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At present, the Si3N4 powder prepared is not pure enough. Therefore, this work introduces a novel method of preparing high‐purity α‐Si3N4 powder. Si3N4 powder with high α phase content was prepared via a unique two‐stage temperature‐rise (TSTR) process, using KCl and metal Co as dual catalysts through low‐temperature pretreatment for silicon powder and subsequent high‐temperature nitriding reaction. Molten KCl insulates silicon particles in three contact modes during low‐temperature pretreatment, promoting complete and uniform nitriding and absorbing the heat released during the reaction. In addition, Co forms a Co–Si liquid phase, causing the reaction to transition into a gas–liquid–solid reaction with lower potential energy, thereby reducing the reaction temperature. Through the synergistic effect of the two catalysts and optimized unique TSTR process, Si3N4 powder can be obtained at 1250°C, boasting a remarkably high α phase content of 99.1%, distinguished by its layered, needle‐like, and spherical structures. The detailed experiments first provide a comprehensive explanation of the growth mechanism of α‐Si3N4. This innovative method for preparing Si3N4 powder offers a new approach to the facile production of high‐purity phase ceramic powder. [ABSTRACT FROM AUTHOR]

With the continuous development of green energy, society is increasingly demanding advanced energy storage devices. Manganese-based asymmetric supercapacitors (ASCs) can deliver high energy density while possessing high power density. However, the structural instability hampers the wider application of manganese dioxide in ASCs. A novel MnO2-based electrode material was designed in this study. We synthesized a MnO2/carbon cloth electrode, CC@NMO, with NH4+ ion pre-intercalation through a one-step hydrothermal method. The pre-intercalation of NH4+ stabilizes the MnO2 interlayer structure, expanding the electrode stable working potential window to 0–1.1 V and achieving a remarkable mass specific capacitance of 181.4 F g−1. Furthermore, the ASC device fabricated using the CC@NMO electrode and activated carbon electrode exhibits excellent electrochemical properties. The CC@NMO//AC achieves a high energy density of 63.49 Wh kg−1 and a power density of 949.8 W kg−1. Even after cycling 10,000 times at 10 A g−1, the device retains 81.2% of its capacitance. This work sheds new light on manganese dioxide-based asymmetric supercapacitors and represents a significant contribution for future research on them. [ABSTRACT FROM AUTHOR]

In order to improve the longitudinal and lateral stability of hub motor driven vehicle, a method was proposed to combine the yaw control and anti-skid control of the vehicle. The joint control model of longitudinal and lateral stability was built by the layered control architecture. The upper layer was the moment decision layer. The longitudinal vehicle speed tracking controller was constructed based on proportion-integral- derivative (PID) control algorithm. The driving anti-skid controller was built based on fuzzy PID control algorithm, and the driving anti-skid torque was determined by feedforward and feedback control method. The direct yaw moment controller was established based on the second order sliding mode control algorithm, and additional yaw moment weighted module was designed to control the yaw characteristics of the vehicle. The lower layer was the moment distribution layer. The total longitudinal moment, driving anti-skid moment and direct yaw moment determined by the upper layer were reasonably distributed to the four wheels by the optimization distribution algorithm. The availability of the proposed method was verified by the acceleration and steering co-simulation conditions. The results show that the maximum slip rate of the wheel is about 0.15, the maximum deviation of yaw rate is about 0. 01 rad/s, and the maximum deviation of sideslip angle is about 0. 011 rad, which verifies the availability of the control strategy. [ABSTRACT FROM AUTHOR]

