Threshold Estimation Research Articles

PSYCHOACOUSTICS-WEB: A free online tool for the estimation of auditory thresholds.

PSYCHOACOUSTICS-WEB is an online tool written in JavaScript and PHP that enables the estimation of auditory sensory thresholds via adaptive threshold tracking. The toolbox implements the transformed up-down methods proposed by Levitt (Journal of the Acoustical Society of America, 49, 467-477, (1971) for a set of classic psychoacoustical tasks: frequency, intensity, and duration discrimination of pure tones; duration discrimination and gap detection of noise; and amplitude modulation detection with noise carriers. The toolbox can be used through a common web browser; it works with both fixed and mobile devices, and requires no programming skills. PSYCHOACOUSTICS-WEB is suitable for laboratory, classroom, and online testing and is designed for two main types of users: an occasional user and, above all, an experimenter using the toolbox for their own research. This latter user can create a personal account, customise existing experiments, and share them in the form of direct links to further users (e.g., the participants of a hypothetical experiment). Finally, because data storage is centralised, the toolbox offers the potential for creating a database of auditory skills.

Threshold Effect of Financial Inclusion on Poverty Reduction in Africa: Does institutional quality play a role?

ABSTRACT In Africa, poverty levels are still very high, especially with the advent of the COVID-19 pandemic, despite efforts by governments and development partners to address it. Financial inclusion has been identified as an important concept in fighting poverty due to its ability to increase the income level of households. This study sought to estimate the threshold level at which financial inclusion, aided by strong institutions, will lead to poverty reduction in Africa, using Hansen’s threshold estimation method, covering a period of 2004–2020. The Hansen threshold estimation method uses an endogenous approach to identify threshold values, which eliminates deterministic process by using a systematic approach, as compared to the linear methods of sample-splitting of threshold-level specifications by other methods. This therefore makes the Hansen threshold estimation method robust in threshold estimations compared to other methods. The study found double threshold values of 0.0534 and 0.341, indicating that a financial inclusion value below 0.0534 would increase household consumption expenditure, leading to poverty reduction. However, a threshold value between 0.0534 and 0.3141 has a negative impact on poverty reduction. Furthermore, beyond a threshold value of 0.3141, financial inclusion will improve household consumption and as such reduce poverty in Africa. The study also established a threshold value of institutional quality index of −1.6325, indicating that below that institutional quality index, financial inclusion will have a negative impact on household consumption as well as poverty reduction in Africa. The results further indicated that dependency ratio, gross national income, interest rate, inflation, education, and government expenditure contribute significantly to poverty reduction in Africa. It is recommended that development partners, central banks and governments in the region should consciously develop and implement financial literacy policies, with the collaboration of all financial institutions that are aimed at promoting financial inclusion due to its ability to end poverty.

A first look at the reliability, validity and responsiveness of L-PF-35 dyspnea domain scores in fibrotic hypersensitivity pneumonitis

BackgroundDyspnea impairs quality of life (QOL) in patients with fibrotic hypersensitivity pneumonitis (FHP). The Living with Pulmonary Fibrosis questionnaire (L-PF) assesses symptoms, their impacts and PF-related QOL in patients with any form of PF. Its scores have not undergone validation analyses in an FHP cohort.MethodsWe used data from the Pirfenidone in FHP trial to examine reliability, validity and responsiveness of the L-PF-35 Dyspnea domain score (Dyspnea) and to estimate its meaningful within-patient change (MWPC) threshold for worsening. Lack of suitable anchors precluded conducting analyses for other L-PF-35 scores.ResultsAt baseline, Dyspnea’s internal consistency (Cronbach’s coefficient alpha) was 0.85; there were significant correlations with all four anchors (University of California San Diego Shortness of Breath Questionnaire scores r = 0.81, St. George’s Activity domain score r = 0.82, percent predicted forced vital capacity r = 0.37, and percent predicted diffusing capacity of the lung for carbon monoxide r = 0.37). Dyspnea was significantly different between anchor subgroups (e.g., lowest percent predicted forced vital capacity (FVC%) vs. highest, 33.5 ± 18.5 vs. 11.1 ± 9.8, p = 0.01). There were significant correlations between changes in Dyspnea and changes in anchor scores at all trial time points. Longitudinal models further confirmed responsiveness. The MWPC threshold estimate for worsening was 6.6 points (range 5–8).ConclusionThe L-PF-35 Dyspnea domain appears to possess acceptable psychometric properties for assessing dyspnea in patients with FHP. Because instrument validation is never accomplished with one study, additional research is needed to build on the foundation these analyses provide.Trial registrationThe data for the analyses presented in this manuscript were generated in a trial registered on ClinicalTrials.gov; the identifier was NCT02958917.

Exploring the nexus of globalization and natural resource scarcity in driving green technology innovation: Insights from advanced panel data techniques

AbstractGreen technology innovation (GTI) plays a pivotal role in improving environmental sustainability. Our study fills a significant research gap by investigating how globalization and natural resource depletion (NRD) impact eco‐innovation. Rooted in knowledge spillover and ecological modernization theories, we utilize advanced panel data techniques, an aspect underexplored in empirical studies. Our panel data span G20 countries from 1986 to 2019, further dissected into sub‐panels—BRICS (emerging economies) and G7 (advanced economies). Initial tests reveal cross‐sectional dependencies and slope heterogeneities across all panels, corroborated by Westerlund cointegration test indicating a long‐term equilibrium. Driscoll–Kraay estimator highlights that economic and social globalization significantly drive eco‐innovation, while political globalization deteriorates GTI. The effect of NRD is also negative for G20 and BRICS countries, while G7 economies exhibit lower vulnerability to NRD shocks. Long‐run estimates from CS‐ARDL underscore the positive role of economic globalization in both the short and long run, while the negative role of NRD remains persistent in the long run. Panel quantile regression results prove that the effect of globalization is asymmetric across GTI distribution and varying across underlying groups. NRD, while hindering progress at higher quantiles, supports eco‐innovation at lower quantiles of advanced economies. Panel threshold estimations confirm the positive influence of both globalization and NRD, particularly for highly eco‐innovative nations. These findings bear significant policy implications, charting a path toward sustainable economic growth through the widespread adoption of green technology.

Psychometric evaluation of the near activity visual questionnaire presbyopia (NAVQ-P) and additional patient-reported outcome items.

The Near Visual Acuity Questionnaire Presbyopia (NAVQ-P) is a patient-reported outcome (PRO) measure that was developed in a phakic presbyopia population to assess near vision function impacts. The study refined and explored the psychometric properties and score interpretability of the NAVQ-P and additional PRO items assessing near vision correction independence (NVCI), near vision satisfaction (NVS), and near vision correction preference (NVCP). This was a psychometric validation study conducted using PRO data collected as part of a Phase IIb clinical trial (CUN8R44 A2202) consisting of 235 randomized adults with presbyopia from the US, Japan, Australia, and Canada. Data collected at baseline, week 2, and months 1, 2, and 3 during the 3-month trial treatment period were included in the analyses to assess item (question) properties, NAVQ-P dimensionality and scoring, reliability, validity, and score interpretation. Item responses were distributed across the full response scale for most NAVQ-P and additional PRO items. Confirmatory factor analysis supported the pre-defined unidimensional structure and calculation of a NAVQ-P total score as a measure of near vision function. Item deletion informed by item response distributions, dimensionality analyses, item response theory, and previous qualitative findings, including clinical input, supported retention of 14 NAVQ-P items. The 14-item NAVQ-P total score had excellent internal consistency (α = 0.979) and high test-retest reliability (Intraclass Correlation Coefficients > = 0.898). There was good evidence of construct-related validity for all PROs supported by strong correlations with concurrent measures. Excellent results for known-groups validity and ability to detect change analyses were also demonstrated. Anchor-based and distribution-based methods supported interpretation of scores through generation of group-level and within-individual estimates of meaningful change thresholds. A meaningful within-patient change in the range of 8-15-point improvement on the NAVQ-P total score (score range 0-42) was recommended, including a more specific responder definition of 10-point improvement. The NAVQ-P, NVCI, and NVS are valid and reliable instruments which have the ability to detect change over time. Findings strongly support the use of these measures as outcome assessments in clinical/research studies and in clinical practice in the presbyopia population.

Towards ASSR-based hearing assessment using natural sounds

Objective. The auditory steady-state response (ASSR) allows estimation of hearing thresholds. The ASSR can be estimated from electroencephalography (EEG) recordings from electrodes positioned on both the scalp and within the ear (ear-EEG). Ear-EEG can potentially be integrated into hearing aids, which would enable automatic fitting of the hearing device in daily life. The conventional stimuli for ASSR-based hearing assessment, such as pure tones and chirps, are monotonous and tiresome, making them inconvenient for repeated use in everyday situations. In this study we investigate the use of natural speech sounds for ASSR estimation. Approach. EEG was recorded from 22 normal hearing subjects from both scalp and ear electrodes. Subjects were stimulated monaurally with 180 min of speech stimulus modified by applying a 40 Hz amplitude modulation (AM) to an octave frequency sub-band centered at 1 kHz. Each 50 ms sub-interval in the AM sub-band was scaled to match one of 10 pre-defined levels (0–45 dB sensation level, 5 dB steps). The apparent latency for the ASSR was estimated as the maximum average cross-correlation between the envelope of the AM sub-band and the recorded EEG and was used to align the EEG signal with the audio signal. The EEG was then split up into sub-epochs of 50 ms length and sorted according to the stimulation level. ASSR was estimated for each level for both scalp- and ear-EEG. Main results. Significant ASSRs with increasing amplitude as a function of presentation level were recorded from both scalp and ear electrode configurations. Significance. Utilizing natural sounds in ASSR estimation offers the potential for electrophysiological hearing assessment that are more comfortable and less fatiguing compared to existing ASSR methods. Combined with ear-EEG, this approach may allow convenient hearing threshold estimation in everyday life, utilizing ambient sounds. Additionally, it may facilitate both initial fitting and subsequent adjustments of hearing aids outside of clinical settings.

Preferential Hydrologic States and Tipping Characteristics of Global Surface Soil Moisture

AbstractA dynamic transition in soil hydrologic states through meteorological variability and terrestrial feedback governs soil‐vegetation‐climate (SVC) interactions, constrained by critical soil moisture (SM) thresholds. However, observational and scaling constraints limit critical SM threshold estimation at the remote‐sensing (RS) footprint scale. Using global surface SM (θRS) from NASA’s Soil Moisture Active Passive (SMAP) satellite, we characterize the seasonal preferential hydrologic states of θRS and derive three tipping characteristics to estimate the intensity (Mean Tipping Depth, ), frequency (Tipping Count, η), and duration (Mean Tipped Time, ) of the excursion of θRS from wet‐ to dry‐average conditions. The preferential state provides the seasonally dominant hydrological states of θRS, while tipping characteristics capture the ecosystem linkages of the dynamic transition in θRS hydrologic states. Globally, θRS predominantly exhibits a (unimodal) dry‐preferential state, especially over arid/semi‐arid drylands and a unimodal wet‐preferential θRS state in high‐latitude boreal forests and tundra biomes. Prevalence of (bimodal) bistable θRS state overlaps with regions of strong positive SM‐precipitation coupling and monsoonal climate in semi‐arid/subhumid climates. Seasonal preferential hydrologic states co‐vary with the regional variability in plant water stress threshold and land‐atmospheric coupling strength. Tipping characteristics of θRS show sensitivity to intra‐biome variability in SVC coexistence patterns and display high skill in partitioning global ecoregions. While and η are climate‐controlled, is moderated by soil and vegetation through their influence over θRS drydown during water‐limited evapotranspiration. Preferential states and tipping characteristics find applications in quantifying SVC coexistence patterns, climate model diagnosis, and assessing ecosystem sensitivity to climate change.

Variational Hybrid-Attention Framework for Multi-Label Few-Shot Aspect Category Detection

Multi-label few-shot aspect category detection (FS-ACD) is a challenging sentiment analysis task, which aims to learn a multi-label learning paradigm with limited training data. The difficulty of this task is how to use limited data to generalize effective discriminative representations for different categories. Nowadays, all advanced FS-ACD works utilize the prototypical network to learn label prototypes to represent different aspects. However, such point-based estimation methods are inherently noise-susceptible and bias-vulnerable. To this end, this paper proposes a novel Variational Hybrid-Attention Framework (VHAF) for the FS-ACD task. Specifically, to alleviate the data noise, we adopt a hybrid-attention mechanism to generate more discriminative aspect-specific embeddings. Then, based on these embeddings, we introduce the variational distribution inference to obtain the aspect-specific distribution as a more robust aspect representation, which can eliminate the scarce data bias for better inference. Moreover, we further leverage an adaptive threshold estimation to help VHAF better identify multiple relevant aspects. Extensive experiments on three datasets demonstrate the effectiveness of our VHAF over other state-of-the-art methods. Code is available at https://github.com/chengzju/VHAF.

Order effects in stimulus discrimination challenge established models of comparative judgement: A meta-analytic review of the Type B effect.

This paper provides a comprehensive review of the TypeB effect (TBE), a phenomenon reflected in the observation that discrimination sensitivity varies with the order of stimuli in comparative judgment tasks, such as the two-alternative forced-choice (2AFC) paradigm. Specifically, when the difference threshold is lower (higher) with the constant standard preceding rather than following the variable comparison, one speaks of a negative (positive) TBE. Importantly, prominent psychophysical difference models such as signal detection theory (Green & Swets, 1966) cannot easily account for the TBE, and are hence challenged by it. The present meta-analysis provides substantial evidence for the TBE across various stimulus attributes, suggesting that the TBE is a general feature of discrimination experiments when standard and comparison are presented successively. Thus, inconsistent with psychophysical difference models, subjective differences between stimuli are not merely a function of their physical differences but rather also depend on their temporal order. From the literature, we identify four classes of potential candidate theories explaining the origin of the TBE, namely (1) differential weighting of the stimulus magnitudes at the two positions (e.g., Hellström, Psychological Research, 39, 345-388 1977), (2) internal reference formation (e.g., Dyjas, Bausenhart, & Ulrich, Attention, Perception, & Psychophysics, 74, 1819-1841 2012), (3) Bayesian updating (e.g., de Jong, Akyürek, & van Rijn, Psychonomic Bulletin and Review, 28, 1183-1190 2021), and (4) biased threshold estimation (García-Pérez & Alcalá-Quintana, Attention, Perception & Psychophysics, 72, 1155-1178 2010). As these models, to some extent, make differential predictions about the direction of the TBE, investigating the respective boundary conditions of positive and negative TBEs might be a valuable perspective for diagnostic future research.

Gender-specific prolactin thresholds to determine prolactinoma size: a novel Bayesian approach and its clinical utility.

