High Statistical Precision Research Articles

TAMie Force Field for Alkanethiols: Multifidelity Gaussian Processes for Dealing with Scarce Experimental Data.

This study extends the transferable anisotropic Mie potential (TAMie) to alkanethiols. The force field parameters are optimized by using an analytic equation of state as a surrogate model. Given the lack of experimental density data at elevated temperatures where Monte Carlo simulations have high statistical precision, the equation of state is supplemented by a linear multifidelity Gaussian process approach to bridge the temperature gap. Force field parameters are adjusted by minimizing squared deviations of calculated vapor pressures and liquid densities from experimental data of 1-propanethiol, 1-butanethiol and 1-pentanethiol leading to small mean absolute relative deviations in liquid densities and vapor pressures. The force field is transferable to higher 1-thiols, as shown for 1-hexanethiol and 1-octanethiol. Individual parameter sets are provided for methanethiol and ethanethiol. The shear viscosity of pure substances is predicted in fair agreement with experimental data, considering that it is not included in the parametrization. Further, the phase behavior of binary mixtures of alkanethiols with alkanes is studied, and predictions of the TAMie model are found in excellent agreement with experimental data.

Leveraging artificial intelligence to summarize abstracts in lay language for increasing research accessibility and transparency.

Returning aggregate study results is an important ethical responsibility to promote trust and inform decision making, but the practice of providing results to a lay audience is not widely adopted. Barriers include significant cost and time required to develop lay summaries and scarce infrastructure necessary for returning them to the public. Our study aims to generate, evaluate, and implement ChatGPT 4 lay summaries of scientific abstracts on a national clinical study recruitment platform, ResearchMatch, to facilitate timely and cost-effective return of study results at scale. We engineered prompts to summarize abstracts at a literacy level accessible to the public, prioritizing succinctness, clarity, and practical relevance. Researchers and volunteers assessed ChatGPT-generated lay summaries across five dimensions: accuracy, relevance, accessibility, transparency, and harmfulness. We used precision analysis and adaptive random sampling to determine the optimal number of summaries for evaluation, ensuring high statistical precision. ChatGPT achieved 95.9% (95% CI, 92.1-97.9) accuracy and 96.2% (92.4-98.1) relevance across 192 summary sentences from 33 abstracts based on researcher review. 85.3% (69.9-93.6) of 34 volunteers perceived ChatGPT-generated summaries as more accessible and 73.5% (56.9-85.4) more transparent than the original abstract. None of the summaries were deemed harmful. We expanded ResearchMatch's technical infrastructure to automatically generate and display lay summaries for over 750 published studies that resulted from the platform's recruitment mechanism. Implementing AI-generated lay summaries on ResearchMatch demonstrates the potential of a scalable framework generalizable to broader platforms for enhancing research accessibility and transparency.

Efficient and accurate calculation of proline cis/trans isomerization free energies from Hamiltonian replica exchange molecular dynamics simulations

Proline cis/trans isomerization plays an important role in many biological processes but occurs on time scales not accessible to brute-force molecular dynamics (MD) simulations. We have designed a new Hamiltonian replica exchange scheme, ω-bias potential replica exchange molecular dynamics (ωBP-REMD), to efficiently and accurately calculate proline cis/trans isomerization free energies. ωBP-REMD is applied to various proline-containing tripeptides and a biologically important proline residue in the N2-domain of the gene-3-protein of phage fd in the wildtype and mutant variants of the protein. Excellent cis/trans transition rates are obtained. Reweighting of the sampled probability distribution along the peptide bond dihedral angle allows construction of the corresponding free-energy profile and calculation of the cis/trans isomerization free energy with high statistical precision. Very good agreement with experimental data is obtained. ωBP-REMD outperforms standard umbrella sampling in terms of convergence and agreement with experiment and strongly reduces perturbation of the local structure near the proline residue.

