Natural Hollow Fiber-Derived Carbon Microtube with Broadband Microwave Attenuation Capacity.

Constructing hierarchical structures is indispensable to tuning the electromagnetic properties of carbon-based materials. Here, carbon microtubes with nanometer wall thickness and micrometer diameter were fabricated by a feasible approach with economical and sustainable kapok fiber. The carbonized kapok fiber (CKF) exhibits microscale pores from the inherent porous templates as well as pyrolysis-induced nanopores inside the wall, affording the hierarchical carbon microtube with excellent microwave absorbing performance over broad frequency. Particularly, CKF-650 exhibits an optimized reflection loss (RL) of −62.46 dB (10.32 GHz, 2.2 mm), while CKF-600 demonstrates an effective absorption bandwidth (RL < −10 dB) of 6.80 GHz (11.20−18.00 GHz, 2.8 mm). Moreover, more than 90% of the incident electromagnetic wave ranging from 2.88 GHz to 18.00 GHz can be dissipated by simply controlling the carbonization temperature of KF and/or the thickness of the carbon-microtube-based absorber. These encouraging findings provide a facile alternative route to fabricate microwave absorbers with broadband attenuation capacity by utilizing sustainable biomass.

[TiRobot-assisted percutaneous sacroiliac cannulated screw fixation for posterior pelvic ring injury with sacral variations].

Objective: To investigate the effectiveness of TiRobot-assisted percutaneous sacroiliac cannulated screw fixation in the treatment of posterior pelvic ring injuries with sacral variations, and to evaluate its feasibility and safety. Methods: The clinical data of 7 patients with Tile type C pelvic fractures and sacral variations treated with TiRobot-assisted percutaneous sacroiliac cannulated screw fixation between January 2020 and June 2021 were retrospectively analyzed. There were 5 males and 2 females with an average age of 36 years (range, 17-56 years). The causes of injury were traffic accident in 4 cases and falling from height in 3 cases. According to Tile classification of pelvic fractures, there were 1 case of type C1.1, 1 case of type C1.2, and 5 cases of type C1.3; according to Denis classification of sacral fractures, there were 3 cases of zone Ⅰ and 4 cases of zone Ⅱ; sacral deformities included 3 cases of lumbar sacralization, 2 cases of sacral lumbarization, and 2 cases of accessory auricular surface of the sacrum. The time from injury to operation ranged from 2 to 7 days, with an average of 4.6 days. The implantation time of each screw, the fluoroscopy times of each guide pin, the quality of fracture reduction (according to Matta score), the excellent and good rate of screw position, the healing time of fracture, and the incidence of complications were recorded, and the effectiveness was evaluated by Majeed score. Results: A total of 13 screws were implanted during the operation, the implantation time of each screw was 10-23 minutes, with an average of 18.2 minutes; the position of the guide pin was good, and no guide pin was adjusted, the fluoroscopy times of each guide pin were 3-7 times, with a median of 4 times. Postoperative imaging data at 3 days showed that the position of sacroiliac screw implantation was evaluated as excellent. No complication such as incision infection or vascular nerve injury occurred, and no adverse events related to robotic devices occurred. At 3 days after operation, according to Matta score, the quality of fracture reduction was excellent in 6 cases and good in 1 case, and the excellent and good rate was 100%. All the 7 patients were followed up 6-15 months, with an average of 12.4 months. Bone union was achieved in all patients, and the healing time ranged from 18 to 24 weeks, with an average of 21.2 weeks. Majeed score at last follow-up was 81-95, with an average of 91.5; 5 cases were excellent, 2 cases were good, and the excellent and good rate was 100%. Conclusion: TiRobot-assisted percutaneous sacroiliac cannulated screw fixation for posterior pelvic ring injury with sacral variation is accurate, safe, minimally invasive, and intelligent, and the effectiveness is satisfactory.

Effect of Nonisoprene Degradation and Naturally Occurring Network during Maturation on the Properties of Natural Rubber.

