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Based on historical flood data (1764—) and measured flood data (1953—2024), the consistency of floods at Feilaixia Station in Beijiang River was tested using time series diagrams, sliding means, M-K method, and Hurst index. According to the P-III frequency analysis method, historical flood data were used to re-rank the flood series for flood frequency analysis. The frequency calculation method based on empirical mode decomposition (EMD) and synthesis was used to analyze and calculate the flood frequency. The results indicate that the extreme floods in Beijiang River have shown a trend of increasing frequency and intensity since the mid-1990s, and significant variations have occurred after testing. The flood design values for each frequency obtained using traditional hydrological frequency calculation methods increase by 500~600 m3/s compared to the original design values. By using the frequency calculation method based on EMD and synthesis, the design values of each frequency for the 2020 level year increase by more than 3 500 m3/s, and for the 2030 level year, the design values of each frequency increase by more than 3 800 m3/s. The flood frequency calculation method based on EMD reconstruction can respond to changing environments in a timely manner and has certain promotion and application value. The hydrological frequency calculation results of Feilaixia Station in Beijiang River have undergone significant changes and need to be re-evaluated as soon as possible.

Abstract Background During tumor progression, HER2 expression undergoes dynamic changes. Circulating tumor cells (CTCs) can be used to monitor HER2 expression in real-time and hold potential for clinical application. This study aimed to evaluate the consistency of HER2 expression between primary tumors and CTCs in patients with breast cancer (BC). Methods We used a previously established telomerase reverse transcriptase-based CTC detection method (TBCD) combined with anti-HER2 antibody to detect CTC and HER2-positive CTC (HER2 + CTC) in 4 ml of peripheral blood from patients with breast cancer prior to radiotherapy. The results indicated that the status of HER2 in CTC was inconsistent with the histological results. Results Discordance in HER2 status between primary tumor and CTC was observed in 32.6% of patients (kappa value = 0.325, p = 0.03). And among patients with histologically HER2-negative breast cancer, the detection rate of HER2 + CTC was 32.1% (9/28). Conclusions We found that the HER2 status of CTC in peripheral blood was inconsistent with the histological findings. Further research should explore the clinical significance of detecting HER2-positive CTCs, and it is desired that real-time HER2 status testing of CTCs could hold potential value for patients with breast cancer.

The need for organizations to remain flexible is crucial. This study aims to assess the way organizational culture, dynamic environments, and strategic choices can be related in the case of the Jordanian ICT industry with emphasis on the mediating effect of the dynamic environment. The paper employed a questionnaire sent to 256 employees from several ICT companies involved in strategic decision-making and planning. The analyses showed that organizational culture significantly affects strategic decision-making, with the dynamic environment serving as an important mediator. More precisely, it explained 50.6% of the variance in decision-making (R² = 0.506) and 52.2% of the variance in perceptions about the dynamic environment (R² = 0.522). Thus, consistency (p = 0.007) and adaptability (p = 0.006) emerged as critical cultural dimensions that enhance effective strategic decision-making. Additionally, the prominent effect of the dynamic environment on decision-making was identified (p = 0.000). Therefore, Jordan’s ICT companies can enhance their strategic decision-making and gain a competitive advantage in a sustainable manner by focusing on organizational culture with priorities on consistency and adaptability. This kind of culture ensures better alignment with strategies and quick responses to market or technological changes, contributing to long-term business sustainability. Acknowledgment Acknowledgments are expressed to Middle East University, Amman, Jordan, for the financial support to cover this article’s publishing fee.

An implicit Superclass of non-block Extended Backward Differentiation Formulae (SEBDF) for the numerical integration of first-order stiff system of Ordinary Differential Equations (ODEs) in Initial Value Problems (IVPs) with optimal stability properties is presented. The stability and convergence properties of the SEBDF schemes show that the methods are consistent, zero stable and convergent. The plotted Region of Absolute Stability (RAS) of the methods using boundary locus shows that the methods are A-stable of order up to order 5 and A(α)-stable of order up to 9. The algorithm is described whereby the required approximate solution is predicted using classical explicit Euler’s method and conventional Backward Differentiation Formula (BDF) schemes of order k and then corrected using a Super class of Extended Backward Differentiation Formula (SEBDF) schemes of higher orders k+1. The SEBDF schemes are implemented using a Modified Newton iteration algorithm iterated to convergence in which some selected systems of first-order stiff IVPs are solved, and the numerical results obtained for the proposed methods are often better than the existing BDF and SBDF methods for solving stiff IVPs.

This article deals with the selection of non redundant response variables in normality-assumed multivariate linear regression, where the redundancy of the response variables is defined by conditional expectation. A sufficient condition for model selection consistency is obtained using a kick-one-out method based on the generalized information criterion under a high-dimensional asymptotic framework such that the sample size tends to infinity and the number of response variables and explanatory variables does not exceed the sample size but may tend to infinity. A consistent kick-one-out method using the obtained condition is proposed. Simulation results show that the proposed method has a high probability of selecting true, non redundant variables. [ABSTRACT FROM AUTHOR]

