Threshold Estimation Research Articles

The determinants of life insurance companies profitability in South Africa: new evidence from a dynamic panel threshold estimation technique

PurposeInsurance companies play a significant role in every economy; hence, it is essential to investigate and understand the factors that propel their profitability. Unlike previous studies that present a linear relationship, this study provides initial evidence by exploring the non-linear impacts of the determinants of profitability amongst life insurers in South Africa.Design/methodology/approachThe study uses a panel dataset of 62 life insurers in South Africa, covering 2013–2019. The generalised method of moments and the dynamic panel threshold estimation technique were used to estimate the relationship.FindingsThe empirical results from the direct relationship reveal that investment income and solvency significantly predict life insurance companies' profitability. On the other hand, underwriting risk, reinsurance and size reduce profitability. Further, the dynamic panel threshold analysis confirms non-linearities in the relationships. The results show that insurance size, investment income and solvency promote profitability beyond a threshold level, implying a propelling effect on life insurers' profitability at higher levels. Below the threshold, these factors have an adverse effect. The study further points to underwriting risk, reinsurance and leverage having a reduced effect on life insurers' profitability when they fall above the threshold level.Practical implicationsThe findings suggest that insurers interested in boosting their profit position must commit more resources to maintain their solvency and manage their assets and returns on investment. The study further recommends that effective control of underwriting risk is critical to the profitability of the life insurance industry.Originality/valueThe study contributes to the literature by providing first-time evidence on the determinants of life insurance companies' profitability by way of exploring threshold effects in South Africa.

Two rapid alternatives compared to the staircase method for the estimation of the vibrotactile perception threshold.

Wearable vibrotactile devices seem now mature for entering the daily lives and practices of more and more users. However, vibrotactile perception can greatly differ between individuals, in terms of psychophysics and physiology, not to mention higher levels (cognitive or affective for example). Broadly-distributed and affordable vibrotactile devices hence must be adapted to each user's own perception, first of all by delivering intensity levels that are in the perceptible range of the user. This implies determining the user's own thresholds of perception, and then adapting the devices' output levels. Classical methods for the estimation of thresholds elicit too long procedures, and little is known about the reliability of other methods in the vibrotactile domain. This article focuses on two alternative methods for the estimation of amplitude thresholds in the vibrotactile modality ("increasing-intensity" and "decreasing-intensity" methods), and compares their estimations to the estimations from a staircase method. Both rapid methods result in much shorter test durations, and are found less stressful and tiring than the classic method, while showing threshold estimations that are never found to differ by more than 1.5 JND from the estimations by the classic method.

Effect of correction of refractive error and threshold estimation in ocular headache patients in a tertiary eye care center

Purpose: Headache is one of the most common symptoms in patients with refractive error. Our study aimed to find the effect of refractive error correction and estimate the threshold of refractive error in patients with ocular headaches in a tertiary eye care center. Methods: We enrolled patients who came with complaints of headaches. It was a prospective, interventional study. All the patients underwent comprehensive ocular examination that included a detailed headache history, objective and subjective refraction, cycloplegic refraction, Humphrey visual fields test (30-2), cover test, and dilated fundus examination. We excluded uveitis, glaucoma, optic atrophy, papilledema, sinusitis, migraine, dental cavities, and neuropathy patients. We prescribed glasses after the post-mydriatic test. We surveyed via phone call regarding the compliance of spectacle wear and relief of headaches. Results: Out of the 98 enrolled patients, 67 were female and 31 were male in the age group of 16 to 35. The patients had simple astigmatism (57.14%), simple myopia (15.30%), simple myopic astigmatism (23.46%), and hyperopia (9.18%). The threshold value of dioptric power was −1.25 D, −1.00 D, −0.75 DS/−0.75 DC, and +1.00 D for simple astigmatism, simple myopia, simple myopic astigmatism, and hyperopia, respectively. 86.73% recovered with glasses. Simple astigmatism had the highest recovery rate. Headaches frequently occurred in the frontal (44.89%), followed by temporal (32.65%), parietal (16.32%), occipital, and parietal (11.22%). Conclusion: Lower degrees of refractive error caused the headache. We reported the threshold values of the refractive error that caused the ocular headache. Correcting the refractive error relieved the headache

