Search

Purpose: This study aims to develop an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline, comparing its reproducibility and observer consistency in image analysis with physicians of varying levels of expertise. Design/methodology/approach: An auto-RUSS was engineered using a 7-degree-of-freedom robotic arm, with real-time regulation based on force control and ultrasound visual servoing. Two phantoms were employed for the human-machine comparative experiment, involving three groups: auto-RUSS, non-expert (4 junior physicians), and expert (4 senior physicians). This setup enabled comprehensive assessment of reproducibility in contact force, image acquisition, image measurement and AI-assisted classification. Radiological feature variability was measured using the coefficient of variation (COV), while performance and reproducibility assessments utilized mean and standard deviation (SD). Findings: The auto-RUSS had the potential to reduce operator-dependent variability in ultrasound examinations, offering enhanced repeatability and consistency across multiple dimensions including probe contact force, images acquisition, image measurement, and diagnostic model performance. Originality/value: In this paper, an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline was proposed. Through comprehensive human-machine comparison experiments, the auto-RUSS was shown to effectively improve the reproducibility of ultrasound images and minimize human-induced variability. [ABSTRACT FROM AUTHOR]

Given k populations and assuming that independent samples are available from each of them, the problem of testing for the equality of the k population variances is addressed. In contrast to the classical setting, where k is kept fixed and the sample size from each population increases without bound, here k is assumed to be large and the size of each sample small in comparison to k. A new test is proposed. The asymptotic distribution of the test statistic is stated under the null hypothesis of equality of the k variances as well as under alternatives, which allows us to study the consistency of the test. Specifically, it is shown that the test statistic is asymptotically free distributed under the null hypothesis. Two bootstrap approximations to the null distribution of the test statistic are also investigated. The finite sample performance of the test based on the asymptotic null distribution and on the two bootstrap approximations, is studied via simulation. The proposal is applied to a real data set. [ABSTRACT FROM AUTHOR]

The paper considers the nonparametric Poisson regression problem with a regular equidistant design on the unit interval. The nonparametric estimation of the Poisson regression function is studied. The uniform consistency conditions are established and the limit theorems are proved for continuous functionals on C [ a , 1 - a ] , 0 < a < 1 2 . [ABSTRACT FROM AUTHOR]

This paper focuses on the estimation of parameters in linear models with fixed regressors and exchangeable errors, especially, these errors are assumed to be a subset of an infinite exchangeable sequence. We propose a modified M-estimation to estimate the slope parameter, which outperforms the traditional M-estimation when the random errors are exchangeable. The modified M-estimation utilizes a design point centralization technique, leading to a more suitable estimator with improved theoretical properties. To establish the asymptotic properties of the modified M-estimator, we also develop a weighted central limit theorem for exchangeable sequences, which is of independent interest. Regarding the intercept, we prove that there is no consistent estimator for the intercept when the exchangeable errors have non-zero covariance, and we propose an unbiased estimator for the intercept as a viable compromise. Based on our theoretical findings, we develop a simulation-based approach to approximate the confidence set of the slope, and we establish a prediction model specifically designed for linear models with exchangeable errors. Additionally, we illustrate the finite sample performance of the proposed method through various numerical simulations and a real data application. [ABSTRACT FROM AUTHOR]

The multivariate Regression model (MRM) is one of the most widely used models for multivariate statistical inference. In this paper, a closed-form and fully objective Bayes factor for comparing two MRMs is introduced. We also introduce a Bayes factor-based method for comparing several MRMs. It is well known that the arithmetic intrinsic Bayes factor (AIBF) does not satisfy the pairwise and multiple coherency conditions. So, the AIBF cannot be used in multiple hypotheses testing and model selection. Even in the case of only two competing hypothesis or models, lack of pairwise coherency leads to the embarrassing position of two Bayes factors for comparing two models instead of just one. In this paper, we have made a simple modification to the original definition and introduced the modified intrinsic Bayes factor (ModIBF) which satisfies the pairwise and the multiple coherency conditions. [ABSTRACT FROM AUTHOR]