In Large Scale Group Decision Making (LSGDM), the differences in decision-makers’ professional backgrounds and attitudes often lead to high-quality decisions being overshadowed by numerous low-quality decisions, thus affecting the accuracy of the final decision. This study proposes a new decision-making method to address this challenge. First, a few experts are invited to make decisions as cluster centers, followed by obtaining decisions from a large number of ordinary decision-makers. The ordinary decisions are then generated and modified using a Discrete Conditional Variational Autoencoder (DCVAE) to enhance decision quality while maintaining consistency with expert decisions. Finally, the normalized prediction selection rate (NPSR) and the Borda Count consensus method are integrated to obtain the final result. Experimental results demonstrate the effectiveness of this method in improving the quality of LSGDM, providing a new solution to the coexistence of high- and low-quality decisions. [ABSTRACT FROM AUTHOR]

We propose an extension of the double autoregressive (DAR) model: the sign-double autoregressive (SDAR) model, in the spirit of the GJR-GARCH model (also named the sign-ARCH model). Our model shares the important property of DAR models where a unit root does not imply non stationarity and it allows for asymmetry, as other alternatives in the literature such as the GJR-GARCH or asymmetric linear DAR and dual-asymmetry linear DAR models. We establish consistency and asymptotic normality of the quasi-maximum likelihood estimator in the context of the SDAR model. Furthermore, it is shown by simulations that the asymptotic properties also apply in finite samples. Finally, an empirical application shows the usefulness of our model specially in periods of supply/demand crises of oil disruptions, where spikes of volatility are very likely to be predominant. [ABSTRACT FROM AUTHOR]

Multi-view clustering (MVC) aimed at partitioning data samples into coherent clusters by integrating information from multiple perspectives. Recently, deep contrastive learning approaches have exhibited substantial capabilities in feature extraction within MVC frameworks. However, the challenge lies in extracting efficient feature representations while ensuring consistency. Moreover, existing deep clustering methods based on contrastive learning often overlook the consistency of cluster representation during clustering processes. In this study, we address these challenges by proposing a novel deep learning method called Contrastive Coordinated Multi-View consistency Clustering (CCMVC). Our approach leverages contrastive learning to coordinate training across three levels: feature, cluster, and view. Specifically, we enhance clustering performance by implementing an alignment method to ensure consistent information alignment across different views. This method assigns semantically similar representations for clustering tasks and effectively explores shared semantics across views while mitigating view-specific noise. Experimental evaluations conducted on seven datasets demonstrate the efficacy and superiority of our proposed CCMVC method over existing state-of-the-art approaches. Code is available at . [ABSTRACT FROM AUTHOR]

In this article, we study weak stationarity conditions (A- and C-) for a particular class of degenerate stochastic mathematical programming problems with complementarity constraints (SMPCC, for short). Importance of the weak stationarity concepts in absence of SMPCC-LICQ are presented through toy problems in which the point of local or global minimizers are weak stationary points rather than satisfying other stronger stationarity conditions. Finally, a well known technique to solve stochastic programming problems, namely sample average approximation (SAA) method, is studied to show the significance of the weak stationarity conditions for degenerate SMPCC problems. Consistency of weak stationary estimators are established under weaker constraint qualifications than SMPCC-LICQ. [ABSTRACT FROM AUTHOR]

In this paper, we propose and investigate novel closed-form point estimators for the beta distribution. The estimators of the first type are a modified version of Pearson's method of moments. The underlying idea is to involve the sufficient statistics, i.e., log-moments in the moment estimation equations and solve the mixed type of moment equations simultaneously. The estimators of the second type are based on an approximation to Fisher's likelihood principle. The idea is to solve two score equations derived from the log-likelihood function of generalized beta distributions. Both two resulted estimators are in closed forms, strongly consistent and asymptotically normal. In addition, through theoretical analyses and extensive simulations, the proposed estimators are shown to perform very close to the maximum likelihood estimators in both small and large samples, and they significantly outperform the method of moment estimators.

Background Nonalcoholic fatty liver disease (NAFLD) is a common digestive system disease, which is often diagnosed by imaging methods in clinical work. At present, there is a lack of research on the effectiveness evaluation of imaging diagnostic methods with histology as the gold standard. Objective To study the consistency of imaging and histological diagnosis of NAFLD, and to analyze the influencing factors of gallstone disease (GD) complicated with NAFLD. Methods From January 2021 to July 2022, 53 patients with GD who underwent simple cholecystectomy and liver biopsy were selected from the Department of Hepatobiliary surgery, Nanjing Hospital affiliated to Nanjing University of traditional Chinese Medicine. The demographic characteristics, BMI, systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the subjects were collected, and the laboratory indexes, imaging and histological results were collected. The consistency of imaging and histological diagnosis of NAFLD was evaluated by Kappa consistency test. According to the histological diagnostic criteria, the subjects were divided into NAFLD group (n=15) and non-NAFLD group (n=38). Multivariate Logistic regression analysis was used to explore the influencing factors of NAFLD in patients with GD. Results The imaging detection rate of NAFLD in GD patients was 20.7% (11/53), which was lower than that of histology (28.3%) (15/53) (Kappa=0.404, P=0.001). The sensitivity of imaging diagnosis was 60.0% (9/15), the specificity was 94.7% (36/38), and the rate of missed diagnosis was 40.0% (6/15). There were 8 cases of nonalcoholic fatty liver (NAFL), 7 cases of nonalcoholic steatohepatitis (NASH) and no NASH associated cirrhosis in 15 patients with histological manifestation of NAFLD. The proportion of fibrosis in the NASH group was higher than that in the NAFL group. There were significant differences in the levels of BMI, SBP, fasting blood glucose (FPG) and aspartate aminotransferase (AST) between NAFLD group and non-NAFLD group (P