Sickness absence due to mandatory COVID-19 certificates in the workplace

BackgroundAs vaccines for COVID-19 became available, many countries introduced an obligation in 2021 for employees to prove their COVID-19 status at work, known in Germany as the 3G rule (vaccinated, recovered, tested). In view of the controversial debate, there was concern that employees might try to avoid providing mandatory COVID-19 certificates by taking sick leave. The aim of this study was to investigate whether mandatory COVID-19 tests in the workplace led to such an evasive response.MethodFor an empirical panel analysis, we collected data from official sources and combined aggregated health insurance data on sick leave, epidemiological data on laboratory-confirmed COVID-19 infections, and vaccination rates for the German states from September 2021 to January 2022. We used a regional panel data analysis to estimate the impact of the mandatory COVID-19 certificates at the workplace on workers’ sick leave. The regional vaccination rate reflected differences in treatment intensity.ResultsThis study contributes to the limited evidence on the potential impact of introducing mandatory COVID-19 certificates at the workplace on sickness absence rates. In fact, our results showed that after controlling for infection rates, a one percentage point lower vaccination rate led to a 0.021 percentage point increase in the sickness absence rate when the 3G rule came into effect. This effect was measured with high statistical precision. In addition, in robustness checks, we controlled for a number of other possible influencing factors that may have affected sickness behaviours, such as time-varying labour market situations. However, the results remained robust.ConclusionsThe results of our empirical panel analysis implied that mandatory COVID-19 certificates in the workplace led to evasive responses and to additional days of sick leave of a relevant magnitude. Testing obligations were meant to help contain the epidemic. However, when introducing controversial obligations, it is important to consider evasive responses and to design the rules appropriately and communicate them convincingly.

A semi-analytic study of self-interacting dark-matter haloes with baryons

ABSTRACT We combine the isothermal Jeans model and the model of adiabatic halo contraction into a semi-analytic procedure for computing the density profile of self-interacting dark-matter (SIDM) haloes with the gravitational influence from the inhabitant galaxies. The model agrees well with cosmological SIDM simulations over the entire core-forming stage up to the onset of gravothermal core-collapse. Using this model, we show that the halo response to baryons is more diverse in SIDM than in CDM and depends sensitively on galaxy size, a desirable feature in the context of the structural diversity of bright dwarfs. The fast speed of the method facilitates analyses that would be challenging for numerical simulations – notably, we quantify the SIDM halo response as functions of the baryonic properties, on a fine mesh grid spanned by the baryon-to-total-mass ratio, Mb/Mvir, and galaxy compactness, r1/2/Rvir; we show with high statistical precision that for typical Milky-Way-like systems, the SIDM profiles are similar to their CDM counterparts; and we delineate the regime of core-collapse in the Mb/Mvir − r1/2/Rvir space, for a given cross section and concentration. Finally, we compare the isothermal Jeans model with the more sophisticated gravothermal fluid model, and show that the former yields faster core formation and agrees better with cosmological simulations. We attribute the difference to whether the target CDM halo is used as a boundary condition or as the initial condition for the gravothermal evolution, and thus comment on possible improvements of the fluid model. We have made our model publicly available at https://github.com/JiangFangzhou/SIDM.

Developing a decision instrument to guide abdominal-pelvic imaging of blunt trauma patients: Methodology and protocol of the NEXUS abdominal-pelvic imaging study.

