honestly. The present paper is devoted to studying coalitional manipulability within the class of scoring voting rules. For any such rule and any number of alternatives, we introduce a new approach allowing us to characterize all the outcomes that are manipulable by a coalition of voters. This then opens the possibility of determining the probability of manipulable outcomes for some well-studied scoring voting rules in the case of small number of alternatives and large electorates, under a well-known assumption on individual preference profiles. • We study coalitional manipulability within the class of scoring voting rules. • Manipulable profiles are characterized whatever the number of alternatives. • We focus on the limiting case where the number of voters tends to infinity. • A probabilistic analysis is conducted under IAC. [ABSTRACT FROM AUTHOR]

Cryptocurrencies are widely regarded as volatile and less predictable assets by financial participants. The behaviour and dynamics of Bitcoin's daily volatility, obtained by fitting GARCH models, are investigated for a period of 8 years using permutation entropy which is represented by the variable H for calculations. The best fitting GARCH models selected are the FIGARCH(1,0.7,1) and SGARCH(1,1) models based on maximum likelihood estimation, Akaike Information Criterion and Bayesian Information Criterion. Simulated volatilities are also obtained from the best fitting GARCH models using their respective parameters, to confirm how well the models fit. The results obtained show that the H values of Bitcoin are generally low and that the dynamics of Bitcoin's volatility is quite predictable, as Bitcoin's volatility is most likely to decline over time than increase or have an alternating movement. Also, the simulated volatilities show good agreement with the real-world volatility, confirming the models as good fits. [ABSTRACT FROM AUTHOR]

PROMETHEUS is a statistical tool that allows creating maps showing the probability of finding tephra deposits of different grain sizes, originating from eruptions of a specific volcanic source, at any location around the vent. It couples wind profiles at different heights in the Mediterranean area with terminal velocity of volcanic particles. The input parameters include the height of the eruption column (which characterizes the intensity of the eruption), wind statistics (directions and intensities), and tephra deposits of a selected grain size. In particular, we used the parameterizations provided by Costa et al. (2016) and performed simulations using the HAZMAP tephra dispersal model to determine the maximum reachable distances that tephra can cover under weak, medium, and strong wind conditions (e.g. 7, 30, and 70 m/s velocities at the tropopause) and with column heights of 10, 20, and 30 km, depositing of at least the loading corresponding to 0.1 mm (corresponding to cryptotephra). Three alternative configurations of the model are validated analyzing first the eruptive source of Somma Vesuvius, with the related explosive eruptions from 22 ka Pomici di Base to the 1944 eruption. A further validation is made by comparing the probabilistic maps with the tephrostratigraphy of known marine and terrestrial cores using standard test of proportions (binomial distributions) and the binary logistic regression model, statistically quantifying the effectiveness of the model against the tephrostratigraphy recorded within this time frame. Based on this validation, a preferred configuration of PROMETHEUS is selected. PROMETHEUS probability maps will guide the selection of sampling sites for specific tephra deposits and could also support the study of the completeness of overall eruption catalogs over time. • Probability maps allow us to determine how far a particular grain size of tephra can reach. • The easy reproducibility of the scripts and the related maps allows one to create probability maps in any place of interest. • These probability maps will allow us to understand which places are most affected by explosive volcanic eruptions with a given eruptive size. [ABSTRACT FROM AUTHOR]

Traditionally, the deterministic rainfall threshold has been widely used for early warning of landslides, which is often developed based on visual inspection of historical rainfall events in a region that triggered landslides. As there is no deterministic relationship between rainfall and the occurrence of landslides, it is not uncommon to observe in practice that a rainfall above the deterministic rainfall threshold may not cause landslides, and vice versa. In this paper, a numerical study is first conducted to gain insights on factors affecting the rainfall threshold for early warning of landslides. Then, a procedure based on the support vector machine is suggested to develop probabilistic rainfall thresholds, where the reliability associated with different rainfall thresholds can be explicitly quantified. Finally, two application examples are introduced to illustrate and validate the suggested method for developing rainfall thresholds probabilistically. The probabilistic rainfall thresholds presented in this study can provide more comprehensive information for issuing warning messages and risk management of landslide hazards. [ABSTRACT FROM AUTHOR]

Despite the importance of uncertainty in decision-making, few published studies have examined how individuals make moral judgments under uncertainty. Across four experiments (N = 445), we examined whether a relatively small shift in probability affected participants' judgments of both moral acceptability and choice. Overall, reading dilemmas where the characters were either certain or likely to die, the probability of the sacrificed individual and the group at risk dying both had independent effects on participants' responses. That is, participants were more accepting of sacrificing the individual if they were not certain to die, but less accepting if the group was only likely to die when the individual was not sacrificed. Furthermore, a number of participants made acceptability ratings that did not match the action they endorsed, either finding the sacrificial decision more acceptable but refusing to make it, or choosing the sacrificial decision while viewing it as less acceptable. Many participants also stated that this was because they recognised a crucial difference between what they viewed as morally acceptable in a dilemma and what they were actually willing to do. Such mismatches may reflect the sensitivity and complexity of the moral principles that individuals employ during their moral decision-making. [ABSTRACT FROM AUTHOR]