In light of the current situation where excessive amounts of excavated earth from subway tunnel construction are being stacked with low utilization and value, this study used residue as a mineral admixture to investigate the effects of different proportions of residue content (0%, 2.5%, 5.0%, 7.5%, and 10.0%) on the workability and mechanical properties of C50 concrete. The results indicate that: (1) The initial slump and slump loss of C50 concrete decrease gradually as the residue content increases. (2) The compressive strength of C50 concrete with varying residue contents is lower than the control group at early stages (3d, 7d), while it is higher than the control group at 28d. There exists an optimal content of residue for improving C50 concrete compressive strength, and it is found that the highest compressive strength at 28d is achieved when the residue content is 7.5% of the cement content. (3) The microscopic structure of C50 concrete with different residue contents at 28d shows that as the residue content increases, the microscopic structure of C50 concrete gradually becomes more compact and the porosity decreases.

Abstract Microplastics (MPs) can enter the body via plastic products. Given modern plastic exposure, we seek to assess MP exposure in large populations through epidemiological tools. In this quasi-experimental study, every participant filled out a questionnaire, and those who satisfied any of the following requirements were not allowed to continue in the study: Diabetes, ulcerative colitis, Crohn’s disease, infectious diseases. Participants in the exposure and control groups were provided three hot meals in disposable plastic tableware (DPT) (n = 30) or non-DPT (n = 30), respectively. After a month of observation, individuals in the exposure group discontinued the three meals provided in DPT (n = 27) for 1 month as the post-exposure group. Each Participant in the three groups received a questionnaire survey and fecal sample collection. We compared the differences in MP levels between different groups and used the Bland–Altman analysis method to evaluate the consistency of the results obtained by different measurement methods. Statistically significant differences in the total quantity (P (0.80 matching degree) = 0.020; P (0.65 matching degree)

Abstract Background Late gadolinium enhancement cardiac magnetic resonance imaging (LGE-CMR) is a valuable cardiovascular imaging technique. Segmentation of cardiac chambers from LGE-CMR is a fundamental step in electrophysiological modeling and cardiovascular disease diagnosis. Deep learning methods have demonstrated extremely promising performance. However, excellent performance often depended on a large amount of finely annotated data. The purpose of this manuscript was to develop a semi-supervised segmentation method to use unlabeled data to improve model performance. Methods This manuscript proposed a semi-supervised network that integrates triple-consistency constraints (data-level, task-level, and feature-level) for cardiac chambers segmentation from LGE-CMR. Specifically, we designed a network that integrated segmentation and edge prediction tasks based on the mean teacher architecture. This addressed the problem of ignoring some challenging regions because of excluding low-confidence regions of previous research. We also applied a voxel-level contrastive learning strategy to achieve feature-level consistency, helping the model pay attention to the consistency between features overlooked in previous research. Results In terms of the Dice, Jaccard, Average Surface Distance (ASD), and 95% Hausdorff Distance (95HD) metrics, for the atrial segmentation dataset, the proposed method achieved scores of 88.34%, 79.30%, 7.92, and 2.02 when trained with 10% labeled data, and 90.70%, 83.09%, 6.41, and 1.72 when trained with 20% labeled data. For the ventricular segmentation task, the results were 87.22%, 77.95%, 2.27, and 0.61 with 10% labeled data, and 88.99%, 80.45%, 1.87, and 0.51 with 20% labeled data, respectively. Conclusion Experiments demonstrated that our method outperforms previous semi-supervised methods, showing the potential of the proposed network for semi-supervised segmentation problems.

Abstract Background The standard approach to local inconsistency assessment typically relies on testing the conflict between the direct and indirect evidence in selected treatment comparisons. However, statistical tests for inconsistency have low power and are subject to misinterpreting a p-value above the significance threshold as evidence of consistency. Methods We propose a simple framework to interpret local inconsistency based on the average Kullback–Leibler divergence (KLD) from approximating the direct with the corresponding indirect estimate and vice versa. Our framework uses directly the mean and standard error (or posterior mean and standard deviation) of the direct and indirect estimates obtained from a local inconsistency method to calculate the average KLD measure for selected comparisons. The average KLD values are compared with a semi-objective threshold to judge the inconsistency as acceptably low or material. We exemplify our novel interpretation approach using three networks with multiple treatments and multi-arm studies. Results Almost all selected comparisons in the networks were not associated with statistically significant inconsistency at a significance level of 5%. The proposed interpretation framework indicated 14%, 66%, and 75% of the selected comparisons with an acceptably low inconsistency in the corresponding networks. Overall, information loss was more notable when approximating the posterior density of the indirect estimates with that of the direct estimates, attributed to indirect estimates being more imprecise. Conclusions Using the concept of information loss between two distributions alongside a semi-objectively defined threshold helped distinguish target comparisons with acceptably low inconsistency from those with material inconsistency when statistical tests for inconsistency were inconclusive.

