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In this paper, we investigate similarities and differences between the main neo-Copenhagen (or “epistemic–pragmatist”) interpretations of quantum mechanics, here identified as those defined by the rejection of an ontological nature of the quantum states and the simultaneous avoidance of hidden variables, while maintaining the quantum formalism unchanged. We argue that there is a single general interpretive framework in which the core claims that the various interpretations in the class are committed to, and which they emphasize to varying degrees, can be represented. We also identify, however, remaining differences of a more substantial nature, and we offer a first analysis of them. We also argue that these remaining differences cannot be resolved within the formalism of quantum mechanics itself and identify the more general philosophical considerations that can be used in order to break this interpretation underdetermination. [ABSTRACT FROM AUTHOR]

Likelihood ratios compare two values (i.e., case rates) in order to illustrate the magnitude of the difference between the two. This ratio increases the confidence one can have in a diagnostic test from a different vantage point than that of sensitivity and specificity. The calculations of likelihood ratios are presented along with a simplified approach. Likelihood ratios are another tool the toxicologist should employ in their understanding of statistics and probability. [ABSTRACT FROM AUTHOR]

In this paper the authors provide an epistemological view on the old controversial random-necessity. It has been considered that either one or the other form part of the structure of reality. Chance and indeterminism are nothing but a disorderly efficiency of contingency in the production of events, phenomena, processes, i.e., in its causality, in the broadest sense of the word. Such production may be observed in natural and artificial processes or in human social processes (in history, economics, society, politics, etc.). Here we touch the object par excellence of all scientific research whether natural or human. In this work, is presented a hypothesis whose practical result satisfies the Hegelian dialectic, with the consequent implication of their mutual reciprocal integration. Producing abstractions, without which, there is no thought or knowledge of any kind, from the concrete, that is, the real problem, which in this case is a given Ontological System or Reality. [ABSTRACT FROM AUTHOR]

Humans use pictures to model the world. The structure of a picture maps to mind space to form a concept. When an internal structure matches the corresponding external structure, an observation functions. Whether effective or not, the observation is self-consistent. In epistemology, people often differ from each other in terms of whether a concept is probabilistic or certain. Based on the effect of the presented IG and pull anti algorithm, we attempt to provide a comprehensive answer to this problem. Using the characters of hidden structures, we explain the difference between the macro and micro levels and the same difference between semantics and probability. In addition, the importance of attention is highlighted through the combination of symmetry and asymmetry included and the mechanism of chaos and collapse revealed in the presented model. Because the subject is involved in the expression of the object, representationalism is not complete. However, people undoubtedly reach a consensus based on the objectivity of the representation. Finally, we suggest that emotions could be used to regulate cognition. [ABSTRACT FROM AUTHOR]

We introduce a framework that can be used to model both mathematics and human reasoning about mathematics. This framework involves stochastic mathematical systems (SMSs), which are stochastic processes that generate pairs of questions and associated answers (with no explicit referents). We use the SMS framework to define normative conditions for mathematical reasoning, by defining a “calibration” relation between a pair of SMSs. The first SMS is the human reasoner, and the second is an “oracle” SMS that can be interpreted as deciding whether the question–answer pairs of the reasoner SMS are valid. To ground thinking, we understand the answers to questions given by this oracle to be the answers that would be given by an SMS representing the entire mathematical community in the infinite long run of the process of asking and answering questions. We then introduce a slight extension of SMSs to allow us to model both the physical universe and human reasoning about the physical universe. We then define a slightly different calibration relation appropriate for the case of scientific reasoning. In this case the first SMS represents a human scientist predicting the outcome of future experiments, while the second SMS represents the physical universe in which the scientist is embedded, with the question–answer pairs of that SMS being specifications of the experiments that will occur and the outcome of those experiments, respectively. Next we derive conditions justifying two important patterns of inference in both mathematical and scientific reasoning: (i) the practice of increasing one’s degree of belief in a claim as one observes increasingly many lines of evidence for that claim, and (ii) abduction, the practice of inferring a claim’s probability of being correct from its explanatory power with respect to some other claim that is already taken to hold for independent reasons. [ABSTRACT FROM AUTHOR]

English speakers use probabilistic phrases such as likely to communicate information about the probability or likelihood of events. Communication is successful to the extent that the listener grasps what the speaker means to convey and, if communication is successful, individuals can potentially coordinate their actions based on shared knowledge about uncertainty. We first assessed human ability to estimate the probability and the ambiguity (imprecision) of twenty-three probabilistic phrases in a coordination game in two different contexts, investment advice and medical advice. We then had GPT-4 (OpenAI), a Large Language Model, complete the same tasks as the human participants. We found that GPT-4’s estimates of probability both in the Investment and Medical Contexts were as close or closer to that of the human participants as the human participants’ estimates were to one another. However, further analyses of residuals disclosed small but significant differences between human and GPT-4 performance. Human probability estimates were compressed relative to those of GPT-4. Estimates of probability for both the human participants and GPT-4 were little affected by context. We propose that evaluation methods based on coordination games provide a systematic way to assess what GPT-4 and similar programs can and cannot do. [ABSTRACT FROM AUTHOR]

Standard accounts hold that regularities of behavior must be arbitrary to constitute a convention. Yet, there is growing consensus that conventionality is a graded phenomenon, and that conventions can be more or less natural. I develop an account of natural conventions that distinguishes two basic dimensions of conventional naturalness: a probabilistic dimension and an inherent one. A convention is probabilistically natural if it is likely to emerge in a population of agents, and inherently natural if its content is a regularity that scores high on relevant measures for naturalness. I motivate the proposal on conceptual grounds and then showcase its descriptive benefits by discussing two case studies in language: the tendency towards word-length optimality and the prevalence of shape opacity in spoken language vocabularies. [ABSTRACT FROM AUTHOR]

