Plume–MOR decoupling and the timing of India–Eurasia collision

The debatable timing of India–Eurasia collision is based on geologic, stratigraphic, kinematic, and tectonic evidence. However, the collision event disturbed persistent processes, and the timing of disturbance in such processes could determine the onset of India–Eurasia collision precisely. We use the longevity of Southeast Indian Ridge (SEIR)—Kerguelen mantle plume (KMP) interaction cycles along the Ninetyeast ridge (NER) as a proxy to determine the commencement of India–Eurasia collision. The geochemical signature of the KMP tail along the NER is predominantly that of long-term coupling cycles, that was perturbed once by a short-term decoupling cycle. The long-term coupling cycles are mainly of enriched mid-ocean ridge basalts (E-MORBs). The short-term decoupling cycle is mostly derived from two distinct sources, MOR and plume separately, whereas the KMP is still being on-axis. The onset of India–Eurasia collision led to continental materials recycling into the mantle; hence the abrupt enrichment in incompatible elements at ca. 55 Ma, the MOR–plume on-axis decoupling, and the abrupt slowdown in the northward drift of the Indian plate was induced by the onset of India–Eurasia collision, thereafter MOR–plume recoupled.publishedVersio

Appraisal of geothermal potentials of some parts of the Abakaliki Anticlinorium and adjoining areas (Southeast Nigeria) using magnetic data

The Abakaliki Anticlinorium and its adjoining areas were appraised with the object of delineating high geothermal potential zones. Spectral depth analysis involving an improved centroid technique was used to analyze high-quality magnetic data. The obtained geothermal parameters were gridded to map various geothermal features within the investigated area. The obtained results varied from 4.99–9.35 km, 2.31–6.15 km, 6.11–16.28 km, 35.63°C–94.93°C/km, and 89.07–237.32 mW/m2 for centroid depth, top depth, Curie point depth, geothermal gradient, and heat flow values, respectively. The delineated semioval structure in the central zone of the investigated region characterized by a shallow Curie point depth (< 8.5 km) correlates with the location of the high-heat flow (>191.0 mW/m2) and geothermal gradient (>74.0°C/km) region. The high geothermal potential of the region is triggered by the massive post-rift tectonic event of the Santonian period related to the Abakaliki Anticlinorium. Further geophysical exploration programs should be carried out before exploitation activities at anomalous geothermal regions

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

A new high resolution filter for source edge detection of potential field data

Determining the source edges is a frequently requested task in the analysis of potential fields. However, the edge detection methods have some drawbacks or shortcomings, for example, blurred responses to weak amplitude anomalies, the estimated peaks over the edges are low in gradient or bring out overestimated edges in the resulting maps. In this paper, a new method based on an arcsine function using the ratio of the vertical gradient to the total gradient of the amplitude of the horizontal gradient field is introduced for outlining the source edges. The validity of the method is tested on both synthetic and real data and the edge detection results are compared with those detected from some other existing methods. The results from the proposed filter provide more accurate and higher resolution edges, and can avoid producing the spurious edges in the results

Large-scale geological structures of the Egyptian Nubian Shield

Abstract Integration of potential field- and structural data make it possible to trace surface and subsurface large-scale geological structures of the Egyptian Nubian Shield (ENS). Obtained results indicate that the Northern Eastern Desert (NED) of the ENS is dominated by relatively younger (c. 580 Ma) E–W and NE–SW trending extensional structures that were controlled by the evolution and retreat of the Cadomian Arc. Density of such extensional structures increases with depth as displayed by the potential data. The prevailing structural trends in the Central Eastern Desert (CED) are NW–SE and WNW–ESE. Both trends are highly prompted by the timing of deformation upon the Najd Fault System, and are themselves dissected by a relatively younger NE–SW shearing trend. Lineament density in the CED is subordinate for both subsurface and near surface structures. The South Eastern Desert exhibits compressional and extrusion-related structures of two main prominent trends; WNW-to-NW (to the western part) and the N-, NNE- to NE (to the eastern part). The previously mentioned Neoproterozoic trends are remarkably influenced by the Oligocene–Miocene Red Sea-Gulf of Suez rift related fractures in the vicinity of the rift shoulder. The remarkable change in trends and densities of structural trends, especially in the NED, is interpreted in terms of concealing of the older structures by the younger extensional structures which in turns reflect an N-ward progressive deformation in the entire ENS. Gravity data are more appropriate in delineating the structural trends compared to the magnetic data which are largely affected by lithological variations and/or alteration zones and magnetic mineralogy

Polymetallic mineralization prospectivity modelling using multi-geospatial data in logistic regression: The Diapiric Zone, Northeastern Algeria

