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1 In the setting where participants are asked multiple similar possibly subjective multi-choice questions (e.g., Do you like Panda Express? Y/N; Do you like Chick-fil-A? Y/N), a series of peer prediction mechanisms have been designed to incentivize honest reports and some of them achieve dominantly truthfulness: Truth-telling is a dominant strategy and strictly dominates other "non-permutation strategy" with some mild conditions. However, those mechanisms require the participants to perform an infinite number of tasks. When the participants perform a finite number of tasks, these mechanisms only achieve approximated dominant truthfulness. The existence of a dominantly truthful multi-task peer prediction mechanism that only requires a finite number of tasks remains to be an open question that may have a negative result, even with full prior knowledge. This article answers this open question by proposing a family of mechanisms, VMI-Mechanisms, that are dominantly truthful with a finite number of tasks. A special case of this family, DMI-Mechanism, only requires ≥ 2C tasks where C is the number of choices for each question (C=2 for binary-choice questions). The implementation of these mechanisms does not require any prior knowledge (detail-free) and only requires ≥ 2 participants. To the best of our knowledge, any mechanism of the family is the first dominantly truthful peer prediction mechanism that works for a finite number of tasks. The core of these new mechanisms is a new family of information-monotone information measures: volume mutual information (VMI). VMI is based on a simple geometric information measure design method, the volume method. The volume method measures the informativeness of an object by "counting" the number of objects that are less informative than it. In other words, the more objects that the object of interest dominates, the more informative it is considered to be. Finally, in the setting where agents need to invest efforts to obtain their private signals, we show how to select the mechanism to optimally incentivize efforts among a proper set of VMI-Mechanisms. [ABSTRACT FROM AUTHOR]

Big data technologies change the way in which data and labor combine to create knowledge. Is this a modest innovation or a data revolution? Using hiring and wage data, we estimate firms' data stocks and their knowledge production functions. Quantifying changes in production functions informs us about the likely long-run changes in output, in factor shares, and in the distribution of income, due to big data technologies. For the investment management industry, our structural estimates predict a 5% decline in the labor share of income; that change is comparable to similar estimates for the industrial revolution. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

The Indian pangolin (Manis crassicaudata) is an "endangered" mammal species that is restricted to four range countries of Asia. The ecology and breeding behavior of Indian pangolins is poorly understood due to a lack of scientific data. Due to heavy poaching and illegal killing, the species population has declined drastically in the last decade. Considering the fact that Indian pangolin has low reproductive output, it needs special conservation measures and authentic information about its breeding ecology. We estimated concentrations of three reproductive hormones from scats using ELISA kits in male and female pangolins inhabiting the Pothwar Plateau, Pakistan, to confirm its breeding pattern in its range. Testosterone levels were found elevated from May (0.59 ng/ml) until October (1.28 ng/ml). Oestradiol levels were raised from May (0.59 pg/ml) until December (2.64 pg/ml). Progesterone concentrations were relatively low from January until March but increased from April (4.85 pg/ml) through December (14.0 pg/ml) with highest concentrations (20.13 pg/ml) in September and October. Mean hormone (testosterone, oestradiol and progesterone) concentrations were elevated in winter compared to summer (p < 0.001). The current study is the first one to quantify hormonal levels in this species, and our findings establish the breeding pattern of Indian pangolin. [ABSTRACT FROM AUTHOR]

Adjusting the sensitivity-weighting matrix, which is a key parameter affecting the filtering accuracy in the desensitized Kalman filter (DKF), is still an open problem. To address this issue, a new adaptive fast DKF (AFDKF) algorithm and adaptive fast desensitized extended Kalman filter (AFDEKF) have been proposed. The fast filters have an adaptive factor that enables them to adjust the sensitivity-weighting matrix based on the orthogonality principle of measurement residuals. This adaptive factor is calculated by using the corresponding process and measurement information. Then, a new desensitized cost function with an adaptive factor is designed. An analytical gain is obtained by minimizing this cost function to reduce computation cost. The performance of the AFDKF and AFDEKF algorithms are demonstrated using two numerical examples. [ABSTRACT FROM AUTHOR]

Objective: Systemic sclerosis (SSc) is a rare, chronic autoimmune disorder associated with disability, diminished physical function, fatigue, pain, and mental health concerns. We assessed minimal detectable changes (MDCs) of the Health Assessment Questionnaire–Disability Index (HAQ‐DI), Patient‐Reported Outcomes Measurement Information System‐29 Profile version 2.0 (PROMIS‐29v2.0) domains, and Patient Health Questionnaire (PHQ)‐8 in people with SSc. Methods: Scleroderma Patient‐Centered Intervention Network Cohort participants completed the HAQ‐DI, PROMIS‐29v2.0 domains, and PHQ‐8 at baseline assessments from April 2014 until August 2023. We estimated MDC95 (smallest change that can be detected with 95% certainty) and MDC90 (smallest change that can be detected with 90% certainty) with 95% confidence intervals (CIs) generated via the percentile bootstrapping method resampling 1,000 times. We compared MDC estimates by age, sex, and SSc subtype. Results: A total of 2,571 participants were included. Most were female (n = 2,241; 87%), and 38% (n = 976) had diffuse SSc. Mean (±SD) age was 54.9 (±12.7) years and duration since onset of first non‐Raynaud phenomenon symptom was 10.8 (±8.7) years. MDC95 estimate was 0.41 points (95% CI 0.40–0.42) for the HAQ‐DI, between 4.88 points (95% CI 4.72–5.05) and 9.02 points (95% CI 8.80–9.23) for the seven PROMIS‐29v2.0 domains, and 5.16 points (95% CI 5.06–5.26) for the PHQ‐8. MDC95 estimates were not materially different across subgroups. Conclusion: MDC95 and MDC90 estimates were precise and similar across age, sex, and SSc subtype groups. HAQ‐DI MDC95 and MDC90 were substantially larger than previous estimates of HAQ‐DI minimal important difference from several small studies. Minimally important differences of all measures should be evaluated in large studies using anchor‐based methods. [ABSTRACT FROM AUTHOR]