Flood events impose great distress on chemical industrial areas, since they may cause Natech accidents involving multiple units. Furthermore, escalation vectors exerted by major accidents can trigger knock-on events, so-called domino effects, causing very severe consequences. In the present study, a methodology is proposed to include domino effects triggered by floods in a quantitative risk assessment, by addressing the frequency assessment of flood-induced domino scenarios. A comprehensive procedure is developed, combining the fragility model for unit damage due to floods, probability estimation for domino escalation, and combinatorial analysis for overall scenarios. Moreover, the flow interference due to the layout of chemical industrial areas is explored to calculate the damage probability more accurately. The methodology has been demonstrated by a case study, the changes in risk indexes and damage zones due to Natech domino effects are discussed. The results show that the overall risk significantly increases with respect to conventional scenarios when considering flood-induced Natech events and domino effects, evidencing the importance of risk analysis of Natech-related domino effects. Finally, some prevention measures have been proposed for chemical industrial areas to make them more resilient and safer when it comes to floods. [ABSTRACT FROM AUTHOR]

Probabilistic design factors for pipes used for hydrogen transport are proposed for 3 locations: urban, peri-urban and rural areas. The used method involves a risk equation defined as the product of probability of leakage after failure, probability to have a gas flow greater than a prescribed value, probability of ignition, probability of lethal effects greater than a threshold value and probability of the presence of a person corrected by an environment factor and a risk reduction coefficient. The results obtained are less conservative than the deterministic values provided by ASME code. • Probabilistic design factors for pipes have been established. • The used method involves a risk equation. • This approach is based on assumption of a risk 10−5 probability. • The results obtained are less conservative than values provided by ASME code. [ABSTRACT FROM AUTHOR]

• Forensic evidence reporting shows a high degree of adherence to prevailing disciplinary standards. • Probabilistic reporting of forensic results remains rare. • Probabilistic reports were mostly subjective verbal assignments of posterior probabilities. [ABSTRACT FROM AUTHOR]

Background: Acute heart failure (AHF) is a complex syndrome associated with high morbidity and mortality. This study aimed to derive a simple risk score with which to identify AHF patients at high risk for an all-cause death event during the first year after hospital discharge.Methods: Three hundred AHF patients from the Heart Failure registry were included in the analysis. Cox regression with a forward-conditional algorithm and bootstrapping procedure was used to build the prognostic score, while c-statistic was used to assess the prognostic performance of the score.Results: Seven variables were independently associated with an all-cause mortality event during the 1-year follow-up (FU): estimated glomerular filtration rate of 40-60; estimated glomerular filtration rate <40 mL/min/1.73 m2; uric acid >450 μmol/L; left-ventricular ejection fraction <45%; sodium <136 mmol/L; systolic blood pressure <115 mmHg; and a positive history of previous heart failure-related decompensation event(s). The score derived from significant variables enabled classification of patients into three risk categories: low (0-2 points), intermediate (3 points), and high (4-6 points). Observed all-cause mortality rates during the 1-year FU were 6.1%, 30.5%, and 80.9% across the three risk categories, respectively. The score demonstrated a high level of discrimination for an all-cause death event in the derivation cohort with the c-statistic value of 0.907 (95% CI, 0.867-0.939; p < 0.0001) and adequate calibration.Conclusions: The S2PLiT-UG score is a simple tool with potential for facilitating risk stratification and therapeutic decision-making during the first year after hospitalisation for an AHF event. Future external validation studies are required to confirm its prognostic performance. [ABSTRACT FROM AUTHOR]

The idea of resolving dispute through the exchange of arguments and reasons has been central to society for millennia. We exchange arguments as a way of getting at the truth in contexts as diverse as science, the court room, and our everyday lives. In democracies, political decisions should be negotiated through argument, not deception, or even worse, brute force. If argument is to lead to the truth or to good decisions, then some arguments must be better than others and 'argument strength' must have some meaningful connection with truth. Can argument strength be measured in a way that tracks an objective relationship with truth and not just mere persuasiveness? This article describes recent developments in providing such measures. The ability to measure argument quality is of central importance not just in our everyday lives, but to scientific endeavors ranging from psychology and philosophy, to computer science and artificial intelligence. Classical logic provides fundamental constraints on argument quality, but most everyday informal argument is already in line with these constraints. This leaves the majority of quality concerns unaddressed. A Bayesian, probabilistic framework significantly expands quality standards for argument evaluation. It not only provides a treatment of the traditional catalogue of logical fallacies, it offers normative guidance that is quantitative, computationally explicit, and can be used for education. Consideration of how both logic and probability work to provide measures of argument quality suggests that 'consistency' and 'relevance' are two sides of the same coin. [ABSTRACT FROM AUTHOR]

