LFE as a development tool for next generation earthquake professionals

In January 2017 the Earthquake Engineering Research Institute in partnership with the National Research Center for Integrated Disaster Risk Management (CIGIDEN) led a five-day travel study program in Chile in which students and young professionals engaged in learning from earthquakes activities. The 16 participants attended lectures and field trips and completed two resilience projects to contribute to the body of knowledge about recovery since the 2010 Maule earthquake while also becoming familiar with reconnaissance tools and techniques. The program was created to provide learning-from-earthquakes opportunities for younger members outside the limited postevent reconnaissance teams; and to engage younger members in EERI activities and train them for future reconnaissance, which might include long-term resilience and recovery components. The success of the program can be attributed to the strong partnership with CIGIDEN, experienced mentors who accompanied the group, senior academics and practitioners who lectured and led tours, as well as a strong interdisciplinary team of participants who worked extremely hard interviewing locals and compiling the data for their resilience project

SVEP1 as a Genetic Modifier of TEK-Related Primary Congenital Glaucoma.

Purpose: Affecting children by age 3, primary congenital glaucoma (PCG) can cause debilitating vision loss by the developmental impairment of aqueous drainage resulting in high intraocular pressure (IOP), globe enlargement, and optic neuropathy. TEK haploinsufficiency accounts for 5% of PCG in diverse populations, with low penetrance explained by variable dysgenesis of Schlemm's canal (SC) in mice. We report eight families with TEK-related PCG, and provide evidence for SVEP1 as a disease modifier in family 8 with a higher penetrance and severity. Methods: Exome sequencing identified coding/splice site variants with an allele frequency less than 0.0001 (gnomAD). TEK variant effects were assayed in construct-transfected HEK293 cells via detection of autophosphorylated (active) TEK protein. An enucleated eye from an affected member of family 8 was examined via histology. SVEP1 expression in developing outflow tissues was detected by immunofluorescent staining of 7-day mouse anterior segments. SVEP1 stimulation of TEK expression in human umbilical vascular endothelial cells (HUVECs) was measured by TaqMan quantitative PCR. Results: Heterozygous TEK loss-of-function alleles were identified in eight PCG families, with parent-child disease transmission observed in two pedigrees. Family 8 exhibited greater disease penetrance and severity, histology revealed absence of SC in one eye, and SVEP1:p.R997C was identified in four of the five affected individuals. During SC development, SVEP1 is secreted by surrounding tissues. SVEP1:p.R997C abrogates stimulation of TEK expression by HUVECs. Conclusions: We provide further evidence for PCG caused by TEK haploinsufficiency, affirm autosomal dominant inheritance in two pedigrees, and propose SVEP1 as a modifier of TEK expression during SC development, affecting disease penetrance and severity

Seismic Source Modeling by Clustering Earthquakes and Predicting Earthquake Magnitudes

Seismic sources are currently generated manually by experts, a process which is not efficient as the size of historical earthquake databases is growing. However, large historical earthquake databases provide an opportunity to generate seismic sources through data mining techniques. In this paper, we propose hierarchical clustering of historical earthquakes for generating seismic sources automatically. To evaluate the effectiveness of clustering in producing homogenous seismic sources, we compare the accuracy of earthquake magnitude prediction models before and after clustering. Three prediction models are experimented: decision tree, SVM, and kNN. The results show that: (1) the clustering approach leads to improved accuracy of prediction models; (2) the most accurate prediction model and the most homogenous seismic sources are achieved when earthquakes are clustered based on their non-spatial attributes; and (3) among the three prediction models experimented in this work, decision tree is the most accurate one