Although computed tomography (CT) of the abdomen and pelvis (A/P) can provide crucial information for managing blunt trauma patients, liberal and indiscriminant imaging is expensive, can delay critical interventions, and unnecessarily exposes patients to ionizing radiation. Currently no definitive recommendations exist detailing which adult blunt trauma patients should receive A/P CT imaging and which patients may safely forego CT. Considerable benefit could be realized by identifying clinical criteria that reliably classify the risk of abdominal and pelvic injuries in blunt trauma patients. Patients identified as "very low risk" by such criteria would be free of significant injury, receive no benefit from imaging and therefore could be safely spared the expense and radiation exposure associated with A/P CT. The goal of this two-phase nationwide multicenter observational study is to derive and validate the use of clinical criteria to stratify the risk of injuries to the abdomen and pelvis among adult blunt trauma patients. We estimate that nation-wide implementation of a rigorously developed decision instrument could safely reduce CT imaging of adult blunt trauma patients by more than 20%, and reduce annual radiographic charges by $180 million, while simultaneously expediting trauma care and decreasing radiation exposure with its attendant risk of radiation-induced malignancy. Prior to enrollment we convened an expert panel of trauma surgeons, radiologists and emergency medicine physicians to develop a consensus definition for clinically significant abdominal and pelvic injury. In the first derivation phase of the study, we will document the presence or absence of preselected candidate criteria, as well as the presence or absence of significant abdominal or pelvic injuries in a cohort of blunt trauma victims. Using recursive partitioning, we will examine combinations of these criteria to identify an optimal "very low risk" subset that identifies injuries with a sensitivity exceeding 98%, excludes injury with a negative predictive value (NPV) greater than 98%, and retains the highest possible specificity and potential to decrease imaging. In Phase 2 of the study we will validate the performance of a decision rule based on these criteria among a new cohort of patients to ensure that the criteria retain high sensitivity, NPV and optimal specificity. Validating the sensitivity of the decision instrument with high statistical precision requires evaluations on 317 blunt trauma patients who have significant abdominal-pelvic injuries, which will in turn require evaluations on approximately 6,340 blunt trauma patients. We will estimate potential reductions in CT imaging by counting the number of abdominal-pelvic CT scans performed on "very low risk" patients. Reductions in charges and radiation exposure will be determined by respectively summing radiographic charges and lifetime decreases in radiation morbidity and mortality for all "very low risk" cases. Trial registration: Clinicaltrials.gov trial registration number: NCT04937868.

The fundamental metallicity relation from SDSS (z ∼ 0) to VIPERS (z ∼ 0.7)

Context. Our knowledge of galaxy metallicity – the result of the integrated star formation history and the evolution of the interstellar medium – is important for constraining the description of galaxy evolution. As such, it has been widely studied in the local Universe, in particular, using data from the Sloan Digital Sky Survey (SDSS). The VIMOS Public Extragalactic Redshift Survey (VIPERS) allows us to extend such studies up to redshift of z ∼ 0.7 and to quantify a possible evolution of the galaxy metallicity with high statistical precision. Aims. We focus on how to homogenize the comparison between galaxy samples having different characteristics. We check the projections of the fundamental metallicity relation (FMR) and the evolution of these projections between a sample selected at z ∼ 0 (SDSS) and z ∼ 0.7 (VIPERS). We check, in particular, whether and to what extent selection criteria can affect the results. Methods. We checked the influence of different biases introduced either by physical constraints (evolution of the luminosity function and differences in the fraction of blue galaxies) or data selection (the signal-to-noise ratio and quality of the spectra) on the FMR and its projections. To separate the differences occurring due to the physical evolution of galaxies with redshift from the false evolution mimed by these biases, we first analyzed the effects of these biases individually on the SDSS sample, and next, starting from the SDSS data, we built a VIPERS-equivalent z ∼ 0 sample, replicating the main characteristics of VIPERS sample at z ∼ 0.7 for a fair comparison. Results. We found that the FMR projections are all sensitive to biases introduced by the selection on S/N and the quality flags of the emission line measurements in the spectra, especially the [O III]λ4959 line. The exception is the metallicity versus the sSFR plane which is insensitive to these biases. The evolution of the luminosity function introduces a bias only in the plane metallicity versus the star formation rate (SFR) while the fraction of blue galaxies has no impact on results. Conclusions. With the applied methodology, the median metallicities estimated in each stellar mass-SFR bin of the samples at z ∼ 0 and z ∼ 0.7 agree within the uncertainties between SDSS and VIPERS samples (Δ log(O/H) ∼ 0.6⟨sVIPERS⟩ = 0.08 dex, where sVIPERS stands for the metallicity standard deviation, without taking into account the biases). This difference can be reduced to ∼0.4⟨sVIPERS⟩ = 0.06 dex taking into account the biases, in particular the evolution of the luminosity function. We find a shift of the FMR projections towards lower metallicity which can be mimicked by a conservative selection on the S/N of emission lines. We also find either an overselection of high-metal galaxies at low stellar mass or an overestimation of the metallicity for the same sources at z ∼ 0.7. Any bias taken into account in this study cannot mimic this overselection or overestimation at low redshift.

