Measurement Bias Research Articles

Unbiased Method to Determine Articular Cartilage Thickness Using a Three-Dimensional Model Derived from Laser Scanning: Demonstration on the Distal Femur

Measuring articular cartilage thickness from 3D models developed from laser scans has the potential to offer high accuracy. However, this potential has not been fulfilled, since generating these models requires that the cartilage be removed, and previous methods of removal have led to systematic errors (i.e., bias) due to changes in the overall dimensions of the underlying bone. The objectives were to present a new method for removing articular cartilage, quantify the bias error, and demonstrate the method on the distal (i.e., 0° flexion) and posterior (i.e., 90° flexion) articular surfaces of example human femurs. The method consisted of creating a 3D articular cartilage model from high-accuracy (i.e., precision = 0.087 mm) laser scans before and after cartilage removal using dermestid beetles to remove the cartilage. Fiducial markers were used to minimize errors in registering surfaces generated from the two laser scans. To demonstrate the method, the cartilage thickness was computed in distal and posterior subregions of each femoral condyle for three example cadaveric specimens. The use of dermestid beetles did not introduce measurable bias, and the previously reported precision achieved in 3D cartilage models with the laser scanner was 0.13 mm. For the different subregions, the cartilage thickness ranged from 1.5 mm to 2.0 mm. A method of imaging by means of laser scanning, cartilage removal by means of dermestid beetles, and 3D model registration by means of fiducial markers ensured that cartilage thickness on the articular surface of the long bones of the knee was determined with negligible bias and a precision of 0.13 mm. With this method, the potential to measure cartilage thickness with high accuracy based on 3D models developed from laser scans can be fully realized.

Association of optic disc drusen and small scleral canals - A systematic review and meta-analysis.

The pathophysiology of optic disc drusen (ODD) has long been discussed. According to one leading theory, they develop from calcified mitochondria extruded from axons compressed by an unusually small scleral canal. To examine this hypothesis, we conducted a systematic review and meta-analysis evaluating the scleral canal size in patients with ODD (PO) in comparison to healthy subjects (HS). We searched MEDLINE, Cochrane Central, EMBASE and gray literature to identify relevant articles. A subgroup analysis compared patients with buried ODD (POb) and patients with visible ODD (POv). The study was registered with the International Prospective Register of Systematic Reviews on December 9th, 2022 (Registration: CRD42022375110). We included fifteen articles in the review and fourteen in the meta-analysis. The mean diameter of the scleral canal computed using both fundus photography (DF) and spectral-domain with enhanced depth imaging optical coherence tomography (DO-EDI) was significantly smaller in PO compared to HS (standardized mean difference -1.21 [-1.85 to -0.56] and -0.66 [-0.94 to -0.37] respectively). DO-EDI, but not DF, was higher in POv as compared to POb. When including all-generation OCT in the analysis, the difference between POv and POb, but not between PO and HS, remained. Several intertwined hypotheses can explain these subgroup and sensitivity results: an enlargement of the canal as the ODD grow, an enlargement with time, or a measurement bias (artefactual enlargement of the canal due to a posterior shadow on OCT). In conclusion, this review and meta-analysis further supports the role of a small scleral canal in the development of ODD.

Impact of Contemporary Redlining on Healthcare Disparities Among Patients with Gastrointestinal Cancer: A Mediation Analysis.

