In Situ Self-Assembled 1D/3D Mixed-Dimensional Perovskite Heterostructures for Efficient White Light Emission.

Mixed-dimensional perovskite (MDP) heterostructures are promising optoelectronic semiconductors. Yet, the current preparation methods involve complex experimental procedures and material compatibility constraints, limiting their widespread applications. Here, we present a one-step room temperature solution-based approach to synthesize a range of 1D C4N2H14PbBr4 and 3D APbBr3 (A = Cs+, MA+, FA+) self-assembled MDP heterostructures exhibiting high-efficiency white light-emitting properties. The ultra-broadband emission results from the synergy between the self-captured blue broadband emission from 1D perovskites and the green emission of 3D perovskites, covering the entire visible-light spectrum with a full width at half-maximum exceeding 170 nm and a remarkable photoluminescence quantum yield of 26%. This work establishes a novel prototype for the preparation of highly luminescent MDP heterostructures, offering insights for future research and industrialization in the realm of white light LEDs.

Colossal Linear Magnetoelectricity in Polar Magnet Fe_{2}Mo_{3}O_{8}.

The linear magnetoelectric effect is an attractive phenomenon in condensed matters and provides indispensable technological functionalities. Here a colossal linear magnetoelectric effect with diagonal component α_{33} reaching up to ∼480 ps/m is reported in a polar magnet Fe_{2}Mo_{3}O_{8}. This effect can persist in a broad range of magnetic field (∼20 T) and is orders of magnitude larger than reported values in literature. Such an exceptional experimental observation can be well reproduced by a theoretical model affirmatively unveiling the vital contributions from the exchange striction, while the sign difference of magnetocrystalline anisotropy can also be reasonably figured out.

Electronic Structure Regulation of Nickel Phosphide for Efficient Overall Water Splitting.

Rational design and fabrication of efficient and low-cost catalysts for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are crucial for hydrogen production from water electrolysis. Herein, we report heteroatom Fe-incorporated Ni5P4 (Fe-NiP) as an excellent bifunctional catalyst for overall water splitting. Density functional theory (DFT) calculations reveal that heteroatom Fe effectively steers the electronic structure of Ni5P4, which optimizes the hydrogen adsorption behavior. Additionally, the hierarchical conductive framework of Fe-NiP contributes to abundant active sites. Thus, the Fe-NiP catalyst shows robust performance with enhanced intrinsic catalytic activity. As a good bifunctional catalyst, it demands low overpotentials of 144 and 223 mV to deliver a current density of 10 mA cm-2 for HER and OER, respectively. Considering the good bifunctional activity, an outstanding electrolyzer has been successfully assembled, which is superior to the benchmark of a RuO2(+)//Pt/C(-) electrolyzer. This study sheds light on steering the electronic structure of electrocatalysts through a heteroatom modulation strategy.

Direct Evidence for an Intermediate Multiferroic Phase in LiCuFe2(VO4)3.

Magnetic susceptibility, specific heat, dielectric, and electric polarization of LiCuFe2(VO4)3 have been investigated. Two sequential antiferromagnetic transitions at TN1 ∼ 9.95 K and TN2 ∼ 8.17 K are observed under zero magnetic field. Although a dielectric peak at TN1 is clearly identified, the measured pyroelectric current also exhibits a sharp peak at TN1, implying the magnetically relevant ferroelectricity. Interestingly, another pyroelectric peak around TN2 with an opposite signal is observed, resulting in the disappearance of electric polarization below TN2. Besides, the electric polarization is significantly suppressed in response to external magnetic field, evidencing a remarkable magnetoelectric effect. These results suggest the essential relevance of the magnetic structure with the ferroelectricity in LiCuFe2(VO4)3, deserving further investigation of the underlying mechanism.

Magnetoelectric Effect in Garnet Mn3Al2Ge3O12.

