Interval Estimation Research Articles

Luminol and the postmortem interval estimation — influence of taphonomic factors

The estimation of the postmortem interval (PMI) is one of the key challenges for forensic anthropologists. Although there are several methods referenced for this purpose, none is sufficiently effective. One of the main reasons justifying the complexity of this task is the influence of several taphonomic factors.The study of the Luminol technique has stood out as a promising method for estimating PMI, complementing the existing methods, since it is an economic, easy and reproducible method that operates as a presumptive test. However, it is not known which taphonomic factors can influence the results obtained by this technique.The aim of this study is to test the influence of taphonomic factors, such as temperature, humidity, soil type and pH, on the estimation of the PMI by the Luminol technique.In order to test the influence of the referred factors, a sample consisting of 30 clavicles, with known and similar PMI, collected from autopsies, was distributed as evenly as possible by six vases and buried with different decomposition conditions for a period of 12 months. After the exhumation and sample preparation, the Luminol technique was applied.It was possible to clearly observe differences in the results. Thus, according to our research, it is possible to conclude that the results obtained by the application of Luminol are influenced by taphonomic factors. Therefore, the context in which a body is found should always be considered for applying this technique.

Feelings of responsibility and temporal binding: A comparison of two measures of the sense of agency

Temporal binding refers to a subjective shortening of the interval between an action and its perceptual consequences. Temporal binding has often been used by researchers to indirectly measure participants’ sense of agency (SoA), or the subjective sense of causing something to happen. Other studies have proposed links between temporal binding and feelings of moral responsibility. The present study compared subjective interval estimates to feelings of responsibility in a between-subjects design (Exp 1) and a within-subjects design (Exp 2). Participants either estimated the interval between two events (two tones in the passive condition, or a keypress followed by a tone in active conditions) or rated their feeling of responsibility for the tone(s). Manipulations of participant involvement and choice impacted feelings of responsibility more than temporal estimates. Overall, the two dependent variables followed different patterns, suggesting subjective interval estimates may not be a reliable proxy for feelings of responsibility.

Geographical Distribution and Multimethod Species Identification of Forensically Important Necrophagous Flies on Hainan Island.

Forensic entomology offers unique advantages for the minimum postmortem interval (PMImin) estimation of decomposed corpses in forensic investigations. Accurate species identification and up-to-date locality information are essential. Hainan Island has a tropical rainforest climate and a vast territory. In this study, the community structure of necrophagous flies on Hainan Island was investigated in detail according to geographical environment. The results showed that the dominant species included C. megacephala, S. peregrina, C. rufifacies, S. misera, H. ligurriens, S. sericea, S. cinerea, S. dux, C. pinguis, and M. domestica. Furthermore, C. rufifacies and C. villeneuvi were found only in the high-altitude areas of Wuzhi Mountain, while S. cinerea was distributed only in coastal areas; the latter is a representative species of Hainan Island and has not been reported before. Furthermore, a GenBank database of forensically important flies was established, whilst a high-resolution melt (HRM) curve analysis was applied to identify the common species of Hainan Island for the first time. This study enriches the database of forensically important flies in tropical rainforest regions.

Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation.

Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0-8Dvs. WPG 16-40D, p < 0.0001; WPS 0-16Dvs. WPS 24-40D, p = 0.003; SPG 0D vs. SPG 8-40D, p = 0.0005; and SPS 0D vs. SPS 8-40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI.

Generalized Fiducial Inference for the Generalized Rayleigh Distribution

This article focuses on the interval estimation of the generalized Rayleigh distribution with scale and shape parameters. The generalized fiducial method is used to construct the fiducial point estimators as well as the fiducial confidence intervals, and then their performance is compared with other methods such as the maximum likelihood estimation, Bayesian estimation and parametric bootstrap method. Monte Carlo simulation studies are carried out to examine the efficiency of the methods in terms of the mean square error, coverage probability and average length. Finally, two real data sets are presented to demonstrate the applicability of the proposed method.

Comparison of very high-power short-duration, high-power short-duration, and low-power long-duration radiofrequency ablation for atrial fibrillation: A systematic review and network meta-analysis.