Holistic processing of face and non-face stimuli has been framed as a perceptual strategy, with classic hallmarks of holistic processing, such as the composite effect, reflecting a failure of selective attention, which is a consequence of this strategy. Further, evidence that holistic processing is impacted by training different patterns of attentional prioritization suggest that it may be a result of learned attention to the whole, which renders it difficult to attend to only part of a stimulus. If so, holistic processing should be modulated by the same factors that shape attentional selection, such as the probability that distracting or task-relevant information will be present. In contrast, other accounts suggest that it is the match to an internal face template that triggers specialized holistic processing mechanisms. Here we probed these accounts by manipulating the probability, across different testing sessions, that the task-irrelevant face part in the composite face task will contain task-congruent or -incongruent information. Attentional accounts of holistic processing predict that when the probability that the task-irrelevant part contains congruent information is low (25%), holistic processing should be attenuated compared to when this probability is high (75%). In contrast, template-based accounts of holistic face processing predict that it will be unaffected by manipulation given the integrity of the faces remains intact. Experiment 1 found evidence consistent with attentional accounts of holistic face processing and Experiment 2 extends these findings to holistic processing of non-face stimuli. These findings are broadly consistent with learned attention accounts of holistic processing. [ABSTRACT FROM AUTHOR]

Assessments of spatiotemporal fine particulate matter (PM2.5) concentrations are crucial for establishing risk maps and maintaining human health. This study spatiotemporally assessed PM2.5 concentrations in Taiwan by using multivariate indicator kriging (MVIK) according to current Taiwanese and US regulatory standards for annual average PM2.5 concentrations (15 and 12 μg/m3, respectively). First, multivariate integration was implemented to analyze data on PM2.5 concentrations for 2019–2021 and 2020–2022 because of no statistical difference of the 3-year PM2.5 data. MVIK was then used for modeling probabilities according to the two standards. Finally, quantile estimates on the basis of the occurrence probabilities of analyzing PM2.5 concentrations were employed to determine the optimal classifications for establishing risk maps according to the two PM2.5 standards. The study results indicated that the multivariate integration of temporal PM2.5 data in MVIK can effectively streamline the analytic process. The multivariate integration of 3-year PM2.5 data was suitable for assessing the risk categories of the regulatory standards for annual average PM2.5. The greatest estimated difference between the 2019–2021 and 2020–2022 multivariate integrations was in the Northern and Chumiao air quality regions. Because many air quality regions were in the PM2.5 categories of exceeding 12 μg/m3, the regulatory standard for annual average PM2.5 of 12 μg/m3 was inappropriate in Taiwan at this point in time according to assessing the 3-year spatiotemporal variability of PM2.5 concentrations. [ABSTRACT FROM AUTHOR]

The efficiency of the first-order reliability method (FORM) and the accuracy of Monte Carlo simulations (MCS) are coupled in probability-based designs of reinforced rock slopes, including a Hong Kong slope with exfoliation joints. Load–resistance duality is demonstrated and resolved automatically in a foundation on rock with a discontinuity plane. Other examples include the lengthy Hoek and Bray deterministic vectorial procedure for comprehensive pentahedral blocks with external load and bolt force, which is made efficient and more succinct before extending it to probability-based design via MCS-enhanced FORM. The FORM–MCS–FORM design procedure is proposed for cases with multiple failure modes. For cases with a dominant single failure mode, the time-saving importance sampling (IS) and the fast second-order reliability method (SORM) can be used in lieu of MCS. Two cases of 3D reinforced blocks (pentahedral and tetrahedral, respectively) with the possibility of multiple sliding modes are investigated. In the case of the reinforced pentahedral block, direct MCS shows that there is only one dominant failure mode, for which the efficient method of importance sampling at the FORM design point provides fast verification of the revised design. In the case of the reinforced tetrahedral block, there are multiple failure modes contributing to the total failure probability, for which the proposed MCS-enhanced FORM procedure is demonstrated to be essential. Comparisons are made between Excel MCS and MATLAB MCS. Highlights: Probability-based design of a Hong Kong slope via coupled FORM and Monte Carlo methods. Efficient analysis of a bolted pentahedral block based on Hoek-Bray procedure and Excel Solver. New extension of Low-and-Tang FORM algorithm to MCS involving correlated nonnormals. FORM-MCS-FORM method for design of 3D rock slopes with multiple failure domains. Importance sampling or SORM in lieu of MCS for cases with a dominant single failure mode. [ABSTRACT FROM AUTHOR]

Can we feel that an unrealized outcome nearly happened if it was never possible in the first place? People often consider counterfactual events that did not happen, and some counterfactuals seem so close to reality that people say they "almost" or "easily could have" happened. Across four preregistered experiments (total N = 1,228), we investigated how judgments of counterfactual closeness depend on possibility, and whether this varies across two kinds of close counterfactuals. In judging whether outcomes almost happened, participants were more strongly impacted by possibility than by incremental manipulations of probability. In contrast, when judging whether outcomes easily could have happened, participants treated the distinction between impossible and possible like any other variation in probability. Both kinds of judgments were also impacted by propensity, though these effects were comparatively small. Together, these findings reveal novel differences between the two kinds of close counterfactuals and suggest that while possibility is privileged when judging what almost happened, probability is the focus when judging what easily could have happened. [ABSTRACT FROM AUTHOR]

Introduction/objectives: To assess and compare the performance of the giant cell arteritis probability score (GCAPS), Ing score, Bhavsar-Khalidi score (BK score), color Doppler ultrasound (CDUS) halo count, and halo score, to predict a final diagnosis of giant cell arteritis (GCA). Method: A prospective cohort study was conducted from April to December 2021. Patients with suspected new-onset GCA referred to our quaternary CDUS clinic were included. Data required to calculate each clinical and CDUS probability score was systematically collected at the initial visit. Final diagnosis of GCA was confirmed clinically 6 months after the initial visit, by two blinded vasculitis specialists. Diagnostic accuracy and receiver operator characteristic (ROC) curves for each clinical and CDUS prediction scores were assessed. Results: Two hundred patients with suspected new-onset GCA were included: 58 with confirmed GCA and 142 without GCA. All patients with GCA satisfied the 2022 ACR/EULAR classification criteria. A total of 5/15 patients with GCA had a positive temporal artery biopsy. For clinical probability scores, the GCAPS showed the best sensitivity (Se, 0.983), whereas the BK score showed the best specificity (Sp, 0.711). As for CDUS, a halo count of 1 or more was found to have a Se of 0.966 and a Sp of 0.979. Combining concordant results of clinical and CDUS prediction scores showed excellent performance in predicting a final diagnosis of GCA. Conclusion: Using a combination of clinical score and CDUS halo count provided an accurate GCA prediction method which should be used in the setting of GCA Fast-Track clinics. Key Points • In this prospective cohort of participants with suspected GCA, 3 clinical prediction tools and 2 ultrasound scores were compared head-to-head to predict a final diagnosis of GCA. • For clinical prediction tools, the giant cell arteritis probability score (GCAPS) had the highest sensitivity, whereas the Bhavsar-Khalidi score (BK score) had the highest specificity. • Ultrasound halo count was both sensitive and specific in predicting GCA. • Combination of a clinical prediction tool such as the GCAPS, with ultrasound halo count, provides an accurate method to predict GCA. [ABSTRACT FROM AUTHOR]