Searching for novel magnetoelectric (ME) materials has been one of the major issues of multiferroics. In this work, we present a systematic research study on garnet Mn3Al2Ge3O12, including structural, magnetic, heat capacity, and ME characterizations. Below the Néel temperature TN ∼ 6.8 K, Mn2+ spins form a long-range antiferromagnetic order, and a magnetic field H-driven electric polarization P is identified simultaneously. The relationship between P and H is nonlinear under low H and becomes linear under high H. Such transition is believed to originate from the H-induced variation of the magnetic structure. In addition, the P reaches 0.6 µC/m2 under µ0H = 9 T, corresponding to an ME coupling coefficient of αME ∼ 0.08 ps/m under high H. The small αME is attributed to the weak spin-orbit coupling and weak magnetic interactions in Mn3Al2Ge3O12. Furthermore, we realize the stable control of P by periodically varying H, which is crucial for potential application. We provide a rare case that a garnet material shows a first-order ME effect.

Constructing Cu-C Bonds in a Graphdiyne-Regulated Cu Single-Atom Electrocatalyst for CO2 Reduction to CH4.

Regulating intermediates through elaborate catalyst design to control the reaction direction is crucial for promoting the selectivity of electrocatalytic CO2 -to-CH4 . M-C (M=metal) bonds are particularly important for tuning the multi-electron reaction; however, its construction in nanomaterials is challenging. Here, via rational design of in situ anchoring of Cu SAs (single atoms) on the unique platform graphdiyne, we firstly realize the construction of a chemical bond Cu-C (GDY). In situ Raman spectroelectrochemistry and DFT calculations confirm that due to the fabrication of the Cu-C bond, during CO2 reduction, the formation of *OCHO intermediates is dominant rather than *COOH on Cu atoms, facilitating the formation of CH4 . Therefore, we find that constructing the Cu-C bond in Cu SAs/GDY can supply an efficient charge transfer channel, but most importantly control the reaction intermediates and guide a more facile reaction pathway to CH4 , thereby significantly boosting its catalytic performance. This work provides new insights on enhancing the selectivity for CO2 RR at the atomic level.

Antiferromagnetism of Double Molybdate LiFe(MoO4)2.

The magnetic properties of the spin-5/2 double molybdate LiFe(MoO4)2 have been characterized by heat capacity, magnetic susceptibility, and neutron powder diffraction techniques. Unlike the multiferroic system LiFe(WO4)2 which exhibits two successive magnetic transitions, LiFe(MoO4)2 undergoes only one antiferromagnetic transition at TN ∼ 23.8 K. Its antiferromagnetic magnetic structure with the commensurate propagation vector k = (0, 0.5, 0) has been determined. Density functional theory calculations confirm the antiferromagnetic ground state and provide a numerical estimate of the relevant exchange coupling constants.

A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study.

BACKGROUND: Imperfect follow-up in longitudinal studies commonly leads to missing outcome data that can potentially bias the inference when the missingness is nonignorable; that is, the propensity of missingness depends on missing values in the data. In the Upstate KIDS Study, we seek to determine if the missingness of child development outcomes is nonignorable, and how a simple model assuming ignorable missingness would compare with more complicated models for a nonignorable mechanism. METHODS: To correct for nonignorable missingness, the shared random effects model (SREM) jointly models the outcome and the missing mechanism. However, the computational complexity and lack of software packages has limited its practical applications. This paper proposes a novel two-step approach to handle nonignorable missing outcomes in generalized linear mixed models. We first analyse the missing mechanism with a generalized linear mixed model and predict values of the random effects; then, the outcome model is fitted adjusting for the predicted random effects to account for heterogeneity in the missingness propensity. RESULTS: Extensive simulation studies suggest that the proposed method is a reliable approximation to SREM, with a much faster computation. The nonignorability of missing data in the Upstate KIDS Study is estimated to be mild to moderate, and the analyses using the two-step approach or SREM are similar to the model assuming ignorable missingness. CONCLUSIONS: The two-step approach is a computationally straightforward method that can be conducted as sensitivity analyses in longitudinal studies to examine violations to the ignorable missingness assumption and the implications relative to health outcomes.

