Engineering reconnaissance following the August 24, 2016 M6.0 Central Italy earthquake

An earthquake with a moment magnitude reported as 6.0 from INGV (Istituto Nazionale di Geofisica e Vulcanologia); occurred at 03:36 AM (local time) on 24 August 2016 in the central part of Italy. The epicenter was located at the borders of the Lazio, Abruzzi, Marche and Umbria regions, about 2.5 km north-east of the village of Accumoli and about 100 km from Rome. The hypocentral depth was about 8 km (INGV). We summarize preliminary findings of the Italy-US GEER (Geotechnical Extreme Events Reconnaissance) team, on damage distribution, causative faults, earthquake-induced landslides and rockfalls, building and bridge performance, and ground motion characterization. Our reconnaissance team used multidisciplinary approaches, combining expertise in geology, seismology, geomatics, geotechnical engineering, and structural engineering. Our approach was to combine traditional reconnaissance activities of on-ground recording and mapping of field conditions, with advanced imaging and damage detection routines enabled by state-of-the-art geomatics technology. We anticipate that results from this study, will be useful for future post-earthquake reconnaissance efforts, and improved emergency respons

A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Objective: Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. Design: Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. Setting: The European Prospective Investigation into Cancer and Nutrition (EPIC). Subjects: Women (n 334 850) from the EPIC study. Results: The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, Ptrend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, Ptrend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, Ptrend<0·01). Conclusions: TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC

Main nutrient patterns and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition study.

BACKGROUND: Much of the current literature on diet-colorectal cancer (CRC) associations focused on studies of single foods/nutrients, whereas less is known about nutrient patterns. We investigated the association between major nutrient patterns and CRC risk in participants of the European Prospective Investigation into Cancer and Nutrition (EPIC) study. METHODS: Among 477 312 participants, intakes of 23 nutrients were estimated from validated dietary questionnaires. Using results from a previous principal component (PC) analysis, four major nutrient patterns were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed for the association of each of the four patterns and CRC incidence using multivariate Cox proportional hazards models with adjustment for established CRC risk factors. RESULTS: During an average of 11 years of follow-up, 4517 incident cases of CRC were documented. A nutrient pattern characterised by high intakes of vitamins and minerals was inversely associated with CRC (HR per 1 s.d.=0.94, 95% CI: 0.92-0.98) as was a pattern characterised by total protein, riboflavin, phosphorus and calcium (HR (1 s.d.)=0.96, 95% CI: 0.93-0.99). The remaining two patterns were not significantly associated with CRC risk. CONCLUSIONS: Analysing nutrient patterns may improve our understanding of how groups of nutrients relate to CRC

Association between plasma phospholipid saturated fatty acids and metabolic markers of lipid, hepatic, inflammation and glycaemic pathways in eight European countries: a cross-sectional analysis in the EPIC-InterAct study.

BACKGROUND: Accumulating evidence suggests that individual circulating saturated fatty acids (SFAs) are heterogeneous in their associations with cardio-metabolic diseases, but evidence about associations of SFAs with metabolic markers of different pathogenic pathways is limited. We aimed to examine the associations between plasma phospholipid SFAs and the metabolic markers of lipid, hepatic, glycaemic and inflammation pathways. METHODS: We measured nine individual plasma phospholipid SFAs and derived three SFA groups (odd-chain: C15:0 + C17:0, even-chain: C14:0 + C16:0 + C18:0, and very-long-chain: C20:0 + C22:0 + C23:0 + C24:0) in individuals from the subcohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study across eight European countries. Using linear regression in 15,919 subcohort members, adjusted for potential confounders and corrected for multiple testing, we examined cross-sectional associations of SFAs with 13 metabolic markers. Multiplicative interactions of the three SFA groups with pre-specified factors, including body mass index (BMI) and alcohol consumption, were tested. RESULTS: Higher levels of odd-chain SFA group were associated with lower levels of major lipids (total cholesterol (TC), triglycerides, apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB)) and hepatic markers (alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT)). Higher even-chain SFA group levels were associated with higher levels of low-density lipoprotein cholesterol (LDL-C), TC/high-density lipoprotein cholesterol (HDL-C) ratio, triglycerides, ApoB, ApoB/A1 ratio, ALT, AST, GGT and CRP, and lower levels of HDL-C and ApoA1. Very-long-chain SFA group levels showed inverse associations with triglycerides, ApoA1 and GGT, and positive associations with TC, LDL-C, TC/HDL-C, ApoB and ApoB/A1. Associations were generally stronger at higher levels of BMI or alcohol consumption. CONCLUSIONS: Subtypes of SFAs are associated in a differential way with metabolic markers of lipid metabolism, liver function and chronic inflammation, suggesting that odd-chain SFAs are associated with lower metabolic risk and even-chain SFAs with adverse metabolic risk, whereas mixed findings were obtained for very-long-chain SFAs. The clinical and biochemical implications of these findings may vary by adiposity and alcohol intake

The long-run relationship between the Italian day-ahead and balancing electricity prices

We study the convergence of day-ahead and balancing prices for the Italian power market. The zonal time-series of the prices are evaluated, seasonally adjusted and tested to assess their long-run properties. We focus on the dynamic behavior of the four continental price zones of Italy (North, Central-North, Central-South and South). Using a sample of data that spans the last decade and applying the fractional cointegration methodology, we show the existence of long-run relationships. This signals the existence of convergence between prices in each zone but zone Central-South, where prices are divergent. We also measure the average price difference, and analyse how it evolves over time. Price differences dynamically reduce for all zones except for Central-South. We comment the results and provide an interpretation for the differences across zones. We also discuss policy consequences for both Italian and other markets