Owing to the current lack of plausible and exhaustive physical pre-eruptive models, often volcanologists rely on the observation of monitoring anomalies to track the evolution of volcanic unrest episodes. Taking advantage from the work made in the development of Bayesian Event Trees (BET), here we formalize an entropy-based model to translate the observation of anomalies into probability of a specific volcanic event of interest. The model is quite general and it could be used as a stand-alone eruption forecasting tool or to set up conditional probabilities for methodologies like the BET and of the Bayesian Belief Network (BBN). The proposed model has some important features worth noting: (i) it is rooted in a coherent logic, which gives a physical sense to the heuristic information of volcanologists in terms of entropy; (ii) it is fully transparent and can be established in advance of a crisis, making the results reproducible and revisable, providing a transparent audit trail that reduces the overall degree of subjectivity in communication with civil authorities; (iii) it can be embedded in a unified probabilistic framework, which provides an univocal taxonomy of different kinds of uncertainty affecting the forecast and handles these uncertainties in a formal way. Finally, for the sake of example, we apply the procedure to track the evolution of the 1982–1984 phase of unrest at Campi Flegrei. [ABSTRACT FROM AUTHOR]

The aim of this paper is to argue for a revised and precisified version of the infamous Verifiability Criterion for the meaningfulness of declarative sentences. The argument is based on independently plausible premises concerning probabilistic confirmation and meaning as context-change potential, it is shown to be logically valid, and its ramifications for potential applications of the criterion are being discussed. Although the paper is not historical but systematic, the criterion thus vindicated will resemble the original one(s) in some important ways. At the same time, it will also be more modest insofar as meaningfulness will turn out to be relativized linguistically and probabilistically, and different choices of the linguistic and probabilistic parameters may lead to different verdicts on meaningfulness. [ABSTRACT FROM AUTHOR]

The automation of the engineering procedure of calibrating instrumentation by introducing digital technology of computer vision into the production process is assessed. Optimization of the production process by means of digital technology of computer vision eliminates the adverse effect of some errors and, by reducing the time spent on certification, diminishes the impact of high-temperature processes on measuring equipment. An operational characteristic of calibration is developed taking into account subjective errors, such as the interpolation and parallax errors, which occur if testing is carried out by an operator. The determined dependence is compared with the plot based on the calibration indicators in introducing computer vision technology into the production process. [ABSTRACT FROM AUTHOR]

A series-parallel graph is a graph that does not contain a complete graph with four vertices as a minor. An explicit formula for the number of labeled series-parallel tricyclic graphs with a given number of vertices is obtained, and the corresponding asymptotics for the number of such graphs with a large number of vertices is found. We prove that under a uniform probability distribution, the probability that the labeled tricyclic graph is a series-parallel graph is asymptotically equal to 13/15. [ABSTRACT FROM AUTHOR]

The binomial distribution is often used in modeling, including in applied climatology, when assessing the likelihood of adverse or dangerous climate-related impacts. The article outlines an algebraic algorithm for obtaining such estimates based on climate monitoring data or modeling data. Using only algebraic operations in calculations minimizes calculation time, which is important when performing detailed global assessments. As an example of such a calculation, the result of an assessment of the global climatic range of a dangerous insect pest of forest and garden trees and shrubs, the gypsy moth, is given. [ABSTRACT FROM AUTHOR]

A minimal mathematical approach is used to state Landauer's principle in a precise, general way. The results are obtained by means of a rigorous development which is based on the use of quantum statistical mechanics. A mathematical form of the principle results as an equality rather than an inequality. The equality version does imply the original statement of the principle as introduced by Landauer. [ABSTRACT FROM AUTHOR]

Findings on children's proportional reasoning abilities strongly vary across studies. This might be due to the different contexts that can be used in proportional problems: fair-sharing, mixtures, and probability. A review of the scientific literature suggests that the context of proportional problems may not only impact the difficulty of the problem, but that it also plays an important role in how children approach the problems. In other words, different contexts might elicit different (erroneous) thinking strategies. The aim of the present study was to investigate the role of context in third graders' (n = 305) proportional reasoning abilities. Results showed that children performed significantly better in a fair-sharing context compared to a mixture and a probability context. No evidence was found for a difference in performance on the mixture and the probability context. However, the kind of erroneous answers that were given in the mixture and probability context differed slightly, with more additive answers in the mixture context and more one-dimensional answers in the probability context. These findings suggest that the type of answers elicited by proportional problems might depend on the specific context in which the problem is presented. [ABSTRACT FROM AUTHOR]

Decisions made under uncertainty often are considered according to their perceived subjective value. We move beyond this traditional framework to explore the hypothesis that conceptual representations of uncertainty influence risky choice. Results reveal that uncertainty concepts are represented along a dimension that jointly captures probabilistic and valenced features of the conceptual space. These uncertainty representations predict the degree to which an individual engages in risky decision-making. Moreover, we find that most individuals have two largely distinct representations: one for uncertainty and another for certainty. In contrast, a minority of individuals exhibit substantial overlap between their representations of uncertainty and certainty. Together, these findings reveal the relationship between the conceptualization of uncertainty and risky decisions. [ABSTRACT FROM AUTHOR]

Extracting statistical regularities from the environment is crucial for survival. It allows us to learn cues for where and when future events will occur. Can we learn these associations even when the cues are not consciously perceived? Can these unconscious processes integrate information over long periods of time? We show that human visual system can track the probability of location contingency between an unconscious prime and a conscious target over a period of time of minutes. In a series of psychophysical experiments, we adopted an exogenous priming paradigm and manipulated the location contingency between a masked prime and a visible target (i.e., how likely the prime location predicted the target location). The prime's invisibility was verified both subjectively and objectively. Although the participants were unaware of both the existence of the prime and the prime-target contingency, our results showed that the probability of location contingency was tracked and manifested in the subsequent priming effect. When participants were first entrained into the fully predictive prime-target probability, they exhibited faster responses to the more predictive location. On the contrary, when no contingency existed between the prime and target initially, participants later showed faster responses to the less predictive location. These results were replicated in two more experiments with increased statistical power and a fine-grained delineation of prime awareness. Together, we report that the human visual system is capable of tracking unconscious probability over a period of time, demonstrating how implicit and uncertain regularity guides behavior. [ABSTRACT FROM AUTHOR]