Supra-Threshold LS CE-Chirp Auditory Brainstem Response in the Elderly

Introduction: Aging deteriorates peripheral and central auditory structures and functions. In elders, for an accurate audiological evaluation, it is important to explore beyond the cochlear receptor. Audiograms provide an estimation of hearing thresholds, while the amplitudes and latencies of supra-threshold auditory brainstem response (ABR) can offer noninvasive measures of the auditory pathways functioning. Regarding ABR, in young populations, level-specific chirp (LS CE-chirp) stimulus has been proposed as an alternative synchronizing method to obtain larger ABR responses than those evoked by clicks. However, the supra-threshold characteristics of chirp evoked ABR, and their association to hearing thresholds is relatively unknown in the elderly. The aim of this study was to evaluate supra-threshold LS CE-chirp ABRs in an aged population by comparing their features with click ABRs, and evaluating their relationship with audiometric hearing thresholds. Methods: We carried out a cross-sectional study to characterize the hearing of 125 adults aged over 65 years. We determined the audiometric hearing thresholds and supra-threshold ABRs elicited by LS CE-chirp and click stimuli at 80 dB nHL. We evaluated associations by means of partial correlations and covariate adjustment. We performed specific frequencies’ analysis and subgroup analysis per hearing level. Results: Wave V responses had significantly shorter latencies and larger amplitudes when elicited by LS CE-chirp as compared to click-evoked responses. Audiometric hearing thresholds correlated with age, but ABR characteristics did not. We found mild correlations between hearing thresholds and ABR characteristics, predominantly at higher frequencies and with chirp. We found scarce evidence of correlation between ABR characteristics and the average of behavioral hearing thresholds between 0.5 to 4 kHz (0.5–4 kHz PTA). After subgroup analysis according to the hearing level, no stronger or more significant correlations were found between ABR characteristics and 0.5–4 kHz PTA. Discussion: In this study, we found that supra-threshold LS CE-chirp ABR presented some of the previously described similitudes and differences with supra-threshold click ABR in younger populations. Although, the average amplitude and latency of wave V evoked by LS CE-chirp were larger and faster than those evoked by clicks, these results should be taken with caution at the individual level, and further studies are required to state that LS CE-chirp ABRs are better than click ABRs in elders for clinical evaluations. We did not find consistent associations between hearing thresholds and supra-threshold wave V features, suggesting that these measures should be considered independently in the elderly.

Using UV absorption measurements for estimation of laser damage thresholds in ultrafast laser applications

Laser damage for ultrafast pulses is connected to the UV absorption edge via bandgap. This connection may be used to facilitate damage testing and thus coating development. Preliminary results are presented here.

Unapređenje procene odnosa troškova i efektivnosti lekova za retke bolesti

Background/Aim. Incremental cost/effectiveness ratio (ICER) of many drugs for rare diseases is often much higher that the accepted cost/effectiveness threshold for reimbursement, primarily due to their extremely high prices, raising the question of their availability. The aim of this article was to review necessary adjustments of methods used for cost/effectiveness analysis of drugs for rare diseases. Methods. This article is a narrative review of methods for adjusting cost/effectiveness analysis of drugs for rare diseases in order to get more realistic estimate of ICER threshold, which is essential information for decision-makers. Results. Inputs in cost/effectiveness analysis of a drug for rare diseases should be adjusted by changing discount rates, estimating utilities in a more precise way, excluding treatment-unrelated costs, calculating local C/E threshold, and most importantly, by negotiating drug price until the C/E threshold is not surpassed. With intensified adjusted cost/effectiveness research within the area, many uncertainties will be ended, and real-life value of many of the drugs for rare diseases will be known, influencing pricing in a sustainable direction. Conclusion. With the adjustments, the true cost/effectiveness of a drug for rare disease will be approached, enabling evidence-based and completely transparent reimbursement decisions.

