β-relaxation has long been attributed to localized motion of constituent molecules or atoms confined to isolated regions in glasses. However, direct experimental evidence to support this spatially ...heterogeneous scenario is still missing. Here we report the evolution of nanoscale structural heterogeneity in a metallic glass during β-relaxation by utilizing amplitude-modulation dynamic atomic force microscopy. The successive degeneration of heterogeneity during β-relaxation can be well described by the Kohlrausch-Williams-Watts equation. The characteristic relaxation time and activation energy of the heterogeneity evolution are in accord with those of excess enthalpy release by β-relaxation. Our study correlates β-relaxation with nanoscale spatial heterogeneity and provides direct evidence on the structural origins of β-relaxation in metallic glasses.
Regulatory T cells (T
) are specialized in immune suppression and play a dominant role in peripheral immune tolerance. T
cell lineage development and function maintenance is determined by the ...forkhead box protein 3 (FoxP3) transcriptional factor, whose activity is fine-tuned by its post-translational modifications (PTMs) and interaction partners. In this review, we summarize current studies in the crystal structures, the PTMs and interaction partners of FoxP3 protein, and discuss how these insights may provide a roadmap for new approaches to modulate T
suppression, and new therapies to enhance immune tolerance in autoimmune diseases.
The purpose of this study was to identify individual and residency program factors associated with increased suicide risk, as measured by suicidal ideation. We utilized a prospective, longitudinal ...cohort study design to assess the prevalence and predictors of suicidal ideation in 6,691 (2012-2014 cohorts, training data set) and 4,904 (2015 cohort, test data set) first-year training physicians (interns) at hospital systems across the United States. We assessed suicidal ideation two months before internship and then quarterly through intern year. The prevalence of reported suicidal ideation in the study population increased from 3.0% at baseline to a mean of 6.9% during internship. 16.4% of interns reported suicidal ideation at least once during their internship. In the training dataset, a series of baseline demographic (male gender) and psychological factors (high neuroticism, depressive symptoms and suicidal ideation) were associated with increased risk of suicidal ideation during internship. Further, prior quarter psychiatric symptoms (depressive symptoms and suicidal ideation) and concurrent work-related factors (increase in self-reported work hours and medical errors) were associated with increased risk of suicidal ideation. A model derived from the training dataset had a predicted area under the Receiver Operating Characteristic curve (AUC) of 0.83 in the test dataset. The suicidal ideation risk predictors analyzed in this study can help programs and interns identify those at risk for suicidal ideation before the onset of training. Further, increases in self-reported work hours and environments associated with increased medical errors are potentially modifiable factors for residency programs to target to reduce suicide risk.
Stratification is a very commonly used approach in biomedical studies to handle sample heterogeneity arising from, for examples, clinical units, patient subgroups, or missing‐data. A key rationale ...behind such approach is to overcome potential sampling biases in statistical inference. Two issues of such stratification‐based strategy are (i) whether individual strata are sufficiently distinctive to warrant stratification, and (ii) sample size attrition resulted from the stratification may potentially lead to loss of statistical power. To address these issues, we propose a penalized generalized estimating equations approach to reducing the complexity of parametric model structures due to excessive stratification. Specifically, we develop a data‐driven fusion learning approach for longitudinal data that improves estimation efficiency by integrating information across similar strata, yet still allows necessary separation for stratum‐specific conclusions. The proposed method is evaluated by simulation studies and applied to a motivating example of psychiatric study to demonstrate its usefulness in real world settings.
We propose a distributed method for simultaneous inference for datasets with sample size much larger than the number of covariates, i.e., N≫p, in the generalized linear models framework. When such ...datasets are too big to be analyzed entirely by a single centralized computer, or when datasets are already stored in distributed database systems, the strategy of divide-and-combine has been the method of choice for scalability. Due to partition, the sub-dataset sample sizes may be uneven and some possibly close to p, which calls for regularization techniques to improve numerical stability. However, there is a lack of clear theoretical justification and practical guidelines to combine results obtained from separate regularized estimators, especially when the final objective is simultaneous inference for a group of regression parameters. In this paper, we develop a strategy to combine bias-corrected lasso-type estimates by using confidence distributions. We show that the resulting combined estimator achieves the same estimation efficiency as that of the maximum likelihood estimator using the centralized data. As demonstrated by simulated and real data examples, our divide-and-combine method yields nearly identical inference as the centralized benchmark.