A Functional Data Analysis Approach for Circadian Patterns of Activity of Teenage Girls.

BACKGROUND: Longitudinal or time-dependent activity data are useful to characterize the circadian activity patterns and to identify physical activity differences among multiple samples. Statistical methods designed to analyze multiple activity sample data are desired, and related software is needed to perform data analysis. METHODS: This paper introduces a functional data analysis (fda) approach to perform a functional analysis of variance (fANOVA) for longitudinal circadian activity count data and to investigate the association of covariates such as weight or body mass index (BMI) on physical activity. For multiple age group adolescent school girls, the fANOVA approach is developed to study and to characterize activity patterns. The fANOVA is applied to analyze the physical activity data of three grade adolescent girls (i.e., grades 10, 11, and 12) from the NEXT Generation Health Study 2009-2013. To test if there are activity differences among girls of the three grades, a functional version of the univariate F-statistic is used to analyze the data. To investigate if there is a longitudinal (or time-dependent activity count) difference between two samples, functional t-tests are utilized to test: (1) activity differences between grade pairs; (2) activity differences between low-BMI girls and high-BMI girls of the NEXT study. RESULTS: Statistically significant differences existed among the physical activity patterns for adolescent school girls in different grades. Girls in grade 10 tended to be less active than girls in grades 11 & 12 between 5:30 and 9:30. Significant differences in physical activity were detected between low-BMI and high-BMI groups from 8:00 to 11:30 for grade 10 girls, and low-BMI group girls in grade 10 tended to be more active. CONCLUSIONS: The fda approach is useful in characterizing time-dependent patterns of actigraphy data. For two-sample data defined by weight or BMI values, fda can identify differences between the two time-dependent samples of activity data. Similarly, fda can identify differences among multiple physical activity time-dependent datasets. These analyses can be performed readily using the fda R program.

Racial/ethnic differences in pregnancy-related hypertensive disease in nulliparous women.

OBJECTIVE: Hypertension and cardiovascular disease rates vary by race/ethnicity in nonpregnant adults. We aimed to examine racial/ethnic differences in prevalence and severity of hypertensive diseases during pregnancy in nulliparous women. DESIGN, SETTING, PARTICIPANTS: Nulliparous women with singleton deliveries and electronic medical record data on demographics and pregnancy outcomes (n = 56,617) were selected from the Consortium on Safe Labor (2002-2008). Multivariable logistic regression was performed to calculate the adjusted odds of gestational hypertension, mild preeclampsia, severe preeclampsia, eclampsia, chronic hypertension, superimposed preeclampsia, and unspecified hypertension for women who were non-Hispanic Black, Hispanic, Asian/Pacific Islander, and multiracial/other race/ethnicity, compared with non-Hispanic White women. RESULTS: Non-Hispanic Black women had higher odds of entering pregnancy with chronic hypertension (adjusted odds ratio (AOR) = 1.43, 95% confidence interval (CI) 1.11-1.84) and had higher odds of developing mild (AOR = 1.26, 95% Cl 1.10-1.45), severe (AOR = 1.31, 95% Cl 1.10-1.57) or superimposed preeclampsia (AOR = 1.98, 95% ClI 1.40-2.80) compared to non-Hispanic White women. Hispanic women and Asian/Pacific Islanders had higher odds of remaining normotensive (AOR = 1.22, 95% CI 1.12-1.33 and AOR=1.55, 95% CI 1.31-1.84, respectively). Conclusions: Odds for specific gestational hypertensive diseases varied by race/ethnicity among women during their first pregnancy. Non-Hispanic Black women experienced more severe disease, while Hispanic women and Asian/Pacific Islanders had an overall decreased risk compared to non-Hispanic Whites. Patterns of racial/ethnic variation associated with hypertensive diseases during pregnancy were similar to racial/ethnic associations reported for adult-onset cardiovascular disease, suggesting that there may be common pathways and shared risk factors.