Structure from motion (SfM) photogrammetry coupled with multiview stereo (MVS) techniques are widely used for generating topographic data for monitoring change in surface elevation. However, study sites on remote glaciers and ice caps often offer suboptimal conditions, including large survey areas, complex topography, changing weather and light conditions, poor contrast over ice and snow, and reduced satellite positioning performance. Here, we provide a review of methodological considerations for conducting aerial photography surveys under challenging field conditions. We generate topographic reconstructions, outlining the entire workflow, from data acquisition to SfM-MVS processing, using case studies focused around two small glaciers in Arctic Canada. We provide recommendations for the selection of photographic and positioning hardware and guidelines for flexible survey design using direct measurements of camera positions, thereby removing the need for ground control points. The focus is on maximising hardware performance despite inherent limitations, with the aim of optimising the quality and quantity of the source data, including image information and control measurements, despite suboptimal conditions. [ABSTRACT FROM AUTHOR]

Objectives Subjects and Methods Results Conclusion To characterise the long‐term success rate of ventral onlay buccal mucosa graft urethroplasty (vBMG) in the management of bulbar urethral stricture disease (USD), assess patient‐reported postoperative satisfaction and decision regret, and delineate clinical factors impacting patient‐reported metrics.Patients with prior vBMG for bulbar USD, performed at Cleveland Clinic between 2003 and 2022, were contacted and brief structured interviews were performed. Stricture recurrence and need for secondary procedures, baseline demographics, and patient‐reported outcome surveys were collected. The surveys included the Decision Regret Scale (DRS), the Urethral Stricture Symptom Impact Measure (USSIM) and the 10‐item Patient‐Reported Outcomes Measurement Information System Short Form, version 1.2 (PROMIS‐10). Descriptive, univariate and multivariable analyses were performed for clinical outcomes and survey responses.A total of 104 patients recorded responses. The median patient age was 49 years and the median follow‐up was 7.4 years at time of survey. The median graft length was 5 cm and 38% of patients underwent partial thickness augmented anastomotic urethroplasty. At time of follow‐up, 10 patients underwent a secondary procedure. Moderate to severe regret on the DRS was found in 12% of patients, and greater regret was associated with recurrence. The mean physical and mental health PROMIS‐10 Global Health T‐scores were 52 and 53. The mean total USSIM score was 56. A significant correlation was found between USSIM and DRS scores, with higher DRS score and recurrence negatively impacting USSIM score. USSIM scoring across all domains was significantly worse in the moderate to severe DRS group.This study showed that vBMG for bulbar USD confers both high success rates and patient‐reported satisfaction at extended follow‐up, based on emerging and validated patient‐reported outcome measures. [ABSTRACT FROM AUTHOR]

Background and Objectives: Accurate diagnosis of cardiovascular diseases often relies on the electrocardiogram (ECG). Since the cardiac vector is located within a three-dimensional space and the standard ECG comprises 12 projections or leads derived from it, redundant information is inherently present. This study aims to quantify this redundancy and its impact on classification tasks using Convolutional Neural Networks (CNNs) in cardiovascular diseases. Methods: We employed signal theory and mutual information to introduce a novel redundancy metric and explored techniques for redundancy augmentation and reduction. This involved lead selection and transformation to evaluate the effects on neural network performance. Results: Our findings indicate that optimizing input configurations through redundancy reduction techniques can enhance the performance of deep learning models in cardiovascular diagnostics, provided that the information is preserved and minimally distorted. Conclusion: For the first time, this research has quantified the redundancy present in the input by validating various redundancy reduction techniques using a CNN. This discovery paves the way for advancing biomedical signal processing research, simplifying model complexity, and enhancing diagnostic performance in cardiovascular medicine within reduced lead systems, such as Holter monitors or wearables. [ABSTRACT FROM AUTHOR]

In this study, we examined how the nonlinearity  α  of the Langevin equation influences the behavior of extremes in a generated time series. The extremes, defined according to run theory, result in two types of series, run lengths and surplus magnitudes, whose complex structure was investigated using the visibility graph (VG) method. For both types of series, the information measures of the Shannon entropy measure and Fisher Information Measure were utilized for illustrating the influence of the nonlinearity  α  on the distribution of the degree, which is the main topological parameter describing the graph constructed by the VG method. The main finding of our study was that the Shannon entropy of the degree of the run lengths and the surplus magnitudes of the extremes is mostly influenced by the nonlinearity, which decreases with with an increase in  α. This result suggests that the run lengths and surplus magnitudes of extremes are characterized by a sort of order that increases with increases in nonlinearity. [ABSTRACT FROM AUTHOR]

A wide range of tasks in network analysis, such as clustering network populations or identifying anomalies in temporal graph streams, require a measure of the similarity between two graphs. To provide a meaningful data summary for downstream scientific analyses, the graph similarity measures used for these tasks must be principled, interpretable, and capable of distinguishing meaningful overlapping network structure from statistical noise at different scales of interest. Here we derive a family of graph mutual information measures that satisfy these criteria and are constructed using only fundamental information theoretic principles. Our measures capture the information shared among networks according to different encodings of their structural information, with our mesoscale mutual information measure allowing for network comparison under any specified network coarse-graining. We test our measures in a range of applications on real and synthetic network data, finding that they effectively highlight intuitive aspects of network similarity across scales in a variety of systems. Graph similarity measures are essential for downstream tasks including clustering, embedding, and regression with populations of networks. Here the authors derive a family of graph mutual information measures that allow for a principled, interpretable, and efficient comparison of networks at multiple scales. [ABSTRACT FROM AUTHOR]

ABSTRACT Output fluctuation and lower transmission efficiency under load and mutual inductance variation are hot concerned in the wireless charging system for power batteries. In this paper, a decoupled tracking strategy is proposed to realize constant voltage (CV) or current (CC) output and high transmission efficiency. The circuit model of series–series compensation network is built, and corresponding transmission characteristics can be derived. First, the load and mutual inductance value can be estimated by measuring the primary electrical information, including the inverter output voltage, current, and the phase error between them. Then load‐independent voltage or current output characteristics under coils misalignment can be maintained by tracking the optimal switching frequency of inverter part. In addition, the value of output voltage or current can be adjusted flexibly for different operation occasions by the employment of pulse‐width modulation. As a result, the load‐independent output characteristics realization and output adjustment can be decoupled. Based on only the primary measuring information, the CV/CC output can be maintained via the proposed hybrid control strategy when the coils misalignment and load variation happen, increasing the robustness of whole wireless power transfer (WPT) system. Furthermore, the soft switching of all power switches in the inverter part can be realized to reduce the switching loss. Compared with previous research, the proposed wireless charging system has a higher power density and a simplified control strategy. Finally, an experimental platform with 60‐V charging voltage and 3.6‐A charging current is built to verify the feasibility of the proposed sys‐tem and control method. [ABSTRACT FROM AUTHOR]