In the article, the error variance estimator σ ^ 2 and its finite sample size bounds are investigated in the framework of a general linear model under linear restrictions (gLMLR) where no distributions are assumed except for some moment conditions and the covariance matrix of the response may be singular, which extends the results in Lindholm and Wahl (2020). In particular, we overcome the difficulty that the matrix of quadratic form in σ ^ 2 is not idempotent. The estimator is obtained by the proposed restricted and proxy-type generalized least square procedure. Meanwhile, the estimable function of the regression coefficient β is estimated, too. Besides, the finite sample properties of these estimators and their consistency are also established. In the end, a simulation study and a real data analysis are done to examine the finite performance of these estimators. [ABSTRACT FROM AUTHOR]

Background: Procalcitonin (PCT) is a useful biomarker for infection and especially useful for sepsis management. Multiple platforms, including the chemiluminescence immunoassay (CLIA), have been used for serum PCT analysis. However, the results from different analytical platforms should be evaluated to determine if they can be mutually substituted in the same laboratory. Methods: The serum PCT were analyzed on the Mindray CL-6000i chemiluminescent immunoassay (candidate method), the Roche Elecsys, and the VIDAS PCT chemiluminescence immunoassay platforms (comparative measurements), and the results were evaluated and compared, following the CLSI EP09-A3 guidelines, by using patient samples with different PCT concentrations. Results: The median of difference was 0.04 (95% CI: 0.038 - 0.045) between the candidate method and the comparative measurements for the concentration interval of < 0.5 ng/mL. The median of percentage difference was 6.6% (95% CI: 5.5% - 8.7%) for the concentration interval of 0.5 - 2.0 ng/mL, the median of difference was 0.11 (95% CI: 0.06 - 0.17) for the concentration interval of 2.0 - 10.0 ng/mL, and the median of percentage difference was -4.7% (95% CI: -6.1% - 2.4%) for the concentration interval of 10.0 - 100.0 ng/mL. The acceptable bias was ± 0.055 (± 10.4%) at 0.53 ng/mL (low value), and the acceptable bias was ± 0.83 (± 9.0%) at 9.34 ng/mL (high value). The bias between the candidate method and comparative measurements was acceptable for the full concentration ranges. Conclusions: The bias between the PCT results from Mindray, Roche, and VIDAS was acceptable. Therefore, the results of the three analytical platforms were comparable, and they may be mixed-used in the same institution. [ABSTRACT FROM AUTHOR]

Rank regression plays a fundamental role in statistical data analysis due to its robustness and high efficiency, and has been widely used in various scientific fields. However, when the data size is huge or massive, but the computing resource is limited, it can lead to an unacceptably computational cost for rank regression estimation. To handle this issue, this paper applies a random perturbation subsampling method to rank regression models. Specifically, we develop two repeatedly random perturbation subsampling algorithms to find the estimation of parameters. Two different weighting strategies with product weights and additive weights are examined in the objective function. Differing from the existing optimal and Poisson subsampling methods, our methods do not require the explicit calculation of subsampling probabilities for all data points, in which some unknown parameters often need to be estimated, thus making the implementation of our methods easier. Theoretically, statistical justifications are further provided for the proposed estimators including consistency and asymptotic normality. Extensive simulation studies and an empirical application are carried out to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Purpose: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized. Methods: We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives. Results: iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB <0]), which depends on estimated variance (larger with iSTMs given first-order noise). While iSTMs overestimate EVPI, their direction of bias for the probability of being cost-effective is ambiguous. Bias is larger when uncertainties in incremental costs and effects are negatively correlated since this increases INMB variance. Conclusions: iSTMs are useful for probabilistic economic evaluations. While more samples at the population uncertainty level are interchangeable with more microsimulations for estimating EINMB, minimizing iSTM bias in estimating decision uncertainty and VOI depends on sufficient microsimulations. Analysts should account for this when allocating their computational budgets and, at minimum, characterize such bias in their reported results. Highlights: Individual-level state-transition microsimulation models (iSTMs) produce biased but consistent estimates of the probability that interventions are cost-effective. iSTMs also produce biased but consistent estimates of the expected value of perfect information. The biases in these decision uncertainty and value-of-information measures are not reduced by more parameter sets being sampled from their population-level uncertainty distribution but rather by more individuals being microsimulated for each parameter set sampled. Analysts using iSTMs to quantify decision uncertainty and value of information should account for these biases when allocating their computational budgets and, at minimum, characterize such bias in their reported results. [ABSTRACT FROM AUTHOR]