Historically, housing policies have perpetuated the marginalization and economic disinvestment of redlined neighborhoods. Residential segregation persists nowadays in the form of contemporary redlining, promoting healthcare disparities. The current study sought to assess the effect of redlining on oncological outcomes of patients with gastrointestinal cancer and identify mediators of the association. Patients with colorectal or hepatobiliary cancer were identified from the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database (2007-2019). The contemporary redlining index, a measure of mortgage lending bias, was assessed relative to disease stage at diagnosis, receipt of appropriate treatment, textbook outcome, and mortality. Mediation analysis was used to identify socioeconomic, structural, and clinical mediating factors. Among 94,988 patients, 32.2% resided in high (n = 23,872) and highest (n = 6,791) redlining census tracts compared with 46.2% in neutral and 21.6% in low redlining tracts. The proportion of Black, Hispanic, and White patients experiencing high and highest redlining was 65.9%, 41.6%, and 27.9%, respectively. Highest redlining was associated with 18.2% higher odds of advanced disease at diagnosis, greater odds of not undergoing surgery for localized disease (adjustedodds ratio [aOR] 1.363, 95% confidence interval [CI] 1.219-1.524) or not receivingchemotherapy for advanced disease (aOR 1.385, 95% CI 1.216-1.577), and 26.7% lower odds of textbook outcome achievement. Mediation analysis for appropriate treatment quantified the proportion of the association driven by socioeconomic status, racial/ethnic minority status, racial/economic segregation, primary care shortage, and housing/transportation. Contemporary redlining contributed both directly, and via downstream factors, to disparities in oncological care and outcomes of patients with gastrointestinal cancer.

Exploring the Synergistic Effects of Concurrent Exercise for Managing Type-II Diabetes Mellitus: A Meta-Analysis.

The effectiveness of concurrent exercise (CE) as an emerging approach for type-II diabetes mellitus (T2DM) patients was evaluated through a comprehensive search on Google Scholar, PubMed, Pedro, CINAHL, and Medline from 2015 to March 2023. Sixteen RCTs were selected which evaluated CE (aerobic + resistance in the same session) effects on a minimum of three days/week among T2DM patients, and the control group received usual care or no exercise. Studies that evaluated at least one glycaemic variable, i.e. HbA1C, fasting blood glucose level (FBGL), andHomeostatic Model Assessment for Insulin Resistance (HOMA-IR), were eligible. Intervention with a follow-up period of ≥8 weeks, patients of any age and gender, and literature in the English language were included. A rigorous review was performed using the Cochrane Collaboration risk of bias tool (RoB 2) to minimise biases, which include the randomisation process, deviation from intended intervention, missing outcome data, outcome measurement, and selection bias. CE significantly improved HbA1C (95% CI of -0.654 to 0.363, I2 = 84.92% moderate heterogeneity), FBGL (95% CI of -0.239 to 1.145, I2 = 93.74% - high level of heterogeneity), and insulin resistance (HOMA-IR) (95% CI of -0.593 to 0.544, I2 = 92.85% - high level of heterogeneity). Collectively, findings indicate the potential of CE as an intervention to impact glycaemic control in T2DM patients positively. However, the relatively high I² values suggest notable variability among studies, and further research to explore the factors contributing to this heterogeneity, exercise protocol along with progression, and duration of diabetes are needed, which is more challenging to determine a precise dose-response relationship. Therefore, more studies are required to provide thorough insights into these components for T2DM management. Key Words: Glycated haemoglobin, Glycaemic control, Insulin resistance, Physical exercise, Type-II diabetes mellitus.

From prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers

ObjectivesRoutine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.Methods and analysisWe used retrospective data from three UK hospitals to develop and validate ML models predicting unacceptable rises in creatinine/bilirubin post cycle 3 for patients undergoing treatment for the following cancers: breast, colorectal, lung, ovarian and diffuse large B-cell lymphoma.ResultsWe extracted 3614 patients with no missing blood test data across cycles 1–6 of chemotherapy treatment. We improved on previous work by including predictions post cycle 3. Optimised for sensitivity, we achieve F2 scores of 0.7773 (bilirubin) and 0.6893 (creatinine) on unseen data. Performance is consistent on tumour types unseen during training (F2 bilirubin: 0.7423, F2 creatinine: 0.6820).ConclusionOur technique highlights the effectiveness of ML in clinical settings, demonstrating the potential to improve the delivery of care. Notably, our ML models can generalise to unseen tumour types. We propose gold-standard bias mitigation steps for ML models: evaluation on multisite data, thorough patient population analysis, and both formalised bias measures and model performance comparisons on patient subgroups. We demonstrate that data aggregation techniques have unintended consequences on model bias.