It well-known that the superior performance of natural rubber (NR) compared to its synthetic counterpart mainly derives from nonisoprene components and naturally occurring network, which varies during the progress of the maturation and thereby results in technically graded rubber with different properties. However, identifying the roles of these two factors in the forming of excellent performance of NR is still a challenge as they change simultaneously during the maturation process. Here, influences of naturally occurring networking and nonisoprene degradation on the components, structures and properties of NR were systematically investigated by tailored treatments of maturation. It was found that the maturation-induced formation of natural network structure contributes to the increase in initial plastic value, Mooney viscosity and gel content for un-crosslinked NR, while the decomposition of nonisoprene components plays a dominant role in improving the mechanical properties of vulcanized NR. Stress-strain curve and Mooney-Rivlin analysis demonstrate that the biodegradation of the nonisoprene components significantly boost the vulcanization process, which significantly increases the number of chemical cross-link networks and effective cross-link density of the material, greatly improving the mechanical properties of NR vulcanizates. This resulted in the tensile strength of TSR 10CV being able to reach 22.6 MPa, which is significantly improved compared to 15.8 MPa of TSR 3CV. Evidenced by tubular model fitting, the increase in chemical cross-linking points effectively reduces the movable radius of the molecular chain under dynamic loading, making the molecular chain more difficult to move, which suppresses the entropy change under dynamic loading and consequently endows NR excellent dynamic mechanical properties. This resulted in a significant decrease in the temperature rising of TSR 10CV to 3.3 °C, while the temperature rising of TSR 3CV was still as high as 14.5 °C. As a minor factor, the naturally occurring network improves the mechanical properties of vulcanizates in the form of sacrificial bonds.

RANK: Large-Scale Inference with Graphical Nonlinear Knockoffs.

Power and reproducibility are key to enabling refined scientific discoveries in contemporary big data applications with general high-dimensional nonlinear models. In this paper, we provide theoretical foundations on the power and robustness for the model-X knockoffs procedure introduced recently in Candès, Fan, Janson and Lv (2018) in high-dimensional setting when the covariate distribution is characterized by Gaussian graphical model. We establish that under mild regularity conditions, the power of the oracle knockoffs procedure with known covariate distribution in high-dimensional linear models is asymptotically one as sample size goes to infinity. When moving away from the ideal case, we suggest the modified model-X knockoffs method called graphical nonlin-ear knockoffs (RANK) to accommodate the unknown covariate distribution. We provide theoretical justifications on the robustness of our modified procedure by showing that the false discovery rate (FDR) is asymptotically controlled at the target level and the power is asymptotically one with the estimated covariate distribution. To the best of our knowledge, this is the first formal theoretical result on the power for the knockoffs procedure. Simulation results demonstrate that compared to existing approaches, our method performs competitively in both FDR control and power. A real data set is analyzed to further assess the performance of the suggested knockoffs procedure.

Testing for heteroskedasticity in two-way fixed effects panel data models.

In this paper, we propose a new method for testing heteroskedasticity in two-way fixed effects panel data models under two important scenarios where the cross-sectional dimension is large and the temporal dimension is either large or fixed. Specifically, we will develop test statistics for both cases under the conditional moment framework, and derive their asymptotic distributions under both the null and alternative hypotheses. The proposed tests are distribution free and can easily be implemented using the simple auxiliary regressions. Simulation studies and two real data analyses demonstrate that our proposed tests perform well in practice, and may have the potential for wide application in econometric models with panel data.

GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data.

High-throughput techniques bring novel tools and also statistical challenges to genomic research. Identification of which type of diseases a new patient belongs to has been recognized as an important problem. For high-dimensional small sample size data, the classical discriminant methods suffer from the singularity problem and are, therefore, no longer applicable in practice. In this article, we propose a geometric diagonalization method for the regularized discriminant analysis. We then consider a bias correction to further improve the proposed method. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. A microarray dataset and an RNA-seq dataset are also analyzed and they demonstrate the superiority of the proposed method over the existing competitors, especially when the number of samples is small or the number of genes is large. Finally, we have developed an R package called "GDRDA" which is available upon request.