The Bradley-Terry model is a common model for analyzing paired comparison data. Under differential private mechanism, there is a lack of asymptotic properties for the parameter estimator of parameters in this model. In this article, we show that the moment estimators of the parameters based on the differential private degree sequence with Laplace noise is uniformly consistent and asymptotically normal. Simulations are provided to illustrate asymptotic results. [ABSTRACT FROM AUTHOR]

The analysis of continuous events for any application involves the discretization of an event into sequences with potential historical dependencies. These sequences represent time stamps or samplings of a continuous process collectively forming a time series dataset utilized for training recurrent neural networks (RNNs) such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for pattern prediction. The challenge is to ensure that the estimates from the trained models are consistent in the same input domain for different discretizations of the same or similar continuous history-dependent events. In other words, if different time stamps are used during the prediction phase after training, the model is still expected to give consistent predictions based on the knowledge it has learned. To address this, we present a novel RNN transition formula intended to produce consistent estimates in a wide range of engineering applications. The approach was validated with synthetically generated datasets in 1D, 2D, and 3D spaces, intentionally designed to exhibit high non-linearity and complexity. Furthermore, we have verified our results with real-world datasets to ensure practical applicability and robustness. These assessments show the ability of the proposed method, which involves restructuring the mathematical structure and extending conventional RNN architectures, to provide reliable and consistent estimates for complex time series data. [ABSTRACT FROM AUTHOR]

AbstractIn the field of neuropsychology, the accuracy of neuropsychological data interpretation has significant implications for both research and clinical practice. The process of test interpretation is fraught with challenges, and a lack of consensus among neuropsychologists can lead to discrepancies in assessment outcomes. Smith et al. (2020) identified this concerning lack of consensus in test score interpretation, raising questions about the standardization of interpretive practices within the field. Similarly, Tuokko and Gabriel (2006) reported moderate interrater agreement in identifying cognitive impairments, with a 77.7% consensus rate, using both history and all available information. The current study investigated the extent to which independent neuropsychologists could reach consistent diagnostic conclusions using only numeric data and the statistical methods available in the Meyers Neuropsychological Battery (MNB), without access to clinical history or contextual information. The results demonstrated a high degree of accuracy, with an overall agreement rate of 85.5% to 92.2% among the six raters. This finding underscores the potential of standardized statistical approaches to enhance the objectivity and consistency of neuropsychological assessments. The study advances neuropsychological assessment methodology by showing that statistical pattern-matching techniques can yield reliable and uniform diagnostic outcomes, even in the absence of additional clinical data. [ABSTRACT FROM AUTHOR]

The Asymmetric Information Management (AIM) technique encourages truth tellers to adopt a forthcoming verbal strategy and liars a withholding strategy. We investigated the effectiveness of this technique using a follow-up statement. We predicted that truth tellers in the AIM condition would provide more new and overall detail, with a higher proportion of complications, compared to control truth tellers, whereas AIM liars would use more self-handicapping strategies and common knowledge details, with fewer commissions, repetitions, and less overall detail than control liars. This was tested using a mixed-factors design in which truth tellers (n = 65) gave an honest recollection of a recent trip while liars fabricated a story (n = 62). Participants provided an initial statement and half received the AIM instructions prior to providing their second statement. Truth tellers in the AIM condition provided more new detail and complications in their second statement compared to truth telling controls. Unlike previous research, AIM instructions had no significant effect on liars' statements. No other differences emerged. In conclusion, the AIM instructions elicit some new information from truth tellers but do not improve classification from liars. [ABSTRACT FROM AUTHOR]

