The analysis of data from experiments in economics routinely involves testing multiple null hypotheses simultaneously. These different null hypotheses arise naturally in this setting for at least three different reasons: when there are multiple outcomes of interest and it is desired to determine on which of these outcomes a treatment has an effect; when the effect of a treatment may be heterogeneous in that it varies across subgroups defined by observed characteristics and it is desired to determine for which of these subgroups a treatment has an effect; and finally when there are multiple treatments of interest and it is desired to determine which treatments have an effect relative to either the control or relative to each of the other treatments. In this paper, we provide a bootstrap-based procedure for testing these null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. Using the general results in Romano and Wolf (Ann Stat 38:598–633, 2010), we show under weak assumptions that our procedure (1) asymptotically controls the familywise error rate—the probability of one or more false rejections—and (2) is asymptotically balanced in that the marginal probability of rejecting any true null hypothesis is approximately equal in large samples. Importantly, by incorporating information about dependence ignored in classical multiple testing procedures, such as the Bonferroni and Holm corrections, our procedure has much greater ability to detect truly false null hypotheses. In the presence of multiple treatments, we additionally show how to exploit logical restrictions across null hypotheses to further improve power. We illustrate our methodology by revisiting the study by Karlan and List (Am Econ Rev 97(5):1774–1793, 2007) of why people give to charitable causes.

The recent expansion of cross-cultural research in the social sciences has led to increased discourse on methodological issues involved when studying culturally diverse populations. However, discussions have largely overlooked the challenges of construct validity- ensuring instruments are measuring what they are intended to- in diverse cultural contexts, particularly in developmental research. We contend that cross-cultural developmental research poses distinct problems for ensuring high construct validity, owing to the nuances of working with children and that the standard approach of transporting protocols designed and validated in one population to another risks low construct validity. Drawing upon our own and others’ work, we highlight several challenges to construct validity in the field of cross-cultural developmental research, including 1) lack of cultural and contextual knowledge, 2) dissociating developmental and cultural theory and methods, 3) lack of causal frameworks, 4) superficial and short- term partnerships and collaborations, and 5) culturally inappropriate tools and tests. We provide guidelines to address these challenges, including 1) using ethnographic and observational approaches, 2) developing evidence-based causal frameworks, 3) conducting community-engaged and collaborative research, and 4) culture-specific refinements and training. We discuss the need to balance methodological consistency with culture-specific refinements to improve construct validity in cross-cultural developmental research.

(Poly)phenol intake has been associated with reduced risk of non-communicable diseases in epidemiological studies1,2. However, there are no dietary assessment tools that have been developed to estimate (poly)phenol intake in the UK. This study aimed to develop a novel food frequency questionnaire (FFQ) to capture dietary (poly)phenol intake in the UK and assess its relative validity by comparison with 7-day diet diaries (7DD) and plasma and urine (poly)phenols metabolites.

The (poly)phenol FFQ was developed based on the EPIC-Norfolk FFQ validated for energy and nutrient intake estimation in the UK population3,4. Food items added to the FFQ based on total (poly)phenols content (≥ 1 mg/serving) and UK consumption. Participants aged 18 ∼ 29 years (n=255) completed the EPIC-Norfolk FFQ and a (poly)phenol FFQ. In a subgroup (n=60), 7DD, spot urine, and fasting plasma samples were collected. An in-house (poly)phenol database was used to estimate (poly)phenol intake from FFQs and 7DD. Plasma and urinary (poly)phenol metabolite levels were analysed using a validated LC-MS method5. The agreements between (poly)phenol intake estimated using the (poly)phenol and EPIC-Norfolk FFQ and 7DDs, as well as plasma and urinary biomarkers, were evaluated by intraclass correlation coefficients (ICC), weighted kappa, quartile classification, and Spearman correlations, and the associations were investigated using linear regression models adjusting for energy intake and multiple testing (FDR < 0.05).

