Determination Of Threshold Research Articles

Determinants of Anaerobic Threshold at Each Stage of Renal Dysfunction in Patients With Heart Disease

Patients with heart disease have a low anaerobic threshold (AT), and the determinants of AT may differ, depending on the severity of renal dysfunction. This study aimed to verify the determinants of AT for each stage of renal function in patients with heart disease. We consecutively enrolled 250 patients with heart disease who underwent cardiopulmonary exercise testing in our institution. The patients were divided into 3 groups by their estimated glomerular filtration rate (eGFR): <45, 45 to 59, and ≥60ml/min/1.73m2. A multivariate linear regression analysis was performed to evaluate the independent determinants of AT for each group. In total, 201 patients were analyzed. AT decreased with the deterioration of renal function (eGFR <45, 10.9 ± 2.1 vs eGFR 45 to 59, 12.4 ± 2.5 vs eGFR ≥60, 14.0 ± 2.6ml/min/kg, p <0.001). In the eGFR <45 group, left ventricular ejection fraction and hemoglobin were significantly associated with AT (β=0.427, p=0.006 and β=0.488, p=0.002, respectively). In the eGFR 45 to 59 and ≥60 groups, ΔPETO2 (end-tidal oxygen partial pressure from rest to AT) showed a significant association with AT (β=0.576, p <0.001 and β=0.308, p=0.003, respectively). The determinants of AT depended on the stage of renal dysfunction in patients with heart disease. In conclusion, in the eGFR <45 group, the determinants of AT were left ventricular ejection fraction and hemoglobin, whereas in the eGFR 45 to 59 and eGFR ≥60 groups, the determinant of AT was ΔPETO2.

Particle perception: Defining sensory thresholds for grittiness of upcycled apple pomace powders

Recent years have seen increased interest in environmentally-friendly and sustainable foods, including upcycled ingredients. However, some of these ingredients can contribute to grittiness or graininess, which could in turn impact consumer acceptance. To explore this topic, the current study used apple pomace powder (APP), a nutrient-rich byproduct from apple juice and cider processing to yield new knowledge on particle perception in upcycled foods. Seven APPs with particle sizes of average hydrated diameter Dv(90): 166, 208, 320, 363, 471, 569, 642 μm were incorporated into fruit yogurts. Napping® was successfully used as a preliminary step to threshold testing to inform selection of threshold testing methodology and an appropriate particle size range. The Ascending Forced Choice Method of Limits was applied to a consumer panel (N = 71) for threshold determination. The group threshold, was 259 μm (Dv(90)). The current study demonstrated that by reducing the particle size, it is possible to use APP in a smoother product, such as yogurt, without introducing grittiness. However, a great deal of individual variability was noted with some participants able to detect the smallest particle sizes (166 μm) and some not able to detect even the largest particle sizes (642 μm). Participants were clustered into groups using agglomerative hierarchical cluster analysis and high (44 %), medium (31 %) and low (25 %) particle sensitivity groups were observed. The diversity of particle size detection thresholds in the population presents both an opportunity and challenge for product developers seeking to avoid gritty or grainy textures and should be further studied.

Poster Session: Towards Understanding Retinal Processing of Single-Cone Scale Stimulation.

The magnocellular (M) visual pathway can be distinguished from its finer-grained parvocellular (P) counterpart by its stronger response gain to contrasts near human detection threshold. This distinction is found when stimulus size is matched to the relatively large receptive field size of M cells, but it is less clear if preserved at smaller spatial scales. We examined foveal detection thresholds in tandem with a masking paradigm known to desensitize the M pathway. We used a custom DLP display in Maxwellian view to present either 3 or 23 arcmin spots for 100 ms against a uniform gray disk (1° VA) surrounded by a 0.5 cpd, 100% contrast, square wave grating flickered at 7 frequencies ranging from 0 to 30 Hz. Detection data were fit with psychometric functions to estimate threshold and thresholds were normalized to the static (0 Hz) condition. Relative sensitivity was fit with a modified impulse response function and compared to a constant model with ANOVA. With masking we found a significant reduction in sensitivity for large (23arcmin) increments (mean=0.39 log units; n=4; p<0.01) and decrements (0.31 log units; n=4; p=0.02)at 8.3Hz. By contrast, no significant masking effect was observed for small spot increments or decrements (p>0.05). These data suggest that the M pathway is not the primary determinant of small spot thresholds under the conditions studied. Further investigation with adaptive optics may be necessary to fully elaborate single-cone processing in the fovea.