The use of digital image correlation for modal analysis is becoming an appealing option thanks to its non-contact and full-field measurement process. However, frequency response function (FRF) estimation can be challenging due to the limited number of time domain data and heavy measurement noise. Thereby, the present work aims to propose a method which improves the estimation accuracy of point-wise FRFs. Firstly, a Gaussian-process-based spatial-frequency model is proposed, which makes use of the intrinsic properties of the FRF and the local spatial information of field measurements. Then, a Bayesian solution is developed, which is enforced by a stable and efficient numerical procedure. Finally, the effectiveness of the proposed method is verified by making a comparison with the spectral estimator through the use of simulated data, and it is further validated based on an experimental application. [ABSTRACT FROM AUTHOR]

This paper studies the predictive power of a set of systemic risk measures for macroeconomic downside risks in China. The quantile single-index model (QSIM) is used to select and combine systemic risk measures to depict the lower tail of macroeconomy distribution. The out-of-sample results show that QSIM provides prominent and robust prediction, as it aggregates all relevant systemic risk measures information and captures parameter nonlinearity. Moreover, we uncover the risk drivers behind macroeconomic downturns using the variable selection technique. The results provide an early warning mechanism for regulators and a criterion for researchers to select systemic risk measures. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethodsResultsConclusionInformational social support can have both positive and negative effects on employees. This research aims to examine the curvilinear relationship between informational social support and employees’ cognitive processes, specifically cognitive depletion and creativity. Additionally, we investigate the moderating role of emotional stability on this curvilinear relationship, particularly regarding cognitive depletion.A total of 108 male employees in South Korea participated in the study, completing 864 two-wave, time-lagged daily diary questionnaires. The surveys measured informational social support, cognitive depletion, creativity, and emotional stability.The findings reveal that informational social support enhances employees’ cognitive processes up to a certain threshold, after which its effects become detrimental, demonstrating a curvilinear pattern. Furthermore, emotional stability moderates this relationship: emotionally stable employees show a linear relationship between informational social support and cognitive depletion, while emotionally unstable employees exhibit a curvilinear relationship.Our results suggest that excessive informational social support may harm employees’ cognitive processes, indicating that there is an optimal level of support, beyond which the effects become counterproductive. [ABSTRACT FROM AUTHOR]

In this work, we explore the impact of adaptive fuzzy measures on edge detection, aiming to enhance how computers interpret images by identifying edges more accurately. Traditional methods rely on analysing changes in image brightness to locate edges, but they often use fixed rules that do not account for the unique characteristics of each image. Our approach differs by adjusting fuzzy measures based on the information within specific areas of an image under a sliding window approach, utilizing a variety of fusion functions and generalizations of the Choquet integral to analyse and combine pixel data. The proposed method is flexible, allowing for the adaptation of measures in response to the image's local features. We put our method to the test against the well‐established Canny edge detector to evaluate its effectiveness. Our experimental results suggest that by adapting fuzzy measures for each image section, we can improve edge detection results. [ABSTRACT FROM AUTHOR]

This study explores the use of TikTok by public broadcasters France TV, BBC and SVT to measure its informational and promotional relevance on the platform, and to identify the types of videos that generate the highest levels of engagement among users. By examining the news profile associated with the information and the corporate profile of each of the selected broadcasters, 120 publications were analyzed, counting the number of users and interactions, including likes and levels of engagement of the content. In addition, a content analysis was carried out focusing on the formal, promotional and informative characteristics of the posts. The findings revealed an interest in both promotional and informational content shared by the platforms on TikTok. In the case of SVT, higher levels of engagement are observed in comparison to the BBC and France TV profiles. Among the contents with the highest engagement, those of an informative kind with a focus on social issues stand out, highlighting proximity and immediacy. In the promotional domain, videos about events and cultural content stand out. From a structural point of view, content designed specifically for the platform predominates, as opposed to adaptations and with a duration of <1 min. [ABSTRACT FROM AUTHOR]

GHOST (Globally Harmonised Observations in Space and Time) represents one of the biggest collections of harmonised measurements of atmospheric composition at the surface. In total, 7 275 148 646 measurements from 1970 to 2023, of 227 different components from 38 reporting networks, are compiled, parsed, and standardised. The components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties. The main goal of GHOST is to provide a dataset that can serve as a basis for the reproducibility of model evaluation efforts across the community. Exhaustive efforts have been made towards standardising almost every facet of the information provided by major public reporting networks, which is saved in 21 data variables and 163 metadata variables. Extensive effort in particular is made towards the standardisation of measurement process information and station classifications. Extra complementary information is also associated with measurements, such as metadata from various popular gridded datasets (e.g. land use) and temporal classifications per measurement (e.g. day or night). A range of standardised network quality assurance flags is associated with each individual measurement. GHOST's own quality assurance is also performed and associated with measurements. Measurements pre-filtered by the default GHOST quality assurance are also provided. In this paper, we outline all steps undertaken to create the GHOST dataset and give insights and recommendations for data providers based on the experiences gleaned through our efforts. The GHOST dataset is made freely available via the following repository: 10.5281/zenodo.10637449. [ABSTRACT FROM AUTHOR]

In order to address the issue of insufficient ability to identify and measure the key information of non-stationary signals collected in practical industrial fields such as logistics transportation, state detection, and fault diagnosis, this paper proposes a method to identify and measure the key information based on variational mode decomposition (VMD), convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and support vector machine (SVM). First, the non-stationary signal is reconstructed by using VMD and linear correlation decomposition. Second, the feature matrix is constructed according to the upper envelope feature, moving kurtosis, and moving root mean square. Finally, CNN-LSTM-SVM is input to identify and measure the key features. The experimental results demonstrate that the proposed method exhibits an outstanding performance on both synthetic and actual collected signals, with recognition accuracies of 99.17% and 99.02%, respectively. [ABSTRACT FROM AUTHOR]

Consistent Akaike information criterion (CAIC) is an adjusted form of classical AIC. This criterion was developed by modifying the penalty. As a result, we propose a novel AIC type criterion, called CAIC ( n α ). The proposed criterion includes a dynamic parameter for controlling the penalty further. The distinctive feature of CAIC ( n α ) is to penalize multicollinearity level considering the information complexity measures. CAIC ( n α ) requires the α parameter, and in addition, a procedure is proposed to estimate α based on the information complexity of the regression model. Monte Carlo simulations and real data set examples demonstrate that CAIC ( n α ) performs better than classical information criteria for the potential multicollinearity problems. [ABSTRACT FROM AUTHOR]