In clinical practice, the size of adenomas is crucial for guiding prolactinoma patients towards the most suitable initial treatment. Consequently, establishing guidelines for serum prolactin level thresholds to assess prolactinoma size is essential. However, the potential impact of gender differences in prolactin levels on estimating adenoma size (micro- vs. macroadenoma) is not yet fully comprehended. To introduce a novel statistical method for deriving gender-specific prolactin thresholds to discriminate between micro- and macroadenomas and to assess their clinical utility. We present a novel, multilevel Bayesian logistic regression approach to compute observationally constrained gender-specific prolactin thresholds in a large cohort of prolactinoma patients (N = 133) with respect to dichotomized adenoma size. The robustness of the approach is examined with an ensemble machine learning approach (a so-called super learner), where the observed differences in prolactin and adenoma size between female and male patients are preserved and the initial sample size is artificially increased tenfold. The framework results in a global prolactin threshold of 239.4 μg/L (95% credible interval: 44.0-451.2 μg/L) to discriminate between micro- and macroadenomas. We find evidence of gender-specific prolactin thresholds of 211.6 μg/L (95% credible interval: 29.0-426.2 μg/L) for women and 1,046.1 μg/L (95% credible interval: 582.2-2,325.9 μg/L) for men. Global (that is, gender-independent) thresholds result in a high sensitivity (0.97) and low specificity (0.57) when evaluated among men as most prolactin values are above the global threshold. Applying male-specific thresholds results in a slightly different scenario, with a high specificity (0.99) and moderate sensitivity (0.74). The male-dependent prolactin threshold shows large uncertainty and features some dependency on the choice of priors, in particular for small sample sizes. The augmented datasets demonstrate that future, larger cohorts are likely able to reduce the uncertainty range of the prolactin thresholds. The proposed framework represents a significant advancement in patient-centered care for treating prolactinoma patients by introducing gender-specific thresholds. These thresholds enable tailored treatment strategies by distinguishing between micro- and macroadenomas based on gender. Specifically, in men, a negative diagnosis using a universal prolactin threshold can effectively rule out a macroadenoma, while a positive diagnosis using a male-specific prolactin threshold can indicate its presence. However, the clinical utility of a female-specific prolactin threshold in our cohort is limited. This framework can be easily adapted to various biomedical settings with two subgroups having imbalanced average biomarkers and outcomes of interest. Using machine learning techniques to expand the dataset while preserving significant observed imbalances presents a valuable method for assessing the reliability of gender-specific threshold estimates. However, external cohorts are necessary to thoroughly validate our thresholds.

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.

Estimation of Soil Moisture Thresholds for Aggravation of Global Terrestrial Carbon Uptake Losses

AbstractMost ecosystems have resistance to soil moisture (SM) deficit, which is termed drought resistance. Drought resistance can be invalid and global terrestrial carbon uptake losses can be aggravated when SM deficit exceeds a critical threshold. However, soil moisture thresholds (SMTs) that detrimentally impact global terrestrial carbon uptake are still unclear. We performed numerical simulations using the Community Earth System Model, and estimated the SMTs by the back propagation neural network method for the years 2004–2014. The SMTs represent the inflection point for vegetation changes from high to low drought resistance phase, and terrestrial carbon uptake losses from low to high rate. Soil moisture‐limited ecoregions have higher SMTs than energy‐limited ecoregions, indicating the increased vulnerability and sensitivity of SM‐limited ecoregions to SM deficit and more easily aggravated terrestrial carbon uptake losses during drought. SMTs varied in different vegetation types and broadleaf deciduous trees displayed the highest SMTs and C3 arctic grasses have lowest thresholds. Humid and high vegetation coverage rate regions have lower thresholds. The SMTs increase with the increase of clay content and the decrease of sand content. In addition, land‐atmosphere feedback caused by SM deficit has a large impact on terrestrial carbon uptake and may be one of the main reasons for the aggravation of vegetation carbon uptake losses. Our results provide a unique perspective for investigating the impact of drought on vegetation.

Development and Psychometric Validation of a Patient-Reported Outcome Measure to Assess the Signs and Symptoms of Chronic Hand Eczema: The Hand Eczema Symptom Diary (HESD).