The DESI N-body Simulation Project – II. Suppressing sample variance with fast simulations

ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\, h^{-3}\, \mathrm{Gpc}^{3}$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

SuperTIGER instrument abundances of galactic cosmic rays for the charge interval [formula omitted

We report preliminary elemental abundance results from the 55-day long-duration-balloon flight of SuperTIGER (Super Trans-Iron Galactic Element Recorder) during the 2012–2013 austral summer. SuperTIGER measured the relative abundances of Galactic cosmic-ray (GCR) nuclei with high statistical precision and well resolved individual element peaks from 10Ne to 40Zr. SuperTIGER also made exploratory measurements of the relative abundances up to 56Ba. Although the statistics are low for elements heavier than 40Zr, we present, for the first time, relative abundance measurements of charges Z=41-56 with individual element resolution. GCR measurements up to 40Zr support a source acceleration model where supernovae in OB associations preferentially accelerate refractory elements that are more readily embedded in interstellar dust grains than volatiles. In addition, injection into the GCR for both refractory and volatile elements appears to follow a charge dependence consistent with their grain sputtering cross sections. By extending the GCR measurement range past 40Zr, we can begin to further constrain these models.

Causal Inference and Machine Learning approaches to discover de novo sub-populations with heterogeneous air pollution health effects

BACKGROUND AND AIM: In environmental health sciences, it is critically important to identify subgroups of the study population where a treatment (or exposure) has a notably larger or smaller causal effect on an outcome compared to the population average. METHODS: In this paper, we propose a new causal rule ensemble (CRE) method that: 1) discovers de novo subgroups with significantly heterogeneous treatment effects (i.e., causal rules); 2) ensures interpretability of these subgroups because they are defined in terms of decision rules; and 3) estimates the causal effect for each of these newly discovered subgroups with small bias and high statistical precision. We also introduce a new sensitivity analysis to unmeasured confounding bias. RESULTS:We apply the proposed CRE method to the Medicare data to study the heterogeneous effects of long-term exposure to PM2.5 on 5-year mortality. The population consists of Medicare beneficiaries in New England regions in the United States between 2000 and 2006. The treatment is whether the two-year (2000-2001) average of exposure to PM2.5 is greater than 12μg/m3. The outcome is five-year mortality measured between 2002-2006. We found that younger than 80 years old and not eligible for Medicaid are significantly less vulnerable than the baseline subgroup. Results were not sensitive to unmeasured confounding bias. CONCLUSIONS:We introduce a new method for studying treatment effect heterogeneity that notably improves interpretability in terms of causal rules. The proposed CRE methodology provides a more stable approach to discover and estimate heterogeneous effects while maintaining high levels of interpretability. KEYWORDS: Air pollution, causal inference, mortality, methodological study design

The Spread of COVID-19 Among 15,000 Physical Therapists in Italy: A Cross-Sectional Study.

