Investigating the critical characteristics of thermal runaway process for LiFePO4/graphite batteries by a ceased segmented method

Lithium-ion batteries (LIBs) are widely used as the energy carrier in our daily life. However, the higher energy density of LIBs results in poor safety performance. Thermal runaway (TR) is the critical problem which hinders the further application of LIBs. Clarifying the mechanism of TR evolution is beneficial to safer cell design and safety management. In this paper, liquid nitrogen spray is proved to be an effective way to stop the violent reaction of LIBs during the TR process. Based on extended-volume accelerating rate calorimetry, the liquid nitrogen ceasing combined with non-atmospheric exposure analysis is used to investigate the TR evolution about LiFePO4/graphite batteries at critical temperature. Specifically, the geometrical shape, voltage, and impedance change are monitored during the TR process on the cell level. The morphologies/constitution of electrodes and separators are presented on the component level. Utilizing the gas analysis, the failure mechanism of the prismatic LiFePO4/graphite battery is studied comprehensively

A unified multi-step wind speed forecasting framework based on numerical weather prediction grids and wind farm monitoring data

Wind speed forecasting is the basis of wind farm operation, which provides a reference for the future operation status evaluation of wind farms. For the wind speed forecast of wind turbines in the whole wind farm, a strategy combining unified forecast and single site error correction is proposed in this paper. The unified forecast framework is composed of a unified forecast model and multiple single site error correction models, which combines the forecasted grids of numerical weather prediction (NWP) with the monitoring data of wind farms. The proposed unified forecast model is called spatiotemporal conversion deep predictive network (STC-DPN), which is composed of temporal convolution network (TCN) and 2D convolution long short-term memory network (ConvLSTM). Firstly, the NWP forecasted grids are interpolated to the fan location, and the sequence matrix is composed of the NWP data and the monitored data of each wind turbine according to the time series, which is entered into the TCN network for time sequence feature extraction. Then, the output of the TCN network is converted into a regular spatio-temporal data matrix, which is entered into the ConvLSTM network for joint learning of spatio-temporal features to obtain the wind speed sequence forecasted in the whole wind farm. Finally, an independent TCN-LSTM error correction model is added for each site. Variational modal decomposition (VMD) is used to process data series, and different processing methods are adopted in unified forecast and single site error correction. In the 96 steps forecast test of a wind farm from Jining City, China, the proposed method is superior to several baseline methods and has important practical application value

The Relative Risk and Incidence of Immune Checkpoint Inhibitors Related Pneumonitis in Patients With Advanced Cancer: A Meta-Analysis

Background: Recently, immune checkpoint inhibitors (ICIs) have been proved one of the most promising anti-cancer therapy, series clinical trials have confirmed their efficacy. But they are also associated with distinctive set of toxic effects, which are recognized as immune-related adverse events. Among those immune-related adverse events, pneumonitis is rare, but it is often clinically serious and potentially life-threatening. Although many clinical trial results of PD-1/PD-L1 inhibitors had been reported incidence of pneumonitis, the knowledge based on the individual cohort data from each clinical trial is limited. So we conducted a meta-analysis of trials of PD-1/PD-L1 inhibitors in patients with advanced cancer and compared relative risk and incidence among different tumor types and therapeutic regimens. Such an analysis may provide important knowledge of this rare but clinically significant and potentially serious immune-related adverse event.Methods: Electronic databases were used to search eligible literatures, include randomized controlled trials (RCTs) comparing immune checkpoint inhibitors vs. standard therapies. All-grade (1–4) or high-grade (3–4) pneumonitis events were extracted. The summary relative risk, summary incidence, and 95% confidence intervals were calculated.Results: The incidence of all-grade and high-grade pneumonitis in non-small cell lung cancer (NSCLC) was significantly higher compared with other tumor types, such as Melanoma, urothelial carcinoma (UC), head and neck squamous cell carcinoma (HNSCC) (3.1% vs. 2.0%; p = 0.02, 1.4% vs. 0.6%; p = 0.03). The risk of all-grade pneumonitis was obtained from all patients in both experimental arm and control arm. Treatment with immune checkpoint inhibitors targeting PD-1/PD-L1 did significantly increase the risk of all-grade and high-grade pneumonitis compared with controls (fixed effects, RR: 4.70; 95% CI: 2.81–7.85; p < 0.00001, RR: 3.33; 95% CI: 1.68–6.59; p = 0.0006).Conclusion: The incidence of immune checkpoint inhibitors related pneumonitis was higher in NSCLC than other tumor types. Patients treated with immune checkpoint inhibitor in experiment arms are more likely to experience any grade pneumonitis than control arms. These findings suggest that clinician need to draw more attention on this rare but serious adverse event

Structure and Photoluminescent Properties of ZnO Encapsulated in Mesoporous Silica SBA-15 Fabricated by Two-Solvent Strategy