Maintaining consistency is a crucial element in ensuring the reliability of pairwise comparisons provided by experts in the Analytic Hierarchy Process (AHP) and Fuzzy AHP. Many researchers have put forth various definitions concerning the consistency of fuzzy Pairwise Comparison Matrices (PCMs) using fuzzy set theory. However, in most applications of fuzzy AHP, fuzzy PCM consistency is evaluated by defuzzifying the fuzzy comparisons, similar to the approach used for crisp PCMs. This paper introduces a novel method for transforming fuzzy comparisons into crisp comparisons through defuzzification, specifically utilizing the geometric mean. Furthermore, it proposes a method to enhance the consistency of the PCM. The presented methodology is applied to several problems previously addressed in the literature.

AbstractHidden Markov models (HMM) are used in different fields to study the dynamics of a process that cannot be directly observed. However, in some cases, the structure of dependencies of a HMM is too simple to describe the dynamics of the hidden process. In particular, in some applications in finance and in ecology, the transition probabilities of the hidden Markov chain can also depend on the current observation. In this work, we are interested in extending the classical HMM to this situation. We refer to the extended model as the observation-driven hidden Markov model (OD-HMM). We present a complete study of the general non parametric OD-HMM with discrete and finite state spaces. We study its identifiability and the consistency of the maximum likelihood estimators. We derive the associated forward-backward equations for the E-step of the EM algorithm. The quality of the procedure is tested on simulated datasets. We illustrate the use of the model on an application focused on the study of annual plant dynamics. This work establishes theoretical and practical foundations for this framework that could be further extended to the parametric context in order to simplify estimation and to hidden semi-Markov models for more realism. [ABSTRACT FROM AUTHOR]

As a society, we can get so engrossed in using the World Wide Web (WWW) also known as the web. We look for, read about and interact with different people, text, images, videos etc. that we often take for granted how we are doing this. We all use a web browser, we must, to get around the web. Yet, do we ever stop to give much thought to this gateway to the web? The web browser can be fittingly described as a transparent technology. This is in the sense that we don't really stop to think about the browser and its features, we just unconsciously absorb and use it. This paper reports on a study that explores just how effectively we understand and use our web browser applications. The study was focused on people's perceived awareness of desktop web browser functionality, what features they are using/aware of and most importantly what understanding they take from these? The findings show that the majority (69%) of the five hundred and twenty-eight participants studied do not fully understand what the padlock feature on their web browsers represents. In fact, the findings highlight that many of the participants feel that the padlock represents a safe website which it clearly does not. This paper succinctly draws attention to the fact that the current desktop web browser application design is not fit for purpose. In summary, the research pushes for more effective web browser application designs; it provides design recommendations aimed at achieving web browser consistency and creating designs that promote safety, trust, and confidence. [ABSTRACT FROM AUTHOR]

The reproducibility crisis highlights several unresolved issues in science, including the need to develop measures that gauge both the consistency and convergence of data sets. While existing meta‐analytic methods quantify the consistency of evidence, they do not quantify its convergence: the extent to which different types of empirical methods have provided evidence to support a hypothesis. To address this gap in meta‐analysis, we and colleagues developed a summary metric—the cumulative evidence index (CEI)—which uses Bayesian statistics to quantify the degree of both consistency and convergence of evidence regarding causal hypotheses between two phenomena. Here, we outline the CEI's underlying model, which quantifies the extent to which studies of four types—positive intervention, negative intervention, positive non‐intervention and negative non‐intervention—lend credence to any of three types of causal relations: excitatory, inhibitory or no‐connection. Along with p‐values and other measures, the CEI can provide a more holistic perspective on a set of evidence by quantitatively expressing epistemic principles that scientists regularly employ qualitatively. The CEI can thus address the reproducibility crisis by formally demonstrating how convergent evidence across multiple study types can yield progress toward scientific consensus, even when an individual type of study fails to yield reproducible results. [ABSTRACT FROM AUTHOR]

In this article, we propose three non parametric kernel estimators for the mean residual life function when the data are selected proportionally to their length. We evaluate the mean squared error of the three estimators and investigate the consistency for all three of them. [ABSTRACT FROM AUTHOR]

This paper deals with the dewatering and handling of dredged sediments in the context of sustainability and renewability of natural resources. Dewatering is a critical part of sediment management, as the high water content of dredged sediments becomes a challenge for transportation, final storage and/or recycling. This is why it is necessary to reduce their water content before transportation. Conventional methods suggest using land-based drained basins, which is a sustainable solution. However, this solution has certain drawbacks: dewatering the sediment is time-consuming and involves the use of large land areas. The main problem with this method of dewatering can be solved by proposing mechanical dewatering in the vicinity of the dredging operation. Once the sediment has been sufficiently dewatered, it should be shoveled and transported again. The proposed paper covers the study of the dewatering and shoveling ability of sediments. After introducing why dewatering is a critical phase in the recycling process of sediment, some techniques for dewatering large volumes of high-water sediments are briefly reported. Typical dewatering laboratory tests are detailed, demonstrating their usefulness for understanding the mechanisms of natural dewatering. A laboratory dewatering press machine is reported and the procedure used for a sediment sludge. The last section concerns a recent innovative test implemented for the study of the shoveling ability and adhesion of sediments. This study improves our understanding of the phenomenon of sediment dewatering, for both natural and mechanical dewatering. It also provides the protocols for typical laboratory tests on sediment dewatering and shoveling ability. [ABSTRACT FROM AUTHOR]