Prospecting and exploring minerals present major challenges in tectonically complex regions for sustainable development as in Northeastern Algeria. This area is promising for its mineral potential, especially the metallogenic province ‘The Diapiric Zone’. This study concerns mapping and predicting potential polymetallic mineralization locations by integration of remote sensing, gravity, and magnetic datasets. Several enhancement and processing methods have been applied on Landsat8_OLI and ASTER_1T remote sensed data to reduce uncertainty for achieving the best detection of hydrothermal alteration zones and lithological mapping. Furthermore, the Centre for Exploration Targeting grid analysis technique, the contact occurrence density and entropy orientation tools were employed on ground-gravity and aeromagnetic data to understand and visualize the pathways for hydrothermal fluids circulation of mineral deposits. The polymetallic mineralization prospective areas were produced using a logistic regression model on the resulting multifactor. High zones of lead-zinc cover most the area that has been confirmed by field investigation

Structural interpretation of potential field data using the enhancement techniques: a case study

The enhancement techniques of potential field data are commonly used to detect the boundary locations of geological structures. There are many different techniques for estimating the source boundaries. Through synthetic examples and Bouguer data from the southern Red Sea, we have evaluated the performance of 15 enhancement techniques. The findings show that the tilt angle of horizontal gradient (TAHG) and fast sigmoid (FSED) techniques perform better than other techniques under almost all scenarios. Moreover, these two techniques can avoid producing false structures or connected structures as other techniques. The extracted lineaments from the TAHG and FSED were compared with surface faults of the study area. As a result, major differences are caused by rifting effect on the oceanic crust. The obtained results provide valuable information to better understand the structural features of the southern Red Sea and to introduce a more reliable structural interpretation

Integration of ERT and shallow seismic refraction for geotechnical investigation on El-Alamein Hotel Building Area, El-Alamein new city, Egypt

Abstract El-Alamein new city is regarded as one of the iconic cities of the Egyptian North Western Coast to be not only residential units but also summer resorts for tourist attractions. This study examines the efficiency of integrating geophysical methods for determining if clay lenses exist or seawater has intruded into shallow strata and for calculating the geotechnical parameters of near-surface layers for construction purposes. Nine electrical resistivity tomography (ERT) and shallow seismic refraction (SSR) profiles are conducted in this study. From ERT data, we observed the intrusion of seawater in layers at different depths. From SSR data, two layers are observed along profiles, while three layers are observed along the other profiles according to their velocities. Near-surface geotechnical parameters, that were calculated from SSR data, are integrated to evaluate our study area. Accordingly, it was considered a low-competent area and suitable for buildings with low heights, and the only difference is the intrusion of seawater, therefore, it is subdivided into 2 zones. In zone (A), the second layer is used as a foundation layer. Zone (B) is pretentious by the intrusion of seawater, and it is not suggested to construct any buildings or to improve the strength of concrete exposed to seawater in this zone to be suitable also for buildings with a low height

Accuracy assessment of various supervised machine learning algorithms in litho-facies classification from seismic data in the Penobscot field, Scotian Basin

Litho-facies classification is an essential task in characterizing the complex reservoirs in petroleum exploration and subsequent field development. The lithofacies classification at borehole locations is detailed but lacks in providing larger coverage areas. The acquired 3D seismic data provides global coverage for studying the reservoir facies heterogeneities in the study area. This study applies six supervised machine learning techniques (Random Forest, Support Vector Machine, Artificial Neural Network, Adaptive Boosting, Xtreme Gradient Boosting, and Multilayer Perceptron) to 3D post-stack seismic data to accurately estimate different litho-facies in inter-well regions and compares their performance. Initially, the efficacy of the said models was critically examined via the confusion matrix (accuracy and misclass) and evaluation matrix (precision, recall, F1-score) on the test data. It was found that all the machine learning models performed best in classifying the shale facies (87%–94%) followed by the sand (65%–79%) and carbonate facies (60%–78%) in the Penobscot field, Scotian Basin. On an overall accuracy scale, we found the multilayer perceptron method the best-performing tool, whereas the adaptive boosting method was the least-performing tool in classifying all three litho-facies in the current analysis. While other methods also performed moderately good for the classification of all three litho-facies. The predicted litho-facies using seismic attributes matched well with the log data interpreted facies on the borehole locations. It indicates that the facies estimated in inter-well regions are accurate and reliable. Furthermore, we validated the estimated results with the other seismic attributes to ascertain the accuracy and reliability of the predicted litho-facies between the borehole locations. This study recommends machine learning applications for litho-facies classification to reduce the risk associated with reservoir characterization