Strong agreements were observed between hydroxycinnamic acids estimated from (poly)phenol FFQ and 7DDs (kappa=0.75), fair agreements were found between 9 (poly)phenol groups, including total (poly)phenol intake (kappa=0.41), while the agreements for the rest of 17 classes and subclasses of (poly)phenols were poor (kappa: 0.07 ∼ 0.39). Strong positive associations were found in 9 (poly)phenols estimated from 7DDs, including dihydroflavonols, flavones, ellagitannins, hydroxyphenylacetic acids, total stilbenes, resveratrol, total other (poly)phenols, tyrosols, and alkylphenols with stdBeta from 0.62 (95% CI: 0.42 ∼ 0.82) to 0.95 (0.86 ∼ 1.00) (FDR p < 0.05). (Poly)phenol FFQs estimated (poly)phenol intake exhibited positive associations with 99 urinary metabolites (stdBeta: 0.27 (0.06 ∼ 0.48) to 0.88 (0.72 ∼ 1.03)) and 25 plasma metabolites (stdBeta:

0.39 (0.17 ∼ 0.62) to 0.83 (0.64 ∼ 1.02)) (FDR p < 0.05). The agreement between (poly)phenol FFQs and the EPIC-Norfolk FFQs was moderate (ICC 0.51 ∼ 0.69) for all (poly)phenol intake after adjusting for energy intake. Compared with the EPIC-Norfolk FFQs estimated (poly)phenol intake, stronger and more agreements and associations were found in (poly)phenol FFQs estimated (poly)phenol with 7DDs and biomarkers.

(Poly)phenols estimated from (poly)phenol FFQ exhibited fair agreements and moderate to strong associations with 7DDs and biomarkers in the target population, indicating the novel questionnaire may be a promising tool to assess (poly)phenol intake. A representative UK population group is warranted for to test the further usability.

Prior to the No Surprises Act (NSA), numerous states passed laws protecting patients from surprise medical bills from out-of-network (OON) hospital-based physicians supporting elective treatment in in-network hospitals. Even in non-emergency situations, patients have little ability to choose physicians such as anaesthesiologists, pathologists or radiologists. Using a comprehensive, multi-payer claims database, we estimated the effect of these laws on hospital-based physician reimbursement, charges, network participation and potential surprise billing episodes. Overall, the state laws were associated with a reduction in anaesthesiology prices and charges, but an increase in pathology and radiology prices. The price effects for each state exhibit substantial heterogeneity. California and New Jersey experienced increases in network participation by anaesthesiologists and pathologists and reductions in potential surprise billing episodes, but, overall, we find little evidence of changes in network participation across all of the states implementing surprise billing laws. Our results suggest that the effects of the NSA may vary across states.

Archaeological sites in Northwest Africa are rich in human fossils and artefacts providing proxies for behavioural and evolutionary studies. However, these records are difficult to underpin on a precise chronology, which can prevent robust assessments of the drivers of cultural/behavioural transitions. Past investigations have revealed that numerous volcanic ash (tephra) layers are interbedded within the Palaeolithic sequences and likely originate from large volcanic eruptions in the North Atlantic (e.g. the Azores, Canary Islands, Cape Verde). Critically, these ash layers offer a unique opportunity to provide new relative and absolute dating constraints (via tephrochronology) to synchronise key archaeological and palaeoenvironmental records in this region. Here, we provide an overview of the known eruptive histories of the potential source volcanoes capable of widespread ashfall in the region during the last ~300,000 years, and discuss the diagnostic glass compositions essential for robust tephra correlations. To investigate the eruption source parameters and weather patterns required for ash dispersal towards NW Africa, we simulate plausible ashfall distributions using the Ash3D model. This work constitutes the first step in developing a more robust tephrostratigraphic framework for distal ash layers in NW Africa and highlights how tephrochronology may be used to reliably synchronise and date key climatic and cultural transitions during the Palaeolithic.

We investigate self-excited axisymmetric oscillations of a lean premixed methane–air V-flame in a laminar annular jet. The flame is anchored near the rim of the centrebody, forming an inverted cone, while the strongest vorticity is concentrated along the outer shear layer of the annular jet. Consequently, the reaction and vorticity dynamics are largely separated, except where they coalesce near the flame tip. The global eigenmodes corresponding to the linearised reacting flow equations around the steady base state are computed in an axisymmetric setting. We identify an arc branch of eigenmodes exhibiting strong oscillations at the flame tip. The associated eigenvalues are robust with respect to domain truncation and numerical discretisation, and they become destabilised as the Reynolds number increases. The frequency of the leading eigenmode is found to correspond to the Lagrangian disturbance advection time from the nozzle outlet to the flame tip. The essential role of this convective mechanism is also supported by resolvent analysis, which finds that the same flame-tip disturbance structure and frequency are optimally amplified when the flame is subjected to external white noise forcing. Strong non-modal effects in the form of pseudo-resonance are not found. Nonlinear time-resolved simulation further reveals notable hysteresis phenomena in the subcritical regime prior to instability. Hence, even when the flame is linearly stable, perturbations of sufficient amplitude can trigger limit-cycle oscillations and higher-dimensional dynamics sustained by nonlinear feedback. A Monte Carlo simulation of passive tracers in the unsteady flame suggests a nonlinear non-local instability mechanism. Notably, linear analysis of the subcritical time-averaged limit-cycle state yields eigenvalues that do not match the nonlinear periodic oscillation frequencies. This mismatch is attributed to the fundamentally nonlinear dynamics of the subcritical V-flame instability, where the dichromatic, non-local interaction between the heat release rate along the flame surface and the vortex dynamics in the jet shear layer cannot be approximated as a simple distortion of the mean flow.

