Unmanned Aircraft System Assessments of Landslide Safety for Transportation Corridors

An assessment of unmanned aircraft systems (UAS) concluded that current, off-the-shelf UAS aircraft and cameras can be effective for creating the digital surface models used to evaluate rock-slope stability and landslide risk along transportation corridors. The imagery collected with UAS can be processed using a photogrammetry technique called Structure-from-Motion (SfM) which generates a point cloud and surface model, similar to terrestrial laser scanning (TLS). We treated the TLS data as our control, or “truth,” because it is a mature and well-proven technology. The comparisons of the TLS surfaces and the SFM surfaces were impressive – if not comparable is many cases. Thus, the SfM surface models would be suitable for deriving slope morphology to generate rockfall activity indices (RAI) for landslide assessment provided the slopes. This research also revealed that UAS are a safer alternative to the deployment and operation of TLS operating on a road shoulder because UAS can be launched and recovered from a remote location and capable of imaging without flying directly over the road. However both the UAS and TLS approaches still require traditional survey control and photo targets to accurately geo-reference their respective DSM.List of Figures ...................................................................................................... vi List of Abbreviations ......................................................................................... vii Acknowledgments ................................................................................................ x Executive Summary ............................................................................................. xi CHAPTER 1 INTRODUCTION .......................................................................... 1 CHAPTER 2 LITERATURE REVIEW ................................................................ 4 2.1 Landslide Hazards .................................................................................... 4 2.2 Unmanned Aircraft Systems Remote Sensing.......................................... 6 2.3 Structure From Motion (SfM) .................................................................. 7 2.4 Lidar terrain mapping ............................................................................... 8 CHAPTER 3 STUDY SITE/DATA .................................................................. 11 CHAPTER 4 METHODS ................................................................................ 13 4.1 Data Collection ............................................................................................. 13 4.1.1 Survey Control ..................................................................................... 14 4.1.2 TLS Surveys ........................................................................................ 16 4.1.3 UAS Imagery ....................................................................................... 17 4.1.4 Terrestrial Imagery Acquisition ........................................................... 19 4.2 Data Processing ............................................................................................ 20 4.2.1 Survey Control ..................................................................................... 20 4.2.2 TLS Processing .................................................................................... 20 4.2.3 SfM Processing .................................................................................... 21 4.2.4 Surface Generation .............................................................................. 22 4.3 Quality Evaluation ........................................................................................ 23 4.3.1 Completeness ....................................................................................... 23 4.3.2 Data Density/Resolution ...................................................................... 23 4.3.3 Accuracy Assessment .......................................................................... 23 4.3.2 Surface Morphology Analysis ............................................................. 24 4.2.6 Data Visualization ............................................................................... 25 CHAPTER 5 RESULTS ................................................................................. 27 v 5.1 UTIC DSM evaluation.................................................................................. 27 5.1.1 Completeness evaluation ..................................................................... 28 5.1.2 Data Density Evaluation ...................................................................... 29 5.1.3 Accuracy Evaluation............................................................................ 30 5.2 Geomorphological Evaluation ...................................................................... 32 CHAPTER 6 DISCUSSION ............................................................................ 35 6.1 Evaluation of UAS efficiencies .................................................................... 35 6.2 DSM quality and completeness .................................................................... 37 6.3 Safety and operational considerations .......................................................... 37 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS ................................ 40 7.1 Technology Transfer..................................................................................... 41 7.1.1 Publications ......................................................................................... 41 7.1.2 Presentations ........................................................................................ 42 7.1.3 Multi-media outreach .......................................................................... 43 6.4 Integration of UAS and TLS data ................................................................. 44 REFERENCES .............................................................................................. 4

Case Histories of Widespread Liquefaction and Lateral Spread Induced by the 2007 Pisco, Peru Earthquake

Case histories of widespread liquefaction and lateral spread induced by the Mw 8.0, 2007 Pisco, Peru earthquake and observed during a post-earthquake GEER reconnaissance are presented. A long duration of the earthquake over 200 seconds and two phases of strong ground motion induced widespread liquefaction and lateral spread of sand coastal deposits and road embankments over a total length of approximately 100 km of coastal region. Six case histories of liquefaction are presented and discussed including a massive lateral spread of a marine terrace believed to be as large or even larger than that reported along the Shinano River during the 1964 Niigata earthquake in Japan

A common founding clone with TP53 and PTEN mutations gives rise to a concurrent germ cell tumor and acute megakaryoblastic leukemia

We report the findings from a patient who presented with a concurrent mediastinal germ cell tumor (GCT) and acute myeloid leukemia (AML). Bone marrow pathology was consistent with a diagnosis of acute megakaryoblastic leukemia (AML M7), and biopsy of an anterior mediastinal mass was consistent with a nonseminomatous GCT. Prior studies have described associations between hematological malignancies, including AML M7 and nonseminomatous GCTs, and it was recently suggested that a common founding clone initiated both cancers. We performed enhanced exome sequencing on the GCT and the AML M7 from our patient to define the clonal relationship between the two cancers. We found that both samples contained somatic mutations in PTEN (C136R missense) and TP53 (R213 frameshift). The mutations in PTEN and TP53 were present at ∼100% variant allele frequency (VAF) in both tumors. In addition, we detected and validated five other shared somatic mutations. The copy-number analysis of the AML exome data revealed an amplification of Chromosome 12p. We also identified a heterozygous germline variant in FANCA (S858R), which is known to be associated with Fanconi anemia but is of uncertain significance here. In summary, our data not only support a common founding clone for these cancers but also suggest that a specific set of distinct genomic alterations (in PTEN and TP53) underlies the rare association between GCT and AML. This association is likely linked to the treatment resistance and extremely poor outcome of these patients. We cannot resolve the clonal evolution of these tumors given limitations of our data