Antedependence models for nonstationary categorical longitudinal data with ignorable missingness: likelihood-based inference.

Time index-ordered random variables are said to be antedependent (AD) of order (p1 ,p2 , … ,pn ) if the kth variable, conditioned on the pk immediately preceding variables, is independent of all further preceding variables. Inferential methods associated with AD models are well developed for continuous (primarily normal) longitudinal data, but not for categorical longitudinal data. In this article, we develop likelihood-based inferential procedures for unstructured AD models for categorical longitudinal data. Specifically, we derive maximum likelihood estimators (MLEs) of model parameters; penalized likelihood criteria and likelihood ratio tests for determining the order of antedependence; and likelihood ratio tests for homogeneity across groups, time invariance of transition probabilities, and strict stationarity. We give closed-form expressions for MLEs and test statistics, which allow for the possibility of empty cells and monotone missing data, for all cases save strict stationarity. For data with an arbitrary missingness pattern, we derive an efficient restricted expectation-maximization algorithm for obtaining MLEs. We evaluate the performance of the tests by simulation. We apply the methods to longitudinal studies of toenail infection severity (measured on a binary scale) and Alzheimer's disease severity (measured on an ordinal scale). The analysis of the toenail infection severity data reveals interesting nonstationary behavior of the transition probabilities and indicates that an unstructured first-order AD model is superior to stationary and other structured first-order AD models that have previously been fit to these data. The analysis of the Alzheimer's severity data indicates that the antedependence is second order with time-invariant transition probabilities, suggesting the use of a second-order autoregressive cumulative logit model.

A crossed random effects modeling approach for estimating diagnostic accuracy from ordinal ratings without a gold standard.

In diagnostic studies without a gold standard, the assumption on the dependence structure of the multiple tests or raters plays an important role in model performance. In case of binary disease status, both conditional independence and crossed random effects structure have been proposed and their performance investigated. Less attention has been paid to the situation where the true disease status is ordinal. In this paper, we propose crossed subject-specific and rater-specific random effects to account for the dependence structure and assess the robustness of the proposed model to misspecification in the random effects distributions. We applied the models to data from the Physician Reliability Study, which focuses on assessing the diagnostic accuracy in a population of raters for the staging of endometriosis, a gynecological disorder in women. Using this new methodology, we estimate the probability of a correct classification and show that regional experts can more easily classify the intermediate stage than resident physicians.

Moisture-Tailored 2D Dion-Jacobson Perovskites for Reconfigurable Optoelectronics.

Humidity- and moisture-induced degradation has been a longstanding problem in perovskite materials, affecting their long-term stability during applications. Counterintuitively, the moisture is leveraged to tailor the reversible hydrochromic behaviors of a new series of 2D Dion-Jacobson (DJ) perovskites for reconfigurable optoelectronics. In particular, the hydrogen bonds between organic cations and water molecules can be dynamically modulated via moisture removal/exposure. Remarkably, such modulation confines the movement of the organic cations close to the original position, preventing their escape from crystal lattices. Furthermore, this mechanism is elucidated by theoretical analysis using first-principles calculations and confirmed with the experimental characterizations. The reversible fluorescent transition 2D DJ perovskites show excellent cyclical properties, presenting untapped opportunities for reconfigurable optoelectronic applications. As a proof-of-concept demonstration, an anti-counterfeiting display is shown based on patterned reversible 2D DJ perovskites. The results represent a new avenue of reconfigurable optoelectronic application with 2D DJ perovskites for humidity detection, anti-counterfeiting, sensing, and other emerging photoelectric intelligent technologies.

Antiferromagnetic to Ferrimagnetic Phase Transition and Possible Phase Coexistence in Polar Magnets (Fe1-xMnx)2Mo3O8 (0 ≤ x ≤ 1).