The importance of automating pavement maintenance tasks for highway systems has garnered interest from both industry and academia. Despite significant research efforts and promising demonstrations being devoted to reaching a level of semi-automation featuring digital sensing and inspection, site maintenance work still requires manual processes using special vehicles and equipment, reflecting a clear gap to transition to fully autonomous maintenance. This paper reviews the current progress in pavement maintenance automation in terms of inspection and repair operations, followed by a discussion of three key technical challenges related to robotic sensing, control, and actuation. To address these challenges, we propose a conceptual solution we term Autonomous Maintenance Plant (AMP), mainly consisting of five modules for sensing, actuation, control, power supply, and mobility. This AMP concept is part of the “Digital Roads” project’s cyber-physical platform where a road digital twin (DT) is created based on its physical counterpart to enable real-time condition monitoring, sensory data processing, maintenance decision making, and repair operation execution. In this platform, the AMP conducts high-resolution survey and autonomous repair operations enabled (instructed) by the road DT. This process is unmanned and completely autonomous with an expectation to create a fully robotized highway pavement maintenance system.

Previous animal studies found beneficial effects of choline and betaine on maternal glucose metabolism during pregnancy, but few human studies explored the association between choline or betaine intake and incident gestational diabetes mellitus (GDM). We aimed to explore the correlation of dietary choline or betaine intake with GDM risk among Chinese pregnant women. A total of 168 pregnant women with GDM cases and 375 healthy controls were enrolled at the Seventh People’s Hospital in Shanghai during their GDM screening at 24–28 gestational weeks. A validated semi-quantitative FFQ was used to estimate choline and betaine consumption through face-to-face interviews. An unconditional logistic regression model was adopted to examine OR and 95 % CI. Compared with the controls, those women with GDM incidence were likely to have higher pre-pregnancy BMI, be older, have more parities and have higher plasma TAG and lower plasma HDL-cholesterol. No significant correlation was observed between the consumption of choline or betaine and incident GDM (adjusted OR (95 % CI), 0·77 (0·41, 1·43) for choline; 0·80 (0·42, 1·52) for betaine). However, there was a significant interaction between betaine intake and parity on the risk of GDM (Pfor interaction = 0·01). Among those women with no parity history, there was a significantly inverse correlation between betaine intake and GDM risk (adjusted OR (95 % CI), 0·25 (0·06, 0·81)). These findings indicated that higher dietary betaine intake during pregnancy might be considered a protective factor for GDM among Chinese women with no parity history.

In this study, we analyse ‘magneto-Stokes’ flow, a fundamental magnetohydrodynamic (MHD) flow that shares the cylindrical-annular geometry of the Taylor–Couette cell but uses applied electromagnetic forces to circulate a free-surface layer of electrolyte at low Reynolds numbers. The first complete, analytical solution for time-dependent magneto-Stokes flow is presented and validated with coupled laboratory and numerical experiments. Three regimes are distinguished (shallow-layer, transitional and deep-layer flow regimes), and their influence on the efficiency of microscale mixing is clarified. The solution in the shallow-layer limit belongs to a newly identified class of MHD potential flows, and thus induces mixing without the aid of axial vorticity. We show that these shallow-layer magneto-Stokes flows can still augment mixing in distinct Taylor dispersion and advection-dominated mixing regimes. The existence of enhanced mixing across all three distinguished flow regimes is predicted by asymptotic scaling laws and supported by three-dimensional numerical simulations. Mixing enhancement is initiated with the least electromagnetic forcing in channels with order-unity depth-to-gap-width ratios. If the strength of the electromagnetic forcing is not a constraint, then shallow-layer flows can still yield the shortest mixing times in the advection-dominated limit. Our robust description of momentum evolution and mixing of passive tracers makes the annular magneto-Stokes system fit for use as an MHD reference flow.

