Seismically induced landslide hazard and exposure modelling in Southern California based on the 1994 Northridge, California earthquake event

Quantitative modelling of landslide hazard, as opposed to landslide susceptibility, as a function of the earthquake trigger is vital in understanding and assessing future potential exposure to landsliding. Logistic regression analysis is a method commonly used to assess susceptibility to landsliding; however, estimating probability of landslide hazard as a result of an earthquake trigger is rarely undertaken. This paper utilises a very detailed landslide inventory map and a comprehensive dataset on peak ground acceleration for the 1994 Mw6.7 Northridge earthquake event to fit a landslide hazard logistic regression model. The model demonstrates a high success rate for estimating probability of landslides as a result of earthquake shaking. Seven earthquake magnitude scenarios were simulated using the Open Source Seismic Hazard Analysis (OpenSHA) application to simulate peak ground acceleration, a covariate of landsliding, for each event. The exposure of assets such as population, housing and roads to high levels of shaking and high probabilities of landsliding was estimated for each scenario. There has been urban development in the Northridge region since 1994, leading to an increase in prospective exposure of assets to the earthquake and landslide hazards in the event of a potential future earthquake. As the earthquake scenario magnitude increases, the impact from earthquake shaking initially increases then quickly levels out, but potential losses from landslides increase at a rapid rate. The modelling approach, as well as the specific model, developed in this paper can be used to estimate landslide probabilities as a result of an earthquake event for any scenario where the peak ground acceleration variable is available

Impact of communal irrigation on the 2018 Palu earthquake-triggered landslides

Anthropogenic changes to the environment can enhance earthquake-triggered landslides, yet their role in earthquake disasters is often overlooked. Coseismic landslides frequently involve liquefaction of granular materials, a process that reduces shear strength and facilitates downslope motion even on gentle slopes. Irrigation systems can increase liquefaction susceptibility and compromise otherwise stable slopes. Here we investigate devastating landslides that affected Palu, Indonesia, during the 28th September 2018 Mw7.5 earthquake. We document fields and buildings translated over 1 km down slopes of less than 2° and show landslides were limited to irrigated ground. A liquefied detachment was rooted upslope in a conveyance canal that supplied water to the irrigation network. A strong correlation between landslide displacement, irrigation infrastructure and the highest slopes (≥1.5°), suggests a causative mechanism that should provoke urgent assessment of gently sloping irrigated terrain elsewhere in Sulawesi and in tectonically active areas worldwide

Notes for genera: basal clades of Fungi (including Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota)

Compared to the higher fungi (Dikarya), taxonomic and evolutionary studies on the basal clades of fungi are fewer in number. Thus, the generic boundaries and higher ranks in the basal clades of fungi are poorly known. Recent DNA based taxonomic studies have provided reliable and accurate information. It is therefore necessary to compile all available information since basal clades genera lack updated checklists or outlines. Recently, Tedersoo et al. (MycoKeys 13:1--20, 2016) accepted Aphelidiomycota and Rozellomycota in Fungal clade. Thus, we regard both these phyla as members in Kingdom Fungi. We accept 16 phyla in basal clades viz. Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. Thus, 611 genera in 153 families, 43 orders and 18 classes are provided with details of classification, synonyms, life modes, distribution, recent literature and genomic data. Moreover, Catenariaceae Couch is proposed to be conserved, Cladochytriales Mozl.-Standr. is emended and the family Nephridiophagaceae is introduced

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified