An Easily Used Phenomenological Magnetization Model and Its Empirical Expressions Based on Jiles-Atherton Parameters.

In this paper, a simple magnetization model convenient for engineering applications is presented based on the expressions of the first-order LTI system model. Considering the trade-off between the nonlinearity of anhysteretic magnetization and the hysteresis width, the proposed model employs two different equations with different magnetic field amplitudes. Furthermore, the proposed model utilizes the first-order LTI system model with a low magnetic field amplitude and a simple nonlinear function, based on the amplitude-frequency function, with a high magnetic field amplitude. Two important characteristic parameters for engineering applications, namely, amplitude and the equivalent phase lag, were exacted and analyzed to validate the computation precision of the proposed model. Then, the model was verified through comparisons to the validated Jiles-Atherton model. For easy use, similar to a physics-based model instead of a fitting method, empirical expressions for the model parameters were given, and applicable ranges of these equations were determined using the parameters of the Jiles-Atherton model. Finally, an example of the magnetization model applied to an on/off type device was computed to further verify the effectiveness of the proposed model with quite a simple expression.

Lignocellulosic Biomass-Derived Carbon Electrodes for Flexible Supercapacitors: An Overview.

With the increasing demand for high-performance electronic devices in smart textiles, various types of flexible/wearable electronic device (i.e., supercapacitors, batteries, fuel cells, etc.) have emerged regularly. As one of the most promising wearable devices, flexible supercapacitors from a variety of electrode materials have been developed. In particular, carbon materials from lignocellulosic biomass precursor have the characteristics of low cost, natural abundance, high specific surface area, excellent electrochemical stability, etc. Moreover, their chemical structures usually contain a large number of heteroatomic groups, which greatly contribute to the capacitive performance of the corresponding flexible supercapacitors. This review summarizes the working mechanism, configuration of flexible electrodes, conversion of lignocellulosic biomass-derived carbon electrodes, and their corresponding electrochemical properties in flexible/wearable supercapacitors. Technology challenges and future research trends will also be provided.

Lignin-Based High-Performance Fibers by Textile Spinning Techniques.

As a major component of lignocellulosic biomass, lignin is one of the largest natural resources of biopolymers and, thus, an abundant and renewable raw material for products, such as high-performance fibers for industrial applications. Direct conversion of lignin has long been investigated, but the fiber spinning process for lignin is difficult and the obtained fibers exhibit unsatisfactory mechanical performance mainly due to the amorphous chemical structure, low molecular weight of lignin, and broad molecular weight distribution. Therefore, different textile spinning techniques, modifications of lignin, and incorporation of lignin into polymers have been and are being developed to increase lignin's spinnability and compatibility with existing materials to yield fibers with better mechanical performance. This review presents the latest advances in the textile fabrication techniques, modified lignin-based high-performance fibers, and their potential in the enhancement of the mechanical performance.

Cost-Effective Yarn-Shaped Lithium-Ion Battery with High Wearability.

Because of flexibility, compactness, weavability, and ergonomic design, yarn-shaped lithium-ion batteries (LIBs) have enormous potential applications in wearable electronics. Still, the yarn-shaped LIB with the ability to meet commercialization requirements has never been reported, owing to the current challenge in complex material synthesis technologies, expensive raw material costs, poor safety performance, and nonstandard manufacturing equipment. Herein, we propose a yarn-shaped LIB that meets the aforementioned requirements. With a highly conductive and flexible stainless-steel yarn acting as the current collector, the electrode active materials and the gel electrolyte, which are commercially available at low cost, are uniformly coated onto the stainless-steel yarn by a simple and facile dipping-drying method. Even at different deformation conditions (i.e., bending or knotting), the specific capacity of the yarn-shaped LIB (7 cm long, <2 mm in diameter) assembled from graphite and lithium iron phosphate electrodes is maintained >85%. After charged treatment, it can successfully power up an electronic watch and an electronic thermo-hygrometer. Thanks to the simple preparation process, low cost of raw materials, and good safety performance, this work can promote the commercialization of wearable energy storage devices.