In the present work, the magnetic properties of a single crystal (Fe1-xMnx)2Mo3O8 (0 ≤ x ≤ 1) have been studied by performing extensive measurements. A detailed magnetic phase diagram is built up, in which the antiferromagnetic state dominates for x ≤ 0.25 and the ferrimagnetic phase arises for x ≥ 0.3. Meanwhile, a sizeable electric polarization of spin origin is commonly observed in all samples, no matter what the magnetic state is. For the samples hosting a ferrimagnetic state, square-like magnetic hysteresis loops are revealed, while the remnant magnetization and coercive field can be tuned drastically by simply varying the Mn content or temperature. A possible coexistence of the antiferromagnetic and ferrimagnetic phases is proposed to be responsible for the remarkable modulation of magnetic properties in the samples.

EEG classification across sessions and across subjects through transfer learning in motor imagery-based brain-machine interface system.

Transfer learning enables the adaption of models to handle mismatches of distributions across sessions or across subjects. In this paper, we proposed a new transfer learning algorithm to classify motor imagery EEG data. By analyzing the power spectrum of EEG data related to motor imagery, the shared features across sessions or across subjects, namely, the mean and variance of model parameters, are extracted. Then, select the data sets that were most relevant to the new data set according to Euclidean distance to update the shared features. Finally, utilize the shared features and subject/session-specific features jointly to generate a new model. We evaluated our algorithm by analyzing the motor imagery EEG data from 10 healthy participants and a public data set from BCI competition IV. The classification accuracy of the proposed transfer learning is higher than that of traditional machine learning algorithms. The results of the paired t test showed that the classification results of PSD and the transfer learning algorithm were significantly different (p = 2.0946e-9), and the classification results of CSP and the transfer learning algorithm were significantly different (p = 1.9122e-6). The test accuracy of data set 2a of BCI competition IV was 85.7% ± 5.4%, which was higher than that of related traditional machine learning algorithms. Preliminary results suggested that the proposed algorithm can be effectively applied to the classification of motor imagery EEG signals across sessions and across subjects and the performance is better than that of the traditional machine learning algorithms. It can be promising to be applied to the field of brain-computer interface (BCI). Graphical abstract.

Anxiety and Depression Diagnosis Method Based on Brain Networks and Convolutional Neural Networks.

At present, only professional doctors can use the professional scales to diagnose depression and anxiety in clinical practice. In recent years, the problems of detecting the presence of anxiety or depression using Electroencephalography (EEG) has received attention as a way to implement assistant diagnosis, and some researchers explored that there are differences in the degree of prefrontal lateralization and functional connectivity of brain networks between patients with anxiety and depression and normal people. In this paper, we proposed a new approach that combines functional connectivity of brain networks and convolutional neural networks (CNN) for EEG-based anxiety and depression recognition. EEG data are collected from subjects consisting ten healthy controls and ten patients with anxiety or depression. In this way, we achieved 67.67% classification accuracy. It points out the way to further explore the application of functional connectivity of brain networks and deep learning technology in EEG about patients with anxiety and depression.

Electro-opto-mechano driven reversible multi-state memory devices based on photocurrent in Bi0.9Eu0.1FeO3/La0.67Sr0.33MnO3/PMN-PT heterostructures.

A single device with extensive new functionality is highly attractive for the increasing demands for complex and multifunctional optoelectronics. Multi-field coupling has been drawing considerable attention because it leads to materials that can be simultaneously operated under several external stimuli (e.g. magnetic field, electric field, electric current, light, strain, etc.), which allows each unit to store multiple bits of information and thus enhance the memory density. In this work, we report an electro-opto-mechano-driven reversible multi-state memory device based on photocurrent in Bi0.9Eu0.1FeO3 (BEFO)/La0.67Sr0.33MnO3 (LSMO)/0.7Pb(Mg1/3Nb2/3)O3-0.3PbTiO3 (PMN-PT) heterostructures. It is found that the short-circuit current density (J sc) can be switched by the variation of the potential barrier height and depletion region width at the Pt/BEFO interface modulated by light illumination, external strain, and ferroelectric polarization reversal. This work opens up pathways toward the emergence of novel device design features with dynamic control for developing high-performance electric-optical-mechanism integrated devices based on the BiFeO3-based heterostructures.