If computers or robots were to replace human scientists, should they adhere to our established principles of the Philosophy of Science? We have been taught to value consistency, Popperian falsifiability, and Occam's razor (also known as the principle of parsimony). While these traditional philosophical principles are valuable, they might limit the exploration of complex phenomena that require more nuanced or multifaceted approaches. Specific formal contexts exist where these principles falter when confronted with reality, as traditional scientific methods may reduce cognitive power. This paper formally highlights the limitations of traditional scientific and philosophical principles through the mathematics of computability (which will be considered softly). [ABSTRACT FROM AUTHOR]

There is evidence that mastery motivation contributes to developmental outcomes, both for typically developing individuals and for those with disabilities such as Down syndrome. Mastery motivation appears to be a stable trait, at least during early childhood, but research with adults has been restricted by the absence of an appropriate measure. The current study investigated the stability and consistency of parent-reported mastery motivation for 21 individuals with Down syndrome across 20 years. Parents completed the Dimensions of Mastery Motivation Questionnaire (DMQ) when their child was aged 4–6 years and 11–15 years. They completed the Dimensions of Adult Mastery Motivation Questionnaire (DAMMQ) when their son or daughter was 23–27 years old. There were strong positive correlations among measures of mastery motivation across the three time points. Persistence decreased significantly from early childhood to adolescence but increased from adolescence to adulthood. Most individual profiles fitted this pattern, with only one of the 21 participants showing continual declines in persistence. For individuals with Down syndrome, patterns of mastery motivation may be developed early in life and sustained into adulthood. [ABSTRACT FROM AUTHOR]

Performance of sport-related ballistic motor skills, like ball hitting in golf and baseball, requires wide movements to produce highly fast and spatially accurate movements. In this study, we assessed the effect of movement amplitude on directional accuracy in a ballistic hitting task. Participants performed the task of moving a manual handle over a flat surface to hit with high speed a moveable disc, aiming to propel it towards a frontal target. Five movement amplitudes were compared, ranging from 11.5 cm to 27.5 cm in steps of 4 cm. Kinematic analysis evaluated motions of the handle, disc, and arm joints. Results showed that greater movement amplitudes led to longer acceleration phases, with delayed peak velocities at the handle, shoulder and elbow, leading to higher contact and peak linear velocities of the handle, and higher angular velocities at the shoulder and elbow. Manipulation of movement amplitude led to no evidence for effects on either disc directional accuracy or variability. Results also revealed no evidence for differences in variability of contact velocity, peak velocity and time of peak velocity across movement amplitudes in the shoulder, elbow, and wrist. Our results indicated that greater movement amplitudes in hitting a spatial target lead to increased contact velocity while not affecting directional accuracy or movement variability. [ABSTRACT FROM AUTHOR]

