Prevalence of and Risk Factors for Peripheral Neuropathy in Chinese Patients With Diabetes: A Multicenter Cross-Sectional Study

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes, and its progression significantly worsens the patient's quality of life. This study investigated the prevalence and risk factors associated with DPN in a large sample of Beijing individuals with type 1 and 2 diabetes, as well as compared the diagnostic methods for DPN. A total of 2,048 diabetic patients from 13 centers in Beijing were assessed for DPN through questionnaires and examination. Patients were divided into DPN group and suspected DPN/non-DPN group. The demographic, clinical and biological characteristics between the two groups were compared. Binary logistic regression analysis was performed to identify potential variables associated with DPN in diabetic patients. The diagnostic methods for DPN were also compared. Among the 2,048 diabetic patients, 73 cases of type 1 diabetes mellitus, 1,975 cases of type 2 diabetes were included in this study. Among them, 714 (34.86%) were identified with DPN, 537 (26.22%) were suspected of having DPN, and 797 (38.92%) were identified without DPN. Patient's age, duration of diabetes, and diabetic retinopathy were the significant independent risk factor for DPN among patients with type 2 diabetes. The odds ratio (OR) was 1.439 (95% confidence interval (CI): 1.282–1.616, P < 0.001), 1.297 (95% CI: 1.151–1.462, P < 0.001), and 0.637 (95% CI: 0.506–0.802, P < 0.001), respectively. Ankle reflex, temperature sensation plus vibration sensation are the best screening test for patients with type 1 and 2 diabetes. The Youden indexes were 62.2 and 69.8%, respectively. The prevalence rates of DPN in the Chinese patients with type 1 and type 2 diabetes in Beijing were 21.92 and 35.34%, respectively. Patient's age, duration of diabetes, and diabetic retinopathy are the independent risk factors for DPN

Electrospun polycaprolactone/silk fibroin nanofiber scaffold with aligned fiber orientation for articular chondrocyte regeneration

Objective: Electrospun nanofibers exhibit potential as scaffolds for articular cartilage tissue regeneration. This study aimed to fabricate electrospun polycaprolactone (PCL)/silk fibroin (SF) composite nanofiber scaffolds and to explore performance of the scaffolds for articular chondrocyte regeneration.Methods: By altering material composition and preparation methods, three types of nanofiber scaffolds were effectively fabricated, including randomly oriented PCL (RPCL) nanofiber scaffold, randomly oriented PCL/SF (RPCL/SF) nanofiber scaffold, and aligned PCL/SF (APCL/SF) nanofiber scaffold. Physiochemical analyses were performed to determine mechanical properties and surface hydrophilicity of the nanofiber scaffolds. In vitro studies were conducted to investigate performance of the scaffolds on articular chondrocyte proliferation, gene expression and glycosaminoglycan secretion. Cytoskeleton staining was used to observe the arrangement of chondrocytes along the direction of the fibers and their elongation along the fiber arrangement.Results: The physicochemical analysis demonstrated that the APCL/SF nanofiber scaffold exhibited improved mechanical properties and surface hydrophilicity compared to the RPCL and RPCL/SF nanofiber scaffolds. Furthermore, the in vitro cell culture studies confirmed that the APCL/SF nanofibers could significantly promote articular chondrocyte proliferation, type II collagen (COL-II) gene expression, and glycosaminoglycan secretion compared to the RPCL and RPCL/SF nanofiber scaffolds. Additionally, cytoskeletal staining displayed that the APCL/SF nanofiber scaffold promoted the elongation of articular chondrocytes in the direction of parallel fiber alignment.Conclusion: The APCL/SF nanofiber scaffold exhibited promising potential as a composite scaffold for articular cartilage regeneration

Analysis of the O-rings that influence the performance of RCP hydrostatic seal based on TEH coupling method

A Multi-body contacting Thermal-Elastic-Hydro Model, MTEHM has been established in this study. And which has been applied to analysis the leakage behavior of No.1 seal of the RCP hydrostatic seal. The hydro-model is based on 2D Reynolds equation and programmed by M-code. An interface program written in C has been carried out. And which is used to transit the end face pressure value from hydro-model to elastic-solid model. The FEA multi-body contacting method has been taken into the elastic-solid model. And which is used to obtain the deformation angle of seal rings. An opening force ratio has been carried out as a convergent judgment of the multi-physics iterative coupling process. The influence of position of O-rings (on the back of seal rings and relative to the hydrostatic clamp rings) has been discussed. For test and verify the MTEHM, a testing rig has been established. It can be used to simulate a high temperature high pressure seal media with a temperature range from 22°C to 100°C and a pressure range from 0.1MPa to 22MPa. At last, a comparison of pressure-leakage data from Westinghouse, Saint Alban power plant and this study has been presented. And a variance analysis has been attached