Parental health status and infant outcomes: Upstate KIDS Study.

OBJECTIVE: To assess parental health status inclusive of infertility and infant outcomes. DESIGN: Birth cohort with cross-sectional analysis of parental health status and infant outcomes. SETTING: Not applicable. PATIENT(S): Parents (n = 4,886) and infants (n = 5,845) participating in the Upstate KIDS birth cohort. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Infertility was defined as [1] sexually active without contraception for 1+ years without pregnancy, [2] ever requiring ≥12 months to become pregnant, and [3] requiring ≥12 months for index pregnancy. Multivariable linear regression with generalized estimating equations estimated the change (ß coefficient and 95% confidence interval [CI]) in infant outcomes (gestation, birthweight, length, head circumference, ponderal index) and relative to each disease, including infertility after adjusting for age, body mass index, and infertility treatment. RESULT(S): Prevalence of parental chronic diseases ranged from <1% to 19%, and 21% to 54% for infertility. Maternal hypertension was negatively associated with gestation (ß, -0.64; 95% CI, -1.03, -0.25) and birthweight (-151.98; -262.30, -41.67) as was asthma and birthweight (-75.01; -130.40, -19.62). Maternal kidney disease was associated with smaller head circumference (-1.09; -2.17, -0.01), whereas paternal autoimmune disease was associated with larger head circumference (0.87; 0.15, 1.60). Infertility was negatively associated with birthweight (-62.18; -103.78, -20.58), length (-0.33; -0.60, -0.06), and head circumference (-0.35; -0.67, -0.03). CONCLUSION(S): Infertility was significantly associated with reduced infant size even after accounting for infertility treatment, although the magnitude of reduction varied by definition of infertility. Absence of pregnancy within a year of being at risk may be informative about health.

Parental Obesity and Early Childhood Development.

BACKGROUND: Previous studies identified associations between maternal obesity and childhood neurodevelopment, but few examined paternal obesity despite potentially distinct genetic/epigenetic effects related to developmental programming. METHODS: Upstate KIDS (2008-2010) recruited mothers from New York State (excluding New York City) at ∼4 months postpartum. Parents completed the Ages and Stages Questionnaire (ASQ) when their children were 4, 8, 12, 18, 24, 30, and 36 months of age corrected for gestation. The ASQ is validated to screen for delays in 5 developmental domains (ie, fine motor, gross motor, communication, personal-social functioning, and problem-solving ability). Analyses included 3759 singletons and 1062 nonrelated twins with ≥1 ASQs returned. Adjusted odds ratios (aORs) and 95% confidence intervals were estimated by using generalized linear mixed models accounting for maternal covariates (ie, age, race, education, insurance, marital status, parity, and pregnancy smoking). RESULTS: Compared with normal/underweight mothers (BMI <25), children of obese mothers (26% with BMI ≥30) had increased odds of failing the fine motor domain (aOR 1.67; confidence interval 1.12-2.47). The association remained after additional adjustment for paternal BMI (1.67; 1.11-2.52). Paternal obesity (29%) was associated with increased risk of failing the personal-social domain (1.75; 1.13-2.71), albeit attenuated after adjustment for maternal obesity (aOR 1.71; 1.08-2.70). Children whose parents both had BMI ≥35 were likely to additionally fail the problem-solving domain (2.93; 1.09-7.85). CONCLUSIONS: Findings suggest that maternal and paternal obesity are each associated with specific delays in early childhood development, emphasizing the importance of family information when screening child development.

Fabrication of zeolite-4A membranes on a catalyst particle level.

Zeolite-4A membranes are coated onto spherical Pt/gamma-Al2O3 particles with an average diameter of 1.5 mm, and a model oxidation reaction of a mixture of CO and n-butane (50 : 50) is used to demonstrate the concept of reactant selectivity via the coated defect-free membranes.