Automated speech recognition bias in personnel selection: The case of automatically scored job interviews.

Organizations, researchers, and software increasingly use automatic speech recognition (ASR) to transcribe speech to text. However, ASR can be less accurate for (i.e., biased against) certain demographic subgroups. This is concerning, given that the machine-learning (ML) models used to automatically score video interviews use ASR transcriptions of interviewee responses as inputs. To address these concerns, we investigate the extent of ASR bias and its effects in automatically scored interviews. Specifically, we compare the accuracy of ASR transcription for English as a second language (ESL) versus non-ESL interviewees, people of color (and Black interviewees separately) versus White interviewees, and male versus female interviewees. Then, we test whether ASR bias causes bias in ML model scores-both in terms of differential convergent correlations (i.e., subgroup differences in correlations between observed and ML scores) and differential means (i.e., shifts in subgroup differences from observed to ML scores). To do so, we apply one human and four ASR transcription methods to two samples of mock video interviews (Ns = 1,014 and 414), and then we train and test models using these different transcripts to score multiple constructs. We observed significant bias in the commercial ASR services across nearly all comparisons, with the magnitude of bias differing across the ASR services. However, the transcription bias did not translate into meaningful measurement bias for the ML interview scores-whether in terms of differential convergent correlations or means. We discuss what these results mean for the nature of bias, fairness, and validity of ML models for scoring verbal open-ended responses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring and closing the energy balance of eddy covariance measurements along a land use gradient in the West African Sudanian savanna

A good understanding of land-atmosphere exchange processes is essential for developing sustainable land management practices in Africa, in order to enhance food security and strengthen the resilience against climate change and extremes in this vulnerable region. In this study, we explore the energy balance closure (EBC) of three eddy covariance (EC) sites implemented along a land use gradient (pristine savanna forest, cropland, and degraded grassland) in the Sudanian savanna of West Africa. Our results show that the EBC strongly varies over the monsoon season and the EC sites. However, the best EBC is observed at the pristine site, which has the most homogenous vegetation. Thus, landscape heterogeneity seems to play an important role in the quality of the EC measurements. Moreover, we develop a novel post-closure method based on a quantile-mapping technique conditioned on monsoonal circulation patterns specifically determined for the West African Monsoon. This method is also compared to two well-established methods, the Bowen-ratio (BR) correction and a pure quantile-mapping using various bias measures. Our results show that the novel post-closure method outperforms the other methods and, therefore, leads to better elimination of the underestimation of the turbulent fluxes at the three savanna sites. In addition, specific characteristics of turbulent fluxes, like their strong diurnal cycle, are well represented by the new correction method.

Cultural Perceptions of Language Development in a Population Sample of 54-Month-Old Children From Aotearoa New Zealand.

There is a dearth of information on cultural perceptions of children's language development for ethnic minorities in New Zealand to guide service provision. The current study explored differences across ethnicities in mothers' report of language concern and child language scores within a complex cultural, social, educational, and political context. Data from the antenatal and 54-month waves of Growing Up in New Zealand were utilized. At the 54-month wave interviews, 5,053 mothers were asked if language concerns had been raised and to rate their child's main language proficiency along with other measures. Logistic regression models (including influencing variables) indicated Chinese, Indian, and other Asian mothers were less likely to report language concern, whereas Māori, Pacific, other Asian, and Middle Eastern, Latin American, and African children were more likely to score low on the language measure. Higher maternal education was associated with higher child main language scores, but not with language concerns. Child multilingualism was not associated with low language scores, and these mothers were less likely to raise concern. This study demonstrated differences by ethnicity in mothers' language concern and child main language scores, which are likely to affect access to speech-language pathology services, as these typically rely on parent concern being expressed. Cultural bias in the language measure may also be present. Further research is needed to ask ethnic communities their views on culturally appropriate ways to identify children with communication needs and to develop culturally safe services.

