Entering the Era of Earth Observation-Based Landslide Warning Systems: A novel and exciting framework

Landslide early warning remains a grand challenge due to the high human cost of catastrophic landslides globally and the difficulty of identifying a diverse range of landslide triggering factors. There have been only a very limited number of success stories to date. However, recent advances in earth observation (EO) from ground, aircraft and space have dramatically improved our ability to detect and monitor active landslides and a growing body of geotechnical theory suggests that prefailure behavior can provide clues to the location and timing of impending catastrophic failures. In this paper, we use two recent landslides in China as case studies, to demonstrate that (i) satellite radar observations can be used to detect deformation precursors to catastrophic landslide occurrence, and (ii) early warning can be achieved with real-time in-situ observations. A novel and exciting framework is then proposed to employ EO technologies to build an operational landslide early warning system.This work was supported by the National Natural Science Foundation of China under grants 41801391, 41874005, and 41929001; the National Science Fund for Outstanding Young Scholars of China under grant 41622206; the Fund for International Cooperation under grant NSFCRCUK_NERC; Resilience to Earthquake-Induced Landslide Risk in China under grant 41661134010; the open fund of State Key Laboratory of Geodesy and Earth’s Dynamics (SKLGED2018-5-3-E); Sichuan Science and Technology Plan Project under grant 2019YJ0404; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project under grant SKLGP2018Z019; the Spanish Ministry of Economy and Competitiveness, the State Agency of Research, and the European Funds for Regional Development under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P; and the Spanish Ministry of Education, Culture, and Sport under project PRX17/00439. This work was also partially supported by the U.K. Natural Environment Research Council through the Center for the Observation and Modeling of Earthquakes, Volcanoes, and Tectonics under come30001 and the Looking Inside the Continents From Space and Community Earthquake Disaster Risk Reduction in China projects under NE/K010794/1 and NE/N012151/1, respectively, and by the European Space Agency through the ESA-MOST DRAGON-4 project (32244 [4]). Roland Bürgmann acknowledges support by the NASA Earth Surface and Interior focus area

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Improved Variational Mode Decomposition and Machine Learning Algorithm

Remaining useful life (RUL) prediction of batteries is important for the health management and safety evaluation of lithium-ion batteries. Because lithium-ion batteries have capacity recovery and noise interference during actual use, direct use of measured capacity data to predict their RUL generalization ability is not efficient. Aimed at the above problems, this paper proposes an integrated life prediction method for lithium-ion batteries by combining improved variational mode decomposition (VMD) with a long short-term memory network (LSTM) and Gaussian process regression algorithm (GPR). First, the VMD algorithm decomposed the measured capacity dataset of the lithium-ion battery into a residual component and capacity regeneration component, in which the penalty factor α and mode number K in the VMD algorithm were optimized by the whale optimization algorithm (WOA). Second, the LSTM and GPR models were established to predict the residual component and capacity regeneration components, respectively. Last, the predicted components are integrated to obtain the final predicted lithium-ion battery capacity. The experimental results show that the mean absolute error (MAE) and root mean square error (RMSE) of the proposed lithium-ion battery capacity prediction model are less than 0.5% and 0.8%, respectively, and the method outperforms the five compared algorithms and several recently proposed hybrid algorithms in terms of prediction accuracy

Type 2 mixed monoclonal IgM and polyclonal IgG cryoglobulinemia can be associated with concurrent renal and intestinal thrombosis: Case report

Three variants of cryoglobulinemic glomerulopathy are well known, however, the concurrent acute enteritis secondary to a mixed polyclonal cryoglobulin associated thrombotic vasculitis is rarely reported in the literature. We report a case of a 72-year-old man with medical history of hypertension, leukocytoclastic vasculitis, positive serum cryoglobulin, hepatitis C, and membranoproliferative pattern of glomerulonephritis diagnosed 4 years ago. This patient recently presented with abdominal pain for one week. Labs showed worsening renal function, monoclonal IgM-kappa, and positive cryoglobulin in his serum, but negative hepatitis C test. The second renal biopsy showed a membranoproliferative pattern of glomerulopathy with many hyaline thrombi in the glomerular capillary loops. A mixed monoclonal IgM and polyclonal IgG cryoglobulinemic glomerulonephritis (type 2) was diagnosed. His concurrent jejunal biopsy revealed infiltration of neutrophils into glands and submucosal thrombus consistent with ischemic acute jejunitis. The submucosal thrombus of the jejunal biopsy was morphologically similar to the hyaline-thrombi found in glomerular capillary loops. Therefore, we concluded that cryoglobulin associated hyaline thrombi were the most likely etiology for both of his renal disease and acute ischemic jejunitis in this patient. This patient’s symptoms are due to simultaneous renal and intestinal thrombosis occurring in cryoglobulinemia. This concurrent thrombosis has not been well described in the literature

Synoptic reporting in tumor pathology: advantages of a web-based system.