The optimal power and duration settings for radiofrequency (RF) atrial fibrillation (AF) ablation to improve efficacy and safety is unclear. We compared low-power long-duration (LPLD), high-power short-duration (HPSD), and very HPSD (vHPSD) RF settings for AF ablation. This network meta-analysis (NMA) was structured according to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Medline, Scopus and Cochrane Central Register of Controlled Trials were systematically searched to identify relevant studies. Observational and randomized studies were included. Eligible studies compared outcomes in AF patients who underwent first-time RF ablation with the following settings: vHPSD (70-90W, 3-10 s), HPSD (45-60W, 5-10 s), or LPLD (20-40W, 20-60 s). Thirty-six studies comprising 10,375 patients were included (33% female). Frequentist NMA showed LPLD tended toward a lower odds of freedom from arrhythmia (FFA) versus HPSD (OR 0.93, 95% CI 0.86-1.00). There was no difference in FFA between vHPSD versus HPSD. Splitwise interval estimates showed a lower odds of FFA in LPLD versus vHPSD on direct (OR 0.78, 95% CI 0.65-0.93) and network estimates (OR 0.85, 95% CI 0.73-0.98). Frequentist NMA showed less total procedural (TP) time with HPSD versus LPLD (generic variance 1.06, 95% CI 0.83 to 1.29) and no difference between HPSD versus vHPSD. This NMA shows improved procedural times in HPSD and vHPSD versus LPLD. Although HPSD tended toward improved odds of FFA compared to LPLD, the overall result was not statistically significant. The odds of FFA in LPLD was lower versus vHPSD on direct and network estimates on splitwise interval analysis. Large prospective head-to-head randomized trials are needed to validate HPSD and vHPSD settings.

The effects of insect repellent on initial Dipteran colonization of decomposing pig remains.

Numerous factors influence insect colonization and development on decomposing remains and can influence postmortem interval (PMI) estimations when insects are used in investigations of suspicious deaths. This study aimed to determine whether insect repellent influences insect colonization of decomposing remains. Pig feet were divided into 4 groups: a control not sprayed with repellent, 40% DEET repellent, 98% DEET repellent, and lemon eucalyptus repellent. The feet were placed in containers, and insect visitation was observed over the course of 3 days, then insects were collected at the end of the third day. This was repeated twice a month from April through November 2022. The analysis focused on the order Diptera. Pairwise comparison determined that there was a significant delay in visitation time for remains with 98% DEET compared to remains with no repellent and 40% DEET. There were significantly fewer adult Diptera collected and more remains with no larvae or eggs present among remains treated with 98% DEET. It was concluded that low concentrations of DEET and lemon eucalyptus repellent did not delay colonization, but that high concentrations of DEET delayed visitation, reduced the number of adult flies collected from the remains, and reduced the likelihood of collecting eggs or larvae from the remains. This contributes to the understanding of factors that can influence insect colonization and development that allow for more accurate PMI estimations by suggesting that insect repellent does not need to be accounted for in PMI estimation, but a high concentration of DEET can deter insects in the short term.

Accelerated degradation data analysis based on inverse Gaussian process with unit heterogeneity

The unit heterogeneity of products and the nonlinear parameter-stress relationship often exist in practice. Therefore, considering the unit heterogeneity, the nonlinear accelerated model and inverse Gaussian process are developed to depict the accelerated degradation data. On the other hand, this more realistic model leads a challenge to derive the model parameter interval estimation. Thereby, a novel two-step interval estimation method is proposed for the proposed accelerated degradation model. First, generalized confidence intervals of the parameters characterizing random effect are derived from the Cornish–Fisher expansion, and their cumulative distribution functions are obtained. Then, using the generalized pivotal quantity procedure, generalized confidence intervals of the accelerated model parameters are derived. In addition, generalized confidence intervals of predictive reliability indexes are derived to guide the practical application. Finally, simulation studies and two real examples on Spiral springs and integrated circuit devices are presented to demonstrate the implementation of the proposed method.

Reliability Estimation of Retraction Mechanism Kinematic Accuracy under Small Sample

Due to intricate operating conditions, including structural clearances and assembly deviations, the acquisition of test data of landing gear retraction mechanism is limited, posing challenges for reliability analysis. To solve the problem, a Bayesian-based reliability analysis method by fusing prior and test data is proposed, focusing on the mechanism kinematic accuracy under small-sample conditions. Firstly, a dynamic simulation model is established to collect prior data, and retraction tests are conducted to obtain test data. Then, based on Bayesian theory, the motion accuracy parameter estimation model integrating prior and test samples is established. To obtain accurate hyper parameters, the prior samples are expanded using neural network. Finally, taking the retraction mechanism as the research object, the kinematic accuracy reliability is quantified, and the impact of uncertainty factors is analyzed in depth. The results show that the proposed method is superior to the classical interval estimation method in stability and effectively mitigates the impact of uncertainty factors.