Cosmology with shear ratios: a joint study of weak lensing and spectroscopic redshift datasets

The ratio of the average tangential shear signal of different weak lensing source populations around the same lens galaxies, also known as a shear ratio, provides an important test of lensing systematics and a potential source of cosmological information. In this paper we measure shear ratios of three current weak lensing surveys –KiDS, DES, and HSC– using overlapping data from the Baryon Oscillation Spectroscopic Survey. We apply a Bayesian method to reduce bias in shear ratio measurement, and assess the degree to which shear ratio information improves the determination of important astrophysical parameters describing the source redshift distributions and intrinsic galaxy alignments, as well as cosmological parameters, in comparison with cosmic shear and full 3x2-pt correlations (cosmic shear, galaxy-galaxy lensing, and galaxy clustering). We consider both Fisher matrix forecasts, as well as full likelihood analyses of the data. We find that the addition of shear ratio information to cosmic shear allows the mean redshifts of the source samples and intrinsic alignment parameters to be determined significantly more accurately. Although the additional constraining power enabled by the shear ratio is less than that obtained by introducing an accurate prior in the mean source redshift using photometric redshift calibration, the shear ratio allows for a useful cross-check. The inclusion of shear ratio data consistently benefits the determination of cosmological parameters such as S_8, for which we obtain improvements up to 34%. However these improvements are less significant when shear ratio is combined with the full 3x2-pt correlations. We conclude that shear ratio tests will remain a useful source of cosmological information and cross-checks for lensing systematics, whose application will be further enhanced by upcoming datasets such as the Dark Energy Spectroscopic Instrument.

Examining the local Universe isotropy with galaxy cluster velocity dispersion scaling relations

In standard cosmology, the Universe is assumed to be statistically homogeneous and isotropic. This assumption suggests that the expansion rate of the Universe, as measured by the Hubble parameter, should be the same in all directions. However, our recent study based on galaxy clusters finds an apparent angular variation of approximately $9<!PCT!>$ in the Hubble constant, $H_0$, across the sky. In the study, the authors utilised galaxy cluster scaling relations between various cosmology-dependent cluster properties and a cosmology-independent property, i.e. the temperature of the intracluster gas ($T$). A position-dependent systematic bias of $T$ measurements can, in principle, result in an overestimation of apparent $H_0$ variations. Therefore, it is crucial to confirm or exclude this possibility. In this work, we search for directional $T$ measurement biases by examining the relationship between the member galaxy velocity dispersion and gas temperature ($ v -T$) of galaxy clusters. Both measurements are independent of any cosmological assumptions and do not suffer from the same potential systematic biases. Additionally, we search for apparent $H_0$ angular variations independently of $T$ by analysing the relations between the X-ray luminosity and Sunyaev-Zeldovich signal with the velocity dispersion, $L_ X v $ and $Y_ SZ v To study the angular variation of scaling relation parameters, we determined the latter for different sky patches across the extra-galactic sky. We constrained the possible directional $T$ bias using the $ v -T$ relation, as well as the apparent $H_0$ variations using the $L_ X v $ and $Y_ SZ v $ relations. We utilised Monte Carlo simulations of isotropic cluster samples to quantify the statistical significance of any observed anisotropies. We calculated and rigorously took into account a correlation of $L_ X $ and $Y_ SZ $ residuals. No significant directional $T$ measurement biases are found from the $ v -T$ anisotropy study. The probability that the previously observed $H_0$ anisotropy is caused by a directional $T$ bias is only $0.002<!PCT!>$. On the other hand, from the joint analysis of the $L_ X v $ and $Y_ SZ v $ relations, the maximum variation of $H_0$ is found in the direction of $(295^ with a statistical significance of $3.64 fully consistent with our previous results. Our findings, based on the analysis of new scaling relations utilising a completely independent cluster property, $ v $, strongly corroborate the previously detected anisotropy of galaxy cluster scaling relations. The underlying cause, for example, $H_0$ angular variation or large-scale bulk flows of matter, remains to be identified.