Smoothing denoising method of spatial filtering image based on Contourlet transform

This paper studies the threshold denoising problem of image in Contourlet transform domain, and proposes a smoothing denoising method of spatial filtering image based on Contourlet transform. This method combined with Contourlet transform can highlight the advantages of image edge information and direction information. The image is decomposed by using the Contourlet transform algorithm, and then the spatial filtered image is obtained. Based on the threshold estimation of the Contourlet coefficient of the Treelet difference variable and the soft threshold denoising of the high-frequency coefficient, the spatial filtered image denoising is realized. Then, aiming at the unsmooth denoising problem of the spatial filtered image, the spatial filtered image filtering smoothing processing method based on generalized Laplace distribution is used to solve the unsmooth denoising problem of the spatial filtered image. The experimental results show that this method has strong smoothing denoising ability and obvious application effect.

Traceless Kalman filter threshold estimation for distributed power loads

Abstract Load forecasting is an important part of smart grid construction, energy management, and sustainable design of power systems, and has a great impact on the reliable operation of power grids, facility planning and other decisions. In this paper, we utilize the traceless transform of the UKF algorithm to obtain the sigma feature points generated by the mean value of the high-frequency wavelet components of the power signals and combine them with the EKF algorithm. We put forward a novel neural network hybrid Kalman TUKF algorithm, which will be used to carry out simulation experiments on the distributed electric loads and to estimate the threshold value of the loads in the numerical experiments. The results show that in comparison with the actual measurements, the TUKF algorithm improves by 34.7% in the RMSE metrics, 38.7% in the MAE metrics, and 40.6% in the MAPE metrics compared to the PFWNN. The TUKF algorithm is closer to the real curves and has the best prediction performance for all the time intervals of the prediction. The change of the threshold value has a more obvious effect on the prediction accuracy, and the best effect is in the scale δ = 0.5, i.e., the threshold frequency is selected as the middle value of the intermediate frequency.

Wavelet estimation for the nonparametric additive model in random design and long-memory dependent errors

We investigate the nonparametric additive regression estimation in random design and long-memory errors and construct adaptive thresholding estimators based on wavelet series. The proposed approach achieves asymptotically near-optimal convergence rates when the unknown function and its univariate additive components belong to Besov space. We consider the problem under two noise structures; (1) homoskedastic Gaussian long memory errors and (2) heteroskedastic Gaussian long memory errors. In the homoskedastic long-memory error case, the estimator is completely adaptive with respect to the long-memory parameter. In the heteroskedastic long-memory case, the estimator may not be adaptive with respect to the long-memory parameter unless the heteroskedasticity is of polynomial form. In either case, the convergence rates depend on the long-memory parameter only when long-memory is strong enough, otherwise, the rates are identical to those under i.i.d. errors. In addition, convergence rates are free from the curse of dimensionality.

Clutter filtering of angular domain data for contrast-free ultrafast microvascular imaging

Objective. Contrast-free microvascular imaging is clinically valuable for the assessment of physiological status and the early diagnosis of diseases. Effective clutter filtering is essential for microvascular visualization without contrast enhancement. Singular value decomposition (SVD)-based spatiotemporal filter has been widely used to suppress clutter. However, clinical real-time imaging relies on short ensembles (dozens of frames), which limits the implementation of SVD filtering due to the large error of eigen-correlated estimations and high dependence on optimal threshold when used in such ensembles. Approach. To address the above challenges of imaging in short ensembles, two optimized filters of angular domain data are proposed in this paper: grouped angle SVD (GA-SVD) and angular-coherence-based higher-order SVD (AC-HOSVD). GA-SVD applies SVD to the concatenation of all angular data to improve clutter rejection performance in short ensembles, while AC-HOSVD applies HOSVD to the angular data tensor and utilizes angular coherence in addition to spatial and temporal features for filtering. Feasible threshold selection strategies in each feature space are provided. The clutter rejection performance of the proposed filters and SVD was evaluated with Doppler phantom and in vivo studies at different cases. Moreover, the robustness of the filters was explored under wrong singular value threshold estimation, and their computational complexity was studied. Main results. Qualitative and quantitative results indicated that GA-SVD and AC-HOSVD can effectively improve clutter rejection performance in short ensembles, especially AC-HOSVD. Notably, the proposed methods using 20 frames had similar image quality to SVD using 100 frames. In vivo studies showed that compared to SVD, GA-SVD increased the signal-to-noise-ratio (SNR) by 6.03 dB on average, and AC-HOSVD increased the SNR by 8.93 dB on average. Furthermore, AC-HOSVD remained better power Doppler image quality under non-optimal thresholds, followed by GA-SVD. Significance. The proposed filters can greatly enhance contrast-free microvascular visualization in short ensembles and have potential for different clinical translations due to the performance differences.

Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability.

Aerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and validate a computational method based on the RR interval (RRI) dynamics of the heart rate (HR) measurement, which enables a simple, yet reasonably accurate estimation of both metabolic thresholds. The method utilizes a newly developed dynamical detrended fluctuation analysis (DDFA) to assess the real-time changes in the dynamical correlations of the RR intervals during exercise. The training intensity is shown to be in direct correspondence with the time- and scale-dependent changes in the DDFA scaling exponent. These changes are further used in the definition of an individual measure to estimate the aerobic and anaerobic threshold. The results for 15 volunteers who participated in a cyclo-ergometer test are compared to the benchmark lactate thresholds, as well as to the ventilatory threshods and alternative HR-based estimates based on the maximal HR and the conventional detrended fluctuation analysis (DFA). Our method provides the best overall agreement with the lactate thresholds and provides a promising, cost-effective alternative to conventional protocols, which could be easily integrated in wearable devices. However, detailed statistical analysis reveals the particular strengths and weaknessess of each method with respect to the agreement and consistency with the thresholds-thus underlining the need for further studies with more data.

Explaining employment and environmental degradation nexus with environmental employment curve (EEC): A sector-wide threshold estimation for China

China is the world's largest emitter of carbon dioxide and has experienced significant economic growth in the last decade. The country also has significant employment capacity and has witnessed rapid economic growth in the recent years. This study aims to investigate the existence of the environmental employment curve (EEC) in China's main economic sectors. This study examines the relationship between carbon emissions, economic growth, energy consumption, renewable energy consumption and employment (industry, services, agriculture) in China over the period 1990–2020 using threshold autoregressive regression estimation. According to the EEC hypothesis, there exists an inverted U-shaped relationship between environmental pollution and employment rate. Empirical results show that the EEC hypothesis seems to hold in China. Further, an analysis of the impact of employment on environmental pollution in China's three main sectors – industry, service and agriculture – shows that the EEC hypothesis cannot be rejected in the industrial and the agricultural sectors. In addition, empirical results show that a 1% increase in energy consumption leads to a 0.92% increase in carbon emissions, while the use of renewable energy leads to a 0.18% decrease. These results suggest that investments in green energy transformation do not cause employment loss. Hence, it is important to drive policies that promote investments in renewable and clean technologies, stimulate research in renewable energy-related institutions and support public-private partnerships. Additionally, to generate employment without compromising on the environment or prosperity, policymakers should choose to implement alternative technologies that are less polluting or do not produce any carbon emissions.

Dynamic Stability of Public Debt: Evidence from the Eurozone Countries

This paper investigates the dynamic stability of public debt and its solvency condition in the face of crisis periods (1980–2021) in a sample of 11 euro-area countries. The focus is on the feedback loop between the dynamic stability of public debt and interest rates, discounted by economic growth, in conjunction with budget deficits during tranquil and turbulent periods. Using the GMM panel dynamic model, the results show that dynamic stability was the case before the global financial crisis (GFC), while from GFC to the pandemic, dynamic instability prevailed and persisted in the evolution of public debt. Furthermore, panel threshold estimates show that dynamic instability of debt starts to violate the solvency condition when the borrowing cost is above 3.29%, becomes even stronger when it is above 4.39%, and exerts even more pressure when the level of debt is greater than 91%. However, the debt sustainability condition reverses course when economic growth is higher than 3.4%. The main policy implication drawn from the results is that low interest rates can create a self-reinforcing loop of high debt, which itself is a serious matter for public authorities when designing economic policies.