The agreement between a wearable inertial sensor (GYKO, G) and the force platform (P) was assessed by evaluating test-retest and inter-rater reliability. Thirty-eight subjects were enrolled; the selected indices of balance were investigated over foot positions and (un)stable conditions. Intraclass correlation coefficient (ICC), standard error of measurement (SEM%) and minimal detectable change (MDC95%) were computed. For G, ICC bounds range from poor to excellent (0.040 ÷ 0.921), mean of 0.687 (= moderate reliability). Regarding P, ICC ranges from poor to excellent (0.070 ÷ 0.920), mean of 0.683 (= moderate reliability). For G, SEM% ranges from 11% to 47%; MDC95% from 30% to 132%. Concerning P, SEM% ranges from 7% to 41%; MDC95% from 21% to 114%. Finally, the inter-rater reliability ICC by comparing devices ranges from poor to excellent (−0.162 ÷ 0.911), mean of 0.338 (= poor reliability). GYKO appears to be a convenient tool with high consistency among multiple measurements but for specific clinic/research purposes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of China Medical University is the property of Journal of China Medical University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially over time, for example the financial series, so it is necessary to consider the autocorrelated structure of errors in functional regression background. To this end, this paper considers a multiple functional linear model with autoregressive errors. Based on the functional principal component analysis, we apply the least square procedure to estimate the functional coefficients and autoregression coefficients. Under some regular conditions, we establish the asymptotic properties of the proposed estimators. A simulation study is conducted to investigate the finite sample performance of our estimators. A real example on China's weather data is applied to illustrate the validity of our model. [ABSTRACT FROM AUTHOR]

This paper presents an efficient numerical approach for first-order delay differential equations containing a piece-wise constant delay. The strategy is based on a five-point hybrid block method that has been developed for ordinary differential equations. We will use the interpolation technique for the evaluation of delay terms that are not defined at the grid points. The main characteristics are discussed, including zero stability, local truncation errors, convergence and stability region. The method is easy to implement, and the numerical experiments show the efficiency and accuracy of the proposed method, compared to other methods appeared in the literature. [ABSTRACT FROM AUTHOR]

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times. [ABSTRACT FROM AUTHOR]

Incorporating corporate social responsibility (CSR) into organizational strategies has become essential, demonstrating a dedication to ethical conduct and sustainable practices. This paper investigates how consistency in CSR practices impacts organizational attractiveness. Drawing upon the theory of the continuum model of impression formation, two separate studies were undertaken to investigate the influence of CSR consistency (both consistent and inconsistent CSR) on the appeal of organizations. Besides, these studies aimed to evaluate the mediating roles of conceptual fluency and perceived corporate hypocrisy in this relationship, as well as the moderating effect of two corporate communication strategies (proactive and passive). The study found that perceptions of corporate hypocrisy played a significant mediating role in the link between inconsistent CSR practices and the appeal of an organization. This mediating effect was diminished by the use of proactive communication strategies. In contrast, conceptual fluency was identified as a key mediator in the relationship between consistent CSR practices and organizational attractiveness, with its mediating effect being enhanced by proactive communication strategies. This study makes a novel contribution by focusing on the temporal stability of CSR initiatives and broadens the understanding of whether sustained engagement in CSR activities over time confers greater organizational attractiveness than occasional or random initiatives. This study extends the theory of the relationship between perceived CSR and job seekers and provides guidance and recommendations for CSR activities and HR recruitment practices for companies in the post‐epidemic era. [ABSTRACT FROM AUTHOR]

Copyright of Arabic Language & Literature (1735-9767) is the property of University of Tehran and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Larq Journal for Philosophy, Linguistics & Social Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We translated the math novel (A certain ambiguity) during the days of Corona, when the universities were closed, with the hope that math can be brought to the society and reduce the distance between them. First, we will briefly introduce this novel and then we will give a relatively detailed review about it.

Climate change, primarily driven by CO2 emissions from energy and non-energy sectors, necessitates effective mitigation strategies. This study develops a stochastic diffusive model to capture the complex dynamics of CO2 concentration, human population growth, and energy production. The objectives are to enhance the predictive accuracy of existing models by incorporating diffusion effects and stochastic variability, offering insights for sustainable environmental policies. A novel numerical scheme, an extension of the Euler-Maruyama algorithm, is proposed to solve stochastic time-dependent partial differential equations governing the model. The scheme's consistency and stability are rigorously analyzed in the mean square sense. Findings reveal that increasing emission rate coefficients in energy and non-energy sectors exacerbates CO2 levels, emphasizing the need for stringent controls. The proposed scheme demonstrates superior accuracy to the non-standard finite difference method, establishing its efficacy in modeling complex environmental processes. This research contributes a robust computational tool to improve existing predictive models, aiding decision-making for long-term ecological sustainability. By addressing uncertainties in the environmental process, the work advances the understanding of interactions between population growth, energy production, and CO2 emissions, offering a significant improvement over the traditional modeling approach. The novelty lies in integrating stochastic dynamics with diffusion to better inform CO2reduction strategies. Doi: 10.28991/ESJ-2025-09-01-012 Full Text: PDF