This review addresses the current knowledge on inclusive education suggesting that many studies focus on predetermined groups of disadvantaged learners . This review aims 1) to map the research on inclusive education for all (IEFA) and 2) to assess the consistency of studies in their approach to inclusive education (IE), research methodology and research results/discussions regarding the concept of IEFA. The analysis of 26 studies (out of 2,780 original datasets) revealed two main results: First, they represent three overarching themes of inclusion – values, practices and school development. They illustrate that beliefs about inclusive education and beliefs about practices are not always aligned. Second, the review highlights the challenges researchers face in describing a student population that includes representatives with diverse needs. While some researchers aim to describe students in detail, they often end up focusing only on those with common characteristics, usually disability. Consequently, the sample sections do not reflect the actual diversity of students addressed by IEFA. Only 46% of the studies are consistent in their approach, meaning, they conceptualise the broader concept of inclusion in theoretical approach, focus on it in methodology and interpret it in the results/discussions. [ABSTRACT FROM AUTHOR]

In this paper, a generalized diffusion–advection–reaction equation (GDARE) is considered and by using the solitary wave solution two new class of exact finite difference (EFD) schemes are proposed under certain functional relationship between the temporal and space step sizes. Suitable denominator functions are identified from these EFD schemes and a new non-standard finite difference (NSFD) scheme is developed. This NSFD scheme preserves positivity and boundedness properties of the solution of GDARE. The $ L_2 $ L 2 , $ L_\infty $ L ∞ errors and CPU times are obtained for the proposed NSFD and EFD schemes to show the proficiency and accuracy of the schemes. [ABSTRACT FROM AUTHOR]

Network meta‐analysis (NMA) incorporates all available evidence into a general statistical framework for comparing multiple treatments. Standard NMAs make three major assumptions, namely homogeneity, similarity, and consistency, and violating these assumptions threatens an NMA's validity. In this article, we suggest a graphical approach to assessing these assumptions and distinguishing between qualitative and quantitative versions of these assumptions. In our plot, the absolute effect of each treatment arm is plotted against the level of effect modifiers, and the three assumptions of NMA can then be visually evaluated. We use four hypothetical scenarios to show how violating these assumptions can lead to different consequences and difficulties in interpreting an NMA. We present an example of an NMA evaluating steroid use to treat septic shock patients to demonstrate how to use our graphical approach to assess an NMA's assumptions and how this approach can help with interpreting the results. We also show that all three assumptions of NMA can be summarized as an exchangeability assumption. Finally, we discuss how reporting of NMAs can be improved to increase transparency of the analysis and interpretability of the results. [ABSTRACT FROM AUTHOR]

Let X, Y be continuous random variables with unknown distributions. The aim of this paper is to study the problem of estimating the probability θ : = P (X < Y) based on independent random samples from the distributions of X ′ , Y ′ , ζ and η , where X ′ = X + ζ , Y ′ = Y + η and X, Y, ζ , η are mutually independent random variables. In this context, ζ , η are referred to as measurement errors. We apply the ridge-parameter regularization method to derive a nonparametric estimator for θ depending on two parameters. Our estimator is shown to be consistent with respect to mean squared error if the characteristic functions of ζ , η only vanish on Lebesgue measure zero sets. Under some further assumptions on the densities of X, Y, ζ and η , we obtain some upper and lower bounds on the convergence rate of the estimator. A numerical example is also given to illustrate the efficiency of our method. [ABSTRACT FROM AUTHOR]

The paper presents error estimates within a unified abstract framework for the analysis of FEM for boundary value problems with linear diffusion‐convection‐reaction equations and boundary conditions of mixed type. Since neither conformity nor consistency properties are assumed, the method is called completely discrete. We investigate two different stabilized discretizations and obtain stability and optimal error estimates in energy‐type norms and, by generalizing the Aubin‐Nitsche technique, optimal error estimates in weaker norms. [ABSTRACT FROM AUTHOR]

Bokiis a new serverless runtime that exports a shared log API to serverless functions. Boki shared logs enable stateful serverless applications to manage their state with durability, consistency, and fault tolerance. Boki shared logs achieve high throughput and low latency. The key enabler is the metalog, a novel mechanism that allows Boki to address ordering, consistency and fault tolerance independently. The metalog orders shared log records with high throughput and it provides read consistency while allowing service providers to optimize the write and read path of the shared log in different ways. To demonstrate the value of shared logs for stateful serverless applications, we build Boki support libraries that implement fault-tolerant workflows, durable object storage, and message queues. Our evaluation shows that shared logs can speed up important serverless workloads by up to 4.2×. [ABSTRACT FROM AUTHOR]

The present research aims to examine the different accounts of induction given by Aristotle, Hume, Leibniz, Carnap and De Finetti, trying to support that probability calculus offers a sufficient grounding of inductive logic. The term induction had been contrasted to deduction, by Aristotle. The Neoplatonic philosopher Alcinous suggested that dialectic firstly investigates the substances and then the accidents. There are five kinds of dialectic reasoning: division, definition, analysis, induction and syllogistic. The first three concern with substances, the last two with accidents. Although Leibniz regarded probability theory as a basis of inductive logic, Hume's skepticism was seminal for the reappraisal of the role of induction in modern philosophy. Enhancing Hume's criticism, Popper and Wittgenstein completely denied that scientists use induction. Hans Reichenbach, however, attempted to build a theory of justification for the use of induction, based on a factual basis of other successful predictive methods that make induction feasible (Earman & Salmon 1999). Moreover, Buchdall (1969) stressed that we must distinguish the inductive process of the scientist from the inductive conclusion, which comes after the completion of observation and experimentation. [ABSTRACT FROM AUTHOR]