Influence of response-time limits on automated hearing threshold determination

Objective In automated hearing threshold determination procedures, prespecified response- time limits can be applied to evaluate whether a stimulus was truly heard by checking whether the test subject reacts to the onset and the offset of the stimuli within given time intervals. The influence of different response-time limits on the threshold of normal-hearing test subjects was investigated. Design Two-stage hearing threshold level measurements applying the ISO 8253-1 (2010) bracketing procedure were performed. Pre-tests at 125 Hz and 1000 Hz were carried out with maximum accepted response times of 600 ms, 1000 ms, and 1200 ms. Subsequently, thresholds were measured at the seven octaves between 125 Hz and 8000 Hz with maximum accepted response times of 600 ms and 1000 ms. Study sample 15 test subjects in pre-tests, 25 test subjects in the main study. Results Threshold levels determined with a maximum accepted response time of 1000 ms are 2.6 dB lower than those obtained with a maximum accepted response time of 600 ms (95% CI −1.6 dB to 6.9 dB). The threshold shift was similar at all frequencies. Conclusions Based on this study, response-time limits after both stimulus onset and offset of at least 1000 ms are recommended.

Rapid DNA extraction and colorimetric amplicon visualisation speed up LAMP-based detection of soybean allergen in foods

AbstractDetection of allergens in foods, including soybean, is relevant for food labelling requirements. Moreover, allergen-specific methods may allow standardisation of allergens in food matrices for use in food challenges as allergy diagnostic approaches. Rapid methods are preferred for screening and along the manufacturing line. Previously, we demonstrated sensitive and specific detection of soybean DNA by combining loop-mediated isothermal amplification (LAMP) and lateral flow device (LFD)-like visualisation. However, lengthy DNA extraction and potential contamination of subsequent by previous LAMP reactions from unclosed LFD may impact its use as a rapid and robust method. Here, we developed a rapid protocol for DNA extraction. Moreover, we identified phenol red for distinct visualisation of positive reactions in permanently closed reaction tubes. The optimised method was validated using complex foods (boiled sausage, instant soup, and chocolate) with known amounts of soybean. Further, its applicability was shown in 12 processed retail foods. Results were verified by orthogonal qPCR. The enhanced LAMP method allowed detection at or below 10 mg soybean per kg processed food. The method provides rapid and easy-to-use screening without the need for detection equipment. Hence, it may serve to verify the presence of soybean ingredients and support a risk-based precautionary labelling of non-ingredient soybean in compound foods. Also, as determination of clinical reaction thresholds before and after allergen immunotherapy (AIT) is both inclusion and exclusion criterion for clinical trials and success parameter of AIT, the method may allow verification of calculable soybean content in provocation meals and thus a standardised administration for threshold determination before and after AIT.

The micromechanics of graphene oxide and molybdenum disulfide in thermoplastic nanocomposites and the impact to the polymer-filler interphase

The addition of two-dimensional nanomaterials to a polymer matrix is a widely known manner to mechanically reinforce the material. The stress-transfer in the polymeric matrices, however, depends on an array of filler and matrix properties as well as on their interface. In this work, we discuss the effects of the distinct levels of interaction of graphene oxide, reduced graphene oxide and molybdenum disulfide with poly(vinyl butyral) in the reinforcement of the polymer. For that, we employed the micromechanical analysis model originally developed by Young et al., which describes the reinforcement behavior of graphene nanoplatelets in a wide range of polymer matrices. Then, using an innovative approach derived from such analysis, we propose novel methods to mathematically evaluate the effects of the filler content upon the polymer/filler interface, and for the determination of the mechanical percolation threshold.