Inter-Vendor differences in speckle tracking strain - A ten year follow-up on the Strain Standardization Task Force Inter-Vendor Comparison Study

Abstract Background Global longitudinal strain (GLS) derived from two-dimensional speckle-tracking echocardiography is feasible and accurate. Nonetheless, in 2013, the Inter-Vendor Comparison Study showed significant differences of measurement results among vendors. In order to make tracking-based strain imaging a clinically accepted and useful parameter, it is of outmost importance to have interchangeable and accurate measurement results from all vendors. Purpose To investigate if the efforts of the EACVI/ASE/Industry Task Force to Standardize Deformation Imaging have led to a reduction of inter-vendor differences during the past ten years. Methods In an unique setting, in one single room, 372 echocardiographic examinations were performed in sixty-two subjects (50 male, age 56.1 ± 16.98) with a wide range of left ventricular (LV) function (ejection fraction from 30% to 64%) using ultrasound systems from six manufacturers. Each subject was scanned consecutively on all machines by the same assigned experienced sonographer. For each subject two image sets of LV apical views were acquired in order to assess reproducibility in a true test-retest setting. We assessed mean GLS (GLSAV) as average peak systolic global strain from the three apical views on five vendor-specific and five vendor-independent software solutions. We measured endocardial and mid-/full-wall GLS. Since there is no gold standard method to measure GLS, we compared GLSAV of each vendor to the average of the GLS values only from vendors that provide tracking software solutions (SWS) for clinical use. Results For both endocardial (Figure 1) and mid-/full-wall (Figure 2) GLS measurements from clinical SWS were comparable and within a very narrow range (mean GLS of vendors 17.25 ± 0.3% and 15.36 ± 0.3% respectively). The maximum absolute difference between all SWS was 4.1% and 4.9% strain units for endocardial and mid-/full-wall GLS respectively. GLSAV of each software versus the mean of clinical SWS showed significant correlation for most of the companies (r² >0.8, p<0.001). Test-retest variability of GLS measurements expressed as relative mean error was good and lower than for LV ejection fraction (6.3% on average for mean GLS and 7% for LV ejection fraction, p>0.05). Conclusions Our data show a substantial inter-vendor bias in GLS measurements. Nevertheless, in contrast to the situation ten years ago, companies that provide tracking software solutions for clinical use provide now very similar GLS values. In addition, most companies do now allow mid-/full-wall tracking. Our data indicate that the efforts of the strain standardization task force have been fruitful. A continuing effort is needed until all software providers adhere to the task force consensus recommendations.Figure 1Figure 2

Combining fractional flow reserve and the index of microcirculatory resistance for prognosis prediction in renal artery stenosis interventions: a feasibility sub-study of FAIR-pilot trial

Abstract Background Interventional therapies for renal artery stenosis (RAS) was debatable in previous randomized trials. Fractional flow reserve (FFR), while useful in coronary interventions, does not assess microcirculatory status, which may be critical in RAS. The index of microcirculatory resistance (IMR) provides additional microvascular information, which has not been used in RAS patients. Purpose To investigate the feasibility of IMR measurement in RAS patients and the association with the outcome. Methods FAIR-pilot study is a multicenter pilot randomized controlled trial exploring the application of FFR to guide the renal artery stenting in patients with renovascular hypertension (NCT05732077). A pressure-temperature sensor guidewire was used to measure the IMR. To derive mean transit time at rest, thermodilution curves were obtained by 3 injections of 4 mL of room temperature saline down the renal artery. Hyperemia was induced using dopamine 50μg/kg bolus to the renal artery. The IMR was calculated as distal arterial pressure (Pd) x mean transit time during hyperemia (TmnH) (Figure 1). Prognostic evaluation was based on improvements in postoperative blood pressure, which was assessed using both ambulatory blood pressure monitor (ABPM) and anti-hypertensive medication number, along with renal function, as determined by the estimated glomerular filtration rate (eGFR). Results The IMR was measured among five patients enrolled in FAIR-pilot study. As shown in Table 1 and 2, stent implantation was conducted on five lesions across patients 1 to 4 based on renal FFR < 0.8, with each experiencing varying degrees of improved blood pressure control subsequently. Patient 5 did not receive a stent and was lost to follow-up. At three-month, the recorded decrease in systolic blood pressure ranged from a maximum of 34 mmHg to a minimum decrease of -6 mmHg among the four patients. The antihypertensive medication number showed a maximum reduction of 2 and no change as the minimum. We observed a correlation between baseline IMR and baseline renal function. No significant change in IMR was noted after interventional procedures. Preliminary findings suggest that IMR measurement is feasible in patients with RAS, while the ∆T (temperature change time) was very small, which potentially increasing the measurement bias. Conclusion The study suggests measuring IMR in patients with RAS is feasible and can offer information into the renal microvasculature. However, the small ∆T encountered during measurement may introduce increased bias, which should be considered when interpreting results.

The Export Dilemma of China under the WTO Framework: An Anti-Dumping Study on the Determination of Market Economy Status

As China emerges as a dominant force in the global economy, the issue of non-market economy status has become a key issue, particularly in the face of biased anti-dumping measures enforced by other nations. These measures have seriously affected China's export-oriented economy by creating substantial trade barriers. The essay utilizes a blend of literature review, comparative analysis, and data examination, drawing on historical experience and the legal principles and rules as outlined in the WTO agreements. The results show that although China has achieved certain advancements in pursuing acknowledgment of its market economy status, it still faces significant challenges due to political and economic factors.This essay will discuss anti-dumping measures exert considerable pressure on businesses operating within developing economies, and on this basis, it will provide corresponding thoughts and suggestions for China to secure the market economy status, and for Chinese enterprises not to be hit by it as far as possible.

Systematic Review of Associations between Anxiety, Depression, and Functional/Biological aging among Cancer Survivors.

Evidence suggests a mind-body component to aging, through which psychological distress from anxiety and depression drives molecular changes that promote early decline (ie, accelerated aging). Cancer survivors experience particularly high rates of anxiety and depression. Some survivors also have accelerated aging, though the relationships between anxiety/depression and aging are not clear. A synthesis of evidence is needed to understand the state of the science and impending priorities. PubMed, Embase, CINAHL, Web of Science, and PsycNet databases were searched for studies that measured associations between depression, anxiety, and non-chronological aging in cancer survivors (2012 to 2022). Data were methodologically evaluated. Survivorship studies were included if they were peer-reviewed, published in English from 2012-2022, and measured associations between anxiety/depression and aging. 51 studies were included. Just over half were cross-sectional (53%). Foci included functional (n = 35, 69%) and biological (n = 16, 31%). Functional aging measures included frailty, sarcopenia, geriatric assessment, and cognition. Biological aging measures included telomere length, telomerase, age-related inflammatory blood-based biomarkers, renal insufficiency, anemia, and DNA methylation. 223 associations were tested. Associations between anxiety, depression and aging were generally positive, though with varying strengths. Most compelling were associations between functional aging-depression. There were concerns for selection and measurement biases. Findings suggest positive associations between anxiety, depression and aging among cancer survivors. Future work is needed to clarify temporality, develop a consensus on the operationalization of aging, and diversify cohorts.