Mechanical Behavior of Entangled Metallic Wire Materials under Quasi-Static and Impact Loading.

In this paper, the stiffness and damping property of entangled metallic wire materials (EMWM) under quasi-static and low-velocity impact loading were investigated. The results reveal that the maximum deformation of the EMWM mainly depends on the maximum load it bears, and that air damping is the main way to dissipate impact energy. The EMWM can absorb more energy (energy absorption rate is over 60%) under impact conditions. The EMWM has excellent characteristics of repetitive energy absorption.

Three-Dimensional Hierarchically Porous Graphene Fiber-Shaped Supercapacitors with High Specific Capacitance and Rate Capability.

Chemically converted graphene fiber-shaped supercapacitors (FSSCs) are highly promising flexible energy storage devices for wearable electronics. However, the ultralow specific capacitance and poor rate performance severely hamper their practical applications. They are caused by severe stacking of graphene nanosheets and tortuous ion diffusion path in graphene-based electrodes; thus, the ultralow utilization of graphene has been rarely carefully considered to date. Here, we address these issues by developing three-dimensional hierarchically porous graphene fiber with the incorporation of holey graphene for efficient utilization of graphene to achieve fast charge diffusion and good charge storage capability. Without deterioration in electrical but robust mechanical properties, the optimal graphene fiber shows ultrahigh specific capacitance of 220.1 F cm-3 at current density of 0.1 A cm-3 and boosted specific capacitance of 254.3 F cm-3 at 0.1 A cm-3 after nitrogen doping. Moreover, the nitrogen-doped 40% holey graphene hybrid fiber-assembled FSSC exhibits ultrahigh rate capability (96, 91, and 87% at current density of 0.5, 1.0, and 2.0 A cm-3, respectively, and 67% even at ultrahigh current density of 10.0 A cm-3) and excellent cycle stability (95.65% capacitance retention after 10 000 cycles). The contribution of three-dimensional interconnected hierarchically porous network to the enhanced electrochemical (EC) performance is semiquantitatively elucidated by Brunauer-Emmett-Teller and energy dispersive spectroscopy mapping. Our work gives insights into the importance of fully utilizing graphene and provides an efficient strategy for high EC performance in chemically converted graphene-based FSSCs.

Relationship between the exposure to cumulative cardiovascular health behaviors and factors and chronic kidney disease-The Kailuan study.

It is unclear whether ideal cardiovascular health (CVH) behaviors and factors, particularly cumulative exposure to ideal CVH (cumCVH), is associated with chronic kidney disease (CKD). The aim of the study was to examine the effect of cumCVH on CKD using the data from the Kailuan study. The study included the 27,970 (21,199 males) of the Kailuan community (China). The participants were 19 to 98 years of age. They were followed in 2008-2009, 2010-2011, and 2012-2013 by the same medical staff that did the initial physical examinations in 2006-2007. Participants were censored on the visit reporting CKD. A CVH score was created based on the seven AHA health metrics. The cumCVH score was CVH1×timev1-v2+CVH2×timev2-v3+CVH3×timev3-v4. In the fully adjusted model, compared with the lowest quintile of cumCVH, individuals in the highest quintile had a 75% lower risk of CKD (95% confidence interval (CI): 66-82%). Every additional year lived with a 1-unit increase in ideal CVH was associated with an 11% (95% CI: 9-13%) reduction in the incidence of CKD. Furthermore, when we excluded each of the six metrics from the cumCVH score in turn, the association was unaffected after the exclusion of individual risk factors. Ideal CVH is associated with a reduced incidence of CKD. Measurements of cumCVH are more likely to reflect the lifetime risk of CKD and possibly of other health outcomes.

Loganin attenuates diabetic nephropathy in C57BL/6J mice with diabetes induced by streptozotocin and fed with diets containing high level of advanced glycation end products.