Bird strike accidents are critical threats for aviation safety especially in airport airspaces. Environment friendly solutions are preferred for wildlife managements to achieve harmonic coexistence between airports and surrounding environments. Avian radar systems are the most effective remote sensing approach for long-range and all-weather birds monitoring. Massive historical avian radar datasets and other data sources provide an opportunity to explore relevance between bird behaviour and environments. This paper proposes a bird behaviour characterisation and prediction method to reveal bird behaviour dependency with weather parameters. Bird behaviours are modelled as indices and grades from selected avian radar datasets. Weather dependence are studied from single parameter to multivariable parameters. The random forest model is selected as a behaviour grade prediction model taking four weather parameters as system inputs. Radar datasets for diurnal and nocturnal birds are constructed to validate their behaviour characters and prediction performance, respectively. Experiment results verify the feasibility of bird behaviour prediction using weather parameters, but also reflect some insufficiencies within the proposed method. Data sufficiency and severe weather considerations are also discussed to analyse their impact on prediction accuracy. A more comprehensive prediction model with standardised avian radar data quality and enhanced weather information accuracy is promising to further elevate the application significance of the proposed method.

Diet is an important modifiable lifestyle factor for human health, and plant-rich dietary patterns are associated with lower risk of non-communicable diseases in numerous studies. However, objective assessment of plant-rich dietary exposure in nutritional epidemiology studies remains challenging. This study aimed to develop and evaluate metabolic signatures of the most widely used plant-rich dietary patterns using a targeted metabolomics method comprising of 108 plant food metabolites.

A total of 218 healthy participants from the POLYNTAKE cohort were included, aged 51.5 ± 17.7 years, with 24h urine samples measured using ultra-high-performance liquid chromatography–mass spectrometry. The validation dataset employed three sample types to test the robustness of the signature, including 24h urine (ABP cohort, n = 88), plasma (POLYNTAKE cohort, n = 195), and spot urine (TwinsUK cohort, n = 198). Adherence to the plant-rich diet was assessed using a priori plant- rich dietary patterns. A combination of metabolites that evaluates the adherence and metabolic response to a specific diet was identified as metabolic signature. We applied linear regression analysis to select the metabolites significantly associated with dietary patterns (adjusting energy intake), and ridge regression to estimate penalized weights of each candidate metabolite. The correlation between metabolic signature and the dietary pattern was assessed by Spearman analysis (FDR < 0.05).

The metabolic signatures consisting of 42, 22, 35, 15, 33, and 33 predictive metabolites across different subclasses were found to be associated with adherence to Amended Mediterranean Score (A-MED), Original MED (O-MED), Dietary Approaches to Stop Hypertension (DASH), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), healthy Plant-based Diet Index (hPDI) and unhealthy PDI (uDPI), respectively. The overlapping and distinct predictive metabolites across six dietary patterns predominantly consisted of phenolic acids (n = 38), including 14 cinnamic acids, 14 hydroxybenzoic acids, seven phenylacetic acids, and three hippuric acids. Six metabolites were included in all signatures, including two lignans: enterolactone-glucuronide, enterolactone-sulfate, and four phenolic acids: cinnamic acid, cinnamic acid-4'-sulfate, 2'- hydroxycinnamic acid, and 4-methoxybenzoic acid-3-sulfate. The established signatures were robustly correlated with dietary patterns in validation dataset (r = 0.13 - 0.40, FDR < 0.05).

We developed and evaluated a set of metabolic signatures that robustly reflected the adherence and metabolic response to plant-rich dietary patterns, suggesting the potential of these signatures to serve as an objective assessment of free-living eating habits.

Inhibitory control plays an important role in children’s cognitive and socioemotional development, including their psychopathology. It has been established that contextual factors such as socioeconomic status (SES) and parents’ psychopathology are associated with children’s inhibitory control. However, the relations between the neural correlates of inhibitory control and contextual factors have been rarely examined in longitudinal studies. In the present study, we used both event-related potential (ERP) components and time-frequency measures of inhibitory control to evaluate the neural pathways between contextual factors, including prenatal SES and maternal psychopathology, and children’s behavioral and emotional problems in a large sample of children (N = 560; 51.75% females; Mage = 7.13 years; Rangeage = 4–11 years). Results showed that theta power, which was positively predicted by prenatal SES and was negatively related to children’s externalizing problems, mediated the longitudinal and negative relation between them. ERP amplitudes and latencies did not mediate the longitudinal association between prenatal risk factors (i.e., prenatal SES and maternal psychopathology) and children’s internalizing and externalizing problems. Our findings increase our understanding of the neural pathways linking early risk factors to children’s psychopathology.