Confidence intervals for ratio of means of delta-lognormal distributions based on left-censored data with application to rainfall data in Thailand.

Thailand is a country that is prone to both floods and droughts, and these natural disasters have significant impacts on the country's people, economy, and environment. Estimating rainfall is an important part of flood and drought prevention. Rainfall data typically contains both zero and positive observations, and the distribution of rainfall often follows the delta-lognormal distribution. However, it is important to note that rainfall data can be censored, meaning that some values may be missing or truncated. The interval estimator for the ratio of means will be useful when comparing the means of two samples. The purpose of this article was to compare the performance of several approaches for statistically analyzing left-censored data. The performance of the confidence intervals was evaluated using the coverage probability and average length, which were assessed through Monte Carlo simulation. The approaches examined included several variations of the generalized confidence interval, the Bayesian, the parametric bootstrap, and the method of variance estimates recovery approaches. For (ξ1, ξ2) = (0.10,0.10), simulations showed that the Bayesian approach would be a suitable choice for constructing the credible interval for the ratio of means of delta-lognormal distributions based on left-censored data. For (ξ1, ξ2) = (0.10,0.25), the parametric bootstrap approach was a strong alternative for constructing the confidence interval. However, the generalized confidence interval approach can be considered to construct the confidence when the sample sizes are increase. Practical applications demonstrating the use of these techniques on rainfall data showed that the confidence interval based on the generalized confidence interval approach covered the ratio of population means and had the smallest length. The proposed approaches' effectiveness was illustrated using daily rainfall datasets from the provinces of Chiang Rai and Chiang Mai in Thailand.

A residual bootstrap for conditional Value-at-Risk

A fixed-design residual bootstrap method is proposed for the two-step estimator of Francq and Zakoïan(2015) associated with the conditional Value-at-Risk. The bootstrap’s consistency is proven for a general class of volatility models and intervals are constructed for the conditional Value-at-Risk. A simulation study reveals that the equal-tailed percentile bootstrap interval tends to fall short of its nominal value. In contrast, the reversed-tails bootstrap interval yields accurate coverage. We also compare the theoretically analyzed fixed-design bootstrap with the recursive-design bootstrap. It turns out that the fixed-design bootstrap performs equally well in terms of average coverage, yet leads on average to shorter intervals in smaller samples. An empirical application illustrates the interval estimation.

The relationship between postmortem interval and protein changes in mice

Postmortem interval (PMI) estimation is important for forensic pathological autopsy. It has been reported that there is a correlation between certain protein changes in cadavers and PMI. However, no specific protein(s) has been used to determine the PMI so far. In this study, the total protein contents of mouse liver and spleen at different time of death were measured. The data showed that they were negatively correlated with the PMI. The degradation of β-actin was found to be positively correlated with the PMI in the liver. Additionally, proteomic technique was used to study the changes of protein expression related to PMI in the liver of mice. By using Two-dimensional electrophoresis, the expressions of four proteins were found to be significantly decreased and those of other three proteins were unchanged with the increase of PMI. Among the seven proteins, six were identified with peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The three altered proteins were SBP2, ENOA, ALDH2 and three unchanged ones were 3HAO, TPIS, CATA, respectively. In the future, those unchanged proteins could be used as internal references to more accurately and reliably infer the time of death by assessing the level of changed proteins.

Bayesian and likelihood estimation of multicomponent stress–strength reliability from power Lindley distribution based on progressively censored samples

In this article, the problem of estimation of reliability of a ℓ-component system when both the stress and strength components are assumed to have a power Lindley distribution is discussed. The multicomponent stress–strength reliability parameter is obtained using both the Bayesian and the classical approaches when component-wise each unit follows a power Lindley distribution. To estimate the multicomponent stress–strength reliability parameter under the classical approach, the method of maximum likelihood and the asymptotic confidence interval estimation method are used as point and interval estimation methods, respectively. Under the Bayesian paradigm, the reliability parameter is estimated under the linear exponential loss function using the Lindley approximation, the Tierney–Kadane approximation and the Markov chain Monte Carlo (MCMC) techniques and subsequently highest posterior density credible intervals are obtained. To validate the efficacy of the proposed estimation strategies, a simulation study is carried out. Finally, two real-life data sets are re-analysed for illustrative purposes.