Deep learning-based dynamic ventilatory threshold estimation from electrocardiograms

Background and objectiveThe ventilatory threshold (VT) marks the transition from aerobic to anaerobic metabolism and is used to assess cardiorespiratory endurance. A conventional way to assess VT is cardiopulmonary exercise testing, which requires a gas analyzer. Another method for measuring VT involves calculating the heart rate variability (HRV) from an electrocardiogram (ECG) by computing the variability of heartbeats. However, the HRV method has some limitations. ECGs should be recorded for at least 5 minutes to calculate the HRV, and the result may depend on the utilized ECG preprocessing algorithms. MethodsTo overcome these problems, we developed a deep learning-based model consisting of long short-term memory (LSTM) and convolutional neural network (CNN) for a lead II ECG. Variables reflecting subjects' physical characteristics, as well as ECG signals, were input into the model to estimate VT. We applied joint optimization to the CNN layers to generate an informative latent space, which was fed to the LSTM layers. The model was trained and evaluated on two datasets, one from the Bruce protocol and the other from a protocol including multiple tasks (MT). ResultsAcceptable performances (mean and 95% CI) were obtained on the datasets from the Bruce protocol (−0.28[−1.91,1.34] ml/min/kg) and the MT protocol (0.07[−3.14,3.28] ml/min/kg) regarding the differences between the predictions and labels. The coefficient of determination, Pearson correlation coefficient, and root mean square error were 0.84, 0.93, and 0.868 for the Bruce protocol and 0.73, 0.97, and 3.373 for the MT protocol, respectively. ConclusionsThe results indicated that it is possible for the proposed model to simultaneously assess VT with the inputs of successive ECGs. In addition, from ablation studies concerning the physical variables and the joint optimization process, it was demonstrated that their use could boost the VT assessment performance of the model. The proposed model enables dynamic VT estimation with ECGs, which could help with managing cardiorespiratory fitness in daily life and cardiovascular rehabilitation in patients.

Integrated modelling of vacuum flashover development: Above‐surface processes and breakdown threshold analyses

AbstractThe flashover in vacuum is a rapid interfacial discharge across the insulator surface when subjected to high applied voltage. Here a theoretical model covering above‐surface processes is introduced. The model calculates the flashover threshold in vacuum, with revised secondary electron emission avalanche theory and improved desorbed neutral transport model. The model serves as the first part of an integrated flashover model, aiming for consistent treatment of both above‐surface and subsurface processes during the entire flashover development. The flashover threshold is obtained by combining the desorbed neutral pressure at given applied voltage and the gas breakdown criterion dictated by the Paschen's law. An analytical formula for threshold estimation containing physical parameters, and a simplified formula consisting of empirical coefficients are introduced, catering for both conceptual understanding and practical application. The derived formulae are validated by experimental data for a variety of insulator materials. The theory generalisation for non‐uniform electric field distribution is further discussed.

OP79 Gene Expression Profiling In The Diagnosis Of Aggressive Large B Cell Lymphoma: An Early Exploratory Economic Evaluation

IntroductionThe addition of gene expression profiles (GEP) to the current clinicopathological diagnosis of aggressive large B cell lymphomas may lead to the reclassification of patients, treatment changes and improved outcomes. A GEP test is in development using TempoSeq technology to distinguish Burkitt Lymphoma (BL) and Primary Mediastinal Large B Cell lymphoma (PMBCL) from Diffuse Large B Cell Lymphoma (DLBCL). This study aims to inform developers about the potential impact of the test on costs and health outcomes, and pricing and evidence generation strategies.MethodsDecision models compared current diagnosis with current plus GEP signatures over a lifetime horizon using a UK health and social care perspective. Inputs were taken from the literature and based on assumptions. Threshold estimates were made of the maximum price of the test and impact of incorrect disease classification using a threshold of GDP30,000 (USD37,155) per Quality Adjusted Life year (QALY). One way sensitivity analysis was conducted.ResultsAt base case values the BL signature delivers incremental QALYs of 0.0249 at an additional cost per patient of GBP508 (USD629). This results in a net monetary benefit (NMB) of GBP239 (USD296). The PMBCL signature delivers 0.0011 QALYs, a cost saving of GBP202 (USD250) and an NMB of GBP236 (USD292). The maximum threshold price for a combined test to be cost effective is GBP776 (USD961) (base case GBP400 (USD495)). Results are sensitive to cost differences in first line treatments and impact of false diagnoses.ConclusionsA combined test could be cost-effective in a UK context at a price around GBP750 (USD929). The developers can use this estimate to inform return on investment calculations. The number of patients who were reclassified as a result of the addition of GEP in our model was taken from small retrospective studies and the impact of false diagnoses was based on limited evidence. If the developers choose to proceed with the development, these aspects should be incorporated in evidence generation strategies.