ObjectivesThe purpose of this study was to explore the prevalence, personal- and work-related exposures, and signs and symptoms among physical therapists during the first wave of coronavirus disease 2019 (COVID-19) in Italy.MethodsThis cross-sectional, survey-based study collected demographic and exposure data from physical therapists from April to May 2020. All physical therapists working in inpatient and outpatient care in Italy were eligible. A self-administered questionnaire was distributed among all eligible physical therapists to collect (1) demographic characteristics, (2–3) personal- and work-related exposures, and (4) signs and symptoms of COVID-19. Factors associated with a COVID-19–positive nasopharyngeal swab (NPS) were explored through logistic regression models and multivariate methods.ResultsA total of 15,566 respondents completed the survey, with a response rate of 43.3%, achieving high statistical precision (99% CI, 1% type I error). Among physical therapists who received NPS testing, 13.1% (95% CI = 12.1–14.1%) had a positive result, with a peak reached in March 2020 (36%). The top 5 symptoms were fatigue and tiredness (69.1%), loss of smell (64.5%), aches and pains (60.8%), loss of taste (58.3%), and headache (51.1%). No symptoms were reported by 8.9%. Working in a health care institution (odds ratio [OR] = 12.0; 95% CI = 7.8–18.4), being reallocated to a different unit (OR = 1.9; 95% CI = 1.3–2.7), and changing job tasks (OR = 1.6; 95% CI = 1.2–2.3) increased the risk of being COVID-19 positive. In therapists with a confirmed diagnosis of COVID-19, comorbidities were associated with male sex and age older than 51 years.ConclusionDuring the first wave in Italy, almost 1 out of 7 physical therapists tested positive on the COVID-19 NPS test. Considering personal- and work-related exposures, health care organizations should adopt prevention measures and adequate preparedness to prevent high rate of infections during future pandemics.ImpactThis is the largest investigation about the spread of and main risk factors for COVID-19 in the physical therapy field.

Leveraging GIS and spatial analysis for informed decision-making in COVID-19 pandemic

•Geographic Information System (GIS) techniques are widely used across scientific disciplines, including public health since the mid-1960s.•GIS has been playing a critical role in understanding the spatial clustering and transmission trend of the ongoing COVID-19.•The Johns Hopkins University created a near-real-time GIS-based COVID-19 case tracking and documentation mechanism.•Applications of GIS in COVID-19 related studies were focused on mapping the cases on different administrative units.•GIS could be used to predict not only the confirmed case numbers but also specific locations where the outbreak would happen with a higher statistical precision.

The GOGREEN Survey: A deep stellar mass function of cluster galaxies at 1.0 < z < 1.4 and the complex nature of satellite quenching

We study the stellar mass functions (SMFs) of star-forming and quiescent galaxies in 11 galaxy clusters at 1.0 < z < 1.4 drawn from the Gemini Observations of Galaxies in Rich Early ENvironments (GOGREEN) survey. Based on more than 500 h of Gemini/GMOS spectroscopy and deep multi-band photometry taken with a range of observatories, we probe the SMFs down to a stellar mass limit of 109.7 M⊙ (109.5 M⊙ for star-forming galaxies). At this early epoch, the fraction of quiescent galaxies is already highly elevated in the clusters compared to the field at the same redshift. The quenched fraction excess (QFE) represents the fraction of galaxies that would be star-forming in the field but are quenched due to their environment. The QFE is strongly mass dependent, and increases from ∼30% at M⋆ = 109.7 M⊙ to ∼80% at M⋆ = 1011.0 M⊙. Nonetheless, the shapes of the SMFs of the two individual galaxy types, star-forming and quiescent galaxies, are identical between cluster and field to high statistical precision. Nevertheless, along with the different quiescent fractions, the total galaxy SMF is also environmentally dependent, with a relative deficit of low-mass galaxies in the clusters. These results are in stark contrast with findings in the local Universe, and therefore require a substantially different quenching mode to operate at early times. We discuss these results in light of several popular quenching models.

Compton scattering from He4 at the TUNL HIγS facility

Differential cross sections for elastic Compton scattering from $^4$He have been measured with high statistical precision at the High Intensity $\gamma$-ray Source at laboratory scattering angles of $55^\circ$, $90^\circ$, and $125^\circ$ using a quasi-monoenergetic photon beam with a weighted mean energy value of $81.3$ MeV. The results are compared to previous measurements and similar fore-aft asymmetry in the angular distribution of the differential cross sections is observed. This experimental work is expected to strongly motivate the development of effective-field-theory calculations of Compton scattering from $^4$He to fully interpret the data.