Constructing shadowed set based on game analysis of uncertainty and decision cost

As a three-way approximation scheme to deal with fuzzy set, shadowed set approximately divides fuzzy objects with uncertainty into elevated, reduced, and shadow areas by a pair of decision thresholds α,β, thus effectively reducing the uncertainty of information. However, the current construction of shadowed set is all based on a single principle, lacking the comprehensive consideration of multiple principles, and these construction principles focus on the rationality of semantic interpretation of model construction process and threshold determination, and lack of consideration of the validity of partition results. To resolve these issues, this paper proposes a new shadowed set model through the game analysis between uncertainty and decision cost (UC-GTSS). First, Combining shadowed set construction with game theory, UC-GTSS is proposed based on game competition mechanism. Through the game analysis of uncertainty and decision cost, the optimal α,β is found, and a game payoff fusion algorithm based on Topsis is proposed. Second, the definition of UC-GTSS model expression, game player, strategy, payoff function, equilibrium analysis, optimization α,β determination and the influence of model parameters are analyzed and discussed. Third, the UC-GTSS model is extended and discussed based on the validity of the partition results, such as the game between approximate classification accuracy and coverage, the game between the Gini coefficient of the partition areas. Finally, through the analysis of algorithms, instances and data experiments, the construction process, validity, and rationality of UC-GTSS and its extended model are demonstrated.

Quantitative analysis of the optogenetic excitability of CA1 neurons.

Optogenetics has emerged as a promising technique for modulating neuronal activity and holds potential for the treatment of neurological disorders such as temporal lobe epilepsy (TLE). However, clinical translation still faces many challenges. This in-silico study aims to enhance the understanding of optogenetic excitability in CA1 cells and to identify strategies for improving stimulation protocols. Employing state-of-the-art computational models coupled with Monte Carlo simulated light propagation, the optogenetic excitability of four CA1 cells, two pyramidal and two interneurons, expressing ChR2(H134R) is investigated. The results demonstrate that confining the opsin to specific neuronal membrane compartments significantly improves excitability. An improvement is also achieved by focusing the light beam on the most excitable cell region. Moreover, the perpendicular orientation of the optical fiber relative to the somato-dendritic axis yields superior results. Inter-cell variability is observed, highlighting the importance of considering neuron degeneracy when designing optogenetic tools. Opsin confinement to the basal dendrites of the pyramidal cells renders the neuron the most excitable. A global sensitivity analysis identified opsin location and expression level as having the greatest impact on simulation outcomes. The error reduction of simulation outcome due to coupling of neuron modeling with light propagation is shown. The results promote spatial confinement and increased opsin expression levels as important improvement strategies. On the other hand, uncertainties in these parameters limit precise determination of the irradiance thresholds. This study provides valuable insights on optogenetic excitability of CA1 cells useful for the development of improved optogenetic stimulation protocols for, for instance, TLE treatment.

Rapid evaluation of the high-speed railway bridge vertical deformation threshold and train operation safety performance based on the virtual track inspection method

This study proposes a method for analyzing the impact of bridge deformation on the train-track-bridge coupled dynamics from the perspective of dynamic track geometry. First, with the static mapping geometry and the superposition of random track irregularities are used as excitations, a mapping analytical model between bridge foundation deformation and dynamic track geometry is established by combining the vehicle-track-bridge dynamics model and the virtual track inspection model. Second, after analyzing the effect of bridge foundation deformation on the ratio of dynamic and static extremums of the second derivative, the mapping relationship among the amplitude of the bridge deformation, the second derivative of the dynamic track geometry and the vehicle dynamic response is obtained. Finally, based on the driving safety indicators, a threshold determination method applicable to different bridge deformation patterns is proposed. This method, when combined with modern track detection technology, allows for rapid evaluation and is adaptable to complex bridge deformation scenarios.

Reliability of threshold determination using portable muscle oxygenation monitors during exercise testing: a systematic review and meta-analysis

Over the last few years, portable Near-Infrared Spectroscopy (NIRS) technology has been suggested for determining metabolic/ventilator thresholds. This systematic review and meta-analysis aimed to assess the reliability of a portable muscle oxygenation monitor for determining thresholds during exercise testing. The proposed PICO question was: Is the exercise intensity of muscle oxygenation thresholds, using portable NIRS, reliable compared with lactate and ventilatory thresholds for exercise intensity determined in athletes? A search of Pubmed, Scopus and Web of Science was undertaken and the review was conducted following PRISMA guidelines. Fifteen articles were included. The domains which presented the highest biases were confounders (93% with moderate or high risk) and participant selection (100% with moderate or high risk). The intra-class correlation coefficient between exercise intensity of the first ventilatory or lactate threshold and the first muscle oxygenation threshold was 0.53 (obtained with data from only 3 studies), whereas the second threshold was 0.80. The present work shows that although a portable muscle oxygenation monitor has moderate to good reliability for determining the second ventilatory and lactate thresholds, further research is necessary to investigate the mathematical methods of detection, the capacity to detect the first threshold, the detection in multiple regions, and the effect of sex, performance level and adipose tissue in determining thresholds.