The American College of Surgeons Commission on Cancer (ACS-CoC) mandates that pathology reports at ACS-CoC-approved cancer programs include all scientifically validated data elements for each site and tumor specimen. The College of American Pathologists (CAP) has produced cancer checklists in static text formats to assist reporting. To be inclusive, the CAP checklists are pages long, requiring extensive text editing and multiple intermediate steps. We created a set of dynamic tumor-reporting templates, using Microsoft Active Server Page (ASP.NET), with drop-down list and data-compile features, and added a reminder function to indicate missing information. Users can access this system on the Internet, prepare the tumor report by selecting relevant data from drop-down lists with an embedded tumor staging scheme, and directly transfer the final report into a laboratory information system by using the copy-and-paste function. By minimizing extensive text editing and eliminating intermediate steps, this system can reduce reporting errors, improve work efficiency, and increase compliance

Kinematic model of crustal deformation of Fenwei basin, China based on GPS observations

Using high precision GPS data for the period of 1999–2007 from the China Crustal Movement Observation Network, we have constructed a plate kinematic model of crustal deformation of Fenwei basin, China. We have examined different kinematic models that can fit the horizontal crustal deformation of the Fenwei basin using three steps of testing. The first step is to carry out unbiasedness and efficiency tests of various models. The second step is to conduct significance tests of strain parameters of the models. The third step is to examine whether strain parameters can fully represent the deformation characteristics of the 11 tectonic blocks over the Fenwei basin. Our results show that the degree of rigidity at the Ordos, Hetao, Yinshan and South China blocks is significant at the 95% confidence level, indicating the crustal deformation of these blocks can be represented by a rigid block model without the need to consider differential deformation within blocks. We have demonstrated that homogeneous strain condition is suitable for the Yinchuan basin but not for other 6 blocks. Therefore, inhomogeneous strains within blocks should be considered when establishing the crustal deformation model for these blocks. We have also tested that not all of the quadratic terms of strain parameters are needed for the Yuncheng-Linfen block. Therefore, four kinds of elastic kinematic models that can best represent the detailed deformation characteristics of the 11 blocks of Fenwei basin are finally obtained. Based on the established model, we have shown that the current tectonic strain feature of the Fenwei basin is mainly characterized by tensile strain in the NW–SE direction, and the boundaries betweem the Ganqing and Ordos blocks and the Shanxi graben possess the maximum shear strain. A comparison between our results and past geological and geophysical investigations further confirms that the model established in this paper is reasonable

IL4 (interleukin 4) induces autophagy in B cells leading to exacerbated asthma

<p>Allergic asthma is a common airway inflammatory disease in which B cells play important roles through IgE production and antigen presentation. SNP (single nucleotide polymorphism) analysis showed that <i>Atg</i> (autophagy-related) allele mutations are involved in asthma. It has been demonstrated that macroautophagy/autophagy is essential for B cell survival, plasma cell differentiation and immunological memory maintenance. However, whether B cell autophagy participates in asthma pathogenesis remains to be investigated. In this report, we found that autophagy was enhanced in pulmonary B cells from asthma-prone mice. Autophagy deficiency in B cells led to attenuated immunopathological symptoms in asthma-prone mice. Further investigation showed that IL4 (interleukin 4), a key effector Th2 cytokine in allergic asthma, was critical for autophagy induction in B cells both in vivo and in vitro, which further sustained B cell survival and enhanced antigen presentation by B cells. Moreover, IL4-induced autophagy depended on JAK signaling via an MTOR-independent, PtdIns3K-dependent pathway. Together, our data indicate that B cell autophagy aggravates experimental asthma through multiple mechanisms.</p