Neural Approximate Sufficient Statistics for Implicit Models

We consider the fundamental problem of how to automatically construct summary statistics for implicit generative models where the evaluation of the likelihood function is intractable, but sampling data from the model is possible. The idea is to frame the task of constructing sufficient statistics as learning mutual information maximizing representations of the data with the help of deep neural networks. The infomax learning procedure does not need to estimate any density or density ratio. We apply our approach to both traditional approximate Bayesian computation and recent neural likelihood methods, boosting their performance on a range of tasks.Comment: ICLR2021 spotligh

Non-linear relationship between red blood cell distribution width and gastrointestinal bleeding risk in stroke patients: results from multi-center ICUs

BackgroundThe red blood cell distribution width (RDW) is closely linked to the prognosis of multiple diseases. However, the connection between RDW and gastrointestinal bleeding (GIB) in stroke patients is not well understood. This study aimed to clarify this association.MethodsThis retrospective study involved 11,107 hospitalized patients from 208 hospitals in the United States, admitted between January 1, 2014, and December 31, 2015. We examined clinical data from 7,512 stroke patients in the intensive care unit (ICU). Multivariate logistic regression assessed the link between RDW and in-hospital GIB in stroke patients. Generalized additive model (GAM) and smooth curve fitting (penalty spline method) were utilized to explore the non-linear relationship between RDW and GIB in stroke patients. The inflection point was calculated using a recursive algorithm, and interactions between different variables were assessed through subgroup analyses.ResultsAmong the 11,107 screened stroke patients, 7,512 were included in the primary analysis, with 190 identified as having GIB. The participants had a mean age of (61.67 ± 12.42) years, and a median RDW of 13.9%. Multiple logistic analysis revealed RDW as a risk factor for in-hospital GIB in stroke patients (OR = 1.28, 95% CI 1.21, 1.36, p < 0.05). The relationship between RDW and in-hospital GIB in stroke patients was found to be non-linear. Additionally, the inflection point of RDW was 14.0%. When RDW was ≥14.0%, there was a positive association with the risk of GIB (OR: 1.24, 95% CI: 1.16, 1.33, p < 0.0001). Conversely, when RDW was <14.0%, this association was not significant (OR: 1.02, 95% CI: 0.97–1.07, p = 0.4040).ConclusionThis study showed a substantial non-linear link between RDW and the risk of GIB in stroke patients. Maintaining the patient’s RDW value below 14.0% could lower the risk of in-hospital GIB

Individualized music induces theta-gamma phase-amplitude coupling in patients with disorders of consciousness

ObjectiveThis study aimed to determine whether patients with disorders of consciousness (DoC) could experience neural entrainment to individualized music, which explored the cross-modal influences of music on patients with DoC through phase-amplitude coupling (PAC). Furthermore, the study assessed the efficacy of individualized music or preferred music (PM) versus relaxing music (RM) in impacting patient outcomes, and examined the role of cross-modal influences in determining these outcomes.MethodsThirty-two patients with DoC [17 with vegetative state/unresponsive wakefulness syndrome (VS/UWS) and 15 with minimally conscious state (MCS)], alongside 16 healthy controls (HCs), were recruited for this study. Neural activities in the frontal–parietal network were recorded using scalp electroencephalography (EEG) during baseline (BL), RM and PM. Cerebral-acoustic coherence (CACoh) was explored to investigate participants’ abilitiy to track music, meanwhile, the phase-amplitude coupling (PAC) was utilized to evaluate the cross-modal influences of music. Three months post-intervention, the outcomes of patients with DoC were followed up using the Coma Recovery Scale-Revised (CRS-R).ResultsHCs and patients with MCS showed higher CACoh compared to VS/UWS patients within musical pulse frequency (p = 0.016, p = 0.045; p < 0.001, p = 0.048, for RM and PM, respectively, following Bonferroni correction). Only theta-gamma PAC demonstrated a significant interaction effect between groups and music conditions (F(2,44) = 2.685, p = 0.036). For HCs, the theta-gamma PAC in the frontal–parietal network was stronger in the PM condition compared to the RM (p = 0.016) and BL condition (p < 0.001). For patients with MCS, the theta-gamma PAC was stronger in the PM than in the BL (p = 0.040), while no difference was observed among the three music conditions in patients with VS/UWS. Additionally, we found that MCS patients who showed improved outcomes after 3 months exhibited evident neural responses to preferred music (p = 0.019). Furthermore, the ratio of theta-gamma coupling changes in PM relative to BL could predict clinical outcomes in MCS patients (r = 0.992, p < 0.001).ConclusionIndividualized music may serve as a potential therapeutic method for patients with DoC through cross-modal influences, which rely on enhanced theta-gamma PAC within the consciousness-related network

Microstructure and Mechanical Properties of Ni-Based Complex Concentrated Alloys under Radiation Environment