Chronic Hand Eczema (CHE) is an inflammatory skin disease of the hands. The Hand Eczema Symptom Diary (HESD) is a new patient-reported outcome measure of worst severity of core CHE signs/symptoms. This study aimed to evaluate content and psychometric validity of the HESD. The HESD was developed based on the literature and concept elicitation interviews. Qualitative cognitive debriefing interviews were conducted with CHE patients to assess relevance and understanding of items, response options and recall period. Psychometric properties of the HESD (item performance, dimensionality, reliability, validity, responsiveness and estimation of meaningful change thresholds) were then assessed, first using data from a phase 2b trial (NCT03683719), and confirmed using data from the first 280 participants completing the 16-week treatment phase of a phase 3 trial (NCT04871711). Cognitive debriefing supported item refinement and removal of items and confirmed all items were well understood and relevant to patients. Item properties and dimensionality analyses in the phase 2b data supported removal of additional items, resulting in the 6-item HESD included in the phase 3 trial. Unidimensionality was supported by inter-item correlations (all > 0.70) and Rasch analysis. Internal consistency (Cronbach's alpha = 0.96) and test-retest reliability (IntraclassCorrelationCoefficient > 0.89) results were very strong. Construct validity was supported by moderate correlations with concurrent measures (0.53-0.64) and significant differences between severity groups (p < 0.001). Large effect sizes for mean change scores in participantsthat improved and significant differences between change groups indicatedthe ability to detect change. Anchor-based analyses supported within-individual responder definitions of ≥ 4-points for improvements in 7-day average HESD scores. The HESD is the first CHE-specific, patient-reported outcome measure of CHE signs/symptoms developed and validated in line with regulatory guidance. This article provides evidence of strong content validity and psychometric validity and shows improvements of ≥ 4 points on 7-day average HESD scores represent clinically meaningful, important changes. NCT03683719, NCT04871711.

Sparse basis covariance matrix estimation for high dimensional compositional data via hard thresholding

Motivated by the high-dimensional compositional data appearing in many fields, this paper addresses the problem of large covariance estimation for compositional data. Firstly, we introduce the hard thresholding estimator to approximate the sparse basis covariance matrix which is relevant with compositional data. Then the upper error bounds are measured by the general matrix lv,w-norm and the general entrywise Lv,w-norm respectively with v,w∈[1,∞] in terms of probability. Finally, numerical simulations and real datasets application demonstrate that our estimator is close to the oracle estimator and outperforms the COAT estimator proposed by Cao et al. (2019).

Gaussian Processes for Hearing Threshold Estimation Using Auditory Brainstem Responses.

The Auditory Brainstem Response (ABR) plays an important role in diagnosing and managing hearing loss, but can be challenging and time-consuming to measure. Test times are especially long when multiple ABR measurements are needed, e.g., when estimating hearing threshold at a range of frequencies. While many detection methods have been developed to reduce ABR test times, the majority were designed to detect the ABR at a single stimulus level and do not consider correlations in ABR waveforms across levels. These correlations hold valuable information, and can be exploited for more efficient hearing threshold estimation. This was achieved in the current work using a Gaussian Process (GP), i.e., a Bayesian approach for non-linear regression. The function to estimate with the GP was the ABR's amplitude across stimulus levels, from which hearing threshold was ultimately inferred. Active learning rules were also designed to automatically adjust the stimulus level and efficiently locate hearing threshold. Simulation results show test time reductions of up to ∼50% for the GP compared to a sequentially applied Hotelling's T2 test, which does not consider correlations across ABR waveforms. A case study was also included to briefly assess the GP approach in ABR data from an adult volunteer.

Towards Achieving the Sustainable Development Goals (SDGs): The Impact of Debts on Income Inequality in Africa

The Agenda for Sustainable Development provides a framework for the creation of a better and sustainable future for all. The Sustainable Development Goals (SDGs) focus on addressing global challenges, including income inequality. Among others, the SDGs also commit countries to work towards reducing income inequality and as such, lowering income inequality is one of the key issues in Africa. However, given the high levels of debt on the continent, reducing income inequality could be a challenge. Majority of the literature examines the link between debts and economic growth with little attention paid to the impact of debts on income inequality. Moreover, not much is known on whether the relationship between debt and income inequality is non–linear. This study therefore contributes to the existing research efforts by investigating the threshold effects of debts using data from 24 African countries by relying on the sample splitting and threshold estimation approach. The results reveal that, while debts generally dampen income inequality, unbridled debt accumulation above the estimated thresholds does not decrease income inequality, indicating that the income inequality–reducing impact holds at lower levels of debt–to–GDP ratio. This evidence is insensitive to different indicators of income inequality and debts. Findings from this study show how increasing indebtedness contributes to widening income inequality in Africa.