Feature extraction-reduction and machine learning for fault diagnosis in PV panels

With the rapid expansion and installation of Photovoltaic (PV) power plants, developing a proper Fault Detection and Diagnosis (FDD) strategy has become a significant issue within the objective to organize and plan for maintenance and reduce repair time, which in turn ensures the availability of operated systems. In this context, supervised Machine Learning (ML) algorithms are undergoing extensive development and their performances are analyzed in terms of different metrics including computation time detection accuracy, precision, recall, and F1-score in addition to False Alarm and missed detection rates. However, such algorithms generally require the extraction of significant features to handle irrelevant and redundant features while reducing the computational burden. Considering that different dimensionality reduction methods directly impact the FDD performances, this paper presents a novel Data Dimensionality Reduction Strategy (DDRS) based on a proposed algorithm for Information Gain (IG) score optimal threshold determination. This strategy also relies on Principal Component Analysis (PCA) to obtain the optimal subset which represents the lowest dimensional feature in the training and testing stages of different supervised ML algorithms. FDD performances are then evaluated by using faulty and non-faulty datasets acquired experimentally from a Grid-connected PV system (GPVS) emulator. The experimental results show the efficiency of the proposed strategy and its ability to improve the FDD based on supervised ML algorithms.

Transient electron temperature and density changes in water breakdown induced by femtosecond laser pulses

When a femtosecond laser pulse travels through water, optical breakdown occurs when the laser intensity exceeds a certain threshold. This photoionization (PI) process and the resulting laser-induced plasma can strongly influence the laser ablation of substances, including transparent biological tissue, etc. However, numerical models of the initial evolution of the laser plasma and its early electron temperature remain inadequate. Here, a transient ionization rate equation involving the solvation process is proposed for calculating the free-electron number density (FED) generated during the interaction of the femtosecond laser with the water surface, along with the temporal evolution of the electron temperature in the focusing region during the entire femtosecond laser pulse utilizing an improved temperature model. The predictions of the proposed model are in better agreement with the experimentally determined breakdown thresholds. The results indicate that the existence of solvated electrons has a considerable influence on the determination of the optical breakdown threshold in water, which may also be one of the reasons why traditional numerical models consistently fail to forecast the actual breakdown threshold.

Static breakdown threshold modeling of quasi-uniform gas gaps with a focus on the PDIV of contacting enameled wire pairs

This paper provides a theoretical and conceptual framework for the determination of static breakdown inception thresholds in quasi-uniform gas gaps bounded by dielectric layers of thickness s and relative permittivity . The special case of uncoated metallic electrodes is included in the limit . Moreover, a review of breakdown mechanisms and the underlying physical processes in quasi-uniform gas gaps is provided, and the applicability of the associated breakdown criteria is discussed. The results include a parametrization of the partial discharge inception voltage of wedge-shaped air gaps at atmospheric pressure as a function of the reduced coating thickness . The predicted results for this prototypical insulation geometry agree well with a broad array of literature data and own measurements. Finally, a physically motivated parametrization of the ionization threshold K(d) is suggested for atmospheric pressure air in terms of secondary electron feedback by energetic photons and ion-enhanced field emission. This contrasts with the ad hoc introduction of modified ‘streamer constants’ often found in literature to explain breakdown voltages that deviate from the predictions of the classical Raether–Meek–Loeb criterion.