The rapid development of fusion-reactor technology calls for excellent anti-irradiation materials. Complex concentrated alloy (CCA) is a newly proposed alloy concept which is a promising candidate of nuclear fusion materials by virtue of its great phase stability under irradiation. This article summarizes anti-radiation mechanism and the microstructure evolution in HEAs. The effective factors on irradiation behavior of HEAs, including entropy, sample size and temperature, are discussed. Finally, the article introduces the potential ways to solve the economic and environmental problems which the HEAs faced for their applications in the future. In summary, the HEAs usually show better irradiation resistance than traditional alloys, such as less swelling, smaller size of defects, and more stable mechanical properties. One possible reason for the irradiation resistance of HEA is the self-healing effect induced by the high-entropy and atomic-level stress among the metal atoms. The activation of the principal element should be considered when selecting components of HEA, and the high throughput technique is a potential way to reduce the design and fabrication cost of HEAs. It is reasonable to expect that coming years will see the application of novel HEAs in fusion reactors

In-situ synthesized a dual-scale Ti2AlC reinforced TiAl composites with superior mechanical properties

To enhance the mechanical properties and service temperature of TiAl alloy, the dual-scale Ti2AlC particles reinforced TiAl composites were successfully designed and fabricated by spark plasma sintering (SPS), utilizing pre-alloyed Ti–48Al–2Nb–2Cr powder and multi-walled carbon nanotubes. The TiAl composites exhibited a fully lamellar structure, with micro-laminated Ti2AlC particles formed at grain boundaries and nano-laminated Ti2AlC particles precipitated at the interfaces of α2 and γ lamellae by adding 0.5 wt% multi-walled carbon nanotubes. The TiAl composites exhibited excellent mechanical properties at room temperature and elevated temperatures. The ultrahigh tensile strength of TiAl composite was 599.6 MPa at 800 °C which was improved by 28.3 % compared with TiAl matrix, while the fracture strain remained 4.2 % without sacrifice. These superior mechanical properties were mainly attributed to the refinement strengthening, solid solution strengthening, and the formation of dual-scale Ti2AlC particles. Moreover, the dual-scale Ti2AlC particles reinforced α2 and γ lamellar interfaces and lamellar colony boundaries resulting in improvement of strength and toughness simultaneously. The TiAl composite was reinforced by dual-scale Ti2AlC particles, which expected to further break the property limitation of TiAl alloy and expanded its application at high temperature

GrOD: deep learning with gradients orthogonal decomposition for knowledge transfer, distillation, and adversarial training

Regularization that incorporates the linear combination of empirical loss and explicit regularization terms as the loss function has been frequently used for many machine learning tasks. The explicit regularization term is designed in different types, depending on its applications. While regularized learning often boost the performance with higher accuracy and faster convergence, the regularization would sometimes hurt the empirical loss minimization and lead to poor performance. To deal with such issues in this work, we propose a novel strategy, namely Gradients Orthogonal Decomposition (GrOD), that improves the training procedure of regularized deep learning. Instead of linearly combining gradients of the two terms, GrOD re-estimates a new direction for iteration that does not hurt the empirical loss minimization while preserving the regularization affects, through orthogonal decomposition. We have performed extensive experiments to use GrOD improving the commonly used algorithms of transfer learning [2], knowledge distillation [3], and adversarial learning [4]. The experiment results based on large datasets, including Caltech 256 [5], MIT indoor 67 [6], CIFAR-10 [7], and ImageNet [8], show significant improvement made by GrOD for all three algorithms in all cases.</p

Elevated platelet count is associated with decreased mortality from hemorrhagic stroke in hospital: a multi-center retrospective cohort study

Abstract This study aimed to investigate the relationship between platelet count (PC) and mortality in patients with hemorrhagic stroke (HS). The research reviewed data from 10,466 patients hospitalized in 208 hospitals in the United States from January 1, 2014, to December 31, 2015. Of these, 3262 HS patients were included in the primary analysis for those admitted to the intensive care unit (ICU). The average age of these patients was 67.05 years, with 52.79% being male. The median PC was (221.67 ± 73.78) × 109/L. Multivariate logistic regression analysis revealed that PC was a protective factor for mortality in HS patients (OR = 0.98, 95% CI 0.97–1.00, P < 0.05). Additionally, a non-linear association between PC and mortality in HS patients was found using a generalized additive model (GAM) and smooth curve fitting (penalty spline method). For the first time, a recursive algorithm identified the inflection point of platelet count as 194 × 109/L. On the left side of the inflection point, for every increase of 10 units in platelet count, the mortality rate of HS patients decreases by 10%. The study demonstrates a non-linear relationship between PC and the risk of mortality in HS patients. A platelet counts higher than the inflection point (194 × 109/L) may be a significant intervention to reduce mortality in HS patients