Analyzing Potential Non-Ignorable Selection Bias in an Off-Wave Mail Survey Implemented in a Long-Standing Panel Study

Abstract Typical design-based methods for weighting probability samples rely on several assumptions, including the random selection of sampled units according to known probabilities of selection and ignorable unit nonresponse. If any of these assumptions are not met, weighting methods that account for the probabilities of selection, nonresponse, and calibration may not fully account for the potential selection bias in a given sample, which could produce misleading population estimates. This analysis investigates possible selection bias in the 2019 Health Survey Mailer (HSM), a sub-study of the longitudinal Health and Retirement Study (HRS). The primary HRS data collection has occurred in “even” years since 1992, but additional survey data collections take place in the “off-wave” odd years via mailed invitations sent to selected participants. While the HSM achieved a high response rate (83 percent), the assumption of ignorable probability-based selection of HRS panel members may not hold due to the eligibility criteria that were imposed. To investigate this possible non-ignorable selection bias, our analysis utilizes a novel analysis method for estimating measures of unadjusted bias for proportions (MUBP), introduced by Andridge et al. in 2019. This method incorporates aggregate information from the larger HRS target population, including means, variances, and covariances for key covariates related to the HSM variables, to inform estimates of proportions. We explore potential non-ignorable selection bias by comparing proportions calculated from the HSM under three conditions: ignoring HRS weights, weighting based on the usual design-based approach for HRS “off-wave” mail surveys, and using the MUBP adjustment. We find examples of differences between the weighted and MUBP-adjusted estimates in four out of ten outcomes we analyzed. However, these differences are modest, and while this result gives some evidence of non-ignorable selection bias, typical design-based weighting methods are sufficient for correcting for it and their use is appropriate in this case.

Tunable Ambipolar Transport in a 2D Kagome Semiconductor

AbstractThe interference of electronic wavefunctions within a Kagome lattice can result in a flat band structure, where low‐energy electrons exhibit highly correlated behavior, facilitating exploration of interactions among intriguing electronic states. However, the inherent high carrier density in most known Kagome materials often hampers the manipulation of these quantum phenomena through conventional means, such as gate voltage. In this work, a unique tunability in the electrical and optoelectronic properties of exfoliated Nb3I8, a 2D semiconductor featuring a “breathing” Kagome lattice is uncovered. Characterization via temperature‐dependent ARPES confirms its semiconducting nature with a flat band structure. Experimental results from bias and gate voltage dependent transport measurements on thin film Nb3I8 transistor devices demonstrate ambipolar conductance. Notably, these findings reveal a broadband photoresponse in the device, spanning from visible to near infrared wavelengths (532 −1100 nm), with the photocurrent showing gate‐dependent characteristics that mirror the dark current's ambipolar nature. This observation marks the first instance of ambipolar transport in a Kagome semiconductor, opening up exciting new avenues for electronic and optoelectronic device development.

Economic policy uncertainty and dividend policy: Insight from private firms

This study examines whether economic policy uncertainty (EPU) is associated with corporate dividend policy. Using a sample of private firms, we find that EPU is negatively related to dividend payouts. Our main findings are robust to endogeneity concerns, omitted variable problems, simultaneity bias, and alternative measures of EPU. Further, we find that firms are less likely to pay dividends when EPU is higher, confirming our main results. We also find that the negative relation between EPU and dividend payouts is stronger for firms with higher leverage, operating cash flows, sales growth, return on assets, and cash flow volatility than their counterparts. In contrast, the negative relation is weaker for firms with higher retained earnings-to-total equity ratios. Our study highlights that issues such as EPU can influence the dividend payout policies of private firms.

The impact of rural health insurance on vulnerability to chronic poverty among rural residents in China: analysis using Probit and IVprobit models.