Handling imbalanced data with concept drift by applying dynamic sampling and ensemble classification model

With the availability of a broad range of applications for Big Data streaming, both the class imbalance and concept drift have become crucial learning issues. The concept of drift handling solutions is sensitive to class imbalance. The sampling techniques are widely applied to process the continuously arriving data streams with a sufficient number of instances. The selected instances have to build a statistical inference to support imbalanced class distribution. The stream data classification model without concept drift adaptation is not preferable to the imbalanced class distribution. To solve the issues, this article presents the dynamic sampling and an ensemble classification technique, named as Handling Imbalanced Data with Concept Drift (HIDC). To provide high statistical precision over imbalanced class distribution with concept drift, the HIDC decides an optimal reservoir size using the metrics regarding statistical properties of stream data and control parameter. The former refers to the inequality level in the values of instances arrived from a source, and the latter one controls over the selection of instances from multiple sources. The HIDC estimates the optimal reservoir size using such statistical and control parameters. To select the appropriate instances with an allocated optimal reservoir size, the HIDC applies random sampling over imbalanced classes and chooses a set of instances from multiple sources. The random sampling cannot solve the issues of imbalanced class distribution among the existing classes. To address such problems, the HIDC applies resampling techniques with respect to the imbalance factor. To identify and address the new concepts, the proposed HIDC sampling model trains the candidate classifier and replaces the worst ensemble member with the candidate classifier. Finally, the experimental results show that the HIDC performs better sampling and mining over imbalanced class distribution with concept drifts.

Transformative experience and social connectedness mediate the mood-enhancing effects of psychedelic use in naturalistic settings

Past research suggests that use of psychedelic substances such as LSD or psilocybin may have positive effects on mood and feelings of social connectedness. These psychological effects are thought to be highly sensitive to context, but robust and direct evidence for them in a naturalistic setting is scarce. In a series of field studies involving over 1,200 participants across six multiday mass gatherings in the United States and the United Kingdom, we investigated the effects of psychedelic substance use on transformative experience, social connectedness, and positive mood. This approach allowed us to test preregistered hypotheses with high ecological validity and statistical precision. Controlling for a host of demographic variables and the use of other psychoactive substances, we found that psychedelic substance use was significantly associated with positive mood-an effect sequentially mediated by self-reported transformative experience and increased social connectedness. These effects were particularly pronounced for those who had taken psychedelic substances within the last 24 h (compared to the last week). Overall, this research provides robust evidence for positive affective and social consequences of psychedelic substance use in naturalistic settings.

Single-cell approaches to cell competition: High-throughput imaging, machine learning and simulations.

Cell competition is a quality control mechanism in tissues that results in the elimination of less fit cells. Over the past decade, the phenomenon of cell competition has been identified in many physiological and pathological contexts, driven either by biochemical signaling or by mechanical forces within the tissue. In both cases, competition has generally been characterized based on the elimination of loser cells at the population level, but significantly less attention has been focused on determining how single-cell dynamics and interactions regulate population-wide changes. In this review, we describe quantitative strategies and outline the outstanding challenges in understanding the single cell rules governing tissue-scale competition dynamics. We propose quantitative metrics to characterize single cell behaviors in competition and use them to distinguish the types and outcomes of competition. We describe how such metrics can be measured experimentally using a novel combination of high-throughput imaging and machine learning algorithms. We outline the experimental challenges to quantify cell fate dynamics with high-statistical precision, and describe the utility of computational modeling in testing hypotheses not easily accessible in experiments. In particular, cell-based modeling approaches that combine mechanical interaction of cells with decision-making rules for cell fate choices provide a powerful framework to understand and reverse-engineer the diverse rules of cell competition.