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public–private collaboration aiming to develop and test a system for rapid benefit-risk monitoring of vaccines using existing healthcare databases in Europe. We estimated vaccine coverage from electronic healthcare databases as part of a fit-for-purpose assessment for vaccine benefit-risk studies. A retrospective dynamic cohort study was conducted through a distributed network approach. Coverage with measles-vaccine for birth year 2006, human papillomavirus (HPV)-vaccine for birth years 1990–2000 and influenza-vaccine for birth years 1920–1950 was estimated using period-prevalence and inverse probability weighting methods. Seven databases from four countries participated: Italy (Pedianet, Val Padana), Spain (BIFAP, SIDIAP), UK (RCGP-RSC, THIN), Denmark (SSI/AUH). Database access providers extracted the data, transformed it into a common structure and ran an R-script locally. The created output tables were shared and pooled at a central server. The total study population comprised 274,616 persons for measles-vaccine, 2,011,666 persons for HPV-vaccine and 14,904,033 persons for influenza-vaccine. Measles-vaccine coverage varied from 84.3% (Denmark) to 96.5% (Italy, Val Padana) for the first dose and from 82.8% (Italy, Val Padana) to 90.9% (UK) for the second dose at the age of 7 years. The HPV-vaccine coverage, aggregated over birth years 1997–2000, ranged from 60% (UK) to 88.3% (Denmark) at the age of 15 years. The influenza-vaccine coverage for the influenza seasons from 2009 to 2015 for persons aged 65 years and more was roughly stable around 43% in Denmark and around 68% in the UK while a decrease from 58 to 50% was observed in Catalonia (Spain). We obtained detailed, age-specific coverage estimates though a common procedure. We discussed between database comparability and comparability to published national estimates. [ABSTRACT FROM AUTHOR]

There is growing evidence that explanatory considerations influence how people change their degrees of belief in light of new information. Recent studies indicate that this influence is systematic and may result from people's following a probabilistic update rule. While formally very similar to Bayes' rule, the rule or rules people appear to follow are different from, and inconsistent with, that better-known update rule. This raises the question of the normative status of those updating procedures. Is the role explanation plays in people's updating their degrees of belief a bias? Or are people right to update on the basis of explanatory considerations, in that this offers benefits that could not be had otherwise? Various philosophers have argued that any reasoning at deviance with Bayesian principles is to be rejected, and so explanatory reasoning, insofar as it deviates from Bayes' rule, can only be fallacious. We challenge this claim by showing how the kind of explanation-based update rules to which people seem to adhere make it easier to strike the best balance between being fast learners and being accurate learners. Borrowing from the literature on ecological rationality, we argue that what counts as the best balance is intrinsically context-sensitive, and that a main advantage of explanatory update rules is that, unlike Bayes' rule, they have an adjustable parameter which can be fine-tuned per context. The main methodology to be used is agent-based optimization, which also allows us to take an evolutionary perspective on explanatory reasoning. • Uses computer simulations to show the ecological rationality of explanatory reasoning. • Connects computational results on explanatory reasoning with empirical results from psychology. • Shows the standard arguments in favor of Bayesian updating to be flawed. • Links to computer code that readers can easily use to run their own simulations and thereby to make further comparisons between update rules. [ABSTRACT FROM AUTHOR]

Objective: To assess the numerical probabilities that individuals associate with frequently-used verbal labels relating to treatment outcomes and their association with medical context, age, gender, educational level, health literacy, and numeracy.Methods: Verbal labels (N = 11) were extracted from N = 90 audiotaped decision encounters in oncology. Three hundred Dutch adults, as proxies for newly-diagnosed cancer patients, assigned numerical probabilities to the labels in the context of cancer recurrence or nausea, and completed questions on their socio-demographic characteristics, health literacy and numeracy.Results: We found considerable variation in how individuals interpreted the verbal labels. Participants' probability estimates of verbal labels was lower in the context of (the more serious) cancer recurrence compared to (less serious) nausea. Lower numerate participants differentiated less between labels. There was no association between participants' estimates and age, gender, educational level or health literacy.Conclusion: There is considerable variation in how individuals interpret verbal labels frequently-used in decision encounters. Individuals seem to take base rates and severity of outcomes into account. Verbal labels may be less helpful to lower numerate individuals.Practice Implications: To minimize misinterpretation and to improve patient-clinician decision making about health and care, we recommend to avoid the use of verbal labels only. [ABSTRACT FROM AUTHOR]