AIMS: Diabetic nephropathy is the most common cause of end-stage renal disease in patients with diabetes. Advanced glycation end-products (AGEs) play a prominent role in the development of diabetic nephropathy. We herein evaluated the effects of loganin on diabetic nephropathy in vivo. MAIN METHODS: We established a diabetic nephropathy model in C57BL/6J mice with diabetes induced by streptozotocin and fed with diets containing high level of AGEs. Diabetic symptoms, renal functions, and pathohistology of pancreas and kidney were evaluated. AGE-RAGE pathway and oxidative stress parameters were determined. KEY FINDINGS: The model mice exhibited characteristic symptoms of diabetes including weight loss, polydipsia, polyphagia, polyuria, elevated blood glucose levels and low serum insulin levels during the experiments. However, loganin at doses of 0.02 and 0.1g/kg effectively improved these diabetic symptoms. Loganin reduced kidney/body weight ratio, 24h urine protein levels, and serum levels of urea nitrogen and creatinine in diabetic mice to different degrees compared to positive controls. Moreover, loganin improved the histology of pancreas and kidney, and alleviated the structural alterations in endothelial cells, mesangial cells and podocytes in renal cortex. Finally, we found that loganin reduced AGE levels in serum and kidney and downregulated mRNA and protein expression of receptors for AGEs in kidney in diabetic mice. Loganin also reduced the levels of malondialdehyde and increased the levels of superoxide dismutase in serum and kidney. SIGNIFICANCE: Loganin improved diabetic nephropathy in vivo associated with inhibition of AGE pathways, and could be a promising remedy for diabetic nephropathy.

[The prediction of high-sensitivity C reactive protein for peripheral arterial sclerosis in middle-aged population].

OBJECTIVE: To explore the predictive value of high-sensitivity C reactive protein (hsCRP) in middle-aged population during the peripheral arteriosclerosis. METHODS: Random sampling method was used in the study. In 2006-2007 Kailuan Group health examination of 101,510 employees, using stratified random sampling method to select 5,852 as observational cohort included, in the final with a standard queue 5,440 in December 2009. This study selected to participate in the 2012-2013 health examination cohort as the research object, in accordance with the inclusion criteria ultimately selected survey 3,978, select the epidemiological investigation, physical examination, laboratory testing data analysis. Of the 3 978 subjects, 2,282 were male and 1,696 were female, and the baseline age was (53.80±11.14) years. According to the baseline hsCRP quartile level was divided into four groups for comparison of baseline data, using multiple linear regression analysis between hsCRP and brachial-ankle pulse wave velocity (baPWV). Area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the prediction of hsCRP levels in peripheral arteriosclerosis. RESULTS: With increase of hsCRP levels, the survey of baseline levels of baPWV showed increasing trend, (1,445.49±300.55), (1,494.46±307.94), (1,547.67±320.34), (1,621.32±342.53) cm/s, respectively. Multiple linear regression results showed that age, by logarithmic transformation of hsCRP (lghsCRP) level, systolic blood pressure and fasting blood glucose for each additional unit, baPWV levels were increased 266.47, 58.00, 5.02, 39.79 cm/s (P<0.001), and BMI for each additional unit, baPWV level decreased 9.52 cm/s (P=0.030). The prediction of hsCRP in peripheral artery showed that lghsCRP level of AUC to 0.59 (95% CI: 0.57-0.61), lower than the age and systolic blood pressure predicted value AUC (95% CI) of 0.69 (0.67-0.71), 0.75 (0.73-0.77), respectively. CONCLUSION: The hsCRP level could not predict the peripheral arteriosclerosis alone, and the combined age and systolic blood pressure level could have better predictive value.

An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method.

In this paper, we develop a novel feature selection algorithm based on the genetic algorithm (GA) using a specifically devised trace-based separability criterion. According to the scores of class separability and variable separability, this criterion measures the significance of feature subset, independent of any specific classification. In addition, a mutual information matrix between variables is used as features for classification, and no prior knowledge about the cardinality of feature subset is required. Experiments are performed by using a standard lung cancer dataset. The obtained solutions are verified with three different classifiers, including the support vector machine (SVM), the back-propagation neural network (BPNN), and the K-nearest neighbor (KNN), and compared with those obtained by the whole feature set, the F-score and the correlation-based feature selection methods. The comparison results show that the proposed intelligent system has a good diagnosis performance and can be used as a promising tool for lung cancer diagnosis.