Psychometric Evaluation of the MENQOL Instrument in Women Experiencing Vasomotor Symptoms Associated with Menopause.

Vasomotor symptoms (VMS) associated with menopause can negatively affect health-related quality of life (HRQoL). The Menopause-Specific Quality of Life (MENQOL) questionnaire has been developed to assess QOL specific to menopause. The objective of the current study was to assess the psychometric properties, sensitivity to change, and clinically meaningful within-patient change of the MENQOL using data from the fezolinetant SKYLIGHT1 and 2 studies in individuals with VMS. Individuals aged ≥ 40 to ≤ 65years with moderate-to-severe VMS (≥ seven hot flashes/day) were enrolled. In addition to MENQOL, eight patient-reported outcome (PRO) measures were used for the psychometric evaluation. All PRO assessments were completed at weeks4 and 12 during the treatment period, and most were completed at baseline. Psychometric analyses included factor analysis and reliability, construct validity, and sensitivity to change assessments. The within-patient threshold for a clinically meaningful change in MENQOL was derived. In total, 1022 individuals were included from SKYLIGHT1 and 2. Mean MENQOL total score at baseline was 4.30, improving to 3.16 at week12. The confirmatory factor analysis supported established MENQOL domain structure, including the overall score. The internal consistency of the MENQOL overall and domain scores was supported using Cronbach's alpha and McDonald's omega, and MENQOL construct validity was supported for overall and domain scores. Item-to-item and item-total correlations were generally sufficient, and moderate test-retest reliability was noted. The scales against which construct validity and responsiveness for MENQOL domains were examined were moderately related to the MENQOL domains in general, providing additional support for acceptable measurement properties of MENQOL in this population. A reduction in MENQOL overall score of ≥ 0.9 points was identified as responding to treatment (a clinically important threshold). Thresholds of 2.0 points for the vasomotor domain and 0.9 for the psychosocial domain were estimated, in addition to distribution-based threshold estimates of 0.8 and 1.2 for the physical and sexual domains, respectively. The psychometric properties of the MENQOL overall and domain scores support use of this instrument to capture experiences among individuals with moderate-to-severe VMS associated with menopause and assess related endpoints in clinical trials. ClinicalTrials.gov identifiers NCT04003155 and NCT04003142.

Development of the Children's English and Spanish Speech Recognition Test: Psychometric Properties, Feasibility, Reliability, and Normative Data.

The Children's English and Spanish Speech Recognition (ChEgSS) test is a computer-based tool for assessing closed-set word recognition in English and in Spanish, with a masker that is either speech-shaped noise or competing speech. The present study was conducted to (1) characterize the psychometric properties of the ChEgSS test, (2) evaluate feasibility and reliability for a large cohort of Spanish/English bilingual children with normal hearing, and (3) establish normative data. Three experiments were conducted to evaluate speech perception in children (4-17 years) and adults (19-40 years) with normal hearing using the ChEgSS test. In Experiment 1, data were collected from Spanish/English bilingual and English monolingual adults at multiple, fixed signal-to-noise ratios. Psychometric functions were fitted to the word-level data to characterize variability across target words in each language and in each masker condition. In Experiment 2, Spanish/English bilingual adults were tested using an adaptive tracking procedure to evaluate the influence of different target-word normalization approaches on the reliability of estimates of masked-speech recognition thresholds corresponding to 70.7% correct word recognition and to determine the optimal number of reversals needed to obtain reliable estimates. In Experiment 3, Spanish/English bilingual and English monolingual children completed speech perception testing using the ChEgSS test to (1) characterize feasibility across age and language group, (2) evaluate test-retest reliability, and (3) establish normative data. Experiments 1 and 2 yielded data that are essential for stimulus normalization, optimizing threshold estimation procedures, and interpreting threshold data across test language and masker type. Findings obtained from Spanish/English bilingual and English monolingual children with normal hearing in Experiment 3 support feasibility and demonstrate reliability for use with children as young as 4 years of age. Equivalent results for testing in English and Spanish were observed for Spanish/English bilingual children, contingent on adequate proficiency in the target language. Regression-based threshold norms were established for Spanish/English bilingual and English monolingual children between 4 and 17 years of age. The present findings indicate the ChEgSS test is appropriate for testing a wide age range of children with normal hearing in either Spanish, English, or both languages. The ChEgSS test is currently being evaluated in a large cohort of patients with hearing loss at pediatric audiology clinics across the United States. Results will be compared with normative data established in the present study and with established clinical measures used to evaluate English- and Spanish-speaking children. Questionnaire data from parents and clinician feedback will be used to further improve test procedures.

AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification.

Dropout events bring challenges in analyzing single-cell RNA sequencing data as they introduce noise and distort the true distributions of gene expression profiles. Recent studies focus on estimating dropout probability and imputing dropout events by leveraging information from similar cells or genes. However, the number of dropout events differs in different cells, due to the complex factors, such as different sequencing protocols, cell types, and batch effects. The dropout event differences are not fully considered in assessing the similarities between cells and genes, which compromises the reliability of downstream analysis. This work proposes a hybrid Generative Adversarial Network with dropouts identification to impute single-cell RNA sequencing data, named AGImpute. First, the numbers of dropout events in different cells in scRNA-seq data are differentially estimated by using a dynamic threshold estimation strategy. Next, the identified dropout events are imputed by a hybrid deep learning model, combining Autoencoder with a Generative Adversarial Network. To validate the efficiency of the AGImpute, it is compared with seven state-of-the-art dropout imputation methods on two simulated datasets and seven real single-cell RNA sequencing datasets. The results show that AGImpute imputes the least number of dropout events than other methods. Moreover, AGImpute enhances the performance of downstream analysis, including clustering performance, identifying cell-specific marker genes, and inferring trajectory in the time-course dataset. The source code can be obtained from https://github.com/xszhu-lab/AGImpute.

Exploring the potential of the Vanilla species from the Brazilian Atlantic Forest: Sensory description and consumer acceptance

AbstractThe present work aimed to explore, for the first time, the sensory potential of three native species of Vanilla collected in the Brazilian Atlantic Forest (V. bahiana, V. chamissonis, V. cribbiana). Ethanolic extracts of vanilla species were obtained from the ripe, enzymatically cured pods, and added to lactose‐free milk making vanilla flavored milk samples. Threshold estimation differences of “vanilla flavor,” and hedonic and sensory consumer perception of samples were evaluated. A 9‐point hedonic scale and the Rate‐All That‐Apply methodology were used for comparison to the commercial species (V. planifolia) and an artificial essence. All native species showed lower average threshold concentrations than the commercial species extract. There was no significant difference in the perception of “vanilla aroma” between V. cribbiana and the commercial species, and neither V. cribbiana nor V. chamissonis showed significant difference to the artificial essence or V. planifolia extract for “sweet taste.” Among the evaluated species, V. cribbiana seemed to show the greatest potential for market success.Practical ApplicationsThe species of Vanilla sp. explored in this work have already been chemically evaluated and presented the components related to the vanilla flavor. However, the mere presence of chemical compounds does not guarantee aroma perception. Their relative concentrations, among other factors that are difficult to determine chemically, are indispensable for generating an agreeable flavor. The only reliable way to determine the acceptability of the flavor is through sensory analysis, applied in this work to prove the commercial potential of native species. Vanilla species native to the Atlantic Forest showed the sensory potential to be used as substitutes for commercial species and to be applied in the genetic improvement of varieties. These native species may be introduced to “gourmet” consumers as vanilla flavors with different nuances. Their production may favor the areas where they are cultivated, bringing economic development to the population, and helping to maintain the forest areas.