Physics related to fast electrons in lower hybrid (LH) current drive (LHCD) plasma is a very important issue, since these particles will play an important role in runaway electron (RE) generation and ...lower hybrid wave (LHW)-related physics. Utilizing a new hard X-ray (HXR) pinhole camera, recent HL-2A tokamak experiments have devoted to enhancing the understanding of the physics on fast electrons and LHW. The fast electron bremsstrahlung (FEB) emission in the HXR energy range between 20 and 200 keV was measured by the HXR camera. To study the conversion of LHW-produced fast electrons into REs, a very short pulse of LHW, so-called “blip”, with duration of 5 ms was injected into the plasma during the current flattop phase. A strong enhancement of REs was induced by the blip injection. Measurements from the HXR camera show that the fast electrons generated by LHWs is mainly concentrated in 40-60 keV, which is well consistent with the calculated value based on Landau damping theory. The energy of these seed electrons is higher than the critical runaway energy. This phenomenon may be come from the synergetic effects of Dreicer and avalanche RE generation. Moreover, the measurements indicate that the spatial distribution of the fast electrons during LHCD has a peaked profile, implying that the fast electrons are mainly produced in the plasma core. It also suggests that the energy of the LHW mainly deposited in the plasma core region.
As proof of concept, we simulate a revised kidney allocation system that includes deceased donor (DD) kidneys as chain‐initiating kidneys (DD‐CIK) in a kidney paired donation pool (KPDP), and ...estimate potential increases in number of transplants. We consider chains of length 2 in which the DD‐CIK gives to a candidate in the KPDP, and that candidate's incompatible donor donates to theDD waitlist. In simulations, we vary initial pool size, arrival rates of candidate/donor pairs and (living) nondirected donors (NDDs), and delay time from entry to the KPDP until a candidate is eligible to receive a DD‐CIK. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Kidney Donation, and the actual DDs from the Scientific Registry of Transplant Recipients (SRTR) data, simulations extend over 2 years. With an initial pool of 400, respective candidate and NDD arrival rates of 2 per day and 3 per month, and delay times for access to DD‐CIK of 6 months or less, including DD‐CIKs increases the number of transplants by at least 447 over 2 years, and greatly reduces waiting times of KPDP candidates. Potential effects on waitlist candidates are discussed as are policy and ethical issues.
The authors suggest, after simulating allocation changes that would divert some deceased donor kidneys into kidney paired exchange programs, that transplant numbers can increase by several hundreds annually. See an editorial from Turgeon on page 5.
Electron microscope was utilized to detect the nucleation of grain boundary carbides in Haynes 282 Ni-based superalloy during creep. Besides, first-principles calculations were conducted to ...comprehensively explore the site preference of alloying elements during the nucleation as well as the effect of tensile strain on the site preference behaviors. Experiment indicates that Mo atoms will segregate to the M.sub.23C.sub.6/Ni interface, which promotes the nucleation of grain boundary M.sub.6C at the interface, during creep. Therefore, the site preference of Mo at the M.sub.23C.sub.6/Ni interface was calculated. The results show that the segregated Mo atoms prefer to occupy the Cr sites rather than the Ni sites. Mo will occupy the two layers of Cr sites near the interface in an alternating way. Tensile strain as well as its directions can seriously influence the site preference of Mo at the interface, while the strains with directions of 001, 101 and 111 only affect the occupation sequence of Mo, the strains with directions of 110 and 100 will inhibit the segregation of Mo by increasing segregation energy. Therefore, in general, tensile strain inhibits the segregation of Mo to the M.sub.23C.sub.6/Ni interface and thus the nucleation of M.sub.6C at the interface.
Directed acyclic mixed graphs (DAMGs) provide a useful representation of network topology with both directed and undirected edges subject to the restriction of no directed cycles in the graph. This ...graphical framework may arise in many biomedical studies, for example, when a directed acyclic graph (DAG) of interest is contaminated with undirected edges induced by some unobserved confounding factors (eg, unmeasured environmental factors). Directed edges in a DAG are widely used to evaluate causal relationships among variables in a network, but detecting them is challenging when the underlying causality is obscured by some shared latent factors. The objective of this paper is to develop an effective structural equation model (SEM) method to extract reliable causal relationships from a DAMG. The proposed approach, termed structural factor equation model (SFEM), uses the SEM to capture the network topology of the DAG while accounting for the undirected edges in the graph with a factor analysis model. The latent factors in the SFEM enable the identification and removal of undirected edges, leading to a simpler and more interpretable causal network. The proposed method is evaluated and compared to existing methods through extensive simulation studies, and illustrated through the construction of gene regulatory networks related to breast cancer.
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