Respondent-driven sampling (RDS) is widely used to sample populations with higher risk of HIV infection for whom no sampling frames exist. However, few studies have been done to assess the consistency of RDS estimators in real world settings. We conducted an assessment study on the consistency of RDS estimators using data from the National HIV Behavioral Surveillance – People Who Inject Drugs surveys in Newark, New Jersey from 2005 to 2018. Population parameter estimates based on RDS-I, RDS-II, Gile's SS, and HCG were compared longitudinally and cross-sectionally. Population homophily statistics and differential recruitment statistics were estimated and compared. Convergence plots were used for RDS diagnosis. Sensitivity analyses were conducted on population size estimates and seeds biases. By comparing time-insensitive population parameters and population homophily statistics estimated by four RDS estimators, the study found that RDS-II and Gile's SS could provide longitudinally and cross-sectionally consistent estimates and population homophily statistics on gender and sexual orientation. Cross-sectional comparison of time-sensitive population parameter estimates also supported the consistency of RDS-II and Gile's SS. However, RDS-I and HCG did not perform well in those comparisons. In conclusion, RDS estimators may not address all inconsistencies, but RDS-II and Gile's SS are recommended to weight RDS samples given enough consistency was observed in them. [ABSTRACT FROM AUTHOR]

The current study details how marketing campaigns featuring event-typical ads adapted to sporting events (e.g., a car ad that displays its brand logo on an Olympic podium) affect brand attitudes and incentive-aligned brand choice in more positive ways than proven advertising strategies such as product category consistency. Presenting four field and lab experiments across a total of 3 events and 32 ads, we show that these effects are driven by the combination of 3 mechanisms: event-typical ads' capacity to trigger a sufficient feeling of knowing what the ad is about, provoke curiosity, and transfer attributes from the event to the brand, even with very short ad exposures. Advertisers, brand managers, or event organizers can thus exploit the creative potential around sporting events by using event-typical ads. Furthermore, when these stakeholders know the most typical elements of an event, they can either adapt their marketing activities or register them to avoid ambush marketing (i.e., advertisers willing to associate their brand with the event in the absence of any legitimate link with it). [ABSTRACT FROM AUTHOR]

In recent years, many tensor data processing methods have been proposed. Tensor low-rank representation (TLRR) is a recently proposed tensor-based clustering method that has shown good clustering performance in some applications. However, TLRR does not make full use of the consistency and diversity information hidden in different similarity matrices. Therefore, we propose the TLRR combined with consistency and diversity exploration (TLRR-CD) method. First, the tensor Frobenius norm and tensor product (t-product), which is defined as the multiplication of two tensors, are used to obtain the low-rank representation tensor, which can be seen as being composed of many similarity matrices. Second, the low-rank representation tensor is further decomposed into a consistent tensor, which contains the common structural information contained in the different similarity matrices, and a diversity tensor, which contains the locally specific structural information of different similarity matrices. Finally, the Hilbert–Schmidt Independence Criterion (HSIC), which is used to measure the relevance of local specific structural information, and spectral clustering are unified into the final objective function to improve clustering performance. In addition, the optimization process of TLRR-CD is also given. The experimental results show the good performance of TLRR-CD. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the reliability of eight specific fitness tests for elite female Chinese wrestlers. Twenty-eight elite female wrestlers participated in the study (age: 26.9 ± 2.81 years). The reliability of the tests was analyzed using the intraclass correlation coefficient (ICC) and the 95% confidence interval (CI), the coefficient of variation (CV), and other metrics. The 30-s Sit-Up (SU30) and 6-m Rope Climb (RC6m) tests showed excellent reliability (ICC > 0.9). The 30-s Dummy Throw (DT30) had good to excellent reliability, while the 30-s Bridge-Return (B-R30) showed moderate to good reliability. The 30-s Burpee (BUR30), 15-s Leg Attack (LA15), 15-s Leg Defense (LD15), and Dummy Suplex and Gut Wrench (DS&GW) tests ranged from poor to good reliability. SU30, DT30, LA15, and RC6m tests displayed low variability (CV < 5%), while others exhibited moderate variability. SU30, B-R30, DT30, and RC6m tests are reliable for assessing wrestling fitness. However, BUR30 and LA15 tests showed high variability and should be used carefully. LD15 and DS&GW tests are not recommended for assessing fitness in elite female wrestlers. [ABSTRACT FROM AUTHOR]

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This study analyzes the transmission of typhoid fever caused by Salmonella typhi using a mathematical model that highlights the significance of delay in its effectiveness. Time delays can affect the nature of patterns and slow down the emergence of patterns in infected population density. The analyzed model is expanded with the equilibrium analysis, reproduction number, and stability analysis. This study aims to establish and explore the non-standard finite difference (NSFD) scheme for the typhoid fever virus transmission model with a time delay. In addition, the forward Euler method and Runge-Kutta method of order 4 (RK-4) are also applied in the present research. Some significant properties, such as convergence, positivity, boundedness, and consistency, are explored, and the proposed scheme preserves all the mentioned properties. The theoretical validation is conducted on how NSFD outperforms other methods in emulating key aspects of the continuous model, such as positive solution, stability, and equilibrium about delay. Hence, the above analysis also shows some of the limitations of the conventional finite difference methods, such as forward Euler and RK-4 in simulating such critical behaviors. This becomes more apparent when using larger steps. This indicated that NSFD is beneficial in identifying the essential characteristics of the continuous model with higher accuracy than the traditional approaches. [ABSTRACT FROM AUTHOR]