Earthquakes are prominent natural hazards that cause loss of life and property in residential areas in the world. The Aegean Graben system is geologically under the influence of the Western Anatolian Opening Regime. There are many active fault lines that can be a source of earthquake activity in the Aegean Graben system. Many earthquakes have been recorded in the region, which have caused serious material and moral damages from the past to the present. This situation reveals the importance of investigation this region in detail and by this way is possible to reduce the risks and consequences of earthquakes. In the study, earthquake data from three different earthquake catalogs were examined, and the earthquakes recorded between 1970 and 2020 in the region were declustered and homogenized in the scale of magnitude wave (Mw). Then, the data are clustered based on the seismic classification via k-means cluster analysis. By this way, the predictions for sequential transition of earthquakes within time and magnitude of the earthquakes are analyzed with a stochastic model, namely Markov chain. It has been concluded that the row probability values of the transition matrices of the earthquake transition probabilities between the clusters of the Aegean Region are fixed values depending on time. We also found an equilibrium distribution for the region. Hence, the probability of an earthquake in Cluster 1 in the region is 30%, Cluster 2–33% and Cluster 3–37%, respectively. We then obtain mean passage time of the earthquakes in each cluster. The results suggest that all clusters have similar characteristics as regard to earthquake sequencing. For these reasons, we finally study the without clustering to find the magnitude transitions depending on the time with Markov chain analysis. [ABSTRACT FROM AUTHOR]

Shear wave velocity (Vs) offers engineers a promising alternative means to evaluate liquefaction resistance of sandy soils. However, the Vs-based probabilistic evaluation of soil liquefaction using machine learning method or Bayesian network method is limited. To this end, an attractive probability framework incorporating grey wolf optimization optimized kernel extreme learning machine (GWO–KLEM), and Bayesian theorem was developed for Vs-based probabilistic liquefaction model. The framework mainly includes two components: (1) an GWO–KLEM-based metamodel is developed to approximate the limit state function and identify the uncertain location of the boundary between the liquefaction and the non-liquefaction points; (2) the Bayesian theorem along with total probability theorem is used to integrate the prior knowledge with the site-specific Vs data for the updated distributions of input parameters. Then, a large number of equivalent samples from the above integrated knowledge can be generated based on the Markov chain Monte Carlo simulation; thus the probability of liquefaction can be calculated. Based on searching technique, perspective under simplified framework is also developed. The results show that limit state function searched by GWO–KELM is reliable and the proposed Vs-based probabilistic liquefaction model has a very good performance. Details on the development of the proposed system are presented, along with comparisons of the results obtained by this system with existing methods. Overall, the proposed method is advantageous and reliable for probabilistic assessment of liquefaction potential. [ABSTRACT FROM AUTHOR]

Grover's unstructured quantum search algorithm gives a quadratic speedup over classical linear search, provided that multiple accesses to the oracle are possible. In this paper, we show that in dealing with NP-complete decision-version problems, the quantum computing paradigm still outperforms classical computation, even if only one invocation of the oracle is allowed. The superiority of the quantum approach under such a restrictive condition can often be maintained even if a simple measurement strategy is chosen. A quantum decider utilizing only Hadamard gates and measurements in the computational basis has a better chance of discriminating between a problem with solution(s) and one without, when compared to the best separation achieved by a classical decider. In addition, the simple quantum measurement strategy is remarkably close to the optimal discriminating measurement, which itself is considerably more complex to devise and implement. If we further require the decider to be unambiguous (any definitive answer must be error-free), then a general positive operator-valued measurement can be devised to classify a problem as unsolvable, with some probability, after one consultation of the oracle. Such a feature remains impossible for a classical decider, even after any less than exhaustive oracle invocations. The inherent probabilistic nature of quantum mechanics seems to be at the heart of the advantage quantum computing exhibits over classical computation, in the context of deciding NP-complete problems based on a single oracle query. [ABSTRACT FROM AUTHOR]

The strict dominance principle that a wager always paying better than another is rationally preferable is one of the least controversial principles in decision theory. I shall show that (given the Axiom of Choice) there is a contradiction between strict dominance and plausible isomorphism or symmetry conditions, by showing how in several natural cases one can construct isomorphic wagers one of which strictly dominates the other. In particular, I will show that there is a pair of wagers on the outcomes of a uniform spinner which differ simply in where the zero degrees point of the spinner is defined to be but where one wager dominates the other. I shall also argue that someone who accepts Williamson's famous argument that the probability of an infinite sequence of heads is zero should accept the symmetry conditions, and thus has reason to weaken the strict dominance principle, and I shall propose a restriction of the principle to "implementable" wagers. Our main result also has implications for social choice principles. [ABSTRACT FROM AUTHOR]

This paper considers aircraft landing on a carrier. We propose two schemes for calculating, first, the probability of a go-around due to disengaging the arresting gear and, second, the maximum descent of the aircraft's trajectory with respect to the deck level immediately after leaving the deck. The instant to increase the aircraft's thrust before touching the deck is a control parameter affecting these characteristics. The requirements imposed on the probability of a go-around and the maximum descent of the aircraft's trajectory allow determining an admissible range for the thrust increase instant. Numerical results are presented for a real aircraft landing on a real carrier. [ABSTRACT FROM AUTHOR]

Conditionals with conditional constituents pose challenges for the Thesis, the idea that the probability of a conditional is the corresponding conditional probability. This note is concerned with two proposals for overcoming those challenges, both inspired by early work of van Fraassen: the Bernoulli Semantics associated with Stalnaker and Jeffrey, and augmented with a mechanism for obtaining "local probabilities" by Kaufmann; and a proposal by Bacon which I dub Ordinal Semantics. Despite differences in mathematical details and emphasis of presentation, both proposals lend themselves for use as a basis for a modal-theoretic interpretation of embedded conditionals. The goal of this note is to compare the two frameworks by implementing a model for the interpretation of conditionals in each, based on the same underlying probability model for non-conditional sentences. I show that in the Ordinal model, certain sentences are assigned probabilities that do not accord with intuitions. This problem is familiar from the literature on Bernoulli models and can be addressed by introducing Kaufmann-style local probabilities into Ordinal models. I then show that Bernoulli Semantics has other limitations, in that it assigns probabilities in violation of the Thesis to certain very complex formulas. The upshot is that a fusion of the theories may be our best shot at getting the predictions right. [ABSTRACT FROM AUTHOR]