Fluid loss changes the slurry's rheological and mechanical properties. Thus, fluid loss proves that the slurry cannot have proper properties. This study tests several types of FLC (fluid loss control) and a liquid dispersant on fresh cement slurries. The study examined changes in several properties. These include rheological properties, compressive strength, fluid loss control, free water, settling, mixing, and thickening time. Also, fluid migration from the pumped cement is a big issue during well cementing. Excessive fluid loss can allow gas to enter the cement slurry. So, fluid loss control additives are used to reduce gas migration. The cement slurry weight was 118 pcf used in 13 3/8″ casing and 7″ liners. Materials with different functional groups were tested: amide, ester, ether, alcohol, and carboxylic acid. Finally, an FLC was made by combining two substances. They had ester and ether functional groups. The Final decision was to mix three substances. They were FLC1, FLC2, and a liquid dispersant. To control the properties of a fresh cement slurry. The target values were 180 and 210 °F for compressive strength and 150 and 180 °F for BHCT. The designed formulation using these additives leads to a reduction in transition time. Reducing transition time helps cut gas migration into the cement slurry.

PurposeThis study aims to develop an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline, comparing its reproducibility and observer consistency in image analysis with physicians of varying levels of expertise.Design/methodology/approachAn auto-RUSS was engineered using a 7-degree-of-freedom robotic arm, with real-time regulation based on force control and ultrasound visual servoing. Two phantoms were employed for the human-machine comparative experiment, involving three groups: auto-RUSS, non-expert (4 junior physicians), and expert (4 senior physicians). This setup enabled comprehensive assessment of reproducibility in contact force, image acquisition, image measurement and AI-assisted classification. Radiological feature variability was measured using the coefficient of variation (COV), while performance and reproducibility assessments utilized mean and standard deviation (SD).FindingsThe auto-RUSS had the potential to reduce operator-dependent variability in ultrasound examinations, offering enhanced repeatability and consistency across multiple dimensions including probe contact force, images acquisition, image measurement, and diagnostic model performance.Originality/valueIn this paper, an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline was proposed. Through comprehensive human-machine comparison experiments, the auto-RUSS was shown to effectively improve the reproducibility of ultrasound images and minimize human-induced variability.

Whether individuals exhibit consistent behavioural variation is a central question in the field of animal behaviour. This question is particularly interesting in the case of social animals, as their behaviour may be strongly modulated by the collective. In this study, we ask whether honeybees exhibit individual differences in stinging behaviour. We demonstrate that bees are relatively stable in their decision to sting—or not—in a specific context and show temporal consistency suggestive of an internal state modulation. We also investigated how social factors such as the alarm pheromone or another bee modulated this behaviour. The presence of alarm pheromone increased the likelihood of a bee to sting but this response decayed over trials, while the presence of a conspecific decreased individual stinging likelihood. These factors, however, did not alter stinging consistency. We therefore propose that social modulation acts by shifting the stinging threshold of individuals. Finally, experimental manipulation of group composition with respect to the ratio of aggressive and gentle bees within a group did not affect the behaviour of focal bees. Overall, our results establish honeybee stinging behaviour as a promising model for studying mechanistically how collective and individual traits interact to regulate individual variability.

The article focuses on evaluating the accuracy and consistency of artificial intelligence responses from GPT-3.5 and GPT-4 in neuropathic pain education. Topics include the comparison of AI models' performance in answering multiple-choice questions, the identification of challenges in specific concepts, and the consistency of GPT-4 responses in repeated sessions.