The two-solvent method was employed to prepare ZnO encapsulated in mesoporous silica (ZnO/SBA-15). The prepared ZnO/SBA-15 samples have been studied by X-ray diffraction, transmission electron microscope, X-ray photoelectron spectroscopy, nitrogen adsorption–desorption isotherm, and photoluminescence spectroscopy. The ZnO/SBA-15 nanocomposite has the ordered hexagonal mesostructure of SBA-15. ZnO clusters of a high loading are distributed in the channels of SBA-15. Photoluminescence spectra show the UV emission band around 368 nm, the violet emission around 420 nm, and the blue emission around 457 nm. The UV emission is attributed to band-edge emission of ZnO. The violet emission results from the oxygen vacancies on the ZnO–SiO2interface traps. The blue emission is from the oxygen vacancies or interstitial zinc ions of ZnO. The UV emission and blue emission show a blue-shift phenomenon due to quantum-confinement-induced energy gap enhancement of ZnO clusters. The ZnO clusters encapsulated in SBA-15 can be used as light-emitting diodes and ultraviolet nanolasers

The VEGF -634G>C promoter polymorphism is associated with risk of gastric cancer

<p>Abstract</p> <p>Background</p> <p>Both TGF-β1 and VEGF play a critic role in the multiple-step process of tumorgenesis of gastric cancer. Single nucleotide polymorphisms (SNPs) of the <it>TGFB1 </it>and <it>VEGF </it>genes have been associated with risk and progression of many cancers. In this study, we investigated the association between potentially functional SNPs of these two genes and risk of gastric cancer in a US population.</p> <p>Methods</p> <p>The risk associated with genotypes and haplotypes of four <it>TGFB1 </it>SNPs and four <it>VEGF </it>SNPs were determined by multivariate logistic regression analysis in 171 patients with gastric cancer and 353 cancer-free controls frequency-matched by age, sex and ethnicity.</p> <p>Results</p> <p>Compared with the <it>VEGF</it>-634GG genotype, the -634CG genotype and the combined -634CG+CC genotypes were associated with a significantly elevated risk of gastric cancer (adjusted OR = 1.88, 95% CI = 1.24-2.86 and adjusted OR = 1.56, 95% CI = 1.07-2.27, respectively). However, none of other <it>TGFB1 </it>and <it>VEGF </it>SNPs was associated with risk of gastric cancer.</p> <p>Conclusion</p> <p>Our data suggested that the <it>VEGF</it>-634G>C SNP may be a marker for susceptibility to gastric cancer, and this finding needs to be validated in larger studies.</p

Efficient Query Evaluation on Large Textual Collections in a Peer-to-Peer Environment

We study the problem of evaluating ranked (top-k) queries on textual collections ranging from multiple gigabytes to terabytes in size. We focus on the case of a global index organization in a highly distributed environment, and consider a class of ranking functions that includes common variants of the Cosine and Okapi measures. The main bottleneck in such a scenario is the amount of communication required during query evaluation. We propose several efficient query evaluation schemes and evaluate their performance. Our results on real search engine query traces and over 120 million web pages show that after careful optimization such queries can be evaluated at a reasonable cost, while challenges remain for even larger collections and more general classes of ranking functions. 1

Performance of Compressed Inverted List Caching in Search Engines

Due to the rapid growth in the size of the web, web search engines are facing enormous performance challenges. The larger engines in particular have to be able to process tens of thousands of queries per second on tens of billions of documents, making query throughput a critical issue. To satisfy this heavy workload, search engines use a variety of performance optimizations including index compression, caching, and early termination. We focus on two techniques, inverted index compression and index caching, which play a crucial rule in web search engines as well as other high-performance information retrieval systems. We perform a comparison and evaluation of several inverted list compression algorithms, including new variants of existing algorithms that have not been studied before. We then evaluate different inverted list caching policies on large query traces, and finally study the possible performance benefits of combining compression and caching. The overall goal of this paper is to provide an updated discussion and evaluation of these two techniques, and to show how to select the best set of approaches and settings depending on parameter such as disk speed and main memory cache size

The Computation of Complex Dispersion and Properties of Evanescent Lamb Wave in Functionally Graded Piezoelectric-Piezomagnetic Plates

Functionally graded piezoelectric-piezomagnetic material (FGPPM), with a gradual variation of the material properties in the desired direction(s), can improve the conversion of energy among mechanical, electric, and magnetic fields. Full dispersion relations and wave mode shapes are vital to understanding dynamic behaviors of structures made of FGPPM. In this paper, an analytic method based on polynomial expansions is proposed to investigate the complex-valued dispersion and the evanescent Lamb wave in FGPPM plates. Comparisons with other related studies are conducted to validate the correctness of the presented method. Characteristics of the guided wave, including propagating modes and evanescent modes, in various FGPPM plates are studied, and three-dimensional full dispersion and attenuation curves are plotted to gain a deeper insight into the nature of the evanescent wave. The influences of the gradient variation on the dispersion and the magneto-electromechanical coupling factor are illustrated. The displacement amplitude and electric potential and magnetic potential distributions are also discussed in detail. The obtained numerical results could be useful to design and optimize different sensors and transducers made of smart piezoelectric and piezomagnetic materials with high performance by adjusting the gradient property