Detect Arbitrary-Shaped Text via Adaptive Thresholding and Localization Quality Estimation

The two-stage scene text detection algorithms based on Mask R-CNN have achieved good performances on multiple challenging benchmarks. However, their effectiveness is degraded due to artificially setting constant thresholds and low localization quality of candidate boxes. In this paper, we present a novel scene text detection method based on Mask R-CNN and the proposed method, named LOAD, proposes adaptive threshold module and localization quality estimation module to address the above two problems. We propose two kinds of adaptive thresholds which are used for the filtering of candidate boxes and the binarization of pixels respectively. We introduce the self-attention mechanism to obtain the global information for generating the adaptive thresholds. Besides, we introduce the localization quality estimation into our model to obtain more accurate candidate boxes for subsequent segmentation. Comparative experiments are conducted on five benchmarks(ICDAR 2015, ICDAR 2017, MSRA-TD500, Total-Text and CTW1500), and the results demonstrate that the proposed method achieves the state-of-the-art performance with an F-measure of 91.0%, 78.7%, 87.4%, 90.6% and 86.0%. We also provide adequate ablation experiments to demonstrate the effectiveness of the proposed components.

SSVEP-based visual acuity threshold estimation: linear extrapolation to noise level baseline with various noise definition criteria.

This study aimed to explore the effect of various noise definition criteria in linear extrapolation technique to noise level baseline on steady-state visual evoked potential (SSVEP)-based visual acuity assessment. Four noise definition criteria on frequency-domain, i.e., the mean amplitude at the two adjacent bins of the target frequency, the mean amplitude of a narrow frequency band on either side of the target frequency, the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, and the mean amplitude at a broad frequency band at resting state, corresponding to noise 1, noise 2, noise 3, and noise 4, were introduced to calculate noise level baselines. Then, two experiments were implemented. In experiment 1, electroencephalography (EEG) signals of resting state were recorded for fourteen subjects. In experiment 2, the visual stimuli of vertical sinusoidal gratings at six spatial frequency steps were used to induce SSVEPs for twelve subjects. Finally, SSVEP visual acuity was obtained via the SSVEP visual acuity threshold estimation of linear extrapolation technique to noise level baseline with various noise definition criteria. The bland-Altman analysis found that the difference between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and objective SSVEP visual acuity was - 0.0892, - 0.1071, - 0.0745, and - 0.0804 logMAR and the 95% limit of agreement was 0.2150, 0.2146, 0.2046, and 0.2189 logMAR for noise 1, noise 2, noise 3, and noise 4, respectively, indicating that visual acuity of noise 3 definition criterion, i.e., the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, showed the best performance. This study recommended noise definition criterion 3 of the mean amplitude at a broad frequency band to calculate the noise level baseline in the linear extrapolation of SSVEP-based visual acuity assessment.

Efek Ambang Batas Inflasi terhadap Pertumbuhan Ekonomi di Indonesia

This study analyzes whether the inflation threshold's effect impacts economic growth and determines the relationship between inflation and economic development. The data used in this study were obtained from the OECD: Economic Growth and Inflation, Investment, Money Supply, and Population Growth. This study uses time-series data from 1970-2019 using a threshold estimation model. The analysis technique used is multiple regression with the OLS method. The results of this study estimate an inflation threshold of 5%. Inflation with a point of 5% has a statistically negative and significant impact on economic growth. However, there is no evidence that an inflation rate below the 5% threshold can increase economic growth in Indonesia.

Piloting a new method to estimate action thresholds in medicine through intuitive weighing

ObjectivesIn clinical decision-making, physicians take actions such as prescribing treatment only when the probability of disease is sufficiently high. The lowest probability at which the action will be considered, is...