The objective in the study of reliability and survival theory is to have precision in the extracted information. The measure of dispersion in the information content has been newly introduced in the information theory, known as varentropy. Studying the variability in the uncertainty measure is found productive for stochastic systems conditional on survival. In this paper, we provide a novel stochastic order based on the notion of residual varentropy and study its properties. Further on the basis of the residual varentropy, novel classes of life distributions are identified and investigated in detail. Moreover, some applications of the proposed order are produced at the end. [ABSTRACT FROM AUTHOR]

The diagnosis of railway system faults is significant for its comfort, efficiency, and safety. The rail surface wear is the key impact factor when considering the health conditions of rails. This paper accomplishes contactless rail wear diagnosis by using multidimensional scaling based on a novel informational dissimilarity measure (IDM) to cluster intact and different worn rail profile data. The IDM uses weighted‐probability distribution of dispersion patterns to extract accurate time domain features from rail profile data, and the loss of information is minimized, which can greatly improve the accuracy for wear diagnosis. All the analyzing data for real experiments are collected by a laser scanner camera on an inspection car, where heavy‐haul railway rails with different types of surface wear are inspected. Experimental results with simulated and reality‐based data show that the proposed methods can identify worn profile data and discriminate different types of worn profiles more effectively when compared with existing methods. Thus, the proposed method offers a new thinking for the diagnosis of rail surface wear for heavy‐haul railways. [ABSTRACT FROM AUTHOR]

Summary: Viscosity–vaso‐occlusion (VVO) and haemolysis–endothelial dysfunction (HED) are pathophysiological mechanisms and clinical subphenotypes of sickle cell disease (SCD). Recurrent vaso‐occlusive crises (VOC) may lead to neuroplastic changes and pain sensitization. Among 257 SCD participants, we assessed the relationship of subphenotypes with pain sensitivity using quantitative sensory testing to identify heat pain thresholds (HPT) and pressure pain thresholds (PPT). VOC history and sleep, social and emotional functioning were assessed using the Adult Sickle Cell Quality of Life Measurement Information System. The 'elbow method' determined the optimal number of clusters as three. Clustering was performed using K‐prototypes. Among clusters 2 and 3, VOC frequency and severity were higher. Clusters 1 and 3 had lower haemoglobin, higher reticulocytes and lactate dehydrogenase and more leg ulcers. In multivariate regression, cluster 3 was associated with approximately 13.6% lower PPT compared to cluster 1, and female sex was associated with decreases in PPT and HPT at the hands and feet (p < 0.001). Hydroxyurea use and unit increases in sleep functioning and age were associated with approximately 20.1% higher foot‐PPT, 6.8% higher hand‐PPT and 2.5% higher hand‐HPT and foot‐HPT respectively. Findings suggest that a third subphenotype with mixed VVO and HED features and worse pain sensitization may exist. [ABSTRACT FROM AUTHOR]

In this study, we disclose several statistical properties of concomitants of dual generalized order statistics (DGOSs) under a generic setting from the Sarmanov family of bivariate distributions. For this family, cross-moments and joint distributions of concomitants of DGOSs are explored. These results' implications for order statistics and record values are examined. Extropy and cumulative residual extropy (CRE), two well-known information measures, are also investigated. This study offers a few beautiful symmetrical relationships that these inaccuracy measurements satisfy. In addition, based on the concomitants of DGOSs, the issue of estimating the negative cumulative residual extropy (NCRE), empirical NCRE and NCE are investigated using the empirical technique. Lastly, a set of bivariate data from the real world is examined. [ABSTRACT FROM AUTHOR]

Event‐related potentials (ERPs) have been used with the concealed information test (CIT) to detect concealed recognition of specific stimuli (i.e., "probes"). While most research has focused on the P300 component, which is larger for infrequent probes than for frequent control stimuli (i.e., "irrelevants"), some studies have investigated an earlier ERP component, the anterior N2, with mixed results. Although some studies have reported a larger anterior N2 for probes than irrelevants (N2 enhancement), other studies, including our own, have not found such an effect. The present study aimed to replicate and extend our previous findings using the same CIT paradigm and measurement parameters. Results of Bayesian analyses show strong evidence against the hypothesis of anterior N2 enhancement by probes, replicating our previous work. Bayesian analyses also show strong evidence against the hypothesis of N2 enhancement for the three components revealed by a temporal principal component analysis (PCA) conducted to disentangle potentially overlapping ERP effects. In conclusion, whereas the CIT has shown promise in detecting recognition of specific information, anterior N2 enhancement cannot be used as an electrophysiological measure of concealed information across CIT paradigms. Finding reliable markers of concealed information is critical for forensic applications. There have been claims that an event‐related potential, the anterior N2, is enhanced when concealing information. This electroencephalographic study directly replicates and extends our previous findings and shows that the anterior N2 is not a general marker of concealed information. [ABSTRACT FROM AUTHOR]

In response to the problems of frequent occurrence of downhole failures, high risk of failures, low warning efficiency, and relatively lagging safety monitoring technology, this paper presents the design of a monitoring system for failure risk of downhole drilling tools based on information measurement and risk warning. Field experiments were conducted to provide a scientific decision-making basis for the design and risk control of complex formation drilling. This system directly measures near-bit mechanical parameters and engineering parameters, and transmits the measured parameters to the drilling risk analysis and assessment module in real time by using the drilling fluid pulse, by which the received data are analyzed and calculated to determine the type of drilling risk and assess the risk level. Through pre-drilling analysis and assessment, real-time downhole monitoring, surface data acquisition, and a comprehensive analysis system platform, the downhole conditions are accurately determined, and feedback solutions are analyzed to achieve the purpose of reducing drilling risks, improving drilling efficiency and reliability of drilling assembly, and optimizing drilling technical measures, to better study the dynamic safety of downhole drilling tools. Field tests confirmed that the downhole safety system is fully functional and has a stable performance. The accuracy rate of the risk assessment is higher than 95%, and some technical indexes have reached the level of similar monitoring systems abroad. The research shows that the downhole safety monitoring system could reduce the drilling risk and drilling cost in deep complex formations. It could create great economic benefits for it has solved the problem of low early warning efficiency of downhole safety accidents. [ABSTRACT FROM AUTHOR]