Flash Flood Guidance (FFG) is a rainfall threshold which initiates flooding in streams. It merely provides a binary output (yes or no) which has large uncertainties in forecasting. In this paper, we propose a new method by combining FFG with the Frequentist method to present the probability of flash flood occurrence based on historical rainfall events. We first calculated deviation from the log transform rainfall data leading to flash floods. Kernel Density Estimation (KDE) was used to describe the deviation. Normal Distribution Function (NDF) was chosen to fit the KDE output and to calculate probabilities of flooding as per the Frequentist FFG. In order to aid decision making, three probability thresholds (10, 20 and 60%) were used for defining four flood risk classes, namely very low, low, significant and high, and were colour coded respectively as green, yellow, orange and red. The proposed Frequentist FFG method was then applied to the Posina River basin in Italy. Comparison of forecasts from the conventional FFG (with probability 0 or 1) and Frequentist FFG for 94 6-hourly rainfall events, including 23 flood events, shows that the Frequentist FFG presented a probability of flooding varying from 0 to 100% and the corresponding risk class can be used to reduce false alarms while still reducing the disaster risk. The application of the developed approach to the Posina basin shows that decision making regarding flash forecasting is easier with the presented approach compared to the traditional FFG approach. [ABSTRACT FROM AUTHOR]

Strainburst poses significant risks to the safety of workers in deep underground engineering. Assessing strainburst potential plays a crucial role in disaster prevention. Due to the anisotropy and heterogeneity of rock mass, it is essential to quantify the strainburst potential from the perspective of probability. This study aims to propose a methodology that integrates Monte Carlo simulation (MCS) and machine learning (ML) algorithms to evaluate the probability of strainburst potential. First, a numerical model based on damage initiation and spalling limit (DISL) method is established. Then, a novel indicator, absolute local energy release rate (ALERR), is proposed to assess strainburst potential, which describes the absolute value of elastic strain energy released after rock mass failure. The location of the maximum value of ALERR is used to determine the depth of outburst pit, which is adopted to evaluate the strainburst potential level. So, the quantitative relationship between strainburst potential and ALERR can be established. Thereafter, a strainburst dataset including six variables and the depth of outburst pit is obtained based on the MCS method and numerical model. To improve the computational efficiency, seven different ML algorithms are integrated with MCS to calculate the probability of strainburst potential, respectively. Finally, the proposed methodology is used for the strainburst potential evaluation in the 3# headrace tunnel of Jinping II hydropower station. Results show that random forest (RF) and gradient boosting (GB) algorithms have better evaluation performance and can be combined with MCS to calculate the probability of strainburst potential reliably. The proposed methodology can provide valuable guidance for the probability assessment of strainburst potential. Highlights: A new methodology that integrates Monte Carlo simulation (MCS) and machine learning (ML) algorithms is proposed to evaluate the probability of strainburst potential. A novel indicator, absolute local energy release rate (ALERR), is proposed to assess strainburst potential. A numerical model, which combines MCS and damage initiation and spalling limit (DISL) approaches, is established to simultaneously simulate the brittle failure behavior of hard rock and variability of rock mechanics parameters. [ABSTRACT FROM AUTHOR]

Scientific and methodological aspects of ensuring the safety of offshore subsea pipelines according to accident risk criteria are considered. A conceptual approach to assessing the hazard of defects according to risk criteria is formulated by analyzing modern norms and requirements on pipeline design. A probabilistic model for assessing the risk of accidents at offshore subsea pipelines considering the randomness of defects and damage from accidents is developed. The criterial conditions for the permissibility of defects in pipelines are formulated. Two conceptual directions for developing a procedural framework for calculating the permissible defects versus risk criteria are proposed on this basis. The first direction consists in elaborating semi-probabilistic calculation procedures using differentiated margin factors, considering the accident risk level. The second direction consists in solving the problem of the probability of pipeline failure, taking into account the restrictions in the form of a preset risk value. The probability and scale of accidents are linked through a risk matrix. The calculation methodology is developed using a semi-probabilistic concept for the most typical defects in offshore subsea pipelines. The suitability of the pipeline for operation after in-line diagnostics is determined using a three-level assessment of permissible defect sizes. The first level is basic and determines permissible defect sizes according to the strength criteria for pipelines exposed to the main loads, i.e., internal overpressure and external hydrostatic external head. The second level is extended and determines permissible defect sizes according to the strength criteria, taking into account the impact of additional longitudinal and bending loads on pipelines. The third level is special and determines permissible dimensions of cracks and cracklike defects according to the crack resistance characteristics of the pipeline metal. The novelty of the method consists in the justification of the margin factors through the failure probability levels corresponding to a preset class of damage and losses. A scheme for making decisions on the permissibility of defects according to risk criteria has been developed. An example of the assessment of the hazard of defects in offshore subsea pipelines is presented. [ABSTRACT FROM AUTHOR]

Results of one of the analytical solutions for the probabilistic parameters of the general theory of spatial transitions of atoms developed by the author and of calculations of these parameters by the standard methods of quantum mechanics are compared. Coincidence of the results is stated. [ABSTRACT FROM AUTHOR]

Context-dependent sensitivities of parameters and reliability-based design (RBD) of rock slopes are the subjects of this paper. The similarities and differences between the design points in RBD and those of partial factor design methods are discussed. It is demonstrated that partial factors provided by the design point of the first-order reliability method (FORM) can provide case-specific insights and guidance to partial factor design methods like Eurocode 7 (EC7) and the load and resistance factor design (LRFD). It is suggested that conducting RBD-via-FORM in tandem with partial factor designs is more illuminating and meaningful than calibration of partial factors of parameters which can be sensitive in one case but insensitive in another case. Three cases are analysed probabilistically with respect to plane sliding in rock slopes with one or more discontinuities. In the first two cases, different deterministic solution procedures are used for the single block and two-block mechanisms, for comparison with stereographic projection method and closed form equation, respectively, prior to extending the cases into RBD. The third case involves a failed slope in a limestone quarry, analysed using FORM in this paper, for comparison with Monte Carlo simulation. Highlights: Alternative deterministic computations obtain same solutions as Goodman's deterministic results for single-block slide and two-block slide. Extend Goodman's deterministic single-block and two-block slides to reliability analysis accounting for input uncertainties. Reliability-based design (RBD) via the first-order reliability method (FORM) provides enlightening information at the FORM design point on parameter sensitivities. RBD-via-FORM automatically reflects context-dependent sensitivities of parameters at the design point of FORM, and can provide insights for Eurocode 7 and LRFD. FORM analysis of a failed slope confirms inadequate reliability. Failure probability from reliability index compares well with Monte Carlo simulation. An efficient procedure for rapid convergence of RBD-via-FORM using the Excel Forecast function. [ABSTRACT FROM AUTHOR]