Abstract 12639: Comparison of Very High-Power Short-Duration, High-Power Short-Duration, and Low-Power Long-Duration Radiofrequency Ablation for Atrial Fibrillation: A Systematic Review and Network Meta-Analysis

Introduction: The optimal power and duration settings for radiofrequency (RF) atrial fibrillation (AF) ablation is unclear. We compared low-power long-duration (LPLD), high-power short-duration (HPSD), and very HPSD (vHPSD) settings for AF ablation. Hypothesis: Ablation utilizing HPSD and vHPSD are expected to have shorter procedural times than LPLD and may have improved arrhythmic outcomes. Aims: To compare LPLD, HPSD, and vHPSD ablation by network meta-analysis Methods: This network meta-analysis (NMA) was structured according to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Medline, Scopus and Cochrane Central Register of Controlled Trials were systematically searched to identify relevant studies. Observational and randomized studies were included. Eligible studies compared outcomes in AF patients who underwent first-time RF ablation with the following settings: vHPSD (70-90 Watts for 3-10 seconds), HPSD (45-60 W, 5-10 s), or LPLD (20-40 W, 20-60 s). Results: Thirty-six studies comprising 10375 patients were included (33% female). Frequentist NMA showed LPLD tended towards a lower odds of freedom from arrhythmia (FFA) vs. HPSD (OR 0.93, 95% CI 0.86-1.00). There was no difference in FFA between vHPSD vs. HPSD. Splitwise interval estimates showed a lower odds of FFA in LPLD vs. vHPSD on direct (OR 0.78, 95% CI 0.65-0.93) and network estimates (OR 0.85, 95% CI 0.73-0.98). Frequentist NMA showed less total procedural (TP) time with HPSD vs. LPLD (generic variance 1.06, 95% CI 0.83-1.29) and no difference between HPSD vs. vHPSD. Conclusion: This NMA shows improved procedural times in HPSD and vHPSD vs. LPLD. Although HPSD tended towards improved odds of FFA compared to LPLD, the result was not statistically significant. The odds of FFA in LPLD was lower vs. vHPSD on direct and network estimates on splitwise interval analysis. Randomized clinical trials are needed to validate HPSD and vHPSD settings.

Evaluating the Time of Death (Post Mortem Interval, PMI) through Forensic Entomo-toxicological Investigations of Maggots and Flies

The estimation of the post mortem interval (PMI) is a critical component of forensic science, aiding investigations and resolving missing persons cases. This abstract explores the innovative approach of forensic entomotoxicological investigations, focusing on the analysis of maggots and flies in PMI estimation. Maggots and flies are key players in the decomposition process, and their lifecycles are closely linked to the stages of decay. Challenges and limitations, such as environmental factors and variable drug metabolism, are considered. Two compelling case studies exemplify the practical applications of forensic entomotoxicology in solving criminal cases and missing persons investigations.&#x0D; The primary goal of this paper is to provide guidance to knowledgeable researchers and investigators in the realm of forensic entomotoxicology. It underscores the need for a heightened focus on forensic Entomotoxicology, particularly in investigations involving the effects of drugs on the growth stages of insect development, for more accurate postmortem interval estimations, especially in cases involving decomposed remains. In conclusion, forensic entomotoxicological investigations of maggots and flies present a dynamic and invaluable approach to PMI estimation, promising to enhance the accuracy and reliability of forensic science in determining the timing of death.

Machine learning framework for Inter-Beat Interval estimation using wearable Photoplethysmography sensors

Accurate estimation of Heart Rate (HR) is crucial for various health and fitness tracking applications in wearable devices. Among the existing techniques, those based on Photoplethysmography (PPG) signals have been extensively explored for continuous HR monitoring. In this paper, we introduce a new framework that utilizes machine learning methods to estimate Inter-Beat Interval (IBI) from wrist PPG signals. The primary objective of the proposed methods is to enhance the accuracy of IBI estimates while ensuring their feasibility for wearable devices, considering typical computational power, and memory constraints. This is achieved through two combined approaches. The first method involves optimizing a set of parameters associated with the interpolation of the systolic peaks. During the training stage of this method, we optimize the weights applied to the neighboring samples of the systolic peaks while minimizing the error between the fine-tuned peak positions and their corresponding ground truth. The second method is related to a supervised machine learning approach that handles the R-peak detection as a classification task. This allows us to accurately detect systolic peaks in PPG signals by classifying candidate peaks as true or false systolic peaks. To evaluate the effectiveness of our proposed methods, we conducted experiments on a dataset collected and carefully organized to this end. It consists of PPG and Electrocardiogram (ECG) signals obtained from 46 volunteers, including individuals with normal sinus rhythm, atrial fibrillation, and other non-specified cardiac arrhythmias. Comparing our framework with other state-of-the-art methods, we observed excellent performance, with lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) in IBI estimation. The proposed approach also achieved higher levels of Precision and Recall in terms of the detection of systolic peaks.