This study compares the overlap among author-furnished keywords, Library of Congress Subject Headings and a consolidated controlled vocabulary for articles published in Annals of Library & Information Studies, published by NISCAIR from 2018 to 2023, India. The study focuses on the effectiveness of controlled vocabulary for keyword generation. The work is intended to contribute to the literature on author keywords versus keyword standardization in measuring information retrieval efficacy in real-time. The aggregated controlled vocabulary constructed for this study provided a positive result, showing the usefulness and requirements of such a robust controlled vocabulary. The study reflects the extended views of thesauri for a standard author keyword suggester or recommender system. [ABSTRACT FROM AUTHOR]

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research. [ABSTRACT FROM AUTHOR]

The tendency for individuals to mind wander is often measured using experience sampling methods in which probe questions embedded within computerized cognitive tasks attempt to catch episodes of off-task thought at random intervals during task performance. However, mind-wandering probe questions and response options are often chosen ad hoc and vary between studies with extant little guidance as to the psychometric consequences of these methodological decisions. In the present study, we examined the psychometric properties of several common approaches for assessing mind wandering using methods from item response theory (IRT). IRT latent modeling demonstrated that measurement information was generally distributed across the range of trait estimates according to when probes were presented in time. Probes presented earlier in time provided more information about individuals with greater tendency to mind wandering than probes presented later. Furthermore, mind-wandering ratings made on a continuous scale or using multiple categorical rating options provided more information about individuals' latent mind-wandering tendency – across a broader range of the trait continuum – than ratings dichotomized into on-task and off-task categories. In addition, IRT provided evidence that reports of "task-related thoughts" contribute to the task-focused dimension of the construct continuum, providing justification for studies conceptualizing these responses as a kind of task-related focus. Together, we hope these findings will help guide researchers hoping to maximize the measurement precision of their mind wandering assessment procedures. [ABSTRACT FROM AUTHOR]

Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design (Cavagnaro et al., 2010). ADO dynamically identifies stimuli that, in expectation, yield the most information about a hypothetical construct of interest (e.g., parameters of a cognitive model). To calculate this expectation, ADO leverages the modeler's existing knowledge, specified in the form of a prior distribution. Informative priors align with the distribution of the focal construct in the participant population. This alignment is assumed by ADO's internal assessment of expected information gain. If the prior is instead misinformative, i.e., does not align with the participant population, ADO's estimates of expected information gain could be inaccurate. In many cases, the true distribution that characterizes the participant population is unknown, and experimenters rely on heuristics in their choice of prior and without an understanding of how this choice affects ADO's behavior. Our work introduces a mathematical framework that facilitates investigation of the consequences of the choice of prior distribution on the efficiency of experiments designed using ADO. Through theoretical and empirical results, we show that, in the context of prior misinformation, measures of expected information gain are distinct from the correctness of the corresponding inference. Through a series of simulation experiments, we show that, in the case of parameter estimation, ADO nevertheless outperforms other design methods. Conversely, in the case of model selection, misinformative priors can lead inference to favor the wrong model, and rather than mitigating this pitfall, ADO exacerbates it. [ABSTRACT FROM AUTHOR]

This study investigates the impact of digital transformation (DT) on trade credit (TC) within Chinese A-share listed manufacturing companies from 2008 to 2020. Utilizing information asymmetry theory and signal transmission theory, the study explores the relationship between DT and TC. Our findings reveal that DT has a notably positive effect on TC, with this impact being more pronounced in privately-owned enterprises, small and medium-sized entities, and particularly those outside the high-tech industry. Additionally, DT is found to foster TC expansion through enhanced cooperation within supply chains and improved relationships with suppliers and customers. These insights offer a comprehensive understanding of how DT influences corporate TC financing behavior and have significant implications for DT practices and policy decisions. [ABSTRACT FROM AUTHOR]

I propose a novel measure of information share, termed tail information share (TIS), which focuses on modeling the tail dependence of price innovations using copulas. I discuss its detailed technical properties, including unique identifiability, estimation procedures, and statistical properties. The proposed TIS improves over two commonly used measures by providing meaningful economic rationale and unique identifiability. My simulation studies indicate that TIS can yield more accurate estimates of market-specific contributions to price discovery when tail dependence is present. Additionally, I demonstrate the asymptotic consistency and efficiency of TIS estimators. An empirical illustration is provided using a new dataset of high-frequency crude oil futures. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of buildings is an important element of the effort to address global warming. The thermal performance of building envelopes is the most important thermal and physical property affecting energy performance. Therefore, identifying the thermal performance of a building envelope is essential to applying effective energy-saving measures. The U-value is a quantitative indicator of the thermal performance of the building envelope quantitatively. Methods for determining the U-value are largely classified into passive methods, which use building information without measurement campaigns, and active methods, which conduct in situ measurements. This paper reviews and evaluates the most commonly used methods and experimental results of previous studies to determine the actual U-value of a building envelope. Accordingly, this paper focuses solely on field measurement studies, excluding laboratory measurements. Comparing the existing methods used to determine the U-value can help researchers choose appropriate field measurement methods and future research directions. [ABSTRACT FROM AUTHOR]

Plain language summary Accurate staging improves lung cancer survival by increasing the chances of delivering stage‐appropriate therapy. However, there is underutilization of, and variability in, the use of guideline‐recommended diagnostic tests used to stage lung cancer. Consequently, the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) convened the Triage for Appropriate Treatment Task Group—a multidisciplinary expert and stakeholder panel—to identify knowledge and/or resource gaps contributing to guideline‐discordant staging and make recommendations to overcome these gaps. The task group determined the following: Gap 1: facilitators of and barriers to guideline‐concordant staging are incompletely understood; Recommendation 1: identify facilitators of and barriers to guideline‐concordant lung cancer staging; Gap 2: the level of evidence supporting staging algorithms is low‐to‐moderate; Recommendation 2: prioritize comparative‐effectiveness studies evaluating lung cancer staging; Gap 3: guideline recommendations vary across professional societies; Recommendation 3: harmonize guideline recommendations across professional societies; Gap 4: existing databases do not contain sufficient information to measure guideline‐concordant staging; Recommendation 4: augment existing databases with the information required to measure guideline‐concordant staging; Gap 5: health systems do not have a performance feedback mechanism for lung cancer staging; Recommendation 5: develop and implement a performance feedback mechanism for lung cancer staging; Gap 6: patients rarely self‐advocate for guideline‐concordant staging; Recommendation 6: increase opportunities for patient self‐advocacy for guideline‐concordant staging; and Gap 7: current health policies do not motivate guideline‐concordant lung cancer staging; Recommendation 7: organize a representative working group under the ACS NLCRT that promotes policies that motivate guideline‐concordant lung cancer staging.Staging—determining the degree of cancer spread—is important because it helps clinicians choose the best cancer treatment. Receiving the best cancer treatment leads to the best possible patient outcomes. Practice guidelines are intended to help clinicians stage patients with lung cancer. However, lung cancer staging in the United States often varies from practice guideline recommendations. This report identifies seven opportunities to improve lung cancer staging. [ABSTRACT FROM AUTHOR]