Under axial tensile-compression loads, fatigue behaviors of a circular lap welding joint of the cone and pipe using stainless steels of different grades with a circular stress raiser were examined. The internal stress raiser caused root fatigue cracks. The fracture starting site was at the weld interface, which had a small weld toe radius inducing stress concentration. When the weld toe radius approached zero, the fatigue strength and scatter depended on the weld opening angle. The failure criteria and prediction under axial loading could be based on the effective stress concentration factor. The uniform scatter band model was used to examine the test data. With the highest coefficient of determination of 0.8164, the semi-logarithmic bilinear model best fitted the actual data. The 3P Weibull distribution most closely matched the Benard's estimate with a coefficient of determination of 0.9728. The strength scatter bands of the welded joint were much larger than those of the plane sheet, depending on the degrees of stress concentrations and defects. The plane sheet to welded joint's fatigue strength ratio rose with fatigue life and was particularly high at low failure probability. [ABSTRACT FROM AUTHOR]

In (Barbero and Sandu 2020 Journal of Philosophical Logic, 50, 471-521), we showed that languages encompassing interventionist counterfactuals and causal notions based on them (as e.g. in Pearl’s and Woodward’s manipulationist approaches to causation) as well as information-theoretic notions (such as learning and dependence) can be interpreted in a semantic framework which combines the traditions of structural equation modeling and of team semantics. We now present a further extension of this framework (causal multiteams) which allows us to talk about probabilistic causal statements. We analyze the expressivity resources of two causal-probabilistic languages, one finitary and one infinitary. We show that many causal-probabilistic notions from the literature on causal inference can already be expressed in the finitary language, and we prove a normal form theorem that throws a new light on Pearl’s “ladder of causation”. In addition, we provide an exact semantic characterization of the infinitary language, which shows that this language captures precisely those causal-probabilistic statements that do not commit us to any specific interpretation of probability; and we prove that no usual, countable language is apt for this task. [ABSTRACT FROM AUTHOR]

The Marmara Region is an active tectonic region in northwestern Türkiye, which comprises some important strike-slip active fault mechanisms and important tectonic units, located near the western part of the North Anatolian Fault Zone. In the historical and instrumental period, the Marmara Region experienced large/devastating earthquakes. Considering this continuous activity, in this study, we investigate the tectonic structure and performed future seismic hazard estimation of the region based on some seismotectonic parameters. For this evaluation, we plot the Coulomb stress change maps of 1912 Mürefte-Şarköy, 1953 Yenice-Gönen and 1999 İzmit mainshocks with the earthquakes (MW ≥ 4.5) that occurred in the study region after 2003. For the estimation of b-value, occurrence probabilities and return periods of earthquakes, we used a homogenous local seismicity catalogue consisting of 119.029 events for the period between 1912 and 2023. In the findings of this study, the lower b-values and increasing Coulomb stress changes which are trigger stress failure compatible are observed in the west and northwest of the Marmara Sea. In contrast, the higher/moderate b-values and decreasing Coulomb stress values are observed in the east and southeast of the Marmara Sea. The results of probability assessments show that an earthquake with Mw = 6.5 may occur with a probability of 98% in the west of the Marmara Sea after 2025. As a remarkable fact, a comprehensive assessment of these types of variables will supply important findings for earthquake hazard and potential in the study region. [ABSTRACT FROM AUTHOR]

Often our expectations are set by sampling many times from the same distribution. When that distribution changes, so should our expectations. If we want to decide whether to take our umbrella today we need to have tracked, and updated, our estimate of the probability of rain by reference to recent temperatures and precipitation. Under debate is whether we update our mental estimates of probabilities given each new incoming piece of evidence or whether we stick with a current estimate until it becomes clearly in need of change. Previous research has suggested that participant estimates of running probabilities are not updated on every trial, but only intermittently. This has been used to support change-point models of probability updating. However, such a pattern could also be explained by the way common laboratory procedures impose a motor cost to update the probability report. This study was designed to remove the motor confound. Our procedure required similar motor actions for both changing and maintaining one’s probability estimate. At a group level, motor cost did affect updating frequency and removing the default response option encouraged more frequent updating. However, intermittent updating response patterns did not disappear completely. Despite this equivalence in response effort, some participants, even when forced to make a new estimate on every trial, continued to update rarely while other participants meticulously updated every trial. We conclude deliberate updating frequency is heterogenous but intermittent updating is not simply an artifact of motor cost. [ABSTRACT FROM AUTHOR]

Fifth-generation district heating systems have appeared in the heating supply of modern cities. There is a growing demand for the use of renewable energy sources, the most significant of which is geothermal energy. Implementing district heating systems is very costly, and reducing investment and operating costs requires accurate forecasting of expected heating demands and uncertainty analysis. The design of district heating systems begins with determining the heat demand to be supplied. The heating demand maximum occurring with a 1% frequency (24-h duration) is called the representative heating demand. In our study, we deal with the probability theory of heating demands. Heating demands are also uncertain primarily due to the uncertainties in meteorological and weather characteristics and, in a mathematical sense, are random variables. We must emphasize that any description that follows a deterministic approach in determining heating demands does not meet the criteria of modern science and can lead to severe planning and operational errors. In our study, following a probabilistic approach, we present a mathematical model that allows the determination of heating demands using probabilistic tools. With the help of the model, we can determine the low-risk representative heat demand and, through this, assess whether the available heat production capacity is sufficient with the prescribed safety or whether its expansion is necessary. Furthermore, in operation, we can prepare with the least risk of the short- and long-term forecasted values of meteorological factors. In our study, using the presented probabilistic method, we proved that for the most common prefabricated housing units in Hungary (approximately 500,000), there is a 30% uncertainty in the representative—previously accepted as 5000 W—heat demand, which, if considered in operation, can avoid significant costs. Our investigations showed that under representative meteorological conditions, the standard deviation of the expected heat demand is 1119 W, while the expected value is 3700 W. With the help of the presented model, the errors and uncertainties in the parameters used to calculate heat demand can be extensively analyzed. [ABSTRACT FROM AUTHOR]