Is There a Direct Causal Effect of Education on Dementia? A Swedish Natural Experiment on 1.3 Million Individuals

Background: Education is related to dementia risk. Researchers in public health often treat education as a modifiable risk factor, implying that prolonging education may reduce dementia incidence. This reasoning rests on the largely untested assumption that education has causal effects on dementia risk. Methods: We used variance in education induced by a compulsory schooling reform, which extended Swedish primary school (Folkskola) from 6 to 7 years as a tool for studying direct causal effects of education on dementia risk. The reform was implemented gradually in school districts and had minor spillover effects. We studied 18 birth cohorts (1920-1937), excluding individuals with unknown reform status, those who died, emigrated, or received dementia diagnosis prior to 65 years of age. The outcome was dementia diagnosis in the National Inpatient and Cause of Death Registers. The reform allowed us to study direct effects of prolonged education with high validity and statistical precision. In the main analyses, we employed sex-stratified Cox survival models with stratified baseline hazards at the school-district level, used chronological age as the time scale, and dummy-coded cohort effects. Findings: 1,341,842 individuals were included. The reform did not affect the risk of dementia diagnosis in a statistically significant way. The estimates and associated confidence intervals (women: HR = 1.01; 95% CI = 0.97-1.04; men: HR = 1.02; 95% CI = 0.99-1.06; all: HR = 1.01; 95% CI = 0.98-1.04) indicate that any direct effect is likely of a negligible or very small magnitude. Sensitivity analyses targeting pre-post changes, differences in healthcare-seeking behavior, and impact of exposure misclassification left results essentially unaltered. Interpretation: Longer education, at least in the absence of sizable spillover effects to adult socio-economic factors, cannot be uncritically assumed to substantially reduce the risk of moderate to severe dementia. Funding Statement: FORTE (2013-2277) and Swedish Research Council (446-2013-7189) to ML. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: The study was approved by the Regional Ethical Review Board in Stockholm (Case number: 2010/1185-31/5).

Three methods for characterizing thermo-optic noise in optical cavities

Thermo-optic noise is likely to be the dominant noise source in next generation ultralow noise optical cavities. We developed three measurement and analysis methods, allowing us to estimate the level of coating thermo-optic noise in optical cavities, including interferometric gravitational wave detectors. We measured the shift in the broadband transmission spectra as a function of temperature for single-layer, high index coatings in order to find the thermo-optic coefficient, ${\ensuremath{\beta}}_{H}$, of a coating while assuming the thermal expansion coefficient, ${\ensuremath{\alpha}}_{H}$. Our value for ${\ensuremath{\beta}}_{H}$ could then be used to calculate the thermo-optic noise in any high-finesse optical cavity using coatings with the same high index layer material. We also measured the spectra as a function of temperature of a multilayer, high-reflectivity coating where the material composition of the layers was similar to the coatings installed in Advanced LIGO. This method has the advantage of allowing us to calculate thermo-optic noise directly; ${\ensuremath{\alpha}}_{H}$ and ${\ensuremath{\beta}}_{H}$ do not need to be known separately, although we do need to know the value of the overall coating thermal expansion coefficient. Finally, we used lasers of different wavelengths to measure transmission changes on the band edges of a multilayer high-reflectivity coating. This gave measurements with high statistical precision but potentially lower systematic accuracy. To address systematic accuracy concerns, we used a constrained Monte Carlo application of the theory of multilayer coating transmission.

Efficient phase imaging using wavelength-resolved neutron Talbot-Lau interferometry with TOF method

For efficient differential-phase-contrast imaging, we have demonstrated the wavelength-resolved neutron Talbot-Lau interferometry with the wavelength resolution of 0.11 Å over a wide wavelength range of 2.5–7.5 Å at RADEN in the J-PARC Materials and Life Science Experimental Facility. The time-of-flight measurement has clearly showed that the visibility of moiré fringes and intensity oscillations of the interferometer varied continuously with the wavelength, and the wavelength dependence of the differential phase of metal samples was measured. Based on the analysis utilizing this wavelength dependence, we achieved both high statistical precision and high accuracy in the differential-phase-contrast imaging, and succeeded in the quantitative evaluation of the optical potentials of metals.