We introduce a new inaccuracy measure in terms of Fisher information. The proposed information measure is referred to as Fisher-based inaccuracy information (FBII) measure. Next, we examine some properties of this information measure and specifically examine it for escort and equilibrium distributions. Further, we propose Bayes–Fisher-based inaccuracy information (BFBII) measure and examine its connection to Kullback–Leibler and chi-square divergence measures. Moreover, in three different optimization problems, we show that the harmonic-mixture distribution gives optimal information based on BFBII measure. Some examples of FBII measure and escort density related to skew-normal and Student-t distributions are also illustrated, and then are applied to fish condition factor time series. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Materials and Methods Results Conclusion To assess the feasibility of immediate (IIP), early (EIP) and delayed implant placement (DIP) for single tooth replacement in the premaxilla on the basis of the complete indication area of each approach in routine practice.Data from 100 patients (59 women, 41 men, all Caucasians) aged between 19 and 81 years old (mean age 51.71) who had been consecutively treated with a single implant in the premaxilla (13–23) in one private periodontal practice were retrospectively collected. Demographic data, diagnostic information and linear measurements were extracted from patient files and CBCTs. The feasibility of IIP, EIP and DIP was assessed for all cases by both authors, based on the following criteria: availability of apical bone, position of the tooth in relation to the morphology of the alveolar process, buccal bone morphology and presence of midfacial recession. The reasons for not being able to perform an approach, and the viable alternatives for each approach were secondary outcomes. DIP was considered to have been preceded by alveolar ridge preservation (ARP).Ninety‐two patients could be treated by means of IIP, EIP or DIP. In eight patients none of these approaches were possible as they required bone augmentation prior to implant placement. Fifty‐two patients (95% CI: 42%–62%) could by treated with IIP, 58 (95% CI: 48%–67%) with EIP and 88 (95% CI: 80%–93%) with DIP. The feasibility proportions of IIP and EIP were significantly lower than the one of DIP (p < 0.001). All patients who could be treated with IIP could also be treated with EIP or DIP. Lack of apical bone for implant anchorage was the main reason for not being able to perform IIP and EIP. Complete loss of the buccal bone wall and the need for bone augmentation prior to implant placement were the reasons for not being able to perform DIP.From the results of this retrospective CBCT analysis, DIP is nearly always possible in contrast to IIP and EIP. Therefore, and since it is much easier than IIP and EIP, inexperienced clinicians should mainly focus on ARP and DIP in clinical practice deferring IIP and EIP until more surgical skills have been acquired. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethodsResultsDiscussionConclusionAmatoxin-containing mushroom poisoning is a significant threat to public health worldwide. We report a mass poisoning of Galerina sulciceps-like mushrooms (Galerina cf. sulciceps) in Luzhou, Sichuan Province, China, aiming to offer insights for future prevention and treatment strategies.We performed a retrospective survey of mass mushroom poisoning patients admitted to our hospital. The demographic data, clinical presentations, laboratory findings, therapeutic measures and prognostic information were collected and analyzed. We used the 2020 Chinese consensus on the clinical diagnosis and treatment of amatoxin-containing mushroom poisoning to assess the severity of poisoning. Mushrooms were examined through morphological analysis, molecular biology identification, and toxin detection.Our patient cohort consisted of nine males and six females, with mean (±SD) age of 34.9 ± 13.0 years. Gastrointestinal symptoms were the first to manifest, with mean (±SD) latency period of 13.4 ± 3.9 h. The majority of patients (86.7%) experienced nausea, vomiting, and diarrhea. Liver dysfunction was noted in 66.7% of patients, and thrombocytopenia was present in 26.7% of patients. In terms of the severity of poisoning, there were 10 mild cases and 5 severe cases. The mushrooms were provisionally labeled as Galerina cf. sulciceps, containing the toxins α-amanitin, β-amanitin, and γ-amanitin. All patients eventually recovered.We report what appears to be a new type of mushroom that is morphologically and phylogenetically similar to the known Galerina sulciceps, but further study is required to determine if it represents a distinct species.This poisoning event was caused by unintentional ingestion of Galerina cf. sulciceps, an amatoxin-containing mushroom. Early symptoms are primarily gastrointestinal, with acute liver damage and coagulopathy being the main toxic effects. Thrombocytopenia is also prominent, particularly in severe cases. Accurate assessment and prompt, individualized, and intensive treatment are crucial for managing patients with acute Galerina cf. sulciceps poisoning effectively. [ABSTRACT FROM AUTHOR]

Recently, metasurface‐based photodetectors (metaphotodetectors) have been developed and applied in various fields. Metasurfaces are artificial materials with unique properties that have emerged over the past decade, and photodetectors are powerful tools used to quantify incident electromagnetic wave information by measuring changes in the conductivity of irradiated materials. Through an efficient microstructural design, metasurfaces can effectively regulate numerous characteristics of electromagnetic waves and have demonstrated unique advantages in various fields, including holographic projection, stealth, biological image enhancement, biological sensing, and energy absorption applications. Photodetectors play a crucial role in military and civilian applications; therefore, efficient photodetectors are essential for optical communications, imaging technology, and spectral analysis. Metaphotodetectors have considerably improved sensitivity and noise‐equivalent power and miniaturization over conventional photodetectors. This review summarizes the advantages of metaphotodetectors based on five aspects. Furthermore, the applications of metaphotodetectors in various fields including military and civil applications, are systematically discussed. It highlights the potential future applications and developmental trends of metasurfaces in metaphotodetectors, provides systematic guidance for their development, and establishes metasurfaces as a promising technology. [ABSTRACT FROM AUTHOR]