Phreatic explosions at volcanoes are difficult to forecast but can be locally devastating, as illustrated by the deadly 2019 Whakaari (New Zealand) eruption. Quantifying eruption likelihood is essential for risk calculations that underpin volcano access decisions and disaster response. But estimating eruption probabilities is notoriously difficult for sudden onset eruptions. Here, we describe two retrospectively developed models for short-term (48 h) probabilistic forecasting of phreatic eruptions at Whakaari. The models are based on a pseudo-prospective analysis of seven Whakaari eruptions whose precursors were identified by time series feature engineering of continuous seismic data. The first model, an optimized warning system, could anticipate six out of seven eruptions at the cost of 14 warning days each year. While a warning is in effect, the probability of eruption is about 8% in 48 h, which is about 126 times higher than outside the warning. The second model used isotonic calibration to translate the output of the forecast model onto a probability scale. When applied pseudo-prospectively in the 48 h prior to the December 2019 eruption, it indicated an eruption probability up to 400 times higher than the background. Finally, we quantified the accuracy of these seismic data-driven forecasts, alongside an observatory expert elicitation that used multiple data sources. To do this, we used a forecast skill score that was benchmarked against the average rate of eruptions at Whakaari between 2011 and 2019. This exercise highlights the conditions under which the three different forecasting approaches perform well and where potential improvements could be made. [ABSTRACT FROM AUTHOR]

Efficient and significant empirical estimate of the multivariate regression parameters will be helpful for the policy maker to make the right decisions about sophisticated interrelated issues in the dynamic world. Since the end of the twentieth century, statisticians are going forward to develop unique working methodology for estimating and testing restricted parameters. This paper reviews existing methods and suggests modified maximum likelihood estimator, modified multivariate t statistic and modified joint confidence interval to get efficient estimates for exact linear restricted parameters of multivariate regression with continuous responses. A Monte Carlo experiment is conducted to examine relative performance of the modified methods. The modified methods are found to perform better than the existing methods. [ABSTRACT FROM AUTHOR]

Probabilistic information is used increasingly, from medical research to weather forecasting. The relationship between probability and causality requires an acceptable philosophical account. Social work, which contributes to healthy wellbeing, increasingly uses language of probabilistic causal relationships between harms and subsequent limitations to healthy functioning. This paper explores causal understandings of probabilistic knowledge using concepts of the theologian, Thomas Aquinas. Social welfare terminology regarding risk (such as factors that are 'causative of' child abuse) is explored using epistemological concepts from scholastic philosophy. Aquinas' anthropological concepts related to modern 'risk science' and his concepts of rationality, harm and prudence are applied to contemporary social welfare. [ABSTRACT FROM AUTHOR]

Two hypotheses were tested: (1) the deflecting motion of fly balls caused by aerodynamic effects varies between the pull side and opposite side of the fair territory, and (2) the probability of flyout is lower on the pull side than the opposite side in Japan's professional baseball games. From all radar-tracking outputs of official games in 2018–2019, fly balls that resulted in outs or base hits were selected for analysis (N = 25,413), and indices representing horizontal and vertical deflecting motions of fly balls were computed and compared between the pull side and opposite side. A machine learning algorithm was used to construct a model to predict the probability of flyout from the kinematic characteristics of fly balls. Flyout zones where the probability of flyout was > 0.6 were computed for a systematically constructed set of fly balls having identical distribution between the pull side and opposite side. The results showed that: (1) most fly balls landing on the opposite side deflected in the same direction whereas the pulled fly balls deflected to either direction, (2) the pulled low fly balls had greater variability in the deflecting motions than the opposite side counterpart, (3) overall probability of flyout of the low fly balls was lower in the pull side (0.41) than the opposite side (0.49), and (4) the flyout zone of an outfielder in the pull side (mean = 698 m2) for low fly balls was smaller than that of the others (≥ 779 m2). The hypotheses were supported. The pulled low fly balls had substantial variations in the direction and magnitude of deflections, which might have reduced the flyout zone on the pull side. [ABSTRACT FROM AUTHOR]

While much has been written about the probabilities referenced in Plantinga's Evolutionary Argument Against Naturalism, insufficient attention has been paid to the question of how these probabilities are to be interpreted. In this paper, I demonstrate that objective interpretations entail the denial of traditional theism, making them unsuitable for Plantinga's purpose here. With respect to epistemic interpretations, I note that standard Bayesianism is too permissive for Plantinga's purposes. I then argue that Plantinga's use of the Principle of Indifference is at odds with his Reformed Epistemology. I conclude with some suggestions for how defenders of the argument might proceed. [ABSTRACT FROM AUTHOR]

This study summarizes the findings of an attitude survey focused on people's perceptions of seismic hazard maps, which illustrate the risk of an earthquake in each location throughout Japan. These seismic hazard maps depict the likelihood of an earthquake with a seismic intensity of "6 Lower" or more within 30 years, with 3.0% being considered a high possibility. The 3.0% occurrence probability within 30 years can be reworded to 2.0% occurrence probability within 20 years, 0.1% occurrence probability within a year, 4.9% occurrence probability within 50 years, or 39.4% occurrence probability within 500 years when being converted according to a Poisson distribution. In this study, we convert the occurrence probability within 30 years in the seismic hazard maps to obtain that within a year up to that within 1000 years, present the involved risk and demonstrate the yearly probability of the people who see the maps becoming most convinced of the need for countermeasures. Although those are shorter than the occurrence probability within 30 years anyway, it is a characteristic that the peaks existed at the occurrence probability within 10–20 years, not at the occurrence probability within one year or five years. However, the results changed according to the age of the people viewing the maps, and it was when the risk was presented as the occurrence probabilities within 20 and 30 years for the people in their 20–40 s, while it was when the risk was presented the occurrence probabilities within 10 years for the people in their 50–60 s, the perception toward the need of countermeasures increased the most. In addition, regardless of gender and place of residence (coast of the Sea of Japan or the Pacific coast), the perception toward the need of countermeasures peaked at the occurrence probabilities within 10 and 20 years. [ABSTRACT FROM AUTHOR]