ОЦЕНКА РАДИАЦИОННЫХ РИСКОВ ЗАБОЛЕВАЕМОСТИ КАТАРАКТОЙ ЛИКВИДАТОРОВ ПОСЛЕДСТВИЙ АВАРИИ НА ЧЕРНОБЫЛЬСКОЙ АЭС С УЧЕТОМ ВЛИЯНИЯ СОПУТСТВУЮЩИХ БОЛЕЗНЕЙ

Purpose: To assess the radiation risk of cataracts among the Chernobyl clean-up workers (liquidators), considering the impact of concomitant diseases on this risk and to determine the dose threshold for the development of cataracts. Material and methods: Radiation risks of cataract incidence were studied in the cohort of liquidators of the consequences of the accident at the Chernobyl nuclear power plant, observed in the system of the National Radiation and Epidemiological Register (NRER) from 1986 to 2021. Among the 62,828 male liquidators, 9,461 new cases of cataracts were detected. The average age of the liquidators at the beginning of exposure was 34 years, the average absorbed dose of external gamma exposure of the whole body was 0.132 Gy, the maximum dose was 1.5 Gy, and the average duration of exposure was 2.5 months. To analyze the relationships of cataract incidence with other diseases and with the dose, a statistical method of link analysis, free from the type of distribution, as well as logistic regression models, were used. Results: The radiation risk of cataracts in the cohort of liquidators who did not have diagnoses of diabetes mellitus, hypoparathyroidism, malnutrition and myotonic disorders depends on the presence of concomitant diseases in the patient: glaucoma (ICD-10 H40–H42), hyperopia (H52.0), myopia (H52.1) or presbyopia (H52.4). For liquidators with comorbidities, radiation risk is statistically significant only 15 years after exposure, with an excess relative risk of ERR/Gy=0.46 with 90 % CI (0.06; 0.90). For liquidators without comorbidities, ERR/Gy decrease over time: from 4.42 with 90 % CI (0.72; 13.41) in the first 5 years, to zero risk 15 years after exposure. Nonparametric estimates of the relative risk (RR) of cataracts for the dose groups of liquidators are consistent with the estimates of ERR/Gy in the linear non-threshold (LNT) model. The determination of the dose threshold for cataracts according to the LNT model, in accordance with the recommendations of the ICRP, leads to estimates from 1.2 Gy to 13.3 Gy, depending on the presence or absence of cataract concomitant diseases in the liquidators. Conclusions: At present, there are no epidemiological evidence for reducing the equivalent dose limit for the lens of the eye for occupational exposure in planned exposure situations at the level of 150 mSv per year, previously established by the recommendations of the ICRP in 2007 and the current Russian radiation safety standards NRB-99/2009.

Psychophysical assessment of pain in adults with moderate and severe haemophilia: A cross-sectional study.

Joint pain is the hallmark of haemophilia; therefore it seems clinically rather a musculoskeletal than a bleeding disorder. Although joint pain in people with haemophilia (PwH) is a complex and multidimensional problem, pain assessment remains primarily focused on the structural evaluation of their joints. Whereas, only few data are available on the potential implication of psychophysical and psychological factors. This study aimed to perform a psychophysical pain assessment including quantitative sensory testing (QST) and an evaluation of psychological factors in a large sample of PwH, to get insight into the individuals' pain system. Ninety-nine adults (36.9±13.5 years) with moderate/severe haemophilia A/B and 46 healthy controls filled in self-reported pain and psychological questionnaires and underwent a QST evaluation including static and dynamic tests. Static tests focused on the determination of thermal detection and pain thresholds and mechanical pressure pain thresholds. Dynamic tests evaluated pain facilitation and the efficacy of endogenous pain inhibition. Besides comparing PwH and healthy controls, between-subgroup differences were studied in PwH based on their pain distribution. The study revealed increased thermal and mechanical pain sensitivity and the presence of unhelpful psychological factors such as anxiety/depression in PwH. Among the subgroups, especially PwH with widespread pain showed altered somatosensory functioning. Enhanced pain facilitation and impaired efficacy of endogenous pain inhibition in PwH could not be observed. Altered somatosensory functioning and unhelpful psychological factors, appear to play an important role in the pathophysiology of pain in PwH, especially in PwH with widespread pain.