A mobile sampler for the collection of aerosol particles on an uncrewed aerial vehicle (UAV) was developed and deployed during three consecutive Pallas Cloud Experiment campaigns in the vicinity of the Sammaltunturi Global Atmosphere Watch site (67°58' N, 24°7' E, 565 m above sea level). The sampler is designed to collect aerosol particles onto Nuclepore filters, which are subsequently analysed for the temperature-dependent number concentration of ice-nucleating particles of the sampled aerosol with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). This setup is an easy and flexible way to connect INP concentration measurements with cloud microphysics. The sampler was flown with a fixed-wing UAV in different altitudes up to 1000 m above ground level. The total flight time ranges from 1 hour to more than 1.5 hours, depending on environmental conditions. Pressure, temperature and relative humidity are also measured to provide information about the meteorological flight conditions. The flow over the filter was maintained by a micro-diaphragm pump, providing around 10 standard litres per minute over a small filter (diameter of 25 mm) and around 11 standard litres per minute over a larger filter (diameter of 47 mm) at a pressure corresponding to 500 m above sea level. For a typical flight time of 1.5 hours, this results in a sampled air volume of about 930 to 1000 standard litres per flight, giving an INP detection limit of approximately 1.1 × 10−3 and 1.0 × 10−3 INPs per standard litre, respectively. For comparison to the flight results, a similar setup was deployed at ground level. The comparison shows a clear distinction from the water and handling blank background for both setups, proving the technical feasibility of the setups. Furthermore, for some flights, a shift between the two INP populations can be seen, indicating that ground-based INP measurements deviate from the samples collected on-board the UAV. [ABSTRACT FROM AUTHOR]

Two-characters continuation, which is a string with two characters emerging in linear sequence, can break through the encapsulation and independence of long solidified language chunks (words and phrases). In this way, two-characters continuation can measure the information of not only static language units (words and phrases) but also their combination in the text. Therefore, two-characters continuation is used as a measurement unit for investigating Chinese text's difficulty, to enhance the accuracy of measuring text's difficulty. Three different measurement methods of text's difficulty are proposed, which are respectively based on "continuation index of character", "new and stable two-characters continuation" and "emerging tendency of two-characters continuation". The results show that compared to other two methods, the measurement method of text's difficulty based on new and stable two-characters continuations has better effectiveness, whose accuracies for measuring text's difficulty with 6 levels, 3 levels and 2 levels difficulties can reach 36.4%, 64.6% and 79.6%, respectively. In addition, compared to Jiang and Wu's research works, the above measurement method also shows a better effectiveness. [ABSTRACT FROM AUTHOR]

Background: waist circumference (WC) is a component of metabolic syndrome (MetS) and an excellent marker for the risk of cardiovascular disease (CVD) in children. This study aimed to provide information on the anatomical measurement sites of WC and their comparative correlation with MetS and its components in children. Methods: the literature search included papers published between January 2005 and September 2023 that met the following criteria: pediatric patients (2-18 years), WC measurement at different anatomical sites (≥ 2), and CVD risk by MetS. The quality of each study was determined using the STROBE and modified GRADE scales. The meta-analysis evaluated the WCiliac-crest and WCmiddle. Results: five observational studies (total population: 1,224) were included. WC was measured at 2-4 anatomical sites. In all studies, the correlations between different WC measurement sites and CVD risk were similar. The STROBE assessment ranged from 12-20/22 and the GRADE was A for all the articles. The meta-analysis showed that the heterogeneity (I2 test) of the WCiliac-crest and WCmiddle with CVD variables was substantial. Conclusion: All WC measurement sites showed adequate correlation with CVD risk, with some small individual differences. WCnarrow and WCumbilucus have adequate consistency and could be excellent alternatives in daily clinical practice because of their ease of measurement. Further studies are needed to evaluate the correlation between different WC measurement sites and CVD risk in children stratified according to pubertal stage and sex. [ABSTRACT FROM AUTHOR]

Neighborhood rough sets (NRS) is widely used in various fields with good adaptability, and its related information measurement plays an important role in uncertainty analysis. In the existing research, although the three-layer granular structure of neighborhood decision system (NDS) has been proposed, there are not many related research on it, especially in the uncertainty measurement. Therefore, this paper firstly deeply discusses the expression of neighborhood dependence in the three-layer granularity structure of neighborhood decision system, as well as its relationship in three levels and some related properties. Secondly, considering the influence of the fixed neighborhood radius(Nr) on the neighborhood model, we define the adaptive neighborhood radius by using the standard deviation and the neighborhood mean. Finally, we use the neighborhood dependence at the macro top level as the split node measurement function to construct the decision tree. Our experimental results show the reliability of the algorithm. [ABSTRACT FROM AUTHOR]

In this article, we approach the structure of the quantum measuring system in the Euclidean regime of the classicalized holographic tensor network from the perspective of integrated information theory. As a result, we obtain the following picture of the Euclidean regime. First, there are complexes, which are independently accompanied by the level and structure of experiences, determined from the full transition probability matrix of the whole particle system. Second, the cause–effect structures of independent complexes would be directly entangled by the physical information propagation in the whole particle system. Finally, distinct full transition probability matrices of the whole particle system that exhibit the maximum cause–effect power may coexist. [ABSTRACT FROM AUTHOR]

The assessment of methodological quality (MQ) in biomedical research is an area that has undergone dynamic development in the last 20 years on a global scale. MQ can be defined as a multidimensional and complex construct composed of items and domains. Different research groups have proposed tools for its assessment, among which our team is included with the development of the MInCir scales. Over the years, we have developed and validated scales to assess MQ in treatment or therapeutic procedure studies (MInCir-T), in diagnostic studies (MInCir-Dg), and prognosis studies (MInCir-Pr in its two versions, MInCir-Pr1 and MInCir-Pr2). However, as is the case with any measurement instrument, it is crucial to specify in a detailed and precise manner how it is applied, aiming to standardize measurements and minimize information biases. A detailed description is provided for the 4 domains and 8 items comprising the MInCir-Pr2 scale, specifying for each of them the characteristics to be assessed and scored in primary prognosis articles. The scale total score ranges from 7 to 60 points, with a cutoff point of 33 points (dichotomous) to define the MQ construct. This cutoff point allows classification into either adequate or high MQ (when the evaluated article receives a score of 33 points or higher), and inadequate or low MQ if the score is 32 points or less. The aim of this article was to elucidate and clarify the application of the MInCir-Pr2 scale for MQ in prognosis studies, through a guide intended to standardize MQ measurements using the MInCir-Pr2 scale, with the goal of enhance both intra- and interobserver reliability. [ABSTRACT FROM AUTHOR]