Estimation of reference intervals for physical fitness indicators in healthy community-dwelling older adults

Estimation of reference intervals for physical fitness indicators in healthy community-dwelling older adults

62 Neural Correlates of Cognitive Function in the Basal Ganglia

Objective:Timing, or the decision of when to act, is essential to mammalian behaviors from escaping predators to driving a car. It requires cognitive functions such as working memory for time-based rules and attention to the passing of time. Thus, it can be used as a proxy for higher order executive functions that are difficult to measure but are impaired in many neurological disorders. Therefore, insights from studies of interval timing, tasks which require estimating time intervals of several seconds, have great value for our understanding of human disease. Crucial to timing is the basal ganglia, which integrates cortical activity with midbrain dopamine signals and sends out signals to the spinal cord that regulate movement, motivation, and other behaviors. We have previously found that within the basal ganglia, medium spiny neurons of the striatum exhibit ramping activity in time-related tasks. In other words, they gradually increase or decrease firing frequency across a timed interval, and this is thought to encode time. Yet it is still unknown how the encoding of time is translated into time-based motor responses. To answer this question, we turned to the external globus pallidus (GPe) because it is a regulatory hub within the basal ganglia and is thus well positioned to regulate timing behavior. We sought to examine how the GPe functions in response to time-based demands.Participants and Methods:We recorded from neuronal ensembles using 16 channel electrode arrays implanted in the GPe of five mice while they performed an interval timing task called the switch interval timing task. Spike sorting was then used to identify signal from individual neurons.Results:Data were compiled from 43 neurons over several trials. Principal component analysis of neural firing activity was then conducted and revealed a downward ramping pattern in GPe neurons during interval timing trials. Data were then separated based on trials in which mice made correct decisions and those in which mice made a mistake. We found that when mice make correct timing decisions, there is downward ramping activity in the GPe, yet when mice make timing mistakes, this ramping pattern is lost.Conclusions:Our findings suggest that the GPe processes timing signals through ramping activity, before projecting to the output nuclei of the basal ganglia. This is a novel finding and contributes to a growing understanding of the temporal code of the basal ganglia. The full extent of this code is still unknown, but this insight contributes to a better understanding of how the globus pallidus represents cognition. If we can better explain the neural correlates of timing, we can use this knowledge to inform therapeutic interventions for basal ganglia dysfunction, which could have profound implications for diseases like Parkinson’s disease, which affects millions around the world.

Machine Learning–Based Bayesian Framework for Interval Estimate of Unsafe-Event Prediction in Construction

Machine Learning–Based Bayesian Framework for Interval Estimate of Unsafe-Event Prediction in Construction

Statistical inference in Burr type XII lifetime model based on progressive randomly censored data

Censoring commonly occurs in real-world scenarios, either intentionally or unintentionally. Unintentional (or accidental) censoring usually happens randomly, i.e., it is out of the experimenters’ control, such as broken equipment, lack of follow-up, etc. Experimenters typically use intentional censoring to save experimental time and cost. In this article, we develop frequentist and Bayesian statistical inferential procedures for the parameters and reliability characteristics of the Burr type XII lifetime model under the Koziol-Green model based on progressive randomly censored data. For the frequentist approach, maximum likelihood methods for point and interval estimation are developed. For the Bayesian approach, the Bayes estimates under the squared error loss function (SELF) are evaluated using the Markov Chain Monte Carlo (MCMC) and Tierney-Kadane (T-K) approximation techniques. A Monte Carlo simulation study is used to assess the performance of the proposed estimation procedures. A real data analysis is performed to illustrate the proposed methods. Moreover, obtaining progressive censoring schemes for experimental planning purposes is also discussed.