Expression and function of PML-RARA in the hematopoietic progenitor cells of Ctsg-PML-RARA mice

Because PML-RARA-induced acute promyelocytic leukemia (APL) is a morphologically differentiated leukemia, many groups have speculated about whether its leukemic cell of origin is a committed myeloid precursor (e.g. a promyelocyte) versus an hematopoietic stem/progenitor cell (HSPC). We originally targeted PML-RARA expression with CTSG regulatory elements, based on the early observation that this gene was maximally expressed in cells with promyelocyte morphology. Here, we show that both Ctsg, and PML-RARA targeted to the Ctsg locus (in Ctsg-PML-RARA mice), are expressed in the purified KLS cells of these mice (KLS = Kit(+)Lin(-)Sca(+), which are highly enriched for HSPCs), and this expression results in biological effects in multi-lineage competitive repopulation assays. Further, we demonstrate the transcriptional consequences of PML-RARA expression in Ctsg-PML-RARA mice in early myeloid development in other myeloid progenitor compartments [common myeloid progenitors (CMPs) and granulocyte/monocyte progenitors (GMPs)], which have a distinct gene expression signature compared to wild-type (WT) mice. Although PML-RARA is indeed expressed at high levels in the promyelocytes of Ctsg-PML-RARA mice and alters the transcriptional signature of these cells, it does not induce their self-renewal. In sum, these results demonstrate that in the Ctsg-PML-RARA mouse model of APL, PML-RARA is expressed in and affects the function of multipotent progenitor cells. Finally, since PML/Pml is normally expressed in the HSPCs of both humans and mice, and since some human APL samples contain TCR rearrangements and express T lineage genes, we suggest that the very early hematopoietic expression of PML-RARA in this mouse model may closely mimic the physiologic expression pattern of PML-RARA in human APL patients

miR-221 Mediates Chemoresistance of Esophageal Adenocarcinoma by Direct Targeting of DKK2 Expression

Background:Chemoresistance is a main obstacle to effective esophageal cancer (EC) therapy. We hypothesize that altered expression of microRNAs (miRNAs) play a role in EC cancer progression and resistance to 5-fluorouracil (5-FU) based chemotherapeutic strategies.Methods:Four pairs of esophageal adenocarcinoma (EAC) cell lines and corresponding 5-FU resistant variants were established. The expression levels of miRNAs previously shown to be involved in the general regulation of stem cell pathways were analyzed by qRT-PCR. The effects of selected miRNAs on proliferation, apoptosis, and chemosensitivity were evaluated both in vitro and in vivo. We identified a particular miRNA and analyzed its putative target genes in 14 pairs of human EC tumor specimens with surrounding normal tissue by qRT-PCR as well as Wnt pathway associated genes by immunohistochemistry in another 45 EAC tumor samples.Results:MiR-221 was overexpressed in 5-FU resistant EC cell lines as well as in human EAC tissue. DKK2 was identified as a target gene for miR-221. Knockdown of miR-221 in 5-FU resistant cells resulted in reduced cell proliferation, increased apoptosis, restored chemosensitivity, and led to inactivation of the Wnt/-catenin pathway mediated by alteration in DKK2 expression. Moreover, miR-221 reduction resulted in alteration of EMT-associated genes such as E-cadherin and vimentin as well as significantly slower xenograft tumor growth in nude mice. RT2 profiler analysis identified a substantial dysregulation of 4 Wnt/-catenin signaling and chemoresistance target genes as a result of miR-221 modulation: CDH1, CD44, MYC, and ABCG2.Conclusion:MiR-221 controls 5-FU resistance of EC partly via modulation of Wnt/-catenin-EMT pathways by direct targeting of DKK2 expression. MiR-221 may serve as a prognostic marker and therapeutic target for patients with 5-FU resistant EAC

New Orleans and Hurricane Katrina. III: The 17th Street Drainage Canal

The failure of the levee and floodwall section on the east bank of the 17th Street drainage canal was one of the most catastrophic breaches that occurred during Hurricane Katrina. It produced a breach that rapidly scoured a flow pathway below sea level, so that after the storm surge had largely subsided, floodwaters still continued to stream in through this breach for the next two and a half days. This particular failure contributed massively to the overall flooding of the Metropolitan Orleans East Bank protected basin. Slightly more than half of the loss of life, and a similar fraction of the overall damages, occurred in this heavily populated basin. There are a number of important geotechnical and geoforensic lessons associated with this failure. Accordingly, this paper is dedicated solely to investigating this single failure. Geological and geotechnical details, such as a thin layer of sensitive clay that was laid down by a previous hurricane, proper strength characterization of soils at and beyond the toe of the levee, and recognition of a water-filled gap on the inboard side of the sheet pile cutoff wall are judged to be among the most critical factors in understanding this failure. The lessons learned from this study are of importance for similar flood protection systems throughout other regions of the United States and the world