Fisher information is a measure to quantify information and have important inferential, scaling and uncertainty properties. Kharazmi and Asadi (Braz. J. Prob. Stat. 32, 795-814, 2018) presented the time-dependent Fisher information of any density function. Specifically, they considered a nonnegative continuous random (lifetime) variable X and define the time-dependent Fisher information and distance for density function of the residual random variable associated to X. In this article, we computed the mentioned measures for generalized gamma, Beta prime, generalized inverse Gaussian and truncated skew-normal densities. For generalized gamma, beta prime and generalized inverse Gaussian densities, exact expressions are provided and, for truncated skew-normal case, we computed the mentioned measures for truncated (at positive support) skew-normal random variables by using exact expressions in terms of cumulants and moments. Some numerical results are illustrated. [ABSTRACT FROM AUTHOR]

This paper investigates secure output consensus problem of heterogeneous multi-agent systems (HMASs) under denial-of-service (DoS) attacks. First, an adaptive dynamic compensator depending on local measurement information is designed for tracking the signal of the virtual exosystem. Second, for mitigating network communication load, a novel adaptive control protocol is developed by introducing dynamic event-triggered control and quantized control strategies. Moreover, Zeno behavior can be eliminated under the proposed scheme. Third, the secure output consensus of HMASs under DoS attacks can be guaranteed by satisfying the designed sufficient conditions. Finally, simulation is shown to verify reliability of the proposed control protocol and theory. [ABSTRACT FROM AUTHOR]

Female patients frequently experience worse clinical outcomes than male patients after undergoing vascular surgery procedures. However, it is unclear whether these sex-based disparities also impact mental health outcomes. This study was designed to investigate sex differences in patient-reported outcome measures of depression for patients undergoing vascular surgery. We retrospectively analyzed 107 patients (73 males and 34 females) who underwent vascular surgery procedures between January 2016 and April 2023. These patients completed a Patient-Reported Outcome Measurement Information System (PROMIS) Item Bank v1.0-Depression assessment 90 d before surgery and at least once after surgery. After stratifying patients by sex, we analyzed changes in PROMIS depression scores using a multiple mixed-effects linear regression model. Then, logistic regression was used to compare the proportion of patients who achieved a clinically meaningful difference in PROMIS depression score within 15 mo after surgery. There was no significant difference between female and male patients among rates of complications, length of hospital stay, or rates of nonhome discharge. However, female sex was associated with significantly improved PROMIS depression scores after surgery compared to male sex (P = 0.034). Furthermore, female patients were over 3-fold more likely than male patients to reach the minimal clinically important difference threshold for improvement in PROMIS depression scores (odds ratio 4.66, 95% confidence interval 1.39-15.61). These results suggest that female sex is associated with improved patient-reported measures of depression after undergoing vascular surgery. Clinicians should consider these mental health benefits when evaluating female patients for vascular interventions. • Females more likely to achieve minimal clinically important difference in Patient-Reported Outcome Measurement Information System depression after vascular surgery. • No sex differences found in clinical outcomes after vascular surgery. • Mental health outcomes are important to evaluate following surgical procedures. [ABSTRACT FROM AUTHOR]

Acquiring real-time status information of the distribution system forms the foundation for optimizing the management of power system operations. However, missing measurements, bad data, and inaccurate system models present a formidable challenge for distribution system state estimation (DSSE) in practical applications. This paper proposes a physics-informed graphical learning state estimation approach, to address these limitations by integrating power flow equations and GraphSAGE. The generalization ability of GraphSAGE for unknown nodes is used to perform inductive learning of measurement information. For unseen measurement points in the training set, the simulation proves that the proposed approach can still satisfactorily predict the state quantity. The training process is guided by power flow equations to ensure it has physical significance. Additionally, the possibility of applying the proposed approach to an actual distribution area is explored. Equivalent preprocessing of the three-phase voltage measurement data of the actual distribution area is conducted to improve the estimation accuracy of the transformer measurement points and simplify the computation required for state estimation. [ABSTRACT FROM AUTHOR]

A metric tensor for Riemann manifold Monte Carlo particularly suited for nonlinear Bayesian hierarchical models is proposed. The metric tensor is built from symmetric positive semidefinite log‐density gradient covariance (LGC) matrices, which are also proposed and further explored here. The LGCs generalize the Fisher information matrix by measuring the joint information content and dependence structure of both a random variable and the parameters of said variable. Consequently, positive definite Fisher/LGC‐based metric tensors may be constructed not only from the observation likelihoods as is current practice, but also from arbitrarily complicated nonlinear prior/latent variable structures, provided the LGC may be derived for each conditional distribution used to construct said structures. The proposed methodology is highly automatic and allows for exploitation of any sparsity associated with the model in question. When implemented in conjunction with a Riemann manifold variant of the recently proposed numerical generalized randomized Hamiltonian Monte Carlo processes, the proposed methodology is highly competitive, in particular for the more challenging target distributions associated with Bayesian hierarchical models. [ABSTRACT FROM AUTHOR]

This study assessed the impacts of a toll information sign with different toll lane configurations on queue length and collision risk at a toll plaza with an estimated high percentage of heavy vehicles (HVs). The toll information sign displays information about different toll payment methods for cars and HVs upstream of the toll booth. The impacts were assessed for the toll plaza of the Gordie Howe International Bridge under construction at the Windsor–Detroit international border crossing using a traffic simulation model. Results show that the toll information sign upstream of the toll plaza and converting the toll lanes with multiple toll payment methods to electronic toll collection (ETC)-only lanes reduced queue length and collision risk. However, increasing the number of HV-only lanes for a higher percentage of HVs increased lane-change collision risk. Thus, it is recommended that toll lane configurations be changed based on the percentage of HVs to reduce collision risk at a toll plaza. [ABSTRACT FROM AUTHOR]

This paper proposes nonparametric estimates for the two information measures extropy and entropy when a progressively Type-I interval censored data is available. Different nonparametric approaches are used for deriving the estimates, including: moments of the empirical cumulative distribution function and linear regression. The performance of the proposed estimates is studied under various censoring schemes via simulation studies. Furthermore, different real data sets are analyzed for illustrative purposes. The estimates based on linear approximation J^2 and H^2 outperform the other estimate in the majority of studied cases. [ABSTRACT FROM AUTHOR]