Poverty is a global problem, and combating it is a major governance issue worldwide. In China, poverty management efforts have shifted from eliminating absolute poverty to managing relative poverty. One of the most important tasks in managing relative poverty in the post-poverty reduction era is to prevent recurring poverty due to illness. Rural health insurance is an important method of preventing and mitigating disease risk and a key part of China's poverty reduction policy, including among rural residents. However, the mechanism by which basic health insurance alleviates vulnerability to poverty, the causal effect of rural health insurance on vulnerability to poverty, and differences based on having a second health insurance policy and by age and income have not been sufficiently explored. Therefore, this study examined the impact of rural health insurance on vulnerability to long-term poverty among rural residents in China. In addition, this study evaluated the impact of having a second health insurance policy and differences in the effects of rural health insurance by age and income. This study used data from the 2014, 2016, 2018, and 2020 China Family Panel Studies. Household-related characteristics, such as finance, education, and healthcare, were retrieved from the household database; while data on healthcare expenditures, healthcare insurance, and personal-related characteristics were retrieved from the adult database. Robustness tests were conducted with Probit models, and endogeneity tests were conducted with IVprobit models. Vulnerability to poverty was significantly lower among residents with rural health insurance than those without any health insurance coverage, and this difference was observed across age and income groups. These findings were consistently robust and significant after controlling for endogeneity, considering sample selectivity, and eliminating measurement bias in the core variables. The findings indicate that rural health insurance is an important tool for poverty alleviation. The current results could effectively reduce the economic vulnerability of rural households facing health risks, ensuring broader economic security. Moreover, these findings provide policy references for managing relative poverty in China.

The only constant is change: Stable vs. variable aspects of food approach bias relate differently to food craving and intake

The tendency to approach food faster than to avoid it (i.e., approach bias) is thought to facilitate food intake, particularly foods that conflict with one's dietary goals. However, this relationship has been difficult to demonstrate, which ties into an ongoing debate about whether such cognitive-behavioral biases represent stable traits or fluctuating states. We thus investigated the temporal fluctuations of food approach bias (1), its within-participant association with food craving (2) and intake (3), and the role of top-down control in this bias-intake association (4). The 76 participants completed an impulsivity questionnaire and performed a smartphone-based approach-avoidance task on nine days. Every day, they also reported their daily craving, intake, and dietary intentions for 12 personalized foods they wanted to eat less or more often over the study period. Approach bias varied considerably within individuals (1), and correlated in unexpected ways with food craving (2) and intake (3); this association of approach bias with intake was moderated by inter-individual differences (rather than day-to-day fluctuations) in dietary intentions and impulsivity (4). Results emphasize the need to re-conceptualize approach bias as comprising both state and trait components, and indicate that the more trait-like aspects of top-down control gate the relationship of approach bias with intake. The large day-to-day variation in approach bias may explain why single-session bias measures often do not predict distal outcomes like body weight. Furthermore, our results suggest that interventions targeting approach bias may be most effective for certain timepoints (high-risk situations) and individuals (those with weak dietary intentions).

Environmental Attitudes, Concerns, and Behaviors Across Survey Modes. Assessing Selection and Measurement Biases in ISSP 2020 ‘Push-to-Web’ Surveys

How much does survey mode matter for predicting environmental attitudes and behaviors? It is essential to consider the influence of survey mode on the measurement of variables, particularly given the increasing popularity of web-based data collection following the Covid crisis. In 2020, several ISSP countries adopted a mixed-mode design, combining web and paper surveys for the Environment IV module. While mixed-mode data collection can reduce mode-specific errors, its success depends on accurately estimating and adjusting for selection and measurement differences between the modes. Failing to do so can increase the Total Survey Error, compromising the accuracy and reliability of the data. In this article, we examine selection and measurement differences in the web and paper modes in the Environment IV data from Switzerland and Finland. Register data are used as a benchmark to estimate selection biases in key socio-demographic variables, and we use these estimates to disentangle mode measurement effects from other sources of error. While we find that age, education, and labor market status account for selection effects across modes, we do not find significant differences in the measurement of environmental attitudes and behaviors across modes once the selection effect is controlled for. Mixing online and paper modes should thus not compromise data quality by introducing measurement biases for environmental variables.