People often prefer simpler explanations, defined as those that posit the presence of fewer causes (e.g., positing the presence of a single cause, Cause A, rather than two causes, Causes B and C, to explain observed effects). Here, we test one hypothesis about the mechanisms underlying this preference: that people tend to reason as if they are using “agnostic” explanations, which remain neutral about the presence/absence of additional causes (e.g., comparing “A” vs. “B and C,” while remaining neutral about the status of B and C when considering “A,” or of A when considering “B and C”), even in cases where “atheist” explanations, which specify the absence of additional causes (e.g., “A and not B or C” vs. “B and C and not A”), are more appropriate. Three studies with US-based samples (total N = 982) tested this idea by using scenarios for which agnostic and atheist strategies produce diverging simplicity/complexity preferences, and asking participants to compare explanations provided in atheist form. Results suggest that people tend to ignore absent causes, thus overgeneralizing agnostic strategies, which can produce preferences for simpler explanations even when the complex explanation is objectively more probable. However, these unwarranted preferences were reduced by manipulations that encouraged participants to consider absent causes: making absences necessary to produce the effects (Study 2), or describing absences as causes that produce alternative effects (Study 3). These results shed light on the mechanisms driving preferences for simpler explanations, and on when these mechanisms are likely to lead people astray. [ABSTRACT FROM AUTHOR]

Cognitive Internet of Things (CIoT) is a new subfield of the Internet of Things (IoT) that aims to integrate cognition into the IoT's architecture and design. Various CIoT applications require techniques to inevitably extract machine-understandable concepts from unprocessed sensory data to provide value-added insights about CIoT devices and their users. The time series classification, which is used for the concept's extraction poses challenges to many applications across various domains, i.e., dimensionality reduction strategies have been suggested as an effective method to decrease the dimensionality of time series. The most common approach for time-series classification is the symbolic aggregate approximation (SAX). However, its main drawback is that it does not select the most significant point from the segment during the piecewise aggregate approximation (PAA) stage. The situation is cumbersome when data is heterogeneous and massive. Therefore, this research presents a novel technique for the selection of the most significant point from a segment during the PAA stage in SAX. The proposed technique chooses the maximum informative point as the most significant point using the probabilistic interpretation of sensory data with an appropriate copula design. The appropriate copula is selected using the minimum akaike information criteria (AIC) value. Subsequently, the modified SAX considers the maximum informative points instead of a selection of mean/max/extreme data points on a given segment during the PAA stage. The experimental evaluation of the environmental dataset reveals that the proposed method is more accurate and computationally efficient than classic SAX. Also, for cross-validation it computes the entropy of the information point (i-value) from each dataset to verify the successful transformation of normal data points to information points. [ABSTRACT FROM AUTHOR]

This work is a generalization and further development of our previous studies of systems of atoms with spatial configurations 1 + 3, 2 + 3, and 1 + 2 + 3. Some results of these studies related to the probabilistic transitions of atoms from one to another configuration and the numbers of atoms in these configurations are obtained from the results of this work as a special case. [ABSTRACT FROM AUTHOR]

We study large uniform random bipartite quadrangulations whose genus grows linearly with the number of faces. Their local convergence was recently established by Budzinski and the author [9-10]. Here we study several properties of these objects which are not captured by the local topology. Namely we show that balls around the root are planar with high probability up to logarithmic radius, and we prove that there exist non-contractible cycles of constant length with positive probability. [ABSTRACT FROM AUTHOR]

This paper models knowledge in cases where an agent has multiple experiences over time. Using this model, we introduce a series of observations that undermine the pretheoretic idea that the evidential significance of experience depends on the extent to which that experience matches the world. On the basis of these observations, we model knowledge in terms of what is likely given the agent's experience. An agent knows p when p is implied by her epistemic possibilities. A world is epistemically possible when its probability given the agent's experiences is not significantly lower than the probability of the actual world given that experience. [ABSTRACT FROM AUTHOR]

Kearns and Star have previously recommended that we measure the degree to which a reason supports a conclusion, either about how to act or what to believe, as the conditional probability of the conclusion given the reason. I show how to properly formulate this recommendation to allow for dependencies and conditional dependencies among the considerations being aggregated. This formulation allows us to account for how considerations, which do not themselves favour a specific conclusion, can modify the strength of a reason for that conclusion, and thus to explain the intensifiers and attenuators described by Dancy. The formulation also accounts for the workings of partial undercutters in epistemology. I then show how my account avoids the counterexamples that Brunero levied against probability-based theories of the strengths of reasons. My account supports the theory, suggested by Kearns and Star, that the strengths of reasons are measured by conditional probabilities. If my account is successful, then it will count in favour of the idea that the strengths of reasons are measured on the same scale as are conditional probabilities. [ABSTRACT FROM AUTHOR]

Accurately locating and quantifying carbon dioxide (CO2) leakage to the atmosphere is important for diffuse degassing studies in volcanic / geothermal areas and for safety monitoring and/or carbon credit auditing of Carbon Capture and Storage (CCS) sites. This is typically conducted by measuring CO2 flux at numerous points over a large area and applying statistics or geostatistical interpolation. Accuracy of the results will depend on many factors related to survey/data-processing choices and site characteristics, and thus uncertainties can be difficult to quantify. To address this issue, we have developed a Monte Carlo-based program (MC-Flux) that repeatedly subsamples a high-resolution synthetic or real dataset using a choice of different sampling strategies (one random and four grid types) at multiple user-defined sample densities. The program keeps track of the anomalies found and estimates total flux using two statistical and two geostatistical approaches from the literature. This paper describes the use of MC-Flux to assess the potential impact of various sampling and interpretation decisions on the accuracy of the final results. Simulations show that an offset grid sample distribution yields the best results, however relatively dense sampling is required to obtain a high probability of an accurate flux estimate. For the test dataset used, ordinary kriging interpolation produces a range of flux estimates that are centered on the true value while sequential Gaussian simulation tends to slightly overestimate values at intermediate sample spacings and is sensitive to input parameters. These results point to the need for developing new approaches that decrease uncertainty, such as integration with high-resolution co-kriging datasets that complement the more accurate point flux measurements. [ABSTRACT FROM AUTHOR]