Determination of lipemia acceptance thresholds for 31 immunoassay analytes

BackgroundLipemia is one of common endogenous interferences that can compromises sample quality and potentially influence results of various laboratory methods. Determination of the lipemic index or triglyceride concentrations are used to define the degree of lipemia. This study was aimed to establish lipemic index (LI) and triglyceride thresholds above where significant interference exists for 31 immunoassay analytes measured on Roche Cobas 6000. Materials and methodsThe study was carried out following CLSI C56-A and EP07-ED3:2018 guidelines using sample pools spiked with increasing concentrations of lipid emulsion solution, reaching 70 mmol/L. To define the LI and triglyceride thresholds, the bias from concentration in the native sample was calculated at different lipemia degree and compared with allowable error limits based on biological variation or state-of-the-art technology. ResultsNo lipemia interference was observed for 27 out of 31 analytes even at the highest concentrations of lipid emulsion (LI ranging from 1737 to 2086 mg/dL, triglyceride concentration 60.34–73.99 mmol/L). However, progesterone, 25-OH vitamin D, testosterone, and estradiol were negatively affected by lipemia at 217 mg/dL (9.58 mmol/L), 222 mg/dL (10.66 mmol/L), 478 mg/dL (18.81 mmol/L), and 941 mg/dL (35.82 mmol/L) of the LI (triglyceride concentration), respectively. ConclusionMost immunoassays evaluated in this study were found to be robust to lipemia interference. By using these thresholds, laboratories can report the immunoassay results from analyzing a lipemic patient sample in many cases.

Threshold Determination for False Track Probability in the Multipath ML-PMHT

We analyze the likelihood distribution for a multipath model in which no target is present, focusing on the peculiarities of the ML-PMHT when multiple peaks emerge. We study analytically the case in which peaks are separated and for the general case we propose a numerical algorithm based on sampling. The final distribution is used to compute a parameter-dependent false alarm probability threshold.

Substrate-mediated leg interactions play a key role in insect stability on granular slopes.

Locomotion on granular inclines is a subject of high relevance in ecological physics as well as in biomimmetics and robotics. Enhancing stability on granular materials represents a huge challenge due to the fluidization transition when inclination approaches the avalanche angle. Our motivating example is the predator-prey system made of the antlion, its pit, and its prey. Recent studies have demonstrated that stability on granular inclines strongly depends on the pressure exerted on the substrate. In this work we show that for multilegged locomotion, along with pressure, the distance between the leg contacts on the substrate also plays a major role in the determination of the stability threshold. Through a set of model experiments using artificial sliders, we determine a critical distance below which stability is importantly affected by the interactions between the perturbed regions generated by each contact point. A simple model based on the Coulomb method of wedges allows us to estimate a stability criterion based on pressure, interleg distance, and substrate characteristics. Our work suggests that mass to leg-length allometric relationships, as the ones observed in ants, may be an important key in determining the locomotion success of multilegged locomotion on granular inclines.

Correction of Threshold Determination in Rapid-Guessing Behaviour Detection

Assessment is one benchmark in measuring students’ abilities. However, assessment results cannot necessarily be trusted, because students sometimes cheat or even guess in answering the questions. Therefore, to obtain valid results, it is necessary to separate valid and invalid answers by considering rapid-guessing behaviour. We conducted a test to record exam log data from undergraduate and postgraduate students to model rapid-guessing behaviour by determining the threshold response time. Rapid-guessing behaviour detection is inspired by the common k-second method. However, the method flattens the application of the threshold, thus allowing misclassification. The modified method considers item difficulty in determining the threshold. The evaluation results show that the system can identify students’ rapid-guessing behaviour with a success rate of 71%, which is superior to the previous method. We also analysed various aggregation techniques of response time and compared them to see the effect of selecting the aggregation technique.

Development and Application of a Novel Snow Peak Sighting Forecast System over Chengdu

As air quality has improved rapidly in recent years, the public has become more interested in whether a famous snow peak, Yaomei Feng on the Tibetan Plateau, can be seen from Chengdu, a megacity located on the western plain of the Sichuan Basin, east of the plateau. Therefore, a threshold-method-based forecasting system for snow peak sighting was developed in this study. Variables from numerical models, including cloud–water mixing ratio, cloud cover over snow peak, water mixing ratio, PM2.5 concentration, and ground solar radiation, were used in the snow peak sighting forecast system. Terrain occlusion rate of each model grid was calculated. Monte Carlo simulations were applied for threshold determination. A WRF-CMAQ hindcast was conducted for 2020, owing to insufficient observation data, hindcast results on the snow peak sighting were compared with posts collected from social media. Estimations showed that the snow peak sighting forecast system performed well in reflecting the monthly trend of snow peak sightings, and the hindcast results matched the daily observations, especially from May to August. Accuracy of the snow peak sighting forecast model was 78.9%, recall value was 57.1%, and precision was 24.4%.