SplitNet: A Reinforcement Learning Based Sequence Splitting Method for the MinMax Multiple Travelling Salesman Problem

MinMax Multiple Travelling Salesman Problem (mTSP) is an important class of combinatorial optimization problems with many practical applications, of which the goal is to minimize the longest tour of all vehicles. Due to its high computational complexity, existing methods for solving this problem cannot obtain a solution of satisfactory quality with fast speed, especially when the scale of the problem is large. In this paper, we propose a learning-based method named SplitNet to transform the single TSP solutions into the MinMax mTSP solutions of the same instances. Specifically, we generate single TSP solution sequences and split them into mTSP subsequences using an attention-based model trained by reinforcement learning. We also design a decision region for the splitting policy, which significantly reduces the policy action space on instances of various scales and thus improves the generalization ability of SplitNet. The experimental results show that SplitNet generalizes well and outperforms existing learning-based baselines and Google OR-Tools on widely-used random datasets of different scales and public datasets with fast solving speed

Using cygnss data to map flood inundation during the 2021 extreme precipitation in henan province, China

On 20 July 2021, parts of China’s Henan Province received the highest precipitation levels ever recorded in the region. Floods caused by heavy rainfall resulted in hundreds of casualties and tens of billions of dollars’ worth of property loss. Due to the highly dynamic nature of flood disasters, rapid and timely spatial monitoring is conducive for early disaster prevention, mid-term disaster relief, and post-disaster reconstruction. However, existing remote sensing satellites cannot provide high-resolution flood monitoring results. Seeing as spaceborne global navigation satellite system-reflectometry (GNSS-R) can observe the Earth’s surface with high temporal and spatial resolutions, it is expected to provide a new solution to the problem of flood hazards. Here, using the Cyclone Global Navigation Satellite System (CYGNSS) L1 data, we first counted various signal-to-noise ratios and the corresponding reflectivity to surface features in Henan Province. Subsequently, we analyzed changes in the delay-Doppler map of CYGNSS when the observed area was submerged and not submerged. Finally, we determined the submerged area affected by extreme precipitation using the threshold detection method. The results demonstrated that the flood range retrieved by CYGNSS agreed with that retrieved by the Soil Moisture Active Passive (SMAP) mission and the precipitation data retrieved and measured by the Global Precipitation Measurement mission and meteorological stations. Compared with the SMAP results, those obtained by CYGNSS have a higher spatial resolution and can monitor changes in the areas affected by the floods over a shorter period.This research was funded by the National Natural Science Foundation of China Projects (42074041,41731066); The National Key Research and Development Program of China (2020YFC1512000, 2019YFC1509802); State Key Laboratory of Geo-Information Engineering (SKLGIE2019-Z-2-1); Shaanxi Natural Science Research Program (2020JM-227)

Study of Aging Temperature on the Thermal Compression Behaviors and Microstructure of a Novel Ni-Cr-Co-Based Superalloy

Nickel-based superalloys have been widely used in the aerospace industry, and regulating the reinforcing phases is the key to improving the high-temperature strength of the alloy. In this study, a series of aging treatments (650 °C, 750 °C, 850 °C and 950 °C for 8 h) were designed to study different thermal deformation behaviors and microstructure evolutions for a novel nickel-based superalloy. Among the aged samples, the 950 °C aged sample achieved the peak stress of ~323 MPa during the thermal deformation and the highest microhardness of ~315 HV after thermal compression, which were the greatest differences compared to before deformation. In addition, the grains of the 950 °C sample exhibit deformed fibrous shapes, and the grain orientation is isotropic, while the other samples exhibited isotropy. In the 850 °C and 950 °C high-temperature aging samples, the γ′ precipitate (about 20 nm in size) is gradually precipitated, which inhibits the movement of dislocation in the grain during compression, thus inhibiting the occurrence of dynamic recrystallization and improving the high-temperature mechanical properties of the alloy

Novel hybrid laser forging and arc additive repairing process for improving component performances

A new hybrid laser forging and arc additive repairing process was developed to significantly improve the performance of repaired components, in which a leading gas metal arc was adopted to repair the partially damaged component, and a trailing short-pulse laser directly acted on the high-temperature solidified metal without coating (laser forging). Compared with arc additive repairing with post-treatment, this hybrid process performed the arc repair and laser forging synchronously. The laser forging region can be accurately determined using a multi-physical molten pool simulation. The molten metal flow was also studied, indicating that the high sulfur content introduced by the filler metal transfer had a significant influence on the Marangoni stress distribution and thus changed the molten metal flow patterns. The mechanism for laser forging without coating and its related physical effects were investigated. The laser shock pressure was significantly higher than the Hugonoit elastic limit of the high-temperature solidified metal, causing plastic deformation of the repaired layer. The high strain and severe plastic deformation induced by laser forging caused martensite formation and grain refinement, which improved the mechanical properties and electrochemical corrosion performance of the repaired layer