To develop a numerical method for global geophysical fluids, we usually need to choose a spherical grid and numerical approximations to represent the partial derivative equations. Some alternatives include the use of finite differences or finite volumes with latitude–longitude or reduced grids. Each of these cases has some advantages and also some limitations. This paper presents a comparison between two methods and describes a composite model using them side by side. The first is a well-known method for latitude–longitude grids and was used from 75 ∘ S until 75 ∘ N. The second is a recently developed scheme for reduced grids and was used only in the polar regions. The similarity between the two methods allows the use of small adaptations in their approximations to obtain consistency and mass conservation also in the transition between the two regions. The composite model combines advantages of the other two schemes and has a smaller computational cost. Numerical tests indicated order 2 of convergence, prevention of grid-imprinting errors, and avoidance of nonlinear instability. This model has numerical properties that may lead to efficient implementations with massive parallel computation. [ABSTRACT FROM AUTHOR]

Sentinel-3 synergy (SYN) VEGETATION (VGT) products were designed to provide continuity to the SPOT/VEGETATION (SPOT VGT) base products archive. Since the PROBA-V mission acted as a gap filler between SPOT VGT and Sentinel-3, and in principle, a continuous series of data products from the combined data archives of SPOT VGT (1998–2014), PROBA-V (2013–2020) and Sentinel-3 SYN VGT (from 2018 onwards) are available to users, the consistency of Sentinel-3 SYN VGT with both the latest SPOT VGT (VGT-C3) and PROBA-V (PV-C2) archives is highly relevant. In past years, important changes have been implemented in the SYN VGT processing baseline. The archive of SYN VGT products is therefore intrinsically inconsistent, leading to different consistency levels with SPOT VGT and PROBA-V throughout the years. A spatio-temporal intercomparison of the combined time series of VGT-C3, PV-C2 and Sentinel-3 SYN VGT 10-day NDVI composite products with an external reference from LSA-SAF, and an intercomparison of Sentinel-3 SYN V10 products with a climatology of VGT-C3 resp. PV-C2 for three distinct periods with different levels of product quality have shown that the subsequent processing baseline updates have indeed resulted in better-quality products. It is therefore essential to reprocess the entire Sentinel-3 SYN VGT archive; a uniform data record of standard SPOT VGT, PROBA-V and Sentinel-3 SYN VGT products, spanning over 25 years, would provide valuable input for a wide range of applications. [ABSTRACT FROM AUTHOR]

Three-dimensionally printed concrete is a transformative technology that addresses housing shortages due to population growth and enables innovative architectural designs. The objective of this study is to investigate the connection between a conventional test and the rheological properties of 3D-printed concrete. A more precise assessment of material quality based on traditional evaluation techniques is proposed. Standard tests are conducted to evaluate the consistency of 3D-printed concrete materials. Complementarily, a rheometer is employed to accurately measure key rheological properties, thereby establishing a link with empiric testing methodologies. The correlation between the flow table test and rheological coefficients, such as yield stress and viscosity, has been identified as the most effective in basic experiments for evaluating material behavior. This approach allows for a preliminary assessment of printability without the need for additional complex equipment. The study has successfully established a relationship between flow table tests and rheological parameters. However, further research involving a broader range of materials and print-test experiments is essential to enhance the correlation between other conventional testing methods and rheometer results. [ABSTRACT FROM AUTHOR]

This paper reports on two flash-mode experiments that test redundant descriptions of small (2-4) cardinalities, borderline (5-8) cardinalities, and color in referential communication. It provides further support for the idea that small cardinalities are more salient (due to subitizing), less sensitive to visual context, and therefore give rise to higher over-specification rates than color. Because of greater salience, Russian speakers more often use prenominal positions for numerals than for color adjectives. The paper also investigates borderline cardinalities and argues for the order factor that affects their salience, since ordered items can be perceived in small subitized parts. The ordered mode of presentation of the borderline cardinalities leads to higher over-specification rates and to higher percentages of prenominal positions than the unordered one. The paper provides further evidence for the consistency of small, borderline cardinalities, and color in people's choices to minimally specify or over-specify given objects in referential communication. [ABSTRACT FROM AUTHOR]

The study highlights that using different distance measures on the same dataset leads to varying clustering results, making the choice of distance measure a challenge when prior knowledge is lacking. To address this issue, a consistency-oriented clustering ensemble via data reconstruction is developed. This approach eliminates the need to select a specific distance measure and achieves higher consistency between the clustering ensemble and base clusterings while maintaining superior clustering performance. First, the base clustering is generated via the clustering with different distance measures and a consistency definition is introduced in the proposed method. Then the ensemble process updates the weights of base clusterings to ensure they reach the consistency. At the same time data reconstruction process is integrated into the ensemble process to guarantee a high convergence rate and efficient clustering. Finally, the clustering ensemble result is achieved with the higher consistency measure and improved clustering performance by balancing both factors. In the experiment, the effectiveness of the proposed method is verified and the specification of the parameters is advised through the various experimental outcomes. [ABSTRACT FROM AUTHOR]