The chemistry of Al transformation has been well documented, though little is known about the mechanisms of structural perturbation of Al precipitates by carbonates at a molecular level. The purpose of the present study was to investigate the structural perturbation of Al precipitates formed under the influence of carbonates. Initial carbonate/Al molar ratios (MRs) used were 0, 0.1, and 0.5 after aging for 32 days, then the samples were analyzed by X-ray absorption near edge structure spectroscopy (XANES), X-ray diffraction (XRD), Fourier-transform infrared absorption spectroscopy (FTIR), and chemical analysis. The XRD data were in accord with the FTIR results, which revealed that as the carbonate/Al MR was increased from 0 to 0.1, carbonate preferentially retarded the formation of gibbsite and had relatively little effect on the formation of bayerite. As the carbonate/Al MR was increased to 0.5, however, the crystallization of both gibbsite and bayerite was completely inhibited. The impact of carbonate on the nature of Al precipitates was also evident in the increase of adsorbed water and inorganic C contents with increasing carbonate/Al MR. The Al K- and L- edge XANES data provide the first evidence illustrating the change in the coordination number of Al from 6-fold to mixed 6- and 4-fold coordination in the structural network of short-range ordered (SRO) Al precipitates formed under the increasing perturbation of carbonate. The fluorescence yield spectra of the O K-edge show that the intensity of the peak at 534.5 eV assigned to σ* transitions of Al-O and O-H bonding decreased with increasing carbonate/Al MR. The XANES data, along with the evidence from XRD, FTIR, and chemical analysis showed clearly that carbonate caused the alteration of the coordination nature of the Al-O bonding through perturbation of the atomic bonding and structural configuration of Al hydroxides by complexation with Al in the SRO network of Al precipitates. The surface reactivity of an Al-O bond is related to its covalency and coordination geometry. The present findings were, therefore, of fundamental significance in understanding the low-temperature geochemistry of Al and its impacts on the transformation, transport, and fate of nutrients and pollutants in the ecosystem.

Using real-time data, we show that currency excess return predictability is in part due to mispricing. First, the risk-adjusted profitability of systematic trading strategies decreases after dissemination of the underlying academic research, suggesting that market participants learn about mispricing from publications. Moreover, the decline is greater for strategies with larger in-sample profits and lower arbitrage costs. Second, the effect of comprehensive risk adjustments on trading profits is limited, and signal ranks and alphas decay quickly. The finding that analysts’ forecasts are inconsistent with currency predictors implies that investors’ trading contributes to mispricing and suggests biased expectations as a possible explanation.

Stress and diabetes coexist in a vicious cycle. Different types of stress lead to diabetes, while diabetes itself is a major life stressor. This was the focus of the Chicago Biomedical Consortium’s 19th annual symposium, “Stress and Human Health: Diabetes,” in November 2022. There, researchers primarily from the Chicago area met to explore how different sources of stress – from the cells to the community – impact diabetes outcomes. Presenters discussed the consequences of stress arising from mutant proteins, obesity, sleep disturbances, environmental pollutants, COVID-19, and racial and socioeconomic disparities. This symposium showcased the latest diabetes research and highlighted promising new treatment approaches for mitigating stress in diabetes.

Dissolved inorganic carbon (DIC) in ocean water is a major sink of fossil fuel derived CO2. Carbon isotopes in DIC serve as tracers for oceanic water masses, biogeochemical processes, and air-sea gas exchange. We present a timeseries of surface DIC δ13C and Δ14C values from 2011 to 2022 from Newport Beach, California. This is a continuation of previous timeseries (Hinger et al. 2010; Santos et al. 2011) that together provide an 18-year record. These data show that DIC Δ14C values have declined by 42‰ and that DIC δ13C values have declined by 0.4‰ since 2004. By 2020, DIC Δ14C values were within analytical error of nearby clean atmospheric CO2 Δ14C values. These long-term trends are likely the result of significant fossil fuel derived CO2 in surface DIC from air-sea gas exchange. Seasonally, Δ14C values varied by 3.4‰ between 2011 and 2022, where seasonal δ13C values varied by 0.7‰. The seasonal variation in Δ14C values is likely driven by variations in upwelling, surface eddies, and mixed layer depth. The variation in δ13C values appears to be driven by isotopic fractionation from marine primary producers. The DIC δ13C and Δ14C values record the influence of the drought that began in 2012, and a major upwelling event in 2016.