Objective: With the growing demand for sharing clinical trial data, scalable methods to enable privacy protective access to high-utility data are needed. Data synthesis is one such method. Sequential trees are commonly used to synthesize health data. It is hypothesized that the utility of the generated data is dependent on the variable order. No assessments of the impact of variable order on synthesized clinical trial data have been performed thus far. Through simulation, we aim to evaluate the variability in the utility of synthetic clinical trial data as variable order is randomly shuffled and implement an optimization algorithm to find a good order if variability is too high.Materials and Methods: Six oncology clinical trial datasets were evaluated in a simulation. Three utility metrics were computed comparing real and synthetic data: univariate similarity, similarity in multivariate prediction accuracy, and a distinguishability metric. Particle swarm was implemented to optimize variable order, and was compared with a curriculum learning approach to ordering variables.Results: As the number of variables in a clinical trial dataset increases, there is a pattern of a marked increase in variability of data utility with order. Particle swarm with a distinguishability hinge loss ensured adequate utility across all 6 datasets. The hinge threshold was selected to avoid overfitting which can create a privacy problem. This was superior to curriculum learning in terms of utility.Conclusions: The optimization approach presented in this study gives a reliable way to synthesize high-utility clinical trial datasets. [ABSTRACT FROM AUTHOR]

Background: Sorafenib and sunitinib are oral vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors (TKIs) approved in 2005 and 2006, respectively, for the treatment of patients with renal cell carcinoma (RCC). A population-based, observational cohort study of the cardiovascular risk of VEGFR TKI therapy in elderly RCC patients was conducted.Methods: Using the Surveillance, Epidemiology, and End Results-Medicare database, this study analyzed patients who were 66 years old or older and were diagnosed with RCC from 2000 to 2009. The incidence of cardiovascular adverse events, including congestive heart failure and cardiomyopathy (CHF/CM), acute myocardial infarction (AMI), stroke, and cardiovascular deaths, was examined through December 2010. A Cox proportional hazards model was created to calculate the hazard ratio (HR), and adjustments were made for age, sex, comorbidity, and the use of other systemic therapy.Results: A total of 171 of 670 patients who received sunitinib or sorafenib had cardiovascular events. The incidence rates for CHF/CM, AMI, and stroke were 0.87, 0.14, and 0.14 per 1000 person-days, respectively. Sunitinib or sorafenib use was associated with an increased risk of cardiovascular events (HR, 1.38; 95% confidence interval [CI], 1.02-1.87) and especially stroke (HR, 2.84; 95% CI, 1.52-5.31) in comparison with 788 patients diagnosed with advanced RCC from 2007 to 2009 who were eligible for Part D but did not receive either agent. In subgroup analyses, patients who were 66 to 74 years old at diagnosis had the highest increased risk of stroke associated with the use of either or both drugs.Conclusions: Sunitinib and sorafenib might be associated with an increased risk of cardiovascular events and particularly stroke. [ABSTRACT FROM AUTHOR]

Objective: To determine the geographic variability of Medicaid acceptance among allergists in the US., Study Design: Geospatial analysis predicted Medicaid acceptance across space, and a multivariable regression identified area-level population demographic variables associated with acceptance., Methods: We used the National Plan & Provider Enumeration System database to identify allergists. Medicaid acceptance was determined from lists or search engines from state Medicaid offices and calls to provider offices. Spatial analysis was performed using the empirical Bayesian kriging tool. Multivariate logistic regression was used to identify county-level characteristics associated with provider Medicaid acceptance., Results: Of 5694 allergists, 55.5% accepted Medicaid. Acceptance in each state ranged from 13% to 90%. Washington, Arizona, and the Northeast had lowest predicted proportion of both Medicaid acceptance and Medicaid acceptance per 10,000 enrollees. Overall, county-level characteristics were not associated with the likelihood of accepting Medicaid in multivariate analyses. Only the percentage of individuals living in poverty was associated with a higher likelihood of providers accepting Medicaid (OR, 1.245; 95% CI, 1.156-1.340; P < .001)., Conclusions: A barrier to accessing allergy-related health care is finding a provider who accepts a patient's insurance, which is largely variable by state. Lack of access to allergy care likely affects health outcomes for children with prevalent atopic conditions such as food allergy.