Background: The standard approach to local inconsistency assessment typically relies on testing the conflict between the direct and indirect evidence in selected treatment comparisons. However, statistical tests for inconsistency have low power and are subject to misinterpreting a p-value above the significance threshold as evidence of consistency. Methods: We propose a simple framework to interpret local inconsistency based on the average Kullback–Leibler divergence (KLD) from approximating the direct with the corresponding indirect estimate and vice versa. Our framework uses directly the mean and standard error (or posterior mean and standard deviation) of the direct and indirect estimates obtained from a local inconsistency method to calculate the average KLD measure for selected comparisons. The average KLD values are compared with a semi-objective threshold to judge the inconsistency as acceptably low or material. We exemplify our novel interpretation approach using three networks with multiple treatments and multi-arm studies. Results: Almost all selected comparisons in the networks were not associated with statistically significant inconsistency at a significance level of 5%. The proposed interpretation framework indicated 14%, 66%, and 75% of the selected comparisons with an acceptably low inconsistency in the corresponding networks. Overall, information loss was more notable when approximating the posterior density of the indirect estimates with that of the direct estimates, attributed to indirect estimates being more imprecise. Conclusions: Using the concept of information loss between two distributions alongside a semi-objectively defined threshold helped distinguish target comparisons with acceptably low inconsistency from those with material inconsistency when statistical tests for inconsistency were inconclusive. [ABSTRACT FROM AUTHOR]

In the geotechnical engineering field, the rapid speed of urbanization triggers the need for direct measurements of sub-soil parameters through in situ testing, accompanied by instant results. At this juncture, the cone penetration test (CPT) is selected for this study. Here, an attempt is made to develop a correlation between cone penetration resistance (qc) and standard penetration blow count (SPT N) in order to predict a reference range of qc for cohesive (silty clay/clayey silt) sub-soil of different SPT-based consistencies. In this context, 25 CPT were conducted adjacent to conventional boreholes accompanied by SPT tests at eight important locations in West Bengal (WB) and Odisha (OR), India, focusing on infrastructure development. Primarily, sub-soil is characterized by bulk unit weight (γ) along with soil behavior type index (IC) estimated from the CPT and compared with the sub-soil profile identified from conventional boreholes. Further, a comparison of qc with SPT N is made to establish a correlation. Also, an attempt is made to tally the established correlation with the earlier correlations established for different regions. This study quantitatively establishes a quadratic correlation (R2 = 0.84) between qc and SPT N, which is found to be in good agreement with the previous correlations. Overall, the key findings of this study, i.e., the predicted range of qc, reveal a reliable method for assessing the consistency of cohesive sub-soil by virtue of the qc. However, this correlation is limited to soft to very stiff silty clay/clayey silt sub-soil formation. [ABSTRACT FROM AUTHOR]

AbstractLet θ=P(XY are independent random variables, with known constants μX,μZ∈R, σ>0. Suppose we observe a random sample Y1′,…,Yn′ from the distribution of Y′=Y+ε. Here ε is a random error and distributed with a known continuous distribution. Our aim is to estimate θ based on the sample as well as on the complete knowledge about the distributions of X, Z and ε. We propose a nonparametric estimator of θ by applying the Fourier deconvolution method. Our estimator is shown to be mean consistent with respect to the mean squared error and strongly consistent. Under some regularity assumptions on the densities of Y and ε, some error estimates of the proposed estimator are derived. A simulation study is also conducted to illustrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Objective To explore the diagnostic value of a wearable flexible patch ECG instrument in arrhythmia, the alarm situation during clinical application, patient satisfaction and safety. Methods A total of 1 443 subjects wore flexible patch ECG and conventional dynamic ECG (control) for 24 h to test the validity and consistency of arrhythmia diagnosis, and counted the alarm of remote ECG and the occurrence of related adverse events during the wearing of the instrument. Results There were 987 cases of arrhythmia detected by flexible patch ECG and 992 cases by conventional dynamic ECG. The total coincidence rate of arrhythmia diagnosis was 98.7%. The mean heart rate was measured by flexible patch ECG (75.4±11.4) times/min, conventional dynamic heart rate (71.5±12.1) times/min, the intra-group correlation coefficient (ICC) of 2 instruments was 0.892 (95%CI: 0.537-0.956), with good repeatability. The correct alarm rate of flexible patch ECG was 100%. The incidences of skin pruritus (0.28% vs.1.32%), skin allergy, redness and swelling (0.14% vs. 0.69%) and electrode strip shedding (0 vs. 0.28%) during wearing the flexible patch electrocardiogram were lower than those of the conventional holter electrocardiogram (P＜0.05). Conclusion The flexible patch ECG has few adverse reactions, high comfort, good safety and clinical applicability. [ABSTRACT FROM AUTHOR]

We consider the problem of dividing the cost of a facility when agents can be ordered in terms of the needs they have for it, and accommodating an agent with a certain need allows accommodating all agents with lower needs at no extra cost. This problem is known as the "airport problem", the facility being the runway. We review the literature devoted to its study, and formulate a number of open questions. [ABSTRACT FROM AUTHOR]